bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evidence for a dominant gene mechanism underlying coeliac disease in the West of Ireland
Authors: Hernández Jaime L. , Michalski Joseph P. , McCombs Candace C. , McCarthy Ciaran F. , Stevens Fiona M. , Elston Robert C. , Vogler G. P. , Rao D. C. 
Published: June 2005

AbstractAlthough coeliac disease (CD) is strongly associated with the HLA alleles B8 and DR3, the genetic basis of this illness remains obscure. Recent studies show that at least two unlinked loci are involved. Most studies agree on recessivity at the HLA‐unlinked locus but differ with respect to dominance or recessivity at the HLA‐linked disease susceptibility locus.To address this controversy, we examined the association of CD with HLA in 39 families from the West of Ireland. Previous studies have shown that the prevalence of CD and the frequencies of the HLA antigens associated with it are higher in this population than in most others. Analysis of the data revealed a significant excess of concordant sib‐pairs with two HLA haplotypes in common and an excess of discordant pairs with no haplotype in common. Chi‐square tests confirmed a highly significant association between HLA‐B8 and CD. Both heterozygotes and homozygotes for B8 had a significantly increased risk of CD. The risk for homozygotes was slightly higher than for heterozygotes, although not significantly so. The segregation ratio for disease occurrence among sibs of probands was estimated to be 0.185 when neither parent is affected. We estimated a gene frequency of 0.003 for the disease allele (C) at the HLA‐linked locus and of 0.648 for the disease allele (d) at the HLA‐unlinked locus. Assuming that CCdd homozygotes are always affected and that only carriers of C who are homozygous dd can be affected, the disease was found to be completely penetrant in Ccdd heterozygotes. These results support dominance at the HLA‐linked locus conferring susceptibility to CD. Possible reasons for the discrepancy between the West of Ireland and other populations are discussed.
Genetic epidemiological study of schizophrenia: Two modes of sampling
Authors: Ritsner Michail S. , Karas Sergei I. , Drigalenko Evgenii I. , Gottesman Irving I. , Vogler G. P. 
Published: June 2005

AbstractThe ascertainment of probands according to place of residence in hospitals or in the community has enabled our sampling to be representative of whole subpopulations of patients. Probands from psychiatric hospitals are characterized by biased clinical parameters. Our sampling procedure provides important preliminary results which appear to be contradictory to those produced by conventional sampling methods.
Genetic and nongenetic determinants of blood pressure in a Southern Brazilian sample
Authors: Robinson Wanyce M. , Borges‐Osório Maria Regina , Callegari‐Jacques Sidia M. , Achutti Aloyzio C. , da Silveira Lúcia G. , Klein Carlos H. , Costa Eduardo A. , Rao D. C. , Vogler G. P. 
Published: June 2005

AbstractA probabilistic sample representative of the adult population of Rio Grande do Sul, Brazil, was studied to estimate the genetic and nongenetic determinants of blood pressure. Four thousand five hundred and sixty‐five individuals, 20 to 74 years old, from 2050 households, were examined. The genetic determination of the SBP (systolic blood pressure) and DBP (diastolic blood pressure) was evaluated in 557 families extracted from this sample. The analysis was performed first with no adjustments for other influencing factors, and then adjusting for the effects of the two significant covariates, age and Quetelel's index, identified through a multiple stepwise regression analysis with nine independent variables. Higher heritability estimates were obtained for DBP (raw data: 0.40; residuals: 0.45) than for SBP (raw data: 0.22; residuals: 0.26). The significant correlation coefficients varied from 0.13 (for father–offspring raw data, total sample), to 0.36 (for siblings, adjusted data, untreated sample). Slight differences were observed between the total and pharmacologically untreated samples in relation to correlation and heritability estimates.
Consanguinity and multiple sclerosis in Orkney
Authors: Roberts D. F. , Vogler G. P. 
Published: June 2005

