HEREDITARY EFFECTS
OF RADIATION
United Nations Scientific Committee on the
Effects of Atomic Radiation
UNSCEAR 2001 Report to the General Assembly,
with Scientific Annex

UNITED NATIONSNew York, 2001

NOTE

The report of the Committee without its scientific annex appears as Official Recordsof the General Assembly. Fifty-sixth Session, Supplement No. 46 (N56146).
The designation employed and the presentation of material in this publication do not
imply the expression of any opinion whatsoever on the pad of the Secretariat of the United
Nationsconcerningthe legal status of any country, temtory, city orarea, or of its authorities,
or concerning the delimitation of its frontiers or boundaries.

The country names used in this document are, In most cases, those that were in use
at the time the data were collected or the text prepared. In othercases,however, the names
have been updated, where this was posslble and appropriate, to reflect political changes.

UNITED NATIONS PUBLICATION
Sales No. E.O1.IX.2
ISBN 92-1-142244-2

ANNEX
Hereditary effects of radiation

CONTENTSPage

INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
I.

THE HUMAN GENOME . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
A. GENE NUMBER AND SIZE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
B. GENE ORGANIZATION AND FUNCTION . . . . . . . . . . . . . . . . . . . . . . . . . . 9II.

MENDELIAN DISEASES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
A. MOLECULAR NATURE OF MUTATIONS . . . . . . . . . . . . . . . . . . . . . . . . . 10
B. MUTATIONAL SPECIFICITIES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
C. GENOTYPE-PHENOTYPE RELATIONSHIPS . . . . . . . . . . . . . . . . . . . . . . . 11
1. Mutations in the same gene causing different clinical phenotypes . . . . . . . 11
2. Mutations in different genes causing similar phenotypes . . . . . . . . . . . . . . 12
3. Identical mutations with different phenotypes . . . . . . . . . . . . . . . . . . . . . . 13
4. Mutations in the same genes inherited as both dominant and recessive . . . 13
5. Mosaicism, genomic imprinting, and uniparental disomy . . . . . . . . . . . . . . 14
6. Allelic expansion (dynamic mutations) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
7. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
D. BASELINE FREQUENCIES OF MENDELIAN DISEASES . . . . . . . . . . . . . 17
1. Autosomal dominant diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2. Autosomal recessive diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3. X-linked diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
4. Revision of the total birth frequency estimates . . . . . . . . . . . . . . . . . . . . . . 18
5. Population/ethnic differences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
6. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
E. SPONTANEOUS MUTATION RATES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
1. The concept of equilibrium between mutation and selection . . . . . . . . . . . 19
2. Spontaneous mutation rates for autosomal dominant
and X-linked diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
3. Sex differences in mutation rates and paternal age effects . . . . . . . . . . . . . 20
4. Relevance of sex differences in spontaneous mutation rates
and paternal age effects in humans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
5. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

III.

MULTIFACTORIAL DISEASES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
A. CONGENITAL ABNORMALITIES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
1. Overall prevalences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2. Aetiological heterogeneity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3. Isolated congenital abnormalities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
4. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

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B. MODELS OF INHERITANCE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
1. The multifactorial threshold model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2. Other models and concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
3. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
C. COMMON MULTIFACTORIAL DISEASES . . . . . . . . . . . . . . . . . . . . . . . . 27
1. General concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2. Overall prevalences and epidemiological features . . . . . . . . . . . . . . . . . . . 28
3. Diabetes mellitus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
4. Essential hypertension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
5. Coronary heart disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
D. MECHANISMS OF MAINTENANCE OF MULTIFACTORIALTRAITS IN THE POPULATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
IV.

THE MUTATION COMPONENT FOR GENETIC DISEASES . . . . . . . . . . . . . . 38
A. BACKGROUND . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
B. DEFINITION OF MUTATION COMPONENT . . . . . . . . . . . . . . . . . . . . . . . 39
C. MUTATION COMPONENT FOR
AUTOSOMAL DOMINANT DISEASES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
1. Mutation component in the absence of sporadics . . . . . . . . . . . . . . . . . . . . 39
2. Mutation component in the presence of sporadics . . . . . . . . . . . . . . . . . . . 41
D. MUTATION COMPONENT FOR X-LINKED
AND AUTOSOMAL RECESSIVE DISEASES . . . . . . . . . . . . . . . . . . . . . . . 41
E. MUTATION COMPONENT FOR MULTIFACTORIAL DISEASES . . . . . . 41
1. Rationale for the development of a finite-locus threshold model . . . . . . . . 41
2. The model and its predictions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
F. SUMMARY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

V.

CANCER PREDISPOSITION, RADIOSENSITIVITY,
AND THE RISK OF RADIATION-INDUCED CANCERS . . . . . . . . . . . . . . . . . 45
A. FAMILIAL CANCER GENES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
1. The RB1 gene and retinoblastoma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
2. The p53 gene and Li-Fraumeni syndrome . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3. BRCA1 and BRCA2 genes and breast and ovarian cancers . . . . . . . . . . . . . 47
4. Hereditary colorectal cancers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
5. Ataxia-telangiectasia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
6. Functions of familial cancer genes
and mechanisms of cancer predisposition . . . . . . . . . . . . . . . . . . . . . . . . . . 50
7. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
B. RADIATION SENSITIVITY OF
CANCER-PREDISPOSED INDIVIDUALS . . . . . . . . . . . . . . . . . . . . . . . . . . 52
1. Human epidemiological and molecular studies . . . . . . . . . . . . . . . . . . . . . . 52
2. Mouse models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
3. The rat model for the human tuberous sclerosis-2 . . . . . . . . . . . . . . . . . . . . 54
4. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
C. COMPUTATIONAL MODELLING TO ESTIMATE RADIATION RISKIN A HETEROGENEOUS POPULATION . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
1. Numerical illustration for an irradiated population . . . . . . . . . . . . . . . . . . . 54
2. Results of computational modelling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
3. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

VI.

OTHER RELEVANT STUDIES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
A. HUMAN STUDIES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
1. Genetic disease in offspring of long-term survivorsof childhood and adolescent cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
2. Reproductive outcome in women irradiated during infancy
for skin haemangiomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
3. Possible genetic effects of radiation exposures resulting from the Chernobyl
accident or from living in the vicinity of a nuclear power plant . . . . . . . . . 57
4. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

ANNEX: HEREDITARY EFFECTS OF RADIATION

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B. ANIMAL STUDIES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
1. Radiation-induced minisatellite mutations in mouse germ cells . . . . . . . . . 60
2. Genetic effects in mice exposed in the Chernobyl accident . . . . . . . . . . . . 60
3. Cytogenetic nature of radiation-induced germ-line mutations in the mouse 61
4. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
C. MOSAIC MUTATIONS AND MUTATION CLUSTERS . . . . . . . . . . . . . . . 62
1. General comments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
2. Mosaic mutations in humans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
3. Mosaic mutations and clusters in mice and their relevancefor risk estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
4. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
VII. CONCEPTS, DATA AND ANALYSES USED FOR
THE ESTIMATION OF GENETIC RISKS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
A. FREQUENCIES OF GENETIC DISEASES IN HUMANS . . . . . . . . . . . . . . 65
B. THE DOUBLING DOSE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
1. The average rate of spontaneous mutations in humans . . . . . . . . . . . . . . . . 66
2. The average rate of induced mutations in mice . . . . . . . . . . . . . . . . . . . . . . 67
3. The doubling-dose estimate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
4. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
C. MUTATION COMPONENT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
D. THE CONCEPT OF POTENTIAL RECOVERABILITY
CORRECTION FACTOR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
1. Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
2. Differences between spontaneous and radiation-induced mutations . . . . . . 69
3. Radiation-induced mutations and their recoverability
in radiation mutagenesis studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
4. Criteria for recoverability and the potential recoverability correction
factor (PRCF) concept . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
5. Potential recoverability correction factor for autosomal dominant
and X-linked diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
6. Potential recoverability correction factor for autosomal recessive diseases 73
7. Potential recoverability correction factor for multifactorial diseases . . . . . 73
8. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
E. MULTISYSTEM DEVELOPMENTAL ABNORMALITIES AS
MANIFESTATIONS OF RADIATION-INDUCEDGENETIC DAMAGE IN HUMANS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
1. Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
2. Insights from studies of human microdeletion syndromes . . . . . . . . . . . . . 75
3. Other naturally occurring chromosomal structural changes
and associated disease phenotypes in humans . . . . . . . . . . . . . . . . . . . . . . . 75
4. Empirical mouse data on the phenotypic effects of radiation-induced
genetic damage other than mutations in known genes . . . . . . . . . . . . . . . . . 75
5. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
VIII. RISK ESTIMATES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
A. INPUT PARAMETER VALUES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
1. Baseline frequencies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
2. Doubling dose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
3. Mutation component . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
4. Potential recoverability correction factor . . . . . . . . . . . . . . . . . . . . . . . . . . 78
B. RISK ESTIMATES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
1. Radiation exposure in every generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
2. Radiation exposure in one generation only . . . . . . . . . . . . . . . . . . . . . . . . . 78
3. Summary of risk estimates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
4. Strengths and limitations of the risk estimates . . . . . . . . . . . . . . . . . . . . . . 79
5. Genetic risk at the new equilibrium between mutation and selection
for a population that sustains radiation exposure in every generation . . . . . 81
6. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82

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C. COMPARISON OF THE PRESENT RISK ESTIMATES
WITH THOSE OF OTHER APPROACHES . . . . . . . . . . . . . . . . . . . . . . . . . . 82
D. GENETIC STUDIES ON SURVIVORS OF THE ATOMIC BOMBINGSIN JAPAN IN THE LIGHT OF THE PRESENT RISK ESTIMATES . . . . . . 83
SUMMARY AND CONCLUSIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84

Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139

INTRODUCTION

1.
Estimation of the genetic risks of exposure to ionizing
radiation has been a continuing endeavour of the Committee.
In the previous assessment in the UNSCEAR 1993 Report[U4], the Committee considered advances in human andradiation genetics relevant to estimating the risks ofhereditary effects of radiation exposures. Additionally, it
directed attention to a subset of human Mendelian diseases
for which cancer of one type or another is the principal
phenotype and reviewed the sensitivity of individuals withsuch genetic diseases to radiation-induced cancers. The
material contained in Annex G, “Hereditary effects ofradiation”, and Annex E, “Mechanisms of radiation
oncogenesis”, of the UNSCEAR 1993 Report broadly
defines the scope of this Annex and its starting point.
2. Knowledge of the molecular aspects of naturally
occurring human genetic diseases and the mechanisms of
their origin has been growing rapidly, especially since thebeginning of the Human Genome Project, in 1990. Much
progress has been made in mapping and cloning the genesthat when mutated result in Mendelian diseases. Promising
methods are now being developed for the “genetic
dissection” of multifactorial diseases as well [L1, W1].
These advances are relevant to radiation risk estimation for
at least two reasons:(a)the yardstick for expressing genetic risks is “inducible
genetic disease”, the implicit assumption being that suchdiseases will be similar to those that occur naturally as aresult of spontaneous germ-cell mutations; and(b)insights gained into the nature and mechanisms of theorigin of naturally occurring genetic diseases and into
genotype-phenotype relationships, used together withdata from mammalian radiation mutagenesis studies,constitute a sounder basis for inferring which of these
diseases are potentially inducible by radiation.

3.
These advances are already allowing the conceptual
framework for risk estimation to be restructured and thecritical questions to be reformulated. In fact, the new
information suggests that radiation is less likely to haveadverse genetic effects than had hitherto been assumed andthat it is possible to reconcile the empirical results fromhuman studies of genetic risks of radiation with predictionsof such risks from mouse data. The aims of this Annex are,therefore, to capture the essence of these advances and to
examine how they might allow estimates of genetic risks ofradiation exposures to be revised. In presenting this review,the general framework of naturally occurring genetic
diseases and their classification into Mendelian (those due
to mutations in single genes), chromosomal (those due tochromosomal abnormalities), and multifactorial (those due
to complex interactions between genetic and environmental
factors) is retained, as was used in the earlier assessmentsof the Committee. This is done primarily for convenience,
although developments in human molecular biology aremaking the distinction between these different classes lesssharp, and radiation-inducible adverse effects may notalways be classifiable into these three subgroups.

ANNEX: HEREDITARY EFFECTS OF RADIATION

9I. THE HUMAN GENOME
A. GENE NUMBER AND SIZE

B. GENE ORGANIZATION AND FUNCTION

4.
The total length of the human haploid genome isabout 3 million kilobases (3 106 kb, or 3,000 Mb),
distributed between 22 types of autosomes and two types ofsex chromosome (the X and Y) that can easily be
differentiated by chromosome banding techniques. The
amount of DNA varies from chromosome to chromosome.
The longest, chromosome 1, contains about 263 Mb and theshortest, chromosome 21, contains 50 Mb. In a 550-band
metaphase chromosome preparation, an average bandcorresponds to about 6 Mb of DNA [M55]. The genes are
not distributed uniformly along the length of DNA; theGiemsa light-staining bands in metaphase chromosomes
contain more genes than do dark-staining bands [S1].

7.
As with other eukaryotic genes, most human genes are
made up of coding (exon) and non-coding intervening(intron) sequences. Each individual gene differs not onlywith respect to its DNA sequence but also with respect toits structure. A few human genes, e.g. histone genes,
interferon genes, and mitochondrial genes, are devoid of
introns, whereas some possess a considerable number of
introns, with their lengths varying from a few base pairs toseveral kilobase. Less than 5% of the genome consists ofprotein-coding sequences (exons of genes), the remainder
being made up of non-coding regions (such as the various
types of repeat sequences present in introns and between
genes), whose functions remain to be elucidated.

5.
The most often quoted range of gene numbers inhumans is 50,000 to 100,000 [U16]. Antequera and Bird
[A1] used the number and distribution of CpG islands ingenomic DNA as a measure for the number of genes. The
CpG islands are clusters of cytosine-(C) and guanine-(G)rich sequences present at the 5' ends (i.e. left ends) of allhousekeeping genes and of a large proportion of genes witha tissue-restricted pattern of expression. Thus, the presenceof a CpG island denotes the 5' end of the associated gene[C1, L2]. Since the number of CpG islands in the humangenome is approximately 45,000, and 56% of the genes so
far sequenced contain CpG-islands, the estimate of total
gene number is about 80,000. Extrapolation fromsequencing of large chromosomal regions suggests that
there are 60,000 to 70,000 genes [F1]. It is worth notingthat in any given tissue, only a relatively small proportionof the genes are expressed. Current estimates, based on thedraft human genome sequences generated by Celera
Genomics [C81] and the Human Genome Project [I15] andpublished in 2001 suggest that the number of genes may beof the order of about 26,000 to 40,000.

8.
The first two bases of the 5' end of each intron are
guanine (G) and thymine (T), and the last two bases (at the
3' end of intron) are invariably adenine (A) and guanine(G). In the sense strand, at the 5' end of the gene is the ATG
codon, which is the transcriptional initiation site. Upstream
from this are a number of non-coding sequences, referred
to as promoters, and further upstream are a number of cisacting regulatory elements of defined sequence (TATAAA
and CCAAAT motifs, which play a role in constitutive
gene expression, and enhancers, which respond toparticular proteins in a tissue-specific manner by increasingtranscription). At the 3' end of the gene, following thetermination codon (e.g. TAA, TAG, and TGA), is apoly(A) tail.

6.
There is a wide range of size differences, from about
2 kb to 2,000 kb, between human genes. The size distributionof the 253 genes for which information is catalogued in
McKusick's compendium [M1] is as follows: 59 (23%) areless than 10 kb, 90 (36%) are between 10 and 25 kb, 51(20%) are between 25 and 50 kb, 33 (13%) are between 50
and 100 kb, 17 (7%) are between 100 and 500 kb, and 3 (1%)
are more than 500 kb. Table 1 presents some examples.

9.
The process by which genetic information in the DNA
is transmitted to mRNA is called transcription. During thisprocess, the entire unit of both introns and exons istranscribed into precursor mRNA. The region of precursor
RNA transcribed from the introns is then excised andremoved and does not form mRNA and therefore does not
specify the primary structure of the gene product. The
accuracy of the excision is determined, at least in part, by
the virtually invariant GT and AG dinucleotides present at
the 5' and 3' exon-intron junctions, respectively. The
precursor RNA from the exons is spliced together to form
the definitive mRNA, which specifies the primary structureof the gene product. The definitive mRNA is transported tothe cytoplasm, where protein synthesis occurs (translation).
These aspects are discussed in detail by Lewin [L2].

10

UNSCEAR 2001 REPORT

II. MENDELIAN DISEASES
10. A large number of phenotypes of Mendelian genetic
disease have been recognized. McKusick's 1994 compendium[M1] has 6,678 entries: autosomal dominant, 4,458;
autosomal recessive, 1,730; X-linked, 412; Y-linked, 19; andmitochondrial, 59. As of January 2000, the on-line version of
the above compendium [M2] had 11,062 entries. Well over
6,980 genes have been assigned to specific chromosomes andmost of them to specific sites on those chromosomes. For
many of these genes, extensive information is available,
including sequence organization, the nature and function of
the gene product, and the diseases associated with mutationsin them; for others, the information on the gene is indirect
and limited to linkage of a Mendelizing phenotype to theparticular chromosomal site [M2, S2].
11. Although well over 1,100 clinical diseases have been
mapped to specific chromosomal regions (about 1,000 loci),
data on mutational spectra (i.e. nature, type, and distribution of
mutations along the gene) are available for fewer than one halfof the above. These data are more extensive for some of thegenes, including the cystic fibrosis gene (CFTR) with morethan 500 independent mutations; the β-globin gene (HBB) withmore than 400 mutations; and the factor IX gene (haemophilia B), α-globin genes (HBA), and the LDLR gene (familial
hypercholesterolemia), each with more than 100 allelicvariants. With many other genes, these numbers are muchsmaller. Some of the reasons for these differences are size andfunction of the gene; clinical relevance of mutations and theamount of effort expended; ease of detection; availability for
analysis; and the specificity of the type of mutational event, i.e.
whether it is restricted to specific gene regions [S2].

A. MOLECULAR NATURE OF MUTATIONS
12. Point mutations and deletions are without doubt themost frequently encountered gene lesions that underlie
Mendelian diseases. Other genetic changes comprise a mixed
assortment of insertions, duplications, inversions, andcomplex rearrangements. Point mutations include transitions(substitution of one purine for another purine [e.g. A to G orvice versa] or of one pyrimidine for another [e.g. C to T orvice versa]) and transversions (replacement of a purine by apyrimidine [e.g. A to T or vice versa]). These may result in
the replacement of one amino acid by another (missense
mutations, which do not affect the remainder of the protein)or the substitution of a codon for an amino acid to a stop or
terminating codon (TGA, TAA, or TAG), which leads topremature termination of translation (nonsense mutations).
Frameshift mutations occur when one or more nucleotides areeither inserted or deleted; since the genetic code is read in
non-overlapping triplets, if the number of bases inserted ordeleted is not a multiple of three base pairs, such insertions ordeletions change the reading frame, and the entire amino acidsequence of the protein is altered beyond the site of mutation,
causing loss of function of the protein.

13. Mutations have been found to occur not only in thecoding sequences but also in regulatory regions, promoter
regions, splice junctions, within introns, and in polyadenylation sites. They may interfere with any stage in the pathway
of expression, from gene to protein product. It is noteworthy
that splicing defects are not uncommon; point mutations
causing a defect in mRNA splicing appear to represent some
15% of all point mutations in Mendelian diseases [C2]. Someof the consequences of splice site mutations are a reductionin the amount of mRNA generated, production of an aberrant
mRNA, and non-recognition by the cellular machinery of an
exon or exons following the lesion. The result of the last of
the above possibilities is that the non-recognized exons are
excluded from the mature RNA transcript, a process called“exon skipping”.
14. So far, about 300 Mendelian diseases have been
analysed [S3, S4]. The recorded molecular changes can beclassified into three broad groups: (a) point mutations; (b)length mutations, including small and large intragenic or
multigenic DNA deletions, insertions, rearrangements, andduplications; some of the latter are fundamentally the same as
microscopically detectable chromosomal aberrations (i.e.
deletions, insertions, rearrangements, and duplications); and(c) those that arise as a result of non-traditional mechanisms
such as expansion of trinucleotide repeat sequences in thecoding or untranslated regions of genes.
15. Based on the types of the molecular change so far
delineated, the Mendelian diseases can be grouped into four
categories, namely, those that are predominantly due to (a)point mutations, (b) both point mutations and length
mutations, (c) large intragenic length mutations andmicrodeletions (contiguous gene deletion syndromes), and(d) those that arise as a result of non-traditional mechanisms.
The results of analysing 309 Mendelian diseases belonging
to the first three categories above are summarized in Table 2.
Those of the fourth category are discussed in a later Section.
16. Overall, 200 of 309 diseases (65%) are due to point
mutations, 69 (22%) are due to both point mutations andlength mutations, and 40 (13%) are associated with length
mutations and microdeletion syndromes. If only the 164
autosomal dominant and X-linked diseases are considered, 89(54%) are due to point mutations, 42 (26%) are due to both
point mutations and length mutations, and 33 (20%) are due
to length mutations and microdeletion syndromes. It is
important to bear in mind that both the numbers and therelative proportions will change when more data are analysed.

B. MUTATIONAL SPECIFICITIES
17. Both the earlier [S5, S6] and the more recent [S3, S4]analyses of the distribution of point mutations along thedifferent genes show that in a small proportion of these, themutational sites appear to be distributed nearly uniformly

ANNEX: HEREDITARY EFFECTS OF RADIATION

throughout the gene; this is particularly true of many
autosomal recessive and X-linked diseases and some autosomal dominant diseases. In contrast, with a large proportion ofgenes that underlie most autosomal dominant diseases, thedistribution of mutational sites is non-random, i.e. there areapparent preferences for one or a few exons or parts of thegene. Examples of both nearly uniform as well as non-random
distribution of mutational sites in genes are given in Table 3.
18. While part of the non-random distribution mentioned
above may stem from differences in ascertainment and theextent of knowledge of the number of sites at which
mutations are recoverable, the current view is that this nonrandom distribution is a reflection of the sequenceorganization of the gene and its genomic context. For
transition-type point mutations, data consistent with this vieware available (reviewed in [C2]). In many genes there are
stretches of methylated CpG sites, and it is in these that asubstantial proportion of C to T and the corresponding G to
A transitions in the complementary strand occur. This isbecause of the high propensity of 5-methylcytosine toundergo spontaneous deamination to thymine. Of the 880
base changes reported to cause human Mendelian diseases(as of 1992), 38% were found to involve CpG dinucleotide
and 86.5% of these (32.8% of the total) were either C to T or
G to A transitions [C2]. Since not all transitions occur at CpG
sequences, there must be other explanations for their origin.
19. For transversion-type point mutations, no such
hotspots are known. Data from in vitro and prokaryotic
systems [K1, K2, L3] show that transversions occur as aresult of DNA polymerase infidelity, the bypass of apurinic
sites, and chemical modification. The important point is thatfor both transitions and transversions, the processes
involved are known to be DNA-sequence-dependent, so it
is hardly surprising that the distribution of point mutations
is non-random. Further, it should be borne in mind that thenear-uniform distribution of mutational sites recorded insome of the genes does not exclude specificities at themolecular level, e.g. the presence of CG dinucleotide
repeats in genes and the occurrence of C to T and G to A
transitions; it merely means that mutations at any one ofthese sites results in a scorable phenotype.
20. Analyses of the distribution of break points in lengthmutation-associated diseases show the same phenomenonof non-randomness and seem to be dependent on thesequence of the gene and its context. All of the 219 short(20 bp or less) deletions in 63 different genes analysed by
Cooper and Krawczak [C2] have direct repeats of 2 bp ormore flanking or overlapping them. The mechanism
proposed to explain the origin of these small deletions
involves misalignment and slippage during DNA
replication. For large deletions, sequence homologies andrepetitive sequences such as Alu located within andbetween genes appear to play an important role. Examplesof Mendelian disease that are believed to arise throughthese mechanisms were discussed by Cooper and Krawczak[C2] and Sankaranarayanan [S5, S6] and in the UNSCEAR
1993 Report [U4].

11

C. GENOTYPE-PHENOTYPE
RELATIONSHIPS
21. The concept that certain genetic diseases represent
generalized single-gene-determined defects ("one mutation,
one disease") is a simple one, especially when viewed fromthe perspective of the 1990s. It was heuristically powerful,
because it predicted the practicability of identifying aunitary "cause" for each of these diseases; this prediction
has been amply fulfilled, as evidenced by advances in theknowledge of the biochemical (and now molecular) basis of
Mendelian diseases during the past few decades, notwithstanding the observations that mutant genes do not always
express the mutant phenotype in all individuals carrying
them (variable penetrance) or affect them to the same
degree (variable expressivity).
22. At the same time, these advances underscore the factthat even in simple Mendelian diseases, when looked atclosely, the relationship between the genotype and phenotype (or clinical manifestation) is not always invariant;there are now many examples of (a) mutations in the samegene causing different phenotypes, and (b) mutations indifferent genes resulting in the same or nearly the same
phenotypes. In current terminology, the former situation isreferred to as allelic heterogeneity and the latter, as locus- or
non-allelic heterogeneity (or genetic heterogeneity). Furthermore, instances of identical mutations (thus, no allelicheterogeneity) causing large differences in clinical severity
have also been reported.
23. In addition to the above, as discussed in the
UNSCEAR 1993 Report [U4], phenomena such as mosaicism, genomic imprinting, and allelic expansion also introduce complexities into genotype-phenotype relationships.
These complexities, however, do not detract from the factthat the genetic factors that influence these relationships ina given disease can often be studied individually and evenquantified, thereby increasing the accuracy of prognoses(reviewed in [H1, W3]).
1. Mutations in the same gene causing
different clinical phenotypes
24. In their survey of allelic variants in 767 genes,
Schinzel et al. [S7] found that in 658 genes the variants
were associated with one clinical disease, in 71 with two, in
30 with three, in 5 with four, in 1 with five, in 1 with six,and in 1 with seven diseases. Thus, out of 767 genes, 109
were found to be associated with more than one clinicaldisease. Some examples are given in Table 4, and a few ofthem are discussed below.
(a) Mutations in the PMP22 gene
25. Of peripheral neuropathies, Charcot-Marie-Tooth
disease type 1A (CMT1A) is the most frequent [B1, P1,
S8]. In nearly 70% of the patients, a stable duplication of
1.5 Mb has been found in the CMT1A region of

12

UNSCEAR 2001 REPORT

chromosome 17p11.2. Within the CMT1A region, a genecoding for a peripheral myelin protein (PMP22) has been
localized. However, in a number of cases without the
duplication, point mutations have been identified in the
PMP22 gene, and most are dominant, although somerecessive mutations have also been found [R1]. Clinically,
the disease phenotype has been observed to vary, evenamong members of the same family, suggesting that
additional factors influence the course of the disease [B1,P1]. Mutations in the PMP22 gene have also been found insome patients with the hypertrophic demyelinating
peripheral neuropathy known as Dejerine-Sottas disease.
26. In cases carrying the duplication mentioned above,
PMP22 is overexpressed, so a gene dosage effect isbelieved to be the cause of the disease. A deletion that is
duplicated in the CMT1A region results in a conditionreferred to as hereditary neuropathy with liability forpressure palsies (HNPP) [B1, C3, P1, S8].
(b) Mutations in the FGFR3 gene
27. Mutations of the fibroblast growth factor receptor(FGFR) genes cause diverse forms of skeletal disorders;these are discussed in the next Section. It will only be noted
here that different point mutations in one of these genes,
FGFR3 on chromosome 4p16.3, have been found inachondroplasia (ACH), in hypochondroplasia (HCH), andin thanatophoric dysplasia (TD). Intriguingly, although
individuals with a deletion of the short arm of chromosome
4 have one copy of FGFR3 deleted (Wolf-Hirschhorn
syndrome), they do not have any of the characteristics of
ACH, HCH, or TD (no skeletal dysplasias).

exocrine pancreatic and pulmonary functions. Severe
mutations comprise all molecular types, in particular thosethat presumably block or impair synthesis of the CFTR
protein, such as nonsense, frameshift, and splice-site
mutations; most of these are located in the NBF domains.
In contrast, most mutations that are mild are in thetransmembrane domains and are predominantly missense,
although some splice-site mutations have also been found.
31. In most CF patients, there is a good correlation between
the different CFTR mutations and pancreatic insufficiency,
but the correlations are not absolute. Other symptoms such as
meconium ileus (a type of intestinal obstruction), which
occur in some 10% of patients with pancreatic insufficiency,
do not seem to be associated with specific genotypes. The
severity of the pulmonary disease also varies independentlyof the respective mutations; thus, unrelated patients with thesame genotype (e.g. homozygotes for the ∆F508 deletion)
show a striking variation in lung function. Similar comments
apply to sweat chloride concentrations. These and other
differences point to the influence of other (genetic, environmental) factors not yet fully identified.
32. In about 97% of CF male patients, congenital bilateralabsence of vas deferens (CBAVD), an obstructive azoospermia, has been observed. ∆F108 and Arg117His mutations are the most common mutations, and ∆F208/Arg117His
is the most common genotype in isolated CBAVD; almost allother genetic compounds include one or the other.

2. Mutations in different genes causing
similar phenotypes(c) Mutations in the CFTR gene
28. In cystic fibrosis (CF), an autosomal recessive
disease, the primary physiological defect is believed to bea reduced conductance of chloride ions in the epithelial
tissues affected by the disease (hence the designation cystic
fibrosis transmembrane conductance regulator, or CFTRgene). As a consequence, fluid secretion and salt absorption
are impaired, and patients show, among other symptoms,
chronic sinopulmonary disease, pancreatic insufficiency,
and elevated sweat chloride levels.
29. The CFTR gene is distributed over 230 kb of genomic
DNA on chromosome 7 and consists of 27 exons. The
predicted protein is 1,480 amino acids long and comprises
two transmembrane domains (containing 12 membranespanning regions), two ATP-binding domains or
nucleotide-binding folds (NBF), and a highly polar domain(R) with many possible phosphorylation sites, believed toplay a regulatory role [R3]. Over 500 mutations in this gene
have been identified, the most common being ∆F508 in
exon 10, a three-nucleotide deletion leading to the loss ofphenylalanine at position 508 [K3, P3, T1].
30. In general terms, ∆F508 homozygotes seem to havea more severe disease than genetic compounds for the

33. Similar phenotypes can arise when, for instance, morethan one gene is required for a common biochemical
pathway or cellular structure. Further, mutations inmembers of a given gene family can give rise to a set of
related pathologies. In their 1994 compilation, Schinzel etal. [S2] found that 26 diseases were associated with
mutations in two different genes, 11 with mutations inthree, 4 with mutations in four, 4 with mutations in five, 1
with mutations in six, 1 with mutations in seven, and 1 with
mutations in ten different genes. Table 5 presents someexamples, a few of which are discussed below.
(a) Osteogenesis imperfecta and Ehlers-Danlos
syndrome type VII
34. Mutations in one of two structural genes for type I
procollagen, namely COL1A1 coding for proα1(I) and
COL1A2 coding for proα2(I), are responsible for more than
90% of the cases of osteogenesis imperfecta (four clinicaltypes) and one type of Ehlers-Danlos syndrome, type VII(EDS-VII) (reviewed in [B2, D2, S10]). The main clinicalfeature that defines osteogenesis imperfecta I is bone
fragility, whereas that of EDS-VII is severe multiple-joint
hypermobility and ligamentous tears; congenital bilateraldislocation of the hip is the rule.

ANNEX: HEREDITARY EFFECTS OF RADIATION(b) Skeletal disorders associated with
mutations in the FGFR genes
35. To date, seven skeletal disorder syndromes, namely,
Apert syndrome, Crouzon syndrome, Jackson-Weiss
syndrome, Pfeiffer syndrome, achondroplasia, thanatophoric dwarfism, and hypochondroplasia, have been foundto be caused by mutations in three fibroblast growth factor
receptor (FGFR) genes [B3, J1, M5, R4, R5, S11, S12, T2,
W4]. All these syndromes show an autosomal dominantmode of transmission and share a number of craniofacialabnormalities that arise as a result of premature fusion of
the flat bones of the skull, leading to an abnormal head
shape. They are clinically distinguished largely on the basisof hand and foot abnormalities. There are at least two othercraniosynostosis syndrome mutations that have been
identified in genes on chromosome 7 (GLI3) [V1] andchromosome 5 (MSX2 gene; the Boston type) [J2].
36. Each of the four FGFR genes described in humans
encode receptor proteins that have an extracellular region
with three immunoglobulin (Ig)-like domains, a transmembrane segment, and a split cytoplasmic tyrosine-kinasedomain; they have amino acid identities of 55%!72% [J3]but differ in their ligand affinity and tissue distribution. The
Ig-like II domain, the interloop region between Ig-likedomains II and III, and the N-terminus of the Ig-III domain
are implicated in ligand binding [G1, J3]. In addition, theC-terminal sequences of the Ig-like III domain appear to beimportant for ligand specificity.
37. Mutations in FGFR genes and the resultant
phenotypes are shown in Table 6. Achondroplasia, the mostcommon form of genetic dwarfism, has been shown to be
due to mutations in the FGFR3 gene: a G to A transition incodon 380 (glycine to arginine substitution) or G to C
transversion in the same codon (also causing glycine toarginine substitution) in the transmembrane domain [B3,R4, S11]. Mutations in the tyrosine kinase domain of thesame gene result in the phenotypically different and more
severe thanatophoric dwarfism [T2] and also in
hypochondroplasia [B4]. Individuals with Pfeiffer
syndrome have mutations in either FGFR1 (ligand-binding
domain) or, more commonly, in the FGFR2 genes (Ig-III
domain). FGFR2 gene mutations in the Ig-III domain are
also responsible for Jackson-Weiss syndrome and Crouzon
syndrome.
3. Identical mutations with different
phenotypes(a) β-S mutation in sickle-cell anaemia
38. Sickle-cell anaemia is a classic example of an autosomal recessive disease in which all patients are homozygous for the same β-globin (HBB) gene lesion (β-Smutation; GAG to GTG, resulting in the substitution ofvaline for glutamic acid at codon 6 of the β-globin gene).
The disease shows wide variation in clinical severity(expressivity) in different patients, ranging from early13

childhood mortality to a virtually unrecognized condition.
There is evidence that the clinical severity of this diseasecan be ameliorated by the effects of genetic variation either
within the HBB gene regulatory regions, in far upstream
regions controlling the expression of the linked G-γ(HBG2) and A-γ (HBG1) globin genes, or at the unlinked
α-globin gene (or a combination of these) (see [C2, L1,
W3]).
(b) Mutations in the CFTR gene
39. As discussed earlier, studies of individual mutations
have shown that the CFTR cystic fibrosis phenotype isclosely associated with pancreatic status and may influencechloride levels in sweat but is unrelated to the severity oflung disease. One patient homozygous for the ∆F508 wasnoted to have a sweat chloride level significantly lower thanusually observed in these patients. DNA sequencing
revealed a second alteration (resulting in an arginine 553 toglutamine change) in the first nucleotide binding folddomain in the CFTR gene. The authors suggested that thischange might modify the effect of ∆F508 mutation [D3].
40. A second example, also in the CFTR gene, relates tothe effect of a neutral amino acid polymorphism(phenylalanine 508 to cysteine) that was associated with thedisease when combined with a second amino acidsubstitution (serine 1251 to asparagine) in the second
nucleotide binding fold [K4]. A further example wasprovided by Kieswetter et al. [K5]; they showed that thephenotypic effects of one CFTR missense mutation(arginine 117 to histidine) varied depending on the lengthof the polypyrimidine tract in the splice acceptor site in
intron 8.

4. Mutations in the same genes inherited
as both dominant and recessive
41. There are now several examples of Mendeliandiseases that are inherited as dominant in some families andrecessive in others, although the same gene is mutated (seeTable 14 in [M1]). Differences in the precise type andlocation of the mutations seem to be responsible for thesedifferences in mode of inheritance. Two examples are
discussed below.
42. Usually, β-thalassemias (haemoglobinopathies due todefects in β-globin chain synthesis) manifest a recessive
pattern of inheritance and can arise as a result of a variety
of molecular changes in the HBB gene (promoter sequence
mutations, premature stop codons and frameshifts, splice
junction mutations, and partial deletions of the gene).
Heterozygotes are usually symptomless. However, anunusual dominant form of β-thalassemia also occurs and isoften caused by heterozygous mutations in exon 3 of the
HBB gene [K6]. A total of 16 different mutations (mostly
but not exclusively in exon 3), causing the dominant formof the disease, were collated by Thien [T5], who classified
them into three distinct groups:

14

(a)
(b)
(c)

UNSCEAR 2001 REPORT

highly unstable β-globin chain variants caused by eitherbase substitution or the deletion of intact codons;
truncated β-globin chain variants caused by prematuretermination of translation; andelongated β-globin chain variants with an alteredcarboxyl terminal resulting from a frameshift mutation.

43. A comparison of these three variants has suggested
mechanisms to explain why exon 3 mutations are some-times
associated with a particularly severe phenotype [C2, T5].
Nonsense mutations occurring in the 5' half of the HBB gene(exons 1 and 2) do not give rise to a detectable β-globin
product (owing to mRNA and/or protein instability), resulting
in a typical heterozygous β-thalassemia phenotype due to asimple reduction in β-globin synthesis. Most unstable
β-globin variants result in unbalanced globin synthesis; lessunstable ones could still transiently form tetramers with
α-chains, resulting in severe anaemia. β-globin chainstruncated by exon 3 nonsense mutations may often be
synthesized, but such chains are unlikely to be capable offorming viable tetramers, although they might still retain theability to bind haem. Elongated β-chain variants, on the other
hand, would possess an abnormal carboxy terminal end,
causing instability and the subsequent aggregation andprecipitation of an abnormal globin molecule. Thus,
production of an abnormal β-chain may often be clinicallymore severe than the abolition of β-chain synthesis, asituation similar to collagen gene mutations, discussed earlier.
44. Christiano et al. [C5] found that a patient homozygous
for a T to A transversion (resulting in a methionine to lysinechange) in the 49-bp exon (in a highly conserved region of
the C-terminus of type VII collagen) manifested a severe
form of epidermolysis bullosa dystropica, a skin blistering
disease; both parents of the patient were heterozygous forthe same mutation but unaffected. However, a mutation in
the COL7A1 gene (G to A transition at the glycine residue
2040 in exon 73; glycine to serine), showed dominant
inheritance [C6] (see McKusick [M1] for other examples ofthese types of effect).
5. Mosaicism, genomic imprinting,and uniparental disomy
45. Discussed in detail in the UNSCEAR 1993 Report[U4] were mosaicism, genomic imprinting, uniparental
disomy, and allelic expansion (dynamic mutations), which
are some other mechanisms/ phenomena that affectgenotype-phenotype relationships. The following
paragraphs focus on uniparental disomy, for which somenew data have been published and mention only briefly thebasic concepts of mosaicism and genomic imprinting.
Allelic expansion, although it could be considered in thissubsection, is deferred to the next in view of the extensive
amount of information.
46. Mosaicism refers to the presence of normal cells andthose carrying a mutation in the same individual; this canhappen in somatic cells or in the germ-line or in both. If

mosaicism for a dominant disease-causing mutation ispresent in the germ-line of an individual, the individual may
not manifest the phenotype of the mutation but risks
transmitting the mutation to his or her offspring. Germ-line
mosaicism has been observed in a number of Mendeliandiseases, such as Duchenne muscular dystrophy, Apert
syndrome, and osteogenesis imperfecta type II [M1].
47. Genomic imprinting refers to a phenomenon in whichan allele at a given locus is inactivated, depending onwhether it is inherited from the father or mother (parent-oforigin effects); this implies a differential expression ofgenetic information depending on whether it is inheritedfrom the father or the mother (see [B7, C2, H4, M1] forrecent reviews). The best-characterized examples ofgenomic imprinting are Prader-Willi syndrome andAngelman syndrome. Both were mapped to the same
chromosomal region, 15q11!q13, by the observation of denovo deletions in sporadic cases. The clinical features ofthe syndromes are quite distinct. Prader-Willi syndrome
includes developmental delay and hypotonia in infancy but
is particularly characterized by hyperphagia (bulimia),leading to gross obesity later in life. Angelman syndrome ischaracterized by ataxia, seizures, and severe mental
retardation, with a particularly pronounced lack of speech.
48. Molecular studies using polymorphic markers fromthe 15q11–q13 region confirmed the similarity of the twodeletions but revealed that the deletions in Prader-Willi
syndrome arose on the chromosome inherited from thefather, whereas deletions in Angelman syndrome arose on
the chromosome inherited from the mother. This suggeststhat this genomic region is not functionally equivalent inboth sexes and that the expression of genes in this region
therefore depends on the parental origin, i.e. they are
imprinted. The Angelman syndrome has been subsequently
found to be a single-gene disorder, resulting from mutationsin the UBE3A gene [K16, M22].
49. Uniparental disomy refers to a phenomenon in which
an individual with a normal chromosome complement has
both members of a chromosome pair (or chromosomal
segments) inherited from a single parent (in contrast to thenormal situation in which one member of each pair ofchromosomes is paternal and the other maternal). The term
“heterodisomy” is used when both chromosomes from one
parent are present, and “homoisodisomy” is used when two
copies of the same parental chromosome (arising throughduplication) are present.
50. Uniparental disomy can create a situation in which achild with a well-known recessive disease is found to have
only one heterozygous parent. When non-paternity or new
mutations in the germ cells of the other parent can be
excluded, it is possible to demonstrate, using DNA
markers, that both the mutant chromosomes are derived
from the heterozygous parent. This was first demonstrated
in the case of cystic fibrosis, in which homozygosity for amutation in the CFTR gene of the patient was found to havearisen as a result of uniparental disomy [S14, V3].

ANNEX: HEREDITARY EFFECTS OF RADIATION

51. Uniparental disomy can result in a clinical disease not
only by rendering the individual homozygous for arecessive mutation inherited from only one parent but also
by uncovering the effects of gene imprinting [H4, R6]. In
fact, the well-known examples of uniparental disomy,
Prader Willi syndrome, Angelman syndrome, and Beckwith-Wiedemann syndrome (an overgrowth disorder due topaternal disomy for chromosome 11), have come to lightbecause they involve regions of the human genome
containing imprinted genes [M1]. Some further instances of
uniparental disomy in humans, regardless of whether
associated with an abnormal phenotype or not, aresummarized in Table 7. The subject has been recently
reviewed [M15].
6. Allelic expansion (dynamic mutations)
52. It has long been known that the human genome
contains many nucleotide sequences that occur repeatedly.
These repeat sequences vary in complexity from complete
genes (such as the ribosomal RNA genes; >400 genes)
down to simple sequences of one or a few base pairs.
Among the repeats of simple sequences are the simple
tandem repeats, which involve mono-, di-, tri-, tetra-, andpentanucleotide repeating units. Many simple tandem
repeats are polymorphic (i.e. variable from individual toindividual) in copy number in human populations. They
therefore provide a rich source of linkage markers that havebeen (and are being) widely exploited in studies of thehuman genome. However, it was with the discovery, in
1991, of an expanded CGG repeat as the mutation causingfragile-X mental retardation [O1, Y1] that trinucleotide
repeat expansions were recognized as an important andnovel mutational mechanism in human genetic disease (see[B8, R7, S15] for recent reviews).
53. Thus far, at least 14 Mendelian diseases have beenshown to be associated with trinucleotide repeat expansions.
These include fragile-X syndromes A and B, spinal andbulbar muscular atrophy, Huntington disease, MachadoJoseph disease, Dentatorubral-pallidoluysian atrophy, spinocerebellar ataxia types 1, 2, 6, and 7, myotonic dystrophy,
Friedreich ataxia, oculopharyngeal muscular dystrophy, andsynpolydactyly. The types of repeat and their location are
given in Table 8. As noted in the footnote to this Table, aform of progressive myoclonal epilepsy has been found to be
due to the expansion of a dodecamer repeat (i.e. 12
nucleotide repeat expansion) located upstream of the 5'transcription start site (untranslated region) of the CSTB
(cystatin B) gene [L12, L20]. Of these, the fragile-X mental
retardation syndrome, Huntington disease, and myotonic
dystrophy are considered below because of their relatively
moderate to high prevalences (and, accordingly, greater
societal relevance).

15

females (range: 0.2!0.6 per 1,000) [W5]. The CGG repeats
are located in the 5' untranslated region of exon 1 of thegene [K7, V4, Y2]. The risk of transmitting the diseasephenotype is correlated with the size of the CGG repeat.
The number of these repeats in the normal X chromosome
is between 6 and 53, with 29 repeats the most frequent.
Within this normal range, the alleles are stably inherited. Ata length of more than approximately 50 copies, the allele
sizes can increase, in a number of steps, through a clinicallyinnocuous premutation phase with a repeat size of up to
about 230 copies. The premutation is unstable, and the copy
number increases to the full mutation range (>230 up to
1,000 copies). In a full mutation, the CpG residues in therepeat itself and in an adjacent CpG island (which is part ofthe promoter region of FRAXA gene) are methylated [O1],and this shuts down transcription of the gene [P6],generating the disease phenotype.
55. The chance of such large expansions depends on copy
number in the premutation phase: if the repeat number issmall (50!70 copies), the risk is low; if the repeat number
is high (>90), the risk is almost 100%, i.e. the carriers ofhigh-copy-number premutations are more likely to haveaffected children [F2, Y1]. Since this expansion occurs
when the repeat array is transmitted from one generation to
the next, the disease shows what is referred to as"anticipation", i.e. an increase in disease severity and/or adecrease in the age at onset as the disease passes throughgenerations. Because of these unique features (transition
from normal copy number to premutation to full mutation
involving more than one step), the term "dynamic mutation"
is used for this type of mutational mechanism (reviewed in[F3, S15]).
56. Males have been observed to transmit only thepremutations, and these do not usually change much in size.
Hence all daughters of male carriers of premutations havea premutation of about the same size as that of their father,
but they never have the full mutations and, consequently,
lack features of the fragile-X syndrome. Sherman delineatedthis paradox, which bears her name: that the mothers anddaughters of males with premutations have very different
risks of having children with fragile-X syndrome [S17,S18]. It is now known that these two groups of women are
at different stages of progression of the dynamic mutation.
The mothers of males with premutations have, on average,
smaller premutations than the daughters of these males. The
premutation usually increases in size when transmitted fromthe mothers to their sons but then goes relatively unchanged
to the daughters of these males. Because the risk of premutation changing to a full mutation on transmission by afemale is a function of its size, the paradox can now be
explained.
(b) Huntington disease(a) Fragile-X syndrome
54. The fragile-X syndrome of X-linked mental
retardation has a prevalence that could be as high as 1 per
1,000 males (range: 0.3!1 per 1,000) and 0.6 per 1,000

57. Huntington disease is a progressive neurodegenerative
disease characterized by a diverse set of symptoms,
including personality changes, progressive chorea, anddementia. It is inherited as an autosomal dominant and16

UNSCEAR 2001 REPORT

affects about 1 in 10,000 individuals in most populations ofEuropean origin [H7]. The onset of symptoms generally
occurs within the fourth or fifth decade but can vary fromvery early childhood to the late 70s. About 6% of cases
have onset before age 21 years, and the disease progression
is more severe. The CAG repeats are located in the firstexon of the Huntington disease gene at amino acid residue
18 [H8]; both increases and decreases in length of CAG
repeats upon maternal and paternal transmission have beenfound, but these are generally less than five repeat units.
With paternal transmission, however, there is a higher
percentage of increases, some of which are quite large. The
majority of expansions in the large size range (>55) are
paternally transmitted, including all juvenile patients withchildhood onset [A3, B11, G3, H8, N3, S21].
58. It is now known that huntingtin, the gene product of
the HD gene, is crucial for normal development and thattranslation and expression of mutant huntingtin result inneuronal death. Huntingtin is specifically cleaved during
apoptosis by a key cysteine protease, apopain, known toplay a pivotal role in apoptotic cell death. The rate ofcleavage is strongly enhanced by longer polyglutamine
tracts, suggesting that inappropriate apoptosis may underlie
Huntington disease. These proteins have now been
identified and shown to interact with huntingtin, two ofthese interactions being influenced by CAG length(reviewed in [N4]).
(c) Myotonic dystrophy

61. The mechanism of the disease has been hypothesized
as follows: since the repeats are present in a very gene-richregion of the genome, the amplified repeats disrupt genetranscription, mRNA processing, or gene translation,
resulting in abnormal levels or functionally altered forms of
the protein product DMPK. The results published so far arecontradictory, showing both increases and decreases in
DMPK expression at the level of transcription. These
results and those from animal model experiments suggestthat other genes may be involved in the disease (reviewed
in [H12]).
7. Summary
62. The examples discussed above document the fact thateven for Mendelian diseases, the relationships between
genotype and phenotype are not necessarily simple or
straightforward. They show that
(a)
(b)
(c)
(d)
(e)

different mutations of the same gene can have quite
different clinical phenotypes (allelic heterogeneity);
the same mutation in a given gene can result indifferent clinical phenotypes;
mutations in different genes can have similar clinicalphenotypes (non-allelic heterogeneity);
mutations in the same gene can be inherited as
dominant or recessive; andthe non-traditional mechanisms of disease, e.g.
mosaicism, genomic imprinting, uniparental disomy,
and trinucleotide repeat expansions, introduce a new
dimension of complexity in genotype-phenotype
relationships.

59. Myotonic dystrophy, like Huntington disease, is an
autosomal dominant disease and is the most common formof adult muscular dystrophy, with an incidence of about 1
in 8,000 in most populations [H10]. In the Saguenay regionof the province of Quebec, Canada, the prevalence is about
1 in 500 [D6, M8]. The disease is characterized byprogressive muscle weakness and sustained muscle
contraction, often with a wide range of accompanying
symptoms (cataracts, cardiac conduction defects, mental
retardation, testicular atrophy, etc.). The age at onset andseverity of the disease show extreme variation, both within
and between families, and can be broadly classified into threeclinical groups: minimally affected (late onset), classical(early adult onset), and severe congenital (onset at birth;
inherited almost solely from the mother) (reviewed in [W6]).

63. In retrospect, the existence of allelic or non-allelicheterogeneities is not entirely unexpected, for at least two
reasons. First, no gene exists in isolation, and no gene (orgene product) is completely insulated from genetic
influences from its immediate sequence environment orfrom other gene loci. Likewise, as McKusick [M1] states“... in defining a given phenotype, the terms dominant andrecessive are of diminishing significance the closer one
comes to primary gene action”. The difference, relative toearlier periods in human genetics, is that advances inhuman molecular biology are now permitting insights into
these complex relationships between mutation anddisease.

60. The disease is due to CTG repeat expansions locatedin the 3' untranslated region of a gene whose sequence
predicts the protein product to be a member of the protein
kinase family [B12, F4, M9]. Amplification of the repeat isfrequently observed after genetic transmission, but extreme
amplifications are not transmitted through the male line.
This explains anticipation and the occurrence of the severecongenital form in the offspring of affected women. Intergenerational repeat size reductions occur predominantlywith paternal transmission [L7, M9, M10, T7, W6, W7].
Worth noting is the finding that in myotonic dystrophy, theexpansions of the CTG repeat can be very large and similar
to those recorded in the FRAXA gene.

64. Secondly, the designations used so far for mostgenetic (including Mendelian) diseases are clinical orbiochemical descriptors, based on the readily observableclinical or biochemical phenotypes. Considering the factthat a wide variety of molecular changes can occur in agene but yet result in a restricted number of clinical orbiochemical phenotypes, as well as the fact that thephenotypes of mutations in structurally and functionallyrelated genes may overlap, it is not entirely surprising thata given clinical disease is caused by mutations in more than
one gene. Thus, hyperlipoproteinaemia, for instance, is notreally a genetic designation but a biochemical descriptor
that refers to the presence of elevated levels of cholesterol-

ANNEX: HEREDITARY EFFECTS OF RADIATION

and/or triglyceride-carrying proteins called lipoproteins in
the blood; there are various genetic types of hyperlipoproteinaemia, depending on which of the several genes in
the lipoprotein metabolic pathway is affected by mutation.
65. The problems presented by these heterogeneities ingenetics and clinical medicine are obvious: molecular
heterogeneity poses a clinical dilemma and clinical heterogeneity, a molecular dilemma. Both present a formidable
challenge in genetic risk estimation. Further, as discussed
in Section III.D, what have been traditionally regarded as
multifactorial diseases are now beginning to yield tomolecular techniques; these heterogeneous clinical entities
are now beginning to be split up into genetically homogeneous constituent groups as the genes involved are
identified. Stated differently, the boundaries between
Mendelian and multifactorial diseases are slowly disappearing. These developments suggest that the strategies
for genetic risk estimation require fine tuning.
66. The Committee takes note of these impending
developments in the field and realizes that in future risk
assessments it may become possible to focus on specific,
clinically relevant genetic diseases, based on a knowledgeof the underlying genes, their organization, their genomic
context, and the extent to which induced mutations may bepotentially recoverable in live births. The rates of induced
mutations, however, have to be extrapolated from mouse
data. This issue is discussed later.

17

1. Autosomal dominant diseases
69. For autosomal dominant diseases (Table 10), the total“unadjusted” estimate for all the diseases included is of theorder of about 92!96 cases per 104. Of the several additional (i.e. subsequent to Carter’s compilation) diseases
included in Table 11, two (hypercholesterolemia due tofamilial defective ApoB-100 [FDB] and familial breast
cancer due to BRCA1 and BRCA2 mutations) contribute
substantially (10!15 per 104 and 10 per 104, respectively;
together, 20!25 per 104) to the unadjusted total. FDB is due
to rare mutations in the ApoB gene that affect the bindingof LDL to the LDL receptor [I11] and is thus different fromthe well known classical form of familial hypercholesterolemia that is due to mutations in the LDL
receptor (LDLR) gene [G17].
70. Many other new entries (neurofibromatosis type 2,
Treacher Collins syndrome, craniosynostosis, holoprosencephaly, van der Woude syndrome, von Hippel Lindau
syndrome, Williams syndrome, Velocardial syndrome,
Hirschprung disease, Li-Fraumeni syndrome) contribute farless to the birth frequency estimates. For some disease
entities such as antithrombin deficiency, familial hypertrophic cardiomyopathy, hereditary haemorrhagictelangiectasia, and dominant forms of adult onset deafness,
only prevalence estimates are available and have not been
included in the unadjusted total birth frequency.
2. Autosomal recessive diseases

D. BASELINE FREQUENCIES OF
MENDELIAN DISEASES
67. The estimates of baseline frequencies of Mendeliandiseases used until 1993 were based on the work of Carter[C67, C68] in the mid-1970s. The estimates were:
autosomal dominant, 95 cases per 104 live births; autosomal
recessive, 25 per 104; and X-linked, 5 per 104 (together, 125
per 104 live births). The advances that have occurred sincethen permit the revision of the above estimates to 150 per
104 for autosomal dominants, 75 per 104 for autosomal
recessives and 15 per 104 for X-linked diseases (together
240 per 104) [S105] (Table 9).
68. Tables 10!12 provide details of the various diseases
and their respective incidences on which the revisions
shown in Table 9 are based. Included in Tables 10!12 are
the earlier estimates of Carter [C67] and the additional ones(designated by footnote). If only population prevalence data
are available, they are given in a separate column. The
Mendelian Inheritance in Man (MIM) numbers for thedifferent entries are from McKusick’s compendium [M2].
The numbers of genes already known or mapped are given
to provide an idea of what is now known about the genetic
basis of these diseases. The original references to Carter’s
compilation are given in his 1977 paper [C67] and are notrepeated here.

71. For autosomal recessive diseases, the total“unadjusted” estimate is 50.8 cases per 104 (Table 11). The
one significant addition to the list of these diseases ishaemochromatosis, a disorder of iron metabolism in which
increased absorption of iron causes iron overload; theexcess iron is deposited in a variety of organs, leading totheir failure and resulting in serious illnesses such as
cirrhosis, hepatomas, diabetes, cardiomyopathy, arthritis,and hypogonadotrophic hypogonadism. Although it can befatal if undetected [B68], life expectancy is normal if ironis removed by venesection in the precirrhotic stage of thedisease [N22]. Patients often do not present until middle
age. Until recently, haemochromatosis was considered arare disease, but it is now clear that among individuals ofnorth European descent about 1 in 300 (range: 1 in 400 to
1 in 200) are homozygotes [E19, L51, W29]. At least one
candidate gene for haemochromatosis has been cloned, andmutations have been identified [F15].
3. X-linked diseases
72. The unadjusted total estimates for X-linked recessive
diseases is 17.65 cases per 104 male births or 8.8 cases per
104 of all, i.e. both male and female births (Table 12). The
significant addition is fragile-X mental retardation with anestimated live birth frequency of 5 per 104 male births [F3].
The entity that Carter designated as “X-linked non-specificmental retardation” and his estimate of 1 per 104 for this

UNSCEAR 2001 REPORT

18

have been retained in view of the fact that McKusick [M2]notes that at least 10 other X-linked genes associated withmental retardation have been mapped.
4. Revision of the total birth frequency
estimates
73. The unadjusted total estimates for each of the threeclasses of Mendelian diseases have been adjusted upwards
to obtain the revised estimates as follows: autosomal
dominant, from 92!96 per 104 live births to 150 per 104;
autosomal recessive, from 50.8 per 104 to 75 per 104 andX-linked, from 8.8 per 104 to 15 per 104. Together, therevised total frequency of 240 per 104 live births (Table 9)
is about twice that estimated by Carter [C67].
74. The reasons for the upward adjustments were thefollowing: (a) for some entries in Tables 10!12, only
prevalence estimates are available and have not been
included in the unadjusted totals, and no estimates arepresented for breast/ovarian cancers associated with genes
other than BRCA1; (b) the estimates in the above tables do
not include all the inherited forms of mental retardation,
abnormalities of motor and physical development, visualand auditory abnormalities, and behavioural disorders, tomention only a few; (c) at present, advances in the Human
Genome Project are rapidly contributing to knowledge of avast number of Mendelian diseases, although frequency
estimates for individual diseases are still not available; and(d) as mentioned in paragraph 10, as of January 2000, theon-line Mendelian Inheritance in Man [M2] already lists
over 11,000 entries (roughly two thirds with locus
assignments to one or the other autosome or the X-chromosome); these numbers are only bound to increase in the
coming years. Considering all the above and the fact that
only about 10% of the human genome has been sequenced
so far [G21], as well as the estimated number of genes(about 80,000; see Chapter I), the revisions mentioned in
the preceding paragraph seem justified. The Committee will
use these figures in risk assessment.
5. Population/ethnic differences
75. The estimates given in Tables 10, 11 and 12 represent
a synthesis of information from studies on western
European or western-European-derived populations in the
mid-1950s to mid-1970s and as such provide some insights
into the load of Mendelian diseases in these populations.
However, marked differences between different
populations or ethnic groups, especially in the frequencies
of autosomal recessives, have long been known, and moresuch instances are being discovered.
76. In considering these differences (and similarities), it
should be remembered that, in general, autosomal dominantdiseases that are severely selected against (e.g.
achondroplasia) will occur at similar frequencies in mostpopulations and that most are due to new mutations.

However, those dominant diseases for which there is little
or no selection either because the abnormality is trivial or
it manifests after reproduction has been completed(minimal or no selection), the incidence and prevalence
may be quite different in different populations dependingon factors such as population size, history, and breeding
structure; most of these diseases (e.g. Huntington disease
and familial hypercholesterolemia) are not due to new
mutations. The above statements are generally true for
X-linked recessive diseases as well. In the case of
autosomal recessive diseases, however, selection pressures
are much less efficient, because most of the mutant genes
are carried by asymptomatic heterozygotes. For this reason
and again depending on population size, history, andbreeding structure, autosomal recessive diseases can appear
at high frequencies in some isolated populations.
77. With the advent of molecular biology, it became
possible to discern the unique pattern of DNA variation
around the mutant genes and to use this to characterize theorigin of the mutation and explain how enrichment for
specific mutations in specific populations might haveoccurred. These high frequencies and enrichment for
specific mutations are believed to have resulted from some
type of bottle-neck in their history, revealing the consequences of “founder effects”, “genetic drift”, andinbreeding in their respective gene pools. The populations
most extensively studied in this regard include the
Ashkenazi Jews, the Finnish, the French-Canadians, and
the Afrikaners of South Africa, descended from Dutch
settlers; further, data are now becoming available for Arab
populations from the Middle East. Illustrative examples are
given in Tables 13 and 14.
78. The principal message of all these findings forradiation genetic risk estimation is that Carter’s [C67]
original lists and the revised lists (Tables 10!12) and theestimated frequencies provide reasonable insights into theburden of Mendelian diseases in western European andwestern-European-derived populations but do not reflect
either the profile or the aggregate burden of such diseases
in any specific population. It can therefore be argued thatthey may not constitute an entirely reliable baseline whenother populations are considered, especially when thesefrequencies are used in the risk equation. For example, forthe sake of argument, if one assumes that the rate ofradiation-induced mutations in specific disease-causing
genes is the same in different populations, the relative
increase in risk, as estimated by the doubling-dose method,is expected to be different when the baseline frequencies
are different. Consequently, there is the need for caution in
extrapolating the radiation risk of Mendelian diseases fromone population to another.
79. Two additional factors not discussed thus far alsoneed to be borne in mind: (a) the spectrum and frequency ofgenetic diseases in different parts of the world can change
as a result of increased mobility and population admixtures,and (b) at least in most industrialized nations of the world,
the increasing availability of genetic screening, genetic

ANNEX: HEREDITARY EFFECTS OF RADIATION

counselling, and prenatal diagnosis (and emphasis on early
detection and primary prevention) may reduce thefrequencies of certain diseases in the long run, although themagnitude of the reduction is hard to fathom at present.
6. Summary
80. Advances in human genetics during the last two
decades now permit an upward revision of the estimates ofbirth frequencies of genetic diseases to about 150 per 104
live births for autosomal dominants, 75 per 104 live births
for autosomal recessives, and 15 per 104 live births for
X-linked diseases (together, 240 per 104 live births). The
main contributors to the revised estimates are the following
disease entities: autosomal dominant: familial breast andovarian cancers due to mutations in the BRCA1 gene (10per 104) and hypercholesterolemia due to mutations in the
ApoB gene (familial defective ApoB-100; 10!15 per 104);
autosomal recessives: haemochromatosis (30 per 104); andX-linked: fragile-X syndrome (2.5 per 104).These estimatesare based predominantly on data from studies of western
European and western-European-derived populations.
81. In several population isolates or ethnic groups, someof these diseases, especially the autosomal recessives, aremore common and/or show an enrichment for specificmutations due to “founder effects” and/or genetic drift,combined with high levels of inbreeding. This isdemonstrated in studies of the Ashkenazi Jewish andFinnish populations. Differences between populations in
the baseline frequencies of Mendelian diseases suggest theneed for caution in extrapolating radiation risks between
populations.

