Behavior Genetics最新文献

Diverse tests of cognitive abilities correlate about 0.30 phenotypically and about 0.60 genetically. Their phenotypic overlap defines general cognitive ability (g), driven largely by genetic overlap. Consequently, much of our understanding of the genetic landscape of specific cognitive tests likely reflects g rather than the tests themselves. Removing this g-associated genetic variance will sharpen research on cognitive tests. Here, we use Genomic Structural Equation Modelling (Genomic SEM) to remove shared genetic variance among 12 diverse cognitive tests that capture verbal and nonverbal cognitive domains. We applied Genomic SEM to summary statistics from the largest genome-wide association studies of verbal tests (GenLang Consortium, five tests) and largely nonverbal tests (UK Biobank, seven tests) to chart the genetic landscape of the 12 tests independent of g as compared to uncorrected cognitive tests. We found that SNP heritabilities were nearly as high for the tests corrected for g as uncorrected: the average SNP heritability was 0.16 (SE = 0.02) for the uncorrected tests and 0.13 (SE = 0.02) for the tests corrected for g. Despite this, the genetic landscape of the cognitive tests transformed after controlling for genomic g. The matrix of positive genetic correlations for the cognitive tests (average 0.45) disappeared after g-correction, and some strong negative correlations emerged; for instance, Memory and Word (-0.72), Fluid and Symbol (-0.72), and Tower and Spelling (-0.79). The summary statistics for these g-corrected cognitive tests can be used by researchers to create polygenic scores that focus on the specificity of the tests.

This paper provides an overview of the most recent assessment, collected in early midlife, of the FinnTwin12 cohort, a population-based study of Finnish twins born in 1983-1987. The twins were invited to complete an online survey assessing a range of variables, including physical and mental health, alcohol use and problems, other substance use, and early midlife environments (e.g., parenthood). In total, 2,085 individuals (~ 40% of the original sample) completed the survey (551 complete twin pairs, 58.7% female, 37.3% monozygotic, M_age = 37.2 years, SD = 1.47 years, age range = 34-39 years). Individuals who participated were more likely to be female, monozygotic, and have higher parental education and less hyperactivity/impulsivity and aggression at age 12 when compared to individuals who were invited but did not participate. Parental alcohol misuse and the twins' alcohol use and misuse at age 14 were not related to study retention. Alcohol misuse in early midlife was positively associated with nicotine dependence, lifetime use of cannabis and other drugs, trauma exposure, and depressive symptoms, and negatively associated with physical health and having biological children. These new data expand upon the wealth of measures collected as part of previous assessments, expanding the scope of work on the etiology and correlates of alcohol misuse within a longitudinal, genetically-informed framework. In addition to these new survey measures, we are planning an in-person assessment to collect physiological measurements and conduct additional in-depth phenotyping on a subset of twins who have been more intensively studied over the years.

Previous research has supported the use of latent variables as the gold-standard in measuring executive function. However, for logistical reasons genome-wide association studies (GWAS) of executive function have largely eschewed latent variables in favour of singular task measures. As low correlations have traditionally been found between individual executive function (EF) tests, it is unclear whether these GWAS have truly been measuring the same construct. In this study, we addressed this question by performing a factor analysis on summary statistics from eleven GWAS of EF taken from five studies, using GenomicSEM. Models demonstrated a bifactor structure consistent with previous research, with factors capturing common EF and working memory- specific variance. Furthermore, the GWAS performed on this model identified 20 new genomic risk loci for common EF and 4 for working memory reaching genome-wide significance beyond what was found in the constituent GWAS, together resulting in 29 newly mapped EF genes. These results help to clarify the underlying genetic structure of EF and support the idea that EF GWAS are capable of measuring genetic variance related to latent EF constructs even when not using factor scores. Furthermore, they demonstrate that GenomicSEM can combine GWAS with divergent and non-ideal measures of the same phenotype to improve statistical power.

