摘要:

AbstractA model of phenotypic assortative mating was developed for application in segregation analysis. The model assumed a constant spouse correlation across the range of a quantitative trait or the liability to a discrete trait. Four traits were analyzed to evaluate: (1) the feasibility of applying likelihood analysis to pedigree data in order to distinguish between assortative mating and shared environmental effects as the source of spouse correlation; and (2) the impact on segregation analysis of the failure to account for either assortative mating or shared environmental effects, as appropriate. Height ratio (the ratio of sitting to standing height) and eye color comprised the traits for which the observed spouse correlation reflected assortative mating; serum cholesterol and peptic ulcers (with genotypes defined by the ABO blood group) comprised the traits for which the observed spouse correlation reflected shared environmental effects. For all four traits the test statistics agreed with the known cause of spouse correlation; however, significance was not attained for height ratio or serum cholesterol. The ability to distinguish between the causes of spouse correlation in pedigree data presumably depends on trait and sample characteristics which remain to be delineated. Despite significant spouse correlation, its omission from the segregation analysis model did not undermine the inference of major locus inheritance for any of the four traits. However, the lack of an impact for these traits does not preclude an impact for other traits of ignoring the appropriate spouse correlation in segregation analysis. © 1995 Wiley‐Liss, I

ISSN:0741-0395    

DOI:10.1002/gepi.1370120202

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1995

数据来源: WILEY

摘要:

AbstractThe role of genetic and environmental factors in determining the variability in plasma lipoprotein(a) [Lp(a)] levels was investigated in 220 members of 14 families with familial hypercholesterolemia (FH) whose plasma Lp(a) levels were previously reported [Leitersdorf et al. (1991) J Lipid Res 32:1513–1519]. One hundred four subjects harbored a mutant low density lipoprotein (LDL) receptor allele as confirmed by the identification of the specific mutations in addition to the haplo‐type analysis reported before. Four different mutant alleles were identified, each in a defined genetic group—Druze, Christian‐Arabs, Ashkenazi, and Sephardic Jews. Sex‐ and age‐adjusted mean plasma Lp(a) levels were significantly higher in FH family members (34.0 mg/dl) than in non‐FH family members (21.1 mg/dl). Lp(a) levels were further adjusted for lipid levels and apo(a) isoforms. A mixture of two normal distributions fitted the adjusted Lp(a) levels better than did a single normal distribution. Segregation analysis indicated that a major effect of a non‐transmitted environmental factor explained the mixture of distributions in addition to polygenic loci which influenced Lp(a) levels within each distribution. The major environmental factor and the polygenic loci accounted for 45% and 20% of the adjusted Lp(a) variation, respectively. Furthermore, sex, age, lipid levels, apo(a) isoform, the major environmental effect, and the unmeasured polygenes could account for 80% of the unadjusted variation of plasma Lp(a) in these families. © 1995

ISSN:0741-0395    

DOI:10.1002/gepi.1370120203

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1995

数据来源: WILEY

摘要:

AbstractIn genetic analysis it is often of interest to analyze associations between traits of unknown genetic etiology and genetic markers from pedigree data. Statistical methods that assume independence of pedigree members cannot be used because they disregard the statistical dependencies of members in a pedigree. For quantitative traits, a regression model proposed by George and Elston[Genet Epidemiol4:193–201, 1987] uses an asymptotic likelihood ratio test and incorporates a correlation structure that allows for statistical dependence among the pedigree members. The statistical validity of this test is assessed for finite samples by measuring the discrepancy between the empirical and theoretical chi‐square distributions. The variance of the mean of the dependent variable is determined to be related to this discrepancy and can be used to determine whether a pedigree structure is large enough for making valid statistical inferences on the basis of the asymptotic test. A multi‐generational pedigree of 200 or so individuals should in many cases be sufficient for valid results when using the asymptotic likelihood ratio test for the association between markers and continuous traits. © 1995 Wiley‐L

ISSN:0741-0395    

DOI:10.1002/gepi.1370120204

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1995

数据来源: WILEY

摘要:

AbstractAnalysis of genetic linkage between a disease and a marker locus requires specifying a genetic model describing both the inheritance pattern and the gene frequencies of the marker and trait loci. Misspecification of the genetic model is likely for etiologically complex diseases. In previous work we have shown through analytic studies that misspecifying the genetic model for disease inheritance does not lead to excess false‐positive evidence for genetic linkage provided the genetic marker alleles of all pedigree members are known, or can be inferred without bias from the data. Here, under various selection or ascertainment schemes we extend these previous results to situations in which the genetic model for the marker locus may be incorrect. We provide sufficient conditions for the asymptotic unbiased estimation of the recombination fraction under the null hypothesis of no linkage, and also conditions for the limiting distribution of the likelihood ratio test for no linkage to be chi‐squared. Through simulation studies we document some situations under which asymptotic bias can result when the genetic model is misspecified. Among those situations under which an excess of false‐positive evidence for genetic linkage can be generated, the most common is failure to provide accurate estimates of the marker allele frequencies. We show that in most cases false‐positive evidence for genetic linkage is unlikely to result solely from the misspecification of the genetic model for disease or trait inheritance. © 1995 Wiley

ISSN:0741-0395    

DOI:10.1002/gepi.1370120205

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1995

数据来源: WILEY

摘要:

AbstractThe use of multiple markers, rather than a single marker, can increase the likelihood of detecting linkage to a locus underlying a quantitative trait. In this paper, the Haseman‐Elston sibpair method is extended to include information from multiple markers. The result is a linear regression of the squared pair trait difference on the jointly estimated proportions of genes shared identical by descent at the two closest flanking marker loci. The results strengthen the theoretical motivation for the interval mapping technique proposed by Fulker and Cardon [1994:Am J Hum Genet54:1092–1103] and extend the method to include information from multiple markers, account for a trait dominance component, and examine the region just outside that defined by the markers. Simulations show that modest increases in power and substantial decreases in bias of parameter estimates are obtained when identity‐by‐descent probabilities are jointly estimated. The regression relationship is also developed for other types of relative pairs. © 1995 Wiley

ISSN:0741-0395    

DOI:10.1002/gepi.1370120206

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1995

数据来源: WILEY

摘要:

AbstractPolylocus linkage analysis methods are modified two‐point analyses which aim to approach the information gain of multilocus analysis. Terwilliger and Ott [(1992)Am J Hum Genet51:A202, (1993)Genet Epidemiol10:477–482] put forth two such methods. This paper presents asymptotic approximations to the null distribution of the likelihood ratio statistics for these two methods, correcting earlier reports [Terwilliger and Ott (1993)Genet Epidemiol10:477–482; Schaid and Elston (1994)Genet Epidemiol11:1–17]. The performance of the approximations is then assessed for finite samples of fully informative meioses. © 1995 Wiley

ISSN:0741-0395    

DOI:10.1002/gepi.1370120207

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1995

数据来源: WILEY

摘要:

AbstractA general purpose model and a flexible computer program, called SEGPATH, have been developed to assist in the creation and implementation of a variety of genetic epidemiological models. SEGPATH is a computer program which can be used to generate programs to implement linear models for pedigree data, based upon a flexible, model‐specification syntax. SEGPATH models can perform segregation analysis, path analysis, or combined segregation and path analysis using any user‐specified path model and can be structured to analyze any number of multivariate phenotypes, environmental indices, and/or measured covariate fixed effects (including measured genotypes). Population heterogeneity models, repeated‐measures models, longitudinal models, auto‐regressive models, developmental models, and gene‐by‐environment interaction models can all be created under SEGPATH. Pedigree structures can be defined to be arbitrarily complex, and the data analyzed with programs generated by SEGPATH can have any missing value structure, with entire individuals missing, or missing on one or more measurements. Corrections for ascertainment can be done on a vector of phenotypes and/or other measures. Because the model specification syntax is general, SEGPATH can also be used in non‐genetic applications where there is a hierarchical structure, such as longitudinal, repeated‐measures, time series, or nested models. A variety of applications are demonstrated. © 1995

ISSN:0741-0395    

DOI:10.1002/gepi.1370120208

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1995

数据来源: WILEY

ISSN:0741-0395    

DOI:10.1002/gepi.1370120209

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1995

数据来源: WILEY

ISSN:0741-0395    

DOI:10.1002/gepi.1370120210

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1995

数据来源: WILEY

ISSN:0741-0395    

DOI:10.1002/gepi.1370120211

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1995

数据来源: WILEY