AbstractFor all patients with multiple sclerosis in Orkney who were alive in 1974 or who had died during 1958 to 1974, pedigree data were analysed. The relationship between their parents, expressed by kinship coefficients, was compared with that between parents of matched controls. The closer relationship between parents of patients suggests that it is the genes that are shared by a patient's parents, and that he inherits from both, that influence his susceptibility to multiple sclerosis.
Statistical analysis of outcomes from repeated pregnancies: Effects of HLA sharing on fetal loss rates
Authors: Hauck Walter W. , Ober Carole , Rao D. C. , Vogler G. P. 
Published: June 2005

AbstractAs part of our ongoing studies of genetic markers of reproductive outcome in the Hutterites, we have been analyzing potential risk factors for pregnancy outcomes. In particular, we are interested in the effects of HLA sharing between parents on fetal loss rates. Pregnancy outcome data such as these have two characteristics that create statistical challenges, i.e., repeated observations per couple and between‐couple heterogeneity in risk. We critically examine four approaches based on the logistic model for the analysis of this and similar data: 1) unconditional likelihood analysis with and without fixed cluster effects; 2) conditional likelihood analysis; 3) mixed‐effects analysis with random cluster effects; and 4) the robust generalized estimating equation (GEE) procedure. Of these approaches, the GEE method of Liang and Zeger would be best suited for the analysis of our data when the question of interest concerns a variable that is constant over all pregnancies, such as HLA sharing. If the question concerns a couple's risk associated with a changing variable such as maternal age, the mixed‐effects analysis is the more appropriate.
Inheritance of human plasma dopamine‐β‐hydroxylase thermal stability
Authors: Vuchetich John P. , Dunnette Joel , Lunetta Kathryn L. , Weinshilboum Richard M. , Price R. Arlen , Vogler G. P. 
Published: June 2005

AbstractAlthough the structural gene for human dopamine‐β‐hydroxylase (DBH) has been cloned, the mechanism by which DBH physical properties and activity are regulated is not well understood. Previous reports have suggested that three‐allele or two‐locus models may account for the genetic regulation of these traits in human blood. It is an interesting challenge to determine the extent to which quantitative analyses will complement or guide molecular genetic studies. In this study we analyzed data on the physical property of DBH thermal stability and DBH activity in 230 individuals in 53 families in an attempt to clarify genetic mechanisms for the inheritance of these traits. Commingling and segregation analyses of the thermal stability data provided the first clear evidence of a major gene polymorphism for DBH thermal stability analyzed as a quantitative trait. Major gene transmission was supported within a mixed model (χ = 13.39, P < .004). In keeping with earlier findings, similar analyses of DBH activity provided strong evidence of genetic transmission. However, in our data support for a major gene polymorphism was equivocal (χ = 2.99, P = .22).
Power and validity of methods to identify variability genes
Authors: Elashoff Janet D. , Cantor Rita M. , Shain Sara , Vogler G. P. 
Published: June 2005

AbstractA variability gene model [Magnus et al., Clin Genet 19:67–70, 1981] hypothesizes that environmental influences on the expression of additive genes for a quantitative trait such as cholesterol are under the control of alleles at a separate nonadditive locus. They suggest identifying such genes using an analysis of variance to compare absolute intrapair monozygotic twin trait differences between the genotypes of the postulated variability locus. However, quantitative traits such as cholesterol often have skewed distributions with a long right tail; what are the effects of such nonnormality on the procedure suggested by Magnus et al. [1981]? We show that their method is a special case of the Levene tests, robust tests for variability differences. We introduce a statistical model representing sources of variability in twin pair differences and demonstrate with simulation studies that although the Levene tests have robust Type I error, power is enhanced when nonnormal data are transformed before analysis, and the apparent presence and degree of variability differences are dependent on the scale of analysis. These findings indicate the importance of appropriate transformation of the trait before analysis. Analysis of a well‐characterized twin data set illustrates these conclusions.
Adequacy of single‐locus approximations for linkage analyses of oligogenic traits
Authors: Vieland Veronica J. , Hodge Susan E. , Greenberg David A. , Vogler G. P. 
Published: June 2005

