The NLSY Kinship Links: Using the NLSY79 and NLSY-Children Data to Conduct Genetically-Informed and Family-Oriented Research.

The National Longitudinal Survey of Youth datasets (NLSY79; NLSY-Children/Young Adults; NLSY97) have extensive family pedigree information contained within them. These data sources are based on probability sampling, a longitudinal design, and a cross-generational and within-family data structure, with hundreds of phenotypes relevant to behavior genetic (BG) researchers, as well as to other developmental and family researchers. These datasets provide a unique and powerful source of information for BG researchers. But much of the information required for biometrical modeling has been hidden, and has required substantial programming effort to uncover-until recently. Our research team has spent over 20 years developing kinship links to genetically inform biometrical modeling. In the most recent release of kinship links from two of the NLSY datasets, the direct kinship indicators included in the 2006 surveys allowed successful and unambiguous linking of over 94 % of the potential pairs. In this paper, we provide details for research teams interested in using the NLSY data portfolio to conduct BG (and other family-oriented) research.

Relations between multi-informant assessments of ADHD symptoms, DAT1, and DRD4.

Researchers conducting candidate gene studies of attention-deficit/hyperactivity disorder (ADHD) typically obtain symptom ratings from multiple informants (i.e., mothers, fathers, and teachers) and use a psychologist's best estimate or a simple algorithm, such as taking the highest symptom ratings across informants, to construct diagnostic phenotypes for estimating association. Nonetheless, these methods have never been empirically validated in the context of a molecular genetic study. In the current study, the authors systematically evaluated several methods of operationalizing phenotypes and the resulting evidence for association between ADHD and the candidate genes: dopamine transporter gene (DAT1) and dopamine D4 receptor gene (DRD4). Use of symptom scores as continuous scales in regression analysis suggested that the combination of mother and teacher ratings yielded the strongest evidence for association between hyperactive-impulsive ADHD symptoms and DAT1 and between inattentive ADHD symptoms and DRD4. Teacher ratings alone were sufficient for evaluating the association between inattentive symptoms and DAT1. Further, this regression-based method consistently yielded stronger evidence for association among ADHD symptoms, DAT1, and DRD4 than did three simple algorithms (i.e., the and, or, and averaging rules). The implications of these results for future molecular genetic studies of ADHD are discussed.

Sources of exposure to smoking and drinking friends among adolescents: a behavioral-genetic evaluation.

Substance-using friends expose adolescents to models of, and opportunities for, substance use that may lead to its initiation or reinforce existing use. Using genetically informative data from the National Longitudinal Study of Adolescent Health (P. S. Bearman, J. Jones, & J. R. Udry, 1998), the authors examined whether adolescents' exposure to friends' tobacco smoking and alcohol drinking was better explained by family-social or genetic influences. To conduct analyses, the authors constructed substance use exposure scores for adolescent siblings from the responses of siblings' nominated friends to self-reported smoking and drinking items. Using behavioral-genetic analyses of these substance use exposure scores, the authors estimated that 64% of the variance in adolescents' exposure to friends who smoke and drink could be explained by genetic influences, whereas shared environmental influences were zero. These results provide evidence of active, evocative, or both types of gene-environment correlations. Genetic factors can influence the formation of friendships with substance-using peers, thereby contributing to adolescents' exposure to substance use behaviors.

Under the skin: On the impartial treatment of genetic and environmental hypotheses of racial differences.

Environmental and genetic explanations have been given for Black-White racial differences in intelligence and other traits. In science, viable, alternative hypotheses are ideally given equal Bayesian prior weights; but this has not been true in the study of racial differences. This article advocates testing environmental and genetic hypotheses of racial differences as competing hypotheses. Two methods are described: (a) fitting means within structural equation models and (b) predicting means of interracial children. These methods have limitations that call for improved research designs of racial differences. One improvement capitalizes on biotechnology. Genetic admixture estimates--the percentage of genes of European origin that a Black individual possesses (independent of genes related to skin coloration)--can represent genetic influences. The study of interracial children can be improved by increasing sample size and by choosing family members who are most informative for a research question. Eventually, individual-admixture estimates will be replaced by molecular genetic tests of alleles of those genes that influence traits.

Expanding variance and the case of historical changes in IQ means: a critique of Dickens and Flynn (2001).

The Flynn effect is the rise in mean IQ scores during the 20th century, amounting to about 0.33 IQ points per year. Many theoretical explanations have been proposed, though none are universally accepted. W. Dickens and J. R. Flynn's (2001) new approach explains the large IQ changes by means of recursive models of IQ growth. A salient feature of their models is that IQ phenotypes and their supportive environments are correlated; in addition, environmental effects can rebound on phenotypic IQ to increase or lower IQ. In this critique, the authors examine an empirical challenge to their models, which typically imply large changes in IQ variance. However, the historical rise in IQ mean level has not been accompanied by substantial variance changes, a finding inconsistent with the properties of the proposed model.

Theory development should begin (but not end) with good empirical fits: a comment on Roberts and Pashler (2000).

S. Roberts and H. Pashler (2000) argued against using goodness of fit as evidence to support theories. The authors agree with their suggestions for how to go beyond good fits but disagree with their starting point. In this comment, the authors argue that good fits are part and parcel of theory development, that they are part and parcel of the processes suggested by S. Roberts and H. Pashler, and that they must be the starting point (though far from the ending point) in theoretical development. The authors discuss historical examples of scientific theory development, recent examples of psychological theory development, and development of a particular theory (social contagion theory; J. L. Rodgers & D. C. Rowe, 1993) that S. Roberts and H. Pashler criticized.

Does education mediate the relationship between IQ and age of first birth? A behavioural genetic analysis.

This study presents a multivariate behavioural genetic analysis of the relationship between education, intelligence and age of first birth. Analyses investigated the mediational role of education in explaining the relationship between intelligence and age of first birth at both the phenotypic and behavioural genetic level. The data come from the National Longitudinal Survey of Youth (NLSY), a nationally representative survey that included genetically informative full- and half-sibling pairs (n = 1423 pairs). Respondents were aged 14 to 22 when contacted in 1979. Heritability estimates were 0.32, 0.50 and 0.06 for IQ, education and age of first birth, respectively. Shared environment estimates were 0.35, 0.23 and 0.20 respectively. Common genetic and shared environmental factors were substantial in explaining the relationship between intelligence and education, and also education and age of first birth. Education partially mediated the relationship between intelligence and age of first birth only in the phenotypic analyses. After considering the genetic and shared environmental factors that influence all three variables, evidence for mediation was less convincing. This pattern of results suggests that the apparent mediational role of education at the phenotypic level is in fact the result of underlying genetic and shared environmental influences that affect education, IQ and age of first birth in common.