Showing papers in "Genetic Epidemiology in 1990"
TL;DR: In this paper, a number of important conceptual issues regarding the genetic etiology of these diseases, as well as the appropriate interpretation of linkage results in studying complex diseases, are discussed.
Abstract: Recent linkage findings for psychiatric disorders, in particular schizophrenia, manic-depression, and Alzheimer disease, have raised a number of important conceptual issues regarding the genetic etiology of these diseases, as well as the appropriate interpretation of linkage results in studying complex diseases. Perspectives on mode of inheritance, genetic heterogeneity, and phenotypic variation are given.
280 citations
TL;DR: Five plausible models are described for relationships between genetic and environmental effects, and an example of a simple mendelian disorder that fits each model is given.
Abstract: This paper illustrates how epidemiologic principles can be used to investigate relationships between genetic susceptibility and other risk factors for disease. Five plausible models are described for relationships between genetic and environmental effects, and an example of a simple mendelian disorder that fits each model is given. Each model leads to a different set of predictions about disease risk in individuals with the genetic susceptibility alone, the risk factor alone, both, or neither. The risk predictions for the different models are described, and research designs for testing them are discussed.
192 citations
TL;DR: A computer‐simulation method is presented for determining and correcting for the effect of maximizing the lod score over disease definitions, penetrance values, and perhaps other model parameters, and it finds that, in this specific case, the P‐value associated with a maximum lod score of 3 is equal to 0.0003.
Abstract: A computer-simulation method is presented for determining and correcting for the effect of maximizing the lod score over disease definitions, penetrance values, and perhaps other model parameters. The method consists of simulating the complete analysis using marker genotypes randomly generated under the assumption of free recombination. It is applicable as a “post-treatment” to linkage analyses of any trait with an uncertain mode of inheritance and/or disease definition. When the method is applied to a linkage analysis of schizophrenia versus chromosome 5 markers, we find that, in this specific case, the P-value associated with a maximum lod score of 3 is equal to 0.0003. We also find that a lod score of 3.0 should be “deflated” by approximately 0.3 to 1 units, and, by tentative extrapolation, the observed lod score of 6.5 should be “deflated” by 0.7 to 1.5 units.
125 citations
TL;DR: The genes investigated in this study were the apolipoprotein (apo) genes: apo B, apo AII, apO E (protein polymorphism), apo AI‐CIII‐AIV gene cluster, and the LDL‐receptor gene.
Abstract: Dietary intervention studies (from a low polyunsaturated/saturated fatty acid ratio P/S diet to a high P/S diet), carried out on a group of healthy individuals from North Karelia, Eastern Finland between 1981-1984, provided evidence that there may be a genetic component contributing to variation in response to dietary change. We have resampled blood from 107 individuals involved in the original studies and used Restriction Fragment Length Polymorphisms (RFLPs) to study the genetic contribution of variation at a number of candidate gene loci to the response to dietary change. The genes investigated in this study were the apolipoprotein (apo) genes: apo B, apo AII, apo E (protein polymorphism), apo AI-CIII-AIV gene cluster, and the LDL-receptor gene. On the basal diet the major effect of genotype on lipid traits was due to variation at the apo E gene locus; this protein polymorphism explained 14.6% of the phenotypic variance in LDL cholesterol levels and 12.7% of the phenotypic variance in total cholesterol levels. When switched to low fat high P/S diet, these effects of variation at the apo E gene locus on the phenotypic variation of LDL and total cholesterol levels disappeared. The major effect on the response to dietary change, delta, was seen on the difference in apo AI levels mediated by variation at the apo B gene locus (MspI RFLP) explaining 6.3% of the phenotypic variance in apo AI change. For the RFLPs of the apo AI-CII-AIV gene cluster, small but not significant differences on delta were found. Our results indicate that within the limits of the candidate genes studied, the major effects in response to dietary change was on apo AI levels mediated through variation at the apo B gene locus.
67 citations
TL;DR: There was a significant difference between identical and fraternal pairs in marginal correlation, both in asthma and hay fever, and in the cross‐correlation between hay fever in one twin and asthma in the other, which suggests that genetic factors are implicated in both hay fever and asthma and that some of these genetic Factors are common (at least among a subgroup of individuals) to both traits.
