This study investigates the degree to which internalizing disorders (anxiety and mood disorders) are prospectively associated with sick leave granted for mental and somatic disorders, and the extent to which common genetic and environmental risk factors influence these relationships. Data include self-reported symptoms of psychological distress from 7,598 young adult twins and diagnostic interviews on a subsample of 2,766 adult twins, subsequently linked to registry data on sick leave. Regression analyses and multivariate twin models were used to investigate the relationship between internalizing disorders and sick leave. Internalizing disorders were associated with sick leave granted for both mental disorders and somatic disorders. The association between internalizing disorders and sick leave granted for mental disorders was influenced by genetic and non-shared environmental factors, while the association between internalizing disorders and sick leave granted for somatic disorders could be explained by common genetic factors alone. Monozygotic twins discordant for internalizing disorders differed significantly in rates of sick leave granted for mental but not somatic disorders. In conclusion, internalizing disorders in young adults predict sick leave granted for both mental and somatic disorders. Environmental risk factors for internalizing disorders seem to influence sick leave granted for mental disorders, but not sick leave granted for somatic disorders.

In order to further understand why depressive symptoms are associated with negative goal appraisals, the present study examined the genetic and environmental correlations and interactions between depressive symptoms and career-related goal appraisals. A total of 1,240 Finnish twins aged 21–26 years completed a questionnaire containing items on the appraisal of their career goals along five dimensions: importance, progress, effort, strain, and self-efficacy. In the same questionnaire, the 10-item General Behavior Inventory assessed depressive symptoms. Structural equation modeling was used to evaluate the genetic and environmental correlations and gene–environment interactions between the career-goal appraisals and depressive symptoms. Associations were identified, and were attributed to environmental factors. Of the career-related goal appraisals, the shared environmental component was of a higher magnitude for the dimension of strain among the depressed compared with non-depressed subjects. The results indicate that the interplay between depressive symptoms and negative career-related goal appraisals is significantly affected by environmental factors, and thus possibly susceptible to targeted interventions.

It is unknown whether there are racial differences in the heritability of major depressive disorder (MDD) because most psychiatric genetic studies have been conducted in samples comprised largely of white non-Hispanics. To examine potential differences between African-American (AA) and European-American (EA) young adult women in (1) Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) MDD prevalence, symptomatology, and risk factors, and (2) genetic and/or environmental liability to MDD, we analyzed data from a large population-representative sample of twins ascertained from birth records (n = 550 AA and n = 3226 EA female twins) aged 18–28 years at the time of MDD assessment by semi-structured psychiatric interview. AA women were more likely to have MDD risk factors; however, there were no significant differences in lifetime MDD prevalence between AA and EA women after adjusting for covariates (odds ratio = 0.88, 95% confidence interval [CI]: 0.67–1.15). Most MDD risk factors identified among AA women were also associated with MDD at similar magnitudes among EA women. Although the MDD heritability point estimate was higher among AA women than EA women in a model with paths estimated separately by race (56%, 95% CI: 29–78% vs. 41%, 95% CI: 29–52%), the best fitting model was one in which additive genetic and non-shared environmental paths for AA and EA women were constrained to be equal (A = 43%, 33–53% and E = 57%, 47–67%). In spite of a marked elevation in the prevalence of environmental risk exposures related to MDD among AA women, there were no significant differences in lifetime prevalence or heritability of MDD between AA and EA young women.

Low weight at birth has previously been shown to be associated with a number of adult diseases such as type 2 diabetes, cardiovascular disease, high blood pressure, and obesity later in life. Genome-wide association studies (GWAS) have been published for singleton-born individuals, but the role of genetic variation in birth weight (BW) in twins has not yet been fully investigated. A GWAS was performed in 4,593 female study participants with BW data available from the TwinsUK cohort. A genome-wide significant signal was found in chromosome 9, close to the NTRK2 gene (OMIM: 600456). QIMR, an Australian twin cohort (n = 3,003), and UK-based singleton-birth individuals from the Hertfordshire cohort (n = 2,997) were used as replication for the top two single nucleotide polymorphism (SNPs) underpinning this signal, rs12340987 and rs7849941. The top SNP, rs12340987, was found to be in the same direction in the Australian twins and in the singleton-born females (fixed effects meta-analysis beta = -0.13, SE = 0.02, and p = 1.48 × 10−8) but not in the singleton-born males tested. These findings provide an important insight into the genetic component of BW in twins who are normally excluded due to their lower BW when compared with singleton births, as well as the difference in BW between twins. The NTRK2 gene identified in this study has previously been associated with obesity.

Studies on the determinants of physical activity have traditionally focused on social factors and environmental barriers, but recent research has shown the additional importance of biological factors, including genetic variation. Here we review the major tenets of this research to arrive at three major conclusions: First, individual differences in physical activity traits are significantly influenced by genetic factors, but genetic contribution varies strongly over age, with heritability of leisure time exercise behavior ranging from 27% to 84% and heritability of sedentary behaviors ranging from 9% to 48%. Second, candidate gene approaches based on animal or human QTLs or on biological relevance (e.g., dopaminergic or cannabinoid activity in the brain, or exercise performance influencing muscle physiology) have not yet yielded the necessary evidence to specify the genetic mechanisms underlying the heritability of physical activity traits. Third, there is significant genetic modulation of the beneficial effects of daily physical activity patterns on strength and endurance improvements and on health-related parameters like body mass index. Further increases in our understanding of the genetic determinants of sedentary and exercise behaviors as well as the genetic modulation of their effects on fitness and health will be key to meaningful future intervention on these behaviors.

