Psychiatry

The primary assumption within the recent personality and political orientations literature is that personality traits cause people to develop political attitudes. In contrast, research relying on traditional psychological and developmental theories suggests the relationship between most personality dimensions and political orientations are either not significant or weak. Research from behavioral genetics suggests the covariance between personality and political preferences is not causal, but due to a common, latent genetic factor that mutually influences both. The contradictory assumptions and findings from these research streams have yet to be resolved. This is in part due to the reliance on cross-sectional data and the lack of longitudinal genetically informative data. Here, using two independent longitudinal genetically informative samples, we examine the joint development of personality traits and attitude dimensions to explore the underlying causal mechanisms that drive the rel...

Twin and family studies implicitly assume that the covariation between family members remains constant across differences in age between the members of the family. However, age-specificity in gene expression for shared environmental factors could generate higher correlations between family members who are more similar in age. Cohort effects (cohort × genotype or cohort × common environment) could have the same effects, and both potentially reduce effect sizes estimated in genome-wide association studies where the subjects are heterogeneous in age. In this paper we describe a model in which the covariance between twins and non-twin siblings is moderated as a function of age difference. We describe the details of the model and simulate data using a variety of different parameter values to demonstrate that model fitting returns unbiased parameter estimates. Power analyses are then conducted to estimate the sample sizes required to detect the effects of moderation in a design of twins a...

This chapter examines issues in studying the heritability of tobacco use behavior and trajectories and their methodological implications for future genetic research in nicotine dependence. Its goal is to follow the discussion of tobacco use trajectories in chapter 5 to examine what can be learned about these trajectories through studies using genetically informed data.

Abstract Neale and Kendler (1995, Am J Hum Genet 57: 935–953) described 13 comorbidity models, providing the most comprehensive set of alternative hypotheses regarding the possible causes of comorbidity to date. This research note describes an extension of the Neale and Kendler model fitting approach that permits the inclusion of measured covariates. An example of 13 models examining the comorbidity between alcohol dependence and illicit drug dependence is presented.

Comparative ratings between pairs of siblings or other relatives are commonly used to refine measures of intrafamily variation. A simple model, based on signal detection theory, is proposed which shows how comparative ratings can be used to estimate within-pair variances of true scores, which can, in turn, be modeled with any of the conventional approaches to partitioning genetic and environmental variance within families.

Abstract: Religious attendance has been shown to correlate negatively with alcoholuse. We investigated whether this relationship is driven by genetic orenvironmental factors. Data on frequency of church attendance and frequencyof alcohol use were obtained from twins and their families in the Virginia30 000 study. A comprehensive bivariate model of family resemblance wasfitted to the data using Mx. This model is described in detail.

BACKGROUND: Knowledge regarding the causes of comorbidity among substance use disorders can have significant impact on future research examining the etiology of these disorders. Unfortunately, the conclusions of past studies examining the comorbidity among substance use disorders are conflicting; some studies emphasize familial influences common to multiple substances, while others emphasize substance-specific influences.

Background. Although an obvious environmental factor influencing drug use, the sources of individual differences in drug availability (DA) are unknown. Method. This report is based on 1788 adult males from the Mid-Atlantic Twin Registry who participated in a structured telephone interview that included retrospective assessments of DA (cigarette, alcohol, marijuana, cocaine and stimulants) between ages 8 and 25.

Modern structural equation modeling (SEM) software programs include user interfaces for the entry of graphical diagrams as a method for the production of the underlying matrixes that are then manipulated in traditional ways to provide parameter estimates and fit statistics. This work presents an algorithm for the solution of the problem in the reverse order: automatically producing a graphical diagram from a matrix formula in such a way that its components are logically and hierarchically arranged.

The contribution of size 3 and size 4 sibships to power in covariance structure modeling of a codominant QTL is investigated. Power calculations are based on the noncentral chi-square distribution. Sixteen sets of parameter values are considered. Results indicate that size 3 and size 4 sibships provided large increases in power over size 2 sibships. On average a size 3 (4) sibship is 3 (6 to 7) times as informative as a size 2 sibship.