E. SPONTANEOUS MUTATION RATES
1. The concept of equilibrium between
mutation and selection
82. Although new mutations arise spontaneously in every
generation, the frequencies of the diseases in the population
are believed to remain stable from one generation to thenext. Population genetic theory dictates that in large,
random-mating populations, this stability is a reflection of
the existence of a balance between the rates of origin of
spontaneous mutations and the rates of their elimination
through selection (the equilibrium theory). For example, inthe case of autosomal dominant and X-linked diseases withonset in childhood, if the individuals with the mutations die
early or are so severely handicapped as to preclude
reproduction (selection coefficient = 1), the birthfrequencies and prevalences are determined mainly by
mutation rate, and most cases with the disease will be new
mutants (e.g. Apert syndrome and achondroplasia). If,
however, disease onset occurs after the age at which
reproduction has already occurred and the selection
coefficient is less than 1 (e.g. familial hypercholesterolemia), the mutant genes will persist in the population for19varying periods of time, and the affected individuals in the
population represent pre-existing and new cases due tospontaneous mutations. For these diseases, the birthfrequencies and prevalences can vary depending on the sizeof the population, history, and breeding structure, as
discussed in the preceding Section.
83. For autosomal recessive diseases, the estimation of
mutation rates is complicated [C69, M57, V20]. It isenough to note here that (a) the phenotypic incidence of
these diseases is not directly proportional to mutation rate,since when a recessive mutation first arises, it is present ina heterozygote; (b) estimates of mutation rates for recessive
mutations depend on the assumption that at some time in
the past an equilibrium was reached between spontaneous
mutations and their loss through selection, although areduction in inbreeding in recent generations in mostpopulations makes the assumption of current equilibria
somewhat questionable; (c) in calculating mutation rates forautosomal recessive mutations, one should take into
account the elimination of mutant alleles through theireffects in heterozygotes, through consanguinity, andthrough the mutant gene’s “meeting” a pre-existing mutant
allele by chance; and (d) instances are known where thestability of the frequencies of recessive diseases (e.g.
sickle-cell anaemia and cystic fibrosis) is believed to reflect
a selective advantage for the recessive mutation in aheterozygous condition vis-à-vis the normal homozygote
and the mutant homozygote. These diseases (that is to say,the mutant genes) are maintained in the population by
selection alone [A24].
2. Spontaneous mutation rates forautosomal dominant and X-linked diseases
84. Methods for estimating the mutation rates ofautosomal dominant and recessive and X-linked mutations
and their difficulties and potential biases are discussed by
Morton [M57], Crow and Kimura [C70], Childs [C39],
Crow and Denniston [C69], and Vogel and Motulsky[V20]. The most important bias in mutation rate studies
arises from the fact that genes that mutate frequently are
more likely to be studied than those that mutate rarely, andobviously, those that have not been observed to mutate
cannot be studied. This bias can enormously inflate
estimates of a representative mutation rate, if there is one[C69, V20].
85. Table 15, taken from the classic reviews of Vogel andRathenburg [V21] and Vogel and Motulsky [V20], presents
some estimates of mutation rates for human genes, most ofthem based on population studies. As can be noted, themutation rates are between 104 and 106 per gamete per
generation and are heterogeneous. Of the autosomal
dominants, neurofibromatosis has the highest mutation rate,
about 1 104, and polycystic kidney disease the next
highest, 5.5!12 105. These are followed by polyposis coli
(1.3 105), achondroplasia (~1 105), myotonic dystrophy(0.8!1 105), and others with lower mutation rates. For the

20

UNSCEAR 2001 REPORT

X-linked recessives listed in Table 15, the median value isin the range 10!30 106 [C69].

these expectations have been fulfilled, and the data thatbear on these issues have been reviewed [C71, C72, V20].

86. Stevenson and Kerr [S106] made the first and so far
the only serious attempt to obtain less biased estimates for
X-linked diseases. Their data, based on 875,000 newborns,
are summarized in Table 16, which includes 49 wellestablished diseases, excluding those whose frequencies are
not dependent on a mutation-selection equilibrium (colour
blindness, Xg blood groups, G6PD variants). The diseases
that are estimated to have high mutation rates include
Duchenne muscular dystrophy (50!70 106), haemophilia A(20!40 106), non-specific, severe mental retardation(10!20 106; presently, this probably corresponds tofragile-X mental retardation), and haemophilia B(5!10 106). For 24 conditions, the estimated rates are
below 1 107. Noting that the distribution of rates set out inTable 16 are “defective of the real total situation at thelower end”, Stevenson and Kerr [S106] went on to say, “Itis difficult to avoid the conclusion that the mean mutation
rate to visibles on the X chromosome in man is not morethan 106, and in the absence of contrary information, there
is no reason to suppose that such a level is not also
representative of rates of occurrence of such mutations over
the whole genome”. The estimates in Table 16 have amedian value of about 0.1 106, which is two orders ofmagnitude lower than that for the sex-linked diseases
included in Table 15 [C69].

89. Vogel and Motulsky [V20] estimated that in thefemale the number of cell divisions from zygote to themature egg (Nf) is about 24. In the male, there are about 30
cell divisions from zygote until the age of puberty (taken to
be 15 years), ~ 23 per year thereafter and 6 for proliferationand meiosis. Thus the number of cell divisions prior tosperm production (Nm) in a 20-year-old male can be
estimated to be 30 + (5 × 23) + 6 . 151, increasing to 381
at age 30, 611 at age 40 and 841 at age 50 [C4]. It is clearthat the Nm/Nf ratio varies with the age of the male, being
about 6 when the male is 20 years of age, increasing to 16
at age 30 years, to 25 at age 40 years and 35 at age 50
years. Assuming that the number of spontaneous mutationsin the male is proportional to the number of cell divisions,
Crow [C71, C72, C4] estimated that, in the age range from17 to 52 years, fathers of children with de novo dominant
mutations (Apert syndrome, achondroplasia, myositis
ossificans, Marfan syndrome etc.) were expected to be older
by 2.7 years on average, relative to those of unaffectedchildren. The observed difference in paternal age, however,
was about 6 years indicating a faster-than-linear increase in
mutation rate with paternal age. The graphs in the paper of
Crow [C72] suggest that even a quadratic relationshipbetween mutation rate and paternal age is insufficient andthat a cubic relationship fits better, although the accuracy ofthe data does not merit detailed curve-fitting [C4]. The
subject has been recently reviewed by Crow [C13].

87. The causes of the large differences in mutation rates
between genes are not fully understood. Mutation rates
estimated from phenotypes can be high if there is genetic
heterogeneity (mutations in different genes resulting insimilar clinical phenotypes), and several examples were
given in Table 5, but this is certainly not the only
explanation. In general, the mutation rate of a given gene isa function of the size and organization of the gene, themechanisms involved, and the number of mutational sites.
For example, the two genes with the highest mutation rate,
namely those that underlie neurofibromatosis 1 andDuchenne/Becker muscular dystrophies, are also among thelargest genes known (genomic sizes of ~300 kb and2,400 kb, respectively), but again, size alone may not be theonly explanation.
3. Sex differences in mutation rates
and paternal age effects
88. The estimates of mutation rates presented in Table 15
do not distinguish between mutations in males and females;
for autosomal genes, they represent the unweighted
averages and for X-linked ones, the weighted averages.
Since most spontaneous mutations arise as a consequenceof errors introduced during DNA replication, one would apriori expect that the male germ line should have a higher
mutation rate than the female germ line as a result ofcontinual post-pubertal mitotic processes in the male.
Further, the likelihood of germinal mutations should
increase in older males (paternal age effect). By and large,

90. In addition to the diseases mentioned above, strong
paternal age effects have also been found for basal-cell nevus
syndrome, cleidocranial dysplasia, Crouzon syndrome,
fibrodysplasia ossificans, oculodentodigital syndrome,
Pfeiffer syndrome, progeria, and Waardenburg syndrome[R43]. Further, the demonstration in molecular studies that all
de novo cases of multiple endocrine neoplasia types A (10cases) and B (25 cases) and Apert syndrome (57 cases), a
total of 92 cases, are paternal in origin lends support to theview that the mutation rate in males is higher than in females[C73, M58, S107]. Additional information that bears on theabove but coming from studies of molecular evolution (maledriven molecular evolution) is provided in the papers of Drostand Lee [D32] and Crow [C72] and references cited therein.
91. There are exceptions to the above pattern, however.
Two conspicuous ones are Duchenne muscular dystrophy(DMD) and neurofibromatosis 1 (NF1) neither of whichshows a significant sex difference or a striking paternal (orin the case of X-linked muscular dystrophy, grandpaternal)
age effect demonstrable for multiple exostoses, bilateralretinoblastoma, neurofibromatosis 1, Sotos syndrome, andTreacher Collins syndrome. For mutations in the factor IX
gene (haemophilia B), a recent population-based study in
the United Kingdom showed that the mutation rate in males
is about 9-fold higher than in females [G7], but
grandpaternal age effect was not studied. The work ofSommer and Ketterling [S108], however, provides someevidence for a maternal age effect, but the data are limited.

ANNEX: HEREDITARY EFFECTS OF RADIATION

92. The explanation for sex differences and paternal age
effect for mutations seems to lie in the nature of mutations.
Grimm et al. [G8] reported on 198 mutations to DMD inwhich the parental origin could be determined. Of these 114
were deletions, 8 were duplications and 76 were notdetectable by deletion screening and were presumably point
mutations. The great majority of the latter were paternal, as
expected, but more than half of the duplications anddeletions were maternal. Although the maternal/paternalratio is not significantly different from 1:1, the data at facevalue suggest that the rate of deletions may be higher infemales. In any case, this difference between the sexes is
not as striking as that recorded for base pair substitution
mutations. The data for NF1 [L21] are similar: of the 11
point mutations, 9 were paternal and of the 21 deletions, 16
were maternal. The presence of both point mutations anddeletions explain the weak paternal age dependence of
spontaneous mutations that cause NF1.

4. Relevance of sex differencesin spontaneous mutation rates
and paternal age effects in humans
93. The reasons for discussing sex differences inspontaneous mutation rates and paternal age effects inhumans are intimately related to the use of the doublingdose method of risk estimation. Briefly, the use of thismethod requires an estimate of what is termed “thedoubling dose” (DD), which is one of the quantities in therisk equation (risk per unit dose = P × 1/DD × MC). In thisequation, P is the baseline frequency of the disease class,
DD is the doubling dose and MC is the mutation
component (a quantity that specifies the relative increase indisease frequency per unit relative increase in mutation rate;
see Chapter IV). The doubling dose is the amount ofradiation required to produce as many mutations as thosethat occur spontaneously. It is calculated as a ratio of theaverage rates of spontaneous and induced mutations in a setof defined gene loci. The reciprocal of the doubling dose
(i.e. 1/DD) is the relative mutation risk per unit dose.
94. It would have been ideal to base doubling-dose
estimates on human spontaneous and induced rates ofmutations; however, this avenue was not open to risk
estimators because of the lack of human data on radiationinduced germ cell mutations, and the situation has notchanged in all these years. A less ideal approach was chosen
in the 1972 BEIR Report [C47], namely, the use of humandata on spontaneous mutation rates and mouse data on
induced rates. This approach had the advantage that the only
specific assumption needed was that the average rate ofinduced mutations in human germ cells was the same as thatin mouse germ cells. This assumption was (and remains)defensible on the grounds of generally similar geneorganization, 70%!90% homology in DNA sequence ofgenes and substantial conservation of synteny (i.e. a group ofgenes on a single chromosome in one species is observed tobe similarly linked in another species) for many, although notall, chromosomal regions between humans and mice.

21

95. A much less ideal approach was to base the doublingdose on mouse data on rates of both spontaneous andinduced mutations, predominantly those pertaining torecessive mutations at the seven extensively studied loci. This
was the approach that gained currency in the UNSCEAR
Reports from 1977 onwards [U4, U5, U6, U7, U8] and in the1980 and 1990 BEIR Reports [C48, C49]. While it had theadvantage that the same genes could be used for determining
the spontaneous and induced rates of mutations, it implied theassumption of similarity of spontaneous mutation rates ofhuman and mouse genes (i.e. the doubling dose could be
extrapolated from mouse to humans). This assumption can nolonger be considered correct in the light of sex differences
and paternal age effects for spontaneous mutations in humans(discussed in the preceding Section) and data on the numberof cell divisions in the mouse (discussed below).
96. In the mouse female, the number of cell divisions (Nf)from zygote to the mature egg is of the order of about 24[D32], which is the same as that in the human female (seeparagraph 89). In the male mouse, the number of cell
divisions from zygote to sperm (Nm) is of the order of about
62 at age 9 months, assuming a 9-month generation [C74,D32]. The Nm/Nf ratio is thus 2.5 (i.e. 62/24), which is much
lower than in the human male (see paragraph 89). The
inference, therefore, is that the spontaneous mutation rates inmice are unlikely to be very different between the two sexes(in contrast to the situation in humans). Worth pointing out
here is the fact that in most mouse experiments, the parental
animals were used at a rather uniform age and the question ofpaternal age effects had not been specifically addressed.
97. The enormous difference in lifespan between humans
and mice, the fact that the published estimates of
spontaneous mutation rates in humans are unweighted
averages of the rates in the two sexes (and therefore
automatically incorporate the sex differences and paternal age
effects) and the fact that it is the average rate that is relevantin the context of the doubling-dose calculation strongly
suggest that extrapolation from short-lived mice to humans isunlikely to provide a reliable average spontaneous rate in aheterogeneous human population of all ages.
98. It is a curious fact that although sex differences in andpaternal age effects for human spontaneous mutation rates
had been known for a long time and were certainly wellestablished by the mid-1970s, neither UNSCEAR nor the
BEIR Committees considered these important enough tomerit consideration in the context of the doubling-dose
calculations. The Committee now feels that the arguments
advanced in this and the preceding Sections are compellingenough to go back to the earlier approach used by the BEIR
Committee in its 1972 Report [C47], namely, to base thedoubling-dose estimate on human data on spontaneous
mutation rates and mouse data on induced mutation rates.
A further argument supporting the need for such a
conceptual change comes from the uncertainties that havebeen recently uncovered in the calculation of spontaneous
mutation rates in mice. This aspect is discussed in
Chapter VI.

UNSCEAR 2001 REPORT

22

5. Summary
99. The population-genetic theory of equilibrium between
mutation and selection (that is used to explain the stabilityof the incidence of genetic diseases in the population) was
briefly reviewed in this Section, and published estimates of
spontaneous mutation rates in humans that cause autosomal
dominant and X-linked diseases were considered; theseestimates vary over a wide range and the underlying causes
are not fully understood. Additionally, the basis for the
pronounced sex differences in mutation rates, thesupporting evidence, and their relevance for doubling-dose
calculations were addressed.
100. Estimates of the number of cell divisions between thezygote and the mature germ cell in humans predict that (a)the spontaneous mutation rates in the two sexes will differ(being higher or much higher in males, depending on age,than in females), and (b) in the male, the mutation rate will

increase with the age of the father. Both these predictions
have been amply fulfilled, and in addition there now is, aswell, supporting evidence from molecular studies. In themouse, the situation is different: no major sex differencesin mutation rates are expected, and the question of paternal
age effects on spontaneous mutations has not been
specifically studied.
101. In the calculation of doubling doses, the spontaneous
mutation rate constitutes the numerator (the denominatorbeing the rate of induced mutations). The spontaneous
mutation rate estimates used thus far in this calculation
come from mouse studies. Since the spontaneous mutation
rates in humans and mice are unlikely to be similar, the useof a doubling dose based on data on spontaneous rates inmice is conceptually flawed. The Committee now feels thatthe use of human data on spontaneous mutation rates (andmouse data on induced mutation rates) for doubling-dose
calculation is the prudent way forward.

III. MULTIFACTORIAL DISEASES
102. The term “multifactorial” is a very general designation
assigned to a disease known to have a genetic component butthat cannot be described in a simple Mendelian fashion. Suchdiseases are interpreted as resulting from a large number ofcauses, both genetic and environmental, although thepotential role of environmental factors has been delineatedfor only a few of these diseases (e.g. excess caloric intake
rich in saturated fat is an environmental risk factor forcoronary heart disease (CHD); environmental allergens arerisk factors for asthma). The common congenitalabnormalities (e.g. neural tube defects and cleft lip with orwithout cleft palate) and many common diseases of adultonset (e.g. coronary heart disease, diabetes mellitus, andessential hypertension) are examples of multifactorialdiseases; most cancers also are multifactorial. Because of
their high prevalence, they contribute very substantially tomorbidity and mortality in human populations.
103. As mentioned above, the majority of multifactorialdiseases do not fit Mendelian expectations in terms oftransmission characteristics, i.e. they are not single-gene
defects, but they occur at higher frequencies among
relatives of affected individuals than in the general
population. However, the risk to relatives varies from one
multifactorial disease to another and from family to family.
These features are not entirely surprising, because each ofthese clinical diseases is, in reality, a group of distinct
diseases with different aetiologies, both genetic (multiple
modes of inheritance) and non-genetic.
104. For most of these diseases, knowledge of the genes
involved, their numbers, the types of mutational alterations,and the nature of environmental factors is woefully
incomplete. At one extreme are the congenital abnormalities,
for which there is virtually no information. At the other iscoronary heart disease for which there is an overwhelming
amount of information at the epidemiological, biochemical,
genetic, and molecular genetic levels; however, the gene-geneand gene-environmental interactions are very complex andnot understood. The situation is in between these two
extremes for diseases such as essential hypertension anddiabetes mellitus, for which at least a few of the genes havebeen identified.
105. In the UNSCEAR 1986 and 1993 Reports [U4, U6],
the Committee reviewed some epidemiological aspects ofmultifactorial diseases. The currently known attributes andadvances in the genetic dissection of these diseases that are
pertinent in the context of risk estimation are discussed inthis Chapter under two broad headings, congenitalabnormalities and common multifactorial diseases.

A. CONGENITAL ABNORMALITIES106. Congenital abnormalities are gross or microscopic
structural defects present at birth whether detected at thattime or not. The adjective “congenital” signifies only theirpresence at birth and has no aetiological connotation.
Congenital abnormalities are the end results of dysmorphogenesis and can occur as isolated or multiple entities.
Isolated congenital abnormalities are structural defects thatcan each be traced back to one localized error inmorphogenesis; multiple congenital abnormalities are theANNEX: HEREDITARY EFFECTS OF RADIATION

result of two or more different morphogenetic errors during
development of the same individual [C33, C34, O5]. It
should be emphasized here that all congenital abnormalities, including the least severe forms, are all-or-nonetraits, i.e. they are not metric traits, and at their least severeend do not shade into normality [O5].

1. Overall prevalences
107. A vast body of data on the prevalences of congenitalabnormalities in different parts of the world has been
published in the literature (e.g. [B36, C33, C34, C36, C37,
C38, M36, S64]). The estimates vary over a wide range, fromabout 1% in live births to a high of about 8.5% in total births(i.e. still and live births), depending, among other things, on
the definition, classification, and diagnostic criteria, entities
included, method of ascertainment, duration of follow-up of
liveborn children, and sample sizes.
108. In Table 17, the estimates of live birth prevalences ofcongenital abnormalities in Hungary [C37] are comparedwith those in the Canadian province of British Columbia[B36]. The comparison shows that under conditions of good
ascertainment, the overall prevalences are similar and are of
the order of 6%!7% (2%!3% if only major congenitalabnormalities, i.e. lethal and severe ones, are considered).

2. Aetiological heterogeneity
109. A small proportion of many of the congenitalabnormalities show Mendelian transmission, e.g. cleft lip
with or without cleft palate found as part of autosomal
dominant conditions (Van der Woude syndrome and of theectrodactyly-ectodermal dysplasia-clefting (EEC)
syndrome). A number of congenital cardiovascular malformations are found in association with different
chromosomal abnormalities [S65] as well as with fetal
alcohol syndrome [H35].
110. The British Columbia [B36] and Hungarian estimates[C37] of the relative proportions of congenitalabnormalities due to single-gene mutations, chromosomal
anomalies, and environmental (including maternal) factors
are summarized in Table 18. Of the total prevalence ofcongenital abnormalities of 5.3% in British Columbia, one
half are judged to be attributable to non-genetic causes (e.g.
prenatal infections, known teratogen or birth trauma) andunknown causes; of the remaining one half, the vast
majority (86.8%) are multifactorial. The Mendelian,chromosomal, and “genetics unknown” categories accountfor, respectively, 4.1%, 6.9%, and 2.1% of congenitalabnormalities with a genetic basis. The estimates for
Hungary are in good agreement with the Canadianestimates, showing similar relative proportions ofMendelian, chromosomal, and multifactorial categories(among those with genetic aetiologies); however, the "nongenetic and unknown" category is much smaller (about 20%
compared with 50% in British Columbia).

23

3. Isolated congenital abnormalities(a) Epidemiological features
111. As mentioned in paragraph 106, isolated congenitalabnormalities are structural defects each of which can betraced back to one localized error in morphogenesis. The
Hungarian prevalences of well studied isolated congenitalabnormalities and some of their epidemiological features
are presented in Table 19. As can be noted, the sex ratio
departs from unity in most congenital abnormalities; there
are racial/ethnic, regional, or seasonal differences in thebirth prevalences of some congenital abnormalities; and theconcordance rates in monozygotic twins are higher (fromabout 15% for undescended testicles to about 80% forcongenital dislocation of the hip in Hungary) than those indizygotic twins (0%!14%), but not 100%. For cardiovascular malformations in general, both the Hungarian[C33] and literature data [C36, N12] suggest that theconcordance between monozygotic twins is of the order of
15%!20%. For dizygotic twins the rates are much lower.
(b) Recurrence risks
112. Data on the prevalences of isolated congenitalabnormalities in relatives of index patients are given in
Table 20. The findings are three: (a) the frequency ofaffected first-degree relatives of a proband is many times(5- to 50-fold) that of the general population; (b) there is a
sharp decrease in the proportion affected as one passes
from first- to second- to third-degree relatives; and (c) the
relative increase in risk (i.e. relative to the birth prevalencein the population) is more marked with low birth frequency.
For instance, in the case of congenital dislocation of the hip(birth prevalence of 2.8%), the risk to sibs is 13.8%, which
is higher by a factor of 5; for cleft lip with or without cleft
palate, with a lower birth frequency of 0.10%, the risk tosibs is 4.8%, which represents an increase by a factor of 48.
113. When the index case is of the more rarely affected
sex, the proportion of affected relatives is generally higher(Table 21). For example, in Hungary, congenital hypertrophic pyloric stenosis has a birth prevalence of 0.07% infemales and 0.22% in males. The risk to brothers ofaffected females is about 20%, which is much higher thanthe value of about 4% for the brothers of affected males[C33]. These estimates are comparable to those for theUnited Kingdom reported by Carter [C36] for brothers andsisters of male and female subjects, as well as for their sonsand daughters.
114. However, for cleft lip with or without cleft palate,which has a higher prevalence in males (0.13%) than infemales (0.08%), the risk to brothers of an affected male isabout 11% whereas that to brothers of an affected female isonly about 1% [C33]. For ventricular septal defect, forwhich sex difference in birth frequency in the population issmall, the risk to sibs of affected females is higher by afactor of 1.5!2 relative to that of sibs of affected males. In
the data from various studies summarized by Nora et al.
[N12], this tendency (i.e. higher risk to offspring of

UNSCEAR 2001 REPORT

24

females) is seen not only for ventricular septal defect but
for other cardiovascular malformations as well.
(c) Chromosome deletion map
115. Recently, Brewer et al. [B46] constructed achromosome map of autosomal deletions associated with 47
different congenital abnormalities using detailed clinicaland cytogenetic information on 1,753 patients with nonmosaic single contiguous autosomal deletions. The 1,753
deletions involved 258 of 289 (89%) possible autosomal
bands (in a standard 400-band preparation). In the 47
malformations chosen for study, 283 malformationassociated bands were identified (a ratio of 1:6), indicatingthat there are indeed a large number of genes controllingdevelopmental processes and that these are distributed inmany different chromosomes. This distribution, however,
was non-random: deletions involving 1q, 4p, 13, and 18p
were significantly over-represented, while those involving
5p and 15 were under-represented. Further, there werechromosomal regions/chromosomes (8q, 12p, 16p, and 20q)
that showed no significant associations with malformations, and only 1 of 1,753 reported deletions was inchromosome 19. As the authors noted, the deletion map
may obviate the need for whole genome scans as a first
approach to the identification of genes involved indevelopmental processes.
4. Summary
116. Congenital abnormalities arise as a result of developmental errors; the term “congenital” merely signifies theirpresence at birth and does not have an aetiologicalconnotation. The estimates of their prevalence at birthvaries from study to study, but in those in whichascertainment is good, the estimate of birth prevalence is of
the order of about 6%.
117. The sex ratios depart from unity for most congenitalabnormalities. The concordance rates in monozygotic twinsare higher than in dizygotic twins but never approach
100%. The frequencies of congenital abnormalities arehigher in relatives of affected individuals than in thegeneral population. The recurrence risks in families varywith the congenital abnormality and the degree of
biological relationship, being higher in first-degree than insecond- and third-degree relatives.
118. The various attributes of congenital abnormalities are
not readily explained on the basis of simple Mendelianpatterns of inheritance; both genetic and shared familial
environmental factors are postulated to play important rolesin their aetiology.
119. The recently published deletion map of congenitalabnormalities, showing that these abnormalities areassociated with deletions in specific chromosomes/
chromosomal regions, represents an important step forwardin the identification of the genetic basis of congenitalabnormalities.

B. MODELS OF INHERITANCE
120. The basic problem with conditions such as thecongenital abnormalities discussed above and chronic
diseases (to be discussed later) that are not simply
inherited in a Mendelian fashion becomes one ofassessing the relative importance of hereditary andenvironmental factors in their causation. Conceptualized
this way, it is a problem of quantitative genetics, thetheoretical basis for which was first established by Fisher[F21]. In that paper, Fisher showed that for acharacteristic showing quantitative variation due tonumerous Mendelizing genetic factors and non-genetic
factors each having a very small effect, the central limit
theorem can be applied to yield a normal (Gaussian)
distribution of phenotypic values from which thecomponents of variation due to genetic and non-genetic
causal factors may be estimated and correlation between
relatives derived.

1. The multifactorial threshold model(a) Assumptions and predictions
121. Falconer [F22] introduced the concept of disease"liability" to overcome the difficulty of the all-or-none
character of a disease (as in the case of congenitalabnormalities), so that a graded scale of the degree ofaffectedness or of normality could be envisaged. On thispremise, one would expect that all individuals above acertain value (the “threshold”) would exhibit the disease
and all below it would not. The general concept ofthresholds and “threshold characters”, however, dates backto the early work of Wright et al. (e.g. [W24, W36]) on
otocephaly (head abnormalities) in guinea pigs. For thequantitative development of the idea of thresholds, it wasnecessary to assume that the distribution of liability in a
population is Gaussian. With these concepts, it became
possible to extend the usual methods of quantitative
genetics developed for threshold characters to situations
where the data in the form of incidences refer to an all-ornone classification. (Note that the term threshold does nothave the same meaning here as in the context of nonstochastic effects of radiation.)122. Details of the multifactorial threshold model (MTM)
have been extensively discussed (e.g. [C33, C36, F22,
F23, F24, S66, S67, S68, V15]). The assumptions of thesimple version of the model are (a) all environmental andgenetic causes can be combined into a single continuous
variable termed liability, which, as such, is immeasurable;(b) liability is determined by a combination of numerous
genetic and environmental factors, acting additively
without dominance or epistasis, with each contributing asmall amount of liability and therefore normally
distributed; and (c) the affected individuals are those forwhom the liability exceeds a certain critical thresholdvalue (Figure I).

ANNEX: HEREDITARY EFFECTS OF RADIATION

General population

25(b) The concept of correlation in liabilities
between relatives

100
0.99

60
40

0.90
0.80
0.70

20
10

0.60

6
4

0.50

2
1

0 .4

0

0 .3

0

0
0.2

0.6
0.4

0
0 .1

0.2

0 .0

0.2

0.4 0.6

0.1
0

1

2

4

-0.
50

123. The multifactorial threshold model permits a numberof predictions, among which are the following. First, therelative risk to relatives of an index case (compared withthe general population) would be expected to beabsolutely greater, but proportionately less, as the
population frequency of the condition increases; thishappens because when the population frequency is high,
the genes for the condition are distributed throughout the
population, so that the likelihood of exceeding thethreshold is high; in a population in which the frequency
in the population is low, only relatives have a significant
risk. Inspection of Table 20 will reveal that, by and large,
this prediction is fulfilled. Second, for conditions forwhich there are marked sex differences in prevalence, themultifactorial threshold model with the added assumptionof different thresholds in the two sexes, would predicthigher relative risks to the relatives of the less frequently
affected sex. For example, congenital pyloric stenosis is
more common in males than in females and the recurrence
risk is higher for the children of a female proband thanthose of a male proband (Table 21). On the assumptionthat the threshold is farther from the mean in females thanin males, it follows that the affected females would haveto have more disease-predisposing alleles, on average,
than would male patients. The relatives of the female
patients would therefore receive more of these (being thus
at correspondingly higher risk) than the relatives of malepatients.

0
-0
. 40

Figure I. Distribution of liability in the general population and in relating relatives according tp the multifactorial threshold model.

125. Smith [S69] used a different approach to the problem
and advanced a slightly modified version of the multifactorial threshold model. Using a normally distributed
liability and assuming that familial environment has no effecton liability or the phenotype, he showed that the correlationof liability (r) between relatives is a product of two quantities,r = Rh2, where R denotes the coefficient of relationshipbetween relatives (and is independent of the number of lociinvolved) and h2 is the heritability of liability. The R values
vary depending on the genetic relationship (1 formonozygotic twins; 0.5 for parent-offspring, dizygotic twins,
and sibs; 0.25 for uncle-nephew; and 0.125 for first cousins).

-0.3Prevalence in relativesof affected probands

0

Mean liability
in relativesof affected probands-0.2

Relatives ofaffected probands.1
0

Population prevalence-0

Threshold value124. The multifactorial threshold model allows conversionof the information on the prevalence of a given multi-factorial
trait in the population (p) and in the relatives of those affected(q) into an estimate of correlation in liability (r) between
relatives, from which h2 (heritability of liability; see later) canbe estimated. To estimate correlation in liabilities between
relatives, Falconer [F22] originally used the parameters of thenormal curve and employed regression and selection methods
on the assumption that the variance of liability was the samein the relatives as in the general population. However, as waspointed out by Edwards [E12] and Smith [S69], since theaffected individuals (i.e. those exceeding the threshold) forma truncated group with a skewed distribution, the liability
among the relatives of the affected individuals will not be
normally distributed.

FREQUENCY IN RELATIVES
OF AFFECTED INDIVIDUALS (%)

Mean liability
in the population

6 8 102040 60 100POPULATION FREQUENCY (%)

Figure II. Correlation in liability between relatives, givenin the population frequency and the frequency inrelatives of affected individuals [D17].

126. Smith's [S69] nomogram (Figure II) depicts therelationships between the three quantities r, p, and q. Whenp and q are known, r can be read directly from thenomogram. Thus, for cleft lip with or without cleft palate,assuming a birth frequency of 0.1% and proportions ofaffected monozygotic twins, first-, second-, and thirddegree relatives of 40%, 4%, 0.7%, and 0.25% respectively,

UNSCEAR 2001 REPORT

26

the r values from Smith's nomogram are approximately
0.90, 0.45, 0.20, and 0.09. These may be compared with thetheoretical correlations of 1.0, 0.5, 0.25, and 0.125, which
would be expected if all the liability were due to additive
polygenic inheritance.
(c) The concept of heritability of liability
127. Heritability is a common statistic in quantitative
genetics for expressing the relative importance of transmissible genetic effects in the overall phenotypic variation[F34]. It is a ratio of variances and not of actual phenotypicvalues. Since the estimate depends on the magnitude of all
the components of variance (see below), a change in any
one of these will affect it. Further, the same trait in different
populations may have different heritabilities. It should also
be borne in mind that heritability estimates say nothing
about the number of genes or about how they work.
128. Since the phenotype owes its origin to genetic andenvironmental factors, the total phenotypic variance isusually partitioned into two components, genetic andenvironmental. If the total variance is denoted by VP,
genotypic variance by VG, and environmental variance by
VE, then, assuming that the genotypic and environmental
values are independent of each other (i.e. they are notcorrelated), VP = VG + VE.
129. The ratio VG/VP provides a measure of the relative
importance of the genotype as a determinant of thephenotypic value. This ratio is called the broad sense
heritability, or degree of genetic determination, and issymbolized by hB2.
130. The genotypic variance, VG, can be subdivided into an
additive component, VA, and a component attributed todeviations from additivity. Additive genetic variance is thecomponent that is attributable to the average effect of genes
considered singly, as transmitted in the gametes. The ratio
VA/VP expresses the extent to which the phenotypes
exhibited by parents are transmitted to the offspring, and it
determines the magnitude of correlation between relatives.
This quantity is termed heritability in the narrow sense andis denoted by hN2. Examples of h2 estimates for the
Hungarian data on congenital abnormalities (based oncorrelations between sibs) are given in Table 22.
131. The non-additive genetic variance is due to theadditional effects of these genes when combined in diploid
genotypes and arises from dominance, VD, interaction(epistasis), VI, between genes at different loci, andassortative mating, VAM. Note that in the absence of thesesources of genetic variance, hN2 = hB2.
2. Other models and concepts
132. The multifactorial threshold model remains useful forunderstanding familial aggregations and excess risks withinfamilies. However, it does not address questions of specificgenetic causes and mechanisms of disease susceptibilities.

Further, although the model assumes a large number ofcontributing factors, each with small effect, it provides areasonable approximation for traits with fewer contributing
factors, and for this reason it is not a good analytical toolfor discriminating between different modes of inheritance.
The fact that the multifactorial threshold model is notdiscriminatory has engendered attempts to fit the familial
aggregations observed with putative multifactorial traits to
Mendelian models (with appropriate choice of assumptions
regarding penetrance, epistasis, and dominance) or to
combinations of major locus and polygenic models [E13,K31, K32, L29, M37]. These are mentioned here merely toindicate that models other than the classic multifactorial
threshold model exist, and their current value lies in the factthat they are helpful in the search for the underlying genes.
As discussed in Section IV.D, the Committee has used amodified version of the multifactorial threshold model topredict the responsiveness of multifactorial diseases to anincrease in mutation rate.

3. Summary
133. Congenital abnormalities and other multifactorialdiseases do not follow simple Mendelian rules of inheritancebut run in families. The models that have been proposed to
explain their transmission patterns and that have been used to
predict recurrence risks in families rely on principles ofgenetics developed for quantitative traits, with suitable
extensions to make them applicable to all-or-none traits.
134. The multifactorial threshold model of disease liability
is commonly used for predicting recurrence risks in families
and risk to relatives from data on the population prevalenceof the disease. The model assumes that numerous genetic
and environmental factors contribute to what is referred toas liability to develop a disease; these factors act additively
without dominance or epistasis, each contributing a small
amount of liability. Because these factors are assumed to be
numerous, the distribution of liability in the population isnormal (Gaussian). Affected individuals are those whose
liability exceeds a certain threshold value.
135. The multifactorial threshold model, which makes useof the properties of the normal curve, enables a number ofpredictions, such as the relative risk to relatives of an index
case, recurrence risks in families, and the sex differences inprevalences. It also enables the conversion of informationon the prevalence of a multifactorial trait in the populationand in relatives of affected individuals into estimates ofcorrelation in liability, from which a useful statistic called
heritability of liability can be estimated. Heritability ofliability, which is a ratio of genetic variance to the total
phenotypic variance, provides a measure of the relative
contribution of transmissible genetic effects to the total
phenotypic variation, which has both genetic and environmental components.
136. The multifactorial threshold model is descriptive anddoes not address questions on specific genetic causes or theANNEX: HEREDITARY EFFECTS OF RADIATION

mechanisms of disease susceptibilities. Modified versionsof the multifactorial threshold model as well as single-locus
models, using additional assumptions, have been proposed
to explain the inheritance patterns of multifactorialconditions.

27

ing on the presence or absence of other risk factors, which
may be genetic and/or environmental (such as other genes,
diet, physical activity, and environmental exposures) [K34].
Thus, for these diseases, the more appropriate concepts are“genetic susceptibility” and “risk factors”. While there aresubgroups of common diseases associated with single
mutant genes (e.g. mutations in the LDLR receptor gene
causing an autosomal dominant form of familial hypercholesterolemia), for most common diseases, susceptibility
is genetically heterogeneous (i.e. different genetic
mechanisms lead to the same clinical endpoint) and istherefore more complex. Furthermore, not all geneticallysusceptible individuals will develop the disease, and nongenetic, environmentally produced phenocopies sometimes
occur.

137. The conclusions on models (of the type discussed
above) reached by Edwards [E12] in 1969 remain as
appropriate now as then. As he stated, “... the many-factor
model, where the factors are so numerous and individually
so feeble, that the central limit theorem can be applied toyield the smooth and tractable luxury of the normal curve,
and the single-factor model, in which the influence of one
factor is so great that all others can be regarded as trivial,
are the extreme interpretations between which reality mustlie ...”. The multifactorial threshold model nonethelessprovides a useful conceptual framework in the field of
multifactorial inheritance.

139. Some diseases require the simultaneous presence ofmutations in multiple genes (oligo- or polygenic). Thesemay be classified as discrete traits, measured by a specificoutcome (e.g. development of type I diabetes mellitus ordeath from myocardial infarction), or quantitative traits,measured by a continuous variable (e.g. diastolic bloodpressure, fasting glucose concentrations, or immunoglobulin E [IgE]), whose levels may be set by the combined
action of individual quantitative trait loci. Discrete traits
may represent a threshold effect (produced whenever anunderlying quantitative variable, influenced by multiple
genes, exceeds a critical threshold), or an effect requiring
the simultaneous and joint action of each of several
mutations [F22, F23].

C. COMMON MULTIFACTORIAL DISEASES
1. General concepts
138. Common adult diseases (e.g. diabetes, coronary heartdisease, essential hypertension), like the congenital abnormalities discussed in the preceding Sections, do not fit
Mendelian patterns of transmission. The genetic basis of acommon disease is the presence of a genetically susceptible
individual who may or may not develop the disease, depend-

Healthy
LEVEL

Diseased
Otherrisk factors

IV ENDPOINT

III RISK FACTOR

Environmental factors

II GENE
PRODUCT

I

GENE

A

B
POLYGENESZ

LDL-receptor
like mutations
MAJOR GENE

Figure III. A general model illustrating the role of polygenes, major genes- andenvironmental factors in the aetiology of a chronic multifactorial disease [S70].

UNSCEAR 2001 REPORT

28140. The general principles that have emerged from studies
on coronary heart disease provide a convenient conceptual
setting to examine the relationships between gene mutations
and diseases. Figure III, from the paper of Sing and Moll
[S70], provides a visual summary. Note that four levels are
distinguished linking mutations in genes (level I), which
through their products (level II) and environmental effects
contribute to quantitative variability of a biological risk
factor trait (level III) and thus ultimately to disease outcome(level IV). At level I, two classes of genes are distinguished:“polygenes”, whose mutant alleles individually have small tomoderate effects on the risk factor trait (indicated in
Figure III as A, B, Z), and “major genes”, whose mutant
alleles have strong effects (indicated by LDLR mutations).
141. Because polygenic mutations are common, they
contribute to the bulk of variation of the risk factor trait in
the population at large. In contrast, mutations in major
genes are associated with discrete phenotypic categories,
each with a discrete risk of developing disease, and aremuch less subject to environmental effects (e.g. LDLR
mutations resulting in the autosomal dominant form offamilial hypercholesterolemia). Such single-gene mutations
contributing to chronic diseases are rare. Although suchmutations may have a devastating effect on the individual
who carries them, they make only a minor contribution to
the variability of the quantitative risk factor trait in the
population at large and thus account for only a small
proportion of the chronic disease.
142. It is thus obvious that, unlike in the case of Mendeliandiseases, the use of genetic information to predict susceptibility to the common chronic diseases presents several
unique problems. For example, having a genetic defect is
not equivalent to having the disease. Further, no single genedefect will be expected to be causal in all or even in a
majority of cases. The genetic “dissection” of common multifactorial diseases therefore represents a great challenge for
medical genetics. In what follows, the general attributes ofcommon multifactorial diseases are first considered. These
attributes are then illustrated with three selected examples(diabetes mellitus, essential hypertension, and coronary heartdisease) to provide a look at the complexities and how thesediffer between the diseases. The subject has been recently
reviewed [S98].
2. Overall prevalencesand epidemiological features
143. A broad overview of the epidemiological features ofsome common multifactorial diseases in Hungary and inother parts of the world is presented in Table 23 [C35]. In
Hungary, the overall population prevalence of these
diseases is of the order of about 65%, including all age
groups; the estimates for individual diseases were computed
taking into account the age structure of the Hungarian
population and are, therefore, age-standardized. For
instance, if the prevalence figure pertains to the adult
population (above age 14 years), this figure was reduced by

21%, since the 0!14 age group represents 21% of the total
Hungarian population. In arriving at these figures, sexdifferences have been ignored. The prevalence estimates
given in parentheses are those from the study of Unoka[U17], in which all inhabitants over the age of 14 years in
one administrative unit in Hungary (n = 3,707) werescreened for the various diseases. This sample represented
96% of the entire population of that administrative unit.
144. The ranges of estimates for other parts of the world
are from data published in the literature; these are not agestandardized, since such information was not always
available. As can be seen, the total Hungarian prevalence of
65% is in good agreement with that (i.e. the total of themedian estimates for the individual estimates) for othercountries. Not obvious from Table 23 is the fact that someindividuals may (and do) have more than one disease, since
there was no easy way to exclude counting the same
individual more than once. The complete population surveyof Unoka [U17] is instructive in this regard. Among the
3,707 individuals studied, 618 (17%) did not have any ofthe diseases for which the screening was made; theremaining 3,089 individuals had a total of 10,097 diseases.
The overall population average was thus 2.7 diseases per
individual (10,097/3,089).
145. Apart from a few diseases (or disease sub-entities)
such as insulin-dependent diabetes mellitus and epilepsy,
most of the diseases included in Table 23 have mean onset
ages in middle life. With the exception of asthma, for which
the age distribution is bimodal (i.e. having two peaks, one
in early life and another in middle or late life), for mostothers the age distribution is normal, i.e. a low prevalencein young age groups, a high prevalence in middle agegroups, and a falling off at later ages. There are no striking
sex differences in prevalence for some (e.g. diabetes
mellitus, epilepsy, and essential hypertension), whereas forothers there is either male or female preponderance. Finally,
the estimates of heritability of liability, h2, encompass awide range, from 0.30 to 0.90.
3. Diabetes mellitus
146. Diabetes mellitus is a genetically heterogeneous groupof disorders that share the common feature of elevatedblood sugar. Collectively it is one of the most common
chronic diseases, afflicting up to 5%!10% of individuals in
Western countries. On the basis of several sources of data,
Rotter et al. [R19] concluded that over 8 million people in
the United States (3%) have diabetes. Diabetics have avariety of clinical features, ranging from an asymptomaticstate to acute diabetic ketoacidosis and chronic microvascular (nephropathy, retinopathy) and macrovascular(atherosclerosis) complications.
147. Two main types (Type 1, or insulin-dependent diabetes
mellitus [IDDM], and type 2, non-insulin-dependent diabetes
mellitus [NIDDM]) and a number of secondary types are
distinguished [H36, N14]. Additionally, over 60 Mendelian

ANNEX: HEREDITARY EFFECTS OF RADIATION

29

syndromes and some mitochondrial mutations have been
described that are associated with glucose intolerance and insome cases, clinical diabetes mellitus; roughly one third of
the Mendelian syndromes are associated with IDDM or
glucose intolerance and the remainder with NIDDM or
insulin resistance [B40, O8, R19]. All these contribute to thegenetic heterogeneity of diabetes mellitus.

where a family member is affected. On the basis of anumber of such studies, Rotter et al. [R19] estimated thatthe empirical recurrence risk to the sibling of an IDDM
patient is of the order of 5%!10% and the risk to offspring
is about 2%!5%. Further, the risk to offspring of fatherswith the disease (4%!6%) is about twice that to offspringof mothers with the disease (2%!3%).

148. It has been estimated that 35%!45% of long-term
diabetics will develop clinical nephropathy, which is known
to occur in all forms of diabetes (e.g. [V16]). Hypertension
is another independent risk factor for nephropathy; it is
twice as prevalent in diabetic as in non-diabetic subjects(e.g. [E7, N13]). Diabetic retinopathy is a complication ofdiabetes (e.g. [R22]). Clinical diabetes has long been
known to be an independent risk factor for macrovasculardisease, and the latter accounts for at least 50% of alldeaths of diabetics (e.g. [J8, L33]).

153. In a population-based study of young twins in Denmark (n = 20,888), Kyvik et al. [K37] found that the crudeconcordance rate for IDDM was 53% for monozygotic
twins and 11% for dizygotic twins. When adjusted for age
at onset of diabetes and age at last observation among
unaffected twin partners, the cumulative risk from birth toage 35 years was estimated to be 70% and 13% for monoand dizygotic twins, respectively. The overall conclusionfrom these and other studies not reviewed here is that not
everyone with a genetic predisposition to IDDM develops
the disease.

(a) Insulin-dependent diabetes mellitus
149. IDDM is a chronic autoimmune disease characterized
by low or absent circulating insulin levels as a result, at the
final stage, of the complete destruction of the insulinsecreting cells (the β cells in the pancreas), pancreatic islet
cell antibodies, and episodes of ketoacidosis. The patientpresents with signs of insulin deficiency, although thepathological process leading to this may predate clinicalpresentation by 10!15 years. When the disease is fully
developed, the patients require exogenous insulin forsurvival.
150. Epidemiology. In the United States, it is estimatedthat about 5%!10% of all diabetics are of type 1 (i.e. about
12!14 per 100,000 in children 0!16 years of age). The
worldwide incidence is accurately known only for about
2% of the world population: the estimated incidences range
from a low of less than 1 per 100,000 children in Japan tomore than 25 per 100,000 in Scandinavia; the figure for
Finland is especially high, about 35 per 100,000. Most
incidence estimates fall in the range 6!15 per 100,000[K35, K36, R19].
151. Risk factors. The main defined risk factor for IDDM
is genetic susceptibility. However, as discussed below, theobservations that the concordance in monozygotic twins isless than 50% suggest that environmental factors may be
important. Because of the potentially long natural history of
IDDM, the roles of specific environmental factors remaindifficult to delineate. These may function as initiating
factors (i.e. they begin or continue the aetiologic processes
that eventually terminate in IDDM) or precipitating factors(i.e. they convert preclinical diabetes into overt clinicaldisease). It is clear, however, that these factors must act on
genetically susceptible individuals.
152. Family and twin studies. Most patients who develop
IDDM have no family history of the disease, and only
10%!15% of them know of an affected relative. The risk ofdeveloping IDDM, however, is clearly increased in families

154. Genetics. Among Caucasian patients, the strong andconsistent association of IDDM (but not NIDDM) withleukocyte human antigen (HLA) has long been known andremains an active area of research (reviewed in [S71]). The
HLA class II region contains at least three genetic loci,namely, HLA-DR, HLA-DQ, and HLA-DP. They are highly
polymorphic (i.e. many alleles are known) (reviewed in[H36 R19]). IDDM is associated with the HLA-DRB,-DQA, and -DQB alleles. The relative risk for IDDM inindividuals who have both DR3 and DR4 is greater thanthose homozygous for either DR3 or DR4. Analysis of DR
and DQ in a population-based study using several statisticalmethods identified DR4 as having a lesser risk than DQ8,
and DR3 as having a higher risk than DQ2 [K39]. In
Caucasians, DQ8 is the most prevalent haplotype, detected
in 74% of Swedish patients, followed by DQ2 in 52%[S71]. The DR2 haplotype is strongly negatively associatedwith IDDM [R21].
155. An association between IDDM and a polymorphic
region in the 5' flanking region of the insulin gene (INS) on
chromosome 11p15.5 has been known for some time (e.g.
[B42]). However, several studies, while establishing that
the INS gene region (19 kb) contains an important genetic
susceptibility locus, failed to demonstrate linkage of thesealleles to IDDM in families (e.g. [B43, J9]). This is partly
because the putative disease-associated allele is present at
a high frequency in the general population.
156. Lucassen et al. [L32] made a detailed sequencecomparison of the predominant haplotypes in the INS generegion in a population of French Caucasian IDDM patientsand controls and narrowed the region of susceptibility to a
4.1-kb segment of DNA spanning the INS gene andassociated 5' VNTR region (VNTR: Variable Number of
Tandem Repeats). They were able to show that 10
polymorphisms within this region are in strong linkage
disequilibrium with each other and extend across the INS
gene and the VNTR situated 365 bp 5' to it. The putative
locus in this region was designated IDDM2, and it has been

30

UNSCEAR 2001 REPORT

suggested that it might account for about 10% of thefamilial clustering. The “mutation” has now been mapped
within the VNTR itself [B44, K40].
157. Finally, a genome-wide search for IDDM-susceptibility
genes [D15, M38, T21] and other studies [H36] have shown
that, in addition to IDDM1, which accounts for a large
proportion of familial clustering, and IDDM2, there are atleast 10 other loci on nine chromosomes. Further, it appears
that IDDM1 and IDDM2 function epistatically(multiplicatively), whereas IDDM1 and IDDM4 may act
independently, although this may depend on the geographicalorigins of the families studied [M38].
158. Summary. IDDM is a group of heterogeneous
diseases probably resulting from exposure to someenvironmental agent(s) of individuals with a geneticallydetermined susceptibility. The disease is the result of thedestruction of insulin-producing β cells of the pancreas,
principally by immunologically mediated (autoimmune)mechanisms. The main defined risk factor is genetic
susceptibility, and apart from IDDM1 (linked to the HLA
complex) and IDDM2 (in the insulin gene region), at least
10 other genes are involved, mutations in which cause
susceptibility to IDDM. Some of these genes may act
independently, while others act epistatically.
(b) Non-insulin-dependent diabetes mellitus

161. Family and twin studies. Family and twin studies
have long suggested a strong familial component forsusceptibility to NIDDM. From published data, Rotter et al.
[R19] estimated that the empirical recurrence risk for firstdegree relatives of NIDDM is of the order of 10%!15% forclinical NIDDM and 20%!30% for impaired glucose
tolerance. This increased risk appears to be only for NIDDM
and not for IDDM. For most cases of maturity onset diabetesof the young (MODY), i.e. those in whom it is an autosomal
dominant disease, the risk to siblings and offspring is 50%.
162. Studies of twins demonstrate high concordance rates(55%!100%) for NIDDM in monozygotic twins [B41, P27],
although lower rates (such as 40%) have also been recorded[K38]. In any case, these rates are higher than those for
IDDM. However, studies of migrants and of populations
from developing countries indicate that the environmental
and lifestyle changes that accompany westernization
promotes NIDDM in those who are genetically susceptible[R19]. The current view is that NIDDM, like IDDM, is also
genetically heterogeneous.
163. Genetics. In most population groups, NIDDM shows
no association with HLA antigens [B45, R19]. MODY, arare subtype of NIDDM, is an autosomal dominant formand has early onset (before age 25 years), although family
members may be diagnosed at older ages [B44, F25, V17].
MODY has been found to occur in about 13% of Caucasian
NIDDM families studied in France [F26].

159. NIDDM is characterized by a relative disparity
between endogenous insulin production and insulin
requirements, leading to an elevated blood glucose. In
contrast to IDDM, there is always some endogenous insulin
production, and many NIDDM patients have normal oreven elevated blood insulin levels. Hyperinsulinemia andinsulin resistance are characteristic of NIDDM patients[R19]. NIDDM occurs usually, but not exclusively, in
persons over the age of 40 years. Approximately 60% of
the patients are obese. It is the more common form of
diabetes mellitus in Caucasian populations.

164. In a small subgroup of NIDDM presenting withhyperglycemia, hyperinsulinemia, and yet a normal
responsiveness to exogenous insulin, autosomal dominantpoint mutations in the insulin gene (INS) have been found(reviewed in [M1]). Important to note here is that in a
population of NIDDM patients screened for mutant insulin,
fewer than 0.5% were found to have such mutations [S72].
Likewise, known gene defects in the insulin receptor gene
(INSR on chromosome 19p13.3) are rare and associatedwith rare syndromes of severe insulin resistance [M1].

160. Epidemiology. It is estimated that between 500,000
and 600,000 persons in the United States become diabetic
each year. While the overall incidence of NIDDM in the
United States is estimated to be around 32 per 100,000 forages of 20 years or more, the actual incidence is difficult todetermine, owing to the mild onset of the disease in someindividuals and the estimated high proportion ofundiagnosed cases [R19]. In terms of prevalence, it isthought that 4%!5% of the population in the United States
aged 20!74 years have NIDDM and an additional 4%!11%
have impaired glucose tolerance [H36]. In the United
Kingdom, at least 3% of the middle-aged and elderly
population have NIDDM [P26]. The rates are higher among
the very elderly. The lowest prevalence rates (<2% of
adults) are recorded among Inuits, Alaskan Athabascan
natives, Japanese, Chinese, and Indonesians and the highest
known prevalences are among the Pimas, other native
American groups, and Pacific Islanders (as high as 60%)
[K35, R19].

165. Mutations in the GCK1 gene appear to be the mostcommon in MODY in France and are present in 56% of thefamilies [F11, V17] (see also [S74]). There is someevidence that the GCK1 region may also be important inmore common forms of NIDDM. There is a simple tandemrepeat polymorphism roughly 10 kb 3' to GCK1. In AfricanAmericans, in whom the prevalence of NIDDM is relatively
high, Chiu et al. [C42] found a statistically significant
association between NIDDM and one of the PCR-definedalleles, suggesting the involvement of GCK region in"ordinary" NIDDM in a proportion of the cases. However,no mutations in the coding region of the gene were found[C43]. In three other populations, Mauritian Creoles,
southern Indians, and elderly Finnish men, GCK was
positively associated with NIDDM [C42, C44, M39, M40].
In some other population groups, however, there was nosuch association [H36]. Finally, Hanis et al. [H17] reported
the results of a genome-wide search for NIDDM genes in
408 Mexican-Americans from Starr County, Texas. The

ANNEX: HEREDITARY EFFECTS OF RADIATION

important finding was that one of the 490 molecularmarkers, D2S125 on chromosome 2 (band 2q37), showedsignificant evidence of linkage to NIDDM.
166. Summary. NIDDM is a very common disease whose
main determinant in Western countries is genetic susceptibility. Compared with insulin-dependent diabetes mellitus,
the concordance rates in monozygotic twins and risks tofirst relatives (of those afflicted) are higher. With the
exception of the subtype of diabetes with earlier onset, mostcases have onset in middle or late life. The known geographical variations in the prevalence and studies of
migrant populations suggest that environmental factors
might also be important.
167. The number of genes in which mutations cause
susceptibility to NIDDM is not yet known. No major genehas yet been identified, although several candidate genes
are currently being investigated. Rare forms such as
MODY are due to dominant genes, and still rarer forms
with abnormal insulin production are due to mutations in
the insulin gene itself.

4. Essential hypertension
168. Hypertension is a pathological elevation of bloodpressure level. An individual is diagnosed as having highblood pressure when repeated measurements show systolicblood pressure is higher than 140 mm Hg or diastolic bloodpressure is higher than 90 mm Hg. Blood pressure is a continuously distributed trait with no intrinsic break at the upper
end of the scale. In the recently revised system recommended
by the Joint National Committee for Detection, Evaluation
and Treatment of High Blood Pressure in the United States[J10], optimal blood pressure is defined as a systolic level<120 mm Hg and a diastolic level <80 mm Hg; theclassification scheme is shown in Table 24. Among the fourstages of hypertension, stage 1 is the most common (80%)
and stage 4 is the least common [W23].
169. The clinical importance of hypertension stems fromthe fact that it is an important risk factor in the developmentof cardiovascular and renal diseases, specifically stroke,atherosclerosis, coronary heart disease, congestive heart
failure, and renal failure [A13, B50, C54, K45, W25]. The
cut-off points for identifying hypertension are arbitrary andchosen for their operational suitability in clinical practice(i.e. to define the level of blood pressure at which risks for
cardiovascular and renal diseases become worrisome and to
facilitate therapeutic decision-making and preventive
efforts) and do not reflect a clear biological distinction
between hypertension and normotension.
170. Epidemiology. Estimates of the prevalence ofessential hypertension in the population vary considerably,
depending on the cut-off points chosen and the methods ofmeasurement, and they are influenced by population
characteristics such as age, gender, race, and socioeconomic status [E15, M43]. Surveys of industrialized31

societies show that the prevalence in the general population
is of the order of 10%!25% (see Table 10!2 in Burke andMotulsky [B50]). In the 1988!1991 National Health andNutritional Examination survey, which used the criteria in
Table 24, the prevalence in the general population of theUnited States varied from 4% in those aged 18!29 years to
65% in those older than 79 years [B51, W23]. The overall
pattern of age-related increases in blood pressure has beenfound in a number of population studies in industrializedcountries [E15, W23].
171. It is instructive to note that essential hypertension ispractically non-existent in several populations or populationgroups from a variety of national backgrounds, including
Malaysians, Polynesians, Australian aborigines, Central andSouth American natives, and Inuits [C52, E15, M43, P28].
In these populations, there is as well no normal rise inblood pressure with age, as is seen industrialized
populations. Ethnic differences in blood pressure have been
extensively studied in African-Americans and whites ofnorthern European origin; in the former group, elevatedblood pressure is evident in all age groups and across therange of blood pressure values; these data have beenreviewed [B50, K47, M45].
172. Risk factors. Both genetic and environmental factors
play important roles in the development of essential
hypertension and its sequelae (e.g. [B50, M44, W26]).
Among the environmental factors are common life-stylerelated factors such as high body weight and central obesity(which itself has genetic determinants), sodium intake that
greatly exceeds physiological needs, excessive consumptionof alcohol, insufficient physical activity, and stress. Further,abnormalities of glucose, insulin, and lipoprotein metabolism are common among patients with essential hypertension. It has been hypothesized that these metabolic
abnormalities may play a role both in the pathogenesis andcomplications of essential hypertension in many patients[R24].
173. Family and twin studies. Family studies in various
populations document familial aggregation of blood pressure
at all levels of blood pressure and across all age groups; both
genetic and environmental factors contribute to this familial
aggregation [B50, C51, C54, S77]. Most frequently, thesestudies have estimated blood pressure correlations forindividuals paired according to their biological relatedness.
While the magnitude of these correlations (r) varies from study
to study, in general the closer the biological relationship, thehigher the correlation (see Table 10!4 in Burke and Motulsky[B50]). Some representative values of correlation coefficientsdetermined in family studies of hypertension are shown in
Table 25. Note that the correlations are slightly higher forsystolic blood pressure than for diastolic blood pressure. The
wide range in correlations recorded in the different studies may
in part stem from genetic heterogeneity as well as the manyenvironmental factors that affect blood pressure (e.g. [A14,
L39, M47, P29]).

32

UNSCEAR 2001 REPORT174. Genetics. At present, four rare Mendelian syndromes
associated with essential hypertension are known: glucocorticosteroid-remediable aldosteronism (GRA), Liddle
syndrome (or pseudo-aldosteronism), pseudoaldosteronism
type II (Gordon syndrome), and the syndrome of apparent
mineralocorticosteroid excess (AME). Glucocorticosteroidremediable aldosteronism is an autosomal dominant disorder that has been shown to be due to a chimeric gene
duplication resulting from unequal crossing-over between
aldosterone synthase gene and steroid 11β-hydroxylase
gene [L36, L37]. Only 51 cases have been reported
worldwide. Liddle syndrome is also autosomal dominant
and is due to mutations in the β or γ subunit of the geneencoding the epithelial sodium channel (SCNN2, SCNN3)[S76]; only 50!60 cases have been reported worldwide.
Apparent mineralocorticosteroid excess is autosomal
recessive and is due to mutations in the renal isozyme of
11β-hydroxysteroid dehydrogenase gene; only about 25
cases have been reported worldwide [M48]. The genetic
basis of Gordon syndrome is not known.
175. A number of genes whose biological function makes
them logical candidates or markers for blood pressure
homeostasis have been studied in recent years (reviewed in[H41, L35, T22]). Among these are loci coding for therenin-angiotensin system, RAS, involving the REN, ACE,
AGT, and AT1 loci (this system plays a vital role in kidney
function and renal homeostasis, and hence in blood pressure
regulation, and is also a target system for antihypertensive
agents), sodium-hydrogen exchanger isoform 1, kallikrein,
estrogen receptor, and the SAH gene (rat hypertensionassociated homolog).
176. The ACE locus. The evidence from studies in
Caucasians on the possible influence of variants at the ACE(angiotensin-converting enzyme) locus on blood pressure
has been either negative or equivocal [S78, T22], in
contrast to the situation recorded in rats [H42, J11, O9].
Likewise, an insertion/deletion (I/D) polymorphism in
intron 16 of the ACE gene was found to be associated withdifferent levels of circulating ACE; those with the D/D
genotype had twice the level of ACE as the I/I genotype,whereas those with I/D genotypes had intermediate levels[T23], but these differences did not correlate with bloodpressure levels [J12]. However, in a cohort of 52
hypertensive and 37 normotensive African-Americans, thefrequency of the ACE deletion allele was found to behigher in hypertensives than in normotensives [D22].
Additionally, the stratification of hypertensives in different
age groups by Morris et al. [M46] revealed a marked andselective decrease in the frequency of the ACE D/D
genotypes with age.
177. There is some evidence that certain ACE locus
genotypes may increase the risk of myocardial infarction[C50, L40]. In a study of a group of 316 unrelated patientswith NIDDM (132 of whom had a myocardial infarction orsignificant coronary stenosis), the D allele was found to bea strong risk factor for coronary heart disease [R25].

