Estimation of individual genetic and environmental profiles in longitudinal designs

Parameter estimates obtained in the genetic analysis of longitudinal data can be used to construct individual genetic and environmental profiles across time. Such individual profiles enable the attribution of individual phenotypic change to changes in the underlying genetic or environmental processes and may lead to practical applications in genetic counseling and epidemiology. Simulations show that individual estimates of factor scores can be reliably obtained. Decomposition of univariate, and to a lesser extent of bivariate, phenotypic time series may yield estimates of independent individual G(t) and E(t), however, that are intercorrelated. The magnitude of these correlations depends somewhat on the autocorrelation structure of the underlying series, but to obtain completely independent estimates of genetic and environmental individual profiles, at least three measured indicators are needed at each point in time. KEY WORDS: longitudinal genetic analysis; environmental profiles; genetic profiles; factor scores; Kalman filter

Factor and Simplex Models for Repeated Measures: Application to Two Psychomotor Measures of Alcohol Sensitivity in Twins

As part of a larger study, data on arithmetic computation and motor coordination were obtained from 206 twin pairs. The twins were measured once before and three times after ingesting a standard dose of alcohol. Previous analyses ignored the time-series structure of these data. Here we illustrate the application of simplex models for the genetic analysis of covariance structures in a repeated-measures design and compare the results with factor models for the two psychomotor measures. We then present a bivariate analysis incorporating simplex processes common and specific to the two measures. Our analyses confirm the notion that there is genetic variation affecting psychomotor performance which is "switched on" in the presence of alcohol. We compare the merits of analysis of mean products versus covariance matrices and confront some practical problems that may arise in situations where the number of subjects is relatively small and where the causal structure among the latent variables places a heavy demand on the data. © 1989 Plenum Publishing Corporation

A frailty model for (interval) censored family survival data, applied to the age at onset of non-physical problems

Family survival data can be used to estimate the degree of genetic and environmental contributions to the age at onset of a disease or of a specific event in life. The data can be modeled with a correlated frailty model in which the frailty variable accounts for the degree of kinship within the family. The heritability (degree of heredity) of the age at a specific event in life (or the onset of a disease) is usually defined as the proportion of variance of the survival age that is associated with genetic effects. If the survival age is (interval) censored, heritability as usually defined cannot be estimated. Instead, it is defined as the proportion of variance of the frailty associated with genetic effects. In this paper we describe a correlated frailty model to estimate the heritability and the degree of environmental effects on the age at which individuals contact a social worker for the first time and to test whether there is a difference between the survival functions of this age for twins and non-twins. © 2009 The Author(s)

Introduction to the Special Issue: Human Linkage Studies for Behavioral Traits

In the post Genome era, the aim of behavior genetics has shifted from estimating the relative contributions of genes and environmental factors to (co-)variation in human complex traits, to localization of genes and identification of functional genetic variants. This special issue reflects this transition and presents fifteen papers that report on genome-wide linkage scans for complex traits in humans and on methodological tools and innovations. Six papers focus on cognition and report overlapping linkage peaks on chromosomes 6p and 14p. Papers on addictive behavior, i.e. smoking and alcohol dependence and its endophenotypes, find moderate LOD scores on chromosomes 6p, 5q, 4p and 7q, respectively. Three papers concentrate on emotionality, depression and loneliness and examine chromosomes 2q and 12q. The papers in this issue represent a summary of the first large scale linkage enterprises of human behavioral traits. © 2006 Springer Science+Business Media, Inc.link_to_subscribed_fulltex

Resemblances of Parents and Twins in Sport Participation and Heart Rate

A model to analyze resemblances of twins and parents using LISREL is outlined and applied to sports participation and heart-rate data. Sports participation and heart rate were measured in 44 monozygotic and 46 dizygotic adolescent twin pairs and in their parents. Genetic factors influence variation in both sports behavior and heart rate, while there is no evidence for transmission from parental environment to offspring environment. For sports participation the data support a model in which there is a high positive correlation between environments of spouses and between environments of female twins. This correlation is absent for male twins and negative for opposite sex twins. For heart rate, a positive correlation between environmental influences was observed for all twins; there is no evidence for assortative mating. The proposed model can also handle data sets where parents and twins have been measured on more than one variable. This is illustrated by an application to the observed association of sports participation and heart rate

