bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of maternal and infant covariates on sibship correlation in birth weight
Authors: Beaty TH , Yang P. , Muñoz A. , Khoury MJ , Rao D. C. 
Published: June 2005

AbstractBirth weight on 12,644 singleton infants from 6,196 sibships born in Maryland between 1980 and 1984 were used to estimate the effects of nine maternal and infant covariates on the sibship correlation in birth weight. Assuming a homogeneous correlation across all families, the estimated intraclass correlation was 0.4664 (± 0.0099). This high sibship correlation makes it possible to predict, with reasonable accuracy, the birth weight of a child given information on previous sibs, as well as covariates on the mother and/or infant pertinent to a given pregnancy. The reduction in variance associated with incorporating information on the nine covariates used here was approximately equal to that obtained by conditioning on a single previous sib. Testing for heterogeneity in correlation among different groups of families showed that a crude measure of parity (first live birth vs. other), time between births, mother's marital status, and maternal age at the birth of the last child significantly influenced the sibship correlation in birth weight.
Estimating genetic parameters of survival distributions: A multifactorial model
Authors: Meyer Joanne M. , Eaves Lindon J. 
Published: June 2005

AbstractFor a number of genetically influenced illnesses, age of onset is correlated between relatives. In some cases, age of onset also serves as an index of an individual's inherited liability to an illness. Typically, survival models for age of onset distributions do not allow for these effects. We have used the gamma distribution as the basis of a model which specifies genetic variability in age of onset. Specifically, we allow the hazard frequency parameter of the gamma distribution to be a monotonic function of an individual's inherited liability to an illness. Simulations under various gamma models indicate that age of onset correlations may be strikingly different from correlations in liability. Maximum likelihood estimation procedures were used to obtain parameter estimates from simulated data sets and to determine whether it is possible to discriminate between gamma processes of different order. The results for 1,000 pairs of twins (500 monozygotic and 500 dizygotic) gave parameter estimates that were fairly accurate but that decreased in precision as the order of the gamma process increased. We discuss the effect this may have on inferences made about age of onset.
Lifestyle and blood pressure levels in male twins in Utah
Authors: Slattery Martha L. , Bishop D. Timothy , French Thomas K. , Hunt Steven C. , Meikle A. Wayne , Williams Roger R. , Rao D. C. 
Published: June 2005

AbstractHealthy male monozygotic (MZ) and dizygotic (DZ) twin pairs (MZ pairs = 77; DZ pairs = 88) were studied to assess the effect of dietary intake, physical activity, physical fitness, body mass index (BMI), sum of the triceps and subscapular skinfold measurements, alcohol and caffeine consumption, and smoking patterns on blood pressure. Data on physical activity, detailed dietary intake, medical history, and demographics were obtained from a questionnaire. A bicycle ergometer was used to estimate level of fitness; other medical information was ascertained from physical examination. After normalizing the study variables, intraclass correlations for BMI and the sum of the triceps and subscapular skinfold measurements were higher in MZ than in DZ twin pairs (BMI: MZ r = 0.76, DZ r = 0.48; skinfolds: MZ r = 0.73, DZ r = 0.28), as were VO2max(MZ r = 0.63, DZ r = 0.25) and post‐bike heart rate (MZ r = 0.69, DZ r = 0.19). Both systolic (SBP) and diastolic blood pressure (DBP) had high heritability estimates (SBP = 0.60, and DBP = 0.66). Using factor analysis, four major lifestyle factors were identified and categorized as: 1) dietary intake; 2) a factor heavily weighted by cigarette smoking, alcohol and caffeine consumption; 3) fatness; 4) physical activity and physical fitness. Adjustment for these factors did not alter heritability estimates for either SBP or DBP.
Twin study of genetic and environmental effects on lipid levels
Authors: O'Connell DL , Heller RF , Roberts DCK , Allen JR , Knapp JC , Steele PL , Silove D. , Vogler G. P. , Rao D. C. 
Published: June 2005