Tattooing has become increasingly common in recent decades, yet little is known regarding factors that influence tattoo behavior. Sources of influence will be important, for instance in aiding studies of long-term health effects. From the population-based Danish Twin Tattoo Cohort established in 2021, the study included 9,173 randomly selected twins born 1920-2004. Among these were 4,790 (52%) responders to a questionnaire on tattooing and lifestyle factors. There were 55% females, 22% were monozygotic twins, and the median age was 51 years. Shared influence of tattooing over time was assessed by comparing monozygotic and dizygotic twin pairs. Responders were population representative on sex, age, and lifestyle factors. The cumulative incidence of being tattooed before age 25 years increased markedly from 6% (95% CI: 4-7%) for males and 0% (0-1%) for females born in 1925-1960 to 30% (25-35%) for males and 41% (37-46%) for females born in 1981-2004. Tattooing was over twice as common among ever smokers compared to never smokers born in 1981-2004 (average smoking effect at age 25 years: 36% (29-43%)). The likelihood of a twin getting tattooed if the co-twin is tattooed, was 2.0 (1.4-2.6) and 1.8 (1.5-2.2) times higher, for monozygotic and dizygotic twins, respectively. The findings indicate that variation in the likelihood of becoming tattooed is primarily explained by shared environmental factors 65% (35-95%), and that genetic influences explained little of this variation. This study demonstrates that strong environmental exposures shared by twin siblings irrespective of degree of genetic relatedness drive the choice for getting tattooed. We conclude that tattooing is a cultural group clustering phenomenon that goes beyond genetically oriented behavioral characteristics.

Artificial selection yielded four replicate high runner (HR) lines of mice that reached apparent selection limits (~ threefold increase in wheel revolutions per day vs. four control lines), despite maintenance of additive genetic variance. After 68 generations, we used animal models to test for changes in additive-genetic variances and covariance of the two measured components (average speed and duration) of running distance. We also attempted to break the selection limit by crossing two HR lines, then continuing directional selection on this hybrid line and on the two parental lines for nine generations. The genetic correlation between speed and duration was positive in the base population, but evolved to be negative in the two parental HR lines. Although heritability for both speed and duration (but not distance) increased in the hybrid line, their genetic correlation remained negative. Hybrid F₁ mice from generation 68 parents showed heterosis for running distance, which was lost in subsequent generations, and the hybrid line did not exceed the limit. Both male and female hybrids ran faster than parental lines for most generations, but running duration was intermediate or reduced, reflecting their negative genetic correlation. The evolved genetic trade-off between speed and duration may explain the inability for the hybrid line to break the selection limit for distance run, despite renewed additive genetic variance for at least one of its component traits.

Attention Deficit Hyperactivity Disorder (ADHD) is a common and heritable neurodevelopmental condition that has been the subject of a wealth of genetics research. Because ADHD has an early age of onset, most of this work has focused on children, meaning that less is known about the genetics of ADHD in adults. Additionally, while much research has assessed the heritability of ADHD as a general dimension, less has assessed the heritability of individual subtypes (inattention, hyperactivity) or symptoms of ADHD. It therefore remains unclear whether the genetic factors underlying ADHD symptoms conform to a unidimensional or multidimensional structure. The aim of this study was to assess the genetic and environmental dimensionality of adult ADHD symptoms. We analyzed data from 10,454 twins of the Twins Early Development Study, who provided self-reports of ADHD symptoms using the Conners scale at age 21 years. The data conformed well to a psychometric bifactor model, providing support for a general dimension of ADHD in addition to secondary dimensions for inattention and hyperactivity. However, a bifactor independent pathway twin model provided support for a general dimension only at the level of non-shared environmental effects and not additive genetic or shared environmental effects. This suggests that symptoms of ADHD cluster together under a general dimension of non-shared environmental effects, although the two subtypes of ADHD (inattention and hyperactivity) are meaningfully genetically distinct. We found the overall heritability of ADHD to be 40%, comparable with previous estimates for adult ADHD symptoms. Our results provide useful insights into the genetic and environmental architecture of specific ADHD symptoms.