178. The AGT locus. In contrast to the studies mentioned
above, the evidence on the role of variants at the AGT locus(which encodes the renin substrate angiotensinogen) in
essential hypertension is more substantial. In two large
cohorts (Paris and Salt Lake City) of Caucasian
hypertensive sib pairs (involving a total of 379 sib pairs),
Jeunemaitre et al. [J13] obtained evidence of linkage
between a GT dinucleotide polymorphism in the 3' flanking
region of the AGT gene and essential hypertension. Thisobservation prompted the search for molecular variants in
the AGT gene that might be causal in the pathogenesis ofessential hypertension. Two such variants, Thr1746Met andMet2356Thr, were found to be significantly more frequent
in all hypertensive cases than in normotensive controls. The
frequencies were Thr1746Met: controls 9%, all index cases
14%, and more severe index cases 17%; and Met2356Thr:
controls 36%, all index cases 47%, and more severe index
cases 51% (see also [C53, F31, H40]).
179. The AT1 locus. In a case-control study of 206 white
hypertensives and 298 normotensives, Bonnardeaux et al.
[B57] identified five polymorphisms in the AT1 genesequence, two in the coding region, and three in the 3'
untranslated region. Only the allele frequency of theA11666C nucleotide variant was found to be increased in
hypertensive patients (36% vs. 28%).
180. Hypertension and risk of stroke and coronary heartdisease (CHD). Stroke is a heterogeneous disorder thatencompasses cerebral infarction (ischaemic stroke being themost common type), intracerebral haemorrhage, and subarachnoid haemorrhage. Epidemiological studies haverepeatedly documented the thesis that essential hypertension is an important and independent risk factor forstroke and coronary heart disease [B55, D21, M44, P30]. In
the multiple risk factor intervention trial (MRFIT), in which
350,977 men were screened and given a six-year follow-up,
the main risk factor for mortality was stroke; about 40% of
strokes could be attributed to systolic blood pressure ofmore than 140 mm Hg [I10, R26].
181. MacMahon et al. [M42] summarized data from nineprospective observational studies involving 418,343 adults
aged 25!70 years. None of these individuals had a historyof coronary heart disease or stroke when the study began.
They were followed for an average of about 10 years. The
difference between the highest (105 mm Hg) and lowest(76 mm Hg) stratum of diastolic blood pressure was only
30 mm Hg. However, even within this narrow range, therisk of stroke was more than 10 times higher and that ofcoronary heart disease nearly five times higher for those in
the highest (compared with the lowest) stratum of mean
overall diastolic blood pressure during follow-up. These
data suggest that a 5!6 mm Hg lower level of diastolicblood pressure is associated with a 20%!25% lower risk ofcoronary heart disease.
182. The risk of mortality from coronary heart disease
increases as systolic blood pressure increases. In the
MRFIT, which involved 347,978 men, the risk of mortality

ANNEX: HEREDITARY EFFECTS OF RADIATION

from coronary heart disease clearly increased with
progressively higher levels of systolic blood pressure;compared with those in the lowest stratum of systolic bloodpressure (>110 mm Hg), individuals in the highest stratum($180 mm Hg) had a 5.65-fold higher risk [S79]. Further,less than a quarter of the cohort had hypertension(n = 82,347), but this group accounted for more than two
thirds of the excess risk of coronary heart disease mortality
related to excess systolic blood pressure. Additionally, therisk of high blood pressure was substantially increased by
the presence of other risk factors; for example, in the
MRFIT, there was a big difference in risk between those
who were smokers and others in the upper quintiles forboth blood pressure and serum cholesterol.
183. Hypertension and the risk of congestive heart
failure and end-stage renal disease. In a 34-year followup of the Framingham Heart Study Cohort, Kannel andBelanger [K46] found that the risk of congestive heart
failure was 2!4 times higher for those in the highest thanfor those in the lowest quintile of blood pressure at entry
into the study. Similarly, for an average of 15.3 years
follow-up of 361,639 individuals screened in the MRFIT
study, after adjusting for other concomitant variables (age,race, cigarette smoking, serum cholesterol concentration,
treatment for diabetes, previous myocardial infarctions, andincome), the estimated risk of end-stage renal disease rosewith an increase in systolic blood pressure.
184. Summary. Essential hypertension is a common
multifactorial disease affecting some 10%!25% of the
population of industrialized countries. Its clinical relevancestems from the fact that it is one of the major risk factors
for cardiovascular and renal diseases, especially stroke,coronary heart disease, and end-stage renal disease. The
role of genetic factors in essential hypertension is madeclear by family studies in which correlations in bloodpressure levels have been studied. The coefficients ofcorrelations are in the range of 0.12!0.37 for sib-sib andparent-child relationships, rising to about 0.55!0.72 formonozygotic twins. The variations in the range andmagnitude of these correlations, however, suggest thatenvironmental factors must play an important role, varying
from individual to individual and population to population.
185. As in the case of NIDDM, no important genes
controlling blood pressure have been identified, and atpresent it is difficult to estimate the number of genes
involved. However, during the past five years or so, linkage
and association studies have shown that there are at least
three gene loci (AGT, AT1, and ACE) at which polymorphism contributes to essential hypertension; however,
the relative proportion of hypertensives in the populationthat each of these accounts for remains to be determined.
Additionally, the molecular basis of three rare Mendeliandisorders associated with hypertension, namely those
involved in glucocorticosteroid-remediable aldosteronism,
Liddle syndrome, and apparent mineralocorticosteroid
excess have been delineated.

33

5. Coronary heart disease186. Cardiovascular diseases occupy the number one
position in the morbidity and mortality statistics in mostindustrialized countries of the world. Among these, coronary
heart disease constitutes the predominant group, accounting
for roughly one half of all cardiovascular deaths. The terms
coronary heart disease, ischaemic heart disease, and coronary
artery disease are more or less synonymous; they all result
from atherosclerosis, the obstruction of blood flow throughthe arterial network, when the vessels that nourish the heart
muscle are affected by the formation of fibrous tissue called
atheromatous plaque. Clinical symptoms of atherosclerosis
do not usually occur until over half of the lumen becomes
obstructed (occluded) by the plaque, typically in the fifth andsixth decades of life. Among the clinical manifestations ofcoronary heart disease are congestive heart failure, conduction defect, arrhythmia, angina pectoris, and myocardial
infarction.
187. Epidemiology: mortality profiles. The death rates
from coronary heart disease and their trends in time vary
widely in different parts of the world (e.g. [H47, W21]).
Until the 1960s, the trend in mortality from coronary heartdisease was generally upward in industrialized countries
and was more pronounced for men than for women. During
the 1960s and 1970s, a peak was reached, followed by adownward trend in many countries, although in somecountries such as Poland and Hungary increases have beenregistered during the last decade.
188. In the United States, more than 300 deaths per 100,000
were observed in the mid-1960s. Since that time, themortality has been declining at 2%!3% per year, with alessened rate of decline in recent years. In the late 1980s,
about 27% of deaths were due to coronary heart disease, and
it is still the principal cause of death. Finland has the highest
mortality rate from coronary heart disease and Japan thelowest. The death rates from coronary heart disease in 1977
ranged from 878 per 100,000 for Finnish men aged 35!74
years to 103 per 100,000 for Japanese men [S79]. The
reported figures in general are higher in countries consuminga Western diet and lower in countries where the consumptionof fat and cholesterol is low [M50, S85].
189. The importance of environmental factors is also
indicated by studies of migrants. When individuals fromJapan migrated to Hawaii, their coronary heart diseasemortality rate doubled, and when they emigrated to theUnited States mainland, it tripled [R35]. Similar changes
were noted for Irish immigrants in Boston compared withthose who stayed in Ireland [K52]. Among the various
immigrants, the rates became nearly similar to those in theiradopted countries within 10!20 years.
190. Risk factors. Current evidence documents thepremise that positive family history, high low- density
lipoprotein (LDL), and low high-density lipoprotein (HDL)
cholesterol levels (separately as well as jointly), high ApoB
levels (the main protein fraction of the LDL particle), high

UNSCEAR 2001 REPORT

34

Lp(a) (lipoprotein(a)) levels, high levels of plasma
fibrinogen concentration, hypertension, diabetes, highdietary fat intake, obesity, increased levels of homocysteine(all these themselves have genetic determinants), lack of
exercise, stress, and smoking are important risk factors (e.g.
[B59, D25, H37, H50, K49, K51, N15, R28, S82, U15]).
191. Family and twin studies. Familial aggregation ofcoronary heart disease has long been known (reviewed in[B58, M53]). First-degree relatives of affected patients
have about a 2!6-fold higher risk of the disease thanmatched controls. The familial aggregation increases withdecreasing age of the affected patients. While women havea lower frequency of coronary heart disease than men, thefirst-degree relatives of index women run a higher risk thanthose of affected index males.
192. Twin studies (reviewed in [B58]) have demonstrated
that the concordance rates for monozygotic twins are higher
than those for dizygotic ones. The estimates formonozygotic (MZ) and dizygotic (DZ) twins in Denmark
were 39% and 29% for males and 44% and 14% forfemales. The corresponding figures for twin pairs in
Sweden were 48% and 28%. In a study in Norway, the con-cordance rates for angina pectoris and/or myocardial
infarction were 0.65 for monozygotic and 0.25 for dizygotic
twin pairs; if only twins with premature coronary heartdisease appearing before the age of 60 years were included,
these figures were 0.83 and 0.22, respectively. Some
representative data on odds ratios from family and twin
studies are summarized in Table 26.
193. Total cholesterol levels. It is now well known that,first of all, variation in cholesterol concentrations in a
population is determined by both genetic and environmental
factors and that the mean and the normal range of total
plasma cholesterol levels vary in different populations.
Secondly, as the total concentrations increase throughout
the range observed in the population at large, there is amarked increase in the risk of developing coronary heartdisease, i.e. the majority of coronary heart disease occurs inindividuals with cholesterol levels that are distributed near
the mean of the population, the coronary heart disease risk
being graded and continuous without a threshold; only asmall fraction of the disease burden is associated withelevated cholesterol levels that are discretely separate fromthe so-called normal range of variability. Figure IV
illustrates these points.
20

>280

150

100

50

DISTRIBUTION (%)

200

15

10

5

<180

INCIDENCE (per 10,000)

250

0

0
120 160 200 240 280 320 360 400

120 160 200 240 280 320 360 400

SERUM CHOLESTEROL [mg (100 ml)-1]

SERUM CHOLESTEROL [mg (100 ml)-1]

Figure IV. The relationship between the distribution of total
serum cholesterol and incidence of coronary heart disease.
The data are from the Framingham Massachussetts survey formales of 30-39 years of age. Incidence is for 10 years of follow-up.

194. Cholesterol, plasma lipids, and lipoproteins. Very
early studies of the atherosclerotic plaque, which were shown
to be deposits of cholesteryl esters, focussed attention on themetabolism of plasma lipids. The main plasma lipids arecholesteryl esters and triglycerides. The plasma lipids aretransported as complexes with other lipids and proteins called
lipoproteins. The lipoproteins are spherical particles with acoat consisting principally of phospholipids and proteins
called apolipoproteins and a core that contains varying
proportions of triglycerides and cholesteryl esters.
195. The main classes of apolipoproteins of particularinterest for the aetiology of coronary heart disease arechylomicrons, very low-density lipoproteins (VLDL),intermediate-density lipoproteins (IDL), LDL, and HDL.
These designations are based on their buoyant density andultracentrifugation profiles (reviewed in [B62, B64]). Someof their properties and the associated apolipoproteins are
summarized in Table 27. Not shown in this Table is theclass of lipoproteins designated as Lp(a), which was
originally discovered by Berg [B60]. Subsequent work
using quantitative immunochemical methods showed that
the Lp(a) concentration is a quantitative genetic marker
whose concentration can vary greatly between individuals(from near zero to over 1,000 mg dl1) [S83]. The Lp(a)particle has a lipid composition that is nearly identical to
LDL, and like LDL, it contains a single copy of apolipoprotein B-100. However, unlike LDL, it also contains a
glycoprotein called apo(a). Lp(a) is highly homologous toplasminogen, and the latter is a member of a protein superfamily composed of regulatory proteases of the fibrinolytic
and blood coagulation systems [E16, M51].

ANNEX: HEREDITARY EFFECTS OF RADIATION

196. Genetics of lipoprotein and other lipid-related genes.
Lipoprotein levels are determined by genes that code forproteins that regulate lipoprotein synthesis, interconversions, and catabolism (e.g. [B62, B64]). These include
the apolipoproteins A1, A2, A4, B, C1, C2, C3, D, E, andapo(a); the lipoprotein- processing proteins lipoprotein
lipase, hepatic triglyceride lipase, lecithin cholesteryl acyltransferase, and cholesteryl ester transfer protein; and thelipoprotein receptors LDL receptor, chylomicron remnant
receptor, and scavenger receptor. Most of these genes havebeen isolated, sequenced, and mapped in the human genome.
197. Mutations in the genes mentioned above may cause
disturbances in one or more of the pathways in lipoprotein
metabolism, resulting in hyper- or, less commonly, hypolipoproteinaemia. Some of these disorders lead to prematureatherosclerosis. Such conditions fall into two main groups,
those due to rare single-gene mutations having large effects(major gene effects) and those due to mutations in several
different genes, each having small to moderate effects (polymorphisms).
198. Major gene effects. The classic example of major
gene effects in hyperlipidaemia is familial hypercholesterolaemia (FH). This is an autosomal dominant trait with apopulation frequency in heterozygotes of 1 in 500. The
pioneering studies of Goldstein and Brown [G17],
Goldstein et al. [G18], and Brown and Goldstein [B65]established that the basic defect concerns the LDL
receptors. FH heterozygotes have levels of circulating LDLthat are twice normal, and these people begin to havemyocardial infarctions as young as age 30 years. The levelof circulating LDL in homozygotes is 6!10 times higher
than the normal level. Although mutations in such genes areimportant for those individuals who carry them, they haveless importance for the population at large.
199. The second example is hyperlipidaemia due tofamilial defective ApoB-100, which is also an autosomal
dominant trait. This is caused by a mutation leading to a
defect in the ligand, interfering with the binding of apoB to
LDL receptor. The mutation is (CGG to CAG; arginine toglutamine) at codon 3500 of the apoB gene. Affectedpatients are heterozygotes, and unlike in FH due to LDLR
mutations, no homozygotes have yet been reported. Studies
among United States and European whites suggest afrequency of around 1 in 500 to 1 in 700, similar to that of
FH [I11, S84].
200. Polymorphisms. The group known as polymorphisms
includes conditions due to many genes that are polymorphic
in the population and for which the alleles have moderate
effects. The contribution of such polymorphic loci to total
genetic variation is large, and interaction between these andenvironmental factors is probably the commonest cause of
hyperlipidaemia in the population. Of these, the impact ofpolymorphism at the apoE locus on cholesterol levels has
been the subject of extensive studies (reviewed by
Davignon et al. [D23]).

35

201. ApoE. ApoE is a key protein in the modulation of themetabolism of the highly atherogenic apoB-containing
lipoproteins. The ApoE gene is polymorphic: three common
alleles designated ε4, ε3, and ε2 determine six genotypes:
three homozygous (ε4/ε4, ε3/ε3, and ε2/ε2) and threeheterozygous (ε4/ε3, ε3/ε2, and ε4/ε2). The corresponding
plasma phenotypes are inherited in a co-dominant fashion
and are designated as E4/4, E3/3, E2/2, E4/3, E3/2, and E4/2.
202. The relative frequencies of the ApoE alleles and theirimpact on apoE, as well as on total cholesterol, HDL
cholesterol, triglyceride, and apoB levels, have been studied
in a number of populations (see Table 1 in Davignon et al.
[D23] and the references cited therein). The findings fromthe above and other studies of particular importance in thepresent context are as follows: (a) ε2/ε2 genotypes had thelowest average levels of total cholesterol, while individuals
with the ε4/ε4 genotypes had the highest average levels; (b)the rank of genotype means was ε2/ε2 <ε3/ε2 <ε3/ε3 <ε4/ε4in every study; and (c) on average, a single ε4 allele raises
the total cholesterol level by about 7 mg (100 ml)1,
whereas the ε2 allele lowers it by about 14 mg (100 ml)1(Table 28).
203. The average effects on plasma cholesterol level forany given individual can be roughly predicted from the
ApoE genotype and can be considerable. Thus in the Nancy(France) series, the average cholesterol level for the ε2/ε2
homozygotes was 199 mg (100 ml)1 and that for the ε4/ε4genotypes was 240 mg (100 ml)1. The highest ε4 allele
frequency (0.226) is observed in Finland, where the highest
cholesterol levels and coronary heart disease mortality havebeen observed. Thus, a small but definite proportion(6%!14%) of the variability in total cholesterol levels canbe ascribed to ApoE polymorphism. In principle, therefore,
ApoE-related differences in cholesterol levels could betranslated into significant variation in coronary heartdisease frequencies, although in some populations, theApoE genotypes did not perfectly correlate with coronary
heart disease rates (see Davignon et al. [D23] and Motulsky
and Brunzell [M53] for details and references).
204. ApoE polymorphism and Alzheimer’s disease. The
ApoE polymorphism discussed above has also been shown
to be an important risk factor for late onset familial cases of
Alzheimer’s disease (FAD). The important finding was thatthe ε4 heterozygotes had a threefold increase in risk ofdeveloping FAD, and the ε4 homozygotes had an eightfold
increase in risk of developing the disease (to a nearcertainty) by the age of 75 years [C58, C59, S86, S87]. The
association of the ε4 allele with FAD has been confirmed
in family studies, clinical case series, and population-basedseries. At least in some studies, there is evidence that the ε2allele may be associated with a decrease in the risk ofdeveloping the disease and with a later onset age [H45].
205. ApoB. Since apoB is the principal constituent of LDL
cholesterol, there are strong correlations between levels of
total cholesterol, LDL cholesterol, and apoB [A15]. The
rare mutation in the apoB gene underlying familial

36

UNSCEAR 2001 REPORT

defective apoB-100 has already been mentioned. Population
association studies have uncovered a few generally
confirmed associations of DNA variants at the apoB locus
with apoB levels. For example, an RFLP at the 3' end of the
apoB gene is detectable using the restriction enzyme XbaI.
The allele lacking the Xba site (i.e. the X-allele) was foundto be associated with reduced levels of total cholesterol,
LDL, apoB, and possibly triglycerides. Paradoxically, thesame allele has been reported to be more common insurvivors of myocardial infarction and patients withcoronary heart disease [B25, B23]. Bohn and Berg [B23]concluded that the (X! X!) genotype confers increased riskof myocardial infarction but is probably not mediatedthrough lipids and apolipoproteins and is unrelated to theeffects of polymorphisms on lipid levels.
206. ApoA1-C3-A4. Low HDL level is a strong risk factor
for coronary heart disease. Because the product of the
ApoA1 gene plays an important role in HDL formation andfunction, a number of studies have addressed the questionof genetic mechanisms. Several epidemiological studies
have reported that the levels of both HDL cholesterol andapoA1 are inversely related to the incidence and severity ofcoronary heart disease and can independently predict therisk of the disease [L42, R29]. Various environmental
factors have been identified that affect plasma HDL levels,
including steroid hormones, alcohol intake, stress, infection,amount of exercise, body mass index, some drug therapy(such as β-blockers), and smoking. Despite this large
contribution of environmental factors, the heritability of HDLcholesterol and apoA1 is in the range of 0.43 to 0.66 [H46].
A strong genetic effect on levels of HDL cholesterol andapoA1 has been demonstrated in twin and family studies[A11, H44]. Recent evidence points to the possibility thatgenetic variation in hepatic lipase activity may be an
important determinant of plasma HDL cholesterol levels[G16].

to the view that for cholesterol variability in the population
at large, the polygenic variance may be attributed to fewer
loci with moderate effects than is generally assumed by theclassic biometrical models, which include a very large
number of loci, each with small additive effects.
209. Apo(a). The observations that the plasma levels ofLp(a) vary widely among individuals and the possibility
that Lp(a) may be an important (perhaps an independent)
risk factor for coronary heart disease were mentioned
earlier. In reviewing many studies, Berg [B47] concluded
that all carefully conducted retrospective and prospective
studies confirm that high Lp(a) levels constitute an
independent risk factor for coronary heart disease and an
additional risk factor for coronary heart disease patientswith familial hypercholesterolemia. High Lp(a) levels havebeen implicated in the aetiology of cerebrovascular disease.
210. The discovery that Lp(a) is highly homologous toplasminogen (from which the enzyme plasmin, which dissolves fibrin blood clots, is released by tissue plasminogenactivator) and the identification of the apo(a) locus that
determines plasma Lp(a) levels [M51] provided theconceptual link between plasma lipids and atherogenesis on
the one hand and thrombogenesis on the other. There is ahigh degree of allelic heterogeneity at the apo(a) locus,
with more than 20 common alleles having been identified[K48, L41]; each allele determines a specific number ofmultiple tandem repeats of a unique coding sequenceknown as Kringle 4 (a unique pretzel-like structure
reminiscent of a Danish cake called Kringle). The size ofthe apo(a) gene correlates with the size of the Lp(a) repeat:
the smaller the size of the Lp(a) protein, the higher theLp(a) levels.

207. The three genes ApoA1, C3, and A4 are clustered in
the long arm of chromosome 11 and span about 4 kb. Morethan 10 common restriction enzyme polymorphisms along
the length of this part of the genome have been detected
within this cluster, occurring within introns, exons,intergenic, and flanking sequences. Many studies havefound associations between some of these polymorphisms
and variations in levels of lipids and lipoproteins in healthy
individuals and patients [C56, H48, H49]. In several
studies, the association was also seen in patients withcoronary heart disease. Overall, these data support theexistence of a mutant gene in the apoA1-C3-A4 cluster thatlowers HDL levels, elevates triglyceride levels, andpredisposes to coronary heart disease.

211. Genetic risk factors other than hyperlipidaemia. In
addition to hyperlipidaemia, a classic risk factor forcoronary heart disease, the role of other potential risk
factors, such as the blood coagulation and fibrinolytic
systems homocysteine and paraoxanase, in the pathogenesisof coronary heart disease has been addressed. [C57, D12,
E17, G6, H3, H49, M21, M52, R27, S29]. The authors of
the European Concerted Action Project [G6] concluded that
increased plasma total homocysteine confers an independent risk of vascular disease similar to that of smoking
or hyperlipidaemia. Likewise, commenting on the role ofparaoxanase polymorphism, Heinecke and Lusis [H3] notedthat this polymorphism should now be added to the shortlist of other genes for which there is significant evidence ofa contribution to coronary heart disease.

208. Summarizing the results of different studies,
Davignon et al. [D23] concluded that approximately 60%of the phenotypic variation of the total cholesterol
concentrations is genetic and the remainder environmental
and that as much as one half of genetic variation iscontributed by three of the many proteins involved in lipid
metabolism (apoE, apoA4, and apoB). This lends credence

212. Summary. Coronary heart disease is a common
multifactorial disease and one of the major contributors tomortality in most industrialized countries. Coronary heartdisease mortality has significantly declined in the UnitedStates and several other countries during the last 20 years.
The disease is caused by atherosclerotic obstruction of thecoronary arteries.

ANNEX: HEREDITARY EFFECTS OF RADIATION

213. Family and twin studies show that genetic factors play
an important role in coronary heart disease. A positive
family history for premature coronary heart disease(occurring before age 60 years) is a strong risk factor byitself. Many genetic and environmental factors act in
combination to determine interindividual variability in risk
factor traits for coronary heart disease. Evidence fromepidemiological studies, clinical correlations, genetic
hyperlipidaemias, etc. indicates that lipids play a key role in
the pathogenesis of coronary heart disease. In every
population, plasma cholesterol has been implicated as a risk
factor for coronary heart disease. Specifically, high levelsof LDL cholesterol and low levels of HDL cholesterol are
strong risk factors.
214. About 60% of the variability of the plasma cholesterolis genetic in origin. While a few major genes have been
identified with rare alleles having large effects on this trait(e.g. LDLR, familial defective apoB-100), variability incholesterol levels among individuals in most families isinfluenced by allelic variation in many genes (polygenic
variation) as well as environmental exposures. Therefore,
in most families coronary heart disease does not segregatewith allelic variation at a single gene.
215. A proportion of the polygenic variation can be
accounted for by two alleles of the apoE locus that increase(ε4) and decrease (ε2) cholesterol levels. The apoEpolymorphism is also relevant in the context of late-onset
familial Alzheimer’s disease. HDL levels are genetically
influenced and are related to apoA1 and hepatic lipase genefunctions. Polymorphism at the apoA1-C3 region is often
associated with hypertriglyceridaemia.
216. The apo(a) gene, which codes for Lp(a), is highly
polymorphic, each allele determining a specific number ofmultiple tandem repeats of a unique coding sequenceknown as Kringle 4. The size of the gene correlates with thesize of the Lp(a) protein: the smaller the size of the Lp(a)protein, the higher the Lp(a) levels. Higher Lp(a) levels
constitute an independent risk factor for coronary heartdisease.
217. Some genetic risk factors other than hyperlipidaemia
are hyperhomocysteinaemia and polymorphisms in genesthat code for paraoxanase and in those that seem related toelevated plasma fibrinogen levels. The precise nature andintensity of these associations and the biochemicalmechanisms involved remain to be fully elucidated.

D. MECHANISMS OF MAINTENANCE
OF MULTIFACTORIAL TRAITSIN THE POPULATION
218. As discussed in Section B of this Chapter, themultifactorial threshold model is descriptive and notmechanistic, i.e. it is not designed to address the questionof the impact of an increase in mutation rate on disease37

frequency in the population. The prediction of the effects ofan increase in mutation rate on disease frequency, however,requires knowledge of the possible mechanisms of
maintenance of multifactorial diseases in the population.
While no specific theories or models have been developed
for this purpose, a wealth of literature exists onmathematical population genetic models dealing withmechanisms of maintenance of polygenic variability inpopulations (e.g. [C61, C62, K53, K54, L13, L43, L44,
T27, T28, T29]; reviewed in [S62]).
219. The main concept in these studies (as in the case of
mutations involving single genes) is the existence of asteady-state or equilibrium in the population between
mutation and some form of selection. For example, Lande[L13, L43, L44] showed that large amounts of genetic
variation in polygenic traits can be maintained in the
population even when there is strong stabilizing selection(i.e. selection for an intermediate optimum). Turelli [T27,
T28, T29], however, argued that unless selection is very
weak or the per locus mutation rates are extremely high (i.e.
>104), the equilibrium variance is considerably lower thanthat estimated by Lande, and therefore much of the additive
polygenic variance observed in natural populations cannot
be explained by mutation-selection balance. In approximations that apply for lower mutation rates per locus, Turelli[T27] in comparing his results with those of Lande, noted
that: (a) his results do not refute Lande’s conclusion (i.e.
considerable additive genetic variance may be maintainedby mutation-stabilizing selection balance in the population),and (b) the validity of Lande’s conclusion can only be
determined with additional data on selection intensities andon mutation rates in metric traits.
220. Stabilizing selection, however, is by no means the
only type of selection that has been envisaged in thesemodels. For example, “directional selection” (broadly
defined as selection for an extreme expression of a given
character) and one form of this, “truncation selection”(selection beyond a certain cut-off point, called thetruncation point, which is equivalent to the threshold in themultifactorial threshold model discussed earlier) are otherconcepts that have been used. Truncation selection is
known to be the most efficient form of directional selection,
because in this form, selection induces the maximum
change in gene frequency for a given effect of the gene on
the trait. Kimura and Crow [K54] and Crow and Kimura[C62] quantified efficiencies of truncation selection interms of the average effects of alleles on the phenotypic
trait and showed that truncation selection may indeed
reduce the mutational load despite high rates of mutations.
However, as they themselves noted [C62], the truncation
selection model may be too simplistic even for thresholdtraits, because the existence of intermediate optima andantagonistic effects among components of fitness cannot be
ruled out.
221. By its very nature, the dynamics of mutation-selection
balance studied in these models are very complex and notreadily applicable to human situations. Several factors

UNSCEAR 2001 REPORT

38

contribute to this complexity. First, most models are fully
specified by several parameters, each of which has its own
sensitivity regarding model predictions. Second, selectionis specified in such models by mathematical functions that
do not take into account the attained age of the individual;
in contrast, for most multifactorial diseases discussed
earlier, fitness is age-dependent. Third, generations aretreated as discrete in these models, while at one time, ahuman population consists of individuals of three or more
overlapping generations. Fourth, as in most population
genetic models, parameters such as effective population
size, selection intensities etc. are assumed to be constantover generations. As a consequence, these models whenapplied for risk estimation purposes, are at best
approximations to the real situation.
222. In conclusion, although several different models withdifferent degrees of complexity have been proposed to

explain the maintenance of multifactorial traits in the
population, not all of them can be used for risk estimation.
Therefore, some judgement needs to be made on which of
the concepts/models discussed can be used, taking into
account current knowledge of the genetics of multifactorialdiseases. Within the framework of an ICRP Task Group[I2], it was considered feasible to develop first, a theoretical
approach by incorporating mutation and selection into themultifactorial threshold model and to use this modified
model to examine the responsiveness of multifactorialdiseases to an increase in mutation rate through computer
simulations. It is to be noted that the concepts of mutationand selection are already built into the doubling-dose
method of risk estimation for Mendelian diseases, although
the application of the method for multifactorial diseases has
not thus far been rigorously examined. The rationale andpertinent details of the model that was developed are
discussed in the next Chapter.

IV. THE MUTATION COMPONENT FOR GENETIC DISEASES
A. BACKGROUND
223. In genetic risk estimation, the aim is to predict theeffects of a small dose of radiation (which causes anincrease in the mutation rate) in terms of its impact on
disease incidence in the population. As may be recalled(paragraph 93), one of the methods used for this purpose iscalled the “doubling-dose” method. The doubling dose is
the amount of radiation required to produce as many
mutations as those occurring spontaneously in a generation.
It is estimated as the ratio of the average spontaneous
mutation rate of a given set of genes relative to the averagerate of induction of mutations by radiation in the same setof genes:
DD =Average spontaneous rate
Average rate of induction(1)

224. The reciprocal of the doubling dose, 1/DD, is therelative mutation risk per unit dose. Since the risk due toradiation is conventionally expressed as the expected
number of cases of genetic disease (over and above thebaseline incidence) for autosomal dominant diseases (forwhich the disease frequency is approximately proportional
to the mutation rate), the risk is estimated as a product of
two quantities, the baseline incidence, P, and the relative
mutation risk, 1/DD:

namely, spontaneous mutations, which occur in every
generation, and natural selection, which eliminates them. In
other words, P in equation (2) represents the equilibriumincidence. If the mutation rate is increased as a result ofradiation, say in every generation, the prediction is that the
population will attain a new balance (over a number ofgenerations) between mutation and selection. For autosomal
dominant diseases, if there is an x% increase in themutation rate, it will be reflected as an x% increase indisease at the new equilibrium. The important point is thatmultiplying P by 1/DD gives the expected total increase indisease frequency at the new equilibrium. Traditionally,
estimates of risk for the first, second, or any subsequent
generation have been obtained by back-calculating fromthat at the new equilibrium. If the population is exposed toradiation in one generation only, there will be a transient
increase in the mutation frequency in the first generation
after irradiation, followed by a progressive decline to theold equilibrium.

(2)226. The response of X-linked recessive disease to changes
in mutation rate is approximately similar to that of
autosomal dominant diseases, discussed above, while thatfor autosomal recessive diseases is a little more involved,
since a recessive mutation does not immediately lead to arecessive disease. For multifactorial diseases such ascongenital abnormalities and chronic degenerative diseases,
the situation is more complex since there is no simple
relationship between mutation and disease.

225. The population genetic theory that underlies equation(2) is the equilibrium theory (see paragraph 82): thestability of the disease incidence is assumed to be a consequence of the balance between two opposing forces,

227. In order to assess the responsiveness of genetic
diseases in general and of multifactorial diseases inparticular to induced mutations, in its 1972 Report [C47],
the BEIR Committee introduced the concept of what isreferred to as the mutation component (MC). In that report,

Risk per unit dose = P × [1/DD]

ANNEX: HEREDITARY EFFECTS OF RADIATION

the mutation component of a genetic disease was defined as
the "proportion of its incidence that is directly proportional
to mutation rate". It was suggested that for multifactorialdiseases as a whole, the mutation component could be as
low as 5% or as high as 50%. Later, in the 1980 BEIR
Report [C48] and in publications of Crow and Denniston[C63, C69] and Denniston [D14], the concept waselaborated and mathematical formulations for estimating
mutation component were presented. When mutation
component is incorporated in the risk equation, the equation
becomes:
Risk per unit dose = P × [1/DD] × MC

(3)228. Although the mutation component concept was
originally developed to address the problem ofmultifactorial diseases, it is equally applicable to Mendeliandiseases. In fact, as discussed below and by Chakraborty etal. [C66], in estimating the expected increase in thefrequency of autosomal dominant diseases at the new
equilibrium (under conditions of radiation exposure in
every generation) and using this to back-calculate risks to
the first (or any post-radiation) generation of interest, thereports of UNSCEAR and BEIR have implicitly used themutation component concept, although they did not specify
how this was actually done. This is one reason why themutation component concept was not fully understood in
the past and was equated to the genetic component of adisease, which it is not. In this Chapter the concept is
discussed first from the standpoint of Mendelian diseases
and then extended to multifactorial diseases.

39

Note that risk per unit dose ÷ P = ∆P/P in equation (4).
Since DD = m/∆m (i.e. spontaneous rate/rate of induction),
1/DD = ∆m/m. Therefore, if m increases to m(1 + k), thedisease frequency increases from P to P(1 + k MC),showing that the concept of mutation component is relevant
only in the context of a change in mutation rate.
231. As mentioned above, the mutation component measures
the responsiveness of the disease under consideration to aunit relative change in mutation rate. Traditionally, such
responses are measured over a large number of generations.
The population is assumed to be in mutation-selection equilibrium when the increase in mutation rate occurs. The
impact of such a change depends on whether it occurs in a“burst” (i.e. in one generation only) or in every generation(permanent change). Under the first scenario, the impact
measured by ∆P relative to the old equilibrium value P will
be maximally manifest in the first generation following themutation rate increase and progressively diminishing insubsequent generations, when the population returns to theold equilibrium. When this occurs, mutation component
becomes zero.
232. In contrast, when the change caused by ∆m of any
given magnitude persists for all subsequent generations,that is, m is now permanently changed to (m + ∆m), thepopulation approaches a new equilibrium value of 1. In
both situations (a one-time-only or a permanent increase in
mutation rate), the quantity ∆P depends on the number ofgenerations following the change.

B. DEFINITION OF MUTATIONCOMPONENT

C. MUTATION COMPONENTFOR AUTOSOMAL DOMINANT DISEASES

229. The mutation component can be derived fromquantities related by the following formulation:

1. Mutation component
in the absence of sporadics∆P/P = [∆m/m] × [∆P/P]/[∆m/m]

233. The procedures for estimating mutation component
for autosomal dominant diseases, as well as for autosomal
recessive and X-linked diseases, and the necessary mathematical equations are discussed in detail by Chakraborty etal. [C66] and in the ICRP Task Group Report [I2]. Some
Mendelian diseases, such as Apert syndrome and Crouzon
syndrome, are entirely due to germinal mutations, whereas
others, such as retinoblastoma and breast cancers, include
a proportion of cases due to somatic mutations (i.e. not due
to germinal mutations; these are called here “sporadics”).
The discussion in this Section pertains to those that do nothave sporadics.

(4)

where P is the disease incidence before an increase in
mutation rate and ∆P is its change due to a ∆m change inthe mutation rate, m. In this equation ∆P/P is the relativechange in disease incidence and ∆m/m is the relativechange in mutation rate. The formal definition of mutation
component becomes
MC = [∆P/P]/[∆m/m](5)Thus, mutation component is the relative change in disease
incidence per unit relative change in mutation rate.
230. Despite the slight differences in the notations used,equation (4) is the same as the familiar risk equation used
for risk estimation with the doubling-dose method, namely:
Risk per unit dose = P × [1/DD] × MC
orRisk per unit dose ÷ P = [1/DD] × MC

(6)(a) The population before irradiation
234. Consider a hypothetical autosomal dominant mutation
in a population under Hardy-Weinberg equilibrium (HardyWeinberg equilibrium refers to the concept that both genefrequencies and genotype frequencies will remain constantfrom generation to generation in an infinitely large
interbreeding population in which the mating is at random

UNSCEAR 2001 REPORT

40

and there is no differential selection, migration, or
mutation). For a single-locus, two-allele situation, if p is themutant gene frequency and q the frequency of the nonmutant (i.e. the wild-type), and p + q = 1, the genotypic
frequencies are
p2 + 2pq + q2

(7)

in which p2 is the frequency of mutant homozygotes, 2pq
that of heterozygotes, and q2 that of normals.
235. Assume that the spontaneous mutation rate m = 1 105and the selection coefficient s = 0.5. For an autosomal
dominant mutation, the equilibrium frequency of the mutant
gene is given by
p . m/s . 2 105(8)

At low mutant gene frequencies, the disease frequency, P,
is approximately 2p = 4 105, because only heterozygotes[2pq in equation (7)] contribute to disease frequency.
(b) A one-time or a permanent increasein mutation rate
236. Assume that as a result of radiation exposure, themutation rate becomes twice that of the spontaneous rate
and that this increase occurs either in only one generationor permanently (i.e. generation after generation). For a onetime increase in mutation rate (“burst”, indicated by thesubscript b in MCb below), the dynamics of change inmutation component with time, t, at any generation is givenby the equation
MCb(t) = s(1 ! s)t1(9)

and for a permanent increase in mutation rate (indicated by
the subscript p), by(10)

238. The pattern of changes following a one-time orpermanent doubling of the mutation rate is depicted in
Figure V and numerically illustrated in Table 29. The left
panel in Figure V shows the change in population
frequency of a hypothetical autosomal dominant disease
with time (in generations) when radiation exposure causes
the mutation rate to increase from 1 105 to 2 105 (i.e.
doubling) either in one generation (“burst”, shown by thebroken line) or permanently (solid line). The initial diseasefrequency, P, before the mutation rate increase is assumed
to be 4 105 (see paragraph 235) and the selection
coefficient s = 0.5. The right panel of Figure V shows thechanges in mutation component for the same conditions.
239. As Figure V and Table 29 show, for a single-generation doubling of the mutation rate, the disease frequency
shows a transitory increase in the first generation and isfollowed by a progressive decline towards the old equilibrium value in subsequent generations. The pattern issimilar for changes in mutation component: a transitory
increase in the first generation followed by a progressive
decline to zero in subsequent generations. With theselection coefficients used, a permanent doubling of themutation rate leads to a doubling of the disease frequency
by the fourth or fifth generation, by which time themutation component becomes nearly 1.

8

1.0Permanent doubling
7

6

5

One-time doubling
4

MUTATION COMPONENTDISEASE FREQUENCY (per 100,000)MCp(t) = 1 ! (1 ! s)t

237. Equations (9) and (10) show an interesting propertyof the effects of the two scenarios of mutation rate changes:
a one-time or a permanent increase in mutation rate has thesame impact in the first generation following the increase,namely, MCb = MCp = s. With no irradiation in subsequent
generations (scenario 1), the mutation component graduallydecays to zero at a rate of (1 ! s) per generation. With apermanent increase in mutation rate, mutation component
continues to increase in subsequent generations to attain avalue of 1 at the new equilibrium.

Permanent doubling

0.8

0.6

0.4

0.2

One-time doubling

0
0

1

2

3

4

5

6

7

8

9 10

GENERATION

0

1

2

3

4

5

6

7

8

9 10

GENERATION

Figure V. Patterns of change in disease frequency and mutation component
following a one-third or permanent doubling of the mutation rate.
The initial mutation rte is assumed to be 1 10-5 and the selection coefficient is 0.5

240. It is now easy to see that although the earlier
UNSCEAR and BEIR Reports did not provide explicit
expressions for estimating mutation component for

autosomal dominant diseases, their use of equation (2) for
estimating the total risk (under conditions of radiation
exposure in every generation) implied the concept that theANNEX: HEREDITARY EFFECTS OF RADIATION

equilibrium MC = 1, which is another way of saying that
under the above conditions, the equilibrium frequencies ofthese diseases are directly proportional to mutation rate.
Likewise, their estimates of risk in the first generation
implied that MC = s in that generation. Now, with theavailability of explicit algebraic formulations to estimate
mutation component, a direct evaluation of the impact of anincrease in mutation rate in any post-radiation generation ofinterest has become possible, obviating the need to backcalculate from the estimate at the new equilibrium.
2. Mutation component in the presenceof sporadics
241. In the preceding Section it was assumed that genetic
disease is entirely due to germinal mutation. However, there
are instances where this assumption may not hold (e.g.
about 40% of retinoblastoma cases are due to germinal
mutations and the remainder are sporadic). For suchdiseases, the disease frequency at equilibrium can beassumed to take the form P = A + Bm. With A (sporadic
component) and B (germinal component) as constants, only
the second term will cause the trait frequency to increase
with an increase in mutation rate. Assume that the dose
dependence of the mutation is linear, namely, that m = α +βD. Substituting this form of m in the equation for P above,
one obtains
P = A + Bα + βBD

41244. For a one-time increase in mutation rate, the first
generation mutation component is equal to the selection
coefficient (and therefore similar to that for autosomal
dominants) but adjusted to take into account the fact that
only one third of the X chromosomes are in males. For
autosomal recessives, the first generation mutation
component is substantially smaller (than that for autosomal
dominants) and is close to zero. In subsequent generations,mutation component gradually decays to zero.
245. With a permanent increase in mutation rate, for bothkinds of diseases the mutation component progressively
increases to reach a value of 1 at equilibrium, but the rates
of approach to equilibrium are different for X-linked andautosomal recessive diseases and are dictated by selection
and time (in generations) following radiation exposure. A
comparison of the effects of increases in mutation rate on
mutation component for autosomal dominant, X-linked, andautosomal recessives shows that the effects are more
pronounced for autosomal dominants, followed by
X-linked, and are far less pronounced for autosomal
recessive diseases.

E. MUTATION COMPONENTFOR MULTIFACTORIAL DISEASES(11)

so that ∆P/P = βBD/(A + Bα) and ∆m/m = βD/α. Consequently,

1. Rationale for the developmentof a finite-locus threshold model

MC = Bα/(A + Bα)

246. As discussed in Section III.B, the standard
multifactorial threshold model of disease liability remains
useful for understanding familial aggregations and excess
risks within families and makes good predictions evenwhen there is uncertainty about the underlying mechanisms.
However, it is essentially a descriptive model and cannot be
used to understand the mechanisms that underlie the stable
incidence of multifactorial diseases in the population or the
impact of an increase in mutation rate on disease incidence.
Likewise, the population genetic models on themaintenance of polygenic variability in populations(Section III.D), also cannot be directly used to determine
the impact of mutation rate increases on the incidence ofmultifactorial diseases.

(12)Thus, depending on the value of B/A, the mutation component of a disease in the presence of sporadics will besmaller than 1, i.e. the larger the fraction of sporadics, thesmaller the B/A ratio and mutation component.
242. Three messages are implicit in equation (12): (a)when A = 0 and B = 1, as they are for most Mendeliandiseases, MC = 1 at equilibrium; (b) as long as there is a
sporadic (or non-genetic) component A, the mutation
component at equilibrium will be less than 1, with the logic
being easily extended to early generations; and (c) mutation
component and the genetic component of the disease are
not the same entities. Mutation component quantifies themutation-responsiveness of the genetic component when
there is a change in mutation rate and has meaning only
when there is such a change.

D. MUTATION COMPONENT FOR
X-LINKED AND AUTOSOMAL
RECESSIVEDISEASES
243. The estimation of mutation components for X-linked
and autosomal recessives is more involved than that for
autosomal dominants. Since this is discussed in detail by
Chakraborty et al. [C66], only the principal conclusions are
summarized below.

247. In considering the various options for risk estimation
for multifactorial diseases, the Committee feels that a useful
first approach is to utilize and combine concepts of both themultifactorial threshold model and the mechanistic
population genetic models. This approach was also taken by
the ICRP Task Group [I2]. The devised hybrid model,
referred to henceforth as the finite-locus threshold model(FLTM), assumes a finite number of loci, uses a redefinedconcept of threshold, and incorporates mutation andselection as two additional parameters. As discussed below,
in this form, the model permits estimating the mutation
component, MC, which is one of the quantities of interestfor estimating the risk of multifactorial diseases.

UNSCEAR 2001 REPORT

42248. The choice of the FLTM rather than the standard
multifactorial threshold model is dictated by the following
considerations. First, it is now evident that the standard
model which assumes an essentially infinite number of loci,cannot be sustained at present. The biometrical andmolecular studies of diseases such as coronary heart diseaseor essential hypertension lend credence to the view that the
number of loci underlying these diseases is probably small,each with moderate effects; genes with large effects at the
population level seem to be infrequent.
249. Secondly, in the absence of precise knowledge of thegenetic basis of most multifactorial diseases, the FLTM
provides a useful starting point, because with such a model,
the meaning of parameters reflecting mutation rates andselection coefficients can be quantitatively assessed interms of those for single-gene effects; further, even if thenumber of loci is large, the predominant contribution to thevariance is still from those genes with large effects at the
population level (i.e. the kind of polymorphic loci discussed
in the Sections on chronic diseases), and these loci may be
only a few in number.
250. Thirdly, the concept of thresholds is implicit inclinical medicine. For example, dietary therapies arerecommended for individuals whose cholesterol
concentrations (a risk factor for coronary heart disease) are
5.2!6.5 mM l1, more stringent dietary recommendations
and some drug therapy for those with concentrations of
6.5!7.8 mM l1, and aggressive individualized therapies forconcentrations exceeding 7.8 mM l1 (and LDL cholesterol
exceeding 4.9 mM l1). A similar situation is true for
essential hypertension.
2. The model and its predictions
251. The details of the FLTM and its predictions are
discussed in the ICRP Task Group Report [I2] and by
Denniston et al. [D17]. In general terms, the model assumes
that the liability underlying the trait, which is made up ofgenetic and environmental factors, is a continuous variable
and that the environmental contribution has a normal(Gaussian) distribution. It differs from the standard
multifactorial threshold model in that the genetic
contribution to liability is assumed to be discrete (i.e. it
comes from a finite number of loci), and mutation andselection are incorporated as two additional parameters,
which are two opposing forces responsible for the stable
incidence of the trait in the population.
252. The mathematical formulations of the model do not
permit expressing the effects of an increase in mutation rate
on mutation component in the form of a single equation.
However, the model’s predictions can be iteratively
evaluated from the computer programme that wasdeveloped for this purpose. The programme is run using aparticular set of parameter values (mutation rate, selection
coefficients, threshold, etc.) until the population reaches
equilibrium between mutation and selection; once thisoccurs, the mutation rate is changed once or permanently.

The computer run is resumed with the new mutation rate(with the other parameters remaining the same), and thechanges in mutation component and its relationship toheritability (hB2) following the mutation rate increase are thenexamined in desired generations following the mutation rate
and at the new equilibrium. The estimates of hB2 are not
inputs but outputs of the computer programme, obtained byusing different combinations of s (selection coefficient), se(environmental standard deviation), and T (threshold).
(a)Effects on mutation component of apermanent increase in mutation rate

253. Figure VI shows, for a five-locus model, the relationships between the heritability of liability (x axis) andmutation component (y axis) at equilibrium following apermanent 15% increase in mutation rate (from 106 locus1
generation1 to 1.15 106 locus1 generation1). The selection coefficients, s, assumed in these calculations are 0.2
and 0.8. Other assumptions include the following: (a) theloci are unlinked (free recombination); (b) the starting
gametic frequencies are equal (1/2n); (c) the mutation rate forall loci is the same; (d) there is no epistasis or dominance atthe liability level; and (e) there are no sporadics.
254. The different data points in Figure VI come fromdifferent computer runs using different combinations ofparameter values (threshold, selection coefficient, andenvironmental standard deviation). The figure shows thatfor hB2 values higher than about 0.1, mutation component isabove 0.8 at equilibrium; for hB2 values higher than 0.4,
mutation component is essentially 1. In other words, fordiseases with heritability values in the range from 0.4 to
0.8, a 15% increase in mutation rate, will result in a 15%
increase in disease frequency at equilibrium.
255. The predicted effects in the early generations (i.e.
generation 1, 5 and 10) following a mutation rate increase
identical to that assumed in Figure VI are summarized in
Figure VII. From the difference in the y axis scale between
Figures VI and VII it is clear that the mutation component
in the early generations is very small, being often much lessthan 2% for the specified conditions of the model.
256. Figure VIII compares the mutation component values
at equilibrium and in generation 10, following a permanent
increase in mutation rate. The shaded areas in the figure are
the ones of interest in risk estimation. The calculations
reinforce the main qualitative result, i.e. for a 15%
permanent increase in mutation rate, the mutation
component at equilibrium is close to 1, whereas even ingeneration 10, the corresponding mutation components arevery small indeed.
(b) Effects on mutation component of a onetime increase in mutation rate
257. The numerical algorithm used for the above
calculations was also used to examine the consequences ofa one-time increase in mutation rate, i.e. the mutation rate

MUTATION COMPONENT AT EQUILIBRIUM

ANNEX: HEREDITARY EFFECTS OF RADIATION

43

1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

HERITABILITY OF LIABILITY

Figure VI. Relationship between mutation component
and heritability of liability at equilibrium.

0.0200

GENERATION 1

0.0175

MUTATION COMPONENTMUTATION COMPONENT

0.02000.01500.01250.01000.00750.00500.0025

GENERATION 5

0.01750.01500.01250.01000.00750.00500.0025
0

0
0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0

1.0

0.1

0.2

MUTATION COMPONENT

0.0200

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

HERITABILITY OF LIABILITYHERITABILITY OF LIABILITY

GENERATION 10

0.01750.01500.01250.01000.00750.00500.0025
0
0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

HERITABILITY OF LIABILITY

Figure VII. Relationship between mutation component
and heritability of liability in early generations.

was increased once by 15% and then brought back to theoriginal value for all subsequent generations. As expected,
the first- generation mutation component is the same as thatshown in Figure VIII, and this is followed by a gradualdecline back to zero in subsequent generations (data notshown). Given the relatively small mutation component in
the first generation, details of these computations are oflittle consequence.

UNSCEAR 2001 REPORTMCTU AT GENERATION 10 AND AT EQUILIBRIUM

44

where P is the frequency of individuals above the threshold,n is the number of loci, µ is the mutation rate per locus, ands is the selection against those above the threshold.

1.0

0.8

0.6

0.4

Mutation component MCTU at equilibrium
Mutation component MC at generation 10
TU

0.2

0
0

0.2

0.4

0.6

0.8

1.0

DOSE (Gy)Figure VIII. Relationship between heritability andmutation component at equilibrium and at generation
ten under conditions of a permanent increase in
mutation rate [D17].
The shaded areas are those of interest in risk estimation.

(c)

Effects of gene interactions and sporadics

258. The effects of interactions between genes on quantitative phenotypes at risk of complex diseases are varied anddo not readily lend themselves to modelling. However,when some assumptions on these interactions wereincorporated into the model, it was found that the results
were qualitatively the same as those obtained under conditions of no gene interactions, i.e. the mutation component
remains basically unaltered and in early generations is
below 2% even for large values of hB2. The results ofcalculations using n (the number of loci) = 3, 4, or 6 arealmost identical (data not shown).
259. As expected, the presence of sporadics (individuals
who are affected by the disease for reasons unrelated to the
genotype) was found to lower the magnitude of mutation
component both at equilibrium and in the early generations.
The factor by which the numerical results are changed canbe estimated to be [1!(a/PT)], where a/PT represents the
proportion of sporadic cases among the total number ofaffected individuals.

(d) Validity of the assumed numbers of lociand selection coefficients260. The theoretical formulations of King [K33] formutation load are applicable to the FLTM discussed in this
Chapter. For the directional mutation-selection balance
assumed, unless the heritability is very low, the relationshipbetween incidence of disease, the number of loci underlying
the disease, and the mutation rate per locus is summarized
by the expression
P # 2nµ/s(13)261. The results of numerical calculations given in
Table 30 provide some notion of the numbers of locipredicted by the model over a range of s values. It is
obvious that the model can explain the current incidencesof multifactorial diseases only when the mutation rates arevery high (much above 106 to 105 per locus, generally
assumed for human mutations) or when the selection
coefficients are much smaller than the ones used inTable 30, or some combination of the above two factors.
For example, for a congenital abnormality to have an
incidence of the order of 103 (0.001), if one assumes amutation rate of the order of 105, for s = 1, 0.5, and 0.1, thenumbers of loci predicted by equation (10) are: 50, 25, and5, respectively. Therefore, when selection is very strong(for example, s = 1), a larger number of loci are needed
than when selection is weak.
262. There is no a priori reason to assume that the
mutation rates of genes underlying the multifactorialdiseases are much higher than those in Mendelian diseases.
If this view is correct, the selection coefficients need to bemuch smaller than the ones in Table 30. Progress in theclinical management of congenital abnormalities over thelast few decades provides evidence for a reduction of
selective pressures on previously deleterious traits, so thats values have become much smaller [C60]. The fact thatmost chronic multifactorial diseases have their onset in
adult life, after the individuals have had children, is
consistent with the inference that selection coefficients forthem are also very small. The overall conclusion, therefore,
is that the FLTM discussed here allows a reasonableassessment of the impact of induced mutations on thefrequencies of multifactorial diseases.

(e) Robustness of predictions of the model
263. The model predicts that with a permanent increase in
the mutation rate (of the magnitude of interest for risk
estimation), the mutation component in the early
generations is generally very much less than 2% for a broad
range of heritability values above 30% (see Figure VIII).
This conclusion holds for so many combinations ofparameter values (truncation points, selection coefficients,
number of loci, environmental variances, backgroundmutation rates, increases in mutation rates, levels ofinteraction between genes, etc.) that it can be consideredrelatively robust, and the predictions of the model are valid
within the framework of the assumptions used. On
biological grounds, however, one of the assumptions of themodel, namely that the mutation rate is increased for all thegenes underlying a given multifactorial disease, can becontested, since this is unlikely to occur at low radiation
doses. This means that the effective mutation component islikely to be far less than 2%. This point is taken up again in
Chapter VIII.

ANNEX: HEREDITARY EFFECTS OF RADIATION(f)

Application for specificmultifactorial diseases

264. In evaluating the impact of an increase in mutation
rate on mutation component, specific assumptions havebeen made about the dynamics of disease incidence before
the change in mutation rate, the range of the liability scaleon which selection operates, and how environmental factors
act, in addition to allelic effects of the loci underlying aquantitative trait. Besides, the combination of parametervalues used to examine model predictions were selected forconvenience of computation (ease of convergence to equilibrium, manageable numbers of gametes, and the like).
Thus, many of the assumptions and parameter values may
not necessarily correspond to any of the specific multifactorial diseases discussed earlier.
265. In principle, it would be interesting to examine theimpact of induced mutations on the responsiveness of eachof the multifactorial diseases of concern. There has,
however, been no attempt to fit the model to empirical data
because such model-fitting involves (a) the estimation(reconstruction) of mutation rates and selection coefficientsthat should have operated in the past to result in thepresent-day equilibrium incidences assumed for the various
multifactorial diseases and (b) the use of these estimates asa starting point to examine the consequences of an increasein mutation rate with different selection coefficients. In thelight of the results obtained, the Committee, as also the
Task Group, feels that such efforts would be unlikely to add
any more precision to the conclusions reached and therefore
did not undertake them.

F. SUMMARY
266. The concept of mutation component was first
introduced in the 1972 BEIR Report [C47] as a means ofassessing the responsiveness of the different classes ofgenetic diseases to an increase in mutation rate, and for thisreason it is important within the framework of genetic risk
estimation. The concept was subsequently elaborated, andthe results obtained from a recent study of the problem by
the ICRP Task Group are presented. Mathematicalexpressions are given to estimate the mutation component

45

for autosomal dominant diseases (for which the relationshipbetween mutation and disease is straightforward) underconditions of a permanent or a one-time increase in
mutation rate and for any post-radiation generation ofinterest. The following points are emphasized: (a) the
mutation component concept is valid only in the context ofa change in mutation rate; (b) mutation component enables
quantifying the responsiveness of the genetic component of
the disease; and (c) mutation component is not the same as
the genetic component of the disease.
267. A finite-locus threshold model was presented and its
properties and application to estimate mutation component
for multifactorial diseases discussed; this model
incorporates the concepts of liability and threshold from thestandard multifactorial threshold model and of mutation andselection from quantitative population genetic models thathave been proposed to explain the dynamics of polygenic
variability in populations on an evolutionary time scale.
268. While mutation component is in principle a functionof mutation rates, selection, threshold value, environmental
variance, recombination, and the magnitude of increase in
the mutation rate, its value at the new equilibrium as well as
in early generations following a mutation rate increase canbe roughly predicted from the currently available
information on heritability of multifactorial diseases. For apermanent small increase in mutation rate, over a broad
range of heritability values (about 30%!80%) that are ofinterest in risk estimation, the mutation component in thefirst few generations following the mutation rate increase isless than 2%, often much less. Stated differently, multifactorial diseases are predicted to be far less responsive to
induced mutations than Mendelian diseases, so the expected
increases in disease frequencies are very small.
269. In response to the question whether estimates of thenumber of genes and the spontaneous mutation rates
underlying multifactorial diseases and selection coefficientsused in studying the properties and predictions of the model
are realistic, it is concluded that the model is indeed
compatible with current understanding of the numbers ofgenes underlying these diseases, their mutation rates, andthe selection coefficients in present-day human populations.

V. CANCER PREDISPOSITION, RADIOSENSITIVITY,
AND THE RISK OF RADIATION-INDUCED CANCERS
270. It has long been known that among Mendeliandiseases, there is a subset in which a cancer of one type oranother is the sole or frequent phenotypic manifestation of
the mutant gene (e.g. [M16]). Individuals carrying suchmutant genes are said to be cancer-predisposed, cancerprone, or cancer-susceptible. Mulvihill’s 1999 compilation[M23] shows that 635 (6.2%) entries in McKusick's 1998
compendium [M17] represent genes and/or disorders thatpredispose to or are associated with neoplasia.
271. In 1968, Cleaver [C16] discovered that in patientswith xeroderma pigmentosum (XP), an autosomal recessive

46

UNSCEAR 2001 REPORT

disorder characterized by predisposition to skin cancer,
defective DNA repair is the biochemical cause for cellular
UV-hypersensitivity, which in turn leads to solar-radiationinduced skin cancers. Around the same time, Gotoff et al.
[G5], Morgan et al. [M18], and Feigin et al. [F9] found thatpatients with ataxia-telangiectasia (A-T), another autosomal
recessive disorder with immune system defects and predisposition to a number of malignancies, reacted catastrophically to conventional x-ray therapy. These discoveries
set the stage for and catalyzed studies of the relationships
between possible enhanced cellular radiosensitivity, thenature of biochemical defects, and cancer predisposition in
Mendelian diseases known to be associated with cancer[L10, L11] (reviewed in [M19]).
272. Thus far, about 20 Mendelian disorders have beenstudied in relation to ionizing radiation exposure. The initialexpectations engendered by the XP paradigm have not,however, been fulfilled; while fibroblasts and/or lymphocytes
from patients with most of these diseases appeared tomanifest increased sensitivity to ionizing radiation (primarily
to cell-killing effects), in most instances the magnitude of theenhancement in sensitivity was small and not always
reproducible. Only in cells derived from patients with A-T
and Nijmegen breakage syndrome is there unequivocal
evidence for a high sensitivity to ionizing radiation [A10,C25, F12, T13]. Until recently, for most of these disorders noclear links could be forged between gene defects, biochemical sequelae, and cancers.
273. These two themes, cancer predisposition and thepotentially increased sensitivity of such predisposed individuals to ionizing-radiation-induced cancers, are now coming
into sharper focus in both basic cancer biology and radiation
carcinogenesis. There are at least three reasons for this:
(a)

(b)

(c)

the discoveries that mutations underlying some ofthese disorders are in tumour-suppressor genes and/or
in genes involved in the maintenance of genomic
stability, cell-cycle control, and DNA repair have
imparted a new dimension to thinking about cancer
predisposition;a view that has been gaining currency in recent years
is that in addition to the rare mutant genes that confer
a high cancer risk, there may be a much larger groupthat confers a lesser degree of risk without obvious
familial clustering [E3, E4, P11, P12]. The inference
here is that such inherited predisposition may
contribute significantly more to the cancer load in the
population than has hitherto been assumed; andthere is some evidence that cancer-predisposed
individuals may also be more sensitive to ionizingradiation-induced cancers. Should this turn out to betrue, the risk of radiation-induced cancers in a
population in which these radiosensitive subgroups
exist may be higher than in a population that does nothave these subgroups.

274. In this Chapter, some essential information on genetic
predisposition to cancer and the sensitivity of cancer-prone

individuals to ionizing-radiation-induced cancers is considered to provide a basis for assessing the possible
increases in risk of radiation-induced cancers. Since thefocus is on the relationship between cancer predisposition
and the sensitivity of the predisposed individuals toionizing-radiation-induced cancers, diseases such as
xeroderma pigmentosum, Fanconi anaemia, and Bloom's
syndrome, which are not relevant in the present context, arementioned but not discussed; instead, they are consideredin Annex F, “DNA repair and mutagenesis”, of the
UNSCEAR 2000 Report [U1]. In what follows, the terms“cancer-predisposing genes” and “familial cancer genes”
are used interchangeably. The subject has recently beenreviewed [C17, C18, F33, S32] and was also considered by
the ICRP Task Group [I1].

A. FAMILIAL CANCER GENES
275. While most cancers are sporadic (attributable tosomatic mutations), some of them (the proportion varies
according to cancer type) occur in individuals who are at ahigher risk than the remainder of the population because of
an inherited predisposition due to specific germ-line
mutations in various inherited cancer genes. Collectively,
these mutations are believed to account for about 1% ofcancer patients [F33].
276. So far, about 30 familial cancer genes have beencloned and for several more the chromosomal localizations
are already known. Table 31 summarizes information on thecloned genes, their location, the established or inferred
normal functions, and the associated cancers. As can benoted, these include tumour-suppressor genes (most of theentries), three proto-oncogenes (the RET, MET, and CDK4)
and DNA repair genes (those responsible for A-T, Bloom’s
syndrome, xeroderma pigmentosum, and Fanconi anaemia).
277. It is important to note the distinction between protooncogenes and tumour-suppressor genes: proto-oncogenes
are those genes in which variant alleles with gain-offunction (activating) mutations cause cancer, whereas
tumour suppressors are genes in which both alleles withloss-of-function (inactivating) mutations cause cancer[F33]. Most of the inherited cancer syndromes show adominant pattern of inheritance and result from inactivating
mutations in tumour-suppressor genes rather than from
activating mutations in proto-oncogenes. Consistent with
Knudson’s two-hit hypothesis [K21] (see paragraph 281),
the germ-line tumour-suppressor gene defect is recessive at
the somatic cell level, and the corresponding normal allele
is inactivated by somatic mutations during cancer
development. In contrast to mutant tumour-suppressor
genes, activated proto-oncogenes act dominantly, andsomatic mutation in the other allele is not necessary forcancer development. Nevertheless, whether the germ-line
mutation is in a tumour-suppressor gene or in a protooncogene, additional somatic mutations are needed forcancer development.

