Behavior Genetics最新文献

We tested the directionality of associations between children’s early-life cognitive development and the cognitive stimulation that they received from their parents. Our sample included up to 15,314 children from the Twins Early Development Study (TEDS), who were born between 1994 and 1996 in England and Wales and assessed at ages 3 and 4 years on cognitive development and cognitive stimulation, including singing rhymes, reading books, and playing games. Using genetically informative cross-lagged models, we found consistent, bidirectional effects from cognitive development at age 3 to cognitive stimulation at age 4, and from cognitive stimulation at age 3 to cognitive development at age 4. These cross-lagged longitudinal effects were largely explained by underlying common genetic and shared environmental factors, rather than reflecting causal mechanisms. Our findings emphasize the active role that children play in constructing their own learning experiences.

Although the impact of occupation on cognitive skills has been extensively studied, there is limited research examining if genetically predicted cognitive score may influence occupation. We examined the association between Cognitive Polygenic Index (PGI) and occupation, including the role of brain measures. Participants were recruited for the Reference Ability Neural Network and the Cognitive Reserve studies. Occupational complexity ratings for Data, People, or Things came from the Dictionary of Occupational Titles. A previously-created Cognitive PGI and linear regression models were used for the analyses. Age, sex, education, and the first 20 genetic Principal Components (PCs) of the sample were covariates. Total cortical thickness and total gray matter volume were further covariates. We included 168 white-ethnicity participants, 20-80 years old. After initial adjustment, higher Cognitive PGI was associated with higher Data complexity (B=-0.526, SE = 0.227, Beta= -0.526 p = 0.022, R² = 0.259) (lower score implies higher complexity). Associations for People or Things were not significant. After adding brain measures, association for Data remained significant (B=-0.496, SE: 0.245, Beta= -0.422, p = 0.045, R² = 0.254). Similarly, for a further, fully-adjusted analysis including all the three occupational complexity measures (B=-0.568, SE = 0.237, Beta= -0.483, p = 0.018, R² = 0.327). Cognitive genes were associated with occupational complexity over and above brain morphometry. Working with Data occupational complexity probably acquires higher cognitive status, which can be significantly genetically predetermined.

The roles of brain asymmetry in Drosophila are diverse, encompassing the regulation of behavior, the creation of memory, neurodevelopment, and evolution. A comprehensive examination of the Drosophila brain has the potential to enhance our understanding of the functional significance of brain asymmetry in cognitive and behavioral processes, as well as its role in evolutionary perspectives. This study explores the influence of brain asymmetry on interval timing behaviors in Drosophila, with a specific focus on the asymmetric body (AB) structure. Despite being bilaterally symmetric, the AB exhibits functional asymmetry and is located within the central complex of the fly brain. Interval timing behaviors, such as rival-induced prolonged mating duration: longer mating duration behavior (LMD) and sexual experience-mediated shorter mating duration behavior (SMD), are essential for Drosophila. We utilize genetic manipulations to selectively activate or inhibit AB neurons and evaluates their impact on LMD and SMD behaviors. The results indicate that specific populations of AB neurons play unique roles in orchestrating these interval timing behaviors. Notably, inhibiting GAL4^R38D01-labeled AB neurons disrupts both LMD and SMD, while GAL4^R42C09 neuron inhibition affects only LMD. Moreover, hyperexcitation of GAL4^R72A10-labeled AB neurons perturbs SMD. Our study identifies NetrinB (NetB) and Abdominal-B (Abd-B) are important genes for AB neurons in LMD and highlights the role of 5-HT1B neurons in generating LMD through peptidergic Pigment-dispersing factor (PDF) signaling. In summary, this study underscores the importance of AB neuron asymmetry in mediating interval timing behaviors and provides insights into the underlying mechanisms of memory formation and function in Drosophila.

Externalizing behaviors encompass manifestations of risk-taking, self-regulation, aggression, sensation-/reward-seeking, and impulsivity. Externalizing research often includes substance use (SUB), substance use disorder (SUD), and other (non-SUB/SUD) "behavioral disinhibition" (BD) traits. Genome-wide and twin research have pointed to overlapping genetic architecture within and across SUB, SUD, and BD. We created single-factor measurement models-each describing SUB, SUD, or BD traits-based on mutually exclusive sets of European ancestry genome-wide association study (GWAS) statistics exploring externalizing variables. We then assessed the partitioning of genetic covariance among the three facets using correlated factors models and Cholesky decomposition. Even when the residuals for indicators relating to the same substance were correlated across the SUB and SUD factors, the two factors yielded a large correlation (r_g = 0.803). BD correlated strongly with the SUD (r_g = 0.774) and SUB (r_g = 0.778) factors. In our initial decompositions, 33% of total BD variance remained after partialing out SUD and SUB. The majority of covariance between BD and SUB and between BD and SUD was shared across all factors, and, within these models, only a small fraction of the total variation in BD operated via an independent pathway with SUD or SUB outside of the other factor. When only nicotine/tobacco, cannabis, and alcohol were included for the SUB/SUD factors, their correlation increased to r_g = 0.861; in corresponding decompositions, BD-specific variance decreased to 27%. Further research can better elucidate the properties of BD-specific variation by exploring its genetic/molecular correlates.