AbstractA study of 106 pairs of monozygotic (MZ) and 94 pairs of dizygotic (DZ) twins tested the hypothesis that part of the previously described genetic influence on blood lipid levels can be ascribed to closer similarities among MZ than among DZ twin pairs in environmental factors that affect lipid levels. Participants were adult twin volunteers (age 17–66; 64 male and 136 female pairs) who were selected from the NH & MRC Twin Registry or were respondents to advertisements. They completed a 4‐day weighed food diary from which mean nutrient intake was derived. Information on lifestyle and demographic variables was obtained by questionnaire and a nonfasting blood sample was taken for measures of total, low‐density lipoprotein (LDL) cholesterol, and high‐density lipoprotein (HDL) cholesterol and the HDL2 and HDL3 subfractions. Height and weight were measured, and body mass index (BMI) was calculated (kg/m2). Estimates of the heritability of sex‐adjusted lipid levels were 0.72 for total cholesterol, 0.79 for HDL cholesterol, 0.69 for HDL2, 0.20 for HDL3, 1.06 for LDL cholesterol, and 0.44 for sex‐adjusted BMI. In all cases except for HDL3, genetic variance was statistically significant. After adjusting for the effects of environmental variables in three different ways, the estimates of heritability were somewhat lower for total cholesterol, HDL2, and BMI, and those for HDL cholesterol (borderline) and LDL cholesterol (definitely) remained statistically significant but were decreased. A genetic influence on HDL3 was not found. Adjusted heritability estimates obtained from one method of analysis were 0.35 for total cholesterol, 0.49 for HDL, 0.04 for HDL2, −0.34 for HDL3, 0.66 for LDL, and 0.32 for BMI. These results suggest that the assumptions made in the classical twin study approach are not appropriate when examining genetic effects on lipid levels or BMI, or indeed on any biological variable that may be more similar in MZ twins than in DZ twins. In these circumstances, more complex models may be needed to differentiate between genetic and environmental influences.
Assessing familial aggregation of congenital cardiovascular malformations in case‐control studies
Authors: Maestri Nancy E. , Beaty Terri H. , Liang Kung‐Yee , Boughman Joann A. , Ferencz Charlotte , Rao D. C. 
Published: June 2005

AbstractRecent data indicate that the familial aggregation of congenital cardiovascular malformations (CCVM) varies with the type of defect in the index case. Using a logistic regression model that allows for dependence among family members, we calculated the risk of any CCVM to case relatives compared with relatives of controls. Data from 3,908 first‐degree relatives of 570 matched cases and controls identified from 1981 through 1985 by the Baltimore‐Washington Infant Study were used in the analyses. Overall risk for any CCVM in case relatives was increased four‐fold over that of control relatives. While relatives of cases with flow lesions (including right and left heart defects, as well as perimembranous ventricular septal defect [VSD]) had a five‐fold increase in risk, the risk to relatives of nonflow lesion cases did not differ significantly from the risk to relatives of controls. Sex, maternal age, miscarriage history in the mother, and birth order had no apparent effect on risk among siblings. However, there was an indication of increased risk in relatives of nonwhite cases with VSD compared to relatives of matched controls. However, with these data it was not possible to distinguish between environmental and genetic sources of this familial aggregation.
Partial linkage map of chromosome 13q in the region of the Wilson disease and retinoblastoma genes
Authors: Haines Jonathan L. , Ozelius Laurie , George‐Hyslop Peter St , Wexler Nancy S. , Gusella James F. , Conneally P. Michael , Vogler G. P. 
Published: June 2005

AbstractGenetic linkage maps are useful tools for defining the location of disease genes. Previously published maps of human chromosome 13 have been incomplete and have had ambiguities of order in the vicinity of the Wilson disease (WND) and retinoblastoma (RBl) genes. We have defined a six‐locus map of this region using a large reference pedigree from Venezuela. Our map provides landmarks which will aid in the localization of WND, in determining the extent of deletions in retinoblastoma, and in the mapping of other marker loci.
The impact of varying diagnostic thresholds on affected sib pair linkage analysis
Authors: Kendler Kenneth S. , Vogler G. P. 
Published: June 2005