Abstract: Self-reported histories of hay fever and asthma were obtained from 3,808 pairs of adult twins 18 years and over registered with the Australian National Health Medical Research Council Twin Registry (1232 MZF, 567 MZM, 751 DZF, 352 DZM, 906 DZO). The prevalence of hay fever and asthma was 0.32 and 0.13, respectively, with little variation with zygosity, sex, and age. The associations between twin pairs for these two traits were analysed, under the assumption of constant prevalences, as a special case of a log-linear model for binary traits in pedigrees using the statistical package GLIM. The model assumption that there are no second- or higher-order interactions was tested in the 2 X 2 X 2 X 2 table of twin by disease outcomes without revealing strong evidence of departure, even in this large data set. The log-linear modelling showed that only three first-order interactions, namely 1) between hay fever in a twin pair, 2) asthma in a twin pair, and 3) hay fever and asthma in the same twin, were necessary to describe the data. The first two interaction terms were significantly larger in identical pairs; the third was independent of zygosity. Under this parsimonious model, there was a significant difference between identical and fraternal pairs in marginal correlation, both in asthma and hay fever, and in the cross-correlation between hay fever in one twin and asthma in the other. This suggests that genetic factors are implicated in both hay fever and asthma and that some of these genetic factors are common (at least among a subgroup of individuals) to both traits.
60 citations
TL;DR: In this paper, the authors examined the impact of censoring on correlations in age at onset in affected relatives and found that early onset is associated with higher risk of illness in siblings and nieces/nephrews but not in children.
Abstract: Previous analyses of age at onset in schizophrenia, which is highly variable and appears to be influenced by familial factors, have neglected to consider either (1) the impact of censoring on correlations in age at onset in affected relatives or (2) the impact of correlated ages at onset on the relationship between age at onset in the proband and risk in relatives. In this report, using methods outlined in the companion paper [MacLean et al., Genet Epidemiol 7:419-426, 1990] we examine these questions in the large family data set of schizophrenia collected by Lindelius [Acta Psychiat Scand (Suppl) 216:1-125, 1970]. Ages at onset are positively correlated in pairs of affected relatives (parent-offspring approximately equal to siblings greater than nieces/nephews) and these correlations are substantially higher after correction for censoring. Early age at onset is associated with higher risk of illness in siblings and nieces/nephrews but not in children. These results are consistent with the hypothesis that age at onset in schizophrenia is influenced by familial factors which are probably genetic and which are mostly unrelated to factors influencing disease liability.
56 citations
TL;DR: Approximations 6 and 8 are found to work appropriately in terms of both the estimation of all parameters and hypothesis testing, for each generating model, and lessen the computer time by allowing use of the Elston‐Stewart algorithm.
Abstract: The regressive models describe familial patterns of dependence of quantitative measures by specifying regression relationships among a person's phenotype and genotype and the phenotypes and genotypes of antecedents. When the number of sibs in the pattern of dependence increases, as in the class D regressive model, computation of the likelihood becomes time consuming, since the Elston-Stewart algorithm cannot be used generally. On the other hand, the simpler class A regressive model, which imposes a restriction on the sib-sib correlation, may lead to inference of a spurious major gene, as already observed in some instances. A simulation study is performed to explore the robustness of class A model with respect to false inference of a major gene and to search for faster methods of computing the likelihood under class D model. The class A model is not robust against the presence of a sib-sib correlation exceeding that specified by the model, unless tests on transmission probabilities are performed carefully: false detection of a major gene is reduced from a number of 26-30 to between 0 and 4 data sets out of 30 replicates after testing both the Mendelian transmission and the absence of transmission of a major effect against the general transmission model. Among various approximations of the likelihood formulation of the class D model, approximations 6 and 8 are found to work appropriately in terms of both the estimation of all parameters and hypothesis testing, for each generating model. These approximations lessen the computer time by allowing use of the Elston-Stewart algorithm.
47 citations
TL;DR: The paper presents an extension of the regressive logistic models proposed by Bonney to address the problems of variable age‐of‐onset and time‐dependent covariates in analysis of familial diseases, and application of the method to familial leprosy data leads to results consistent with previous analysis performed using the unified mixed model.
