Genetic and social influences on starting to smoke: a study of Dutch adolescent twins and their parents

In a study of 1600 Dutch adolescent twin pairs we found that 59% of the inter‐individual variation in smoking behaviour could be attributed to shared environmental influences and 31% to genetic factors. The magnitude of the genetic and environmental effects did not differ between boys and girls. However, environmental effects shared by male twins and environmental effects shared by female twins were imperfectly correlated in twins from opposite‐sex pairs, indicating that different environmental factors influence smoking in adolescent boys and girls. In the parents of these twins, the correlation between husband and wife for‘currently smoking’(r = 0.43) was larger than for‘ever smoked’(r = 0.18). There was no evidence that smoking of parents (at present or in the past) encouraged smoking in their offspring. Resemblance between parents and offspring was significant but rather low and could be accounted for completely by their genetic relatedness. Moreover, the association between‘currently smoking’in the parents and smoking behaviour in their children was not larger than the association between‘ever smoking’in parents and smoking in their children. Copyright © 1994, Wiley Blackwell. All rights reserve

Mx Scripts Library: Structural Equation Modeling Scripts for Twin and Family Data

Structural equation modeling (SEM) provides a flexible tool to carry out genetic analyses of family and twin data. The basic model which decomposes the variance between and within families for a particular trait into genetic and non-genetic components can be generalized to multivariate and/ or longitudinal data, incorporate sex differences in parameter estimates, and model the effects of measured environment, candidate genes or DNA marker data. We introduce a web-based library ( http://www.psy.vu.nl/mxbib ) of scripts for uni- and multivariate genetic epidemiological analyses, as well as for linkage and genetic association tests. The scripts are written to be used with the freely available software package Mx and provide a flexible and uniform approach to the analysis of data from relatives. © 2005 Springer Science+Business Media, Inc

Application of nonlinear factor analysis to genotype-environment interaction

The intention of this paper is to show how the methods of nonlinear factor analysis as developed by McDonald (Br. J. Math. Stat. Psychol. 20:205-215, 1967) can be used to study genotype-environment interaction. The method is applied to the interaction of genotype and within-family en-vironmental influences. Simulated twin data are used to illustrate how this type of interaction may be detected and estimated. It is shown that estimates of genetic influences are not affected by G x E interaction. KEY WORDS: genotype-environment interaction; nonlinear factor analysis; twin data

Reconsidering the Heritability of Intelligence in Adulthood: Taking Assortative Mating and Cultural Transmission into Account

Heritability estimates of general intelligence in adulthood generally range from 75 to 85%, with all heritability due to additive genetic influences, while genetic dominance and shared environmental factors are absent, or too small to be detected. These estimates are derived from studies based on the classical twin design and are based on the assumption of random mating. Yet, considerable positive assortative mating has been reported for general intelligence. Unmodeled assortative mating may lead to biased estimates of the relative magnitude of genetic and environmental factors. To investigate the effects of assortative mating on the estimates of the variance components of intelligence, we employed an extended twin-family design. Psychometric IQ data were available for adult monozygotic and dizygotic twins, their siblings, the partners of the twins and siblings, and either the parents or the adult offspring of the twins and siblings (N = 1314). Two underlying processes of assortment were considered: phenotypic assortment and social homogamy. The phenotypic assortment model was slightly preferred over the social homogamy model, suggesting that assortment for intelligence is mostly due to a selection of mates on similarity in intelligence. Under the preferred phenotypic assortment model, the variance of intelligence in adulthood was not only due to non-shared environmental (18%) and additive genetic factors (44%) but also to non-additive genetic factors (27%) and phenotypic assortment (11%).This non-additive nature of genetic influences on intelligence needs to be accommodated in future GWAS studies for intelligence