AbstractFor Mendelian disorders, it is usually simple to classify individuals as either affected or unaffected. By contrast, for “complex” phenotypes, the diagnostic boundary of the disorder is often uncertain. This paper explores the following question: to most efficiently detect linkage in such a complex phenotype by the affected sib pair method, where should the diagnostic threshold be drawn? The model assumes that the disorder is due to a generalized two‐allele single major locus (SML) where liability in each genotype is normally distributed. Evidence for linkage between the marker and disease loci is highly dependent on the location of the threshold. The relationship between the placement of the threshold and population linkage information (PLI) is Gaussian‐like. At high thresholds, linkage efficiency (LE) (or the amount of linkage information per affected sib pair) is high but PLI is low because the number of affected sib pairs is very small. At low thresholds, the number of affected sib pairs is high, but PLI is low because LE is very low. The model is applied to published SML parameters for schizophrenia, and maximal PLI is achieved at thresholds broader than those for schizophrenia alone.
HLA and insulin‐dependent diabetes: An overview
Authors: Svejgaard Arne , Ryder Lars P. 
Published: June 2005

AbstractThe present knowledge of the HLA system and its biological function is summarized as a basis for the subsequent discussion of the associations between this system and insulin‐dependent diabetes (IDDM) and some mechanisms that may explain them. Although the serologically detectable DR determinants are still the most handy markers, there is now increasing evidence from studies of restriction enzyme fragment length polymorphism (RFLP) in IDDM that DQ determinants may play a primary role in causing susceptibility and/or resistance to this disease. Thus, it is now evident that about 90% of DR4‐positive diabetics carry the DQw8 determinant present in only about 65% of DR4‐positive controls. Most recently, it has been claimed that an aspartic acid in position 57 of the DQBI (DQ‐beta‐1) chain confers resistance to IDDM. Although this may be true, it does not explain the disproportionate decrease of DR2 or the particularly high risk of DR3/4 heterozygotes, which is still good evidence that several HLA genes are involved. Because Class II antigens show the strongest associations, the most plausible hypothesis about the mechanism(s) involves specific presentation of as yet unknown antigenic peptides to T‐helper lymphocytes, which may induce the formation of both anti‐islet cell antibodies and T‐cytotoxic lymphocytes capable of destroying beta cells. However, T‐suppressor lymphocytes also may be involved. If this hypothesis is correct, the most urgent task is to define the antigenic peptides in question, whether they are environmental (e.g., viral) or autologous.
Coxsackie B virus assays in IDDM families: The GAW5 data on antibody prevalence
Authors: Yoon J. W. , Kim K. W. , Kim H. M. , Pak C. Y. , Kim Y. W. , McArthur R. G. 
Published: June 2005

AbstractThere is evidence that infection by Coxsackie viruses can serve as an environmental “trigger” for insulin‐dependent diabetes mellitus (IDDM). This background information is summarized briefly, and the data in the IDDM component of Genetic Analysis Workshop 5 (GAW5) concerning serum antibodies to Coxsackie B viruses are described.
Autoantibodies to pancreatic islet cells and insulin in IDDM families: The GAW5 data
Authors: Maclaren Noel K. , Riley William J. , McCulloch David K. , Palmer Jerry P. 
Published: June 2005

AbstractAntibodies to pancreatic islet cells and insulin were studied in the Genetic Analysis Workshop 5 (GAW5) families, as indicators of an autoimmune component of pathogenesis. The rationale for these studies is summarized briefly, and references to the laboratory methods used are provided.
The insulin gene and susceptibility to IDDM
Authors: Cox Nancy J. , Spielman Richard S. 
Published: June 2005

AbstractThe association between insulin‐dependent diabetes mellitus (IDDM) and an allele of a restriction fragment length polymorphism (RFLP) 5′ to the coding region of the insulin gene has raised the possibility that variation in the vicinity of the insulin gene confers susceptibility to IDDM. To test this hypothesis, the distribution of insulin gene sharing in affected sib pairs (ASPs) from the Genetic Analysis Workshop 5 (GAW5) families has been compared with that expected on the basis of random assortment. There is no deviation from random expectation in insulin gene sharing among 95 ASPs from families fully informative for the insulin gene. This is also true when insulin gene sharing is conditioned on HLA sharing, on the particular HLA DR types in ASPs, or on the parents' insulin allele classes. These results thus provide no evidence that variation at or near the insulin gene confers susceptibility to IDDM. However, we also used computer simulation to investigate how the insulin gene region could contribute susceptibility to IDDM without yielding evidence for distortion in insulin gene sharing in a sample comparable to that of GAW5. We found that various levels of insulin gene involvement in IDDM could generate a population association between the insulin gene RFLP and IDDM comparable to that reported in the literature, without producing significant distortion in insulin gene sharing of ASPs.
Linkage studies of HLA and insulin gene restriction fragment length polymorphisms in families with IDDM
Authors: Donald J. A. , Barendse W. , Cooper D. W. 
Published: June 2005