Abstract: The paper presents an extension of the regressive logistic models proposed by Bonney [Biometrics 42:611-625, 1986], to address the problems of variable age-of-onset and time-dependent covariates in analysis of familial diseases. This goal is achieved by using failure time data analysis methods, and partitioning the time of follow up in K mutually exclusive intervals. The conditional probability of being affected within the kth interval (k = 1...K) given not affected before represents the hazard function in this discrete formulation. A logistic model is used to specify a regression relationship between this hazard function and a set of explanatory variables including genotype, phenotypes of ancestors, and other covariates which can be time dependent. The probability that a given person either becomes affected within the kth interval (i.e., interval k includes age of onset of the person) or remains unaffected by the end of the kth interval (i.e., interval k includes age at examination of the person) are derived from the general results of failure time data analysis and used for the likelihood formulation. This proposed approach can be used in any genetic segregation and linkage analysis in which a penetrance function needs to be defined. Application of the method to familial leprosy data leads to results consistent with our previous analysis performed using the unified mixed model [Abel and Demenais, Am J Hum Genet 42:256-266, 1988], i.e., the presence of a recessive major gene controlling susceptibility to leprosy. Furthermore, a simulation study shows the capability of the new model to detect major gene effects and to provide accurate parameter estimates in a situation of complete ascertainment.
45 citations
TL;DR: It is shown that the probability of getting a lod score value of 3 under independent transmission of the disease and the marker may be not negligible.
Abstract: The significance of a lod score value of 3 is very difficult to assess in linkage studies between a genetic marker and a complex disease. One reason is that multiple tests may have been performed, voluntarily or otherwise. For the same disease, linkage may be tested by different laboratories with several markers under various genetic models and diagnostic schemes for the disease. In such a case, we show that the probability of getting a lod score value of 3 under independent transmission of the disease and the marker may be not negligible.
42 citations
TL;DR: The method is first illustrated with simulated twin data and next is applied to blood pressure data obtained in a Dutch sample of 59 male adolescent twin pairs, which shows that subjects with high blood pressure can be distinguished into groups with high genetic or high environmental scores.
Abstract: Implicit in the application of the common-factor model as a method for decomposing trait covariance into a genetic and environmental part is the use of factor scores. In multivariate analyses, it is possible to estimate these factor scores for the communal part of the model. Estimation of scores on latent factors in terms of individual observations within the context of a twin/family study amounts to estimation of individual genetic and environmental scores. Such estimates may be of both theoretical and practical interest and may be provided with confidence intervals around the individual estimates. The method is first illustrated with simulated twin data and next is applied to blood pressure data obtained in a Dutch sample of 59 male adolescent twin pairs. Subjects with high blood pressure can be distinguished into groups with high genetic or high environmental scores.
41 citations
TL;DR: Several statistical tests for linkage between a disease susceptibility locus and a marker locus for sib‐pair data are examined analytically and a new statistic based on the maximum of the “mean” and “proportions” statistics is derived.
Abstract: Several statistical tests for linkage between a disease susceptibility locus and a marker locus for sib-pair data are examined analytically. Two common statistics, a test based on the mean number of marker alleles shared identical by descent by sib-pairs, and a test based on the proportion of sib-pairs sharing exactly two marker alleles, are shown to be special cases of a more general statistic. We use this more general statistic to derive the asymptotically most powerful statistic for a given genetic alternative hypothesis, and then compare this statistic with the "mean" statistic and the "proportion" statistic. Results indicate that the "mean" statistic generally compares well with the most powerful statistic. However, in some instances the "mean" statistic may lose power, relative to the most powerful. To guard against this, a new statistic (the maximum of the "mean" and "proportions" statistics) is considered and its asymptotic distribution is derived. Results indicate that this new statistic performs well.
TL;DR: Statistical methods for testing whether a normal mixture distribution better characterizes a set of data than the proposed skewed, single‐population‐oriented models are offered and the power of these tests is examined through Monte Carlo experimentation.
Abstract: The long-standing problem of determining whether the skewness in a sample frequency distribution is the manifestation of the intermixing of disparate groups characterizable by a normal mixture distribution or the manifestation of non-mixture, skew-producing determinants is discussed. Biometrical tools for modeling and quantifying the significance of the skewness in a trait of interest that invite interpretations other than those formed in mixtures or "subgroups" are elaborated. Statistical methods for testing whether a normal mixture distribution better characterizes a set of data than the proposed (or any other) skewed, single-population-oriented models are offered. The power of these tests is examined through Monte Carlo experimentation. A brief application in hypertension research demonstrates some of the problems and methods discussed in the paper.