ANNEX: HEREDITARY EFFECTS OF RADIATION

278. The familial cancer genes shown in Table 31 pertain
to only a small subset of the “cancer genes” thus far known.
The cancer genes include, among others, the cellular
oncogenes [A7, B17, B18, B19, B20] and transforming
genes identified through cloning of rearrangement breakpoints in myeloid and T-lymphoid cancers (reviewed in[E5, M56, R13, R14]). In what follows, some selected
examples of familial cancer genes, as well as the postulated
functions and mechanisms of cancer predisposition, arediscussed, with emphasis on recent data.
1. The RB1 gene and retinoblastoma
279. Retinoblastoma is a childhood eye tumour occurring inboth familial and sporadic forms. A high proportion (40%) ofchildren with retinoblastoma carry a germ-line mutation in
one allele of the RB1 gene; 85% of these children develop
multifocal tumours affecting both eyes (bilateral tumours).
The mutation predisposes them to retinoblastoma in infancy
and is transmitted as an autosomal dominant. The tumoursthat they develop, however, have both alleles mutated. The
other 60% of children with retinoblastoma have unifocal
tumours and have only a 15% chance of a germ-line RB1mutation, although in their eye tumours both alleles are
mutated [C19, H18, V8].
280. Apart from retinoblastoma and osteosarcomas
associated with germ-line mutations at the RB1 locus, RB1
inactivation is also observed in retinoblastomas and sarcomasof purely somatic mutational origin and in several other, morecommon tumours (e.g. most small-cell lung carcinomas andsome non-small-cell lung, bladder, and breast carcinomas) inwhich the gene inactivation is also presumed to derive
exclusively from somatic events [H18, S37, W15].
281. On the basis of statistical analysis of clinical data,
Knudson [K21] proposed, in 1971, the now classic two-hit
model for the genesis of retinoblastoma; he inferred that inthose individuals carrying a predisposing mutation, a single
additional event (which was later proved to be at thehomologous normal locus) is sufficient for tumorigenesis.
In familial cases, individuals who inherit one normal andone mutant allele, the loss or inactivation of the normal
allele (loss of heterozygosity or reduction to homozygosity)
occurs somatically through chromosome loss, deletion,
mitotic recombination, or gene conversion. The predictionthat in sporadic (non-familial) cases the events inactivating
both alleles should occur somatically, i.e. that the tumours
should show a loss of function of both alleles, was indeed
found to be true [C20, D11]. Further, the model appears to
fit the data for mutations in genes involved inneurofibromatosis (NF1 and NF2) and in the von-HippelLindau (VHL) and Li-Fraumeni syndromes (see [E4, K17]
and the references cited therein). Knudson's model thus
provided a basis for (a) explaining why the RB1 mutation
is dominant in pedigrees but recessive at the cellular level;(b) conceptualizing the recessive mode of action of
dominantly inherited tumour-suppressor genes in general;and (c) establishing the use of loss of heterozygosity as a47

hallmark in the search for other tumour-suppressor genes.
For some other dominant cancer syndromes, however, thesituation appears to be more complex; these are consideredbelow in Section V.A.6.
2. The p53 gene and Li-Fraumeni syndrome282. Acquired (i.e. somatic) mutations in the p53 gene are
the most frequently encountered events in humanmalignancy, being present in about 50% of some cancers(e.g. cancers of the colon, lung, oesophagus, breast, liver,brain, and reticuloendothelial and haemopoietic tissues;
reviewed in [H19, L15, V9]). Testicular tumours,
neuroblastomas, and thyroid tumours are among the known
exceptions in which few p53 mutations have so far been
detected [K22, P15, V10].
283. Germ-line mutations of the p53 gene result in the LiFraumeni syndrome (LFS), which is a rare autosomal
dominant cancer syndrome. It is characterized by theoccurrence of sarcomas and multiple primary cancers inaffected family members [B22, M24, M25, M26, S39].
Other cancers do occur, and of these, early-onset breast
cancer is most frequently encountered. Although acquired
alterations of the p53 gene or its encoded protein are
frequently identified in sporadic breast cancers, thefrequency of germ-line p53 mutations in breast cancer
patients outside of families with the classical Li-Fraumeni
syndrome is not known. Most of the reported germ-line
mutations are missense, although occasional nonsense
mutations (base pair deletions or insertions) have also been
described (reviewed in [M24, M25]). There is a report on
the occurrence of a 2.53 kb germ-line deletion in a LiFraumeni syndrome patient [P14].

3. BRCA1 and BRCA2 genes andbreast and ovarian cancers
284. Breast cancer is an extremely common malignancy,
affecting approximately 1 in 10 women during their
lifetime, with more than 180,000 women having been
diagnosed in the United States in 1993. Ovarian cancer isthe second most common female gynaecologic malignancy,with about 22,000 new cases in the United States in 1993
[M20]. Most cases of both these cancers are sporadic.
While germ-line mutations in several genes confer somesusceptibility to breast cancer (e.g. p53, the androgen
receptor gene [for male breast cancer] and the ATM gene),
they account for only a minority of breast cancer cases. The
initial linkage analysis [C21, C22, S40, W14] andsubsequent cloning [M12, T12] of two genes, BRCA1 andBRCA2, established the important contribution of mutationsin these two genes to familial breast and ovarian cancers
and gave a boost to studies in this area.
285. Early on in these studies, it was assumed (based on
observations of loss of heterozygosity for markers in the
17q12!q21 region in the case of BRCA1 and 13q12!13

48

UNSCEAR 2001 REPORT

region in the case of BRCA2) that these genes would betumour suppressors and that mutations in them would playa role in both inherited and sporadic breast and ovariancancers (reviewed in [B24, C27]. Analyses of tumours ofpatients with BRCA1 germ-line mutations indeed showed
loss of the wild-type allele [C10, F6]. This was also true of
BRCA2 [C27]. However, so far, few clearly disease-causing
somatic mutations in BRCA1 or BRCA2 have been found insporadic cancers, suggesting that mutations in these genes
may not be critical for the development of the majority ofbreast and ovarian cancers [C27, F5, S48].
286. A worldwide effort is now underway to clarify thegenetics of breast and ovarian cancers, and the publishedwork already permits a number of conclusions (Table 32;
reviewed in [S93]). First, it is clear that the proportion ofhigh-risk families with breast and ovarian cancer attributable to BRCA1 mutations varies widely in different
populations. BRCA1 mutations are by far the most common
in the Russian Federation, occurring in 79% of the breast/
ovarian cancer families in which the mutation-carrying
families have one or two common alleles [G19]. The
proportion of familial breast and ovarian cancers associatedwith BRCA1 is next highest in Israel, occurring in 47% of
high-risk families [L45], and Italy (29% of families).
Finally between 20% and 25% of high-risk families inFrance, Great Britain, Hungary, and Scandinavia have
BRCA1 mutations, and in each region, BRCA1 mutations
are substantially more common than BRCA2 mutations[A16, G10, G11, G19, J17, R39, S94]. In Iceland, however,BRCA2 mutations are more frequent. Further, one specificmutation (999del5) explains virtually all inherited breastand ovarian cancers in Icelandic families [T30]. Inherited
BRCA1 mutations explain less than 20% of high-risk (i.e.
early onset) families in Belgium, Germany, Japan, theNetherlands, and Norway [A16, H29, H43, I5, J18, P32].
287. In most populations, BRCA1 and BRCA2 mutations
together explain 6%!10% of breast and ovarian cancer
unselected for family history; in Israel, the proportion issomewhat higher (15%) [S93]. In about 30% of high-riskfamilies, no BRCA1 or BRCA2 mutations have been
detected. In families with male breast cancer, BRCA2
mutations are more common than BRCA1 mutations. The
combined data from the United States studies suggest that
BRCA2 is responsible for 19% of familial male breast
cancer but a considerably lower fraction of male breast
cancer in the general population. Finally, in Ashkenazi
Jews, two ancestral mutations, BRCA1 185delAG and
BRCA2 617delT, each appear in the general population atabout 1% frequency [A17].
288. For non-Jewish Caucasian women in the United
Kingdom, on the basis of two population-based databases
on cancer mortality in first-degree relatives of breast andovarian cancer patients, Ford et al. [F14] and Peto et al.
[P16] estimated that the BRCA1 gene frequency is 0.0006(95% CI: 0.0002!0.01). As stated above, the genefrequency of 0.0006 implies that about 1 in 833 women
carries a mutation, and even at the upper confidence limitof 0.01, the carrier frequency would be 1 in 500 (note thatto derive carrier frequency from mutant gene frequency, thefollowing expression is used: carrier frequency of anautosomal dominant mutant genes = 2pq, where p is themutant gene frequency and q = 1-p, the non-mutant genefrequency; see Section V.C). The calculations of Ford et al.
[F14] show that the proportion of breast cancer cases in thegeneral population due to BRCA1 is 7.5% between ages 20
and 29 years, falling to 5.1% between 30 and 39 years, 2.2%
between ages 40 and 49 years, and 1.1% between ages 50 and
70 years. In their paper, Ford et al. noted that an importantunresolved issue is the genetic basis of familial breast cancer
that is not explained by BRCA1 or BRCA2. They estimatedthat the combined gene frequency of other highly penetrant
genes, including BRCA2, might be of the order of 0.0003,(implying that about 1 in 1,600 women carries the mutation).
On the basis of the prevalence estimate of 1 in 833 in nonJewish women [F14] and 1 in 107 for the 185delAG
mutation in Jewish women [S49] and the age-dependent
penetrance curves for the observed risk of breast cancer in
BRCA1 families, Collins [C24] estimated that for womenwith breast cancer, 7.5% of non-Jewish women and 38% ofJewish women under age 30 years would be expected to havegerm-line BRCA1 mutations.
289. A number of studies have examined whether there arecorrelations between the position of the mutation in the
BRCA1 gene and the risk of breast or ovarian cancer(reviewed in [S48]). Truncating BRCA1 mutations infamilies with a high proportion of ovarian cancers tended
to be located in the 5' two thirds of the gene, while families
with predominantly or exclusively breast cancer tended tohave mutations in the 3' third of the gene [G10, H26].
Similarly, with BRCA2, it was found that truncating
mutations in families with the highest risk of ovarian cancer
relative to breast cancer were clustered in a region of
approximately 3.3 kb in exon 11. Other published data on
BRCA2-linked families support this finding [G11].

4. Hereditary colorectal cancers
290. At least 50% of the populations of Western countries
develop a colorectal tumour by the age of 70, and in about 1
in 10 of these individuals progression to malignancy ensues[K41]. Epidemiological studies have suggested that at least
15% of colorectal cancers occur in dominantly inherited
patterns [C65, H30]. The two best-defined familial forms arefamilial adenomatous polyposis (FAP) and hereditary nonpolyposis colon cancer (HNPCC). In the last six years, thegenetic bases for both these syndromes have been discovered,providing new insights into their nature.
(a) Familial adenomatous polyposis (FAP)
291. FAP is an autosomal dominantly inherited disease that
affects about 1 in 7,000 individuals [K41]. Patients with
FAP typically develop hundreds to thousands of colorectal
tumours (called adenomas or adenomatous polyps) during
their second to third decade of life. Although these tumours

ANNEX: HEREDITARY EFFECTS OF RADIATION

are not individually life-threatening, their large numbers
virtually guarantee that some will progress to invasive
lesions (cancers or carcinomas). Additionally, FAP patients
often develop extracolonic manifestations, including retinal
lesions, osteomas, desmoids of the skin, and brain tumours.
292. Patients with germ-line mutations of the APC gene do
not necessarily develop colorectal cancer; they are simply
at a much a greater risk of doing so than the general
population. For tumours to form, additional genetic
alterations are required. Thus, although FAP patients eachdevelop numerous colorectal tumours, only about 1 in 106
colorectal epithelial stem cells gives rise to such a tumour.
Studies in humans with FAP, as well as in mice withanalogous mutations of the murine homolog of APC (Apc),
have suggested that the rate-limiting step in tumour
initiation is a somatic mutation of the wild-type APC allele
inherited from the unaffected parent [I4, L46, L47].
293. The relationship between phenotype and genotype iscomplex, and FAP patients do not develop uniform clinicalfeatures despite the fact that all have mutations of the samegene and most of these mutations result in C-terminallytruncated proteins. For example, retinal lesions (congenital
hypertrophy of the retinal pigment epithelium, or CHRPE)
are associated with truncating mutations between codons
463 and 1387 [O10]. Truncating mutations between codons
1403 and 1578 are associated with increased extracolonic
manifestations such as desmoids and mandibular lesions,but patients with such mutations lack CHRPE [D28]. On
the other hand, patients with identical mutations candevelop dissimilar clinical features: some patients develop
Gardner syndrome (mandibular osteomas and desmoid
tumours) while others do not [N21].
(b) Hereditary non-polyposis colon cancer(HNPCC)294. HNPCC is one of the most common cancer predisposition syndromes and accounts for 2%!4% of allcolorectal cancers in Western countries [L48]. Sporadic
cancers with microsatellite instability (see below) accountfor another 14% of all colorectal cancers [K41]. Assumingthat HNPCC contributes only around 2% of colon cancer
and using a lifetime cumulative colon cancer rate of 3% fora population in the United States [P18], a provisional
estimate can be made of about 1 in 2,000 individuals
carrying the genetic determinants for HNPCC. Affectedindividuals develop tumours of the colon, endometrium,
ovary, and other organs, often before 50 years of age.
295. The search for the genes involved was catalyzed by
the finding of instability of microsatellite DNA and othershort repeat sequences and the accumulation of a large
number of mutations scattered over the whole genome in
HNPCC cells [A9, P19, T15]. Since this looked like thetypical hallmark of a mutator gene at work, it did not takelong before a link was forged between the HNPCC
phenotype and that of mutS and MSH2 mutants in E. coliand S. cervisiae, all of which are deficient in DNA

49

mismatch repair correction. So far, four genes involved in
HNPCC have been cloned [B17, F17, L17, L18, N11, P13],
and both germ-line and somatic mutations in one or theother of the above genes of HNPCC patients have been
identified [F28, H27, L19, M28, V18] and theirinvolvement in DNA mismatch repair demonstrated [P20,
P21, R15] (reviewed in [E14, L48]).
5. Ataxia-telangiectasia
296. Ataxia-telangiectasia is a multisystem disorder. Its
clinical attributes include immune deficiency and a highincidence of neoplasia, especially leukaemia andlymphoma. The clinical, cellular, and genetic features of
A-T and the response of A-T cells to ionizing radiation
have been extensively reviewed [B27, H28, J7, S52, T16,
T17, T18]. The overall incidence of A-T observed in the
United States is about 1 in 300,000, with the highest
observed incidence within the United States being in
Michigan (1 in 90,000) [S53]. For the United Kingdom, theobserved incidence is 1 in 100,000 [P22]. On the basis of
pedigree analysis, in which the gene frequency is estimatedfrom the proportion of affected close relatives ofhomozygous probands, Swift et al. [S53] estimated the most
likely gene frequency to be 0.007 on the assumption that
A-T is a single homogeneous genetic syndrome. This would
correspond to a heterozygote frequency of 1.4%. The A-T
gene has been cloned (designated as ATM) [B28, S54, S55]
and was found to be mutated in all A-T patients, despite thefact that cellular complementation analyses had suggested
the existence of at least six complementation groups.
297. Early retrospective as well as prospective studies havereported that A-T heterozygotes are at a higher risk forseveral cancers, especially female breast cancer [S56, S57].
The estimated relative risk for female breast cancer was 6.8
in the retrospective [S56] and 5.1 in the prospective [S57]study. From these analyses, Swift et al. [S57] estimated thatperhaps as many as 9% of all breast cancer cases in the
United States occur in A-T heterozygotes with a propensity
for early onset. In 1994, Easton [E8] addressed the questionof breast and other cancers in A-T heterozygotes and thecontribution of A-T mutations to familial breast cancer.
Published data on the birth prevalences of A-T and cancers
in A-T heterozygotes, including an updating of cancer
mortality in the 1988 study in the United Kingdom [P22],
were used in the analysis. The main findings were that (a)the contribution of A-T mutations to familial breast cancers
is about 8% for those below 40 years and about 2% for
those between 40 and 59 years, and since only a small
proportion of breast cancers is familial, the contribution of
A-T mutations to familial breast cancer is therefore verysmall, and (b) there is no consistent evidence for increased
risk of any other cancer in A-T heterozygotes.
298. Three papers published in 1996!1997 presented
apparently discrepant results on the risk of breast cancer in
A-T female heterozygotes. In two of these [F29, V11],
there was no evidence for the involvement of mutations in

50

UNSCEAR 2001 REPORT

the A-T gene. In contrast, the work of Athma et al. [A12]showed that A-T heterozygotes may be at an increased risk ofbreast cancer. The authors followed the identified ATM
mutation through the families of those with clinicallyrecognized A-T; analysis of the markers flanking the A-T gene
allowed the authors to identify precisely which female
relatives with breast cancer carry an ATM mutation. On thebasis of the genetic relationship between each relative and theproband, the a priori probability that these should share theATM mutation was calculated. This led to an estimated relativerisk of 3.8 (95% CI: 1.7!8.4) compared with non-carriers.
299. The potential reasons for the apparent discrepancy
between the findings of Athma et al. [A12] and of Fitz
Gerald et al. [F29] were discussed by Bishop and Hopper[B49]. They noted that (a) in the work of FitzGerald et al.,the conclusions are based on finding four A-T
heterozygotes in a total of 603 women, giving a confidence
interval ranging from no increase in risk to a sevenfold
increase in risk, and are, accordingly, not incompatible withthe results of Athma et al. [A12]); (b) because theconfidence interval in the Athma et al. study does notinclude 1.0, it does show significant evidence of an increasein risk; and (c) when relying on such small number ofmutation carriers as the FitzGerald study does or on such asmall number of breast cancers as in the Athma et al. study,
chance is a big factor and the precision of the estimate
suffers (for more details, see Annex F, “DNA repair andmutagenesis”, of the UNSCEAR 2000 Report [U1]).
6. Functions of familial cancer genes
and mechanisms of cancer predisposition
300. As noted in Table 31, the proteins encoded byinherited cancer genes are implicated in a diverse array ofcellular processes, including proliferation, differentiation,
apoptosis, and maintenance of genomic integrity. These
proteins appear to function as transmembrane receptors(MET, PTH, and RET), cytoplasmic regulatory or structuralproteins (NF1, NF2, APC, and PTEN), transcription factors(p53, WT1, RB1, and VHL), cell-cycle factors (CDK4 andp16), or DNA damage repair pathway proteins (MSH2,
MLH1, PMS2, A-TM, BRCA1, BRCA2, FACC, FACA,
XPA, XPB, XPD, and BLM). In several cancer syndromes
for which genetic heterogeneity has been found, such as
HNPCC, inherited melanoma, and breast cancer, all of theimplicated genes appear to function in a conserved
pathway. For instance, inactivation of MSH2, MLH1, andPMS2 in patients with HNPCC alters the fidelity of DNA
mismatch recognition and repair. Mutations in p16 and
CDK4 in individuals with inherited predisposition tomelanoma presumably alter cell-cycle control, including
phosphorylation of p105-RB and entry into the DNA
synthesis (S) phase of the cell cycle.
301. Recent studies of the BRCA1 and BRCA2 proteinssuggest that both interact directly or indirectly withhomologues of the yeast Rad51 protein, which functions in
the repair of double-strand breaks in the DNA [S96, S97].

In addition to showing that BRCA2 binds to Rad51, Sharan
et al. [S97] reported that Brca2-knockout mice show early
embryonic lethality and hypersensitivity to ionizing
radiation, similar to that observed in Rad51-knockout mice[T14]. Brca1-knockout mice also show embryonic lethality[H31]. BRCA1 and Rad51 proteins also show striking colocalization along synaptenemal complexes (junctions
between meiotic chromosomes, necessary for homologous
recombination) [S96].
302. The findings that both Brca2- and Rad51-knockout
mice show hypersensitivity to ionizing radiation inembryonic and trophoblast cells and the known role of
Rad51 in DNA double-strand break repair lend credence tothe view that disruption of this BRCA/Rad51 pathway mightlead to genetic instability. Although the nature of thisputative instability is not clear, studies of Rad51 provide aclue: mouse cells that are deficient for Rad51 show
frequent abnormal mitoses with a markedly reduced
chromosome number, suggesting that alterations of thispathway might lead to gross chromosomal changes [L50].
There are now data that show that BRCA2 gene productfunctionally interacts with the p53 tumour suppressor andthe Rad51 proteins, suggesting that BRCA2 participates inmaintaining genomic integrity [M11].
303. Kinzler and Vogelstein [K26, K41] provided a
stimulating conceptual framework for envisioning cancer
predisposition by dividing the underlying genes into twogroups, gatekeepers and caretakers, and showing how thetwo have different attributes, although inherited mutations
in either group of genes predispose a person to neoplasia.
The principal lines of their reasoning and conclusions are
the following. Gatekeepers are genes that directly regulate
the growth of tumours by inhibiting growth or promoting
death. Each cell type has only one (or a few) gatekeepers,
and inactivation of a given gatekeeper leads to a very
specific distribution of cancer. For example, inherited
mutations of the RB1, VHL, NF1, and APC genes lead totumours of the retina, kidney, Schwann cells, and colon,
respectively. Inactivation of these genes is rate-limiting forthe initiation of a tumour, and both the maternal andpaternal copies must be altered for tumour development.
Cancer-predisposed individuals inherit one copy of themutant gatekeeper gene, and so they need only one
additional (somatic) mutation to initiate neoplasia. Sporadic
tumours arise in those who do not have a germ-line
mutation when both copies of the relevant gatekeeper gene
become mutated somatically. Because the probability ofacquiring a single somatic mutation is far greater than thatof acquiring two such mutations, individuals with ahereditary mutation of a gatekeeper gene are at a muchgreater risk (>103) of developing tumours than the general
population. This is the essence of Knudson’s hypothesis[K21], discussed earlier in this Chapter.
304. In contrast, inactivation of a caretaker gene does notpromote tumour initiation directly. Rather, neoplasia occur
indirectly; inactivation leads to genetic instabilities, which

ANNEX: HEREDITARY EFFECTS OF RADIATION

result in increased mutation of all genes, including
gatekeepers. Once such a tumour is initiated by inactivationof a gatekeeper gene, it may progress rapidly, owing to an
accelerated rate of mutation in other genes that directly
control cell proliferation or death.
305. In dominantly inherited cancer predisposition
syndromes of the caretaker type, the individual inherits asingle mutant caretaker gene, and three subsequent somatic
mutations are usually required to initiate cancer: mutationof the normal caretaker allele inherited from the unaffectedparent, followed by mutation of both alleles of a gatekeeper
gene. Because three mutations are needed, the risk ofcancer in affected families is generally only 5- to 50-foldgreater than in the general population and much less than
the risk in families with inherited defects in a gatekeeper
gene [K26]. Further, mutations in caretaker genes would
not be expected to lead to sporadic cancer very often, as
four mutations would be required (two caretaker alleles
plus two gatekeeper alleles).
306. Known caretaker genes include the nucleotideexcision-repair genes (in XP and HNPCC). To this list canbe added BRCA1 and BRCA2. Consistent with the reasoning mentioned above, mutations in BRCA1 or BRCA2 arerarely found in sporadic cancers. The data of Scully et al.
[S96] and of Sharan et al. [S97] relating BRCA1 andBRCA2 to Rad51 provide a biochemical explanation that
supports the hypothesis. In the case of A-T, the predictedgene product is a protein with considerable homology to a
family of signal transduction molecules encoded by a genefamily known as the phosphatidylinositol-3-kinases involved in cell-cycle control and response to DNA damage(reviewed in [J7]). This family of transducing proteins is
novel in that it responds to DNA damage signals originatingin the cell nucleus rather than the cell membrane andtransmits these signals downstream to enzyme pathways
associated with the maintenance of genomic stability and cell
viability, including protection against ionizing radiation.
7. Summary
307. The material discussed in this Section documents theexistence of a subset of genes in the human genome atwhich germinal mutations predispose the carriers tocancers. These familial cancer genes include the tumoursuppressor genes, DNA replication/repair genes, and at
least three proto-oncogenes. Mutations in most of thesegenes have high penetrance, i.e. they are certain to cause
cancer. About 30 of these genes have been cloned.
308. It has been postulated that in addition to these mutant
genes, there may be a much larger group of genes in which
mutations cause a lower degree of cancer predisposition
and which are therefore difficult to detect. More data areneeded on both the numbers of such cancer-predisposing
genes and the extent of cancer predisposition to reliably
assess the contribution of germinal mutations to thebackground load of cancers in the population.

51

309. The transmission patterns of tumour-suppressor genes
are Mendelian dominant, although at the cellular level they
are recessive, i.e. cancers arise when both copies of thegene are mutated. While for some cancers caused bytumour-suppressor gene mutations (e.g. RB1, NF1, NF2,
and VHL) the loss-of- heterozygosity model (the two-hit
model) proposed by Knudson is adequate to explain the
resultant cancers; for most adult cancers that result from theaccumulation of additional mutations in other genes, thetwo-hit model does not fully describe the genetic changes
that occur.
310. Germinal mutations in the p53 gene cause a rare
cancer syndrome, the Li-Fraumeni syndrome. However, therelevance of p53 gene mutations in the context of humancancers goes far beyond the Li-Fraumeni syndrome; p53
mutations are present in at least 50% of some humancancers.
311. As a result of efforts around the world, considerable
progress has been made in studies of the genetics of breastand ovarian cancers. Germinal mutations in the BRCA1 andBRCA2 genes account for between 6% and 10% of breastand ovarian cancers unselected for family history. In Israel,
this proportion is higher, about 15%. The proportion ofhigh-risk families with breast or ovarian cancer varies
widely between different populations (the range is fromabout 10% in Japan to 79% in Russia for BRCA1-linked
families and 9%!64% for BRCA2-linked families). In
virtually all populations, BRCA1 mutations are much morecommon than BRCA2 mutations. In Iceland, however,BRCA2 mutations are more common, and one specificmutation explains virtually all inherited breast and ovariancancers in Icelandic families. In families with male breast
cancer, BRCA2 mutations are more common than BRCA1
mutations.
312. The best defined forms of familial colorectal cancers
are familial adenomatous polyposis and hereditary nonpolyposis colon cancer. During the past few years, thegenetic bases of these forms have been delineated. For
HNPCC, at least four genes in which mutations predispose
to hereditary non-polyposis colon cancer are now known.
313. Ataxia-telangiectasia, an autosomal recessive,
multisystem disorder that was originally thought on thebasis of cellular complementation tests to be due tomutations in at least six genes, is now known to be due tomutations in one gene. A-T patients (i.e. homozygotes for
the ATM mutations) are afflicted by a variety of neoplasms,
especially leukaemia and lymphoma. A-T heterozygotes
also develop breast cancers, but the proportion of familial
breast cancers attributable to ATM mutations appears small.
The question of an increase in the risk of breast cancers in
A-T heterozygotes is not settled.
314. Evidence from cellular and biochemical studies
supports the view that the familial cancer genes are
involved in the maintenance of genomic integrity (DNAUNSCEAR 2001 REPORT

52

repair, replication, cell-cycle control, and apoptosis) in asystem of interconnected and coordinated network
pathways. Mutations in these genes are therefore expected
to liberate the cells from the constraints imposed by thesegenes, causing uncoordinated growth characteristic ofcancer. The mechanisms appear to be different, dependingon whether the inactivation is in a gatekeeper gene (one that
directly regulates the growth of tumours by inhibiting
growth or promoting cell death, e.g. the tumour-suppressor
genes such as RB1, VHL, and APC genes) or in a caretakergene (inactivation of this type of gene does not directly
promote tumour initiation but results in genetic instabilities
and increased mutations in many genes, including gatekeeper
genes, e.g. XP genes and mismatch repair genes).

B. RADIATION SENSITIVITY
OF CANCER-PREDISPOSED INDIVIDUALS
315. As discussed above, one effect of spontaneous
mutations in genes intimately involved in the maintenanceof genomic integrity is the liberation of cells from normal
cellular constraints, resulting in the uncontrolled
proliferation characteristic of cancer; such mutations also
impart genomic instability. Essentially the same lines ofreasoning can be extended to radiosensitivity by postulatingthat heterozygosity for inherited germ-line mutations inthese genes may render the genome more sensitive/
vulnerable to radiation-induced cancers by exacerbating thealready existing derangement of the cell-cycle machineryand may drive the cells towards overt cancer. Cancerpredisposed individuals may therefore be at a higher risk
for radiation-induced cancers. The human and animal datathat bear on this point are discussed in the following
paragraphs (see also [I1, S32]).

318. In 1991, Swift et al. [S57] (Table 33, item 1) reported
that the blood relatives of A-T patients (female A-T
heterozygotes) have about five times the breast cancer risk of
the general population, that 20% of heterozygotes have been
exposed to diagnostic or occupational exposures of #10 mGy,and that those exposed have about six times the breast cancer
risk of the non-exposed remainder. These data have been
criticized on a variety of grounds [B33, H32, K29, L27] (seealso Annex F, “DNA repair and mutagenesis”, of the
UNSCEAR 2000 Report [U1]). The estimates provided by
Swift et al. [S57] imply relative risks for the non-exposed andexposed heterozygotes of 2.6 and 15.6 times, respectively, therisk of the general population. The ratio of excess relative risks
in the two groups, 1.6 to 14.1, is 8.8, which seems very
unlikely considering that the contribution of mutations in the
A-T gene to familial breast cancers is quite small.
319. The high relative risk for early-onset breast cancers insurvivors of the atomic bombings [L28, T26] is consistent
with the notion that a putative breast-cancer-predisposing
gene mutation may underlie the sensitivity of the genome toradiation-induced cancers. As Land et al. [L28] noted, it
was possible to detect this because for those women
exposed before age 20 years and diagnosed before age 35
years, the rates for both baseline and radiation-related
breast cancer are normally low.
320. The apparent increase in the risk of radiation-induced
breast cancer in the contralateral breast of women who
received radiotherapy before the age of 45 years [B34]
likewise suggests that mutations at a putative gene may affectthe sensitivity of the breast to radiation-induced cancers.

316. Human epidemiological data on the risk of radiationinduced cancers in cancer-predisposed individuals or onradiation-induced mutations in cancer-predisposing genes
are limited at present. However, the resurgence of interestin this question and on-going studies (retrospective
examination of cancer data from this perspective andprospective inquiries, including molecular analysis ofmutations in cancers in human populations exposed toradiation) are likely to provide useful information.

321. A susceptibility gene or genes for Hodgkin's disease
have not yet been identified, and an increased risk of breast
cancer in radiotherapeutically treated Hodgkin's disease
survivors is not well established. The study of Hancock et
al. [H33], however, suggested high breast cancer risks,
again for those irradiated when young. Because of this, thisstudy has been included in Table 33. The retinoblastoma
studies [D13, E11, R18, S30] indicate that irradiated“genetic” cases have a higher risk of second neoplasms
than non-irradiated ones. This finding is highly suggestiveof the possibility that individuals predisposed toretinoblastoma due to inherited RB1 mutation are at ahigher risk for radiation-induced second tumours. Further,
the possible reduction in latency periods for second primarycancers [S30] in irradiated retinoblastoma cases is
consistent with expectations discussed earlier.

317. Data that provide some evidence for the enhanced
sensitivity of cancer-predisposed individuals to radiationinduced cancers and for a reduction in tumour latencies are
summarized in Table 33. Note that not all the materialpresented in this table pertains to cancers, and a sizeable
proportion of the studies did not report significant
differences; the estimated relative risks have wide
confidence limits. The evidence presented is therefore
suggestive but by no means compelling. It does, however,allow identifying situations that may merit further study.

322. An increase in nevoid basal-cell carcinoma syndromein radiotherapeutically treated medulloblastoma cases [S30,
S31] has been noted. These data, like data from some of theretinoblastoma studies, also suggest a reduction in latency
period in the irradiated individuals. The evidence insurvivors of the atomic bombings [S61] for a high excess
relative risk of stomach cancer mortality for those who
were exposed at less than 10 years of age may also suggest
the existence of a cancer-predisposing radiosensitive genemutation for this type of cancer.

1. Human epidemiological andmolecular studies

ANNEX: HEREDITARY EFFECTS OF RADIATION

2. Mouse models
323. In the past decade, advances in molecular and cellbiology, gene targeting, and embryonic stem-cell technologies have led to the creation of mouse models that havegerm-line mutations of various tumour-suppressor genes.
These models permit systematic analyses of their functions
within the mammalian organism and are potentially
important models for familial cancer syndromes in humans.
They have demonstrated the importance of the function ofthese genes in embryonic development and tumorigenesis
and have also revealed that not all these models emulate
their corresponding human syndromes [J4]. The subject has
been recently reviewed [V19]. Table 34 summarizes the 10mouse models currently available and their attributes. Onlya limited number of radiation studies have been carried out,
however.
(a) Studies with mice heterozygous for a
p53 mutation or lacking the p53 gene324. In experiments involving 4 Gy whole-body gamma
irradiation of 7!12-week-old mice that were wild-type orheterozygotes for a p53 mutation, Kemp et al. [K25] foundthat (a) none of the irradiated wild-type mice developed
tumours; (b) unirradiated heterozygous mice developed
lymphomas and sarcomas at a median age of more than 70
weeks, whereas irradiated heterozygotes developed tumours(also lymphomas and sarcomas, but with fewer
osteosarcomas and more lymphomas) at a median age ofabout 40 weeks; and (c) 20 of 23 (96%) of the tumoursfrom irradiated heterozygotes showed loss of the wild-type
p53 allele (detected through Southern analysis), suggestingthat the p53 gene itself may be a target for radiationinduced loss of the wild-type allele. No firm conclusions
can as yet be drawn, however, because the sample sizes
were small and the period of observation was not longenough, especially for irradiated wild-type mice.
325. In untreated control heterozygotes, 5 of 7 tumours(71%) showed loss of the wild-type allele. In otherpublished studies with untreated p53 heterozygotes cited by
the authors, the frequencies of loss of the wild-type allele
in tumours were also lower than in the radiation experimentmentioned above [18 of 33 tumours (55%), 5 of 9 tumours(56%), and 9 of 12 tumours (75%)].
326. Another important finding in the study of Kemp et al.
is that in p53 heterozygotes, 14 of 17 (82%) radiationinduced tumours showed duplication of the mutant allele,
whereas this was true of only 1 in 5 in spontaneous
tumours. The authors suggested that mitotic recombination,
non-disjunction with reduplication, or gene conversion
could explain the results in the majority of radiationinduced tumours; in spontaneous tumours, the pattern ofloss of heterozygosity with no duplication was consistent
with deletion of the wild-type allele.
327. In the same study, but involving seven-week-old p53
null mice and 4 Gy of irradiation, Kemp et al. [K25] noted

53

that there was no decrease in tumour latency, presumably
because of the already very rapid rate of spontaneous
tumour development in these mice. However, with six-dayold mice irradiated with 4 Gy and two-day-old mice with
1 Gy, there was a decrease in tumour latency from a medianof 21 weeks of age in controls to 14!15 weeks of age in thenull mice. Additionally, in p53 null mice, multiple tumours(23 tumours in 14 mice) were observed in the 4 Gy groupbut in only 1 mouse in the 1 Gy group.
328. In follow-up studies, Bouffler et al. [B48] compared
the cytogenetic response of wild-type, p53 heterozygous,
and p53 null mice by analysing stable structural andnumerical chromosomal aberrations in bone marrow cell
populations sampled 29!30 days after 3 Gy irradiation.
Additionally, chromatid damage repair, sister chromatid
exchanges (SCEs), and mitotic delay were studied in spleencells in vitro. The important findings were the following:(a) in p53 heterozygous and p53 null mice, the spontaneous
frequencies of stable structural and numerical aberrations
were about 20-fold higher than in the wild-type; (b) there
was no excessive induction of stable structural chromosomal aberrations in vivo, and in vitro studies provided noevidence of a significant effect of p53 deficiency withrespect to chromatid damage repair or SCE induction after
irradiation; and (c) in contrast, p53-deficient genotypes
were 10- to 15-fold more sensitive to the induction ofnumerical chromosomal changes (chromosome gains >>losses) and in the in vitro studies, there was a profounddefect in the operation of post-radiation mitotic delay inspleen cells from p53-deficient mice, implying a failure of
a G2/M cell-cycle checkpoint for repair. The authors concluded that this checkpoint failure might underlie increased
hyperploidy, which subsequently provided the drive for theincreased tumorigenic radiosensitivity of p53-deficientmice.
(b) Studies with Brca2 mutation in mice
329. In the work of Sharan et al. [S97], blastocysts wereisolated at day 3.5 from crosses of Brca2/+ females matedto Brca2/+ males and exposed to 4 Gy from acute gammaradiation and then cultured for seven days. Survival andoutgrowth of the inner cell mass and trophoblast cellnumbers were compared in homozygous mutant,heterozygotes, and normal embryos. In the unirradiatedseries, the values for the above were the same for the
mutant and control embryos; in the irradiated series, theinner cell mass outgrowth was marginally reduced in wildtype and heterozygous embryos and totally ablated in thehomozygotes. Additionally, whereas gamma radiation
reduced the number of trophoblast cells in wild-type andheterozygous embryos slightly, in homozygous embryos
this effect was more pronounced (reduction to about one
half of that seen in the cells derived from the wild-type andheterozygous embryos). These findings, which are similar
to those obtained with Rad51 mouse mutants, have beeninterpreted to mean that the cell proliferation defect ofhomozygotes is probably secondary to a response to a
defect in DNA repair.

UNSCEAR 2001 REPORT

54

3. The rat model for thehuman tuberous sclerosis-2
330. Hereditary renal carcinoma in the rat, an autosomal
dominant cancer, was originally described by Eker andMossige [E18]. At the histological level, these carcinomas
develop through multiple stages from early pre-neoplastic
lesions, which begin to appear at 2!3 months of age, toadenomas in virtually all heterozygotes by the age of one
year. Homozygotes die in the fetal stage. Kobayashi et al.
[K27] and Hino et al. [H15] found that the Eker mutation
was in fact a germ-line insertion of an approximately 5 kb
DNA fragment in the tuberous sclerosis (Tsc2) gene locatedon rat chromosome 10p. Although the overall phenotypic
manifestations in human tuberous sclerosis patients differ
from that of Tsc2 mutation in rats in many respects, theyshare a strong predisposition to renal cancers.
331. Hino et al. [H16] irradiated male and female rats
carrying the Eker mutation with gamma-ray doses of 3, 6,
and 9 Gy to the renal region. The animals were killed at
10!11 months, and the incidence of kidney tumours wasassessed in serial sections. It was found that in both sexes,
the mean number of tumours per animal, calculated
according to a linear regression analysis, increased withdose. In males, for example, it was 59 at 9 Gy vs. 4.4 incontrols; in females, it was 30 vs. 2.8, which is some 11 to
13-fold higher. Taking into account the limitations of thisstudy (the heterozygous and normal animals could not be
identified before irradiation and the irradiated animals were
therefore made up of equal numbers of +/+ and +/!
animals; the mutant homozygotes (!/!) die in utero; andthe radiation effects seen were in the heterozygotes andnormal animals), the ICRP Task Group [I1] made apreliminary estimate that the tumorigenic radiosensitivity of
the +/! animals may be 170 times that of +/+ animals. It
cautioned that since +/! animals develop these tumours at
an earlier age than +/+ animals, the above estimate may
overestimate the true tumorigenic radiosensitivity.
4. Summary
332. The modest amount of human epidemiological datathat are available are consistent with the possibility thatheterozygotes for mutations in familial cancer genes may
exhibit enhanced tumorigenic radiosensitivity, although nofirm conclusions can as yet be drawn about the magnitudeof such an effect. The earlier claims for a higher risk ofradiation-induced breast cancers in women heterozygous
for the ATM mutation no longer appear tenable.
333. Mice heterozygous for the p53 mutations are
susceptible to radiation-induced tumours, and these tumours
develop with shorter latency periods. The limited data
currently available from these studies suggest that the p53
gene itself may be a target for radiation-induced mutations.
New data on Brca2 mutations in mice suggest that cells
derived from homozygotes are very sensitive to radiationinduced cell-killing effects.

334. Data from the Eker rat model for mutations in thehuman tuberous sclerosis gene (TSC2) show that heterozygotes may be more sensitive than the wild type for the
induction of renal tumours.

C. COMPUTATIONAL MODELLINGTO ESTIMATE RADIATION RISKIN A HETEROGENEOUS POPULATION
335. The material discussed in the preceding Sections of
this Chapter substantiates the premise that individuals witha genetic predisposition to cancer as a result of germinal
mutations exist in human populations and that they may
also be sensitive to cancers induced by radiation. It is
possible, using principles of population genetics, toestimate the amount by which the radiation risks in such aheterogeneous population will be increased compared to a
population that does not contain such subgroups.
336. The basic characteristic of gene frequency in large
populations is its stability over time in the absence ofdifferences in viability or fertility among the genotypes atthe locus under consideration. In the further absence ofassortative mating, i.e. the tendency of like to mate withlike, migration, mutation, and geographical subdivision of
the population, genotypic frequencies also remain constantfrom generation to generation. This is reflected, in the caseof genetic diseases, as stable prevalences of genetic
diseases in the population. These properties are summarized
in the Hardy-Weinberg equilibrium concept, which is oneof the fundamental concepts in population genetics whenlarge random-mating populations are considered.
1. Numerical illustration
for an irradiated population
337. A Mendelian one-locus, two-allele dominant model ofcancer predisposition and radiosensitivity can be illustrated
by the following numerical example. Consider a single
autosomal locus at which there are two alleles, the normal
or wild-type allele, a, and the dominant cancer-predisposing
mutant allele, A, in a population under Hardy-Weinberg
equilibrium. The individuals in the population will have one of
the following three genotypes: AA, Aa, or aa. If the frequencyof the mutant allele, A, is 0.01, then the frequency of the nonmutant allele, a, is 0.99 and the distribution of genotypes in a
population of 10,000 is 1(AA), 198(Aa), and 9,801(aa).
338. Situation 1. Assume that none of the genotypes iscancer-predisposed and that the background cancer risk is
0.001 for all genotypes. In 10,000 individuals, one would
therefore expect 10 cancers, most of them in aa individuals.
339. Situation 2. Assume now that the population receives
radiation at a dose that confers a risk of 0.01. The numberof cancers due to radiation exposure will be 100. Most of
the induced cancers will again occur in aa individuals
because of their high frequency. So, the total number ofcancers in this population is 100 + 10 = 110.

ANNEX: HEREDITARY EFFECTS OF RADIATION

340. Situation 3. Assume that the A allele confers cancer
susceptibility and that AA and Aa individuals are cancerpredisposed (“susceptibles”) and to the same extent andthat aa individuals are not (“non-susceptibles”). Assume
further that the background cancer risk for aa individuals is
0.001 (as in situation 1) and that the risk for AA and Aa
individuals is 0.1, i.e. the last two genotypes have a 100fold higher “normal” cancer risk than aa individuals. In thissituation, the distribution of the expected number of cancers
will be as follows: for AA: 1 × 0.1 = 0.1; for Aa: 198 × 0.1=19.8; for aa: 9,801 × 0.001 = 9.8. The total is about 30.
Note that a large proportion of the cancers (~20/30) occur
in the susceptible individuals.
341. Situation 4. Assume that the above population is
irradiated and that the dose is such that it confers a risk of
0.01 to aa but that AA and Aa individuals respond with arisk of 0.5 (50-fold higher). The expected number ofradiation-induced cancers will be as follows: for AA, 1 ×
0.5 = 0.5; for Aa, 198 × 0.5 = 99; for aa, 9,801 × 0.01 = 98.
The total is about 198. The total number of cancers is 198+ 30 = 228 in 10,000 individuals.
342. It is clear that in a homogeneous population (nocancer-predisposing genotypes present), the total number ofcancers is 110, i.e. 10 background and 100 induced. In aheterogeneous population, with 199/10,000, or roughly 2%,of individuals cancer-prone (100x) and more radiosensitive(50x) and assuming that all these cancers are due tomutations at this locus, the radiation cancer risk in thispopulation is greater by a factor of about 2 (i.e. 228/110)
than in a homogeneous population.
343. For the sake of illustration, no account was taken in
the above example of the fact that in most cancers (e.g.
breast and colorectal cancers) the proportion attributable toallelic variation at a single locus is small or of the fact thatseveral concomitant variables such as age and radiationdose influence the risk. Models taking into account theabove factors and a number of others (e.g. different mutant
gene frequencies, strengths of predisposition,
radiosensitivity differentials, proportions of cancers
attributable to mutant genes at given loci) have been
published [C26, C40, C41]. While the derivations ofexpressions for the different epidemiological measures ofrisk need not be of concern here, some of the important
assumptions of the model, the general strategies, and main
conclusions are relevant and are discussed below.
2. Results of computational modelling
344. Assumptions. The model developed by Chakraborty
and Sankaranarayanan [C40] and Chakraborty et al. [C41]is a one-locus, two-allele autosomal dominant model ofcancer predisposition and radiosensitivity. The model in thelatter paper is an improved version and is considered below.
Its principal assumptions are the following:(a)the dominant allele A confers cancer predisposition
and a is the normal allele;

(b)

(c)
(d)
(e)

55

the predisposed genotypes, i.e. the homozygotes (AA)and heterozygotes (Aa), also have enhanced
sensitivity to radiation-induced cancers comparedwith the non-predisposed genotype (aa);only a proportion of cancers (π) of a given type are
due to the locus under study;
the genotype frequencies conform to Hardy-Weinberg
expectations; anddifferential radiosensitivity is mediated through thesame predisposing locus.

345. Penetrance (i.e. the fraction of mutation carriers who
manifest a specific phenotype associated with that mutation)is represented by the parameter θ. When θ has the value 1,
there is complete penetrance, meaning all individuals having
the mutant gene manifest the phenotype; when it is less than
1, the mutant gene is incompletely penetrant.
346. To incorporate dose dependence of radiosensitivity
differentials in the model, it is assumed that in the nonpredisposed individuals (aa), a radiation dose D increases
cancer risk by a factor (1 + βD) in comparison with thebackground risk (R0). In the predisposed genotypes (the AA
homozygotes and a portion of the Aa heterozygotes), thesame dose of radiation increases the cancer risk by a factor(1 + βDRi).
347. Mathematical expressions were derived incorporating
all the above to provide estimates of total risk, RT(D), in theirradiated population at dose D; relative risk, RR(D), i.e.
the risk of cancer in cancer-predisposed radiosensitive
genotypes compared with the risk in non-predisposed
genotypes; attributable fraction, AF(D), i.e. the fraction ofcancers attributable to the predisposed genotypes; and thefraction due to radiosensitivity differentials alone, α(D).
348. Choice of parameter values to study model
predictions. The parameter values chosen come from dataon breast cancers discussed in Chapter V of this Annex andfrom data on breast cancers in the survivors of the atomic
bombings [T20]. They are as follows:
(a)
(b)

(c)
(d)

(e)
(f)
(g)
(h)
(i)

mutant gene frequency, p, in non-Jewish Caucasian
women = 0.0006 [F14, P16];
proportion of breast cancers, π, attributable to BRCA1
mutations = 1.7% for those diagnosed before age 70
years and 7.5% for those diagnosed before age 30
years;
mutant gene frequency, p, Ashkenazi Jewish women= 0.0047 [S49];
proportion of breast cancers, π, due to BRCA1
mutations diagnosed before age 30 years in
Ashkenazi Jewish women = 0.38 [C24];
penetrance, θ = 0.50, 0.75, and 1.00;
slope of the dose-effect curve, β = 2.0 Gy1 [T26];
range of predisposition strength, Rp (arbitrary) = 10 to
1,000;
range of radiosensitivity differentials for thepredisposed genotypes, Ri (arbitrary) = 10 to 100; andradiation doses (arbitrary) = 0.5, 1.0, and 2.0 Gy.

UNSCEAR 2001 REPORT

56

349. Results. The results obtained for the different combinations of parameter values for breast cancer are illustrated
in Table 35. Note that RR quantifies the risk of radiationinduced cancer in a population in the presence ofpredisposition and radiosensitivity differentials relative to thatrisk in the absence of both these factors. The results shown in
the first two parts of Table 35 may be deemed applicable toradiation-induced breast cancers in non-Jewish Caucasian
women (p = 0.0006 and π = 1.7% for women under 70 yearsof age and 7.5% for those under 30 years of age).

354. A Mendelian one-locus, two-allele model of cancer
predisposition and radiosensitivity is discussed and used toassess the impact of cancer predisposition andradiosensitivity differentials on cancer risks in an irradiatedpopulation. The model predictions are illustrated using
breast cancers in non-Jewish Caucasian and Ashkenazi
Jewish women as examples and ranges of possible values
for the strength of predisposition and radiosensitivity
differentials.

350. As can be seen from Table 35, RR values aredetectably different from 1 only when Ri and Rp are both very
high (e.g. at Ri = 100 and Rp = 1,000, for 100% penetrance
RR becomes 2.64 at 2.0 Gy). Similarly, the proportion ofexcess cancers in the irradiated population that is due topredisposition and radiosensitivity, also called the attributablefraction (AF), is also low unless both Ri and Rp are high.
However, most of these excess cancers are contributed by theradiosensitivity differential alone (i.e. α is quite high evenwhen RR is close to 1 and AF is close to zero). With anincrease in π, all risk measures become more pronounced forthe same levels of Ri and Rp.

355. Comparisons of radiation cancer risks are madebetween a heterogeneous population, i.e. one that consistsof cancer-predisposed and non-predisposed individuals andwhere the predisposed individuals are assumed to be moresensitive to radiation-induced cancers, and a homogeneous
population, i.e. one in which there are no cancerpredisposed subgroups and all individuals are equallysensitive to radiation-induced cancers. It is shown that afterradiation exposure the ratio of risks between the above two
populations, the relative risks, increases with increasing
dose, but the dose dependence of the relative risks
diminishes at higher doses.

351. Other general observations that can be made from thefirst two parts of Table 35 are the following: (a) an increasein penetrance, θ, causes an increase in RR and AF; (b) at alllevels of θ and combinations of Ri and Rp values, the RR and
AF increase with radiation dose, but the dose dependence of
RR, AF, and α diminishes at higher doses; (c) incomplete
penetrance dilutes the effect; and (d) incomplete penetrance
and dose dependence of radiosensitivity differential do notchange the main conclusion, namely that RR, AF, and α
increase with an increase in mutant gene frequency and/or an
increase in the proportion, π, of cancers due to thepredisposing allele.
352. The third part of Table 35, which may be applicable toradiation-induced breast cancers in Ashkenazi Jewish womenfor cancers before age 30 years, shows that when both p andπ are high, the risks become appreciably higher at lower
values of Ri and Rp. Even in such high-risk situations a larger
value of Rp (rather than a larger one of Ri) contributes to theelevation of risk in a more pronounced manner.
3. Summary
353. Genetic predisposition to cancer and enhanced
radiosensitivity of the susceptible genomes have an impact
on radiation cancer risks.

356. Likewise, the attributable risk, which is the proportionof cancers due to both increased cancer susceptibility andincreased radiosensitivity, and the proportion of attributablerisk due to radiosensitivity differentials alone increase withan increase in dose, and the dose dependence of eachmeasurement also diminishes at higher doses. However,when the proportion of cancers due to the susceptible
genotypes is small (<10%), as is likely to be the case forbreast cancers in non-Ashkenazi women, the increase in therelative risk and attributable risk are marked only when
there are very large increases in cancer susceptibility(>1,000-fold) and radiosensitivity (>100-fold) in thesusceptible group.

357. When the proportion of cancers due to the susceptible
genotypes is appreciable ($10%), as may be the case forbreast cancer in Ashkenazi Jewish women, there may belarge increases in the relative risk and attributable risk forrelatively modest increases in cancer susceptibility (>10fold) and radiosensitivity (>100-fold) in the susceptible
subgroup. For any given combination of strength ofpredisposition and radiosensitivity differential, incomplete
penetrance dilutes the effect.

ANNEX: HEREDITARY EFFECTS OF RADIATION

57

VI. OTHER RELEVANT STUDIES
A. HUMAN STUDIES
1. Genetic disease in offspringof long-term survivorsof childhood and adolescent cancer
358. The work of Byrne et al. [B69] addressed the questionof genetic risks to the offspring of survivors of childhood
and adolescent cancer. Genetic disease was defined as a
syndrome of malformations known to have an associatedcytogenetic abnormality (regardless of whether karyotypes
were available), a single-gene (i.e. Mendelian) disorder, or
any one of the 15 common simple birth defects. The data
and analysis pertain to 2,198 offspring of 1,092 cancer
survivors and 4,544 offspring of 2,032 control parents; ofthe cancer survivors, 72.8% received non-mutagenic
therapy and the remainder received therapy that could beclassified as mutagenic. The authors noted that the dosagesof radiation and chemotherapeutic agents were notquantified because of the complexities involved, but they
can be assumed to have been high.
359. The list of Mendelian diseases included achondroplasia, acrocephalosyndactyly, aniridia, Apert syndrome,
myotonic dystrophy, Gardner syndrome, Marfan syndrome,
multiple polyposis, neurofibromatosis, osteogenesis
imperfecta, polycystic kidney disease, retinoblastoma, andSteinert syndrome. The two main findings were thefollowing: (a) when types of genetic disease, as defined
above, were examined individually or together, the rates ofthese defects in offspring of survivors and of controls were
not significantly different (3.4% vs. 3.1%), and (b) there
was no association of the risk of sporadic genetic disease inchildren with the treatment status of the parents (acondition was considered sporadic if in the opinion of tworeviewing physicians, no relative had the same or a related
genetic disease). An earlier report of this study [B21]
showed that radiation therapy below the diaphragm
depressed fertility in both sexes and that chemotherapy withalkylating agents was associated with decreased fertility inmale survivors. Byrne et al. [B69] noted that, “… although
this may represent genetic damage, infertility is acomplicated outcome with many causes … [and] a genetic
aetiology for infertility has not been studied”.
2. Reproductive outcome inwomen irradiated during infancy
for skin haemangiomas
360. Källen et al. [K30] conducted a detailed analysis of
the possible impact of early gonadal irradiation with beta
particles, gamma rays, and x rays by examining 19,494
infants born to 10,237 women who had been irradiated at
the age of 18 months or less for skin haemangiomas in
Sweden. The ovarian dose distribution of the mothers andthe numbers of children in the different maternal dosegroups were as follows: <0.01 Gy (14.7% of women, 4,949
children); 0.01!0.05 Gy (43.7%, 8,522 children);
0.06!0.1 Gy (13.3%, 2,586 children); 0.11!0.2 Gy (10.3%,
2,014 children); 0.21!0.5 Gy (6.7%, 1,301 children);>0.5 Gy (0.6%, 122 children). The mean ovarian dose was
0.06 Gy and the maximum, 8.55 Gy.
361. The main findings were the following:
(a)

(b)

(c)

(d)

(e)

women with ovarian doses of more than 0.01 Gy had
fewer infants than women who received less than
0.01 Gy (14,545 children vs. 15,401 expected);
there was a small excess of perinatal deaths(stillbirths plus early neonatal deaths) in the >0.01 Gygroups, but this was not related to dose;overall, there was a small excess in the rate ofcongenital malformations (about 8%), but again, thiswas unrelated to dose and was presumably the resultof variable recording practices. Only for neural tube
defects was there a statistically significant increasingrate with maternal ovarian dose and for cleft lip withor without cleft palate, although at levels significantly
below expectation; both findings may represent
chance results of multiple statistical testing;the frequencies of infants with low birth weight(<2,500 g) and of infants born pre-term (<37 weeks
of gestation) were lower than expected compared withthose calculated from all births in Sweden; theauthors interpreted these findings as a reasonable
consequence of the longer educational durations andthe fact that these women smoked less; andthere was no increase in the rate of infants with
Down’s syndrome or in childhood malignancies.

3. Possible genetic effects of radiation
exposures resulting from the Chernobyl accident
or from living in the vicinityof a nuclear power plant(a) Down’s syndrome andcongenital abnormalities
362. In the UNSCEAR 1993 Report [U4], it was
mentioned that the results of Czeizel et al. [C23] had
showed no increase in the prevalence of selected sentinel
anomalies (predominantly autosomal dominant andX-linked diseases of childhood onset and Down's
syndrome) in Hungary after the Chernobyl accident.
Sperling et al. [S35], however, reported that in West Berlin,
nine months after the Chernobyl accident (i.e. in January1987), there was a significant increase in Down's
syndrome; a cluster of 12 cases was found compared with
two or three expected. (Note that the term cluster is usedhere in an epidemiological sense and not in the sense usedin genetics to describe mutations originating from a single

58

UNSCEAR 2001 REPORT

progenitor cell.) After excluding factors that might have
explained the increase, including maternal age distribution,
only exposure to radiation after the Chernobyl accident
remained. In six of the seven cases that could be
cytogenetically studied, the extra chromosome was foundto be of maternal origin. The occurrence of the above cases
coincided with the time of highest radiation exposure (whenthe conceptions should have occurred), particularly
inhalation of 131I, prompting the authors to suggest that
exposure to ionizing radiation, especially 131I, might be thecausal factor. This interpretation is open to doubt, however,in view of the very low radiation doses.
363. In another study carried out in Germany, Burkart et al.
[B26] recorded an increase in Down's syndrome births (10observed vs. 4.4 expected) in northern Bavaria in December
1986, close in time to the occurrence of the Down's
syndrome cluster in West Berlin. Further analysis revealed
that the increase in northern Bavaria was due mainly to four
diagnoses made in the urban areas of Nuremberg, Fuerth,and Erlangen. Chernobyl radiation exposure could be excluded as the cause, because the areas had received very
little contamination and because the peak occurred in
December 1986, one month before the occurrence of the
Down's syndrome cluster in West Berlin.
364. In commenting on the Berlin cluster, Burkart et al.
[B26] noted that (a) biological considerations argue against
Chernobyl fallout as a plausible cause of the Berlin cluster;(b) the Chernobyl exposure cannot have been a common
causal factor in northern Bavaria and West Berlin, since thehigher rates in the former area can be traced to a time period
shortly before fallout took place; and (c) in the absence offurther clues, the close temporal relationship of the Berlin
and the Bavarian clusters should be carefully analysed togenerate hypotheses on a common factor influencing theincidence of Down's syndrome.
365. De Wals et al. [D26] reported on the results of a survey
on the incidence of chromosomal syndromes (including
Down's syndrome) in Europe registered in 19 birth defects
registries from January 1986 to March 1987. The study
population comprised 764 chromosomal syndrome cases, ofwhich 621 were Down's syndrome cases in 482,193 totalbirths. No evidence for any clustering was found in any of theregistries for the period January to March 1987. Analysis of
the frequency rates by month of conception also did notindicate any increase after May 1986.
366. Little [L30] provided a comprehensive review ofstudies undertaken in the wake of the Chernobyl accident
with particular reference to those on congenital abnormalities
and other adverse reproductive outcomes. The main points
that emerge are the following: (a) an increased frequency of
Down's syndrome in West Berlin in January 1987 andincreases in the frequency of neural tube defects in several
small hospital-based series in Turkey are not confirmed inlarger and more representative series in Europe; (b) no clear
changes are apparent in the birth prevalence of congenital
anomalies in Belarus or the Ukraine (the republics with thehighest exposures), although the data are difficult to interpretbecause the methods of acquisition were not described andwere not reported in full; (c) the conclusion that there is no
consistent evidence on congenital anomalies applies to othermeasured outcomes of pregnancy as well (miscarriages,
perinatal mortality and low birth weight, sex ratio shifts, andmultiple births); (d) there is evidence of indirect effects: anincrease in induced abortions due to anxieties created, which
is substantial enough to show up as a reduction in the total
number of births; (e) no data are available on the reproductive
outcomes of women pregnant at the time of the accident who
were evacuated from the 30-km zone of contamination, ofworkers on site at the time of the accident, or of recovery
operation workers; and (f) no data are available from severalof the countries closest to the Chernobyl area (see also [B5,G9]).
367. Siffel et al. [S34] studied the occurrence of sentinel
anomalies (also including congenital abnormalities andDown's syndrome) in children (n = 26,893) born within a
20-km radius of the Paks nuclear power plant in Hungary.
Comparisons of the frequencies of sentinel anomalies,
congenital abnormalities, unidentified multiple congenitalabnormalities, and Down's syndrome before and after theoperation of the power plant revealed no significant
differences. It was concluded that the slightly elevatedradiation background (0.2!0.4 µSv a1) attributable to theoperation of the power plant did not affect germinal andsomatic mutation rates. Izhevsky et al. [I9], carried out aretrospective study on the pregnancy outcomes and prereproductive mortality of children of workers of the Mayaknuclear power plant. The workers were occupationally
exposed to gamma radiation during 1948!1954, and dataon doses and medical documents of the families wereavailable. The authors found indications for a possible
increase in pre-reproductive mortality of the children of
exposed mothers.

(b) Mutations in human minisatellite loci368. Background. As discussed in paragraph 52, asignificant fraction of the eukaryotic (including the human)
genome is composed of repetitive-sequence DNA. Much ofthis DNA has been grouped into various families based onsequence, organization, and size [S92]. In some of thesefamilies, variations in sequence and/or in the number of
repeat units occur within and between species. One class of
the repetitive DNA elements, simple tandem repeats, ischaracterized by a motif of short oligonucleotide coresequences reiterated in tandem arrays. These elements havebeen variously called minisatellites [J15], midisatellites[N17], and microsatellites [L34]. This repetitive DNA has
been found to occur at many highly polymorphic(hypervariable) loci dispersed throughout the genome. The
exceptionally high levels of polymorphic variation at theseloci are due to variation in the number of tandem repeat
cores. Family studies have demonstrated that simple tandem
repeat loci are inherited in a co-dominant Mendelianfashion [K42] (see Jeffreys et al. [J5] for a recent review.)