AbstractLinkage analysis of HLA DR antigen as well as DR and DQ restriction fragment length polymorphism (RFLP) data using the LIPED computer program and various three‐allele disease locus models showed very close linkage to an insulindependent diabetes mellitus (IDDM)‐susceptibility locus. RFLP data alone were equal or superior to conventional HLA antigen typing in the linkage analysis. Insulin gene restriction fragment data were analyzed for evidence of either a susceptibility locus linked to the insulin gene or an effect of alleles at the insulin locus on the HLA‐linked susceptibility gene. No evidence was found of any effect of the insulin gene, and it is suggested that alternative explanations of the reported population associations between the insulin gene and IDDM should be considered.
NIMH collaborative program on the psychobiology of depression: Clinical
Authors: Rice John , Andreasen Nancy C. , Coryell William , Endicott Jean , Fawcett Jan , Hirschfeld Robert M. A. , Keller Martin B. , Klerman Gerald L. , Lavori Philip , Reich Theodore , Scheftner William A. 
Published: June 2005

AbstractAs part of the National Institute of Mental Health Collaborative Program of Depression study, data were collected on 2, 225 first‐degree relatives of 612 probands. A subset consisting of 187 families of bipolar patients was made available to participants of Genetic Analysis Workwhop 5 (GAW5). A description of these data, including sample sizes, diagnoses, and a summary of published analyses, is given.
Linkage analysis with cohort effects: An application to X‐linkage
Authors: Van Eerdewegh Paul 
Published: June 2005

AbstractThe LIPED program has been modified to incorporate cohort effects in a linkage analysis. Very significant positive lod scores are obtained between bipolar affective disorder and both the deutan and protan markers on the X‐chromosome. Lod score methods are shown to be sensitive to the specification of the age onset distributions and the parameters of the model of transmission.
Linkage analysis with inbreeding
Authors: Van Eerdewegh Paul 
Published: June 2005

AbstractFor computational reasons, linkage analysis of highly inbred pedigrees is often performed under the assumption that spouse pairs are genetically unrelated. A formulation of the likelihood of a pedigree which takes into account all of the genealogical information Ω, for an arbitrary relationship between a pair of spouses, is proposed. Lod scores at a recombination fraction of 0 for an inbred three‐member nuclear family are presented.
Utility of the affected sib pair method to detect linkage of a sex‐linked dominant disease with a sex‐linked recessive trait
Authors: Chakraborty Ranajit 
Published: June 2005

AbstractUse of affected sib‐pairs for linkage determination of a sex‐linked dominant disease with a recessive X‐chromosome marker will require extremely large sample sizes, particularly when the marker is marginally polymorphic. In addition, this method should not be used without caution on data collected for a traditional LOD score analysis, without considering the parental mating types involved in the informative families. Nevertheless, ascertainment adjustment and correction for dependence of multiple pairs of affected sib‐pairs in families suggests that this method provides linkage inference concordant with that of the traditional LOD score analysis.
Affective disorder not linked to HLA
Authors: Price R. Arlen 
Published: June 2005

AbstractThese analyses focused on the relationship of affective disorders to HLA. The sample of 86 previously unpublished families from Ontario and 10 unpublished pedigrees from Newfoundland, as well as the original Weitkamp et al. [1981] sample of 20 families, the samples provided by NIMH [Goldin et al., 1982] (18 families), and Egeland et al. [1987] (2 large pedigrees), were examined using sib pair methods as well as standard linkage analysis of the full pedigrees. A variety of genetic models were examined. There was no evidence for linkage from any of the samples based on either analytic approach or for any genetic model. Groups of sibling pairs concordant for affective illness, concordant for being well, or discordant for affective illness did not differ in the proportion of genes identical by descent. No group differed significantly from 50%. From the analysis of full pedigrees, linkage to HLA could be excluded to a distance of approximately 20 to 25 centimorgans. There was no evidence for linkage heterogeneity. These results argue against linkage of affective disorder to HLA.
Nonrandom sampling in genetic epidemiology: An implementation of the Hanis‐Chakraborty method for multifactorial analysis
Authors: Rao D. C. , Wette R. , Chakraborty Ranajit 
Published: June 2005