TL;DR: It is shown that under the null hypothesis of no linkage the maximum likelihood estimator of the recombination fraction converges to 1/2 even when the trait‐related parameter values in the likelihood function are misspecified.
Abstract: We show that under the null hypothesis of no linkage the maximum likelihood estimator of the recombination fraction converges to 1/2 even when the trait-related parameter values in the likelihood function are misspecified. Furthermore, we show that under the null hypothesis of no linkage, but with misspecified trait-related parameter values, the negative of twice the natural logarithm of the likelihood ratio statistic still has a limiting chi-square distribution with 1 degree of freedom.
TL;DR: Whether assuming the correct mode of inheritance at the linked locus leads to a higher lod score than assuming the incorrect mode of inherited irrespective of penetrance assumptions is determined and whether it is possible to estimate the apparent penetrance due to the second, unlinked locus from the linkage data is determined.
Abstract: What happens to the results of linkage analysis when one assumes that a disease results from a single genetic locus with reduced penetrance when the actual cause is two epistatically interacting loci? We wanted to (1) determine whether assuming the correct mode of inheritance at the linked locus leads to a higher lod score than assuming the incorrect mode of inheritance irrespective of penetrance assumptions and (2) determine whether it is possible to estimate the apparent penetrance due to the second, unlinked locus from the linkage data. Linkage data were simulated under three different two-locus models. Different “penetrances” were simulated by using different disease allele frequencies at the unlinked locus. Data were then analyzed assuming a single locus with reduced penetrance. The maximum lod score was maximized with respect to penetrance (LVP curves).
We found that if there were enough data, assuming the correct (i.e., generating) mode of inheritance at the linked locus always led to a higher lod score than assuming the incorrect mode of inheritance no matter what the penetrance assumption. In contrast to the case where reduced penetrance is due to random factors, the estimate of the apparent penetrance (the “penetrance” due to the second locus) was biased, thus making any estimation of the gene frequency at the second locus doubtful. The ability to detect linkage was apparently not affected when the effects of the second locus were treated as random reduced penetrance. The results suggest that analyzing the data under the assumption of a single-locus model with reduced penetrance rather than a two-locus model will not substantially decrease the ability to establish linkage nor will it affect determining the mode of inheritance at the linked locus from the linkage data.
TL;DR: Extensions of the approach to sib‐pair linkage tests developed by Haseman and Elston are proposed which incorporate information on age of onset and age at examination, and alternate sources for the age‐of‐onset corrections are described.
Abstract: Extensions of the approach to sib-pair linkage tests developed by Haseman and Elston [Behav Genet 2:3–19, 1972] are proposed which incorporate information on age of onset and age at examination. Alternate sources for the age of onset corrections are described, including models for the estimation of parameters associated with the age of onset distribution. Simulation is used to examine the performance of the approach when applied to a dominant disorder of late onset for a range of recombination fractions ranging from very tight linkage to free recombination. For each set of genetic parameters, 2,000 samples of 50 four-member sibships were generated under a complete ascertainment model to investigate power and Type I error, and to compare variants of the proposed technique. Results with and without age-of-onset correction are compared to each other and to those obtainable if penetrance were complete, i.e., if there were no intervening age-of-onset phenomenon.
Results from simulation studies show that significance probabilities are enhanced in the presence of linkage when age-of-onset extensions are used. The proposed methods are associated with acceptable levels of Type I error, and substantive gains in power are obtained when data related to age of onset and age at examination are incorporated into the analysis.
TL;DR: The present study shows that detection of linkage in presence of heterogeneity is feasible with a realistic sample size of small pedigrees as long as the linked disease locus accounts for more than 25% of the cases.