AbstractWhen a disease is controlled by two or more mendelian loci acting epistatically, it can be modeled in a linkage analysis as a single‐locus mendelian disease with reduced penetrance. However, the reliability of such an approximation has not yet been demonstrated. This study evaluates the adequacy of such single‐locus approximations, when the disease under investigation is determined by two loci, one of which is tightly linked to a genetic marker.A wide range of two‐locus models were simulated, and analyzed under both the correct two‐locus model and under a single‐locus approximation to that model. In general, the single‐locus approximations yielded lod scores very close to the correct ones, but estimates of θ tended to be upwardly biased. We conclude that a single‐locus linkage analysis will, in general, provided an excellent approximation to a correct (two‐locus) linkage analysis of epistatic two‐locus diseases. This enables researchers to continue to use single‐locus linkage analyses when two‐locus disease transmission is a possibility, and it validates linkage findings already obtained under single‐locus analysis, even if the disease under in vestigation proves ultimately to be governed by two mendelian loci. We also examine alternative methods for obtaining parameter estimates for the single‐locus approximations, and we discuss both generalizations and limitations of our findings. © 1992 Wiley‐Liss, Inc.
An analytical method for assessing patterns of familial aggregation in case‐control studies
Authors: Zhao L. P. , Le Marchand L. , Chakrawarti Aravinda 
Published: June 2005

AbstractThis paper describes an analytical method that is used to assess patterns of disease aggregation within family based on family history information collected in case control studies. In such a study, cases and controls are thought of as probands whose relatives are identified, and relatives' phenotypes and other covariates such as age, sex, and genealogical relationship with the probands are recorded. By modeling the dependence of relatives' phenotypes on case‐control status and other covariates, this method yields adjusted odds ratios that quantify familial aggregation. The estimated standard errors are obtained for statistical inference since the method acknowledges the potential correlations between relatives' phenotypes by using the estimating equations technique. In population‐based case‐control studies, the estimates and statistical inferences are generalizable to the general population. To illustrate this method, we analyzed a case‐control study of colorectal cancer involving 5,190 relatives of 792 cases and 4,478 relatives of 680 population‐based controls conducted in Hawaii. Although detailed results will be presented elsewhere, the colorectal cancer was found to aggregate within family with an odds ratio of 2.74 (95% confidence interval (CI): 1.78–4.21). Among parents, the odds ratio for familial aggregation was 2.38 (95% CI: 1.25–4.54). The corresponding value for siblings was 3.09 (95% CI: 1.87–5.11). It was also found that the odds ratio increases from about 2.00 for relatives of the probands who were 50 years or older to 7.66 and 12.84 for relatives of the probands who were between 40 and 50 years and under 40 years, respectively, suggesting that the familial aggregation of colorectal cancer decreases as probands' age increases. © 1992 Wiley‐Liss, Inc.
Familial analysis of eosinophilia caused by helminthic parasites
Authors: Moro‐furlani A. M. , Krieger H. , Vogler G. P. 
Published: June 2005

AbstractA highly significant familial aggregation of eosinophil levels (X2/3 = 38.00) was detected in a sample from three Brazilian populations with a high incidence of helminthic parasitism. The data were unable to resolve genetic or common environment causation due to the lack of environmental concomitant variables. Results of path analysis indicate that the familial cause accounts for about 58% of the total variability of eosinophil levels among parasite‐infected individuals. © 1992 Wiley‐Liss, Inc.
Do bilineal pedigrees represent a problem for linkage analysis? basic principles and simulation results for single‐gene diseases with no heterogeneity
Authors: Hodge Susan E. , Mulvihill J. J. 
Published: June 2005