AbstractThe method of Hanis and Chakraborty: [Statistics in Medicine 6:629–646, 1987] is known to yield unbiased estimates of familial correlations from family data ascertained according to just about any method of nonrandom sampling. For multifactorial analysis of such family data, the method is implemented here so as to provide a unique solution, handle variable sibship sizes, and provide likelihood ratio tests of hypotheses. Simulation results are presented to illustrate the utility of the proposed implementation.
Linkage detection tests under heterogeneity
Authors: Risch Neil , Rao D. C. 
Published: June 2005

AbstractA two‐parameter (admixture) test (Lod2) for the detection of linkage which allows for heterogeneity is described. Lod score values for this test which lead to comparable type 1 error probabilities as the conventional (homogeneous) single‐parameter lod score test (Lod1) are derived. For example, a Lod2 value of 3.70 corresponds to the conventional lod score (Lod1) value of 3.0. In terms of power to detect linkage, the Lod2 test is advantageous only for moderate to large pedigrees (autosomal dominant inheritance with high penetrance) and when the proportion of linked families is low (less than 40%). Otherwise, there appears to be no serious disadvantage in using the conventional Lod1 test when heterogeneity is present.
The distribution of debrisoquine metabolic phenotypes and implications for the suggested association with lung cancer risk
Authors: Caporaso Neil , Pickle Linda Williams , Bale Sherri , Ayesh Riad , Hetzel Martin , Idle Jeffrey , Rao D. C. 
Published: June 2005

AbstractDebrisoquine hydroxylation exhibits wide inter‐individual variation in Caucasian populations. After similar doses of the drug, extensive metabolizers excrete up to several hundred times more of the urinary metabolite 4‐hydroxy‐debrisoquine than do poor metabolizers. The phenotypes have traditionally been defined by the metabolic ratio (MR), or the molar ratio of debrisoquine to its chief metabolite recovered in an aliquot of an eight hour urine sample, after a test dose of the drug. Deficient metabolism is inherited as an autosomal recessive condition.We have reanalyzed previously published data from a study of lung cancer patients and controls using a computerized optimization method to more accurately estimate the parameters describing the three phenotypic distributions. Using these new distributions to categorize controls, we show that Hardy‐Weinberg conditions are now fulfilled. When the newly defined phenotype parameters are employed to assign the phenotypes of cases and controls, a highly significant difference in phenotype distribution between cases and controls is still observed. This result supports the hypothesis that the debrisoquine metabolic phenotype may be associated with lung cancer susceptibility.
Equivalence of the mixed and regressive models for genetic analysis. I. Continuous traits
Authors: Demenais Florence M. , Bonney George E. , Rao D. C. 
Published: June 2005

AbstractThe mixed model of segregation analysis specifies major gene effects and partitions the residual variance into polygenic and environmental components. The model explains familial correlations essentially in terms of genetic causation. The regressive model, on the other hand, is constructed by successively conditioning on ancestral phenotypes and major genes. Familial patterns of dependence are described in terms of correlations without necessarily introducing a particular scheme of causal relationship. These two approaches are compared both theoretically and numerically through computer simulations for the case of continuous traits on nuclear families. The class D regressive model, which is characterized by equal sib—sib correlations, is mathematically and numerically equivalent to the mixed model. The simpler class A regressive model, which is also characterized by equal sib—sib correlations determined in this case by the common parentage, provides good estimates of the mixed model parameters: major gene parameters and residual polygenic heritability, derived from the parent—offspring correlation. However, in the absence of a major gene, the restriction imposed by the class A model on the sibling correlation can affect the conclusions of segregation analysis: False inference of a major gene was observed in two out of ten replicates. Our simulations also indicate that the mixed model allowing for different heritabilities in adults and children leads to correct estimates of the major gene parameters and residual familial correlations (parent—offspring and sib—sib) as specified by the class A model. For all the models studied, major gene effects, when present, are correctly detected and estimated.