Abstract: We have conducted a simulation study in small pedigrees to investigate the power to detect linkage and heterogeneity for a disorder due to either one of two independent disease loci. We have considered a highly polymorphic marker locus (PIC = 70%) linked to one disease locus and unlinked to the second. The power to detect linkage has been examined by using the admixture test. We have varied the mode of transmission of each disease locus, the ascertainment of families and the proportion of cases in the population due to the linked disease locus. Generally, for the multiplex ascertainments we have considered, the power to detect linkage is greater when the linked disease locus has a high penetrance, when the unlinked disease locus has a low penetrance, and when pedigrees with multiple affected are selected. When selecting families with multiple affected, the rate of "mixed" families (i.e., those segregating for both disease loci) increases. However, for the pedigree structure we have considered, the power of the linkage test is more affected by a decrease in the rate of "linked" families than by an increase in the rate of "mixed" families. Finally, the present study shows that detection of linkage in presence of heterogeneity is feasible with a realistic sample size of small pedigrees as long as the linked disease locus accounts for more than 25% of the cases.
TL;DR: Although it was able to detect strong linkage disequilibrium between some pairs of RFLPs in this sample, most R FLPs at the LDLR locus were not in strong linkage Disequilibrium despite their physical proximity.
Abstract: We determined pairwise linkage disequilibria between 12 restriction fragment length polymorphism (RFLP) markers at or near the low-density lipoprotein receptor (LDLR) locus on chromosome 19p13.2-13.1 in 92 unrelated individuals. Of these 12 RFLPs, two were newly identified under a cosmid-based strategy designed to screen for RFLPs. We estimated linkage disequilibrium by determining three different measurements: D (the maximum likelihood estimate of linkage disequilibrium), D' (Lewontin's normalized estimate of D), and r (an index of gametic correlation). When r was used as the estimate of linkage disequilibrium, five of the 66 comparisons were significant according to a level of significance adjusted by the Bonferroni-Holm correction. Only four pairs of RFLPs within a 100 kb region that included the LDLR gene itself were in significant linkage disequilibrium. Although we were able to detect strong linkage disequilibrium between some pairs of RFLPs in this sample, most RFLPs at the LDLR locus were not in strong linkage disequilibrium despite their physical proximity.
TL;DR: Analysis of untransformed data under a conditional likelihood provides evidence for Mendelian transmission of a major gene with commingling of two distributions and demonstration of familiality warrants continued investigation of the index as an indicator of liability for schizophrenia.
Abstract: The genetic analysis of schizophrenia would be facilitated by identification of a heritable correlate of liability Deviance on an index of Minnesota Multiphasic Personality Inventory (MMPI) signs is associated with the disease phenotype; the familial aggregation and mode of transmission of this continuous psychometric indicator have yet to be established In this paper, we examine the indicator through commingling analysis and segregation analysis with both the mixed and unified models on 65 nuclear families containing 211 normal individuals Evidence for a high degree of familiality is found Analysis of untransformed data under a conditional likelihood provides evidence for Mendelian transmission of a major gene with commingling of two distributions The frequency of the "high index score" allele is 015, with the gene accounting for 31% of the total population variance; such a locus would be relevant to the study of psychopathology as 28% of the population would carry at least one deviant allele When power-transformed scores are used to eliminate skewness, there is evidence for one distribution and it is not possible to distinguish single gene from multifactorial (polygenic or cultural) inheritance While our findings regarding mode of transmission must be interpreted cautiously and confirmation of a single locus requires further study, demonstration of familiality warrants continued investigation of the index as an indicator of liability for schizophrenia
TL;DR: Overall, 6 of 77 (8%) of cases came from families that included two or more relatives with breast or lung cancer in addition to the proband with malignant glioma, which may form familial clusters worthy of further evaluation in future studies by pedigree and genetic linkage analyses.
Abstract: Family histories of male patients with histologically confirmed malignant gliomas were compared to family histories of controls (wives). Included were 77 case families with 892 relatives and 77 control families with 719 relatives. Cases had significantly more siblings than controls (P = 0.02), although cases were not preferentially the oldest or the youngest sibs. Odds ratios of two or more were found for mental retardation, Parkinson's disease, and meningitis for the relatives of cases versus controls, but none were statistically significant. The excesses of Parkinson's disease and meningitis were explained by the family of one particularly interesting case containing three relatives with meningitis and two relatives with Parkinson's disease. Noteworthy age-adjusted odds ratios for cancer among relatives of cases compared to relatives of controls were 1.6 (95% confidence interval (CI) = 1.0-2.3) for cancer of any site, 2.4 (95% CI = 0.8-6.1) for breast cancer, and 4.0 (95% CI = 0.6-10.7) for lung cancer. Only the odds ratio for cancer of any site was statistically significant. Overall, 6 of 77 (8%) of cases came from families that included two or more relatives with breast or lung cancer in addition to the proband with malignant glioma. These three cancer sites may form familial clusters worthy of further evaluation in future studies by pedigree and genetic linkage analyses.