Education-related variables are positively associated with intelligence in both causal directions, but little is known about the associations' underlying genetically and environmentally intertwined processes and many 'third variables' are probably involved too. In this study, we investigated how school achievement, measured by grade point average (GPA), moderated intelligence test score variation in young adulthood in broadly representative samples from the U.S. state of Minnesota, Denmark, and Germany, attempting to improve both understanding of the importance of environmental contexts and the limitations of currently available modelling techniques to help remedy them. School achievement was positively associated with intelligence test scores in all three contexts, but it moderated variances differently, even within the two cohorts comprising the Minnesota sample. One Minnesota cohort and the German sample suggested that shared environmental variance was larger among individuals with extreme GPAs, while the Danish sample suggested that this was only true among individuals with low GPAs. In contrast to these observations, the other Minnesota cohort suggested that genetic and non-shared environmental variances were greater among individuals with high GPAs. These observations indicated that underlying individual developmental processes and population-level impacts differed. However, our statistical models did not capture these differences clearly. The ways in which they failed all suggested the model limitations involve an inability to address degrees to which environmental constraints restrain social movements that are confounded with individual variations in capacities to move within society.

Causal inference is inherently complex and relies on key assumptions that can be difficult to validate. One strong assumption is population homogeneity, which assumes that the causal direction remains consistent across individuals. However, there may be variation in causal directions across subpopulations, leading to potential heterogeneity. In psychiatry, for example, the co-occurrence of disorders such as depression and substance use disorder can arise from multiple sources, including shared genetic or environmental factors (common causes) or direct causal pathways between the disorders. A patient diagnosed with two disorders might have one recognized as primary and the other as secondary, suggesting the existence of different types of comorbidity. For example, in some individuals, depression might lead to substance use, while in others, substance use could lead to depression. We account for potential heterogeneity in causal direction by integrating the Direction of Causation (DoC) model for twin data with finite mixture modeling, which allows for the calculation of individual-level likelihoods for alternate causal directions. Through simulations, we demonstrate the effectiveness of using the Direction of Causation Twin Mixture (mixDoC) model to detect and model heterogeneity due to varying causal directions.

Experimental evolution is a powerful approach to study the mechanisms underlying the adaptation of selected characters under the conditions chosen in the laboratory. Drosophila melanogaster is a species frequently used to investigate the experimental evolution of characters, especially those related to reproduction. Recent intra-generational studies showed that cis-vaccenyl acetate (cVa), a sex pheromone transferred with bacteria on eggs by females either 1 day (D1) or 5 days (D5) after copulation, differentially affected the behavior and pheromone release in adult males emerging from these eggs. Here, we extended this finding to determine whether this alternative egg exposure repeated over many generations could affect a larger set of reproduction-related characters in both sexes. To test the repetitive effects of maternal D1 or D5 post-copulatory factors, we carried out an experimental selection procedure consisting of exposing eggs during 40 successive generations to D1 or D5 maternal post-copulatory factors. We compared cVa and cuticular pheromones, courtship and mating behaviors, and fecundity at different generations in flies of D1 and D5 lines. Based on findings obtained at earlier generations, we also determined survival, bacterial composition and gene expression in adults. Some of these complex traits significantly diverged between D1 and D5 lines indicating that maternal post-copulatory factors transmitted to eggs can influence adult life history traits.

We aimed to understand the long-term impact of negative life events on epigenetic aging in 1783 adults from the Netherlands Twin Register, analyzing five epigenetic biomarkers (Hannum, Horvath, PhenoAge, GrimAge, DunedinPACE) and a series of negative life events, including victimization and economic hardship. In population-level analyses, associations between a higher number of negative life events (particularly financial adversities, sexual crimes, and job loss) were seen for the GrimAge biomarker. The association between the number of negative life events and financial problems and epigenetic age acceleration measured by the GrimAge biomarker persisted after adjusting for BMI, smoking, and white blood cell counts. In monozygotic twin pairs discordant for negative life events (263 pairs) the associations were diminished, indicating that the population associations may be confounded by shared familial (genetic and environmental) factors. These findings underscore the intricate link between environmental stressors and biological aging, stressing the need for comprehensive studies considering both genetic and environmental influences.