ANNEX: HEREDITARY EFFECTS OF RADIATION

369. The diversity of alleles at both human and mouseminisatellite loci is a result of mutation rates that are ordersof magnitude higher than those of most protein-coding
genes (e.g. [J5, J16, K42, K43, S63]). The principal
advantage of these high mutation rates is that significant
changes can be detected with smaller sample sizes. There isevidence to suggest that in somatic cells, the new length
alleles may arise by mitotic recombination or unequal sister
chromatid exchange; replication slippage does not appear
to be a dominant process [J5, W22]. Analysis of minisatellite mutations in sperm suggests that they may arise by
gene-conversion-like events, the reasonable candidate stage
being meiosis [J5]. Worth noting here is that minisatellite
variations very rarely have phenotypic effects (e.g.
trinucleotide repeat expansions; see Table 8).
370. Radiation-induced minisatellite mutations. Dubrova
et al. [D19] studied germ-line minisatellite mutations amongchildren born between February and September 1994 toparents who were continuously resident in heavily polluted
areas of the Mogilev region of Belarus after the Chernobyl
accident. Blood samples were collected from 79 families(father, mother, and child) for DNA analysis. The control
sample consisted of 105 non-irradiated Caucasian families
from the United Kingdom, sex-matched to the offspring of
the exposed group. DNA fingerprints were produced from allfamilies by using the multi-locus minisatellite probe 33.15
and two hypervariable single-locus probes, MS1 and MS31.
Additionally, most families were profiled with the minisatellite probes MS32 and CEB1. For the Mogilev families,
the level of 137Cs surface contamination was used as a dose
measure, i.e. families were divided according to the median137
Cs contamination levels into those inhabiting less contaminated areas (<250 kBq m2) and more contaminated areas(>250 kBq m2).
371. The important findings are that (a) the frequency ofminisatellite mutations is about twice as high in the childrenof the exposed families as in controls, and (b) the mutation
frequencies show a correlation with the level of caesium
contamination as demarcated above. The authors suggested
that these findings are consistent with radiation inductionof germ-line mutations but also noted that other nonradioactive contaminants from Chernobyl, such as heavy
metals, could be responsible for the observed, apparently
dose-dependent increase in the mutation rate.
372. In a subsequent extension of the above study, Dubrova
et al. [D29] recruited 48 additional families from the affected
region and used five additional minisatellite probes, including
the multi-locus probe 33.6 and four hypervariable singlelocus probes. These additional data confirmed the twofold
higher mutation rate in children of exposed parents than inthose of non-exposed. The spectra of mutations seen in theunexposed and exposed groups were indistinguishable,suggesting that the increased mutation frequency observed
over multiple loci arise indirectly by some mechanism thatenhances spontaneous minisatellite mutations. Obviously,
further work is needed to clarify the structural basis ofradiation-induced minisatellite mutations.

59373. It has been argued [N19] that the use of control
families from the United Kingdom introduces a significant
confounding factor as well as possible ethnic/genetic
differences from the population of Belarus. Secondly, thefamilies in the United Kingdom may have experienceddifferent patterns of environmental exposure to potentiallymutagenic industrial and agricultural chemicals that might
have contributed germ-line variation. Thirdly, it is not clear
from the surface contamination maps of the region why
control families receiving insignificant radiation doses were
not obtained or why a second set of controls of children
conceived prior to the accident could not be identified.
Fourth, the trend in mutation frequency with likely dose
received is also dependent on the division of families into
just two groups on the basis of radiocaesium contamination;an analysis of trends based on individual assessment ofcontamination would be more revealing. Finally, from thedata presented, it would seem that the germ-line doses in
the whole region remain sufficiently uncertain to question
the true significance of a less than twofold difference inmutation frequency between the two groups.
374. In a pilot feasibility study carried out on the childrenof survivors of the atomic bombings in Japan, Kodaira et al.
[K44] (see also Neel [N18] for a commentary) screened 64
children from 50 exposed families and 60 from 50 control
families for mutations at six minisatellite loci using thefollowing probes: Pc-1, λTM-18, ChdTC-15, pλg3, λMS-1,
and CEB-1. The cell lines chosen for this study were fromthe most heavily exposed parents, whose average parental
combined gonadal equivalent dose was 1.9 Sv. A total of 28
mutations were found, but these were at the pλg3, λMS-1,
and CEB-1 loci (there were no mutations at the other threeloci). Twenty-two of these were in controls (of 1,098 alleles
tested, i.e. 2%), six in the children derived from theirradiated gametes (among 390 alleles, i.e. 1.5%). Thus,
there was no significant difference in mutation frequencies.
Since they used different loci from Dubrova et al., theauthors suggested that the use of the DNA fingerprintprobes 33.16 and 33.15 may be worthwhile in studies of thechildren of survivors of the atomic bombings. However, thesubsequent preliminary results of Kodaira and Satoh [K50]
and Satoh and Kodaira [S44] using the above two probes
showed no significant difference in mutation frequencies
between the children of the exposed parents and the control
children.
4. Summary
375. Two studies of the genetic effects of radiation inhumans have recently been published. One of them
involved the offspring of survivors of cancer who hadreceived chemo- and/or radiotherapy treatments and theother involved females who had been exposed to radiation(from beta particles, gamma rays, and x rays) during
infancy for the treatment of haemangiomas. Neither ofthese found significant effects attributable to parental
exposure to chemical agents and/or radiation.

UNSCEAR 2001 REPORT

60376. The results of studies of minisatellite mutations in thechildren of those exposed in areas contaminated by the
Chernobyl accident and in the children of those exposed tothe atomic bombings in Japan are not consistent: in children
from Chernobyl areas, the mutation frequencies wereincreased, while in the Japanese children, there were nosuch increases. It should be noted that the control children
for the Chernobyl study were from the United Kingdom.

spermatids (3 weeks) and spermatogonia (6 and 10 weeks).
In the second experiment, mutation frequencies were
determined after irradiation (0.5 and 1 Gy) of premeiotic
stages in males. By using two multi-locus and two singlelocus probes, 30 different minisatellite bands were scoredper animal. The results showed a linear dose-effectrelationship for mutations in spermatogonial cells, but there
was no evidence for induced mutations in spermatids.

377. The search for genetic effects associated withChernobyl exposures in Belarus or Ukraine, which had thehighest contamination, and in a number of European
countries provide no unambiguous evidence for an increasein the frequencies of one or more of the following: Down's
syndrome, congenital anomalies, miscarriages, perinatal
mortality, etc.

381. Dubrova et al. [D4, D5] suggested that these findings
support the interpretation that they advanced earlier [D19],
namely, the minisatellite loci themselves are not directtargets for radiation-induced mutations; if they were, thenthe observed rate would require an unrealistically highnumber of induced DNA double-strand breaks or otherdamage in the genome. If the inference is correct thatinduced minisatellite mutations are non-targeted events, thiswould mean that damage elsewhere in the genome or inother “sensor molecules” might be relevant. The authors
also noted that similar mutation rates in the spermatogonial
cells sampled 6 and 10 weeks post-irradiation can beinterpreted to mean that the mutations result from damage
accumulated in germ cells prior to meiosis but do notnecessarily indicate that the mutational events themselvesoccur premeiotically rather than later, for example, inmeiosis. Since, however, meiotic stages were not includedin the study, no firm conclusions can be drawn.

B. ANIMAL STUDIES
1. Radiation-induced minisatellite mutations
in mouse germ cells
378. In work that preceded the Chernobyl investigation,
Dubrova et al. [D18] conducted a pilot study to determine
the inducibility of minisatellite mutations in mouse germ
cells by radiation. Hybrid (F1) male mice (101/HY ×
C3H/SnY) were given acute gamma-ray exposures of 0.5 or
1 Gy and mated to unirradiated females. The progeny
derived from stem-cell spermatogonia at the time ofirradiation and the parents were used for detecting new (i.e.
not present in either parent) mutations in their DNA
fingerprints. Two multi-locus minisatellite probes, 33.6 and33.15 [J15], were used. The results showed that thefrequencies of mutations in the progeny derived from
irradiated males were higher than in the controls (ratios tocontrols 1.9 and 1.6 for mice irradiated at 0.5 and 1 Gy,
respectively).
379. Dubrova et al. [D18] stressed three points: (a) in thisstudy, evidence for radiation induction of minisatellite
mutations was obtained in a total of 232 offspring from 26
control and irradiated families at radiation doses andsample sizes substantially lower than those used inconventional genetic studies with specific-locus mutations
in mice; (b) if induced mutations can be verified both forthe mouse pedigrees and for the offspring of wellcharacterized control and irradiated human populations,then minisatellite mutations may be of use in monitoring
germ-line mutations in humans; and (c) the probableselective neutrality of minisatellite mutants should ensurethat mutants will not be lost prenatally.
380. In a subsequent investigation, Dubrova et al. [D4]studied the x-ray induction of mutations at the mouseminisatellite loci in premeiotic and post-meiotic stages ofspermatogenesis. Two experiments were designed: in one,the frequency of mutations was measured in three groups ofoffspring conceived 3, 6, and 10 weeks after paternal acutex-irradiation with 1 Gy to sample, respectively, irradiated382. In similar experiments, Sadamoto et al. [S36] and Fan
et al. [F32] investigated 60Co gamma- radiation-induced
germ-line mutations at a hypervariable minisatellite mouse
locus (ms6hm). Male C3H/HeN mice were acutely exposed
to 3 Gy from 60Co and mated to C57BL/6N females. The
matings were made at 1!7, 15!21, and 71!77 days postirradiation to sample progeny from irradiated spermatozoa,
spermatids, and stem-cell spermatogonia. DNA fromparents and the progeny was analysed in Southern blots toscreen for new mutations. The locus-specific Pc-1 probe
was used. The data showed that the frequencies ofmutations in the progeny in the irradiated group werehigher than in the controls, and this was true of all thegerm-cell stages (in contrast to the work of Dubrova et al.,which showed that no minisatellite mutations were inducedin spermatids). However, as in the study of Dubrova et al.,significant increases could be detected with relatively small
sample sizes.
2. Genetic effects in mice exposedin the Chernobyl accident
383. Shevchenko et al. [S73] and Pomerantseva et al. [P17]studied adverse genetic effects in mice caught in 1986 and1987 within a 30-km radius of the Chernobyl reactor (fourdifferent sites with different levels of gamma radiation
background and with estimated doses from <0.01 Gy to
1.5 Gy). The frequencies of cytogenetically ascertained
reciprocal translocations were found to be consistent withprevious findings of the effects of dose and dose rate ontranslocations. Of 122 male mice, 2 (from the maximally

ANNEX: HEREDITARY EFFECTS OF RADIATION

contaminated region) were sterile and for the rest, there wasa period of temporary sterility. Nonetheless, in these males,
the frequencies of abnormal sperm were in the range 2%!
5%, with no radiation-dose-dependent effects. In matingsof these males with laboratory females, post-implantationmortality rates were nearly the same for sites II, III, and IV,i.e. they did not depend on the degree of radioactive contamination. However, in matings of males from site I within
the first two weeks of capture, there was a significant
increase in post-implantation mortality. This was an
expected result when one considers the fact that postmeiotic germ-cell stages were sampled in these matings.
384. Other data reported in the paper of Shevchenko et al.
[S73] pertain to parallel experiments in which laboratory
mice were exposed to elevated background radiation in the
Chernobyl region for 22!25 days, resulting in absorbed
gonadal doses of 0.1, 0.3, and 2.5 Gy (gamma rays) in one
set of experiments and 3.4 Gy (gamma rays) and 2.7 Gy(beta rays) in the other (in the first, only males were
exposed, while in the latter, both males and females as wellas pregnant females were exposed). In the first series ofexperiments, the most significant effects were injuries totestes that caused irreversible sterility at high doses. In thesecond, when the exposed males were mated to unexposed
females in the laboratory, the overall embryonic mortality(i.e. pre- and post-implantation mortality) during the firstweeks was four to six times as high. In the case of exposed
females mated to unexposed males three months after thetermination of the exposures, there were no significant
differences compared with controls. However, of 74 males
exposed as embryos, 4 (5.4%) showed significant increases
in post-implantation mortality in the range 40%!63%;
cytogenetic analysis revealed that males were heterozygous
for reciprocal translocations.
3. Cytogenetic nature of radiation-induced
germ-line mutations in the mouse385. Genetic and cytogenetic analyses of mutations
recovered in large-scale mutation work with the mouse
7-locus specific-locus method have provided evidence forthe induction of large deletions and other forms of grosschromosome imbalance by radiation and/or chemicalmutagens [D20, R16, S42]. Among these loci are the dilute(d) and short ear (se) loci on chromosome 9, the albino (c)and pink-eye (p) loci on chromosome 7, and the brown (b)locus on chromosome 4 (e.g. [R12, S42]). The largest ofthese spanned 4!9 cM (8 to about 16 Mb) and are
cytologically visible.
386. Some dominant mutations at loci such as the steel (Sl)on chromosome 10 and the splotch locus (Sp) on chromosome 1 were associated with runting, reduced viability, andeither pre- or post-implantation loss of homozygotes. Cytogenetic analysis revealed visible deletions at the respective
loci that removed between 2% and 30% of the chromosomes([C45] and references cited therein). Prompted by thesefindings, Cattanach et al. [C46] undertook a systematic

61

cytogenetic analysis of these and other mutants recovered in
the course of their specific-locus experiments (6 Gy fromacute x-irradiation) and/or chemical mutagen treatments ofstem-cell spermatogonia as well as of animals that showed
only the growth retardation (runting) phenotype.
387. The principal findings were the following: (a) animals
with radiation-induced mutations at the most radiosensitive
locus, the s (piebald spotting), were growth-retarded todifferent degrees and also showed other phenotypicabnormalities, such as head shaking or waltzing behaviour;
all of the 21 analysed by Cattanach et al. proved to be large
deletions, variably comprising from 2.5% to 30% of the distal
region of chromosome 14 spanning the s locus; (b) Sl
mutations were also frequently recovered in radiation experiments; all of the eight analysed were deletions comprising up
to 10% of chromosome 10 spanning the locus; and (c)mutations at the other known loci (W, Ph, and T) were also
associated with deletions, but relative to Sl, they were
smaller.
388. In addition to deletions associated with known gene
phenotypes, cytogenetically visible deletions without
specific mutant genotypes were found to be distributed
throughout the genome. Besides growth retardation, theseanimals showed associated head abnormalities, dark coatsetc., often with limited levels of white spotting. Several ofthese effects may be secondary to runting, as they arecommon to a number of different deletions involving
different chromosomes.
389. Even in the group of deletions identified mainly on
the basis of known gene phenotypes, it was clear that the
distribution across the genome was non-random. Thus, nodeletions have been found so far in four chromosomes (11,12, 15, and 19), only rarely are they found in others(chromosomes 2, 6, 7, and 9) and multiple examples insome others (chromosomes 1, 3, and 8). Multiple deletions
were most evident in chromosome 1, where 12 independent
deletions were found; other examples of multiple deletions
were found in chromosomes 3 and 8.
390. This non-random distribution does not seem to be
associated with a refractoriness of some chromosomes toradiation-induced breakage, as there is no hint of acorrelation with the distribution of translocation
breakpoints. It would thus seem that the non-random
distribution of the recovered deletions is a reflection of the
non-random distribution of haplo-sufficient and haploinsufficient genes in the genome (the terms refer to thesituation where loss of one copy of the gene is compatible[haplo-sufficient] or not compatible [haplo-insufficient]with viability).
391. In addition to deletions, 24 duplications (including
two insertions) were also found in growth-retarded animals.
The distribution of the deletions was non-random; multiple
examples were found in chromosomes 7, 9, 14, and 16, andin chromosome 9, duplication of up to 10% of thechromosome was compatible with viability. The recovery

UNSCEAR 2001 REPORT

62

of multiple examples of chromosome 9 duplications
contrasts with the rarity of deletions in this chromosome.
Six inversions and 24 translocations were also detected bychance but were not associated with growth retardation.
392. It is difficult to estimate the incidence of the various
types of chromosomal change because of the subjectivity inthe recognition of the associated phenotypes and, in thecase of duplications, the modifications to the screening
process employed throughout the studies. Also, thecytogenetic identification of the changes is governed bothby the resolution of the light microscope and the quality of
the G-bands; losses or gains of <2% will probably beundetected.
393. Notwithstanding these limitations, some crude
estimates are possible. From about 30,000 young screened
from four specific-locus experiments in which males had
been exposed to spermatogonial irradiation (6 Gy), 394 wereselected for screening by phenotype. Of the 360 screened sofar, 33 (9.2%) proved to carry large deletions and 15 (4.2%)
carried duplications. If the percentage of deletions in theremaining 34 progeny is the same as in the 360 screened,based on the total number of 30,000 progeny, the overall rateof deletions can be estimated to be about 12 104. If thes locus mutations are included, this rises to about 18 104, andif all untested and tested Sl mutations are included, to about
20 104. The frequency of duplications, however, is much
lower, reflecting the late introduction in the study ofscreening for growth retardation without other phenotypic
effects, which proved effective for detecting this category ofdamage.
394. Twenty-seven of the 360 animals carrying translocations unassociated with phenotypic effects were incidentally found in these tests (7.5%), providing an
independent measure of radiation effect with which tocompare the deletion and duplication frequencies. A second
measure is provided by the overall specific-locus mutation
frequency; however, since virtually all the s locus mutations
were large deletions, the specific-locus mutation frequency
for the remaining six loci, excluding the s locus mutations,is 14.5 105 per locus per gamete.
4. Summary
395. Laboratory studies with mice have now provided
evidence for radiation-induced minisatellite mutations inmale germ cells. In one study, significant increases in thefrequencies of these mutations could be detected in progeny
descended from irradiated spermatogonia, spermatids andspermatozoa. In another study, focussed on spermatids andstem-cell spermatogonia alone, increases were detected inspermatogonia but not in spermatids.
396. In other work, mice caught in 1986 and 1987 within a
30-km radius of the Chernobyl reactor (i.e. after the accident;with estimated doses from <0.01 Gy to 1.5 Gy) were foundto have higher frequencies of translocations induced inspermatogonia. Two of the 122 male mice caught in the
maximally contaminated region were sterile, while others had
a period of temporary sterility followed by resumption offertility; the tests revealed that 2% to 5% of the sperm wereabnormal.
397. Cytogenetic studies of the progeny of irradiated malemice that had known mutant phenotypes (recovered in thespecific locus tests) and of those that had only the runting
phenotype have shown that (a) a significant proportion ofthese animals carry large deletions and duplications that arecompatible with survival of the heterozygotes even if they
reduce viability and cause growth retardation and otherdevelopmental abnormalities; (b) the distribution of thesestructural changes is non-random across the genome; and (c)not all growth-retarded mutants carry detectable deletions.
The studies suggest that smaller deletions below the range of
cytogenetic detection will also occur and may be detected bymolecular techniques.

C. MOSAIC MUTATIONS AND
MUTATION CLUSTERS
1. General comments
398. As mentioned in paragraph 46, mosaicism, theoccurrence of two or more genetically different cell lines
derived from a single zygote, is an important cause ofphenotypic modification resulting in variation in clinicalexpression of an inherited trait or disease. Mosaicism for a
specific gene mutation may be confined to somatic cells orto the germ line or may be present in both, depending on
the developmental stage at which the mutation occurs. Puresomatic mosaicism, where the mutant clone is not present
in the germ line, is not relevant to inherited disease and will
not be considered further.
399. Germ-line mosaicism (the occurrence of a de novo
mutation in a germ-line cell or one of its precursors during
early embryonic development), however, will result in a
“mutant sector” in the gonad of an otherwise phenotypicallynormal individual, and such an individual will generate
gametes carrying the mutation, which in turn may result in
individuals carrying the same mutation in the following
generation (“mutant clusters”). The occurrence of germ-line
mosaicism provides an explanation for the inheritancepatterns in cases where multiple affected children are bornto clinically normal parents. For instance, some diseases
that satisfy two of the requirements for autosomal recessive
inheritance, namely, expression in the offspring of
unaffected parents and recurrence within sibs, may actually
be due to a dominant mutation that was present as a mosaic
in the parental germ line. In organisms such as the
Drosophila and the mouse, a sizeable proportion of
spontaneous mutations is known to arise as mosaics in thegerm line and can be readily inferred from the occurrenceof clusters of identical mutations in the progeny of singlepair matings [F27, R40, S99, S100, S101, S102, W28].

ANNEX: HEREDITARY EFFECTS OF RADIATION

2. Mosaic mutations in humans
400. In humans, mosaicism for constitutional and somatic
chromosomal anomalies has long been known, but its
occurrence among single-gene mutations leading to
Mendelian diseases, although suspected from family
studies, could be demonstrated only after investigators
began to use molecular techniques. Thus, for instance, inDuchenne muscular dystrophy (DMD), “restriction fragment length polymorphism tracking” has been used todemonstrate that deletions of the DMD gene were transmitted to two or more offspring by mothers who themselves
showed no evidence of the mutation in their somatic cells(e.g. [B67]). The available data for DMD suggest that the
proportion of mosaics among the mothers of sporadic
patients may be about 7% [G20]. Known examples ofgerm-line mosaicism include osteogenesis imperfecta type2, neurofibromatosis 1, retinoblastoma, pseudoachondroplasia, Ehlers-Danlos syndrome, dominantly inheritedectrodactyly, tuberous sclerosis (autosomal dominant),
haemophilia A, ornithine trans-carbamylase deficiency, andagammaglobulinemia (X-linked), and several more arebeing reported in the literature. The subject has beenreviewed [C2, H20].
3. Mosaic mutations and clusters in miceand their relevance for risk estimation
401. In the mouse, data on spontaneous mosaic mutations
come from studies on recessive visible specific-locus
mutations that have recently been published [R9, R40]. The
following general points are applicable to mosaic mutations

and clusters of mutations detected in the mouse specificlocus work: (a) the wild-type animals used in mutation tests(“the treated generation”, the authors’ terminology for G1
generation) are obtained by crossing two inbred laboratory
strains (G0 generation); (b) these (treated or control
animals) are mated to the tester stock, which is homozygous
for seven recessive visible markers; (c) mutations arescored in the progeny of the treated animals (“the scoredgeneration”, G2 generation); (d) mosaic mutations at fivecoat colour loci (of the seven loci in the tester stock) aredetectable by their mottled phenotypes (visible mosaics) of
the progeny in the scored generation; confirmation of
gonadal mosaicism requires breeding studies; (e) gonadal
mosaics that arise in the G0 generation will not be visible in
the G1 generation (called “masked mosaics”, because themosaic is covered by the wild-type allele from the otherparent) but will give rise to clusters of mutations in the G2
generation; and (f) in the work of Russell and Russell[R40], the mean of the observed (flat-topped) distribution
with respect to the proportion of germ-line mosaicism for50 visible mosaics is 50%. They suggest that a 50:50
mosaic could result from (a) a double-strand mutation at thetwo-cell stage, or (b) a single-strand mutation occurring ina parental germ cell any time after the last premeiotic
mitosis and before the first post-meiotic mitosis in one ofthe parental genomes (in G0 or G1 generations), a stage thatthey refer to as the perigametic interval. The authors favour
alternative (b).
402. The following flow chart summarizes the origin ofmosaics and clusters and their detection in the mouse
specific-locus experiments discussed above:

G0[grandparental generation] ÿG1[treated generation](animals treatedor kept as controls)ÿremains “masked”

A mosaic mutation arises

ÿG2[scored generation](progeny scored)ÿmutant cluster

A mosaic mutation arises ÿ
403. Russell and Russell [R40] suggested that: (a) the most
likely frequency of visible mosaics (in generation G2) is
9.6 106 locus1; (b) the frequency of singletons (thosemutants that do not occur in clusters and based on publisheddata from Oak Ridge, Neuherberg, and Harwell) is 6.6 106locus1 (generation G2); (c) the best estimate of the
spontaneous mutation rate is derived from the G2 generation,
namely, including visible mosaics with singletons (andallowing for the fact that mosaics contribute only half as
many new mutations to the next generation), i.e. 6.6 + (9.6 ×
0.5) = 11.4 106 locus1, which is 1.7 × 6.6, the singleton rate;(d) adding the female contribution of singletons (1.6 106)[R41] and mosaics, assuming that the latter is the same infemales, yields 17.8 106 (i.e. 11.4 + 1.6 + 4.8 = 17.8), which
is more than twice the singleton rate; and (e) a less reliable
way of computing the total spontaneous rate is from63

“visible mosaic”(mottled animals)

mutations detectable in G1 (rather than G2) by adding masked
mosaics (weighted by ½ ) to heterozygotes (also masked )appropriately weighted), which gives a rate that is 1.4 times
the singleton rate.
404. The main message of the above paper, therefore, isthat taking visible mosaics into account will approximately
double the spontaneous rate of 6.6 106 locus1. It is clearthat if the new estimate is to be used in the doubling-dose
calculations, then the doubling dose will become twice thecurrently used value of 1 Gy (for low-LET, low-dose, orchronic exposures), which in turn means that the relative
mutation risk per unit dose will be halved.
405. Selby [S101, S102] tabulated the data on clusters in themouse specific-locus experiments carried out at Oak Ridge,

64

UNSCEAR 2001 REPORTHarwell, and Neuherberg and showed that these are notuncommon. Note that for the occurrence of a cluster in thescored generation, the mutations must have existed as
masked mosaics in the parental generation. Selby has argued
that the method used by Russell and Russell (i.e. adding therate of visible mosaics to the singleton rates) seriously
underestimates the spontaneous rate per generation. He
developed a computer programme to model specific locus
experiments that incorporates the hypothesis originallyadvanced by Russell [R9, R36] for the origin of mosaics,
namely the “first cleavage gonadal mosaic” hypothesis(FCGM). He used the programme to estimate the consequence of the FCGM hypothesis on the total mutation
frequency. His results from computer simulation show thatthe combined spontaneous mutation frequency in both sexes
is of the order of 39.6 105 mutations per gamete, or 5.66 105per locus. The latter is about three times higher than
17.8 106, given in paragraph 403. He has further argued that,
if the increase in mutation rate with paternal age known inhumans is used to correct the mouse mutation rate, thespontaneous mutation rate will be even higher. The message
therefore is that if the mouse spontaneous rates of mutations
are to be used with the corrections suggested by Selby, thedoubling dose will be much higher than the 1 Gy thus far
used in risk estimation.
406. As discussed in Section II.E.3, when the Committee(in 1977) and BEIR (in 1980) began using the mouse-databased doubling dose for risk estimation in humans, neither
addressed the basic questions of (a) paternal age effects for
spontaneous mutations in humans and their impact on
spontaneous mutation rates, and (b) whether it is indeed
appropriate to extrapolate spontaneous mutation rates fromshort-lived mice to a heterogeneous human population of allages (especially since males at increasingly advanced ages
are siring offspring). Evidently, the conceptual basis forusing mouse spontaneous rates had been erroneous all theseyears, and the Committee now feels that it is important torectify this error. Additionally, because of the newawareness of mosaics and clusters in the mouse, thespontaneous mutation rate in mice has become even more
uncertain than had been thought.
407. Although the potential importance of mosaics andclusters is recognized, and it may eventually become possible
to take them into account for estimating spontaneous
mutation rates, the Committee believes that for the purpose ofrisk estimation at present, the prudent way forward is torevert to the use of data on human spontaneous and mouse
induced rates for calculating doubling doses as was done in
the 1972 BEIR Report [C47] for several reasons.
408. First, most of the available human data on germinal
mosaics are in the form of case reports that do not permit
reliable quantitative estimates of their contribution to thespontaneous mutation rate. The main relevance of germ-line
mosaicism in humans stems from the fact that there may be

a real risk for the recurrence of disease in subsequent
offspring in what had been previously thought to represent
a risk-free situation.
409. Second, if germ-line mosaics arise at a finite rate inevery generation and result in clusters in the generation
following their origin, these may affect not only theestimates of spontaneous mutation rates (as Selby’s
computer simulations show) but also the estimates of
disease frequencies in the population. It is therefore
incorrect to introduce corrections to spontaneous mutation
rates and not to disease frequencies; corrections for thelatter are not possible at present.
410. Third, whereas clusters are detected in the mouse
because of large numbers of progeny from a single parent,
human family sizes are generally too small to detectclusters. (In fact, it can be argued that clusters are far lessrelevant in humans because of small family sizes.) Even ifclusters had occurred, they would have been automaticallycounted, since human geneticists include all mutants thatarise anew in calculating spontaneous mutation rates.
Judging from the numbers of mutants actually recorded in
the various studies of spontaneous mutations and diseasefrequencies in humans, it seems very unlikely that there
were mutant clusters causing “mutational explosions” inour species. Consequently, it is difficult to extrapolate fromdata on mosaics and clusters in mice to spontaneous
mutation rates in humans.
411. Finally, placing heavy reliance on the spontaneous
mutation rate estimated from a small number of genes in themouse (and extrapolating from this to the human genome)
ignores both the availability of spontaneous mutation rateestimates for a much larger number of human genes(discussed in Chapter II) and the fact that these estimates
included paternal age effects (and clusters had theyoccurred). It should also be noted that when humanspontaneous rates are used, one less assumption is needed.
4. Summary
412. The occurrence of mosaic mutations in humans, ofmosaics and clusters in mice and the difficulties in using
the data on the latter for the calculation of spontaneous
mutation rates for the purpose of estimating the doublingdoses are reviewed. Arguments are advanced to support thepresent conclusions of the Committee, namely, that: (a) theuse of entirely mouse-data based doubling doses to estimate
human genetic risks is conceptually incorrect; (b) it is notpossible to extrapolate from mouse data on mosaics andclusters to human spontaneous rates at present; and (c) the
prudent way forward is to use spontaneous mutation rates
of human genes and rates of induced mutations in mousegenes to estimate doubling doses, as was first done in the1972 BEIR Report.

ANNEX: HEREDITARY EFFECTS OF RADIATION

65

VII. CONCEPTS, DATA AND ANALYSES USED FOR
THE ESTIMATION OF GENETIC RISKS
413. As mentioned in the Introduction to this Annex, theyears following the publication of the Committee’s 1993
Report [U4] have witnessed a number of significant
advances in human (especially molecular) genetics andexperimental radiation genetics that are particularly relevant
for the estimation of genetic risks of radiation. Amongthese advances are: (a) the revision of the estimates ofincidence of Mendelian diseases in human populations(Chapter II); (b) the use of human data on spontaneous
mutation rates and mouse data on induced mutation rates(instead of using mouse data for both these rates as had
been done thus far) for calculating the doubling dose
(Chapter II) [S22, S105]; (c) the development of methods,
using the mutation component (MC) concept, for predicting
the extent to which the frequencies of Mendelian [C66] andmultifactorial [D17] diseases will increase as a result ofradiation exposures (Chapter IV); (d) the delineation of theconcept of disease-class specific potential recoverability
correction factors to bridge the gap between radiationinduced mutations that have been recovered in the progenyof irradiated mice and the potential risk of inducible genetic
diseases in humans [S16]; and (e) the introduction of theconcept that multisystem developmental abnormalities arelikely to be among the principal phenotypes of radiationinduced genetic damage in humans [S43]. Of these, items(d) and (e) incorporate advances in human molecularbiology and in molecular studies of radiation-induced
mutations in experimental systems.

frequency of genetic diseases in humans were presented by
Stevenson in 1959 for the population of Northern Ireland[S103]. Since then, these estimates have been periodicallyreviewed and revised in the light of advances in knowledge
in this area (e.g. [C67, C68, D30, S104, T25, U5]). The
estimates used until 1993 (e.g. [N20, U4]) date back to thecompilations of (a) Carter [C67, C68] for Mendeliandiseases; (b) Czeizel and Sankaranarayanan [C37] forcongenital abnormalities and (c) Czeizel et al. [C35] forcommon chronic diseases. Additionally, the results ofseveral newborn surveys for chromosomal abnormalities(reviewed in [U7]) provided estimates of incidence for thisclass of diseases.
416. There are no compelling reasons at present toconsider revising the estimates for chromosomal (40 per 104
live births) and multifactorial diseases (congenitalabnormalities, 600 per 104 live births, and chronic
multifactorial diseases, 6,500 per 104 in the population)used in the 1993 Report [U4]; however, as discussed in
Chapter II, progress in human genetics during the last
several years now permits an upward revision of theestimates for Mendelian diseases. The revised estimatesare:150 per 104 for autosomal dominants, 75 per 104 forautosomal recessives, and 15 per 104 for X-linked diseases,
together 240 per 104 (Table 9).

B. THE DOUBLING DOSE
414. The aim of this Chapter is to recapitulate the advances
discussed in the earlier Chapters, review those that have notbeen considered, and present a synthesis of how they can beused to adapt the conceptual framework for the doublingdose method of risk estimation, thus setting the stage forrisk estimates discussed in Chapter VIII. The equation useduntil 1993 for estimating risks provides a convenient
starting point to consider these advances:
Risk per unit dose = P × 1/DD × MC

(14)

in which P is the incidence of the class of genetic diseaseconsidered, 1/DD is the reciprocal of the doubling dose,
which is the relative mutation risk per unit dose, and MC is
the mutation component, which provides a measure of therelative increase in disease frequency (relative to thebaseline incidence) per unit relative increase in mutation
rate (relative to the spontaneous rate).

A. FREQUENCIES OF GENETIC DISEASESIN HUMANS
415. Incidence estimates of genetic diseases constitute an
integral part of the risk equation used with the doublingdose method. The first comprehensive estimates of the417. The doubling dose is the amount of radiation required
to produce as many mutations as those that occur
spontaneously in a generation and is obtained as a ratio of
spontaneous and induced rates of mutations in a set ofdefined gene loci. The value of the doubling dose used inrisk estimation since the mid-1970s was 1 Gy (for lowLET, chronic/low dose radiation) and was based on mouse
data on spontaneous and induced rates of mutations(predominantly at the 7 specific loci mutating to recessive
visible mutations).
418. The two main reasons for reverting to the use of theconcept in the BEIR 1972 Report [C47] namely, the use ofhuman data on spontaneous mutation rates and mouse dataon induced mutation rates for doubling-dose calculations(instead of using mouse data on both these rates) werediscussed in Chapters II and VI. Briefly, the arguments are
the following: (a) the pronounced sex differences inspontaneous mutation rates, the increase in the rate of
spontaneous mutations with paternal age in humans, and thefact that the human lifespan is longer than that of the mouseconsidered together strongly suggest that extrapolating fromthe short-lived mice to humans is unlikely to provide areliable average spontaneous rate in a heterogeneous humanpopulation of all ages, and (b) the recent analysis of mouse

66

UNSCEAR 2001 REPORT

data on mutations that arise as germinal mosaics (which
result in clusters of identical mutations in the following
generation) has introduced considerable uncertainty about
the magnitude of the spontaneous mutation rate in thisspecies; at present, there are no easy ways to extrapolate
from mouse data on mosaics and clusters to the situation inhumans.
419. In view of the above (and the lack of an alternative tothe use of mouse data for induced mutation rates), theCommittee considers that it is prudent now to basedoubling-dose calculations on human spontaneous andmouse induced rates. The advantages in using humanspontaneous mutation rates for the doubling-dose
calculations are: (a) they pertain to human disease-causing
genes; (b) the mutation rate estimates in humans, because
they are averaged over both sexes, automatically include
sex differences and paternal age effects; and (c) inestimating mutation rates, human geneticists count all
mutants that arise anew irrespective of whether they arepart of a cluster or not; consequently, should clusters ofmutations occur, they are also taken into account.
1. The average rate of spontaneous mutations
in humans
420. Since the purpose of calculating doubling doses is touse its reciprocal to estimate the risk of societally important
Mendelian diseases (such as those included in P in the risk
equation), it would seem that the choice of spontaneous
rates needs to be guided by diseases that have highpopulation incidences and/or genes that have high mutation
rates. In practice, however, the situation is not that simple,
as illustrated below. Consider the main contributors todisease incidence such as polycystic kidney disease (8 per104), familial hypercholesterolemia (20 per 104),
hypercholesterolemia due to familial defective apoB-100(10!15 per 104), and BRCA1-associated breast and ovariancancers (15 per 104) (Table 10). These are all adult-onset
diseases and together account for roughly one third of thetotal estimated incidence of 150 per 104 of all autosomal
dominant diseases. Of these four, autosomal dominant
polycystic kidney disease has an estimated mutation rate of
87.5 106 [V20], but it is now known that this disease canbe due to mutations in either of two autosomal genes,
PKD1 and PKD2. For the other three diseases, no new
spontaneous mutations have been reported, and thepreferred interpretation is that their high incidence is due
not to high mutation rates but to small selection
coefficients.
421. Examples of diseases that fall at the high end of the
distribution of spontaneous mutation rates are neurofibromatosis (~70 106; average from two studies; for thisdisease, at least two genes, NF1 and NF2, are now known),
spherocytosis (~22 106), myotonic dystrophy (~18 106;average from two studies), achondroplasia (~11 106;average from four studies), and osteogenesis imperfecta(~10 106; average from two studies; at least two genes are

known to underlie this disease). Their estimated incidence
in live births are, respectively, 4, 2, 2, 0.2, and 0.4 per 104,
showing that there is no clear correspondence between highmutation rates and high incidences.
422. It can therefore be concluded that a reasonable
procedure to obtain a representative average of spontaneous
mutation rates of human genes is to (a) use all the available
estimates for individual autosomal dominant diseases (forwhich estimates of selection coefficients are also available;
see later) irrespective of whether these diseases have a highor low incidence or high or low mutation rates, and (b) also
include the numbers of genes thus far known or estimatedto underlie the various diseases [M2, S105] (see Chapter II
and Table 10). Note that taking into account the numbers ofgenes represents an important departure from the earlier
practice of basing mutation rate estimates on diseasephenotypes alone (i.e. earlier, a one-to-one relationshipbetween mutation and disease phenotype was assumed
because the information that now exists on the numbers ofgenes was not available then for most of the diseases). The
relevance of the estimates of selection coefficients stems
from the fact (discussed in Chapter IV) that they enable thedetermination of mutation components for autosomal
dominant diseases.
423. Table 37 taken from the paper of Sankaranarayanan
and Chakraborty [S22], summarizes the data that have beenused to obtain an estimate of the average spontaneous
mutation rate of human genes. These 26 disease phenotypes
encompass an estimated 135 genes. The average(unweighted) mutation rate obtained from these data is 2.95
± 0.64 106 locus1 generation1. This figure is well within
the range 0.5 106 and 5 106 per locus used in the 1972
BEIR Report [C47].
424. It should be noted that the 26 diseases used in theabove calculations are but a subset of dominant diseases(Table 10) used to provide the basis for the incidence
estimate for autosomal dominant diseases. These “other”
diseases were not included in the present analysis becauseof lack of information on mutation rates and selection
coefficients. Further, X-linked genes have not been
considered; instead, it has been assumed that the average
spontaneous mutation rate calculated for autosomal
dominants also will apply to the X-linked diseases. The
justification for this assumption rests on the following linesof reasoning: (a) among Mendelian diseases, autosomal
dominants constitute the most important group from thestandpoint of genetic risks, and (b) while X-linked
recessive diseases are also expected to respond directly to
an increase in mutation rate, since their incidence is anorder of magnitude lower than that of autosomal dominants(0.15% vs. 1.5%), the assumption of similar average
spontaneous rates of mutations for autosomal dominants
and X-linked recessives is unlikely to result in any
significant underestimation of the total risk (in fact, it isbecause of this reason that these two classes of diseases are
considered together in risk estimation).

ANNEX: HEREDITARY EFFECTS OF RADIATION

2. The average rate of induced mutations
in mice425. For estimating the average induced rates of mutations
in mice, the Committee has now made an important departurefrom its previous practice [U8] of basing it on data onrecessive mutations induced at the 7 specific loci extensively
studied and the 5 additional loci used by Lyon and Morris[L5], for which the data were (and remain) much lessextensive. Instead, it examined all available data on induced
mutations in defined genes in mice; these relate to recessive
specific locus mutations at the 12 loci mentioned above (butincluding additional data), “bio-chemical mutations”(mutations in enzyme-coding genes that cause loss of enzyme
activity [C12, P10]; data of Lewis and of Peters, cited in[N8]) and autosomal dominant mutations at four loci (Sl, W,
Sp, and T) collected in the course of specific-locus
experiments conducted at Harwell (together, 72 loci). The
inclusion of data for the above autosomal dominant mutationsin these calculations was dictated by the consideration that,
although the underlying genes were not well defined at thetime these experiments were conducted (but mutations were“frequently” observed and recorded and so the ascertainmentis believed to be complete), not only their identity is known,
but also the molecular nature of mutations in these genes.
426. All of the data considered are from studies involving
stem-cell spermatogonia. The data from female mice have notbeen used, since, as discussed in the UNSCEAR 1988 Report[U5], there is uncertainty whether mouse immature oocytes
would provide a good model for assessing the mutational
radiosensitivity of human immature oocytes. The argument
rests on (a) the strikingly higher sensitivity of mouse
immature oocytes to radiation-induced killing (the majority
are destroyed by 0.5 Gy [O6] in contrast to those of humanand rhesus monkey immature oocytes, for which the dose
required is at least 100 times higher [B6]), and (b) the
insensitivity of mouse immature oocytes sampled 7 weeks
after irradiation to radiation-induced mutations in contrast to
mature and maturing oocytes [R37]. In view of theuncertainty of the mutational response of human immature
oocytes, the Committee will use the conservative assumptionthat the rate estimated for males will also be applicable tofemales.

67

and Morris [L5], the rate is about one third of the above,
being 0.78 105 locus1 Gy1; one locus, the a is common toboth sets of loci). For the various sets of biochemical lociat which null mutations have been scored, the estimatesvary from 0.24 105 to 1.64 105 locus1 Gy1. The averagerate for dominant visibles is within the above range. The
unweighted average of the induced mutation rates is 1.09
105 locus1 Gy1. The use of this rate for doubling-dose
calculations is somewhat problematic since (a) there isoverlap of one or more loci in different data sets, (b) insome studies, all the loci involved could not be ascertained(see footnote e in Table 37), and (c) there is no simple wayof taking into account the inter-locus variation andsampling variance of induced rates from the above average
estimate of 1.09 105 locus1 Gy1.
429. Therefore the following approach was used to derive
the average induced rates of mutations. All data fromindividual experiments (detailed in [S22]) were firstgrouped by loci, so that an unweighted estimate of thelocus-specific induced rates could be derived from theaverage of the estimates from all experiments involving
each of the loci. Subsequently, the locus-specific rates wereaveraged across loci to arrive at the induced mutation rate.
This procedure permitted the estimation of the standard
error the estimated rate that incorporated sampling
variability across loci as well as the variability of the rates
in individual experiments. The algorithm of thesecomputations is described in [S22]. In this approach, theunpublished data of Lewis (cited in [N8]) were excluded
since details of the identity of all the loci and the loci atwhich mutations were recovered were not available.
Although fewer data were used (the total number of locibecame 34), this procedure was preferred because (a) nolocus was double-counted while averaging over all loci; (b)the loci and the corresponding mutant phenotypes wereclear; (c) the standard error of mean (which took into
account both intra- and inter-locus variability) could begiven. The locus-specific rates for the 34 loci used are
given in Table 39. These data permit an overall average
estimate of 1.08 ± 0.30 105 locus1 Gy1. With a dose-rate
reduction factor of 3 traditionally used (the original basis
for which was provided by the studies of Russell et al.
[R38]), the rate for chronic low-LET radiation becomes
0.36 ± 0.10 105 locus1 Gy1.

427. Tables 37 and 38 present summaries of the data considered for the estimation of induced mutation rates inmice. Details of data from individual experiments are discussed in Sankaranarayanan and Chakraborty [S22]. In
these experiments, male mice were exposed to either single,
acute high doses of x- or γ-irradiation or to high dose
fractionated x-irradiation (usually two fractions separated
by 24 hours). The rates for the latter were appropriately
normalized to acute x-irradiation conditions to facilitate
easy comparisons (see footnotes d of Table 37 and b and cof Table 38).

430. With the estimate of 2.95 ± 0.64 106 locus1
generation1 for the rate of origin of spontaneous mutations
in humans (paragraph 423) and of 0.36 ± 0.10 105 locus1
Gy1 for induced mutations in mice (paragraph 429), thedoubling-dose estimate becomes 0.82 Gy, which is not very
different from 1 Gy based on mouse data that has been usedthus far.

428. Table 37 shows that the average rate of induced
mutations is highest for the original 7 specific loci 3.03 105locus1 Gy1. For the 6 loci used in the experiments of Lyon

431. Since the doubling dose is defined as a ratio of
spontaneous and induced rates of mutations, with these
rates estimated by ms and mi, respectively, the estimate of

3. The doubling-dose estimate

UNSCEAR 2001 REPORT

68

the doubling dose, DD, is given by:
DD = m s/m i(15)

for which the approximate sampling variance can be writtenas:V(DD)  (DD)2

σ2 ms
ms2



σ2 mi
mi2



2rsi σms σmi
msmi

(16)

where σ2 ms and σ2 mi are the sampling variances of ms andmi, respectively, and rsi is the correlation between ms and miacross loci. In principle, to apply equation (15), thecorrelation of the estimated spontaneous and induced
mutation rates should be based on the same set of loci. Thisnot being the case in the present analysis, one can assume
that rsi is equal to zero (i.e. the estimates of ms and mi are
independent). With ms = 2.95 106, σms = 0.64 106, mi =0.36 105 and σmi = 0.10 105, the variance and the standard
error of the doubling dose estimate are 0.0834 and 0.29,
respectively. It should be noted that the standard error
calculation for the doubling dose (which in turn is based on
the estimated standard errors of the average spontaneousand induced rates of mutations) is valid for the small
sample of genes included in the analysis and may not apply
to all radiation-responsive genes in the genome. When moredata become available on the spontaneous and induced
rates, there may be a need to revise the average rates (andtheir standard errors), and the doubling dose (and its
standard error). The currently revised doubling dose of 0.82
± 0.29 Gy is not significantly different from 1 Gy that has
been used thus far, but the conceptual basis of the former(and the database used for estimating the average
spontaneous and induced rates of mutations) is now
different. The Committee will use the round figure of 1 Gyfor doubling dose for risk estimation in the next Chapter.

434. The average rate of induced mutations in mice forcalculating the doubling dose has been estimated on thebasis of locus-specific rates for 34 loci taking into accountboth inter-locus and intra-locus variabilities of rates in the
different experiments. The rate estimated in this way is 1.08
± 0.30 105 locus1 Gy1 for acute x-irradiation and 0.36 ±0.10 105 locus1 Gy1 for chronic irradiation.
435. The doubling dose based on the actual estimates of
spontaneous and induced mutation rates (the latter forchronic irradiation) becomes 0.82 ± 0.29 Gy. The Committee
will use the round figure of 1 Gy in risk estimation.

C. MUTATION COMPONENT
436. The third quantity in the risk equation, i.e. equation (1),is MC or the mutation component. As discussed in
Chapter IV, the relationship between induced mutations anddisease is one of the central problems in risk estimation. The
relationship is straightforward for autosomal dominant andX-linked diseases, slightly complicated for autosomal
recessives (since an induced recessive mutation does not
result in disease in the immediate post-radiation generations)and much more complicated for multifactorial diseases. The
use of the mutation component concept enables one to predict
the impact of an increase in mutation rate on diseasefrequency for the different classes of genetic diseases. With
the mathematical formulations now available, the mutation
component can be evaluated in any post-radiation-exposure
generation of interest following either a one-time or apermanent increase in the mutation rate (i.e. radiation
exposure generation after generation).
437. For a one-time increase in mutation rate (“burst”;
indicated by the subscript b in MCb below) the dynamics ofchange in mutation component with time t (in generations)is given by the equation:

4. Summary

Mc b (t) = s (1!s) t1

432. In this Section, the arguments presented in Chapters
II and VI on the need to to revise the conceptual basis forthe calculation of the doubling dose are recapitulated.
Although in the past, the Committee had assumed that adoubling dose calculated on the basis of spontaneous andinduced mutation rates of mouse genes could be used for
estimating the risk of genetic disease in humans, thisassumption is no longer considered valid. In this Annex,
therefore, the Committee has adopted the use of human dataon spontaneous mutation rates and mouse data on induced
mutation rates for estimating the doubling dose, as wasdone in the 1972 BEIR Report.

and for a permanent increase in mutation rate (indicated by
the subscript p)

Equations (17) and (18) show that MCb = MCp = s for the
first post-radiation generation following either a one-timeor a permanent increase in mutation rate. With noirradiation in subsequent generations, mutation component
will gradually decay back to zero at a rate of (1!s) per
generation. With a permanent increase in mutation rate,
mutation component will continue to increase to attain avalue of 1 at the new equilibrium.

433. Published data on spontaneous mutation rates inhumans have been analysed taking into account the current
knowledge of the numbers of genes (n = 135) underlying 26
autosomal dominant disease phenotypes. These data permit
an estimate of the average spontaneous mutation rate of
2.95 ± 0.64 106 per gene per generation.

438. On the basis of the analysis of published datasummarized in Table 36, an estimate of the average selection
coefficient s for autosomal dominant diseases has been
derived. This is of the order of ~0.3, a value which defines
the first generation mutation component. Although no
X-linked diseases are considered in these computations, it can

Mc p (t) = 1! (1!s) t

(17)

(18)

ANNEX: HEREDITARY EFFECTS OF RADIATION

be argued that the assumption of the same mutation
component value for autosomal dominant plus X-linked
diseases for risk computations will not underestimate the risk
because (a) the net effect of selection for X-linked diseases
is lower (s/3 for these as opposed to s for autosomal
dominants) in the first generation, and (b) the baseline
incidence of X-linked diseases is an order of magnitude
lower than that of autosomal dominant diseases. The
Committee will use the value of MC = 0.3 for computing therisk of autosomal dominant and X-linked diseases for the firstpost-radiation generation. It is nonetheless aware of the factthat selection intensities in present-day human populations isprobably lower than the above estimate.
439. Autosomal recessive diseases do not merit any
detailed consideration here, since their mutation component
is close to zero in the first few generations. For
multifactorial diseases, as discussed in Chapter IV, theestimate of mutation component, obtained using the finitelocus threshold model is not more than ~0.02 for the first
several post-irradiation generations for a radiation scenario
involving radiation exposure in every generation. The
Committee, however, will use this value only for chronic
diseases. For congenital abnormalities the mutation
component cannot be reliably estimated for reasons
explained in Section E of this Chapter.

D. THE CONCEPT OF POTENTIAL
RECOVERABILITY CORRECTION FACTOR
440. The concept of potential recoverability correction
factor (PRCF) is a new one in risk estimation andrepresents one of the logical outcomes of integrating
advances in human molecular biology into the frameworkof genetic risk estimation [S16]. Since the Committee will
use this for the first time in risk estimation to bridge the gap
between the rates of induced mutations determined inmouse studies and the risk of inducible genetic diseases inhuman live births, the rationale underlying the concept andhow the potential recoverability correction factors can be
estimated for the different classes of genetic diseases arereviewed in this Section.
1. Background441. As may be recalled from equation (14), the risk per unit
dose is predicted to be a product of three quantities (i.e. P ×
1/DD × MC). The disease entities included in the estimate of
P are those considered to be societally relevant. In
multiplying P by the other quantities, it is assumed that thegenes (at which spontaneous mutations cause these diseases)
will respond to induced mutations, that these induced
mutations will be compatible with live births and that theywould be “recoverable”in the offspring. This assumption
gained support from studies in a variety of experimental
systems demonstrating that, by and large, the phenotypes ofradiation-induced mutations in the specific genes that wereused were similar to those of spontaneous mutations. Despite69

this evidence, no radiation-induced germ-cell mutations, letalone genetic diseases attributable to induced mutations, havethus far been identified in human studies [B69, N20, O11].
442. Progress in human molecular biology and in radiation
genetics during the past few years now permits anunderstanding of the causes for the above discrepancy
between prediction and observation. More specifically, it is
now evident that induced mutations in only a small
proportion of the human genes of relevance may becompatible with live births. This is because spontaneous
disease-causing mutations and radiation-induced mutations
studied in experimental systems differ in a number ofimportant ways. Since these have been discussed in detail[S4, S6, S43], only the salient points are considered below.
2. Differences between spontaneous andradiation-induced mutations(a) Types of molecular changes
443. As discussed in Chapter II, the molecular alterations
identified in Mendelian diseases include point mutations(base-pair changes) and small and large intragenic
deletions, followed by insertions, duplications, inversions,complex rearrangements, and multigene deletions or
microdeletion syndromes. In addition, at least 14 Mendeliandiseases are known in which the predominant molecularchange is the expansion of specific trinucleotide repeat
sequences in the coding or untranslated regions of the gene
(Table 8). However, although the types of changes (e.g.
point mutations, small and large deletions, and complex
rearrangements) induced by radiation in experimental
systems are similar to those seen in disease-causing
spontaneous mutations in humans, most radiation-induced
mutations are DNA deletions; point mutations constitute a
minority group. The deletions include not only the gene
under study but often adjacent genomic regions as well, i.e.
they are multi-locus deletions [R44, S38, S41, T3]. The
extent of the deletions, however, varies with the genomic
region in which the gene under study is located.
(b) Mechanisms
444. The different types of molecular alterations seen in
Mendelian diseases have their origin in a variety ofmechanisms, most of which are dependent on the DNA
sequence organization of the genes and their genomic
context (Chapter II). In contrast, radiation-induced
deletions originate through random deposition of energy inthe cell (i.e. one can assume that the initial probability ofradiation inducing such changes may not be different
between different genomic regions). However, theirrecoverability in live births seems more dependent onwhether the loss of the gene/genomic region is compatible
with viability in heterozygotes.
445. Genes are known to differ in their response toradiation-induced mutations. For example, data on recessive
specific-locus mutations in mouse spermatogonia show that

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UNSCEAR 2001 REPORT

even among the small number (n = 7) of genes studied, there
is more than a 30-fold difference in their observed radiation
mutabilities, with the s locus being the most mutable and thea locus the least mutable [R17, R20]. If one includes the locistudied by Lyon and Morris [L5], the range is even wider.
Further, there are those such as the histocompatibility (H)genes in the mouse [K23, K28] or the ouabain resistancegene in mammalian somatic cells, at which no radiationinduced mutations have been recovered [A8, T4].
446. The observations that in mice most radiation-induced
recessive mutations at specific loci, although initially identified
through the phenotype of the marker gene under study, areoften multi-locus deletions strongly support the view thatdifferences in response between genes for induced mutations
stem not only from the properties of the marker gene but also
from the genomic region in which it is located. One would
therefore expect that in some genes, radiation-induced
mutations will be recovered at high frequencies because either
they or the genomic region in which they are located cantolerate deletions and yet be compatible with viability of theheterozygotes (in vivo studies) or of the cell carrying themutation (somatic cell studies). In other genes, however,induced mutations will be recovered at lower frequencies or
not at all, because these genes or the genomic regions cantolerate only specific types of changes or no change at all.
These considerations underscore the general concept that thestructural and functional attributes of the genes and theirgenomic context are among the major determinants that permit,
minimize, or exclude an induced genetic change (e.g. adeletion) being recovered in a liveborn offspring.
(c) Mutational changes and their effects
on gene function
447. With Mendelian diseases, the effects of mutationalchanges can be classified according to whether the changes
cause loss of normal gene function or gain of a new
function. As is well known, normal gene function can beabolished by different types of point mutations, partial or
total gene deletions, disruption of gene structure bytranslocations or inversions, etc. In most cases, loss-offunction mutations in enzyme-coding genes are recessive.
This is so because for most of these genes, 50% of the
product is sufficient for normal functioning.
448. Loss-of-function mutations in genes that code forstructural or regulatory proteins result, however, in
dominant phenotypes through haplo-insufficiency (i.e. a
50% reduction of the gene product in the heterozygote is
insufficient for normal functioning but is compatible withviability) or through dominant negative effects (the mutant
product not only loses its own function but also prevents
the product of the normal allele from functioning in aheterozygous individual). Dominant negative effects areseen particularly with genes whose products function as
dimers or multimers [B2, S10].
449. In contrast, a gain of function is likely when only
specific changes in a gene cause a given disease phenotype.

While gains of truly novel functions are unusual except incancer, in inherited diseases, gain of function usually meansthat the mutant gene is expressed at the wrong time indevelopment, in the wrong tissue, in response to the wrong
signals, or at an inappropriately high level [S13]. The
mutational spectrum of gain-of-function mutations would
therefore be more restricted, and deletion or disruption of
the gene would not produce the disease.
450. Radiation-induced mutations, on the other hand,because they are often multigenic deletions, cause loss offunction through haplo-insufficiency. It is an interesting
fact that most mutation systems used thus far to study
radiation-induced mutations were designed to score forinduced recessive mutations, although some were aimed atdominant mutations in (as yet) unknown genes. Attempts torecover radiation-induced mutations in genes in which the
mutant phenotype is due to a dominant gain of function(e.g. mutations in histocompatibility genes in the mouse) or
when a specific base-pair change is involved (e.g. electrophoretic mobility variants such as those used in genetic
studies of the children of atomic bomb survivors) have been
unsuccessful. Gene systems in which the mutant phenotype
is due to loss of function arising via dominant negative
effects have not been used in studies of radiation-induced
mutations.
3. Radiation-induced mutations and theirrecoverability in radiation mutagenesis studies
451. In spite of the number of differences between
spontaneous and radiation-induced mutations, the fact
remains that radiation mutagenesis studies with a variety ofexperimental systems have been very successful. The
possible reasons for this are now becoming evident:
although the initial choice of marker genes for the study of
induced mutations (in Drosophila, mice, etc.) was dictatedmore by practical considerations such as obtaining
sufficient numbers of mutants and their easily recognizable
mutant phenotypes than by their relevance to human genetic
diseases, in retrospect, it is clear that the successful
mutation test systems (such as the mouse specific-locus
systems) have been those in which, by and large, the genes
chosen for study and their genomic regions were notessential for survival of the heterozygotes, and most of themutational events scored are of the recessive loss-offunction type involving the marker and several
neighbouring genes. Consequently, induced mutations(predominantly multi-locus deletions) could be identified
through the phenotype of the marker genes and recovered
for further studies.
452. Considering the potentially large numbers of genes
involved in the development of the vertebrate skeleton andof the lens of the eye and in which mutations can result inskeletal abnormalities and cataracts, respectively, theabsolute numbers of mutations recovered in the skeletal andcataract mutation tests with mice (e.g. [E10, E21, F16,
S109, S110]) are much lower than those in the recessive

ANNEX: HEREDITARY EFFECTS OF RADIATION

specific-locus tests. Again, this is not unexpected, since theinduced mutational events scored are predicted to be of thedominant loss-of-function through haplo-insufficiency type,
and the recoverability of such mutations, especially themulti-locus deletions, must be associated with far morefunctional constraints than that of recessive loss-of-function
mutations. Finally, the test systems that have been least
successful (e.g. the H-loci in the mouse [K23, K28] orouabain resistance in mammalian somatic cells [A8] arethose in which the genes themselves are essential forsurvival and/or are located in gene-rich regions of the
genome and for that reason cannot tolerate induced
deletions.
453. The above concepts are illustrated in Table 40 in which
the genes studied in experimental systems are ranked indescending order of recoverability of mutations induced inthem. The genes at which induced mutations have been
recovered belong to the first two categories. Although there
are no empirical data for genes assigned to ranks 3!5 and
7!9, such genes have been included in Table 38 to provide aframework for inquiring which of the studied human genes
may be judged to be potentially responsive to recoverable
induced deletions, as discussed in the next Section.
4. Criteria for recoverability and the potential
recoverability correction factor(PRCF) concept454. Since at present, there is no alternative to the use of“recovered” mutations in the mouse for quantitative
prediction of risks in humans, ways need to be found to
bridge the gap between these and the possible risk ofgenetic diseases to liveborn progeny of irradiated parents.
One way to do this is to define some tentative criteria forrecoverability on the basis of “recovered” mutations instudies with experimental systems, apply these criteria tohuman genes of relevance on a gene-by-gene basis and assess
which of these may be considered to be candidates forpotentially recoverable radiation-induced mutations in live
births. The operative words are “potentially recoverable”
because (a) knowledge of the structural and functional
genomics of the human genome is incomplete at present; (b)no radiation-induced germ cell mutations have been foundthus far in humans to provide a frame of reference or toverify the validity of the assessments; and (c) at the present
state of knowledge, the criteria cannot be considered anything
more than tentative; they will certainly change with advancesin knowledge.
(a) Criteria for recoverability
455. To keep the arguments simple, one starts with theassumption that a multigenic deletion is induced in agenomic region containing the gene of interest and thequestion asked is: given the structural and functional
attributes of the gene and genomic region, can this deletion
be considered potentially recoverable in a live birth?
Among the attributes considered in applying these criteria
are: gene size, location, normal function, known mutational

71

mechanisms, the spectrum of naturally-occurring mutations,
whether the genomic region of the gene is gene-rich andwhether intragenic (including the whole gene) and multilocus deletions are known.
456. In assessing gene-richness, the MIM gene map [M2]
which presents the cytogenetic location of “disease” genes
and other expressed genes in given cytogenetic bands, isused. While it is clear that the resolution of the cytogenetic
map is coarse (an average band in a 550 band metaphase
chromosome preparation contains about 6 Mb of DNA, anamount sufficient to accommodate many, even large-sized
genes), there is no other alternative at present to judge
gene-richness of different chromosomal regions. On further
point relates to deletions. Although, as discussed in
Chapter II, naturally occurring deletions do not occur
randomly (and have specificities determined by DNA
organization of the genomic region in which they occur),for the purpose of these assessments, it has been assumed
that the recoverability of an induced deletion is governedmore by whether a given genomic region can tolerate largechanges and yet be compatible with viability than bystructural organization per se. The criteria used for theassessments are the following:
(a)

(b)

(c)

An induced deletion of a gene/genomic region isconsidered “unlikely to be recovered” when thephenotype of a given naturally occurring disease isdue to (a) specific gain-of-function mutations or lossof-function mutations through dominant negative
effects or is the result of expansion of trinucleotide
repeats; (b) loss-of-function mutations restricted toonly a part of the gene; and (c) overexpression of thewild-type gene product (for example, with specificduplications). The assessment “unlikely to be
recovered” also applies when the gene is located in acytogenetic (sub)band in which at least a few
additional genes are also located;
The potential recoverability of an induced deletion is
judged to be “uncertain” (a) when the gene is large,
codes for an essential structural protein, the known
genetic changes are missense and nonsense mutations(or small intragenic deletions or insertions) and when
whole gene deletions are rare and (b) with structuralprotein coding genes in which naturally arising wholegene deletions are not rare, but the gene is located ina putative gene-rich region (not necessarily in thesame cytogenetic band) and information on the othergenes and/or their functions is insufficient.
An induced deletion in a gene/genomic region isconsidered “potentially recoverable” when that geneis non-essential for viability of the heterozygotes andis also located in a genomic region that is also notessential for viability (e.g. when the gene is large andwhole gene as well as multi-locus deletions are
known to occur in that region). Additionally, if
rearrangements (e.g. translocations or inversions) are
known to occur with breakpoints in the gene/genomic
region of interest and produce the disease phenotype,then “mutations” in that region are also assessed to be

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UNSCEAR 2001 REPORT

potentially recoverable. The presumption is that suchgenes are similar to the mammalian genes used inexperimental studies on induced mutations; categories
1 and 2 in Table 40.
(b) The concept of potential recoverability
correction factor (PRCF) and revision of therisk equation
457. The criteria defined above provide a reasonable basis
to classify the response of the genes of interest to
recoverable induced deletions into three groups, namely,group 1, “unlikely to be recovered”, group 2, “uncertain”
and group 3, “potentially recoverable”. It should be notedthat the assignment to group 1 is less subjective andtherefore more reliable than that to the other two groups. In
general terms, if one analyses a total of N genes, and if namong them can be excluded as “unlikely to be recovered”,
the remainder (made up of the “uncertain” and “potentially
recoverable” groups) together constitutes (N ! n) and thefraction (N ! n) /N provides a crude measure of genes atwhich induced mutations may be recovered. This fraction
is called the unweighted potential recoverability correction
factor (PRCF).
458. The potential recoverability correction factor as
estimated above, however, does not take into account thedifferences in the incidence of the diseases that areassigned to the different groups. For example, if a disease
with a high incidence belongs to group 1, societal concern
about radiation effects will be far less than when it belongs
to the other two groups. Consequently, some weighting for
disease incidences is required.

disease; (c) introduce disease-class-specific potential
recoverability correction factors into the risk equation. Of
these, the third alternative is preferable for two reasons: (a)the original definitions of doubling dose (i.e. a ratio of
spontaneous and induced rates of mutations of a set of
known genes based on empirical observations) andmutation component (a quantity that predicts the relative
increase in disease incidence per unit relative change inmutation rate, but which does not take into accountrecoverability of induced mutations) can be retained
without modifications and (b) with further advances instructural and functional genomics of the human genome
and in the molecular analysis of radiation-induced
mutations, there is the real prospect of defining potential
recoverability correction factors with greater precision thanis now possible. With the incorporation of potential
recoverability correction factor, the revised risk equation
becomes:
Risk per unit dose = P × [1/DD] × MC × PRCF

(19)461. It is worth stressing here that the starting assumption
in the assessments is that the principal type of radiationinduced genetic change is a multi-locus deletion and thatthe genomic region containing the gene of interest hassustained such a deletion. Consequently, the potential
recoverability correction factor as estimated above does nottell anything about the absolute radiation risk of a genetic
disease; it only indicates which disease-causing mutations,if induced, may be potentially recoverable within theframework of the criteria used.
5. Potential recoverability correction factor
for autosomal dominant and X-linked diseases

459. If P is the total incidence of diseases due to mutations
in N genes and p is the incidence of diseases due tomutations in (N  n) genes classified in groups 2 and 3,
then the weighted PRCF becomes p(N  n)/(PN). The
Committee suggests, however, the use of a range provided
by the unweighted and weighted PRCFs to avoid theimpression of undue precision. One would hope that
advances in structural and functional genomics of thehuman (and mouse) genomes and in molecular studies ofradiation-induced mutations in experimental systems might
permit defining the magnitude of PRCFs with greater
precision than is now possible.