TL;DR: It is shown how the widely used “proportional hazards” model of Cox is extended by the addition of latent variable, ε, reflecting the shared susceptibility of related subjects because of their shared genes or shared environment to allow the main effects of measured genetic markers and environmental variables to be estimated, as well as the residual variance of genetic and environment and their interactions.
Abstract: Classic methods in genetics for the analysis of binary attributes, based on an assumption of a "threshold" on a normally distributed latent variable called "liability," estimate the strength of genetic and environmental effects from differences in correlations between relatives of differing genetic relatedness. Two problems that are not easily addressed by these methods are the need to take the age of onset into account (particularly in chronic diseases in which incidence rates vary considerably with age and the lengths of time at risk can vary between individuals) and the desirability of incorporating measured covariates (genetic or environmental). The standard methods of cohort analysis used in epidemiology allow for both of these features, but until recently have been restricted to independent individuals. Recent developments in survival analysis have extended the widely used "proportional hazards" model of Cox by the addition of latent variable, epsilon, reflecting the shared susceptibility of related subjects because of their shared genes or shared environment. We show how this approach can be combined with more traditional models of gene-environment interaction to allow the main effects of measured genetic markers and environmental variables to be estimated, as well as the residual variance of genetic and environment and their interactions. The approaches are applied to a cohort of female twin births in Sweden from 1886 to 1958, linked with the Swedish cancer registry from 1961 to 1982.
TL;DR: Applying both commingling and segregation analyses to samples of simulated pedigree data in which a major locus is segregating in the presence of polygenes and an individual‐specific environmental effect shows limited usefulness as a screening technique for the presence for a single locus.
Abstract: Commingling analysis is commonly used to provide preliminary evidence for a single genetic locus with a major effect on the quantitative trait of interest. In this paper, the effectiveness of commingling analysis as a screening technique to identify samples for segregation analysis is assessed by applying both commingling and segregation analyses to samples of simulated pedigree data in which a major locus is segregating in the presence of polygenes and an individual-specific environmental effect. Under the circumstances simulated here, there is evidence for a single locus from segregation analysis but not from commingling analysis in at least 20% of the samples. No more than 2% of the samples provided evidence for commingling but not for segregation of a single locus. Comparisons of the samples that give evidence for both commingling and segregation, evidence for one but not the other, and no evidence for either show that evidence for commingling depends on the distributional characteristics of the trait in the sample, while support for the single locus from segregation analysis depends on both the distributional characteristics as well as the transmission of the rarer allele from parents to offspring. Since lack of commingling does not rule out the existence of a single locus in the realistic situations considered here, commingling analysis has limited usefulness as a screening technique for the presence for a single locus. In contrast, evidence for commingling does suggest the possibility that a single locus has a major effect on the trait and commingling analysis can provide guidance in the choice of initial parameter estimates for segregation analysis.
TL;DR: The data suggest that variation in the apo B gene influences the metabolism of LDL and that it is different in individuals of different ethnic background.
Abstract: Circulating levels of low-density lipoprotein (LDL) vary considerably within and between populations, paralleled by differing coronary heart disease (CHD) mortality rates. We have previously shown that variation in the apolipoprotein (apo) B gene as associated with certain restriction fragment length polymorphisms (RFLPs) influences the metabolism of LDL in the U.K. population. To investigate a possible genetic contribution to variation in LDL levels in differing populations we have extended this original study. RFLPs of the apo B gene were determined in samples of individuals from the United Kingdom, Finland, Italy, Spain, and Africa. Significant associations of LDL fractional catabolic rate with the apo B EcoRI and XbaI RFLP genotypes were detected only in the two North European populations. In the African population sample, the XbaI RFLP displayed a significant association with LDL apo B synthesis. The data suggest that variation in the apo B gene influences the metabolism of LDL and that it is different in individuals of different ethnic background.