AbstractSome investigators have expressed concern—specially for psychiatric disorders—that bilineal pedigrees should not be included in linkage studies. This study compares the ‘informativeness’ of bilineal and unilineal families for a homogeneous single‐gene disorder. Three approaches were used: (1) simulation studies of three‐generation pedigrees, ( 2 ) calculation of expected lod scores (ELODs) in nuclear families, and ( 3 ) calculation of Fisher's information number I(θ) in nuclear families. The simulation studies in (1) permitted a realistic comparison between bilineal datasets and purely unilineal ones. The calculations in nuclear families in ( 2 ) and (3) then made it possible to analyze the sources of information loss in bilineal families.Overall, in datasets of five three‐generation pedigrees each, the drop in mean maximum lod score was approximately 50% from purely unilineal datasets to extremely bilineal ones. In less‐extreme bilineal datasets, which are closer to most real data than the extremely bilineal ones, the drops in lod score were very small—less than 10% in some, and practically zero in others. The details will vary, depending on size and structure of the pedigree, genetic model, true value of the recombination fraction, and informativeness of the marker. However, these results imply that the information loss due to bilineality is not necessarily very great.The nuclear‐family calculations showed that for phase‐known matings there is relatively little information loss in bilineal families, but for phase‐unknown matings the loss is much greater.In conclusion, for single‐gene disorders with no genetic heterogeneity, whereas bilineal families can be less informative than comparable unilineal families, they are not so much less informative that they should automatically be discarded from linkage datasets. The implications of bilineal pedigrees for linkage studies of heterogeneous disorders are also discussed. © 1992 Wiley‐Liss, Inc.
Epidemiologic analysis of gene‐environment interaction in twins
Authors: Ottman Ruth 
Published: June 2005

AbstractOur aim was to develop a simple method for testing gene‐environment interaction in twin data ascertained through affected twins (probands), with known exposure status of both cotwins. To this end we derived formulae for two epidemiologic measures, as a function of prevalence of an exposure and genotype, and disease risk conditional on exposure and genotype: (1) relative risk of disease in exposed vs. unexposed cotwins, stratified by zygosity and proband exposure status (RRE), and (2) relative risk of disease in MZ vs. DZ cotwins, stratified by exposure status of proband and cotwin (RRZ). Then we investigated the behavior of these two measures under different assumptions about the relations between exposure and genotype in terms of their effect on disease risk. If an exposure has a different effect in the presence vs. absence of the genotype, RRE differs between MZ and DZ cotwins. Similarly, if a genotype has a different effect in exposed vs. unexposed persons, RRZ differs between exposed and unexposed cotwins. However, large differences in RRE between MZ and DZ cotwins, or large differences in RRZ between exposed and unexposed cotwins, do not occur except under very extreme conditions, such as a genotype that increases disease risk in exposed individuals, and has a protective effect in unexposed individuals. These results suggest that power to detect gene‐environment interaction is limited with this approach. Conversely, if large differences in RRE or RRZ are observed, they are likely to reflect strong gene‐environment interaction. © 1994 Wiley‐Liss, Inc.
Censored survival models for genetic epidemiology: A gibbs sampling approach
Authors: Gauderman W. James , Thomas Duncan C. 
Published: June 2005

AbstractMethods are proposed for the analysis of diseases with variable age at onset. The Cox proportional hazards model, widely used for epidemiologic analysis, is modified to include both measured (environmental) covariates and latent (genetic) variables, as well as their interactions. A Monte Carlo technique known as Gibbs sampling is utilized to generate observations from the posterior distributions of all model parameters. A correction to account for single ascertainment of pedigrees is also described. Simulation studies show that parameter estimation is nearly unbiased for a wide variety of models, and that moderate gene‐environment interaction effects can be detected. © 1994 Wiley‐Liss, Inc.
Extended latent class approach to the study of familial/sporadic forms of a disease: Its application to the study of the heterogeneity of schizophrenia
Authors: Melton Beth , Liang Kung‐Yee , Pulver Ann E. 
Published: June 2005

AbstractWhen no method exists for detecting genetic forms of a disorder, epidemiologists classify probands according to the presence or absence of an affected relative (familial or sporadic). Not only is this a surrogate measure but if the risk for the disorder is associated with characteristics such as age and gender, then probands with varied distributions of these characteristics among their relatives are subject to misclassification. A latent class approach is presented which explicitly models the relationship between the affected status of the relatives and the unobservable familial/sporadic status of the proband in order to adjust for these characteristics. Lastly, an approach is introduced to correct for attenuation in measures of association between familial/sporadic status and other variables that could result if probands are misclassified. This approach incorporates the latent class probabilities directly into the regression model without classifying probands. These methods are applied to a study of theheterogeneity of schizophrenia.
Familial risks for Alzheimer disease from a population‐based series
Authors: Hirst C. , Yee I. M. L. , Sadovnick A. D. 
Published: June 2005