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

A Multivariate Genetic Analysis of Sensation Seeking

The genetic architecture of sensation seeking was analyzed in 1591 adolescent twin pairs. Individual differences in sensation seeking were best explained by a simple additive genetic model. Between 48 and 63 % of the total variance in sensation seeking subscales was attributable to genetic factors. There were no sex differences in the magnitude of the genetic and environmental effects. The different dimensions of sensation seeking were moderately correlated. The strongest correlations were between the subscales Thrill and Adventure Seeking and Experience Seeking (r = 0.4) and between Boredom Susceptibility and Disinhibition (r = 0.4 in males, r = 0.5 in females). A triangular decomposition showed that the correlations between the sensation seeking subscales were induced mainly by correlated genetic factors and, to a smaller extent, by correlated unique enviromnental factors. The genetic and environmental correlation structures differed between males and females. For females, higher genetic correlations for Experience Seeking with Boredom Susceptibility and Disinhibition and higher correlations among the unique environmental factors were found. There was no evidence that sex-specific genes influenced sensation seeking behavior in males and females. KEY WORDS: Sensation seeking; adolescent twins; multivariate genetic analysis

Accounting for a Quantitative Trait Locus for Plasma Triglyceride Levels: Utilization of Variants in Multiple Genes

For decades, research efforts have tried to uncover the underlying genetic basis of human susceptibility to a variety of diseases. Linkage studies have resulted in highly replicated findings and helped identify quantitative trait loci (QTL) for many complex traits; however identification of specific alleles accounting for linkage remains elusive. The purpose of this study was to determine whether with a sufficient number of variants a linkage signal can be fully explained.We used comprehensive fine-mapping using a dense set of single nucleotide polymorphisms (SNPs) across the entire quantitative trait locus (QTL) on human chromosome 7q36 linked to plasma triglyceride levels. Analyses included measured genotype and combined linkage association analyses.Screening this linkage region, we found an over representation of nominally significant associations in five genes (MLL3, DPP6, PAXIP1, HTR5A, INSIG1). However, no single genetic variant was sufficient to account for the linkage. On the other hand, multiple variants capturing the variation in these five genes did account for the linkage at this locus. Permutation analyses suggested that this reduction in LOD score was unlikely to have occurred by chance (p = 0.008).With recent findings, it has become clear that most complex traits are influenced by a large number of genetic variants each contributing only a small percentage to the overall phenotype. We found that with a sufficient number of variants, the linkage can be fully explained. The results from this analysis suggest that perhaps the failure to identify causal variants for linkage peaks may be due to multiple variants under the linkage peak with small individual effect, rather than a single variant of large effect

Genome-wide Linkage Scan to Identify Loci for Age at First Cigarette in Dutch Sibling Pairs

Most smokers begin smoking during adolescence and early age of smoking initiation is related to more frequent current smoking, daily smoking and more dependent smoking (Everret et al., 1999; Lando et al.

Heritability of cardiovascular risk factors in a Brazilian population: Baependi Heart Study

<p>Abstract</p> <p>Background</p> <p>The heritability of cardiovascular risk factors is expected to differ between populations because of the different distribution of environmental risk factors, as well as the genetic make-up of different human populations.</p> <p>Methods</p> <p>The purpose of this analysis was to evaluate genetic and environmental influences on cardiovascular risk factor traits, using a variance component approach, by estimating the heritability of these traits in a sample of 1,666 individuals in 81 families ascertained randomly from a highly admixed population of a city in a rural area in Brazil.</p> <p>Results</p> <p>Before adjustment for sex, age, age², and age × sex interaction, polygenic heritability of systolic (SBP) and diastolic (DBP) blood pressure were 15.0% and 16.4%, waist circumference 26.1%, triglycerides 25.7%, fasting glucose 32.8%, HDL-c 31.2%, total cholesterol 28.6%, LDL-c 26.3%, BMI 39.1%. Adjustment for covariates increased polygenic heritability estimates for all traits mainly systolic and diastolic blood pressure (25.9 and 26.2%, respectively), waist circumference (40.1%), and BMI (51.0%).</p> <p>Conclusion</p> <p>Heritability estimates for cardiovascular traits in the Brazilian population are high and not significantly different from other studied worldwide populations. Mapping efforts to identify genetic loci associated with variability of these traits are warranted.</p