TL;DR: Application of fourth‐order moments of factor scores to detect interactive origin of common factors is illustrated with simulated twin data.
Abstract: Moment expressions for individual factor scores can serve as simple tests for the presence of a particular class of interaction factors that are disguised as pure genetic and/or environmental factors. That is, individual genetic and environmental factor scores may be used to construct fourth-order moments of these factors in order to test whether a common genetic or environmental factor in the multivariate genetic factor model is in fact of the interactive origin concerned. Expected fourth-order moments are derived for cases with and without interaction. Application of fourth-order moments of factor scores to detect interactive origin of common factors is illustrated with simulated twin data.
TL;DR: Systolic and diastolic blood pressures and body‐size indices such as body height, body weight, sitting height, chest circumference, skinfold thickness, and body mass index were assessed in 110 pairs of like‐sex Chinese twins.
Abstract: Systolic and diastolic blood pressures and body-size indices such as body height, body weight, sitting height, chest circumference, skinfold thickness, and body mass index (BMI) were assessed in 110 pairs of like-sex Chinese twins (75 monozygotic and 35 dizygotic) aged 7-12 years. Significant correlations of blood pressure with body-size indices were found. Prior to adjusting for body-size effects, three twin methods yielded low heritability estimates for both systolic (0.32-0.41) and diastolic (0.32-0.51) pressures. Adjusting systolic pressure for body height and BMI via multiple regression nearly halved heritability estimates, but adjusting diastolic pressure for body height and skinfold thickness only changed the estimates slightly.
TL;DR: Methods for correcting the effects of censoring on the relationship between age at onset in the proband and liability in relatives and a large family study of schizophrenia are described.
Abstract: Genetic studies of disorders with adult onset often contain individuals who have not completed their age at risk when last observed. Without correction for such censoring, correlation in ages at onset among relatives is substantially underestimated. Moreover, without correction for the effect of correlated ages at onset, the relationship between age at onset in the proband and liability in relatives is substantially overestimated. The present paper describes methods for correcting the effects of censoring on these estimates. In a companion paper [Kendler and MacLean, Genet Epidemiol 7:409-417, 1990] these methods are applied to a large family study of schizophrenia.
TL;DR: The familial resemblance of plasma apolipoprotein B was investigated in a sample of 102 families including 419 members who volunteered for a free health checkup in the Preventive Center of Vandoeuvre‐lès‐Nancy, France, which indicated that a recessive and a dominant major‐locus model appeared nearly equally supported by the data.
Abstract: The familial resemblance of plasma apolipoprotein B (apo B) was investigated in a sample of 102 families including 419 members who volunteered for a free health checkup in the Preventive Center of Vandoeuvre-les-Nancy, France. The mean levels (+/- SD) of apo B were 141.0 (+/- 32.6), 121.8 (+/- 27.7), and 98.6 (+/- 22.6) mg/dl in fathers, mothers, and offspring, respectively. The familial correlations were 0.04, 0.13, 0.21 (P less than .01), and 0.47 (P less than .001) between spouses, father-offspring, mother-offspring, and siblings, respectively, after adjustment on age, body mass index, and sex. A genetic analysis was performed using the approach proposed by Bonney, which indicated that a recessive and a dominant major-locus model appeared nearly equally supported by the data. Under the recessive model, the frequency q of the most common allele was estimated as 0.825, with a mean difference of 60.4 mg/dl between high and low homozygotes. Under the dominant model, q was estimated as 0.875, with a mean increase of 34.2 mg/dl in heterozygotes and high homozygotes. However, the hypothesis of Mendelian transmission and the environmental hypothesis could not be formally tested because of great numeric difficulties encountered in the estimation of the three transmission probabilities. Given these analytical restrictions, we cannot conclude in favor of a major locus influencing apo B level in our population, even though the evidence is suggestive. The genetic heterogeneity underlying the familial aggregation of apo B level, suggested by several recent publications, might explain the difficulty in discerning a single major locus in a population sample of small nuclear families, not ascertained through patients enriching the sample in high values of apo B. These findings call into question the relevance of the approach through "healthy" populations in the search for major loci influencing biological traits.