462. Tables 10 and 12 provide the basic information on
estimates of incidence of autosomal dominant and X-linked
diseases and on the genes that underlie these diseases.
Since not all of them fulfill the requirements for inclusion(sufficient data on: incidence, chromosome map position of
the genes, gene size, structure and function, genomic
context), only a subset of diseases considered could be used
for the present analysis. The diseases (genes) included in
the different groups are given in Table 41. Full details of
the assessments are discussed in [S16].

460. It is obvious that when the potential recoverability of
induced mutations is taken into account, the predicted risk
will become smaller than when it is not. Stated differently,
the rate of induced mutations in human disease-causing
genes that are compatible with viability will be smaller thanthe estimated rate of such mutations in the mouse
experiments that provide the basis for risk estimation. In
principle, one can envisage three ways of incorporating theconcept of potential recoverability of induced mutations
within the framework of the risk equation, i.e. equation(13): (a) suitably increase the doubling dose (DD) such that
1/DD becomes a smaller fraction; (b) decrease the mutation
components (MCs) for the different classes of genetic

463. Inspection of Table 41 reveals that in group 1 arediseases which are due to (a) trinucleotide repeat
expansions (e.g. Huntington disease, spinocerebellar
ataxias, myotonic dystrophy); (b) specific point mutations
causing gain of function (e.g. mutations in the FGFR3(achondroplasia), FGFR2 (Apert syndrome) and RHO(retinitis pigmentosa); (c) a specific tandem duplication
causing gain of function (i.e. overexpression of the wildtype gene product) (e.g. PMP22-gene associated CharcotMarie Tooth (CMT) disease; and (d) a restricted array ofpoint mutations (e.g. mutations in ApoB-100 (in one formof autosomal dominant familial hypercholesterolemia) or
point mutations, small specific intragenic deletions which

ANNEX: HEREDITARY EFFECTS OF RADIATION

cause loss of function due to dominant negative
mechanisms (e.g. MYH6, MYH7, TNNI3 and others infamilial hypertrophic cardiomyopathies) and COL1A1,
COL1A2 and COL1A3 in osteogenesis imperfecta types II
to IV and FBN1 in Marfan syndrome). Also included in thisgroup are genes which are relatively small in size which arelocated in putative gene-rich regions (e.g. VMD2 gene inBest macular dystrophy, PBGD gene in acute intermittent
porphyria and TP53 gene in Li-Fraumeni syndrome).
464. The group 2 is comprised of genes for which the
genomic context information is insufficient (e.g. VHL,
BRCA2, EDNRB) and/or those in which large intragenic
and multilocus deletions are rare. Group 3 includes genes
which are generally large and constitutional deletions, someextending beyond the confines of the genes (andtranslocations and inversions with the breakpoints in thegene causing the disease phenotype) are known in spite of
the putative gene-rich nature of the region (e.g. ANK1,
EXT1, EXT2, RB1).
465. For X-linked diseases, the assessment is based onwhether the induced deletion will be compatible withviability in males and cause disease (since the loss of even
the whole X chromosome is compatible with viability but
results in 45,X females).
466. The summary of the analysis, presented in Table 42shows that 42 of 59 genes involved in autosomal dominantdiseases (71%) are judged to belong to group 1 (“unlikely
to be recovered”group) and the remaining 17 (29%) to theother two groups, yielding an unweighted PRCF estimate of
0.29. The estimated incidence for the former group of 42
diseases is 46.45/104 live births and that for the latter groupof 17 diseases, 55.9/104. Therefore, the weighted PRCF
becomes 0.157 (i.e. [17 × 55.9]/ [59 × 102.35] = 0.157). If
X-linked genes are included, the comparable estimates forunweighted and weighted PRCFs become, respectively 0.36
(i.e. 24/67) and 0.199. Since the overall estimated incidenceof autosomal dominants is an order of magnitude higher
than that for X-linked diseases (i.e. 150/104 versus 15/104;
Table 9), the PRCF estimates for the former are more
relevant in the context of risk estimation. The Committee
therefore suggests the use of the PRCF range of 0.15 to
0.30 in the risk equation for estimating the risk of
autosomal dominant and X-linked diseases.
6. Potential recoverability correction factor
for autosomal recessive diseases
467. The recoverability of induced recessive mutations is
also subject to constraints imposed by the structure,function and the genomic contexts of the underlying genes.
However, since these mutations are first present inheterozygotes (and 50% of the gene products are generally
sufficient for normal function), one can assume that evenlarge deletions may be recoverable in heterozygotes (unlessthe deletion involves neighbouring essential structuralgenes, resulting in inviability of heterozygotes). Addi-

73

tionally, induced recessive mutations do not, at least in thefirst few generations, result in recessive diseases. As
discussed in Chapter IV and in Section C of this Chapter,the mutation component for recessive diseases is close tozero in the first few generations. Consequently, there is noneed to estimate potential recoverability correction factor
for this class of diseases. Note, however, that ignoring
potential recoverability is equivalent to assuming PRCF
= 1, which theoretically will result in an overestimation of
the risk, i.e. see equation (19). However, in reality, since
mutation component is close to zero, the use of the above
assumption has no consequence to the estimate of risk.
7. Potential recoverability correction factor
for multifactorial diseases(a) Chronic multifactorial diseases
468. The finite-locus-threshold model used to estimate themutation component of multifactorial diseases (Chapter IV),
assumes that (a) the genetic component of liability to disease
is due to mutations in a finite number of genes; (b) the
affected individuals are those whose genetic component ofliability exceeds a certain threshold; and (c) radiation
exposure causes a simultaneous increase in mutation rate in
all the underlying genes, which in turn, causes the liability toexceed the threshold. Consequently, the requirement ofpotential recoverability also applies to all the induced
mutations as well.
469. A crude approximation of total potential recoverability(for each multifactorial phenotype) is the xth power of that for
mutation at a single-locus, where x is the number of gene loci,assumed to be independent of each other, controlling a
multifactorial disease. If, as discussed earlier, the potential
recoverability correction factor for autosomal dominant andX-linked diseases is in the range of 0.15 to 0.3, for chronic
multifactorial diseases, these figure becomes 0.15x to 0.30x.
With the assumption of just 2 loci, the estimates become 0.02
to 0.09 and with more loci, will be even smaller. Intuitively,
these conclusions are not unexpected when one considers that
here one is estimating the probability of simultaneousrecoverability of induced mutations in 2 or more independent
genes, mutations at which underlie a multifactorial disease.
470. The Committee will use the range of 0.02!0.09 forrisk estimation noting that this range (based on just 2 loci)is unlikely to underestimate the risk: this is because of thefact that at low doses of radiation of interest in risk
estimation, even the initial probability of simultaneously
inducing mutations in at least 2 genes underlying a chronic
multifactorial disease must be very small.
(b) Congenital abnormalities
471. Although naturally occurring congenital abnormalities
are classified as a subgroup of multifactorial diseases(Chapter III), it should be realized that the adjective“congenital” (meaning present at birth), has no aetiologicalconnotation. As discussed in Section E of this Chapter, inUNSCEAR 2001 REPORT

74

contrast to naturally occurring congenital abnormalities,
radiation-induced ones are predicted to show, by and large,
autosomal dominant patterns of inheritance, as has indeed
been found to be the case in mouse radiation studies onskeletal abnormalities, cataracts, growth retardation, etc.
(e.g. [C45, C46, E10, E21, E22, F16, K24, K18, K19, L52,
S109, S110]). It is therefore possible to develop a
composite estimate of the risk of these effects on the basisof mouse data, without recourse to the doubling-dose
method, obviating the need to calculate potential
recoverability correction factor for this class of diseases(see Section VII.E).

475. With the revision of the risk equation by including
potential recoverability correction factors, the risk per unit
dose becomes a product of four quantities, i.e. risk per unit
dose = P × 1 / DD × MC × PRCF. Since potential
recoverability correction factor is a fraction, the estimate ofrisk obtained with the revised risk equation will be smaller.

8. Summary

1. Background472. In this Section, a new concept, namely that of potential
recoverability radiation-induced mutations in human live
births is advanced and the procedure for estimating what arereferred to as the potential recoverability correction factors(PRCFs) are discussed. It is suggested that the inclusion of
disease-class specific potential recoverability correction
factors in the risk equation permits one to bridge the gap
between radiation-induced mutations recovered in mouse
experiments and the potential risk of radiation-inducible
genetic disease in humans.

476. The concept advanced in this Section, namely thatradiation-induced genetic damage in humans is more likely
to be manifest as multisystem developmental abnormalities
rather than as single-gene diseases in the progeny ofirradiated parents, is also new and used for the first time by
the Committee. It does not necessarily contradict the viewthat there may be a finite but small risk of radiationinducible Mendelian diseases when the potential
recoverability correction factors discussed in Section D aretaken into account. This concept represents another logicaloutcome of the integration of knowledge and insights fromhuman molecular genetics into the framework of genetic
risk estimation [S43]. The basis for this concept, theexperimental data supporting it and the implications for risk
estimation are discussed in the following paragraphs.

473. On the basis of mutations recovered in mouse
experiments, criteria for assessing the potential recoverabilityof induced mutations in human genes are developed andapplied to human genes of interest from the disease point ofview on a gene-by-gene basis. The attributes of human genes
considered in applying these criteria are: gene size, location,
normal function, known mutational mechanisms, thespectrum of naturally occurring mutations, whether the
genomic region of the gene is gene-rich and whether
intragenic (including whole gene) and multi-locus deletions
are known.
474. The analysis permits the estimation of unweighted
potential recoverability correction factors or PRCFs (i.e. thefraction of genes among the total studied that may be
responsive to recoverable induced mutations) and weighted
potential recoverability correction factors (i.e. weighted by
the respective incidence of the diseases). The results showthat the potential recoverability correction factors forautosomal dominant and X-linked diseases are of the orderof 0.15 (weighted) to 0.30 (unweighted) and unlikely to be
more than 0.02 (weighted) to 0.09 (unweighted) for chronic
multifactorial diseases. The potential recoverability
correction factor calculations are not made for autosomal
recessive diseases, since for these diseases, one of the factors
in the risk equation, namely, the mutation component is close
to zero and the projected risks are already very small for the
first few generations. For congenital abnormalities, thepotential recoverability correction factor calculations areunnecessary, since the available empirical mouse data on
developmental abnormalities can be used to obtain an
approximate estimate of risk without recourse to the
doubling-dose method.

E. MULTISYSTEM DEVELOPMENTAL
ABNORMALITIES AS MANIFESTATIONSOF RADIATION-INDUCEDGENETIC DAMAGE IN HUMANS

477. In the work of the UNSCEAR and BEIR Committees,
naturally occurring genetic diseases have been (and stillare) used as a convenient framework for risk estimation.
The general logic remains easy to defend. If, in wellconducted studies, significant increases could bedemonstrated, this would be cause for concern; however, if,
as it turned out, no increases could be seen, this would
strengthen the premise for the conclusion that the genetic
risks of radiation are likely to be small (as extrapolated
from the specific genetic diseases considered). This, in turn,
reassured geneticists and the public alike. However, theabove inference provides only a partial answer to thebroader question of the genetic risks of radiation exposures.
478. Consider the following: radiation does not “know”
that genetic risk estimators are interested in mutations incertain genes, and it is unlikely to “respect” the fact thatgeneticists have classified these diseases as Mendelian,chromosomal, and multifactorial for convenience of study.
What if the phenotype of damage induced in regions of the
genome other than the genes under study goes undetected
and is therefore not scored? It is clear that the problem
becomes one of delineating the phenotypes of thosechanges that are compatible with viability and thus
recoverable and that may not necessarily have thephenotypes of known, studied mutations.
479. For the sake of the present discussion, assume that a
multigenic deletion has been induced in a certain region of

ANNEX: HEREDITARY EFFECTS OF RADIATION

the genome in stem-cell spermatogonia or oocytes. To berecoverable in a live birth, the induced deletion must
successfully pass through the screen of gametogenesis,
fertilization, and embryonic development and result in a
viable birth. Induced genetic changes, including deletions,that are incompatible with viability will not come to view inlive births; they will add to the already high amount of
spontaneously occurring genetic changes that is normallyeliminated either as zygotic deaths, early embryonic losses,
or spontaneous abortions.
480. A proportion of the induced damage, however, may becompatible with viability and could therefore be recoverable
in the offspring if it is known what their phenotypes are likely
to be, bearing in mind that the recoverable damage may be
induced in regions of the genome for which there are, as yet,no “windows”. Some insights into the potential phenotypesof such changes come, again, from human molecular biology,
namely, from studies of naturally occurring microdeletions in
the human genome.
2. Insights from studies of humanmicrodeletion syndromes
481. The microdeletion syndromes, also termed contiguous
gene deletion syndromes or segmental aneusomy syndromes,
are conditions that result from deletions of multiple, often
functionally unrelated yet physically contiguous loci that arecompatible with viability in heterozygous condition; they are
identified clinically through a characteristic association ofunusual appearance and defective organ development. Mental
retardation and growth retardation are often prominent
features.
482. It is now known that some chromosomes, such as 19
and 22, are relatively gene-rich (the same is true of Xq22.3,
Xq21.2, and Xp11.4!p11.3), whereas other chromosomes,
such as 4, 13, and 18 (and the Y) are relatively gene-poor,and that the gene density is high in telomeric regions [M2].
The fact that except for trisomy 21, only trisomy 13 and 18
are compatible with viability speaks also to the relative
scarcity of genes on these chromosomes. Considering thelarge variations in gene density in different chromosomes/
chromosomal regions, one would a priori expect that if
viability-compatible microdeletions occur in gene-richregions, they may have a clinically recognizable phenotype;if not, the diagnostic hallmarks may be fewer. For instance,in the Xq22.3 region, small and large deletions of one to six
genes have been found [B9, S13], with the affected males
showing superimposed features of contiguous loss of genes,
depending on which have been deleted.
483. Many examples of autosomal microdeletions(detected cytogenetically and/or using molecular methods)
are now known (Table 43). These examples show that theirdistribution across the genome is non-random. This is not
unexpected in the light of differences in gene density indifferent chromosomes (and chromosomal regions)discussed above. The important point here is that despite
their occurrence in different chromosomes, the common

75

denominators of the phenotype of many of these deletions
are mental deficiency, a specific pattern of dysmorphic
features, serious malformations, and growth retardation[E9, E20, S13]. The non-random distribution of
cytogenetically visible deletions across the genome is also
supported by the recent analysis of Brewer et al. [B46],
discussed in Chapter III.
3. Other naturally occurring chromosomal
structural changes and associated diseasephenotypes in humans
484. The fact that, in addition to deletions, a proportion ofnaturally occurring translocations, inversions etc. may be
associated with clinical effects such as mental retardation
and/or congenital abnormalities, spontaneous abortions,
infertility etc., has long been known and continues to bereported in the literature (e.g. [F10, F13, J6, P2]). Whenstudies were made on the location of the breakpoints ofthese chromosomal abnormalities, they were found to be
non-randomly distributed in the different chromosomes(e.g. [C32]). Most of these studies were carried out using
conventional chromosome banding techniques, andconsequently, subtle chromosome rearrangements would
escape detection.
485. Prompted by a number of case reports showing that
subtle chromosome rearrangements at the ends of chromosomes (subtelomeric regions), which are beyond the resolution of coventional banding techniques, may constitute animportant cause of developmental defects and mental
retardation. In particular, Knight et al. [K11] used the FISH
technique (fluorescent in situ hybridization), to study the
integrity of chromosome ends of 284 children with
unexplained moderate to severe mental retardation. The
authors found that such subtle chromosome rearrangements(mostly translocations and unbalanced products derived fromthem) occurred with a frequency of 7.4% in the children withmoderate to severe mental retardation and of 0.5% in thechildren with mild retardation. The abnormalities werefamilial in almost half of the cases. The reason for
mentioning these observations on chromosomal
abnormalities other than deletions is that radiation is capableof inducing such structural changes and a proportion of thesecan cause clinical effects of the types mentioned above.
4. Empirical mouse data on the phenotypic
effects of radiation-induced genetic damage
other than mutations in known genes
486. The general predictions that (a) multisystem developmental abnormalities (which include growth retardation) arelikely to be among the principal phenotypes of deletions andother gross changes induced in different parts of the genome,and (b) by and large, these phenotypes will show autosomal
dominant patterns of inheritance are supported by mouse dataon radiation-induced skeletal abnormalities [E10, E21, S109,
S110] and cataracts [E22, F16, K24], both of which can beconsidered as developmental malformations. The congenital

76

UNSCEAR 2001 REPORT

abnormalities were ascertained through in utero analysis ofpregnant females [N1, N9, N10, N16, K18, K19, L52], andconsequently, no transmission tests could be carried out. It is
known, however, among the malformed fetuses about 30% to
50% are growth retarded [N1, N9, N10, N16, K18, K19], anda proportion of these survive to live birth and adulthood.
[C45, C46, S33]. Searle and Beechey [S33] showed that thephenotype of growth retardation is transmissible as autosomal
dominant albeit with variable penetrance. Further, as may berecalled from Section VI.B.3, the studies of Cattanach et al.
[C45, C46] showed that radiation-induced multi-locus
deletions, duplications and other gross changes constitute thegenetic basis for a significant proportion of the growthretarded animals recovered in their work.
487. It might seem that there is a conceptual contradiction
between naturally occurring developmental abnormalities,
which are interpreted as being multifactorial in origin(Chapter III), and radiation-induced ones in mice, which are
predicted to show autosomal dominant pattern of inheritance(because the underlying events are multi-locus deletions orother gross changes in the genome) and that are documented
here to the extent possible. However, when one views thesedifferences in the light of the following, it is obvious that thecontradiction is only an apparent and not a real one: (a) the
existence of non-allelic heterogeneities (mutations indifferent genes resulting in similar phenotypes); (b) the
existence of a very large number of genes involved indevelopmental processes and which are located in different
chromosomes; (c) the primary reasons for treating naturally
occurring developmental abnormalities as multifactorial are
the absence of knowledge on the genetic factors involved,
aetiological heterogeneity, and the role of environmental
factors in the causation of several of these; and (d) the
emerging concept that human developmental abnormalities
may be treated as inborn errors in development or morphogenesis in obvious analogy with and as an extension of theclassical concept of inborn errors of metabolism [E20].
Therefore, diverse dysmorphogenetic causes (including those“driven” by multi-locus deletions) can produce similar malformations.
488. It is possible to obtain a crude estimate of risk fordevelopmental abnormalities using mouse data on skeletal
abnormalities, cataracts, and congenital abnormalities
diagnosed in utero, all involving irradiation of males[S111]. The rates of induced skeletal abnormalities in thework of Ehling [E10, E21] is about 11 104 gamete1 Gy1
(5 in 754 progeny after 6 Gy of acute x-irradiation) andabout 15 104 gamete1 Gy1 (5 in 277 after fractionatedx-irradiation with 1 + 5 Gy, separated by 24 hours; theactual rate is divided by 2 to take into account theenhancing effect of fractionated irradiation to normalize it
to acute x-irradiation conditions). The comparable rate forthe studies of Selby and Selby [S109] is about 12 104
gamete1 Gy1 (37 in 2,646 after fractionated irradiation as
above; normalized to acute x-irradiation conditions). The
average of the above three estimates is about 13 104
gamete1 Gy1. In discussing these data, the Committee
previously noted [U8] that only about 50% of the skeletal

abnormalities observed in the mouse are likely to impose aserious handicap in humans. Consequently, the rate adjusted
for severity of effect, becomes about 6.5 104 gamete1 Gy1.
For dominant cataracts, the rate is much lower, being about
0.33 104 gamete1 Gy1 (5 sets of experiments with acuteirradiation doses from 1 to 6 Gy [F16].
489. Data on the induction of congenital abnormalities inmice have been published by various investigators [K18,K19, L52, N1, N9, N10, N16]. The following discussion isrestricted to experiments in which males were irradiatedand abnormal live fetuses (descended from irradiated stem
cell spermatogonia) were scored in utero. In one of their
two experiments, Kirk and Lyon [K18] found that thefrequency of malformed fetuses in the controls was high
(2.1%) as a consequence of which, no increases could bedemonstrated at dose levels in the range of 1.08 to 5.04 Gy.
In the second experiment [K19], however, the frequency inthe controls was 0.7% and in the radiation groups, 2.2%
(5 Gy) and 3.1% (5 + 5 Gy, 24 hours interval). The latter
two frequencies were significantly higher than that in thecontrols.
490. In the work of Nomura [N10], involving four doses in
the range from 0.36 Gy to 5.04 Gy, the data show that thefrequencies increase linearly up to 2.16 Gy followed by afalling off at 5.04 Gy. In the light of the above, theCommittee considers it justifiable to restrict its calculations
to Nomura’s data pertaining to doses up to 2.16 Gy. The
data and the rate estimated from these (68 104 Gy1) aresummarized in Table 44. It should be stressed that theseabnormalities were scored in utero, and a significant
proportion of them are lethal after birth. In a review of his
studies over the years, Nomura [N10] made comparisons of
the frequencies of abnormalities in live fetuses with those
ascertained at one week after birth, taking into accountthose that could not have been seen in the fetuses (e.g.
hypogenic testes, atresia hymenalis; see footnote to Table 1
in [N10]). From these, one can estimate that about 40% of
the abnormalities are compatible with survival up to 1 week
[S43]. This means that the rate applicable to human live
births is about 40% of 68 104 or 27 104 gamete Gy1.
491. When the rates estimated for skeletal abnormalities,
cataracts and congenital abnormalities are combined, (i.e.
[6.5 + 0.3 + 27] 104), the resultant figure is about 34 104
gamete1 Gy1. The above rate is for acute x-irradiation.
With an assumed dose-rate reduction factor of 3 for chronic
radiation conditions, the rate applicable for humans
becomes about 10 104 gamete1 Gy1. Assuming further
that this rate is also applicable to irradiation of females, therate for radiation of both sexes becomes twice the above,i.e. 20 104 gamete1 Gy1 [S111]. The Committee will use
this rate in risk estimation.
492. In extrapolating from mice to humans, the Committee
is fully cognizant of the fact that rigorous comparisons of
the abnormalities in the mouse and humans are fraught withconsiderable uncertainties, since the types of abnormalities
one can detect as well as their effects on the individual areANNEX: HEREDITARY EFFECTS OF RADIATION

different in the mouse and humans [N8, S19]. Nonetheless,in view of the fact that many of those observed in mice(albeit lethal in this species) are similar to those known inhuman live births, the Committee considers it useful to gain
some notion, even if only a crude one, of the magnitude ofrisk of congenital abnormalities.
5. Summary
493. In this Section, the concept is advanced that multisystem developmental abnormalities are likely to be among
the more important phenotypic manifestations of radiationinduced genetic damage in humans than mutations in single
genes. The concept is based on what is known about thenature of radiation-induced mutations in experimental
systems (i.e. predominantly multi-locus deletions) and thephenotypes of multi-locus deletions that occur in different

77

chromosomal regions in humans (multisystem developmental
abnormalities). The concept predicts that radiation-induced
developmental abnormalities, by and large, will show autosomal dominant patterns of inheritance. This has been
fulfilled: mouse experiments on radiation-induced skeletal
malformations, cataracts, and growth retardation show thatthese phenotypes are transmitted as autosomal dominant. It issuggested that these data and those for congenital abnormalities ascertained in utero can be used to provide anapproximate estimate of the risk of these developmental
abnormalities without using the doubling-dose method.
494. The mouse data on skeletal abnormalities, cataracts,
and congenital abnormalities diagnosed in utero considered
together permit a crude estimate of risk of developmental
abnormalities of about 10 104 Gy1 for chronic irradiation ofeither sex and twice this value for irradiation of both sexes.

VIII. RISK ESTIMATES
495. In this Chapter, the concepts, data and analyses,
discussed in the earlier Chapters and summarized in thepreceding one, are used for predicting the risk of different
classes of genetic diseases and the revised estimates arecompared with those made by the Committee in the
UNSCEAR 1993 Report [U4]. Additionally the principal
message from the genetic studies carried out on survivorsof the atomic bombings in Japan [N20], i.e. a lack ofdemonstrable adverse genetic effects of radiation, areconsidered in the light of the present risk estimates.
496. The risk of Mendelian and chronic multifactorialdiseases is predicted with the doubling-dose method forwhich the revised equation is:
Risk per unit dose = P × 1/DD × MC × PRCF

(20)

where P is the baseline frequency of the disease class underconsideration, 1/DD is the relative mutation risk per unit
dose, MC is the disease-class-specific mutation component
for the generation of interest, and PRCF is the potential
recoverability correction factor.
497. For developmental abnormalities, which are predicted
to be due to radiation-induced multi-locus deletions and othergross changes, however, the risk estimate is based on
empirical mouse radiation data on skeletal abnormalities,
cataracts, and congenital abnormalities diagnosed in utero,i.e. the doubling-dose method is not used. The direct method,which was used together with the doubling-dose method until
recently, has now been abandoned, but as mentioned above,the data on skeletal abnormalities and cataracts used with thedirect method (along with those on congenital abnormalities
diagnosed in utero) now provide the basis for estimating therisk of developmental abnormalities as a whole. Additionally,
it is no longer considered necessary to make separate

estimates of the risk of chromosomal diseases, since these are
already assumed to be included with developmental
abnormalities.
498. The two radiation scenarios considered here are (a)radiation exposure in every generation and (b) radiation
exposure in one generation only. Although the emphasis ison the risks to the first two post-radiation generations (forboth scenarios), some speculations are made with respect tothe increase in risk at equilibrium for the first scenario.

A. INPUT PARAMETER VALUES
1. Baseline frequencies
499. The baseline frequencies of diseases, P, used in thisAnnex are 16,500 per million live births for autosomal
dominant and X-linked diseases, 7,500 per million live
births for autosomal recessive diseases, 650,000 per millionof the population for chronic multifactorial diseases, and
6,000 per million live births for congenital abnormalities(Table 9; Chapters II and VII).
2. Doubling dose
500. The doubling dose, calculated in this Annex using
human spontaneous mutation rates and rates of induction of
mutations in mouse genes, is 1.0 Gy for chronic, low-dose,
low-LET radiation exposures and is assumed to apply toboth sexes (Chapter VII).
3. Mutation component
501. As in the previous reports, autosomal dominant andX-linked diseases are considered together and are assumed

78

UNSCEAR 2001 REPORT

to have the same mutation component for the purpose ofrisk estimation. For the first post-radiation generation(following radiation exposure either in one generation or in
every generation), MC = s = 0.3; for the second generation,
mutation component is calculated using the equations 9 or
10 discussed in Chapter IV (paragraph 236) for autosomal
dominant diseases. For autosomal recessive diseases,
mutation component in the first few post-radiation
generations is assumed to be zero (paragraph 244). For
chronic multifactorial diseases, a value of 0.02 is used forthe first as well as the second post-irradiation generation forboth radiation scenarios (paragraphs 255 and 268).
502. Radiation-induced developmental abnormalities are
now assumed to result from induced multi-locus deletions(predominantly) and hence predicted to show, by and large,
autosomal dominant patterns of inheritance (Section VII.E).
Since the empirical mouse data on induced developmental
abnormalities can be used to obtain a provisional estimate ofrisk of this type of effects to the first generation progeny (i.e.
without recourse to the doubling-dose method), an estimateof mutation component is not necessary. However, for theestimation of risk to the subsequent post-radiation
generations (under conditions when the population sustains
radiation exposure in one generation only or in every
generation), knowledge of mutation component (which is
dictated by the magnitude of the selection coefficient, s) is
required (see equations (17) and (18)). Useful clues in thisregard are provided by the mouse data of Nomura [N11] andof Lyon and Renshaw [L52] on congenital abnormalities andof Selby and Selby [S109, S110] on skeletal abnormalities.
Tests of F1 male progeny of irradiated [L2, N11] orchemically-treated mice [N11] (i.e. mating of the F1 males tounirradiated females and intrauterine examination of pregnant
females) showed that abnormalities indeed occurred in thelater generations albeit with reduced penetrance and variable
expressivity. Likewise, most animals with induced skeletal
defects (and cataracts) lived to breed [S109, S110] althoughcharacterized by variable expressivity. These observations
support the view that s is not equal to 1 although it is difficult
to estimate its magnitude. The Committee will assume that,for all induced developmental defects considered overall, s
may be in the range from 0.2 to 0.5 for the second postradiation generation (meaning that between 20% and 50% of
the abnormal progeny may transmit the damage to the second
generation).
4. Potential recoverability correction factor
503. The potential recoverability correction factor values
used are 0.15!0.30 for autosomal dominant and X-linked
diseases (paragraph 466), and 0.02!0.09 for chronic
multifactorial diseases (paragraph 470). For autosomal
recessive diseases, potential recoverability correction factor
is not necessary and hence not estimated (paragraph 467).
Note that the range for potential recoverability correction
factor reflects biological and not statistical uncertainties.
For congenital abnormalities, no potential recoverability
correction factor estimates are made.

B. RISK ESTIMATES
504. The calculation of risks is very straightforward oncethe estimates for the input parameters are known. However,to be very clear on the basis for the estimates, theprocedures are presented explicitly in the paragraphs below.
1. Radiation exposure in every generation(a) Autosomal dominant and X-linked diseases
505. Risk per Gy to the first generation progeny= 16,500 106 × 1 × 0.3 × (0.15 to 0.30)
P
1/DD MC
PRCF. 750!1500 cases per million
Risk per Gy to the second generation progeny= 16,500 106 × 1 × [1 ! (1 ! 0.3)2] × (0.15 to 0.30)
P
1/DD
MC
PRCF

. 1300!2500 cases per million(b) Autosomal recessive diseases
506. As stated in paragraph 501, since the mutation
component for autosomal recessive diseases is close to zeroin the first few post-radiation generations, the risk ofrecessive diseases in the second generation is also assumed
to be zero.
(c) Chronic multifactorial diseases
507. Risk per Gy to the first generation progeny= 650,000 106 × 1 × 0.02 × (0.02 to 0.09)
P
1/DD MC
PRCF. 250!1200 cases per million
Since the mutation component in the early generations isestimated to be about the same, i.e. 0.02, the estimate ofrisk to the second generation is the same as shown above,i.e. there will be no noticeable increase.
(d) Developmental abnormalities
508. As discussed in Chapter VII (paragraph 491), based onmouse data (on skeletal abnormalities, cataracts andcongenital abnormalities scored in utero), the risk ofdevelopmental abnormalities to the first generation progeny
can be estimated to be about 2,000 cases per million per Gy.
The risk for the second generation is likely to be [(0.2 to 0.5)
× 2,000] + 2,000 = 2,400 to 3,000 cases per million per Gy.

2. Radiation exposure in one generation only(a) Autosomal dominant and X-linked diseases
509. Risk per Gy to the first generation progeny= 16,500 106 × 1 × 0.3 × (0.15 to 0.30)
P
1/DD MC
PRCF. 750!1500 cases per million

ANNEX: HEREDITARY EFFECTS OF RADIATION

Risk per Gy to the second generation progeny= 16,500 106 × 1 × (0.3 × 0.7) × (0.15 to 0.30)
P
1/DD
MC
PRCF

. 500!1000 cases per million(b) Autosomal recessive diseases
510. Since the mutation component for autosomal
recessive diseases has been estimated to be close to zero in
the first few post-radiation generations, the risk of recessive
diseases in the first two generations is assumed to be zero.
(c) Chronic multifactorial diseases
511. Risk per Gy to the first generation progeny= 650,000 106 × 1 × 0.02 × (0.02 to 0.09)
P
1/DD MC
PRCF. 250!1200 cases per million
Since the mutation component in the early generations isestimated to be about the same, i.e. 0.02, the estimate ofrisk to the second generation is the same as shown above.
(d) Developmental abnormalities
512. The risk of developmental abnormalities to the first
generation progeny is the same as calculated earlier forconditions of radiation exposure in every generation, i.e.
about 2,000 cases per million per Gy. Under the assumptionthat s is in the range from 0.2 to 0.5, the risk to the second
generation can be of the order of about 400 to 1,000 cases
per million per Gy.
3. Summary of risk estimates
513. Table 45 (top portion) presents a summary of the(rounded) risk estimates for the first and second generation
descendants of a population exposed to low-LET, low-doseor chronic radiation in every generation. All the rates are
expressed per Gy of parental irradiation and per million
progeny. It shows that, for the first generation, the risk is of
the order of about 750 to 1,500 cases for autosomal
dominant and X-linked diseases (compared to 16,500 cases
per million live births of naturally occurring ones) and zerofor autosomal recessive diseases (compared to 2,500 cases
per million live births of naturally occurring ones).
514. For chronic multifactorial diseases, the risk is of theorder of about 250 to 1,200 cases (compared to 650,000
cases per million of naturally occurring ones). The estimateof risk for congenital abnormalities (about 2,000 cases
compared to 60,000 cases per million live births) is basedon mouse data. Note that no separate estimates arepresented for chromosomal anomalies, since these effects
are assumed to be subsumed in part under that of autosomal
dominant and X-linked diseases and in part undercongenital abnormalities. Overall, the predicted risks for the
first generation (3,000!4,700 cases per million progeny

79

per Gy of parental irradiation) represent about 0.41% to
0.64% of the baseline frequency (738,000 per million). The
risks to the second generation, as expected, are higher andyet constitute only about 0.53% to 0.91% of the baselinefrequency. Note that for congenital abnormalities complete
selection has been assumed (i.e. none is transmitted; s = 1)
and consequently all the cases are new.
515. The bottom portion of Table 45 shows the estimatesof risk contained in the UNSCEAR 1993 Report [U4]. As
will be evident, (a) the estimates of the baseline frequency
of Mendelian diseases was lower in 1993; (b) the estimatesof risk for these diseases was also made using a doublingdose of 1.0 Gy but did not take into account the potential
recoverability of radiation-induced mutations in live births;
and (c) it was not possible then to provide risk estimates for
multifactorial diseases.
516. Table 46 summarizes the estimates for the first two
post-radiation generations of a population that has sustained
radiation exposure in one generation only. It is clear that thefirst generation risks are the same as those given in
Table 45. With no further radiation, the risk of autosomal
dominant and X-linked diseases declines as a result of
selection. For chronic multifactorial diseases, since
mutation component remains low for several generations,the risk in the second generation remains about the same asthat in the first generation. The risk of congenitalabnormalities is assumed to be of the order of 400 to 1,000
cases per million per Gy.
4. Strengths and limitationsof the risk estimates
517. For the first time, the Committee has been able, in thisAnnex, to incorporate advances in human molecularbiology into the conceptual framework of genetic risk
estimation and to present risk estimates for all classes ofgenetic diseases. In considering these risk estimates, it isinstructive to examine the assumptions that have been
made, the consequent uncertainties, and more specifically,
whether the estimates are likely to be over- or underestimates. The first of these assumptions, namely, equalsensitivity of both sexes to radiation-induced genetic
damage, was dictated by the view that the mouse immature
oocytes may not constitute a suitable model for assessing
the mutational response of human immature oocytes. If, forexample, the human immature oocytes are less sensitive
than stem cell spermatogonia to induced mutations, then the
sex-averaged rate of induced mutations would be lower (i.e.
the doubling dose will be higher, which means lower
relative mutation risk). At present it is not possible toaddress this issue.
518. The average spontaneous mutation rate estimate (thenumerator in doubling-dose calculations) is based on 26
disorders encompassing some 135 genes. Obviously, it
would have been ideal to calculate an average rate based on
rates of mutations for all the diseases included in the

80

UNSCEAR 2001 REPORT

estimate of P, the baseline frequency. This was notpossible. One can only speculate at present on the extent towhich the estimate of the average rate will change whenmutation rate data for all the genes become available.
519. The average induced rate of mutations (thedenominator in doubling-dose calculations) is now basedon 34 mouse genes including 4 loci at which dominant
mutations have been frequently recovered; there are,however, other loci at which dominant mutations have been
recovered rarely, but the data are very sparse. Analysis ofvariations in the locus-specific rates of the loci included in
the computations indicates predominance of loci at which
induced mutations are rare. The Committee’s conjecture atpresent is that the estimated average induced rate may bebiased upwards (i.e. may be an overestimate), but until
more information becomes available, it is difficult to
examine the validity of this conjecture.
520. For autosomal dominant and X-linked diseases, theCommittee has used a mutation component value of 0.3 forthe first generation; this estimate was obtained from ananalysis of a set of autosomal dominant diseases for which
selection coefficients have been published in the literature(recall that the first generation mutation component is equal
to the selection coefficient). Considering the fact that for a
substantial proportion of autosomal dominant diseases
included in the estimate of the baseline frequency, P, onset
is in middle age or later (i.e. after the age at reproduction),
one can infer that the selection coefficients are likely to besmaller. So the average first generation mutation
component will be lower. Consequently, the use of theassumption MC = 0.3 is likely to overestimate the risk.
521. An additional uncertainty is the possible overlap
between the risk of autosomal dominant diseases and that ofthose grouped under “congenital abnormalities” which arealso predicted to be mainly autosomal dominant. While it isevident that many of the former included in the estimate of P
in the risk equation are in fact developmental abnormalities(with effects not always restricted to the bodily system after
which the disease is named), the extent of overlap is difficult
to gauge at present since the estimates for the two classes
have been arrived at in different ways. If the overlap issubstantial, then the overall risk of dominant effects may beless than the sum of the risk for these two classes.
522. For estimating the risk of chronic multifactorialdiseases, a mutation component value of 0.02 has been used.
The estimate actually obtained in the computer-simulation
studies on the dynamics of change of mutation component
and its relationship to broad-sense heritability (of between
about 0.30 to 0.80 for most chronic diseases) is in the range
from 0.01 to 0.02, often closer to 0.01 than to 0.02. If theactual mutation components were in fact closer to 0.01 than
to 0.02, then the use of MC = 0.02 will overestimate the risk.
523. The concept of potential recoverability of radiationinduced mutations in live births represents one of the logicaloutcomes of integrating advances in human molecular bio-

logy into the framework of risk estimation and has been used
for the first time by the Committee (Section VII.D). The
limits of the range of 0.15 to 0.30 for potential recoverability
correction factors used for autosomal dominant and X-linked
diseases represent weighted (i.e. weighted by the incidence
estimates) and unweighted (the fraction of genes among thetotal studied that might be considered to respond to
recoverable induced mutations) as judged by the criteria
developed for this purpose. When the available information
was insufficient to make a proper assessment of potential
recoverability (which was the case with 7 out of 67 genes
considered), these genes were included under the “potentially
recoverable” category, to err on the side of caution.
524. The criteria for potential recoverability of radiationinduced mutations that were developed, however, do nottake into account the breakpoint specificities of naturally
occurring deletions (which seem related to the nucleotide
sequence organization of genes and genomic regions andwhich render them susceptible to the occurrence ofdeletions); a priori, one would not expect that radiation
would be able to faithfully reproduce the specificities ofbreakpoints that nature has perfected over millennia, at least
not in all genomic regions. Should this be the case, even theweighted potential recoverability correction factor would bean overestimate. Only further advances in structural andfunctional genomics of the human (and mouse) genomes
and in molecular studies of radiation-induced mutations inexperimental systems might permit the magnitude ofpotential recoverability correction factors to be defined withgreater precision than is now possible.
525. In estimating potential recoverability correction factors
for chronic multifactorial diseases, it has been assumed thatthe probability of simultaneously recovering induced
mutations in all the genes underlying a given multifactorial
phenotype is the x power of that of mutation at a single locus,
where x is the number of gene loci, assumed to be
independent of each other, controlling a multifactorialdisease. Since one needs to assume a minimum of two loci toconsider a disease multifactorial, the PRCF estimates become(0.15)2 to (0.30)2, i.e. 0.02 to 0.09. Current knowledge
suggests that the number of loci for well studied chronic
multifactorial diseases such as coronary heart disease,essential hypertension and diabetes (Chapter III) is certainly
more than 2. This means that the potential recoverability
correction factors for chronic multifactorial diseases arelikely to be smaller than 0.02 to 0.09, which in turn meansthat the risk is probably less than about 250 to 1,200 cases per
million progeny per Gy that has been estimated.
526. The concept that multisystem developmental abnormalities are likely to be among the quantitatively more
important adverse effects of radiation and that, by and large,
they would show autosomal dominant patterns of inheritanceis used for the first time by the Committee. This is yet anotherlogical outcome of the integration of knowledge and insightsfrom human molecular genetics into the framework of risk
estimation. One should hasten to add, however, that although
not in this form, the concept was implicit in the use of data on

ANNEX: HEREDITARY EFFECTS OF RADIATION

skeletal abnormalities and cataracts (both are developmental
abnormalities) with the “direct method” of risk estimation[U4, U5, U6, U7, U8].
527. For the above class of adverse effects, mutation
component, and potential recoverability correction factor
cannot be reliably estimated. However, a provisional
estimate of risk has been obtained using the available
mouse data on induced skeletal defects, cataracts, andcongenital abnormalities diagnosed in utero (and the
doubling-dose method has not been used). The estimate isabout 2,000 cases per million live births per Gy to the first
generation with the risk to the second generation being
lower i.e. 400 to 1,000 cases (depending on the assumed
selection coefficient range of 0.2 to 0.5). Under conditionsof radiation exposure in every generation, the risk to thesecond generation is assumed to be equal to the sum of the
newly-induced ones plus that due to persistent damage. The
assumption of the selection coefficient range of 0.2 to 0.5
requires validation.
528. Considering the fact that the “target” for radiation
action is the whole genome and that genes involved indevelopmental pathways are in the hundreds (if not
thousands) distributed throughout all the chromosomes, theestimated magnitude of the risk of developmental defects
per se (which is not strikingly different from that for
autosomal dominant and X-linked diseases) is surprisingand even counter-intuitive. One explanation for thisapparent discrepancy is that the risk estimate for autosomal
dominant and X-linked diseases may be an overestimate(for reasons stated in paragraphs 523!524) and that foradverse developmental effects, it may be an underestimate
for at least two reasons:(a) in mouse studies not allabnormalities (especially those affecting the internal organsystems could be fully ascertained and (b) although a
substantial proportion of the induced congenitalabnormalities in the mouse are lethal after birth, this may
not be true of induced congenital abnormalities in humans.
529. It can be argued, however, that a significant proportionof mutations or deletions in developmental genes is recessive,i.e. heterozygotes do not manifest the abnormal developmental phenotype. Some support for this line argument
comes from homozygosity tests of radiation-induced specificlocus mutations in mice which uncovered the existence of
this class of mutations that were not detected by phenotypic
analysis (e.g. [R12]).
530. One can envisage other explanations, which are notmutually exclusive, for the relatively low rate of induced
developmental defects: (a) the structural and functional
constraints associated with the recoverability of induced
multi-locus deletions (which are assumed to constitute themain basis of induced developmental abnormalities),
including those imposed by the simultaneous induction ofat least one inviable deletion elsewhere in the genome,
along with viability-compatible deletions) are such that onlya small fraction of the latter may result in live births; (b) the
low estimated rate is a reflection, although not in any direct

81

sense, of the fact that the coding sequences constitute only
about 3% of the genome, the remainder being made up of
non-coding sequences; therefore, although damage
induction by radiation may not entirely follow the 1:30 ratioof coding versus non-coding sequences (and which mustcertainly be true of multi-locus deletions), relatively moredamage may be sustained by non-coding regions with
presumably no adverse phenotypic effects; and (c) it is due
to some kind of functional redundancy that must be present
in developmental networks.
531. Notwithstanding the uncertainties discussed in thisSection, the Committee believes that in its judgement, (a)the risk estimates presented for the first two generations inthis Annex adequately reflect the current state ofknowledge in this evolving area and (b) further advances inhuman molecular biology and experimental radiation
genetics will enable more precision to be achieved than is
now possible.
5. Genetic risk at the new equilibrium between
mutation and selection
for a population that sustains radiation
exposure in every generation
532. The population genetic theory of equilibrium between
mutation and selection that underlies the use of the doublingdose method predicts that, under conditions of a permanent
increase in mutation rate, the mutation component will reacha value of 1 at the new equilibrium for both Mendelian andmultifactorial diseases. In other words, if there is an x%
increase in mutation rate, there will be an x% increase indisease frequency at the new equilibrium. So, in principle, theequation used for estimating risk (namely, risk per unit dose
= P × 1 / DD × MC × PRCF) can be used, assuming MC = 1
for all classes of genetic disease for which the doubling-dose
method is used.
533. For autosomal dominant and X-linked diseases, using
P = 16,500 106, 1/DD = 1.0, MC = 1 and PRCF = 0.15 to
0.30, one can predict that the risk at the new equilibrium
will amount to some 2,500 to 5,000 additional cases per
million live births per Gy. For autosomal recessive diseases,
MC in the first few generations is zero (and consequently
no potential recoverability correction factor was estimated);
however MC = 1 at the new equilibrium. If the potential
recoverability correction factors estimated for autosomal
dominant and X-linked diseases are assumed to be
applicable to recessive diseases as well, then with P = 7,500
106 (and all the other quantities remaining the same), theprediction is about 1,100 to 2,200 additional cases per
million per Gy. For chronic multifactorial diseases, with
P = 650,000 106 and PRCF = 0.02 to 0.09, the estimate
becomes, about 13,000 to 58,500 additional cases per
million per Gy. For congenital abnormalities, an estimate ofrisk at the new equilibrium is very difficult to obtain inview of the fact a progressive increase in genetic damage in
the genome over time may dramatically increase themagnitude of selection such that individuals affected with

UNSCEAR 2001 REPORT

82

these developmental abnormalities may not survive toreproductive age to transmit the damage. For all classes ofgenetic diseases, the time it takes to reach the new
equilibrium is critically dependent on the magnitude of
selection.
534. Although the calculations shown above illustrate thekind of predictions that are potentially possible, theCommittee firmly believes that it is prudent to limit thesepredictions to the foreseeable future, namely, the first one
or two generations. This is because of the reasoning thatrisk predictions at the new equilibrium imply the totally
unrealistic and untestable assumptions that (a) the
circumstances (e.g. demographic and health care) of humanpopulations would remain constant over very long periodsof time, and (b) the estimates of the various parameters
used to estimate mutation component and the otherquantities in the risk equation would remain unchanged
over tens or hundreds of human generations.

6. Summary
535. In this Section the estimates of parameter values
discussed in Section A have been used to estimate thegenetic risks of radiation exposure. The doubling-dose
method is used for all classes of genetic diseases except fordevelopmental abnormalities, for which mouse data areused. While the emphasis is on risks to the first two postradiation generations (following irradiation in one
generation only or in every generation), some speculations
are made on the approximate magnitude of risks at the new
equilibrium for the latter radiation scenario. Additionally,
the strengths and limitations of the risk estimates are
discussed.
536. The estimates (all expressed per Gy of parental
irradiation per one million progeny) are the following: forthe first generation, the risk is of the order of about 750 to
1,500 cases for autosomal dominants and X-linked diseases(compared to 16,500 cases per million live births ofnaturally occurring ones) and zero for autosomal recessive
diseases (compared to 2,500 cases per million live births ofnaturally occurring ones). For chronic multifactorialdiseases, the risk is of the order of about 250 to 1,200 cases(compared to 650,000 cases per million of naturally
occurring ones). The estimate of risk for congenitalabnormalities is about 2,000 cases per million live births(compared to 60,000 cases per million live births). Overall,
the predicted risks for the first generation (3,000! 4,700
cases per million progeny per Gy of parental irradiation)
represent about 0.41% to 0.64% of the baseline frequency(738,000 per million).
537. For a population exposed to radiation in every
generation, the risk in the second generation (which
includes the risk to the first generation as well) is higher, as
expected, and yet constitutes only about 0.53% to 0.91% of
the baseline frequency.

C. COMPARISON OF THE PRESENTRISK ESTIMATES
WITH THOSE OF OTHER APPROACHES
538. Other approaches to genetic risk estimation are theuse of the “direct method” and the use of a mouse-databased doubling dose of 5 Gy advocated by Selby [S101,
102]. As may be recalled, the Committee first used the
direct method in the UNSCEAR 1977 Report [U8] toobtain an estimate of the risk of dominant effects in thefirst generation progeny on the basis of data on radiationinduced dominant mutations causing skeletal abnormalities
in male mice. Subsequently, in the UNSCEAR 1982 Report[U7], the direct method was extended to include dominant
mutations that resulted in cataracts. The estimated range ofrisk was 1,000!2,000 cases per million progeny per Gy forirradiation of males and 0!900 cases per million per Gy forirradiation of females. For irradiation of males, the lower
limit of the range was based on data on cataracts and theupper limit, on those on skeletal effects. For irradiation of
females, the lower limit of the range was based on theassumption that human immature oocytes would have amutational sensitivity similar to that of mouse immature
oocytes and the upper limit, on the assumption that thehuman oocytes would have a mutational sensitivity similar
to that of mature and maturing oocytes and that it is 0.44
times that of spermatogonia.
539. The various assumptions that were used to convert thedata on skeletal abnormalities and cataracts to estimates theoverall risk of genetic damage causing dominant phenotypic
effects have been discussed in detail in the above andsubsequent reports including the UNSCEAR 1993 Report([U4]; see Table 7 in this Report) and will not be repeated
here. In the UNSCEAR 1993 Report, the Committee
introduced another component of dominant damage based ondata on litter-size reduction (i.e. between birth and weaning)in mice [S20] and other unpublished data bearing on thisissue. The estimates for this category of damage were500!1,000 cases per million progeny per Gy for irradiationof males and 0!500 cases per million progeny per Gy forirradiation of females. [Note that the figures for females are
based on the same assumption as that mentioned in thepreceding paragraph.] The total risk, estimated by this method
therefore was 1,500 to 4,400 cases per million per Gy forirradiation of both sexes (see Table 3 in [U4]).
540. In view of the fact that no new data of relevance tothe direct method have become available since the
UNSCEAR 1993 Report, this method is not further
discussed here. However, the Committee has used the basic
mouse data (on skeletal abnormalities and cataracts) thatwere used with the method (along with those on congenitalabnormalities also in mice) to obtain an overall estimate ofrisk of developmental abnormalities in this Annex.
541. It is instructive to note that, despite the very different
assumptions used with the earlier direct method, the estimateof 1,500 to 4,400 cases per million per Gy of dominant
effects in the first generation progeny obtained with this

ANNEX: HEREDITARY EFFECTS OF RADIATION

method is of the same order as that of 2,750 to 3,500 diseases
per million per Gy (autosomal dominant and X-linked
diseases plus developmental abnormalities) given here (Table
46). Although the direct method as used earlier is notemphasized in this Annex as the way forward, the Committee
considers it a useful one.

D. GENETIC STUDIES ON SURVIVORSOF THE ATOMIC BOMBINGS IN JAPANIN THE LIGHT OF
THE PRESENT RISK ESTIMATES
542. The main focus of the genetic studies of survivors of
the atomic bombings in Japan [N20] had always been a direct
assessment of hereditary risks of exposure to the atomic
bombs in the children of survivors using indicators of genetic
damage that were practicable at the time the studies were
initiated; they were not aimed at expressing risks in terms ofgenetic diseases. As the studies progressed, it became clearthat no statistically significant adverse effects (in any of theeight indicators used) could be demonstrated in the childrenof the survivors. The indicators were: untoward pregnancy
outcomes [UPO], deaths among liveborn infants exclusive of
those resulting from malignant tumours, malignancies in the
F1 children, frequency of balanced structural rearrangementsof chromosomes, frequency of sex-chromosomal aneuploids,
frequency of mutations affecting protein charge or function,
sex ratio among children of exposed mothers, and growth anddevelopment of the F1 children). The data on five of theindicators (i.e. untoward pregnancy outcomes, F1 mortality,
F1 cancer, sex-chromosomal aneuploids, and mutations
altering protein charge or function), however, were
subsequently used to set some limits to the doubling doseswith which they were consistent [N20]. These doubling doses
were expressed as (a) endpoint-specific “minimal doublingdoses” excluded by the data at specified probability levels or(b) the “most probable gametic doubling doses”. The latter
were 3.4 to 4.5 Sv for chronic radiation conditions.
543. Recalling that in the case of UNSCEAR (a) the risk
estimates have been obtained through the use of the doublingdose method (except for congenital abnormalities); (b) theseare expressed in terms of genetic diseases; (c) the estimate of
doubling dose is based on spontaneous and induced rates ofmutations at defined human and mouse gene loci,respectively; and (d) the reciprocal of the doubling dose isused, as one of the factors in the risk equation to predict risks
prospectively. It is obvious that comparisons of the doublingdose used in this Annex with the doubling doses of 3.4 to
4.5 Sv retrospectively estimated in the Japanese studies areinappropriate. The Committee wishes to stress this point here
in view of the fact that over the years, the doubling doses
have become identified with the magnitude of risk as if they
are the only determinant of risk, i.e. a low doubling dose
implying a high risk and a high doubling dose implying a low
risk, irrespective of the fact that the Committee’s calculation
procedure and use of the doubling dose in risk estimation arequite different from that in the Japanese studies.

83

544. Nonetheless, it is possible to make a limited
comparison, admittedly crude, between the empiricallydetermined risk of adverse effects manifest as untoward
pregnancy outcome in the Japanese studies (the untoward
pregnancy outcomes include stillbirths, congenitalabnormalities and death during the first week of life) andthe risk of congenital abnormalities predicted in this Annex.
The regression coefficient for untoward pregnancy outcomein the Japanese studies is 26.4 104 per parental Sv(although the standard error for this is as large [27.7 104]
as the estimate itself) compared to the total background riskof about 500 104 assumed in the calculations As discussed
earlier, the estimate of risk for congenital abnormalities (forirradiation of both sexes) presented in this Annex is of theorder of 60 104 per parental Gy for acute x-irradiation(paragraph 491) compared to the background risk of
600 104 (Table 45). Considering the uncertainties involvedin both these estimates, one can consider the estimated risk
(this Annex) and the risk of untoward pregnancy outcomein the Japanese studies are of the same order. Although thissimilarity may be due to pure coincidence, it should be
realized that the estimate of gonadal dose for this endpointis only about 0.36 Sv in the Japanese studies, andconsequently, the lack of a significant effect is not entirely
surprising.
545. None of the other endpoints used in this Annex issimilar to those used by Neel et al. [N20] in their doublingdose calculations (F1 mortality, F1 cancers, sexchromosomal aneuploids, and electrophoretic mutations),
and so no comparisons are possible. Note, however, that thefirst two of these are multifactorial traits (similar to
untoward pregnancy outcomes) and their responsiveness toan increase in mutation rate (as a result of radiation
exposures) will depend on the magnitude of the genetic (i.e.
mutation-responsive) component, which as Neel et al.
themselves point out, is quite small. Therefore the rates of
induced genetic damage underlying these traits are expected
to be small, and increases will be undetectable at the low
radiation doses (about 0.4 Sv) sustained by most of thesurvivors. The reasons for the lack of significant effects in
sex-chromosomal aneuploidy and electrophoretic mutations(mobility variants and null enzyme mutants) are different:
there is no evidence from mouse studies that radiation iscapable of inducing chromosomal nondisjunction (which isthe principal basis for the origin of sex chromosomal
aneuploidy). A priori, one would not expect electrophoretic
variants to be induced by radiation to any great extent, as
they are known to be mostly due to base-pair changes. Nullenzyme mutants would be expected to be induced but
unlikely to be found at the dose level experienced by mostof the survivors.
546. In spite of the differences in the endpoints and theway the risks are quantified, the main message from theJapanese studies and the risk estimates discussed in thisAnnex is basically the same, namely, that at low doses, thegenetic risks are small compared to the baseline risks ofnaturally occurring genetic diseases.

84

UNSCEAR 2001 REPORTSUMMARY AND CONCLUSIONS
547. No radiation-induced genetic (= hereditary) diseases
have so far been demonstrated in human populations
exposed to ionizing radiation. However, ionizing radiation
is a universal mutagen and experimental studies in plants
and animals have clearly demonstrated that radiation can
induce genetic effects; consequently, humans are unlikely
to be an exception in this regard. Since the publication of
the UNSCEAR 1993 Report, several advances haveoccurred in human genetics, experimental radiation genetics
and in modeling efforts. The Committee took into accountall these developments in revising the estimates of genetic
risks of exposure to low-LET, low dose, low-dose-rateirradiation. The introductory chapter (Chapter I) provides
a setting by briefly outlining the advances in humanmolecular biology and how these, together with those inradiation genetics, permit a restructuring of the conceptual
framework of genetic risk estimation and a reformulation ofsome of the critical questions in the field.
548. The basic molecular aspects of the human genome,
genes, their organization are discussed in Chapter II as are
the kinds of changes (mutations) that are known to occur
spontaneously in single genes and that cause hereditarydiseases; these are called Mendelian diseases. Aspects ofthese diseases covered in this Chapter include: the molecularnature of mutations, the mechanisms by which mutations
arise (including some novel ones), and the complexities of therelationship between mutation and disease.
549. Mendelian diseases are classified into autosomal
dominant, autosomal recessive and X-linked depending on
the chromosomal location of the underlying genes and themode of transmission. Advances in human genetics have
now permitted an upward revision of the estimates ofincidence of Mendelian diseases from 1.25% to 2.4% (from0.95% to 1.50% for autosomal dominants, from 0.25% to
0.75% for autosomal recessives and from 0.05% to 0.15%
for X-linked diseases).
550. Until 1993, the calculation of the doubling dose (oneof the quantities of relevance for risk estimation) was based
entirely on mouse data on spontaneous and induced
mutation rates. The data on spontaneous rates of mutationsof human genes are considered in Chapter II. These rates
differ between the two sexes: the rate in males is higher
than in females, and the former increases with paternal age.
Since spontaneous mutations rates in humans and mice areunlikely to be similar, the Committee favours the view thatthe use of a mouse-data-based doubling dose is incorrect
and that the use of spontaneous mutation rates in humangenes and of induced mutation rates in mouse genes fordoubling- dose calculations is the prudent way forward. An
additional reason for the above conceptual change is that
uncertainties in the calculation of spontaneous mutation
rates in mouse genes have now been uncovered, owing to
the non-inclusion (in the earlier estimates) of data on
spontaneous mutations that arise as mosaics (which

generate clusters of identical mutations in the following
generation). This issue is addressed in Chapter VI.
551. Human genetic diseases that are interpreted to arise as aresult of a complex interplay between genetic and environmental factors are discussed in Chapter III. These diseases arecalled multifactorial diseases and include the common
congenital abnormalities that are present at birth (i.e. cleft lip
with or without cleft palate, congenital dislocation of the hip,etc.) and chronic diseases of adults (e.g. coronary heartdisease, diabetes, etc.). Unlike Mendelian diseases, these
diseases do not show simple predictable patterns of inheritance,
but they do “run” in families, i.e. the risk to relatives of anaffected individual is several times the risk for a random
member in the general population.
552. Congenital abnormalities arise as a result of errors indevelopment and affect an estimated 6% of live births.
Chronic diseases affect about 65% of the population. The
genetic basis of a chronic disease is the presence of agenetically susceptible individual who may or may notdevelop the disease, depending on the presence or absenceof other risk factors, which may be genetic or
environmental. Thus, for these diseases, the more
appropriate concepts are “genetic susceptibility” and “riskfactors”. For example, elevated serum cholesterol levels areamong the known risk factors for coronary heart disease,elevated blood pressure for stroke, and elevated blood sugar
levels for diabetes.
553. For most multifactorial diseases, knowledge of thegenes involved, their number, the types of mutational
alterations and the nature of environmental factors is still
very incomplete. Data from well studied chronic diseases
such as essential hypertension, diabetes, and coronary heartdisease, reviewed in Chapter III, permit one to conceptualize
the relationships between gene mutations and multifactorialdiseases: genetic susceptibility to develop a multifactorialdisease resides in two classes of genes, the so-called“polygenes” whose mutant alleles have small to moderate
effects on the risk factor trait and “major genes” whosemutant alleles have strong effects. Because polygenes are
more common, they contribute to the bulk of variation of risk
factor traits in the population at large. In contrast, mutations
in major genes, although having a devastating effect at theindividual level, are rare and therefore contribute far less tothe variability of risk factor traits.
554. One of the models that has been used to explain thetransmission patterns of multifactorial diseases and which
permits the prediction of risks to relatives of affectedindividuals (from population prevalences) is what isreferred to as the multifactorial threshold model. Thismodel, which relies on principles of quantitative genetics,
assumes that numerous genetic and environmental factors
contribute to what is referred to as “liability” to develop a
disease. Because these factors are assumed to be numerous,ANNEX: HEREDITARY EFFECTS OF RADIATION85

the distribution of liability in the population is normal(Gaussian). Affected individuals are those whose liability
exceeds a certain threshold value.

the rate at which the new equilibrium is reached, depend on
the induced mutation rate and selection coefficients andvary between different classes of genetic diseases.