Epistasis is a growing area of research in genome-wide studies, but the differences between alternative definitions of epistasis remain a source of confusion for many researchers. One problem is that models for epistasis are presented in a number of formats, some of which have difficult-to-interpret parameters. In addition, the relation between the different models is rarely explained. Existing software for testing epistatic interactions between single-nucleotide polymorphisms (SNPs) does not provide the flexibility to compare the available model parameterizations. For that reason we have developed an R package for investigating epistatic and penetrance models, Epi2Loc, to aid users who wish to easily compare, interpret, and utilize models for two-locus epistatic interactions. Epi2Loc facilitates research on SNP–SNP interactions by allowing the R user to easily convert between common parametric forms for two-locus interactions, generate data for simulation studies, and perform power analyses for the selected model with a continuous or dichotomous phenotype. The usefulness of the package for model interpretation and power analysis is illustrated using data on rheumatoid arthritis.

Our goal was to estimate genetic and environmental sources of influence on adolescent problematic internet use, and whether these individual differences can be explained by effortful control, an important aspect of self-regulation. A sample of 825 pairs of Chinese adolescent twins and their parents provided reports of problematic internet use and effortful control. Univariate analysis revealed that genetic factors explained 58–66% of variance in problematic internet use, with the rest explained by non-shared environmental factors. Sex difference was found, suggesting boys’ problematic internet use was more influenced by genetic influences than girls’ problematic internet use. Bivariate analysis indicated that effortful control accounted for a modest portion of the genetic and non-shared environmental variance in problematic internet use among girls. In contrast, among boys, effortful control explained between 6% (parent report) and 20% (self-report) of variance in problematic internet use through overlapping genetic pathways. Adolescent problematic internet use is heritable, and poor effortful control can partly explain adolescent problematic internet use, with effects stronger for boys. Implications for future research are discussed.

The hypothesis that twinning raises risk for behavioral difficulties in childhood is persistent, yet there is limited and inconsistent empirical evidence. Simple mean comparison without control for confounders provides data on prevalence rates but cannot provide knowledge about risk or etiology. To assess the effect of twin relationship on behavior, comparison of patterns of association with single-born siblings may be informative. Analyses of data from an Australian sample of twins and single-born children (N = 305, mean age 4 years 9 months, and a follow-up 12 months later) were undertaken. The outcome measure was the Strengths and Difficulties Questionnaire. Predictor and control measures were obtained from parent report on the sibling/co-twin relationship behavior, family demographics, and obstetric history. We assessed difference between twins and single-born children in two respects: (a) mean behavioral difficulties, and (b) patterns of association between sibling relationship and behavioral difficulties, controlling for confounders. Results showed no differences in mean levels of behavioral difficulties between twins and single-born siblings identifying the importance of statistical control for family and obstetric adversity. Differences in patterns of association were found; for twin children, conflict in their co-twin relationship predicted externalizing behaviors, while for single-born children conflict predicted internalizing behaviors. The findings of mean differences between twin and single-born children in social background, but not in behavioral difficulties, underscore the necessity of statistical control to identify risk associated with twinning compared with risk associated with family and obstetric background factors.

I was part of a people-to-people tour of Havana, Cuba during the first week in April 2014. Among the many highlights of that adventure were an informal meeting with Dr Beatriz Marcheco-Teruel, from Cuba's National Center for Medical Genetics, and a visit to the famous ‘Street of Twins’. A fortuitous meeting with parents of twins in the fishing town of Jaimanitas was also an extraordinary event. The Cuban experience is followed by summaries of recent twin research, covering umbilical cord entanglement, the heritability of clubfoot and school separation policies for twins. Media reports include twins reunited at age 78, the future of UCLA's twin basketball players, MZ twins born holding hands, a twin conflict over beer and a pair of American Psychological Association honors for Drs Nancy L. Segal and Thomas J. Bouchard, Jr.

Epistasis is a growing area of research in genome-wide studies, but the differences between alternative definitions of epistasis remain a source of confusion for many researchers. One problem is that models for epistasis are presented in a number of formats, some of which have difficult-to-interpret parameters. In addition, the relation between the different models is rarely explained. Existing software for testing epistatic interactions between single-nucleotide polymorphisms (SNPs) does not provide the flexibility to compare the available model parameterizations. For that reason we have developed an R package for investigating epistatic and penetrance models, EpiPen, to aid users who wish to easily compare, interpret, and utilize models for two-locus epistatic interactions. EpiPen facilitates research on SNP-SNP interactions by allowing the R user to easily convert between common parametric forms for two-locus interactions, generate data for simulation studies, and perform power analyses for the selected model with a continuous or dichotomous phenotype. The usefulness of the package for model interpretation and power analysis is illustrated using data on rheumatoid arthritis.