AbstractKaplan‐Meier risks estimates are calculated and compared for two consecutive series (N1 = 840, N2 = 819) of first‐degree relatives of Alzheimer disease (AD) patients diagnosed as either “probable” or “autopsy‐confirmed” AD. The consistency of results increases confidence in estimates and suggests consistent case ascertainment over 8 years. Lifetime risk estimates to age 88 for the combined sample (23.4% ± 3.0%) do not approach the 50% risk compatible with an autosomal dominant model of transmission. These results support our previous finding and suggest that an autosomal dominant gene(s) is not responsible for all cases of AD.
Segregation analysis of human red blood cell thiopurine methyltransferase activity
Authors: Vuchetich John P. , Weinshilboum Richard M. , Price R. Arlen 
Published: June 2005

AbstractThiopurine methyltransferase (TPMT) catalyzes thiopurineS‐methylation, an important metabolic pathway for drugs such as 6‐mercaptopurine (6‐MP). Inherited differences in the activity of this enzyme are related to individual differences in the therapeutic efficacy and toxicity of 6‐MP and other thiopurine drugs. Variation of TPMT activity in the red blood cell (RBC) has been found to reflect activity differences in less accessible tissues. Previously reported qualitative analyses of inheritance of RBC TPMT in families suggested that a major gene plays a role in the regulation of activity of this enzyme. In the present study we completed complex segregation analyses of RBC TPMT activity of 213 individuals in 49 families that were randomly ascertained through children in the Rochester, MN, public school system. We found clear evidence of a major gene effect on RBC TPMT activity. Both transformed and untransformed data supported the segregation of a Mendelian major gene with frequency of 0.94 for the allele conferring high enzyme activity. The genotype distributions of individuals who were homozygous for the low activity allele, heterozygous, and homozygous for the high activity allele accounted for approximately 0.3%, 11.2%, and 88.5%, respectively, of the individuals in the sample. This major locus accounted for 66% of the total variance in untransformed RBC TPMT activity. Although there were significant residual family correlations among probable high activity homozygotes, there was insufficient power to detect additional major locus or polygenic inheritance effects on the residual variance. © 1995 Wiley‐Liss, Inc.
Comparison of analysis of variance and maximum likelihood based path analysis of twin data: Partitioning genetic and environmental sources of covariance
Authors: Christian Joe C. , Norton James A. , Sorbel Jeffrey , Williams Christopher J. 
Published: June 2005

AbstractIn order to investigate currently used model fitting strategies for twin data, analysis of variance (ANOVA) and path‐maximum‐likelihood (PATH‐ML) methods of analyzing twin data were compared using simulation studies of 50 monozygotic (MZ) and 50 dizygotic (DZ) twin pairs. Phenotypic covariance was partitioned into additive genetic effects (A), environmental effects common to cotwins (C), and environmental variance unique to individuals (E). ANOVA and PATH‐ML had identical power to detect total covariance. The PATH‐ML AE model was much more powerful than ANOVA comparisons of rMZ and rDZ to detect A. However, to be unbiased, the AE model requires the assumption that C = 0.0. To allow use of the AE model to estimate A, the null hypothesis C = 0.0 is tested by comparing the goodness of fit of the ACE and AE models. Simulation of 50 MZ and 50 DZ pairs revealed that C must be greater than 55% of total variance before the null hypothesis would be rejected (P < 0.05) 80% of the time. Several recent publications were reviewed in which the null hypothesis C = 0.0 was accepted and apparently upwardly biased estimates of A, containing C, were presented with unrealistic P values. It was concluded that use of the AE model to estimate A gives an inflated view of the power of relatively small twin studies. It was recommended that ANOVA or comparison of the ACE and CE PATH‐ML models be used to estimate and test the significance of A as neither requires that C = 0.0. © Wiley‐Liss, Inc.