555. The multifactorial threshold model makes use of theproperties of the normal curve and enables a number ofpredictions, such as the risk to relatives of affectedindividuals. It also enables the conversion of information on
the prevalence of a multifactorial disease in the populationand in relatives of affected individuals into estimates ofcorrelation in liability, from which a useful statistic called
heritability of liability can be estimated. Heritability provides
a measure of the relative contribution of transmissible genetic
effects to the total phenotypic variability, which has both
genetic and environmental components. The multifactorial
threshold model, however, is essentially a descriptive model,
i.e. it does not address the questions on specific genetic
causes or mechanisms of disease susceptibilities or how thedisease frequencies in the population will be affected whenthe mutation rate is increased as a result of radiation
exposure.

559. One of the methods that has been used for risk
estimation (and the one used in this Annex) is what isreferred to as the doubling-dose (DD) method. It is basedon the equilibrium theory mentioned above. The doublingdose is the amount of radiation required to produce as many
mutations as those occurring spontaneously in a generation.
It is estimated as the ratio of the average spontaneous
mutation rate of a given set of genes relative to the averagerate of induction of mutations in the same set of genes. The
reciprocal of the doubling dose is the relative mutation risk
per unit dose. Since 1/DD is a fraction, it is clear that thelower the doubling dose, the higher the relative mutation
risk and vice versa. The risk due to radiation isconventionally expressed as the expected number of casesof genetic disease (over and above the baseline incidence).
For autosomal dominant diseases, for which the diseasefrequency is approximately proportional to the mutation
rate, the risk is estimated as a product of two quantities:

556. The aim of genetic risk estimation, whether it be for
Mendelian or multifactorial diseases, is to predict theeffects of a small dose of radiation (which causes anincrease in the mutation rate) on disease incidence in the
population. Until recently, most of the efforts in this area
were focussed on Mendelian diseases because of the simple
relationship between mutation and disease for this class of
diseases, the availability of empirical data on induced
mutation rates in the surrogate organism chosen for thispurpose, namely, the mouse, and the long-establishedpopulation genetic models which permit inquiry into the
dynamics of mutant genes in populations.
557. The population genetic theory used for the above
purpose is what is referred to as the “equilibrium theory”.
This theory postulates that there exists in the population abalance between two opposing forces, namely, mutations thatarise in every generation and selection that eliminates someof these mutations, depending on their effects on
reproduction (= fitness). The effects of mutations on fitness
can vary, ranging from those that cause death before
reproduction (and therefore are eliminated in one generation)
to those that do not cause death before reproduction in all
individuals (and therefore can persist in the population forvarying periods of time (because they do not cause death of
all affected individuals before reproduction). The mainconcept here is that the stability of disease frequencies thatone sees in a population is a reflection of the existence of an
equilibrium between mutation and selection.
558. When a population is exposed to radiation, newmutations are introduced into the gene pool of the
population, and these induced mutations are also subject toselection. Thus, when a population sustains radiation
exposure in every generation, eventually the population willreach a new equilibrium between mutation and selection ata higher mutation (and thus of disease) frequency. The timein takes (in generations) to reach the new equilibrium and

Risk per unit dose = P × [1 / DD](21)

where P = the baseline incidence and 1/DD is the relative
mutation risk.
560. Since, as stated in paragraph 557, the disease
incidence, P, represents the equilibrium incidence before
radiation exposure, the product of P and 1/DD represents thepredicted incidence at the new equilibrium. Traditionally,
estimates of risk for the first, second, etc. generations wereobtained by “back-calculating” from that at the new
equilibrium, assuming specific values for the selection
coefficient. For X-linked diseases, the procedure is basicallythe same. For autosomal recessive diseases, while estimationof risk at the new equilibrium is straightforward, the risk to
the first few generations is essentially zero, since an induced
recessive mutation does not result in disease. For
multifactorial diseases (for which there is no simple
relationship between mutation and disease), the situation ismore complex and depends on the model used to explain thestability of their prevalence in the population.
561. Methods and algebraic formulations have now beendeveloped to predict the risk of any class of genetic diseasein any post-radiation generation of interest following
radiation exposure either in one generation or in every
generation. These constitute the subject matter ofChapter IV. These methods make use of the concept ofwhat is referred to as the “mutation component” (MC),which enables one to predict the relative increase in disease
incidence (relative to the baseline) per unit relative increasein mutation rate (relative to the spontaneous rate). With
illustrative examples, it is shown that for autosomal
dominant and X-linked diseases, mutation component in thefirst post-radiation generation is equal to the selection
coefficient; under conditions of continuing radiation
exposure in every generation, mutation component
progressively increases to reach a value of 1 at the new

86

UNSCEAR 2001 REPORT

equilibrium. In other words, an x% increase in mutation
rate will result in an x% increase in mutation rate at the new
equilibrium. For autosomal recessive diseases, while themutation component at the new equilibrium is also equal to1, in the first few post-radiation generations, it is essentiallyzero, indicating that the frequencies of these diseases will
not detectably increase in the first few generations. Whenthe increase in mutation rate occurs in one generation only,
the first generation mutation component is the same as thatin the first generation for a radiation scenario involving
radiation exposure in every generation.
562. For predicting mutation component for multifactorialdiseases, the multifactorial threshold model discussed inparagraphs 554!555, was modified by (a) assuming a finite
number of loci underlying the disease and (b) incorporating
mutation and selection as two additional parameters. The
assumption of finite number of loci (in contrast to theinfinite of loci in the multifactorial threshold model) was
dictated by emerging data on chronic multifactorial diseases(reviewed in Chapter III). The incorporation of mutationand selection into the multifactorial threshold model was
dictated by population genetic models on the maintenanceof polygenic variability in populations, which show that theequilibrium theory can be applied to polygenic traits aswell. The resulting finite-locus-threshold model (FLTM)
was used to predict mutation component.
563. The formulation of the finite-locus-threshold modeland the number of parameters that enter into it are such thatthe mutation components cannot be expressed in the formof simple equations (unlike the situation with Mendeliandiseases). Therefore, using specified values for mutation
rate, selection, threshold, etc., computer simulation studies
were carried out to study the dynamics of changes inmutation component with time (in generations) and its
relationship to heritability (paragraph 555) for two radiation
scenarios: radiation exposure in every generation and in one
generation only. The results show that under conditions ofcontinuous radiation exposure in every generation and overa broad range of heritabilities (0.3 to 0.8 for most
multifactorial diseases), the mutation component in the first
several generations is very small, being about 0.02, often
smaller. At the new equilibrium (which is reached after
many or scores of generations, depending on selection
coefficients and assumed increases in mutation rates),
mutation component becomes equal to 1 (a situation similar
to that of autosomal dominant diseases mentioned inparagraph 560). When the increase in mutation occurs in
one generation only, after a transient increase, the mutation
component progressively declines to zero. Although themutation component estimation with the finite-locusthreshold model was originally intended for use in risk
estimation for both chronic diseases and congenitalabnormalities, they are used only for chronic diseases. The
reason for this is explained in paragraph 571.
564. A review is provided in Chapter V of selected aspectsof current knowledge of genes involved in maintenance ofgenomic stability, cell-cycle control, and DNA repair, which,when mutated, cause predisposition to cancers. Collectively,
such cancer-predisposing mutations are believed to accountfor about 1% of cancer cases. Since a proportion of cancerpredisposed individuals may also be sensitive to radiationinduced cancers, the potential increase in cancer risks in aheterogeneous population (i.e. consisting of cancerpredisposed and normal individuals) is discussed using
mathematical models and illustrative examples. It is shownthat unless (a) the mutant gene frequencies; (b) the proportionof cancers attributable to the mutant genes; (c) the
predisposition strength; and (d) radiosensitivity differentials
between predisposed and normal individuals are all high, theamount of increase in cancer risks in the heterogeneous
population is small compared to one that is homogeneous inthis regard.
565. New information is discussed in Chapter VI that has
become available since the publication of the UNSCEAR
1993 Report, from human studies of genetic diseases in theoffspring of long-term survivors of childhood andadolescent cancer (no significant increases), reproductive
outcome in women irradiated during infancy for skinhaemangiomas (no demonstrable adverse outcomes) andpossible genetic effects of radiation exposure resulting fromthe Chernobyl accident (none demonstrable). Additionally,
data are considered on the induction of minisatellite mutations in human germ cells (in the progeny of those who
were resident in heavily contaminated areas in Belarus after
the Chernobyl accident) and in laboratory experiments withmouse germ cells. In both, radiation-induced increases were
demonstrated, but since these are not protein-coding genes,
their relevance for risk estimation cannot be readily
discerned.
566. Also considered in Chapter VI are data on mosaic
mutations in mice (briefly alluded to in paragraph 550) andthe question of their possible relevance for estimating the
spontaneous mutation rate. It is concluded that, at thepresent state of knowledge, the extrapolation of observations on mosaic mutations in a limited number of mousegenes to the human situation is not possible. In view of thisand the lack of similarity of spontaneous mutation rates inhumans and mice mentioned earlier (paragraph 550), theprudent way forward is to abandon the use of an entirely
mouse-data-based doubling-dose estimate and use a doublingdose based on human data on spontaneous mutation rates andmouse data on induced mutation rates.
567. The concepts and data discussed in the preceding
Chapters that are used for risk estimation are recapitulated
in Chapter VII. Additionally presented are (a) an analysis
of human data on spontaneous mutation rates and mouse
data on induced mutation rates and the doubling dose basedon this analysis and (b) two concepts that have not beenused hitherto in risk estimation. One of these has to do withbridging the gap between radiation-induced mutations
studied in mice and the risk of genetic disease in humans,
and the other argues that multisystem developmental
abnormalities are among the principal adverse effects ofradiation-induced genetic damage in human germ cells;

ANNEX: HEREDITARY EFFECTS OF RADIATION

both these concepts represent logical outcomes of theintegration of the advances in human molecular biology
into the framework of genetic risk estimation.
568. The analysis of human data on spontaneous mutation
rates (26 disease phenotypes and an estimated 135 genes)shows that the average rate is 2.95 ± 0.64 106 per gene per
generation. A similar analysis of mouse data on induced
mutations (which now encompasses, besides the morphological specific loci, other genes used in biochemical
studies and dominant mutations at 4 loci, a total of 32
defined genes) shows that the induced rate is 0.36 ±0.10 105 per locus per Gy. The resulting doubling-dose
estimate is 0.82 ± 0.29 Gy. The Committee uses a roundfigure of 1 Gy in risk estimation. Although the doublingdose is the same as that which the Committee has used in
the earlier reports, the present doubling dose is supported
by more data on defined genes.
569. The concept of potential recoverability correction
factor (PRCF) for radiation- induced mutations has been
introduced to bridge the gap between radiation-induced
mutations studied in mice and the risk of inducible genetic
diseases in human live births. It is based on the known
differences (in nature, type, and mechanisms) between
spontaneous disease-causing mutations in humans andradiation-induced mutations in mice. On the basis ofrecovered mutations in mouse experiments, criteria forassessing the potential recoverability of radiation-induced
mutations were developed and applied to human genes ofinterest from the disease point of view. The attributes ofhuman genes considered in the assessments are: gene size,
location, normal function, known mutational mechanisms,
the spectrum of naturally occurring mutations, generichness of the region containing the gene of interest, etc.
570. A gene-by-gene analysis of a total of 67 human genes
permitted the estimation of the unweighted potential
recoverability correction factor (i.e. the fraction of genes
among the total studied at which induced mutations may berecovered in live births) and weighted potential
recoverability correction factors (i.e. weighted by therespective disease incidences). The estimates are: about
0.15 (weighted) to 0.30 (unweighted) for autosomal
dominant and X-linked diseases and no more than 0.02
(weighted) to 0.09 (unweighted) for chronic multifactorialdiseases. No potential recoverability correction factor
calculations are made for autosomal recessives, since forthese, the mutation component is close to zero in the firstfew generations. For congenital abnormalities, potential
recoverability correction factor calculations are notnecessary (see paragraph 571).
571. The concept that the multisystem developmental
abnormalities are likely to be the principal adverse effects ofradiation damage of human germ cells rests on the following
observations or inferences: (a) the whole genome is the target
for radiation action; (b) genetic damage is induced by random
deposition of energy in the cell; (c) the observations that mostradiation-induced mutations are multilocus deletions; (d) the87

knowledge that genes involved in developmental processes
are very many and distributed in nearly all the chromosomes;(e) the findings from studies of many microdeletions (i.e.
those that encompass multiple contiguous genes on a chromosome) in humans (identified in different chromosomes) thatthey share some common attributes, namely, mental
deficiency, specific pattern of dysmorphic features, serious
malformations, and growth retardation; (f) mouse data that
support the view that radiation-induced multi-locus deletions
in different chromosomal regions are associated with growth
retardation and dysmorphic features. The Committee believes
that mouse data on radiation-induced skeletal abnormalities,
cataracts, and congenital abnormalities can be used to provide
a provisional estimate of risk without the need to use thedoubling-dose method.
572. Since most radiation-induced developmental abnormalities are predicted to show dominant patterns ofinheritance (in contrast to naturally occurring ones, which
are interpreted as being multifactorial), the mutation component and potential recoverability correction factor
estimates calculated for chronic multifactorial diseases are
not applicable to developmental abnormalities. However, as
stated in the previous paragraph, since one can now
estimate the risk of these effects using mouse data (without
the need to use the doubling-dose method), the inability toestimate mutation component and potential recoverability
correction factor for developmental effects does not pose
any problem.
573. The final Chapter (Chapter VIII) builds on theconcepts and estimates of the different parameterssummarized in Chapter VII to provide estimates of genetic
risks of radiation exposure focussing on the the first twogenerations. Two radiation scenarios are considered,namely, radiation exposure of the population in one
generation only and radiation exposure in every generation.
The strengths and limitations of the new risk estimates arealso discussed in the Chapter and compared with thosepresented in the UNSCEAR 1993 Report. Additionally, thelack of significant genetic adverse effects in the studies ofsurvivors of the atomic bombings in Japan are consideredfrom the perspective of the new risk estimates.
574. The estimates of risk for the different classes ofgenetic diseases (except congenital abnormalities) havebeen obtained using the doubling-dose method. The
estimate of doubling dose used in the calculations is 1 Gy
for low dose/chronic low-LET radiation conditions. For a
population exposed to radiation in one generation only orin every generation, the estimates of risk to the progeny of
the first post-radiation generation are the following, allexpressed as the number of cases per Gy per million
progeny: autosomal dominant and X-linked diseases,
750!1,500; autosomal recessive diseases, zero; chronic
multifactorial diseases, 250 ! 1,200; congenitalabnormalities, 2,000. The total is about 3,000 to 4,700
cases per Gy per million progeny and constitutes 0.41 to
0.64% of the baseline frequency of 738,000 per million.

88

UNSCEAR 2001 REPORTThe figures for Mendelian diseases are roughly similar to
those presented in the UNSCEAR 1993 Report.
575. When the radiation exposure is limited to one
generation only, the risk to the second post-radiation
generation is lower, as expected. If however, the radiation
exposure occurs in every generation, the risks are higher inthe second post-radiation generation, since these representrisks to the first and second generations.

576. It is argued that while the doubling doses of 3.4 to
4.5 Sv, retrospectively estimated from the Japanese data
(showing no significant adverse genetic effects of radiation)
are not comparable to the doubling dose of 1 Gy used by
the Committee, an approximate comparison of the risk of
untoward pregnancy outcomes in the Japanese studies withthe risk of congenital abnormalities in this Annex showsthat the risks are similar, considering the uncertainties
involved in these estimates.

ANNEX: HEREDITARY EFFECTS OF RADIATION

89

Glossary
AlleleOne of several alternative forms of a gene (or DNA sequence) at a specific chromosome
allocation. At each autosomal locus, an individual possesses two alleles, one inherited fromthe father and one from the mother.

Aneuploid

The chromosome number is not an exact multiple of the haploid number; an individual withan aneuploid chromosome number; usually refers to an absence (monosomy) or an extra
copy (trisomy) of a single chromosome

Anticipation

A phenomenon in which the severity of a disorder appears to become more severe and/or
arise at an earlier age in succeeding generations.

Autosome

Any chromosome other than the sex chromosomes, X and Y; the diploid human genome
consists of 22 pairs of autosomes and one pair of sex chromosomes (X and Y in males and2 X’s in females).

Autosomal dominant disease

One that is due to a mutation in a gene carried on one of the autosomes and manifests its
phenotype in a heterozygote.

Autosomal recessive disease

One that requires two mutant genes at the same locus (one from each parent) carried in theautosomes for disease expression.

Candidate gene

Any gene by virtue of its property (function, expression pattern, chromosomal location,
structural motif, etc) is considered a possible locus for a given disease.

Coding sequence

Those parts of a gene from which the genetic code is translated into amino acid sequencesof a protein.

Codon

A group of three adjacent nucleotides that codes for particular amino acids or for the
initiation or termination of the amino acid chain.

Congenital abnormality

An abnormality that is present at birth; the term does not have an aetiologic connotation.

Contiguous gene syndrome

A syndrome due to abnormalities of two or more genes that map next to each other on achromosome; most often caused by a deletion that involves several contiguous genes.

DiploidA full set of genetic material, consisting of paired chromosomes – one chromosome fromeach parental set; most animal cells except the gametes have a diploid set of chromosomes(compare haploid)

Deletion

Loss of a portion of a gene or chromosome; a type of mutation; a synonym for deficiency.

Dominant allele

One that determines the phenotype displayed in a heterozygote with another (recessive)
allele.

Dominant negative mutations Dominant mutations in which the product of the mutant allele interferes with the functionof the normal allele in the heterozygous state.
Doubling dose (DD)An important concept used in genetic risk estimation. It is defined as the dose of radiation
required to produce as many mutations as those which occur spontaneously in a generation.
It is calculated as a ratio of the average spontaneous and induced rates of mutations in adefined set of genes.

DNA sequence

The relative order of base pairs, whether in a fragment of DNA, a gene, a chromosome, oran entire genome.

Epistasis

The non-reciprocal interaction of non-allelic genes in which one gene masks the expressionof another.

Equilibrium theory

One of the fundamental concepts in population genetics which postulates that mutant
alleles are maintained in the population as a result of a balance between mutations thatarise in every generation and selection which eliminates them.

Exon

A region of a gene containing a coding sequence. Most genes have several exons separated
by introns (non-coding) which are usually longer.

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UNSCEAR 2001 REPORT

Fitness (also called
Darwinian fitness)

The relative ability of an organism to survive and transmit its genes to the next generation.

Frameshift mutations

A mutation that alters the normal triplet reading frame so that codons downstream from themutation are out of register and not read properly.

GameteMature reproductive cell (sperm or ovum); contains a haploid set of chromosomes (23 forhumans.

Gene

The fundamental physical and functional unit of heredity. A gene is an ordered sequenceof nucleotides located in a particular position on a particular chromosome that encodes a
specific functional product.

Genotype(a) the genetic constitution of an individual;(b) the types of alleles found at a locus in an individual.

Germ-line mosaicism

Presence of two or more cell lines in the gonadal cells; implies risk of transmisssion of
mutation present in the gonads to offspring; synonymous with gonadal mosaicism.

Genomic imprinting

A phenomenon in which an allele at a given locus is altered or inactivated depending onwhether it is inherited from the father or the mother. Implies a functional difference ingenetic information depending on whether it is inherited from the father or the mother.

Haploid

A single set of chromosomes (half the full set of genetic material) present in the egg andsperm cells of animals (compare diploid).

Hardy-Weinberg equilibrium The concept that both gene frequencies and genotype frequencies will remain constantfrom generation to generation in an infinitely large, interbreeding population in whichmating is at random and there is no selection, migration or mutation. In a situation wherea single pair of alleles (A and a) is considered, the frequencies of germ cells carrying A anda are defined as p and q, respectively. At equilibrium, the frequencies of genotypic classes
are p2 (AA), 2 pq (Aa) and q2 (aa).
Heritability

An attribute of a quantitative trait in a population that expresses how much of the total
phenotypic variation is due to genetic factors. In the broad sense, heritability is the degree
to which a trait is genetically determined; it is expressed as the ratio of the total genetic
variance to the phenotypic variance. In the narrow sense, it is the degree to which a trait
is transmitted from parents to offspring and it is expressed as the ratio of additive genetic
variance to the total phenotypic variance.

Heterozygote

An individual with different alleles at some particular locus.

Homologous chromosome

Chromosome containing the same linear gene sequences as another, each derived from one
parent.

Homozygote

An individual with the same allele at the corresponding loci on the homologous
chromosomes.

Intron

The DNA base sequence interrupting the protein-coding sequence of a gene; this sequenceis transcribed into RNA, but is cut out of the message before it is translated into protein.

Linkage

The tendency of genes (or other DNA sequences) at specific loci to be inherited together
as a consequence of their physical proximity on a single chromosome; measured by percent
recombination between loci.

Locus (plural: loci)A unique chromosomal location defining the position of an individual gene or DNA
sequence.

Major genes

Those with pronounced phenotypic effects as compared with polygenes.

Mendelian disease

One that is due to mutations in a single gene. Depending on the location of the mutant
genes (in autosomes or the X-chromosome) and their effects on the phenotype, Mendeliandiseases are classified as autosomal dominant, autosomal recessive and X-linked recessiveor dominant.

Mendelian inheritanceA pattern of inheritance which obeys Mendel’s first law of independent segregation of thealleles at the same locus conveyed by each parent.

ANNEX: HEREDITARY EFFECTS OF RADIATION

91

Microdeletion

Deletion of a small piece of chromosome or DNA sequence; may or may not be visible atthe microscopic level.

Microsatellite

Highly polymorphic DNA markers comprised of mono-, di-, tri- or tetranucleotides that are
repeated in tandem arrays and distributed throughout the genome; the best studied ones are
the CA (alternatively GT) dinucleotides repeats; they are used for gene mapping.

Minisatellites

Highly polymoprhic DNA marker comprised of a variable number of tandem repeats that
tend to cluster near the telomeric ends of chromosomes; the repeat often contains a repeatof 10 nucleotides; they are used for gene mapping.

Missense mutation

Mutation that causes one amino acid to be substituted for another.

Mitochondrial DNA

DNA distinct from nuclear DNA in that it is mostly unique sequence DNA and codes forproteins that reside in mitochondria.

Mosaicism

Presence of two or more cell lines derived from a single zygote; can be limited to somatic
cells or to germ cells or can occur in both somatic and germ cells.

Multifactorial disease

A disease that is interpreted to result from the joint action of multiple genetic andenvironmental factors.

Mutational cluster

If a gonad is a germinal mosaic for a mutation in a given generation, clusters of identicalmutant individuals will result in the following generation; this is called a mutational
cluster.
One of the important concepts used in risk estimation with the doubling-dose method. It
is defined as the relative change (i.e. increase) in disease incidence (i.e. relative to theincidence before irradiation) per unit relative change in mutation rate (i.e. relative to thespontaneous rate). It is not the same as the genetic component of the disease; rather, it
quantifies the responsiveness of the genetic component of the disease to increases inmutation rate. If the disease is only partly genetic, since only the genetic component will
respond to an increase in mutation rate, mutation component for such diseases will belower than that for a fully genetic disease. If the disease is entirely of environmental origin,
the mutation component concept does not apply.

Mutation component

Nonsense mutation

Mutation that changes a codon for an amino acid to a termination or stop codon and leads
to premature termination of translation so that the protein is either truncated or absent.

Nucleotide

A subunit of DNA or RNA consisting of a nitrogenous base (adenine[A], guanine [G],thymine [T] or cytosine [C] in DNA, adenine, guanine, uracil [U] or cytosine in RNA.

Oncogene

A gene, or more forms of which is associated with cancer; many oncogenes are involved,
directly or indirectly, in controlling the rate of cell growth.

Paternal age effect

Used in the context of spontaneous mutation rates, it refers to the increase in mutation ratewith the age of the father.

Penetrance

The frequency of expression of a trait or genotype; the proportion of individuals observed
to show a particular phenotypic effect of a mutant gene compared with that expected on
the basis of Mendelian inheritance.

Phenotype

The physical characteristics of a cell or organism as determined by the genetic constitution.

Point mutation

A mutation confined to a single nucleotide.

Polygenic inheritance

Inheritance determined by many genes at different loci, each with small additive effects;
a simple example is height within either sex; see also multifactorial.

Recessive

A trait that is expressed in individuals who are homozygous for a particular allele.

Recessive mutations

Those that produce a specific phenotype when present in the homozygous (autosomal
recessive) or in hemizygous state (X-chromosomal recessive).

Sex-chromosomes

The chromosomes that primarily govern sex determination (XX in women and XY in men);the other chromosomes are autosomes.

Sex-chromosomal geneA gene located on either the X or the Y chromosome. Since the number of genes on the Y
chromosomes is small, unless otherwise specified, most often the term implies location of
the gene on the X chromosome.

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UNSCEAR 2001 REPORT

Somatic cells

All cells in the body except gametes and their precursors.

Synteny

The term synteny (meaning same thread or ribbon; a state of being together in location assynchrony would be together in time) refers to gene loci on the same chromosome
regardless of whether or not they are genetically linked by classic linkage analysis.
Although not quite correct, the term is used nowadays to refer to gene loci in different
organisms located on a chromosomal region of common evolutionary ancestry.

Telomere

The end of a chromosome. This specialized structure is involved in the replication andstability of linear DNA molecules.

Transition type mutation

A mutation which results from the substitution of one purine by another (A to G or G toA) or of one pyrimidine by another (C to T or T to C).

Transversion type mutation

A mutation which results from the substitution of a purine by a pyrimidine or vice versa.

Uniparental disomy

Situation in which an individual has two homologous chromosomes (or chromosomal
segments) from one parent and none from the otherX-linked gene

Gene carried on the X-chromosome.

ANNEX: HEREDITARY EFFECTS OF RADIATION

93

Table 1
Sizes of human genes
Based on [M1], with additions

Gene

Genomic size
(kb)

cDNA (mRNA)(kb)

Number of introns

0.8
1.5
1.7
3.6
4.2

0.5
0.6
0.4
1.2
1.0

2
2
2
3
2

11
18
38
25
32
34
34.
45

1.4
5.0
5.0
2.1
1.5
2.8
1.6
5.5

7
50
50
14
11
7
12
17

90
.100
.110

2.4
5.6
.9.3

12
22
64

186
.230
>300

9.0
6.5
8.4

26
26
>36

2 500

14

69

Small
α-globinβ-globinInsulin
Apolipoprotein E
Parathyroid hormone
MediumProtein C
Collagen 1 pro-α-1Collagen 1 pro-α-2Albumin
Adenosine deaminase
Factor IX
Catalase
Low-density lipoprotein receptor
Large
Phenylalanine hydroxylase
Breast cancer gene 1 (BRCA 1)
Fibrillin

[M10]
[P6]
Giant

Factor VIII
Cystic fibrosis transmembrane conductance regulator (CFTR)
Thyroglobulin[T1]

MammothDystrophin (Duchenne muscular dystrophy)[K13, R8]

Table 2
Molecular nature of mutations in Mendelian diseases[S4]
Number of Mendelian diseases caused byCategory

Autosomal dominant
X-linked
Subtotal
Autosomal recessive
Total

a
b

Base-pair changes.
Predominantly DNA deletions.

Total
Point mutations a

Point mutations andlength mutations b

Length mutations andmicrodeletion syndromes

73
16

18
24

25
8

116
48

89 (54%)42 (26%)33 (20%)

164

111

27

7

145

200 (65%)69 (22%)40 (13%)309

UNSCEAR 2001 REPORT

94

Table 3Distribution of point mutations in some human genes

Disease

Gene

Genomicsize(kb)

Numberof exons

Comments

Ref.

Autosomal dominantOsteogenesis imperfecta

COL1a1

18.50

Nearly over the entire gene

[B2, D2]

Familial hypercholesterolemia

LDLR

45

18

Nearly over the entire gene

[H13, S23]

Breast and ovarian cancer due
to BRCA1 mutations

BRCA1

.100

23

Nearly over the entire gene

[C10, F5, F6,
L8, M12, S24,
T9]

Achondroplasia

FGFR3(.2.5)(cDNA)?

G6A at amino acid residue 380 (Gly307 Arg) in
the transmembrane domain of the protein mostcommon; G6C at the same residue resulting inthe same amino acid substitution in some cases[M5, R4, S11]

Amyloidosis V; gelsolin genedefects

GSN(.2.6)(cDNA)?

G6A (Asp187Asn) is the only mutational event
recorded in studies worldwide; the othermutation is G6T transversion at the same codon(Asp187Tyr) in Danish and Czech families[D8, M1]

Acute intermittent porphyria

HMBS

11

15

21 of the 34 recorded mutations in exons 9, 10,
and 12 (7 in exon 10 and 11 in exon 12)[A5]

Autosomal recessive
Gaucher disease (glucocerebrosidase deficiency)

GBA

.7.6

11

In all exons except 3 and 4; most widespread
missense mutations in exons 9 and 10)[H14, M13]

Mucopolysaccharidosis, type I(glycosidase α-Liduroniase deficiency)

IDUA

19

14

In all exons except 5 and 13; most clustered
towards the beginning (exons 1-3) and middle(exons 6-10) of the gene

[S9]

Phenylketonuria (phenylalaninehydroxylase deficiency)

PAH

90

13

Distributed nearly over all exons[E2]

Cystic fibrosis

CFTR

.230

27

In exons 3-5, 7-8, 10-12, and 20-21; paucity ofpoint mutations in exons 6b, 16, 17a, and 24[T1]

X-linked
X-linked severe combined
immunodeficiency (interleukin-2 receptor defect)

SCIDX1,
IL2RG

4.2

8

In all exons, but most in 2-4[P8]

Glucose-6-phosphate dehydrogenase deficiency

G6PD

.18

13

In all exons except 9, the smallest, and exon 13,
which codes for the carboxyterminus[V5]

Agammaglobulinaemia,
Bruton type

AGMX1,
BTK1

20

19

Over the whole gene, including in the ATG start
codon

[P8]

Lesch-Nyhan syndrome

HRPT

44

9

Nearly over the whole gene including somesplice sites; about 40% of the point mutations
occur in exon 3 in two regions of only 6 bp; exon
5 has 11% of mutations with a 8 bp region[C11, D27, S25,
T10]

Haemophilia A

FVIII

186

26

Missense mutations over the whole gene except
for exon 14 which codes for the B domain which
has no known function; nonsense mutations inexon 1, 7-9, 11, 12-14, 16-19, and 22-26[A4]

ANNEX: HEREDITARY EFFECTS OF RADIATION

95

Table 4
Examples of mutations in one gene resulting in more than one clinical disease (allelic heterogeneity)[M1, R52]
Gene

Chromosomal
location

DiseaseRef.

CMT1A (PMP22) (peripheral
myelin protein 22)

17p12-p11.2

Charcot-Marie-Tooth disease type 1A (CMT1A); hereditaryneuropathy for pressure palsies (HNPP), Djerine-Sottas
syndrome (DSS)[B1, C3, P1, R1,
S8]

APOA1 (apolipoprotein A1)

11q23.3

COL2A1 (collagen type 2, α1)12q12-q13.2

FBN1 (fibrillin)

15q21.1

COL1A1 (collagen type 1, α1)17q21.3-q22

FGFR3 (fibroblast growth factor
receptor 3)

4p16.3

FGFR2 (fibroblast growth factor
receptor 2)

10q25.3-q26

Hypertriglyceridaemia, amyloid nephropathy
Wagner syndrome, spondyloepiphyseal dysplasia,
Stickler syndrome, Kniest dysplasia
Classic Marfan syndrome, neonatal Marfan syndrome,
ectopia lentis
Osteogenesis imperfecta types I-IV, Ehlers-Danlos syndrome
type VII[F7, N5][B13, K14, W8][D9][B2, S10]

Achondroplasia, thanatophoric dysplasia types I and II,
hypochondroplasia[M5]

Pfeiffer syndrome, Apert syndrome, Jackson-Weiss
syndrome, Crouzon syndrome[M5]

RET protooncogene

10q11.2

Multiple endocrine neoplasia MEN2A, MEN2B, medullary
thyroid carcinoma, Hirschprung disease

IDUA (α-L-iduronidase)

4p16.3

Hurler syndrome, Scheie syndrome[D1, E1, H2,
M3, M4, R2][S9]

LIPA (Lipase A, lysosomal acidcholesteryl esterase)

10q23.2-q23.3

Wolman disease, cholesteryl ester storage disease[A6, K15]

DMD (Dystrophin)

Xp21.3-p21.2

Duchenne muscular dystrophy, Becker muscular dystrophy[W9]

AR (Androgen receptor)

Xq11.2-q12

Androgen insensitivity syndrome; Kennedy spinal and bulbar
muscular atrophy; male breast cancer[B10, B14,
W10]

UNSCEAR 2001 REPORT

96

Table 5
Examples of similar clinical diseases resulting from mutations in different genes[M1]
Disease

Gene

Chromosomal
location

Ref.

Alport syndrome, X-linked
Alport syndrome, autosomal recessive
Alport syndrome, autosomal recessive

COL4A5
COL4A3
COL4A4

Xq22-q23
2q36-q37
2q35-q37[B15][L9, M14][L9, M14]

Familial Alzheimer disease, early onset, autosomal dominant
Familial Alzheimer disease, early onset, autosomal dominant
Familial Alzheimer disease, early onset, autosomal dominant
Familial Alzheimer disease, late onset, autosomal dominant

APP
E51
S182/AD3
ApoE/AD2

21q21.2
1
14q24.3
19q13/2[G4][R10, S26]
[R10, S26]
[M59, S26]

Diabetes insipidus, nephrogenic, autosomal dominantDiabetes insipidus, nephrogenic, autosomal recessive
Diabetes insipidus, neurohyphyseal, autosomal dominant

AQP2
AVPR2
AVP

12q12-q13
Xq28
20p13

[D10]
[R11, V6]
[B16, I12, I3]

Diabetes mellitus, MODY, type II, autosomal dominantDiabetes mellitus, MODY, type I, autosomal dominant

GCK
MODY1

7p
20q12-q13.1[S27, V7]
[S27, V7]

Osteogenesis imperfecta, types I-IV, autosomal dominantOsteogenesis imperfecta, types I, autosomal dominant

COL1A1COL1A217q21.3-q22
7q21.3-q22.1

[B2]
[B2]

Ehlers-Danlos syndrome, type VII, autosomal dominant
Ehlers-Danlos syndrome, type VII, autosomal dominant

COL1A1COL1A217q21.3-q22
7q21.3-q22.1

[S10]
[S10]

Hirschprung disease, autosomal dominant
Hirschprung disease, autosomal dominant

RET
EDNRB

10q11.2
13q22

[E1]
[P9]

Epidermolysis bullosa, Dowling-Meara type
Epidermolysis bullosa, Dowling-Meara type

KRT5
KRT14

12q
17q12-q21

[S28]
[S28]

Usher syndrome

USH1A
USH1B
USHIC

14q32.1-q32.3
11q13.5
11p15.1-p14

[C14]
[C14]
[C14]

Retinitis pigmentosa, autosomal dominant
Retinitis pigmentosa, X-linked
Retinitis pigmentosa, X-linked
Retinitis pigmentosa, X-linked
Retinitis pigmentosa, autosomal dominant
Retinitis pigmentosa, autosomal dominant
Retinitis pigmentosa, autosomal dominant
Retinitis pigmentosa, autosomal recessive
Retinitis pigmentosa, autosomal recessive

RP1
RP2
RP3
RP6
RP9
RP10
RP11
RP12
RP14

8p11-q21
Xp11.4-p11.23
Xp21.1
Xp21.3-p21.2
7p
7q
19q13.4
1q31-q32.1
6p21.3-p21.2[C15, M1]
[C15, M1]
[C15, M1]
[C15, M1]
[C15, M1]
[C15, M1]
[C15, M1]
[C15, M1]
[C15, M1]

ANNEX: HEREDITARY EFFECTS OF RADIATION

97

Table 6
Skeletal disorder phenotypes associated with mutations in the fibroblast growth factor receptor (FGFR) gene
[M5]
Phenotype/gene

Hypochondroplasia

Achondroplasia

Thanatophoricdwarfism

Pfeiffer
syndrome

Apert
syndrome

JacksonWeiss
syndrome

Crouzonsyndrome

Main clinical features
Short limb dwarfism

+

+

+

–

–

–

–

Cloverleaf skull

–

–

+

+

–

–

–

Underdeveloped midface

–

+

+

+

+

+

+

Craniosynotosis

–

–

–

+

+

+

+

Foot anomalies

–

–

–

+

+

+

–

Hand anomalies

–

–

–

+

+

–

–

S252W (25)
P253R (15)A344G

C342Y (3)A344A (3)
Y340H (2)
S354C
S347C
Y328C
C342R
C342S

Mutations identified a
FGFR1

P252R (7)FGFR2C342R (8)exB acc.ss b
C342Y
T341P
D321A

FGFR3

a

b

N540K (8)G380R (192)
G375D

R248C (22)K650E (16)S371C

Predicted amino acid changes with number of times observed in unrelated individuals in parentheses.
Amino acid designations: P = proline; R = arginine; C = cysteine; Y = tyrosine; T = threonine; D = aspartic acid; A = alanine; N = asparagine;
K = lysine; G = glycine; E = glutamic acid; S = serine; W = tryptophan
Three different point mutations within the acceptor splice site of exon B of FGFR were described in five unrelated patients. A recurring
synonymous change Ala344 to Ala, within the same exon B in individuals with Crouzon syndrome was shown to activate a new donor splice site
within exon B of FGFR.

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98

Table 7
Reported instances of uniparental disomy in humans
[S2]

a
b

Chromosome segment

Hetero-/isodisomy

Clinical disorder*2mat a4 mat
*5 mat
6 pat*7 pat*7 pat

?
i (?)
i
i
h, i
i

[Developmental delay] b
None
None [SMA]
None
Silver-Russell (-like) syndrome
None [chloride diarrhea]

11pter-p15.4 pat
11 pat mosaicism
13 mat*13 pat14 pat14 mat

i
i
i
i
h, i
h, i

Beckwith-Wiedemann syndrome
Beckwith-Wiedemann syndrome
None
None
MCA/MR syndrome
MCA syndrome

15q11.2-q12path, iAngelman syndrome

15q11.2-q12path, iPrader-Willi syndrome

16 mat*20 pat
21 mat21 path, i
i
ii

Growth retardation?
[MCA/MR syndrome] a
None
None

*22 mat

i

None

X pat
X and Y pat*XXXX mat

i
h
h, i

Growth retardation? a
None
Severe 48,XXXX

mat = maternal; pat = paternal; SMA = spinal muscular atrophy; MCA = multiple congenital abnormality; MR = mental retardation.
Mosaicism for trisomy (monosomy) makes clinical evaluation difficult.

ANNEX: HEREDITARY EFFECTS OF RADIATION

99

Table 8Trinucleotide repeat expansions in mendelian diseases[A2, B8, B29, C80, D7, D24, G15, K10, K12, M7, S15, Z1]
Repeat number range
Disease a b

ab

Repeat sequence
NormalPremutation

Disease50!200

>200
>200
36!62
27!121

Fragile X-A (FRAXA)
Fragile X-E (FRAXE)
Spinal and bulbar muscular atrophy (SBMA)
Huntington’s disease (HD)

CGG
GCC
CAG
CAG

5!50
6!25
6!39
10!35

Dentatorubral pallidoluysian atrophy (DRPLA)
Spinocerebellar ataxia 1 (SCA 1)
Spinocerebellar ataxia 3 (SCA 3)/
Machado Joseph disease (MJD)
Spinocerebellar ataxia 2 (SCA 2)
Spinocerebellar ataxia 6 (SCA 6)
Spinocerebellar ataxia 7 (SCA 7)
Myotonic dystrophy (DM)Friedreich’s ataxia
Oculopharyngeal muscular dystrophy (OPMD)
Synpolydactyly (SPD)

CAG
CAG
CAG

7!23
6!39
13!61

49!75
54!75
61!84

CAG
CAG
CAG
CTG
GAA
GCG
GCG

15!24
4!16
7!17
5!37
7!22
6
15

35!59
21!27
38!130
100!4 000
200!1 700
8!13
22!29

30!38

For FRAXA, FRAXE and SCA 1, the repeats are in the 5'-untranslated region of the gene; for SBMA, HD, SCA 3, SCA 7, MJD, DRPLA,
OPMD, SPD and Friedreich’s ataxia, they are in the coding region; for DM and SCA6, they are in the 3'-untranslated region.
Not shown in Table 9 is a form of progression myoclonus epilepsy that is due to an expansion of a dodecamer repeat (12 nucleotide repeat
expansion) located upstream of the 5' transcription start site of the GSTB gene.

Table 9
Summary of baseline frequencies of genetic diseases in humans
Estimates of frequency in 104 persons a
Disease classa

Ref.
Previous estimate [U4]This estimate

Mendelian
Autosomal dominantAutosomal recessive
X-linked

95
25
5

150
75
15

[C67, C68, S105][C67, C68, S105][C67, C68, S105]

Chromosomal

40

40

[U8]

Multifactorial
Congenital abnormalities
Chronic

600
6 500

600
6 500

[C37]
[C35]

Frequencies in live births for Mendelian diseases and congenital abnormalities; population frequency for chronic multifactorial diseases,
frequency in population.

UNSCEAR 2001 REPORT

100

Table 10
Estimates of the frequency of autosomal dominant diseases in humans

DiseaseNumberof genes
known ormappedMIM
number[M2]

Frequency (× 104)
Age at clinical diagnosis / onset
Live births[C67]

Population

Ref.

(years)Nervous and neuromuscular systems
Huntington disease11431005.0

0.4-0.8

3 to late 70s; 6% of cases withchildhood/juvenile onset; others
fourth and sixth decade[H7, M49]

Neurofibromatosis 1

1162200

4.0

3.5

First decade[L53, R46]

Neurofibromatosis 2

11010000.3 a-

Severe type: 20 years;
milder type: third decade[E23]

Tuberous sclerosis

21910921911001.0

0.3-0.6

Childhood and young adults[H21, O2]

Primary basilar impression

0109500

3.0-

Young adults[C67]

Cerebellar ataxias

7109150164400164500183086
1830906002236002240.5

0.5

Young adults[H22, I6]

Dentatorubral pallidoluysian
atrophy1125370-0.04-0.7

First to sixth decade;mean: 32 years[I7, O3]Myotonic dystrophy1160900

2.0

1.3

Severe congenital form: at birth;classical form: early adult life;
mild form: late adult life

[H10, W6]

Peroneal muscular atrophy(Charcot-Marie-Tooth disease)3118200118210118220

2.0

4.0

Second decade[P1, S89]

Spastic paraplegia

3

1826001826016003630.5

0.7

Early childhood to adult[P34, R47]

Facioscapulohumeral muscular
dystrophy

1158900-0.4-0.5

Variable: young adult to late adult
life

[L49]

Skeletal system
Diaphyseal aclasis (multiple
exostoses)

3

1337001337016002095.0

0.1-0.2

Childhood[H23, L49,
S90, S91,
W30]

Thanatophoric dwarfism

1

1349340.8
0.2-0.5 a-Birth (neonatal lethal)[A18, M41,
O4, S95]

Achrondroplasia

11349340.2
0.1-1.5 a

-

Birth

[A18, M41,
S95]

Osteogenesis imperfecta

21201501201600.4
1-2.2 a-Birth[A18, B2,
O4]

Ehlers-Danlos syndrome

31201501201601201800.1

2.0Childhood[S10]

Osteopetrosis tarda

1

1666000.1

0.5Childhood[B70, B66,
V2, W30]

Treacher Collins syndrome11545000.2 a-Childhood[D33]

ANNEX: HEREDITARY EFFECTS OF RADIATION

Numberof genes
known ormappedMIM
numberCraniosynostosis (Pfeiffer,
Apert, Crouzon and JacksonWeiss syndromes)

5

Holoprosencephaly

Van der Woude syndrome(Cleft lip ± palate with mucous
pits of lip)

Disease101

Frequency (× 104)
Age at clinical diagnosis / onset

Ref.

Live births[C67]

Population

101200101400101600123101123500

4.0 a

-

Birth

[C75, W31,
W32]

3142946157170600725

1.7 a

-

Birth

[C76]

1

173900

0.1
0.3 a

-

Birth

[B63, R48]

Most cases in late middle age[D34, H24]

[M2]

(years)Kidneys
Autosomal dominant
polycystic kidney b21739001739108.0

10.0

Von Hippel Lindau syndrome c11933000.3 a-Second to third decade

[M29]

-

Multiple polyps in colon by age 20
and progression to cancer by age 50
in 90% of cases

[B61]

[B56]

Intestines
Familial adenomatous
polyposis coli

1175100

1.0

Blood/circulatory system
Hypercholesterolemia (FH)

1

14389020.0-

50% of heterozygous males havesome manifestation of coronary heartdisease by age 50; in females thisoccurs 10-15 years later

Hypercholesterolemia due tofamilial defective apoB-100

1107730

10-15 a-Roughly similar to FH

Congenital spherocytosis

1

1829002.0-Childhood[C67]

Antithrombin III deficiency

1107300-2-5Childhood[A19, P35,
R49]

Familial hypertrophic
cardiomyopathy

7160760160781191010191044191045600858600958-2.0

Young adults[W33]

Williams syndrome1130160

1.0 a-Childhood[B53]

Velecardial syndrome(DiGeorge syndrome)

1 (?)

1924302.5-Childhood[C77]

Hereditary haemorrhagictelangiectasia

2

187300600376-

1.0Childhood[P36][H51, I11,
M30, M31,
T19]

Ear and eye
Dominant forms of earlychildhood pre-lingual deafness

36013176015436018421.0-Childhood[P37, V12]

Dominant form of adult-onset
deafness

10121011124900600101600652600965-2.5

Adults[P37, V12]

UNSCEAR 2001 REPORT

102

DiseaseNumberof genes
known ormappedDominant form of adult-onset
deafness(continued)

MIM
number[M2]

Frequency (× 104)
Age at clinical diagnosis / onset
Live births[C67]

Population

Ref.

(years)600994601316601369601412601848

Dominant forms of blindness(for retinitis pigmentosa)

9180100180103180104180105180380600132604414601850?

1.0-

Young adults[B54, D16,
X1]

Retinoblastoma

1

1802000.3
0.4-0.7 a-Childhood[B71, V8,
Y3]

Teeth
Dentinogenesis imperfecta

21254901.0

1.3-1.6

Childhood[W13]

Amelogenesis imperfecta

11045000.2

0.5Childhood

[W11]

-

About 30 years[C21, E6,
F14, N6,
S93]

Breast and ovary
Early onset familial breast andovarian cancers

211370510.0 aMetabolism
Acute intermittent porphyria

11760000.1>0.5
10.0 dAfter puberty[A20, W34]

Variegate porphyria

1

1762000.1-

First decade[C67]

Neonatal for a small subset; theremainder first and second decade[D9]

OthersMarfan syndrome (skeleton,
cardiovascular, ocular)

1

1547000.4

2.0

Waardenburg syndromes(auditory, pigmentation)

2

193500193510-0.1-0.2

Childhood[F18, R50]

Hirschprung disease (nervous,
gastrointestinal)

3131244142623164761

2.0 a-Childhood[I8, P38]

Malignant hyperthermia
susceptibility (skeletal muscle
homeostasis)5154275154276180901600467601888-1.0Childhood[H25, R51]

Li-Fraumeni syndrome11911700.2 a-Invasive cancers by age 30
in 50% of cases

Total frequency[(104) live births (38 entries)]
Total adjusted frequency(104 live births)

a
b
c
d

Additional or new estimate included.
Also affects liver and cerebrovascular systems.
Also affects nervous system, eye, and pancreas.
Northern Sweden.

~92-96150[M24]

ANNEX: HEREDITARY EFFECTS OF RADIATION

103

Table 11
Estimates of the frequencies of autosomal recessive diseases in humans
Unless otherwise stated, most of these diseases have early onset

DiseaseNumberof genes
known ormappedMIM
number[M2]

Birthfrequency(× 104)[C67]

Comments

Ref.

Metabolism
Cystic fibrosis

1

219700

5.0

Varies from ~1.3 10-4 in Sweden to ~6.0 10-4 inFaroe Islands; very rare in Orientals and African
blacks[S80, T1]

Phenylketonuria, classical1

2616001.0Frequency in United States blacks one third ofthat in whites; rare in Ashkenazi Jews

[B30, C78,
H34]

Cystinuria

12201000.6

High frequency in Israeli Jews of Libyan origin(4 10-4)[S81]

Tay-Sachs disease12728000.4

High frequencies in Ashkenazi Jews (1.7 10-4 to
2.6 10-4) and non-Jewish French Canadians fromsouth eastern Quebec[A21, G22]

Mucopolysaccharidosis type IIIB

1

2529200.4

Estimates vary from 0.5 10-4 in Germany to
0.2 10-4 in Australia to 0.04 10-4 in Northern
Ireland[W35]

Mucopolysaccharidosis type I(Hurler syndrome)1252800<0.2

Rare in Ashkenazi Jews

[L16]

Metachromatic leukodystrophy

12501000.2[G12, G13]

Galactokinase deficiency

12302000.1[M2]

Galactosaemia

1

2304000.1[M2]

Homocystinuria

32362002362502774000.1[M32]

Methylmalonic aciduria

12510000.3 a[C79, L31]

Krabbe disease1

2452000.1a

Hereditary fructose intolerance

12296000.1a

Haemochromatosis

1

23520030.0 aHigher frequency in Druze and Moslem Arab
villages in Israel

[W2]

[T8]
Range: 20-50 10-4; mid-adulthood[C64, E19,
F15, L51]

Neuromuscular
Spinal muscular atrophy

1253300

1.0Friedreich’s ataxia

12293000.2 aLimb girdle muscular atrophies

6114241253601253700600900601411601954

0.1? a[P31]
Population frequency 2-4 10-4 in several
European populations; onset <20 years of age[C55, L38,
P34, R45][M33]

UNSCEAR 2001 REPORT

104

DiseaseNumberof genes
known ormappedMIM
number[M2]

Birthfrequency(× 104)[C67]

Comments

Ref.

The estimate for the non-classical (late onset or
cryptic) form of 201910 is higher: 3.7% in
Ashkenazim, 2% in Hispanics and Yugoslavs,
0.3% in Italians;
202010 and 202110 are less frequent than
201910[S88]

Endocrine glands
Adrenal hyperplasias

3

201910202010202110

1.0 b

Red blood cells
Sickle cell anaemia

1141900

1.0

Sickle-cell trait (heterozygotes) present in about
8% of the African-American population[M34]

601386 (DFNB3) affects 2% of the residents ofan Indonesian village on the north shore of Bali

[F19, P37,
V12]

Hearing
Severe congenital deafness

10276903600316601386600791600792600971600974601071601072
?

~2.0

Sight
Recessive forms of blindness(retinitis pigmentosa loci)>10123825180069180071
1800906001056017181.0

Mental retardation
Non-specific recessive forms ofmental retardation

Total frequency
in 104 live births
Total adjusted frequency
in 104 live birthsabAdditional or new estimate included.
For the severe “classical” form 201910.

-

5.0

50.8
75

[D16]

ANNEX: HEREDITARY EFFECTS OF RADIATION

105

Table 12Estimates of the frequencies of X-linked diseases in humans
Unless otherwise stated, most of these diseases have early onset

DiseaseNumberof genes
known ormappedMIM
number[M2]

Birthfrequency(× 104)[C67]

Comments

Ref.

MuscularDuchenne muscular dystrophy

1310200

4.0

Becker muscular dystrophy

1310200~0.5 aRange: 2.2-3.0 10-4 male births;
DMD has early onset and rapid progressive
muscle wasting resulting in death in the teens;with BMD, onset in early teens and death inmiddle age[B31, E24,
N7, V13]Skin
Ichthyosis (steroid sulfate
deficiency

13081002.0[S75]

Anhidrotic (hypohidrotic
ectodermal dysplasia)

1305100~1.0 a

[K20]

Blood
Haemophilia A
Haemophilia B

3067002.0[A22]306900

a

[M35]

0.2

Mental retardation
Fragile-X syndrome (X-linked
dominant)

Non-specific X-linked mental
retardation (including fragile-X
E and F types)>103095505.0 aRange: 3-10 10-4 male births; about 30% female
heterozygotes mentally retarded and 10-20% ofmales in fragile-X pedigrees predicted to carry thefragile-X mutation are normal[F3]

300031300046300047300062300077309530309540309545309548
?

~1.0

-

[M2]

Eye, earOcular albinism

2300500300600<0.10 a-[W12]

Choroideraemia

13031000.10 aAffected males develop night blindness in theirteens, followed by progressive construction ofvisual fields and complete blindness by middle
age

[V14]

X-linked nystagmus

1

310700

0.10

X-linked deafness

5300030300036300039304500304700

0.10

OthersFabry disease13015000.25 a[E25]

UNSCEAR 2001 REPORT

106

Numberof genes
known ormappedMIM
numberX-linked immune disorders(agammaglobulinaemia, hyperIgm syndrome, severe combined
immunodeficiency)

33003003004003082300.25 a[H11, P8]

Hypophosphataemia (X-linked
dominant)

13078100.05 a[F20]

Batten disease (juvenile neuronallipofuscinosis)

1

3042001.00 aDisease

a

[M2]

Birth
frequency(× 104)[C67]

Total frequency
104 male live births

17.65

In total births

8.8

Total adjusted frequency
in 104 live births

15

Additional or new estimate included.

Comments

Increased prevalence in northern European
populations

Ref.

[Z2]

ANNEX: HEREDITARY EFFECTS OF RADIATION

107

Table 13
Examples of Mendelian diseases with high prevalence and/or enrichment for specific mutations among
Ashkenazi Jews
[M2, M6]

DiseaseMIM
number[M2]

Findings

Ref.

Autosomal dominants
BRCA1- and BRCA2-associatedbreast and ovarian cancers

113705600185

Two ancestral mutations (BRCA1: 185del AG and BRCA2 6174 delT) eachappear in the general population at ~1% frequency; a third mutation, BRCA1
5382 insC, occurs at a population frequency of 0.11%

Idiopathic torsion dystonia

128100Overall heterozygote frequency: 0.1-0.3%[A17, S93,
T11]

[R42]

Autosomal recessives aa

Tay-Sachs disease272800Overall heterozygote frequency 3-4%; a four-base-pair insertion in exon 1 is
the most common mutation, found in about 80% of the carriers tested; in theclassic infantile form, the disease causes lethality by age 2-3 years[K9]

Gaucher disease230800Overall heterozygote frequency 4-6%; two mutations, a G6A transition at
nucleotide 5841 (aspargine to serine) and an insertion of G at nucleotide 84
account for 80% of the mutant alleles; nearly 90% of the homozygotes for the
first of these mutations have a mild clinical course[H9]

Canavan disease

271900Overall heterozygote frequency 1.7-2%; three mutations, an A6C (glutamic
acid 285 alanine), A6C (tyrosine 231 ter), and A6G (IVS-2, -2), account for
98.8% of mutant alleles; homozygotes almost lethal in infancy[K8]

Niemann-Pick disease,types A and B

257200Overall heterozygote frequency 1-2%; three mutations, a T6C (leucine 302
proline), del C in codon 330, and a C6A (arginine 456 leucine) account for
65% of the mutant alleles in patients with type 1 disease; homozygotes lethal
in infancy[L14]

Mucolipidosis

252650Overall heterozygote frequency ~1%; the disease is generally lethal but
milder variants may exist[M34]

Bloom’s syndrome

210900Overall heterozygote frequency ~1%; homozygosity for a six-base-pairdelation and a seven-base-pair insertion at nucleotide 2281 in four ostensibly
unrelated patients of Ashkenazi Jewish ancestry.
Overall, out of 168 cases worldwide, 107 had survived infancy and 93 werealive as of 1996. Of the 61 deceased patients, 50 had died of cancer at a mean
age of 26.4 years.

[E26, G14]

Familial dysautnomia

223900Overall heterozygote frequency ~3%; disease incidence 1 in 3600 live births[B32, M27]

Factor XI deficiency(clotting factor)

264900Overall heterozygote frequency 8.1%; two mutant alleles, one causing
glutamic acid 117 to ter and another causing phenylalanine 283 to leucinechange accounted for 96% of the 86 mutant alleles examined; heterozygotes
have a mild bleeding tendency; survival of patients almost normal[A23]

Pentosuria

260800Overall heterozygote frequency 2.5-3%; survival of patients normal[L4]

A rough guide to the disease frequency for autosomal recessive is as follows: if the disease frequency of a monogenic recessive trait is 1/104,
under the assumption of Hardy-Weinberg equilibrium, the mutant gene frequency is 1/102 (i.e., 0.0001 = 0.01). The heterozygote frequency is 2
× 0.01 × 0.99 = 1.98%.

UNSCEAR 2001 REPORT108

Table 14
Examples of Mendelian diseases that are more common in Finland than elsewhere[D31, P33]
MIM
number[M2]

DiseaseApproximate number of affected described
In Finland

Elsewhere

Autosomal dominants
Familial amyloidoses, Finnish type; also Meretoja syndrome, amyloidosis V

1051201000 a<40

Familial benign erythrocytosis

13310040?

Autosomal recessives
Aspartylglucosaminuria

208400>200

20Cartilage hair dysplasia

250250112

80Congenital nephrotic syndrome (Finnish type)

256300300>200Congenital choroid diarrhoea

21470040>60Cornea plana congenita

21730060>20Diastrophic dysplasia

222600170

200

Gyrate atrophy of chloride and retina, also gyrate atrophy with ornithinedelta amino transferase deficiency

25887070<50

Autoimmune polyadrenopathy-candidasis-ectodermal dystrophy (APECED)

24030063<50

Mulberry dwarfism

25325054<10

Early infantile ceroid lipofuscinosis

256730

107

50

68

<10

Salla disease (also sialuria, Finnish type)
Progressive myoclonal epilepsy

254800170>100

Usher syndrome type III

27690270<100

Choroideraemia

303100150300Retinaschisis

312700300>300

X-linked diseasesaEstimate; some 300 cases actually diagnosed.

ANNEX: HEREDITARY EFFECTS OF RADIATION

109

Table 15
Selected “classic”mutation rates for human genes[V20, V21]
Trait

Population examined

Mutation rate (× 106)

Autosomal dominant mutations
Achondroplasia

Denmark
Northern Ireland
Four cities
Münster, Germany

10
13
14
6-9

Aniridia 1, 2

Denmark
Michigan, United States

2.9-5
2.6

Myotonic dystrophy

Northern Ireland
Switzerland, Germany

8
11

Retinoblastoma

United Kingdom; Michigan, United States
Switzerland, Germany, Hungary
Netherlands
Japan
FranceNew Zealand

Acrocephalosyndactyly (1) (Apert syndrome)

United Kingdom
Münster, Germany

3
4

Osteogenesis imperfecta types I, II, IV

SwedenMünster, Germany

7-13
10

Tuberous sclerosis (epiloia)

Oxford, United Kingdom
Chinese10.5
6

Neurofibromatosis (1)Michigan, United States
Moscow, Russian Federation

100
44-49

Polyposis of intestinesMichigan, United States

13

Marfan syndrome

Northern Ireland, United Kingdom

4.2-5.8

Polycystic disease of the kidneys

Denmark

55-120Diaphyseal aclasis (multiple exostoses)

Münster, Germany

6.3-9.1

6-7
6
12.3
8
5
9.3-10.9

Sex-linked recessive mutations
Haemophilia

Denmark
Switzerland
Münster, Germany

32
22
23

Haemophilia A

Hamburg, Germany
Finland57
23

Haemophilia B

Hamburg, Germany
Finland3
2

Duchenne type muscular dystrophy

Utah, United States
Northumberland and Durham, United Kingdom
Südbaden, Germany
Northern Ireland
Leeds, United Kingdom
Wisconsin, United States
Bern, Switzerland
Fukuoko, Japan
Northeast EnglandWarsaw, Poland
Venice, Italy

95
43
48
60
47
92
73
65
105
46
35-61

Incontinentia pigmenti, Mainz type 2 (Bloch-Sulzberger)

Münster, Germany

6-20

Orofacidigital (OFD) syndrome

Münster, Germany

5

UNSCEAR 2001 REPORT110

Table 16
Distribution of 49 human X-linked traits according to estimated mutation rates[C69, S106]
Estimated mutation rate (10-6)

Frequency of traits with this mutation rate

50
20!49
10!19
5!9
1!4
0.1!0.9
<0.1

1
1
1
2
9
11
24

Total

49

Table 17Comparison of birth prevalences of congenital abnormalities in Hungary and British Columbia
Prevalence per 1,000 live births
ICD code a740-742743
744
745-747748
749
750-751752-753754-756
757
758
759

Type of abnormality

Central nervous system
Eye
Ear, face, and neckHeart and circulatory system
Respiratory system
Cleft lip with/without cleft palate
Other parts of digestive system
Urogenital system
Musculoskeletal system
Integument disorders
Chromosomal anomalies
Other unspecified disorders

Total
550
227-228
Total

a
b
c
d

Inguinal hernia
Congenital tumours

Hungary, 1970-1981[C37]

British Columbia b, 1974-1983
[B36]

2.2
0.3
0.5
7.9
0.3
1.5
2.8
9.1
31.3 c
0.7
1.3
2.0

2.3
1.2
1.8
10.5
1.5
1.7
6.3
9.0
17.4
2.4
1.3
0.9

59.9

52.8 d

11.0
0.1

7.9 d
-

71.0

60. 7dBased on WHO [W20].
Most of these rates are based on total diagnoses and therefore have been adjusted downward by a factor of 0.8; see Baird et al. [B36] for details.
Prevalence would be 5.5 if congenital dislocation of the hip were excluded.
Based on actual cases and not adjusted.