Regular cigarette smoking and cannabis consumption are strongly positively related to each other, yet few studies explore their underlying variation and covariation. We evaluated the genetic and environmental decomposition of variance and covariance of these two traits in twin data from three countries with different social norms and legislation. Data from the Netherlands Twin Register, FinnTwin12/16, and the Minnesota Center for Twin Family Research (total N = 21,617) were analyzed in bivariate threshold models of lifetime regular smoking initiation (RSI) and lifetime cannabis initiation (CI). We ran unstratified models and models stratified by sex and country. Prevalence of RSI was lowest in the Netherlands and prevalence of CI was highest in Minnesota. In the unstratified model, genetic (A) and common environmental factors (C) contributed substantially to the liabilities of RSI (A = 0.47, C = 0.34) and CI (A = 0.28, C = 0.51). The two liabilities were significantly phenotypically (rP = 0.56), genetically (rA = 0.74), and environmentally correlated in the unstratified model (rC = 0.47and rE = 0.48, representing correlations between common and unique environmental factors). The magnitude of phenotypic correlation between liabilities varied by country but not sex (Minnesota rP ~ 0.70, Netherlands rP ~ 0.59, Finland rP ~ 0.45). Comparisons of decomposed correlations could not be reliably tested in the stratified models. The prevalence and association of RSI and CI vary by sex and country. These two behaviors are correlated because there is genetic and environmental overlap between their underlying latent liabilities. There is heterogeneity in the genetic architecture of these traits across country.

Co-twin studies are an elegant and powerful design that allows controlling for the effect of confounding variables, including genetic and a range of environmental factors. There are several approaches to carry out this design. One of the methods commonly used, when contrasting continuous variables, is to calculate difference scores between members of a twin pair on two associated variables, in order to analyse the covariation of such differences. However, information regarding whether and how the different ways of estimating within-pair difference scores may impact the results is scant. This study aimed to compare the results obtained by different methods of data transformation when performing a co-twin study and test how the magnitude of the association changes using each of those approaches. Data was simulated using a direction of causation model and by fixing the effect size of causal path to low, medium, and high values. Within-pair difference scores were calculated as relative scores for diverse within-pair ordering conditions or absolute scores. Pearson's correlations using relative difference scores vary across the established scenarios (how twins were ordered within pairs) and these discrepancies become larger as the within-twin correlation increases. Absolute difference scores tended to produce the lowest correlation in every condition. Our results show that both using absolute difference scores or ordering twins within pairs, may produce an artificial decrease in the magnitude of the studied association, obscuring the ability to detect patterns compatible with causation, which could lead to discrepancies across studies and erroneous conclusions.

We investigate natural selection on polygenic scores in the contemporary US, using the Health and Retirement Study. Across three generations, scores which correlate negatively (positively) with education are selected for (against). However, results only partially support the economic theory of fertility as an explanation for natural selection. The theory predicts that selection coefficients should be stronger among low-income, less educated, unmarried and younger parents, but these predictions are only half borne out: coefficients are larger only among low-income parents and unmarried parents. We also estimate effect sizes corrected for noise in the polygenic scores. Selection for some health traits is similar in magnitude to that for cognitive traits.

Retraining retired racehorses for various purposes can help correct behavioral issues. However, ensuring efficiency and preventing accidents present global challenges. Based on the hypothesis that a simple personality assessment could help address these challenges, the present study aimed to identify genetic markers associated with personality. Eight genes were selected from 18 personality-related candidate genes that are orthologs of human personality genes, and their association with personality was verified based on actual behavior. A total of 169 Thoroughbred horses were assessed for their tractability (questionnaire concerning tractability in 14 types of situations and 3 types of impressions) during the training process. Personality factors were extracted from the data using principal component analysis and analyzed for their association with single nucleotide variants as non-synonymous substitutions in the target genes. Three genes, CDH13, SLC6A4, and MAOA, demonstrated significant associations based on simple linear regression, marking the identification of these genes for the first time as contributors to temperament in Thoroughbred horses. All these genes, as well as the previously identified HTR1A, are involved in the serotonin neurotransmitter system, suggesting that the tractability of horses may be correlated with their social personality. Assessing the genotypes of these genes before retraining is expected to prevent problems in the development of a racehorse's second career and shorten the training period through individual customization of training methods, thereby improving racehorse welfare.