Implementation of a combined association-linkage model for quantitative traits in linear mixed model procedures of statistical packages

Atransmission disequilibrium test for quantitative traits which combines association and linkage analyses is currently available in several dedicated software packages. We describe how to implement such models in linear mixed model procedures that are available in widely used statistical packages such as SPSS. We also briefly mention a few extensions of the model that become naturally available once the model is implemented in such procedures. Genotyping of many microsatellite markers or single nucleotide polymorphisms (SNPs) over the entire genome is becoming increasingly common in human genetics. In those high-resolution maps the average distance between microsatellite markers may be as small as 5 cM and between SNPs one half cM or less. At those small distances it becomes fairly likely that some markers in the set are in linkage disequilibrium (LD) with a gene affecting the trait (a so-called quantitative trait locus or QTL if the trait or the vulnerability distribution is quantitative). Different alleles or combinations of alleles of the markers or SNPs can then be associated with different trait means. Association studies are conducted to discover such allelic effects. Abecasis et al. (2000) generalized the model proposed by Fulker et al. (1999) for combined linkage and association tests, within and between families. The Fulker-Abecasis or F-A model is implemented in the program QTD

Genetic Covariance Structure of Reading, Intelligence and Memory in Children

This study investigates the genetic relationship among reading performance, IQ, verbal and visuospatial working memory (WM) and short-term memory (STM) in a sample of 112, 9-year-old twin pairs and their older siblings. The relationship between reading performance and the other traits was explained by a common genetic factor for reading performance, IQ, WM and STM and a genetic factor that only influenced reading performance and verbal memory. Genetic variation explained 83% of the variation in reading performance; most of this genetic variance was explained by variation in IQ and memory performance. We hypothesize, based on these results, that children with reading problems possibly can be divided into three groups: (1) children low in IQ and with reading problems; (2) children with average IQ but a STM deficit and with reading problems; (3) children with low IQ and STM deficits; this group may experience more reading problems than the other two

Genetic and environmental contributions to loneliness in adults: the Netherlands Twin Register study

Heritability estimates based on two small studies in children indicate that the genetic contribution to individual differences in loneliness is approximately 50%. Heritability estimates of complex traits such as loneliness may change across the lifespan, however, as the frequency, duration, and range of exposure to environmental influences accrues, or as the expression of genetic factors changes. We examined data on loneliness from 8,387 young adult and adult Dutch twins who had participated in longitudinal survey studies. A measure of loneliness was developed based on factor analyses of items of the YASR (Achenbach, (1990) The Young Adult Self Report, University of Vermont, Department of Psychiatry, Burlington, VT). Variation in loneliness was analyzed with genetic structural equation models. The estimate of genetic contributions to variation in loneliness in adults was 48%, which is similar to the heritability estimates found previously in children. There was no evidence for sex or age differences in genetic architecture. Sex differences in prevalence were significant, but we did not see an association with age or birth cohort. All resemblance between twin relatives was explained by shared genes, without any suggestion of a contribution of shared environmental factors. ©2005 Springer Science+Business Media, Inc

An exploration of gene-environment interaction and asthma in a large sample of 5-year-old Dutch twins.

A consistent finding from twin studies is that the environment shared by family members does not contribute to the variation in susceptibility to asthma. At the same time, it is known that environmental risk factors that are shared by family members are associated with the liability for asthma. We hypothesize that the absence of a main effect of shared environmental factors in twin studies can be explained by gene-environment interaction, that is, that the effect of an environmental factor shared by family members depends on the genotype of the individual. We explore this hypothesis by modeling the resemblance in asthma liability in twin pairs as a function of various environmental risk factors and test for gene-environment interaction. Asthma data were obtained by parental report for nearly 12,000 5-year-old twin pairs. A series of environmental risk factors was examined: birth cohort, gestational age, time spent in incubator, breastfeeding, maternal educational level, maternal smoking during pregnancy, current smoking of parents, having older siblings, and amount of child care outside home. Results revealed that being a boy, born in the 1990s, premature birth, longer incubator time, and child care outside home increased the risk for asthma. With the exception of premature birth, however, none of these factors modified the genetic effects on asthma. In very premature children shared environmental influences were important. In children born after a gestation of 32 weeks or more only genetic factors were important to explain familial resemblance for asthma