ANNEX: HEREDITARY EFFECTS OF RADIATION

111

Table 18
Classification by aetiology of congenital abnormalities

Category

Birth prevalenceper 1,000

Per cent of total

Per cent of those withgenetic aetiology (I-IV)

British Columbia (ICD 740-754) [B36]
I
II
III
IV

V

1.1
1.8
23.1 b
0.6 c

2.1
3.5
43.7
1.1

4.1
6.9
86.8
2.1

Subtotal genetic

26.6

50.4

100

Non-genetic plus unknown aetiology a26.2 d

49.6

Total

52.8

Mendelian
Chromosomal
Multifactorial
Genetics unknown

Hungary (ICD 740-749) [C60]
I
II
III
IV

V

a
b
c
d
e

Mendelian
Chromosomal
Multifactorial
Genetics unknown

3.6
3.0
45.3
-

5.5
4.6
69.7
-

Subtotal genetic

51.9

79.8

Non-genetic plus unknown aetiology eTeratogens
Maternal factors
Unknown aetiology

2.0
0.4
10.7

Total

65.0

3.1
0.6
16.6

]
]
]

20.2

100

For about 8%, no aetiology of the types I-IV could be assigned.
Also includes conditions other than those listed under ICD 740-759.
Sum for the decade (1952-1963) showing the highest rate; these are judged to have a genetic basis, but the precise mode of inheritance could not be
determined.
Arrived at by subtraction from the total.
For about 8%, no aetiology of the types I-IV could be assigned.

a
b
c
d
e
f

28.7

1 : 1.5

1.8 : 1.0

4 : 1 to5:1
1 : 1.2
1 : 5 to
1:8
2:1

9:1
Only inmales
Only inmales

0.29 b0.10 b0.15 c0.15 c2.8 c1.30 c, d0.13 c1.14 c0.44 c, e

1.35 c,e0.80 fCongenital abnormality

Anencephaly, spina bifida cystica,
and encephalocele

Cleft lip with or without
cleft palate

Congenital hypertrophic pyloric
stenosis

Ventricular septal defectCongenital dislocation of the hip

Structural talipes equinovarus

Congenital inguinal hernia

Simple hypospadias

Undescended testicle(s)

0

0

8.3

3.5

13.6

0

–

0

0

Dizygotic

More common in boys born between February and June; two thirds of cases unilateral with the right side
affected more often than the left side

Lower birth weights and higher proportion of first-borns among index cases

More common in winter births; predominance of right side involvement; higher with advanced maternal age

Half the cases of congenital are bilateral; more frequent among twins; pre-term births slightly more common
and breech presentations three times more frequent; about three times more prevalent among gypsies

Higher birth prevalence in Bretagne (France); also in native American and Lapps; higher birth prevalence inwinter months, breech deliveries, and among first-borns

Accounts for 25%-30% of all cases of congenital cardiovascular malformations

Lower birth prevalence in African people (5-10 per 104), Orientals (1-5 per 104), and still lower in Filipinos(below 1 per 104)

Isolated CL with or without CP has about 1:2 ratio of CL and CL with or without CP; CL three times morecommon on the left side; higher birth frequencies in Japan and lower ones in African people; higher birthprevalence with advanced maternal age

Regional and seasonal variations in birth frequency; significantly less frequent in Oriental and African
peoples and more frequent in Sikhs of Northern India and in Egypt; high stillbirth and infant mortality rates; higher prevalence among first-borns and with more advanced maternal age

Other features

Concordance rates published in the literature are different to some extent, but in common with Hungarian data the rates for monozygotic twins are higher.
Among total (i.e. still and live) births.
Among live births.
Recent figure.
In male births.
Prevalence at one year of age.

15.4

28.7

46.2

50.8

83.3

22.2

–

20.0

Monozygotic

Sex ratio(M : F)

Prevalenceper
100 births

Concordance rates a for twins(%)

Table 19
Epidemiological features of selected isolated abnormalities in Hungary
[C33]

112
UNSCEAR 2001 REPORTANNEX: HEREDITARY EFFECTS OF RADIATION

113

Table 20
Increased prevalence of isolated congenital abnormalities in relatives of index patients[C33]

Congenital abnormality

Anencephaly, spina bifida cystica, and encephalocele
Cleft lip with or without cleft palate
Congenital hypertrophic pyloric stenosis
Ventricular septal defectCongenital dislocation of the hip
Budapest study
Békés county study
Structural talipes equinovarus
Congenital inguinal hernia
Simple hypospadias a
Undescended testicle(s) aaPopulation
prevalence(%)

Prevalence in relatives of index patients (%)
Parents(first degree)Sibs(first degree)

Uncles/aunts(second degree)First cousins(third degree)

1.9
1.4
-

2.1
4.8
6.3
1.7

0.19
0.72
0.25
0.69

0.26
0.33
0.72
0.79

2.3
2.1
2.3
5.7
3.7
4.8

13.8
14.0
5.6
10.1
4.8
6.7

1.37
1.17
0.55
6.03
0.77
0.62

6.13
4.72
1.09
7.62
0.48
1.04

0.29
0.10
0.15
0.15
2.8

0.13
1.14
0.44
1.35

In males only.

Table 21
Influence of sex on the risk to relatives of isolated congenital abnormalities[C33]

Congenital abnormality
Anencephaly, spina bifida cystica and encephalocele
Males
Females
Cleft lip with or without cleft palate
Males
Females
Congenital hypertrophic pyloric stenosis
Males
Females
Ventricular septal defectMales
Females
Congenital dislocation of the hip
Males
Budapest study
Females
Budapest study
Males
Békes county study
FemalesBékés county study
Structural talipes equinovarus
Males
Females
Congenital inguinal hernia
Males
Females

Sex-specificprevalence

Risk to relative (%)
Brother

Sister

0.22
0.36

1.0
2.4

2.3
2.3

0.13
0.08

11.2
1.3

4.5

0.22
0.07

4.2
20.0

5.3
-

0.14
0.16

0.8
2.1

1.8
2.5

1.20
3.90
0.81
5.06

16.0
6.9
9.1
6.7

15.9
19.9
33.3
18.7

0.17
0.08

6.6
6.9

1.7
10.0

1.89
0.25

12.9
5.7

1.8
7.7

UNSCEAR 2001 REPORT114

Table 22
Estimates of heritability of liability in the first-degree relatives of index cases for congenital abnormalities[C23]
Congenital abnormality
Anencephaly-spina bifida
Cleft lip with/without palate
Congenital hypertrophic pyloric stenosis
Ventricular septal defectCongenital dislocation of the hip
Structural talipes equinovarus
Congenital inguinal hernia
Simple hypospadias
Undescended testicles

Estimate of h2
0.52 ± 0.17
0.79 ± 0.10
0.74 ± 0.18
0.57 ± 0.22
0.70 ± 0.07
0.82 ± 0.15
0.53 ± 0.08
0.65 ± 0.18
0.51 ± 0.15

a
b
c
d
e
f
g
h

Total

Graves' disease (toxic diffuse goitre)
Diabetes mellitus (maturity onset; NIDDM)
Diabetes mellitus (juvenile onset; IDDM)
Gout
Schizophrenic psychoses
Affective psychoses: unipolar
Affective psychoses: bipolar
Multiple sclerosis
Epilepsy
Glaucoma (open-angle and primary-angle closure)
Essential hypertension
Acute myocardial infarction, other acuteand sub-acute forms of ischaemic heart disease
Varicose veins of lower extremities
Allergic rhinitis (hay fever)Asthma (extrinsic and intrinsic)
Peptic ulcer (gastric and duodenal)
Idiopathic protocolitis (including ulcerative colitis)
Cholelithiasis
Coeliac disease
Calculus of the kidney (nephrolithiasis)
Atopic dermatitis (eczema)
Psoriasis
Systemic lupus erythematosus
Rheumatoid arthritis
Ankylosing spondylitis
Juvenile osteochondrosis of the spine: Scheuermann disease
Adolescent idiopathic scoliosis

Disease

6 541 (3 740)

1 250 (607)360 (-)
249 (86)
460 (458)
3 (-)
94 (36)
13 (-)
90 (94)60 (94)39 (16)4 (-)
131 (602)
19 (-)
1 100 h (-)
41 (86)65 (70)407 (291) g
20
18 (-)
85 (10)500 (10)100 (10)4 (-)
60 (56)160 (-)
850 (642)
359 (582)

Hungary

e

0.70
0.43
0.70
0.65
0.60
0.63
0.80
0.70
0.50
0.75
0.90
0.58
0.79
0.56
0.88
1:3
1:1
1:1
2:1
1:3
1:3
1:1
2:1
1:1
1:1
1:9
1:2
5:1
1:2
1:1
I
N
B
N
N
I
D
I
N
N
N
N
N
N
N
30 (2070)
25 (550)
35 (170)
45 (3060)35 (2060)35 (2570)
1 (110)45 (3060)
18 (1025)
20 (1060)
34 (1345)
40 (3564)
23 (1835)
12 (818)
13 (1018)600 (2003 560)
400 (3001 000)500 (50900)
500 (150900)
5 (410)100 (40120)
12 (325)
60 (10250)
70 (5080)200 (10400)
4 (27)270 (50500)
18 (523)
900 (4001 500)
33 (1364)
6 367

0.47
0.65
0.30
0.50
0.80
0.60
0.90
0.58
0.50
0.32
0.63
0.65
1:4
1:2
1:1
15 : 1
1:1
1:2
1:1
1:2
1:1
1:1
1:1
3:1

Heritabilityof liability dSex ratio
M:F

Age
distribution c
I
I
N
I
N
I
I
N
D
I
I
I

Age of onset(years) a b
43 (1170)
58 (2670)
11 (125)
25 (1855)
21 (1545)
38 (1570)
30 (2060)
33 (1050)
4 (070)
45 (2070)58 (1070)50 (3070)f100 (25500)
480 (1901 600)
20 (856)
30 (1337)
100 (70200)
430 (402 000)100 (7150)
5 (113)170 (33429)
160 (80220)
600 (2001 000)500 (2001 500)

Other countries

Lifetime prevalence per 104 persons

The mean ages of onset are based on Hungarian data and the age ranges of those reported in the literature.
Value gives mean, with range in parentheses.
I: increases with age; N: normally distributed; B: biomodel; D: decreases with age.
Estimates of narrow heritability of liability, based on Hungarian data.
Values in parentheses are prevalence from a population screening carried out in an administrative unit in Hungary that included 3,707 persons over the age of 14 years and 96% of all inhabitants [U17].
Value is median with range given in parentheses.
Value for prevalence is for both diseases 250.0 and 250.1 together.
Radiographic screening; only about 5% are clinically affected.

454
477
493
531-532
556
574
579.0
592.0
691.8
696.1
710.0
714.0
720.0
732.0
737.3

242.0
250.0
250.1
274
295
296.0-1
296.2-5340345
365.1-2
401
410-411

ICD
code

Table 23
Epidemiological features and heritability estimates for selected common multifactorial diseases[C35]

ANNEX: HEREDITARY EFFECTS OF RADIATION
115

UNSCEAR 2001 REPORT

116

Table 24
Classification of blood pressure for adults aged 18 years or older a[J10]
Blood pressure (mm Hg)
Category
OptimalNormalHigh normal
Hypertension
Stage 1
Stage 2
Stage 3
Stage 4aSystolic

Diastolic<120
120!129
130!139

<80
80!84
85!89

140!159
160!179
180!209$210

90!99
100!109
110!119$130

Based on an average of two or more readings on two or more occasions in individuals not taking antihypertensive medications and not actually
ill. When the average falls in different categories of systolic and diastolic blood pressure, the higher category applies.

Table 25
Selected estimates of correlation coefficients for blood pressure reported in family studies of hypertension[B50]
Correlation coefficient
RelationshipMonozygotic twins
NHLBI twin study, United States
Midwest, United States
Dizygotic twins
NHLBI twin study, United States
Sib-sib
Evans County, Georgia, United States (whites)
Evans County, Georgia, United States (blacks)
Midwest, United States
Framington, Massachusetts, United States
Montreal, Canada
Tecumsek, Minnesota, United States
Parent-child
Evans County, Georgia, United States (whites)
Evans County, Georgia, United States (blacks)
Midwest, United States
Framington, Massachusetts, United States
Montreal, Canada
Tecumsek, Minnesota, United States

Reference
Systolic

Diastolic

0.55
0.72

0.58

[F30]
[W27]

0.25

0.27

[F30]

0.20
0.14
0.23
0.17!0.23
0.28
0.22!0.31

0.17
0.19

[H39]
[H39]
[W27]
[H38]
[B52]
[L39]

0.13
0.26
0.26
0.13!0.14
0.32
0.20!0.24

0.18!0.24
0.29
0.14!0.23
0.14
0.17
0.17!0.21
0.37
0.16!0.19

[H39]
[H39]
[W27]
[H38]
[B52]
[L39]

ANNEX: HEREDITARY EFFECTS OF RADIATION

117

Table 26
Familial aggregation of coronary heart disease
Age

Study design

Sample size

Odds ratio a

P valueRef.

$45 years

Case-control

6 509

Father: 2.5
Mother: 1.9
Brother: 1.37

<0.05
NS
NS

[P7]

Adult

Case-control

1 375 (blacks)

Father: 6.0
Mother: 2.0
Brother: 3.5
Sister: 2.0

<0.01
<0.05
<0.0010.09[R32]#70 years

Case-control

3 207

Father: 1.71
Mother: 1.58
Brother: 1.36
Sister: 1.32

NS
NS
NS
NS

[T24]

Cohort of male twins

Monozygotic: 3 298
Dizygotic: 5 964
Monozygotic: 4 012
Dizygotic: 7 730

8.1 (CI: 2.7!24.5)
3.8 (CI: 1.4!10.5)[M54]

1 420 (blacks)

Parent and offspring:5.30 (CI: 2.51!11.23)

[R23]

Adult

Cohort of female twins$45 yearsaCase-control

Relative risks in relatives of affected individuals compared to controls.

Table 27
Major classes of human plasma lipoproteins and the associated apolipoproteins
[B62]
Class
Chylomicrons
VLDL
IDL
LDL
HDL

a
b

Density (g ml- 1)

Electrophoretic mobility a

Associated apolipoproteins<0.94
0.93!1.006
1.006!1.019
1.0019!1.063
1.063!1.120

OriginPre-βBroad ββαA1, A4, B48 b, C1, C2, C3, E
B100, C1, C2, C3, E
B100, C1, C2, C3, E
B100
A1, A2, C1, C2, C3, D, E

According to the mobility of plasma α and β globulins on agarose gel electrophoresis.
The apo-B48 protein corresponds to the amino-terminal half of the apoB100 protein; both proteins are products of a single apoB gene.

Table 28
ApoE polymorphisms and their effects on total cholesterol levels[M53]

AlleleGene productTypical frequency

Average allelic effecton total cholesterol (mg dl-1)

ε2
ε3
ε4

E2
E3
E40

0.109
0.760
0.131

!14
!0.16
+7

UNSCEAR 2001 REPORT

118

Table 29
Effects of a one-time or a permanent doubling of the mutation rate on gene frequency, disease frequency,
and mutation component for a hypothetical autosomal dominant disease a[C66]
Permanent doubling

One-time doubling

GenerationaMutant genefrequency

Diseasefrequency

Mutationcomponent

Mutant genefrequency

Diseasefrequency

Mutationcomponent

Initial123450.000020
0.000030
0.000035
0.000038
0.000039
0.000039

0.000040
0.000060
0.000070
0.000075
0.000078
0.000079

0.00000.50000.75000.87500.93750.96880.000020
0.000030
0.000025
0.000023
0.000021
0.000021

0.000040
0.000060
0.000060
0.000045
0.000043
0.000041

0.00000.50000.25000.12500.06250.0313New equilibrium

0.000040

0.000080

1.00000.000020

0.000040

0.0000The values used in the computation are the following: mutation rate (m) = 1 10-5; selection coefficient (s) = 0.5; initial mutant gene frequency(p) = m/s = 2 × 10-5; and initial disease frequency (p) = 2p = 4 × 10-5.

Table 30
Minimum number of loci needed to explain a specified prevalence for various mutation rates and selection
coefficients for affected individuals[D17, I2]
Mutation rate (10-5per locus)

Mutation rate (10-6per locus)

Prevalence

0.0001
0.001
0.01
0.1

a

Selectioncoefficient 0.05

Selectioncoefficient 0.20

Selectioncoefficient 0.50

Selectioncoefficient 0.05

Selectioncoefficient 0.20

Selectioncoefficient 0.50

1a
2
25
250

1
10
500
5 000

2
25
250
2 500

2
25
250
2 500

10
100
1 000
10 000

25
250
2 500
25 000For sp/2µ < 1, a value of 1 is used.

Retinoblastoma

Sarcomas, breast cancer

Colorectal cancer

Colorectal cancer

Neurofibromas

Acoustic neuromas,
meningiomas

Wilms’ tumour

Wilms’tumour

Basal-cell skin cancer

Breast cancer

Breast cancer

Renal cancer (clear cell)

Renal cancer (papillary type)

Li-Fraumeni syndrome (LFS)

Familial adenomatous polyposis(FAP)

Hereditary nonpolyposis
colorectal cancer

Neurofibromatosis type 1 (NF1)

Neurofibromatosis type 2 (NF2)

Wilms’ tumour

Beckwith-Wiedman syndrome(BWS)

Nevoid basal-cell carcinoma
syndrome (NBCCS)

Familial breast cancer 1

Familial breast cancer 2

von Hippel-Lindau (VHL)
syndrome

Hereditary papillary renal cancer(HPRC)

Primary tumour

Familial retinoblastoma

Syndrome

Table 31
Summary of selected inherited cancer syndromes[F33]? Other cancers

Pheochromocytomas, retinal angiomas,
hemangioblastomas

Male breast cancer, pancreatic cancer, ? others(e.g., ovarian)Ovarian cancer

Jaw cysts, palmar and plantar pits,
medulloblastomas, ovarial fibromas

Oranomegaly, hemi-hypertrophy hepatoblastoma, adrenocortial cancer

WAGR (Wilms’, aniridia, genitourinary
abnormalities, mental retardation)

Gliomas, ependymomas

Neurofibrosarcoma, AML, brain tumours

Endometrial, ovarian, hepatobiliary and urinary
tract cancer, glioblastoma

Colorectal adenomas, duodenal and gastrictumours, CHRPE jaw osteomas and desmoid
tumours (Gardner syndrome), medulloblastoma(Turcot syndrome)

Brain tumours, leukaemia

Osteosarcoma

Dominant inheritance

Associated cancers or traits

7q31

3p25

13q12

17q21

9q22.3

11p15

11p13

22q12.2

17q11.2

2p16, 3p21
2q32, 7p22

5q21

17p13.1

13q14.3

Chromosome
location

MET

VHL

BRCA2

BRCA1

PTCH

?p57/KIP2? Others
contiguous genedisorder

WT1

NF2

NF1

MSH2, MLH1
PMS1, PMS2

APC

P53 (TP53)

RB1

Clonedgene

Transmembrane receptor for HGF?Regulates transcriptional elongation by RNA
polymerase II

Interacts with Rad51 protein, ? Repair ofdouble-strand breaks

Interacts with Rad51 protein; repair of doublestrand breaks

Transmembrane receptor for hedgehog
signalling molecule

Cell cycle regulator

Transcriptional repressor

Links membrane proteins to cytoskeleton?

GAP for p21 ras proteins; microtubule binding?

DNA mismatch repair

Regulation of β-catenin; microtubule binding

Transcription factor; response to DNA damage
and stress; apoptosis

Cell cycle and transcriptional regulation;
E2F binding

Proposed function of gene product

ANNEX: HEREDITARY EFFECTS OF RADIATION
119

Medullary thyroid cancer

Exostoses (cartilaginous
protuberances on bones)

Breast cancer, thyroid cancer(follicular type)

Prostate cancer

Oesophageal cancer

Lymphoma

Solid tumours

Skin cancer

AML

Multiple endocrine neoplasia
type 2 (MEN2)

Multiple exostoses

Cowden disease

Hereditary prostate cancer(HPC)

Palmoplantar keratoderma

Ataxia-telangiectasia (A-T)

Blooms’s syndrome

Xeroderma pigmentosum

Fanconi’s anaemia

Recessive syndromes

Pancytopenia, skeletal abnormalities

Pigmentation abnormalities
hypogonadism

Immunodeficiency, small stature

Cerebellar ataxia, immunodeficiency, ? breast
cancer in heterozygotes

Leukoplakia

Unknown

Intestinal hamartomous, polyps, skin, lesions

Chrondrosarcoma

Type 2A, pheochromocytoma, parathyroid,
hyperplasia
Type 2B, pheochromocytoma, mucosal,
hamartoma
Familial medullary thyroid cancer

Parathyroid hyperplasia, pituitary adenomas

Pancreatic cancer, dysplastic nevi, atypicalmoles

Associated cancers or traits

9q22.3, 16q24.3? two others

Multiplecomplementationgroups

15q26.1

11q22

17q25

1q25, ? Others

10q23

8q24.1, 11p11-13
19p

10q11.2

11q13

9p21

Chromosome
location

FACC
FACA

XPB. XPD
XPA

BLM

ATM

Unknown

Unknown

PTEN (MMAC1)

EXT1, EXT2,
EXT3

RET

MEN1

p16 (CDKN2)

Clonedgene? DNA repair? DNA repair

DNA repair helicases, nucleotide excision
repair? DNA helicase

DNA repair, ? induction of p53

Unknown

Unknown

Dual-specificity phosphatase with similarity totensinUnknown
Unknown

Transmembrane receptor tyrosine kinase for
GDNF

Unknown

Inhibitor of CDK4 and CDK6 cyclin-dependent
kinases

Proposed function of gene product

E2F: a transcription factor;
CHRPE: congenital hypertrophy of the retinal pigment epithelium;
AML: acute myelogenous leukaemia;
GAP: GTPase-activating protein, a negative regulator of the p21 ras guanine nucleotide-binding proteins;
Contiguous gene disorder; alterations in several distinct genes in a particular chromosomal region account for the phenotype seen in patients with the disorder;
Hedgehog: a secreted factor that regulates cell fate determination via its binding to the PTCH protein;
GDNF: glial derived neurotrophic factor.

Pancreatic islet cell

Multiple endocrine neoplasia
type 1 (MEN1)

Abbreviations:

Melanoma

Primary tumour

Familial melanoma

Syndrome

Table 31 (continued)

120
UNSCEAR 2001 REPORTANNEX: HEREDITARY EFFECTS OF RADIATION

121

Table 32
Breast and ovarian cancer families and patients from various populations tested for inherited mutations in
BRCA1 and BRCA2 genes[S93] a
BRCA1

BRCA2

Population
Number b
with mutations

Number b
screened

Percentage

Number b
with mutations

Number b
screened

Percentage

Families with three or more cases of female breast and/or ovarian cancer
CanadaFinlandFranceGermany
Great Britain
Holland and Belgium
Hungary
IcelandIsraelItaly
Japan
NorwayRussian Federation
Sweden and Denmark
United States

12

30

40

38
9
71
71
7
1
16
21
2
3
15
24
69

160
49
339
517
32
11
34
73
20
25
19
106
179

24
18
21
14
22
9
47
29
10
12
79
23
39

8
8
14

49
100
77

16
8
18

25

290

9

4
7
8

32
11
34

13
64
24

12
24

106
94

11
25

33
10
64

33
90
19

42
14

497
243

8
6

2

103

2

Families with male and female breast cancer
Hungary
IcelandUnited States

0
0
2

6
10
24

0
0
8

2
9
12

Breast and/or ovarian cancer patients not selected for family history
IcelandIsrael
Italy
Japan

a
b

23
4
8

The original references are cited in this paper.
Number of families or patients.

243
49
179

9
8
4

Second cancers in retinoblastoma patients

Breast cancer

Endpoint of study

Genetic form of retinoblastoma
in 241 of 319 patients treated by radiotherapy
in 73 of 95 patients treated by radiotherapy
and chemotherapy
in 3 of 11 patients treated by chemotherapy
in 67 of 457 patients not treated
137 patients treated by radiotherapy
78 patients not treated
Follow-up: 30 years

Retinoblastoma patients receiving various
treatments [D13]

Bilateral retinoblastoma patients with and without
radiotherapy [R18]

Bilateral retinoblastoma patients and patients withother childhood malignancies (Wilms' tumour,neuroblastoma, sarcomas, lymphoma) treatedwith radiotherapy [S30]

1 408 patients, mortality compared withpopulation of United States
Mean follow-up: 17 years

Long-term survivors of retinoblastoma with andwithout radiotherapy [E11]855 women treated between 1961-1990;
mean follow-up 10 years

Hodgkin's disease patients [H33]

Peak incidence of second malignancies in fifth andsixth post-therapy years in retinoblastoma patients.
Latency period >15 years in childhood malignancy
group.

Cumulative incidence rate of second neoplasms: 35.1%
in treated patients
5.8% in untreated patients
In treated patients, 24.3% of neoplasms were within theradiotherapy field and 8.1% outside.

Cumulative incidence rate of all second neoplasms inthose with genetic form of retinoblastoma was 8.5% andof osteosarcoma alone 6.0%. Inherent risk forretinoblastoma survivors for developing osteosarcoma
after 18 years (excluding effects of treatment) was 2.2%.

Significant excess mortality for second cancers,
suggesting cancer predisposition for those with RB1
mutations. Children with bilateral retinoblastoma treatedwith radiotherapy had 3-fold higher mortality than nonirradiated cases, suggesting radiation enhancement ofgenetic susceptibility.

RR: 136 (age <15); 19 (age 15-19, 20-24);
7.3 (age 25-29)

RR 1.6 (at 1 Gy: 1.2) (for those exposed < age 45);
RR 1 (no increase in risk for those exposed > age 45)655 second breast cancer cases
1 189 matched controls
Dose to breast 2.8 Gy average, 7.1 Gy maximum

Patients treated by radiotherapy for cancer incontralateral breast [B34]

Excess risk 5-6

Findings

RR at 1 Gy: 14.6 (for those exposed < age 20);
3 (for those exposed > age 20)

Single or multiple fluoroscopic examinations ofchest or abdomen; dose to breast 1-9 mGy per
exposure

Study conditions

Female survivors of atomic bombings [L28, T26]

Female blood relatives of ataxia-telangiectasia
patients [S57]

Population

Table 33
Summary of studies suggestive of either higher radiation-induced cancer risks in putative cancer-predisposed individuals
or radiation-induced tumour-suppressor or proto-oncogene mutations in tumours
[S32]

122
UNSCEAR 2001 REPORTChildren with thyroid cancers from areas
contaminated by the Chernobyl accident [I14]

Thyroid carcinoma and fibrosarcoma cells [I13]In vitro irradiation with x rays

All sarcomas of the 7 patients were histologicallydifferent from original ones and developed within or at
margin of radiotherapy field 6-20 years after irradiation.
One possible whole gene deletion, one 8-bp deletion inexon 7 and G$T transversion in exon 7. Abnormal orabsent RB protein in another one.
These changes could have been radiation-induced orarisen during tumour progression.

Patients with osteo- and soft-tissue sarcomas
previously treated by radiotherapy for different
cancers [B35]

Ret somatic mutations

About one third of mutations in 52 miners weretransversions at codon 249 (AGG-ATG), which isnormally very rare. None of 6 mutations in 12 nonminers was of this type.

Uranium miners with radon-associated lungcancer [T20]p53 somatic gene mutations

Ret proto-oncogene rearrangements found in 4 of 7 casesof thyroid cancer. One case revealed a p53 loss from apoorly differentiated papillary adenocarcinoma.

Two Ret-rearrangements were found, one specific forthyroid cancer and the other a 150 bp insert; induction athigh dose (50 and 100 Gy). Same two types ofrearrangements found in fibrosarcoma cells.

Several-fold higher risk for all cancers except leukaemia
in those <10 years at time of bombings; excess relativerisk 7.2 in this group for stomach cancer and 1.2 in older
age groups. Suggests susceptible subgroup.

Survivors of atomic bombings [S61]

Unusually large number of basal-cell tumours in and nearradiotherapy field within 5 years, often less than 1 year

Findings

Cancer mortality

Study conditions

Patients with medulloblastoma treated byradiotherapy [S30, S31]

Population

Cancer in patients with nevoid basal-cellcarcinoma syndrome

Endpoint of study

Table 33, continued

ANNEX: HEREDITARY EFFECTS OF RADIATION
123

UNSCEAR 2001 REPORT

124

Table 34
Mouse models for inherited human cancer syndromes
[V19]

Gene

a
b

Development defect in -/- mice

Tumours in +/- mice

Tumours in humans

Good model ? atumours arise in
Mice

Humansp53

Viable (low-frequency exencephaly)

Osteosarcomas
Soft-tissue sarcomas
Lymphoma
Breast/brain cancers

Osteosarcomas
Soft tissue sarcomas
Lymphoma/Leukaemia

Yes

Yes

RB

Lethal (14!16 days gestation)
Erythropoiesis and neurogenesis

Pituitary adenomas

Retinoblastomas
Osteosarcomas

Yes

No

APC

Early lethality (before day 7)

Intestinal carcinomas

Colon carcinomas

Yes

Yes

NF1

Lethal (13!14 days gestation)
Cardiac defects

Myeloid leukaemia
Phoechromocytomas

Myeloid leukaemia
Pheochromocytomas
Neurofibromas

Yes

Yes

NF2

Lethal (6!7 days gestation)

Sarcomas

Schwannomas
Meningiomas
Ependymomas

Yes

No

INK4a

ViableFibrosarcomas b
Lymphomas b

Melanomas
Pancreatic cancer

Yes

No

BRCA1

Early lethality (5!6 days)

No tumours

Breast/ovarian cancer

No

No

BRCA2

Early lethality (7!8 days)

No tumours

Breast cancer

No

No

WT-1

Lethal (13!15 days)
Urogenital defects

No tumours

Kidney cancer

No

No

VHL

Lethal (10!12 days)
Placental blood vessel defects

No tumours

Renal cell carcinomas
Pancreatic cancers

No

No

The +/- mouse represents a good model for the human syndrome if early tumours arise in +/- mice and the tumour types also occur in the humansyndrome.
Tumours arising in null mice.

ANNEX: HEREDITARY EFFECTS OF RADIATION

125

Table 35
Estimates of risk of breast cancer obtained using the dominant model of cancer susceptibility
[C41]

Dose
(Gy)

Penetrance: 0.50
Relativerisk

Attributablefraction

Penetrance: 0.75
α aRelativerisk

Attributablefraction

Penetrance: 1.00
αaRelativerisk

Attributablefraction

αa1.7% of cancer due to mutation
Radiosensitivity of predisposed genotypes (Ri) = 10.0; predisposition strength (Rp) = 10.0
0.5
1.0
2.0

1.00
1.00
1.00

0.00
0.00
0.00

0.83
0.87
0.89

1.00
1.00
1.00

0.00
0.00
0.00

0.83
0.87
0.89

1.00
1.00
1.00

0.00
0.00
0.00

0.83
0.87
0.89

0.01
0.01
0.01

0.82
0.86
0.88

1.01
1.01
1.01

0.01
0.01
0.01

0.82
0.86
0.88

1.01
1.01
0.02

0.01
0.01
0.02

0.82
0.86
0.88

0.05
0.07
0.08

0.82
0.86
0.88

1.08
1.11
1.13

0.08
0.10
0.11

0.82
0.86
0.88

1.11
1.14
1.17

0.10
0.12
0.14

0.82
0.86
0.88

0.01
0.01
0.01

0.98
0.99
0.99

1.01
1.01
1.01

0.01
0.01
0.01

0.98
0.99
0.99

1.01
1.01
1.02

0.01
0.01
0.02

0.98
0.99
0.99

0.05
0.06
0.08

0.98
0.99
0.99

1.08
1.10
1.12

0.07
0.09
0.11

0.98
0.99
0.99

1.10
1.14
1.16

0.09
0.12
0.14

0.98
0.99
0.99

0.34
0.41
0.45

0.98
0.99
0.99

1.77
2.02
2.23

0.44
0.51
0.55

0.98
0.99
0.99

2.03
2.37
2.64

0.51
0.58
0.62

0.98
0.99
0.99

Ri = 10.0; Rp = 100.0
0.5
1.0
2.0

1.01
1.01
1.01

Ri = 10.0; Rp = 1000.0
0.5
1.0
2.0

1.06
1.07
1.08

Ri = 100.0; Rp = 10.0
0.5
1.0
2.0

1.01
1.01
1.01

Ri = 100.0; Rp = 100.0
0.5
1.0
2.0

1.05
1.07
1.08

Ri = 100.0; Rp = 1000.0
0.5
1.0
2.0

1.52
1.68
1.82

7.5% of cancer due to mutation
Ri = 10.0; Rp = 10.0
0.5
1.0
2.0

1.00
1.00
1.00

0.00
0.00
0.00

0.83
0.87
0.89

1.00
1.00
1.01

0.00
0.00
0.01

0.83
0.87
0.89

1.00
1.01
1.01

0.00
0.01
0.01

0.83
0.87
0.89

0.02
0.03
0.04

0.82
0.86
0.88

1.04
1.05
1.06

0.04
0.05
0.05

0.82
0.86
0.88

1.05
1.06
0.07

0.05
0.06
0.07

0.82
0.86
0.88

0.20
0.24
0.27

0.82
0.86
0.88

1.37
1.47
1.55

0.27
0.32
0.36

0.82
0.86
0.88

1.49
1.63
1.74

0.33
0.39
0.42

0.82
0.86
0.88

0.02
0.03
0.03

0.98
0.99
0.99

1.03
1.05
1.05

0.03
0.04
0.05

0.98
0.99
0.99

1.05
1.06
1.07

0.04
0.06
0.07

0.98
0.99
0.99

Ri = 10.0; Rp = 100.0
0.5
1.0
2.0

1.02
1.03
1.04

Ri = 10.0; Rp = 1000.0
0.5
1.0
2.0

1.25
1.31
1.37

Ri = 100.0; Rp = 10.0
0.5
1.0
2.0

1.02
1.03
1.04

UNSCEAR 2001 REPORT

126

Dose
(Gy)

Penetrance: 0.50
Relative
risk

Penetrance: 0.75

Penetrance: 1.00

Attributablefraction

α aRelativerisk

Attributablefraction

αaRelativerisk

Attributablefraction

αa

0.19
0.23
0.27

0.98
0.99
0.99

1.34
1.45
1.54

0.25
0.31
0.35

0.98
0.99
0.99

1.45
1.60
1.72

0.31
0.38
0.42

0.98
0.99
0.99

0.69
0.75
0.78

0.98
0.99
0.99

4.41
5.52
6.41

0.77
0.82
0.84

0.98
0.99
0.99

5.54
7.03
8.22

0.82
0.86
0.88

0.98
0.99
0.99

Ri = 100.0; Rp = 100.0
0.5
1.0
2.0

1.23
1.30
1.36

Ri = 100.0; Rp = 1000.0
0.5
1.0
2.0

3.27
4.01
4.61

38% of cancer due to mutation
Ri = 10.0; Rp = 10.0
0.5
1.0
2.0

1.10
1.12
1.14

0.09
0.11
0.13

0.83
0.87
0.89

1.14
1.18
1.22

0.13
0.16
0.18

0.83
0.87
0.89

1.19
1.25
1.29

0.16
0.20
0.22

0.83
0.87
0.89

0.50
0.56
0.59

0.82
0.86
0.88

2.47
2.87
3.19

0.59
0.65
0.69

0.82
0.86
0.88

2.96
3.49
3.92

0.66
0.71
0.74

0.82
0.86
0.88

0.47
0.54
0.59

0.98
0.99
0.99

2.35
2.79
3.14

0.57
0.64
0.68

0.98
0.99
0.99

2.80
3.38
3.85

0.64
0.70
0.74

0.98
0.99
0.99

0.90
0.92
0.93

0.98
0.99
0.99

14.51
18.92
22.45

0.93
0.95
0.96

0.98
0.99
0.99

18.99
24.87
29.58

0.95
0.96
0.97

0.98
0.99
0.99

Ri = 10.0; Rp = 100.0
0.5
1.0
2.0

1.98
2.25
2.46

Ri = 100.0; Rp = 10.0
0.5
1.0
2.0

1.90
2.19
2.43

Ri = 100.0; Rp = 100.0
0.5
1.0
2.0

a

10.02
12.96
15.32

α is the fraction due to radiosensitivity alone.

ANNEX: HEREDITARY EFFECTS OF RADIATION

127

Table 36
Database for estimating the average spontaneous mutation rate of human autosomal genes associated with
autosomal dominant phenotypes and their selection coefficients[C39, V20]
Estimated value of parameter
Disease phenotypeab

Number of loci

Mutation rate (× 10-6) a

Selection coefficient b

Achondroplasia
Amelogenesis imperfecta
Aniridia
Apert syndrome
Blindness
Cataracts (early onset)
Cleft lip
Deaf mutism
Dentinogenesis imperfecta
Huntington disease
Hypercholesterolaemia
Marfan syndrome
Multiple exotoses
Myotonic dystrophy
Neurofibromatosis
Osteogenesis imperfecta
Osteopetrosis
Otosclerosis
Polyposis of intestine
Polycystic kidney disease
Porphyria
Primary basilar impression
Rare diseases (early onset)
Retinoblastoma
Spherocytosis
Tuberous sclerosis

1
1
2
1
9
30
1
15
2
1
1
1
3
1
2
2
1
1
1
2
2
1
50
1
1
2

11.0
1.0
3.8
3.5
10.0
6.0
1.0
24.0
1.0
5.0
20.0
5.0
7.7
18.0
70.0
10.0
1.0
20.0
10.0
87.5
1.0
10.0
30.0
8.7
22.0
8.0

0.8
0
0.1
0
0.7
0.3
0.2
0.7
0
0.2
0
0.3
0.3
0.3
0.5
0.4
0.2
0
0.2
0.2
0.05
0.2
0.5
0.5
0.2
0.8

Total

135

Average per locus-

2.95 ± 0.64

0.294

Mutation rate estimates apply for phenotypes; for some, the estimates are uncertain (see [C39] for details).
Estimated from reproductive fitness.

UNSCEAR 2001 REPORT

128

Table 37
Database for calculating rates of induced mutations in mice
The data are from experiments involving irradiation of males (stem-cell spermatogonia) and all the rates arenormalized to single acute x-irradiation conditions

Number of loci

Average rate
per locus per Gy(× 105)

Reference

The seven-locus system (recessive visible mutations)(3 and 6 Gy; acute x- or γ- irradiation)

7a

3.03

[C8, L26, P5, P10, R33, R34]

The six-locus system (recessive visible mutations)(6 Gy; acute x-irradiation)

6b

0.78

[L5]

Biochemical loci (recessive, null enzyme)(3 + 3 Gy, 24-h interval; x rays)

12 c

0.70 d[C12, P10]

Biochemical loci (recessive, null enzyme)(3 Gy; 3 + 3 Gy 24-h interval and 6 Gy; x rays)

32 e
32
32

1.64
0.67 d0.24[N8] fBiochemical loci (recessive, null enzyme)(3 + 3 Gy; 24-h interval; x rays)

4g

1.24 d[N8] hDominant visibles (Sl, W, Sp, and T) i (x rays)

4

0.44

See Table 38

System8.74/8 = 1.09 10-5 per locus per Gy

Unweighted average

a
b
c
d
e
f
g
h
i

a: non-agouti; b: brown; c: chinchilla; d: dilute; p: pink-eyed dilution; s: piebald; se: short ear.
a: non-agouti; bp: brachypodism; fz: fuzzy; ln: leaden; pa: pallid; pe: pearl.
Ldh1, Tpi, Gpi1, Pgk, G6pd1, G6pd2, Pk, Gr, Mod1, Pgam, Gapdh, Ldr.
Normalized assuming additivity of the effect of dose fractionation.
Acy1,Car2, G6pd1, Ggc,Es1, Es3, G6pd1, Gpi1, Hba, Hbb, Idh1,Ldh1,Ldh2, Mod1, Mod2, Np1, Pep2, Pep3, Pep7, Pgm1, Pgm2, Pgm3,
Pk3, Trf (the identity of the other 8 loci could not be ascertained).
Unpublished data of S.E. Lewis summarized in [N8].
Hba, Hbb, Es3, Gpi1.
Unpublished data of J. Peters cited in [N8] and communicated to the UNSCEAR Secretariat.
Sl: Steel; W: Dominant spotting; Sp: Splotch; T: Brachyury.

Table 38
Dominant visible mutations recovered in the course of mouse specific locus experiments (spermatogonial
irradiation)
These experiments were carried out during 19641994 at Harwell, England. All rates normalized to single acutex-irradiation conditions.
Expt.
no

1
2
3
4
5
6
7
8
9

x-ray dose6 + 6 Gy (8-week interval)
6 Gy
5 + 5 Gy (4-day interval)
3 + 3 Gy (24 hours interval)
3 + 3 Gy (24 hours interval)
6 Gy
6 Gy
1 + 9 Gy (24 hours interval)
1 + 9 Gy (24 hours interval)

Number of mutations at a

Numberofprogeny

S1

W

Sp

T

3 612
16 7357 168
7 645
15 84910 89719 285
10 31814 980

1
!
1
2
1
1
1
1
!

!
1
!
!
1
!
!
!
!

!
!
!
!
1
!
!
!
!

!
!
!
!
3
!
!
1
3

Total

Mutations
per locus per Gy(× 105)

Ref.

1
1
1
2
6
1
1
1
3

0.58 b
0.25
0.35 b
1.09 b0.35 c0.38
0.22
0.24 b0.50 b

[L6]
[L5]
[C7]
[C8]
[C8]
[C8]
[C8]
[C9]
[C9]

Unweighted average mutation rate/locus/Gy = 3.96/9

a
b
c

0.44

Sl: Steel; W: Dominant spotting; Sp: Splotch; T: Brachyury.
Normalized to single unfractionated irradiation conditions under the assumption of additivity of yields.
Normalized on the basis of observations of the enhancement of specific-locus mutation frequency (in the same experiment) by a factor of 3
(3H1 strain of mice).

ANNEX: HEREDITARY EFFECTS OF RADIATION

129

Table 39
Locus-specific rates for radiation-induced mutations in mice
Estimated from the data in Tables 37 and 38ab

Locus aRate (× 105 per Gy)

S.E. (× 105)

pa
pe
G6pd1
G6pd2
Ldh2
Ldr
Pgk1
Tpi
Hba2
Hbb1
Hbb2
Gapdh
Pk
Mod1
Sp
W
Gpi
a
T
ln
Ldh1
se
Sl
bp
Es3
Hba1
c
Gr
b
fz
p
d
Pgam
s

0
0
0
0
0
0
0
0
0
0
0
0
0
0
0.04
0.15
0.33
0.45
0.45
0.67
0.97
0.97
1.31
1.34
1.67
1.67
1.90
2.19
2.35
2.68
2.93
3.14
3.91
7.59

0
0
0
0
0
0
0
0
0
0
0
0
0
0
0.04
0.12
0.33
0.24
0.18
0.67
0.69
0.33
0.51
0.95
1.67
0.67
0.48
1.40
0.52
1.34
0.56
0.62
1.93
0.89

Average rate (acute x-irradiation)
Chronic irradiation

1.08
0.36

0.30 b0.10 bIn these calculations, two additional loci (Ldh2 in the experiments of Pretsch et al. [P10] and Hba2 in the experiments of Peters (cited in [N8])have been included based on current evidence [L54].
The standard error of the average rate was calculated taking into account variation of the rates between loci as well as sampling variation of theexperimental data for each locus.

UNSCEAR 2001 REPORT

130

Table 40
Approximate decreasing relative rank of genes studied in experimental systems that are responsive torecoverable radiation-induced deletions
[S43]
Rank
1

2

Organism/cells

Genes under study

Mouses+, d+, c+, b+; p+Sl, W, Sp, Ph, T

Human somatic cell

HPRT, TK, HLA-A2

Chinese hamster cells

dhfr

Mouse embryonalcarcinoma cells

aprt

Mouse

a+, se+Chinese hamster cells

aprt

Inferred attributes and location of the genes
Non-essential for survival and flanked (5' and 3' to the gene under study) bygenes (genomic regions) that are also non-essential for survival

Non-essential for survival and flanked by genomic regions of which either the 5'or the 3' region may be essential for survival

3?

Non-essential for survival but flanked by genomic regions both of which may beessential for survival

4?

Only small changes (point mutations or small intragenic deletions) arecompatible with survival but both the 5' and 3' flanking regions may be nonessential for survival

5?

Only small changes are compatible with survival and one of the flanking regions
is essential for survival

6

Mouse

H-genes

Chinese hamster cells

Na+/K+ ATPase

Only small changes are compatible with survival; flanked by genomic regions
both of which may be essential for survival

7?

The known phenotype is due to loss-of-function mutations through dominantnegative effects

8?

The known phenotype is due to specific gain-of-function mutations

9?

The known phenotype is due to non-conventional mechanisms of origin of
disease such as specific expansion of trinucleotide repeats0.10.2

Waardenburg syndrome

0.3
5.0
0.2
0.8
0.2

0.5

0.2

0.5

?

Retinitis pigmentosa 4

Huntington disease

Achondroplasia a

Thanatophoric dwarfism

Treacher Collins syndrome

Spinocerebellar ataxias

Nevoid basal-cell carcinoma

Tuberous sclerosis 1

Best macular dystrophy

Type 2Type 11015

0.1

Variegate porphyria

Familial hypercholesterolaemia due to ApoB-100 defect25

Incidence(× 104)[S105]

Antithrombin III deficiency

Disorder107730193500156845180380143100

APOB
PAX3
MITF
RHO
HD

601309191100153700

PTCH

TSC1
VMD2

11q13

9q32q34

9q22.3

Missense mutations in a relatively small gene (16 kb) located in an extremely gene-richregion (several genes map to the same chromosome band)

Tumour-suppressor gene; very gene-rich region (several genes map to the same
chromosome band)A relatively small (34 kb) tumour-suppressor gene in a gene-rich region; most mutations(small deletions) cause protein truncation; no whole gene deletions; loss of function
through haplo-insufficiency; gene-rich

CAG repeat expansion
CAG repeat expansion; gene-rich region
CAG repeat expansion; gene-rich region
CAG repeat expansion
CAG repeat expansion; gene-rich region

601556601517109150601011164500

SCA1
SCA2
SCA3
SCA6
SCA7

6p23
12q24
14q24.3q31
19q13
3p21.1p12

Missense, nonsense and splice-site mutations and small deletions predicted to result intruncated protein; no large deletions known; gene-rich region

5q32q33.1

154500

TCOF1

Specific gain of function mutations; gene-rich region

CAG repeat expansion; very gene-rich region

Mostly missense; gene-rich region

A small (paired-box) gene with 3 exons; loss of function through haploinsufficiency;
gene-rich region (at least four genes map to the same chromosome band)
Splice site mutations and small deletions; putative gene-rich region

Only two specific point mutations affecting LDL receptor binding have been reported

Missense and frameshifts; gene-rich region (several genes including MPZ map to thesame chromosome band)Specific gain of function mutations; gene-rich region

4p16.3

4p16.3

3q21q24

3p14.1p12.3

2q35

2p24

1q22

Type I deficiency due to missense/nonsense mutations; partial/whole gene deletions;gene-rich region (several genes map to the same chromosome band)

Comments

FGFR3134934600923

PPOX

1q23q25

Group 1: Unlikely to be recovered
107300FGFR3Chromosomal
location

AUTOSOMAL DOMINANT

MIM
numberAT3

Gene

Table 41
Assessment of recoverability of radiation-induced mutations in human genes that underlie autosomal dominant and X-linked diseases[S16]

ANNEX: HEREDITARY EFFECTS OF RADIATION
131

8.0

4.0

0.2

0.4

0.1

Polycystic kidney disease

Charcot-Marie Tooth disease (all forms)

Li-Fraumeni syndrome

Osteogenesis imperfecta types IIV a

Ehlers-Danlos syndrome

20.0

<<1.0

Familial hypercholesterolaemia

Malignant hyperthermia susceptibility

2.0

0.4

Marfan syndrome a

Myotonic dystrophy

2.0

Familial hypertrophic cardiomyopathya0.040.07

0.1

4.0

Incidence(× 104)[S105]

Dentatorubral pallidoluysian atrophy

Crouzon syndrome
Jackson-Weiss syndrome
Boston-type craniosynostosis

Apert syndrome aPfeiffer syndrome

DisorderAcute intermittent porphyria

Craniosynostosis

Table 41 (continued)

176000125370160760191044191045191010160781600958

PBGD
DRPLA
MYH7
TNNI3
TNNT2
TPM1
MYL2
MYBPC3160900143890180901

DMPK?
LDLR

RYR1

120180191170TP53

COL1A1COL1A2
COL3A1601097159440

PMP22
MPZ120150120160601313173910

PKD1
PKD2

COL1A1COL1A2134797FBN1

8p11.2p11.1

136350

19q13.1

19p13.2p13.1

19q13.2q13.1

2q31

17q21.31q22.05
7q22.117p13.105p12

17p11.2
1q22

16p13.3p13.1
4q21q23

15q21.1

14q12
14q13.4
1q32
15q22.1
12q23q24.3
11p11.2

12p13.31

11q23.3

5q34q35

10q26

Chromosomal
location

176943123101

MIM
number

FGFR2
FGFR2
FGFR1
FGFR2
FGFR2
MSX2

Gene

Only missense mutations; gene-rich region (several genes map to the same chromosomeband)

A large gene in which various types of mutations including deletions and duplications ofdifferent sizes have been recorded; very gene-rich region (several genes map to the same
chromosome band region)

CTG repeat expansion; very gene-rich region

Loss of function through dominant negative mechanisms

Null mutations cause OI type I (haplo-insufficiency); other events cause types I-IV OI
through dominant negative mechanisms

A very well-studied, small (20 kb) tumour-suppressor gene with multiple functions;missense and nonsense mutations; no whole gene deletions; the 17p13 is a very gene-richregionSpecific 1.5 Mb duplication; dominant gain-of-function; gene-rich region
Most mutations missense; dominant gain of function; gene-rich region

Both genes located in very gene-rich regions (several genes map to the same band
region)Disease due to gain-of-function mutations

Loss of function through dominant negative mechanisms; all genes located in gene-richregions

CAG repeat expansion; gene-rich region

Mostly missense mutations and small intragenic deletions; gene-rich region (several
genes map to the same chromosome band)Specific gain of function mutations; gene-rich region
Specific gain of function mutations; gene-rich region
Specific gain of function mutations
Specific gain of function mutations; gene-rich region
Specific gain of function mutations; gene-rich region
Mutation (C to A; pro 148 his) presumed to act via a “dominant positive” mechanism

Comments

132
UNSCEAR 2001 REPORT

?
2.0

15.0

0.2

2.0
2.2

BRCA2-associated male and female breast cancers

Hirschsprung disease

BRCA1-associated breast and ovarian cancers

Neurofibromatosis 2 a

Congenital spherocytosis

Multiple exotoses

0.3
0.5
4.0

Retinoblastoma a

Tuberous sclerosis 2

Neurofibromatosis 1 a

0.10.2

1.4

Multiple exotoses

Aniridia a

1.0

Familial adenomatous polyposis coli a

Incidence(× 104)[S105]

0.3

DisorderVon Hippel Lindau syndrome

Table 41 (continued)

MIM
number

Chromosomal
location

164761

RET133700EXT1162200191092TSC2
NF1180200RB1106210182900

PAX6

22q12.2

17q21

10q11.2

13q22

13q12.3

11p13p11
19p

5q21q22

3p26p25

17q11.2

16p13.3

13q14.1q14.2

11p13

8q24.11q24.13

8p11.2

Comments

A 110 kb tumour-suppressor gene; no whole gene deletions; constitutionaltranslocations with breakpoint in the gene known; gene-rich region

A large (100 kb) tumour-suppressor gene rich in AT sequences; and Alu repeat
sequences point mutations and small deletions mutations (most of which cause protein
truncation) known; no whole gene deletions; very gene-rich region

A small (24 kb) gene; missense and nonsense mutations; loss of function through haploinsufficiency; deletions which include the EDNRB locus known; insufficient genomic
context information
One of the proto-oncogenes in which germinal mutations (missense and nonsense) arecompatible with viability; loss of function through haplo-insufficiency (in the case of
absent or truncated protein) and through dominant negative effects in the case of
missense mutations; gene-rich region

A 70 kb tumour-suppressor gene in which most of the mutations are small deletions; richin AT sequences; moderately gene-rich; information on genomic context insufficientA 108 kb long tumour-suppressor gene; not enough information on genomic context
Not much is known of genome size or context

A relatively large tumour-suppressor gene; 5q deletions are known; insufficient genomic
context information

A relatively small (50 kb; 3 exons) tumour-suppressor gene; insufficient genomic context
information

A 350 kb tumour-suppressor gene; variety of mutations including very large (700 kb)
deletions; very gene-rich region

A 45 kb long tumour-suppressor gene; large deletions account for 5% of cases;
deletions involving also the adjacent PKD1 locus known

A 200 kb long tumour-suppressor gene; constitutional deletions known; not muchgenomic context information

A paired box gene located in a subregion of WAGR region which also contains thetumour-suppressor gene, WT1; micro-deletions known; moderately gene-rich region

A 300 kb long tumour-suppressor gene; large multi-locus deletions including EXT1,
LGGR and TRPS1 known; gene- rich region

Deletions of 8p11-p21.1 region known; gene-rich region

Group 3: Potentially recoverable

101000

ANK1

NF2

113705131244

EDNRB

BRCA1

600185133701600209

EXT2
EXT3
BRCA2

175100193300APC

VHL

Group 2: Potential recoverability uncertainGene

ANNEX: HEREDITARY EFFECTS OF RADIATION
133

a
b
c

0.05

~0.1

1.0

Choroideraemia

Haemophilia B

Haemophilia A

X-LINKED b c

Chromosomal
location

309550

FRAXA
Xq22.3

Xq12q13.1

310200300500308100303100306900306700DMD/BMD

OA1

STS
CHM
F9

F8
Xq28

Xq27.1q27.2

Xq21.2

Xp22.32

Xp22.3

Xp21.2

Group 3: Potential recoverable

305100Comments

Large (186 kb) gene; majority of mutations nonsense; deletions from 2 kb to <60 kb andone deletion ~210 kb; extremely gene-richCompared to F8 (see below), the F9 gene is smaller (34 kb); missense, nonsense andsplice site mutations; deletions of different sizes (some ~110-115 kb) known; genomic
region appears less gene-rich than Xq28

Nonsense, frameshift or splice site mutations; deletions which include CHM andcontiguous genomic regions associated with mental retardation and deafness

Most patients have large deletions although point mutations are also known; see also
entry 30500 above

Missense, nonsense and frameshift mutations; patients with microdeletions of Xp23(~10 Mb) have, in addition to ocular albinism, short stature, chondrodysplasia punctata,mental retardation and ichthyosis

Both diseases due to mutations in the very large (2.3 Mb) gene; ~2/3 of mutations aredeletions of one or many exons; some duplications and point mutations; deletions in the
Xp21.2 region can include DMD, CGD, XK and RP6 loci proximally and GKD and AHC
distally

Most cases due to CGG expansions

Missense, splice-site and frameshift mutations; small in-frame deletions; no whole genedeletions; gene-rich region

Group 1: Unlikely to be recovered

MIM
numberED1

Gene

Diseases considered in [S43].
Disease incidences for X-linked diseases given in [S105] are per 104 male births; the figures have been divided by 2 to take into account both sexes.
Assessment based on whether an induced deletion will be compatible with viability in males.

1.0

Steroid sulfatase deficiency (Ichthyosis)

<0.05

2.3

Duchenne/Becker muscular dystrophy

Ocular albinism

2.5

Fragile X syndrome

Incidence(× 104)[S105]

0.5

DisorderAnhidrotic (hypohidrotic) ectodermal dysplasia

Table 41 (continued)

134
UNSCEAR 2001 REPORTANNEX: HEREDITARY EFFECTS OF RADIATION

135

Table 42
Summary of the assessments of potential recoverability of radiation-induced mutations in autosomal andX-linked genes[S16]
Group(s)Number of genes

Unweighted
PRCFa

Incidence (104)

Weighted PRCF b

46.45
55.90
102.35

!
0.157

48.95
60.90
109.85!
0.199

Autosomal dominants
1 (unlikely to be recovered)
2 and 3 (Uncertain and potentially
recoverable)
Subtotal

42
17
59

!
0.29

Autosomal dominants + X-linked
1 (unlikely to be recovered)
2 and 3 (Uncertain and potentially
recoverable)
Total

a
b

43
24
67

!
0.36

Unweighted PRCF, autosomal dominants: 17/59 = 0.29; autosomal dominants + X-linked = 24/67 = 0.36.
Weighted PRCF, autosomal dominants: (55.9 × 17)/(102.35 × 59) = 0.157; autosomal dominants + X-linked = (60.9 × 24)/(109.85 × 67) =0.199.

UNSCEAR 2001 REPORT136

Table 43
Examples of human microdeletion syndromes[S43, S45]

Chromosome localization

Designation

MIM
numberEstimated
size

Ref.

Well-known syndromes often caused by autosomal microdeletions
4p16.35p15.2!p15.3
7q11.23 (including ELN gene)
7q36
8q24.11!q24.13(including EXT1 and TRPSII genes)
11p13 (including WT1 and PAX6 genes)
11q23.3!qter
15q11!q13 (loss of paternal genes)
15q11!q13 (loss of maternal genes)
16p13.3

17p13.3
17p11.2
20p12!p11.23
20p12.11!q11.23

Wolf-Hirschhorn; Pitt-Rogers-Dank
Cri du chat
Williams-Beuren
Holoprosencephaly 3
Langer-Giedion tricho-rhino-phalangeal II

194190123450194050142945150230165 kb
>2 Mb
1.5!2.5 Mb

WAGR aJacobsenPraderWilli
AngelmanRubinstein-Taybi
Deletion of PKD1 and TSC2 genes
α-thalassaemia-mental retardation
Miller-Dieker b
Smith-Magenis
Alagille
Di George, velocardiofacial, Shprintzen

194072147791
176270105830180849!
141750247200182290118450192430~600 kb
1.5!3.1 Mb~3.5 Mb

c

~2 Mb

d
e

~100 kb~120 kb~500 kb
1.5!9 Mbf

>1.5 Mb g

[W16]
[O7]
[L22, N2]
[P30, P31]
[H5]
[H6]
[P23]
[C28]
[K16, M22]
[P24]
[B37]
[L23, W17]
[B53]
[P25, T6]
[L24]
[B53]

Other reported autosomal microdeletion syndromes
1p36
1q32
2p21
3p14
3q22!q23
4q12!q21.1
5q15!31.1
7p21.1
8q12.2!q21.2
9p22
9q22!q23.1
10q23.3!q26.2
11p11.2!p22 (includes EXT2 gene)
13q32
14q22.1!q23.2
18q21.3!q22.2
18q23
19q13
22q13.3

a
b
c
d
e
f
g
h
i

?
Van der Woude
Holoprosencephaly II?
Blepharophimosis?
?
Craniosynostosis (Saethre-Chotzen syndrome)?
119300157170?
110100?
?
123100Duane syndrome?
Gorlin syndrome
?
?
?
?
?
?
Diamond-Blackfan anaemia?

126800?
109400?
?
?
?
?
?
205900?

?
840 kb!4 Mb
<1 Mb
?
?
?
?
3.5 Mb!
11.6 Mb h?
~2!3 Mb
i

?
?
~1 Mb
?
9!26 Mb~36 Mb
~1 Mb
$5 Mb

[S46]
[S47]
[S50]
[S51]
[F35, W18]
[F8]
[C29]
[J14]
[C30]
[P39]
[S58]
[P4]
[B38]
[B39]
[L25]
[S59, S60]
[C31]
[G2]
[W19]

Wilms’ tumour, Aniridia, Genitourinary anomalies and mental Retardation
Now considered to be autosomal dominant [M2].
Not all patients have a deletion; now presumed to be a single gene disorder (HPE3 gene).
Not all patients have a deletion; now presumed to be a single gene disorder (UBE3A gene).
Not all patients have a deletion; now presumed to be a single gene disorder (CBP gene).
Not all patients have a deletion; now presumed to be a single gene disorder (JAG1 gene).
At least 17 genes.
While Saethre-Chotzen syndrome patients have been found to have mutations in the TWIST gene, a significant proportion of these patients havelarge deletions in the 7p21.1 region resulting in haploinsufficiency of genes neighboring the TWIST gene.
Not all patients have a deletion; now known to be due to mutations and deletions in PTCH gene (MIM 601309).

ANNEX: HEREDITARY EFFECTS OF RADIATION

137

Table 44
Radiation-induced congenital abnormalities following irradiation of male mice
Number of
Mouse strain

ICR

Dose (Gy)

0
0.36
1.08
2.16

Live fetuses

Abnormalfetuses

1 967
163
234
496

8
1
3
9

Per centInduced rate
per Gy(× 104)

0.4
0.6
1.3
1.8

56
83
65

Estimated regressionof frequency on dose

Ref.

[N10]

68

Table 45
Estimates of genetic risks from continuing exposure to low-LET, low-dose or chronic radiation

Disease class

Baseline frequency
per million
live births

Risk per Gy per million progeny in theFirst generation

Second generation a~1 300 to 2 500
0

Estimates in the present document(Assumed doubling dose = 1.0 Gy)
Mendelian
Autosomal dominant and X-linked
Autosomal recessive

16 5007 500~750 to 1 500
0Chromosomal

4 000

b

Multifactorial
Chronic multifactorial
Congenital abnormalities

650 000 c
60 000~250 to 1 200~2 000 d~250 to 1 200
2 400 to 3 000 d

Total

738 000~3 000 to 4 700

3 930 to 6 700~0.41 to 0.64

0.53 to 0.91

Total risk per Gy expressed as per cent of baselinebPrevious estimate [U4](Assumed doubling dose = 1.0 Gy)

a

b
c
d

Mendelian
Autosomal dominant and X-linked
Autosomal recessive

10 0002 500~1 500~5~2 800~5Chromosomal

4 000

240

100

Multifactorial
Chronic multifactorial
Congenital abnormalities

650 000
60 000Not estimatedNot estimatedNot estimatedNot estimatedTotal

726 500

Risk to the second generation includes that of the first (under the continuous radiation conditions assumed) except for congenital abnormalities
for which it is assumed that between 20% and 50% of the abnormal progeny in the first post-radiation generation may transmit the damage to thesecond post-radiation generation, the remainder causing lethality.
Assumed to be subsumed in part under the risk of autosomal dominant and X-linked diseases and in part under that of congenital abnormalities.
Frequency in the population.
Estimate obtained using mouse data on developmental abnormalities and not with the doubling dose method; note also that although thedesignation “congenital abnormalities” is used in column 1, the risk estimate is based not only on data on congenital abnormalities ascertainedin utero but also on skeletal abnormalities and cataracts studied at weaning age in the mouse.

UNSCEAR 2001 REPORT138

Table 46
Estimates of genetic risks from one-generation exposure to low-LET, low-dose or chronic radiation

Disease class

Baseline frequency
per million
live births

Risk per Gy per million progeny in theFirst generation

Second generation a~500 to 1 0000

Estimates in the present document(Assumed DD = 1.0 Gy)
Mendelian
Autosomal dominant and X-linked
Autosomal recessive

16 5007 500~750 to 1 500
0Chromosomal

4 000

b

Multifactorial
Chronic multifactorial
Congenital abnormalities

650 000 c
60 000~250 to 1 200~2 000 d~250 to 1 200
400 to 1 000 e

Total

738 000~3 000 to 4 700

1 150 to 3 200~0.41 to 0.64

0.16 to 0.43

Total risk per Gy expressed as per cent of baseline

a
b
c
d
e

b

Risk to second generation is lower than that in the first because of the assumption that radiation exposure occurred in one generation only; therisk will progressively decrease with time (in generations).
Assumed to be subsumed in part under the risk of autosomal dominant and X-linked diseases and in part under that of congenital abnormalities.
Frequency in the population.
Estimate obtained using mouse data on developmental abnormalities and not with the doubling-dose method.
Under the assumption that selection coefficient is 0.2 to 0.5.

ANNEX: HEREDITARY EFFECTS OF RADIATION

139

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