Behavior Genetics最新文献

Mendelian Randomization (MR) has become an important tool for causal inference in the health sciences. It takes advantage of the random segregation and independent assortment of alleles to control for background confounding factors. In brief, the method works by using genetic variants as instrumental variables, but it depends on the assumption of exclusion restriction, i.e., that the variants affect the outcome exclusively via the exposure variable. Equivalently, the assumption states that there is no horizontal pleiotropy from the variant to the outcome, i.e., no association with the outcome except via the exposure. This assumption is unlikely to hold in nature, so several MR extensions have been developed to increase its robustness against horizontal pleiotropy, though not eliminating the problem entirely (Sanderson et al., in Nat Rev Methods Primer 2:6, 2022). The Direction of Causation (DoC) twin model, which includes information from cross-twin cross-trait correlations to estimate causal paths, was extended with polygenic scores to explicitly model horizontal pleiotropy and a causal path (MR-DoC, Minică et al., in: Behav Genet 48:337-349, 2018). MR-DoC was further extended to accommodate bidirectional causation (MR-DoC2; Castro-de-Araujo et al., in: Behav Genet 53:63-73, 2023). In the present paper, we compared the performance of the DoC, MR-DoC, and MR-DoC2 models to evaluate the effects of phenotypic measurement error, potential unshared (individual-specific) environmental confounding, and statistical power across the three models. It was found that MR-DoC2 is less vulnerable to measurement error than is standard DoC or MR-DoC. The latter two models have biased estimates of causal paths when unshared environmental covariance between exposure and outcome is assumed to be absent.

Past research indicates that genetic and environmental sources contribute to Right-Wing Authoritarianism (RWA) and Social Dominance Orientation (SDO). However, less is known about the differences between the sources of variance in RWA and SDO, and how these sources differ across different developmental stages. Based on data from 1440 twin families, including 1198 complete twin pairs, 435 non-twin full siblings, and 2016 parents of twins from the German TwinLife project, nuclear twin family modeling was used to estimate different genetic and environmental variance components of RWA and SDO, and to examine the extent to which the variance components vary across three age cohorts of twins (average age 15, 21, and 27 years). We hypothesized increasing levels of genetic variance across age cohorts, reflecting more active genotype-environment transactions with development, and declining levels of passive genotype-environment correlation (rGE). The model analyses yielded additive and nonadditive genetic factors as well as influences shared in families due to non-genetic intergenerational transmission from parents to offspring and significant passive rGE for RWA. For SDO, passive rGE components, nonadditive genetic components and non-genetic intergenerational transmission were negligible. However, significant individual environmental sources and those only shared by twins were found for both RWA and SDO. Inconsistent with our expectations, passive rGE and genetic variance did not vary significantly across age cohorts. Counterintuitively, the influence of twin-specific shared environmental factors on RWA was larger in adulthood than adolescence, suggesting increasingly relevant environmental influences across developmental periods. These results have important implications for socio-developmental theories on socio-political attitudes.

Suicidal thoughts and behaviors (STBs) represent a significant public health concern. This study aimed to examine the extent to which polygenic risk scores (PRSs) for suicide attempt and major depression (MD) explain variance in suicidal ideation, plans, and attempts among young adult twins. Data from 2876 participants of European ancestry in the Brisbane Longitudinal Twin Study were analyzed. PRSs for MD and suicidal behavior (SB PRS) were calculated. Multivariate twin modeling was used to estimate genetic and environmental influences on DSM-IV Major Depressive Disorder (MDD) diagnosis and STBs, as well as their associations with PRSs. Heritability estimates were higher for STB phenotypes (51-80%) compared to DSM-IV MDD (39-41%). The MD PRS showed more consistent genetic correlations with DSM-IV MDD, while both PRSs showed modest correlations with suicide outcomes. Multivariate analyses revealed remarkably high genetic correlations among STBs (rA = 0.85-0.99) and moderate genetic correlations with MDD (rA = 0.48-0.65). Environmental factors contributing to DSM-IV MDD risk were largely distinct from those influencing suicide-related phenotypes. This study provided compelling evidence for shared genetic architecture between DSM-IV MDD and STBs. The MD PRS demonstrated more consistent prediction of MDD compared to the SB PRS, though both showed modest correlations with suicide outcomes. These results have important implications for risk assessment strategies, though the substantial unique environmental influences highlight the need to address modifiable environmental risk factors. Future research should focus on replication in larger, more diverse samples and exploring the interactions between genetic risk factors and environmental influences across the lifespan.

Globally, most children and adolescents live in low- and middle-income (LAMI) countries. Despite the high and under-recognized mental health burden in these settings, there is little systematic research to inform cost-effective mental health interventions. Identifying causal risk and protective mechanisms is important to inform such interventions. Longitudinal genetically informative designs can help identify potentially causal environmental mechanisms in the etiology of childhood psychopathology but few have been carried out in LAMI settings. We tested the feasibility of a twin-family study in a semi-urban setting in South-Western Nigeria. We recruited 320 family units, each comprising at least one parent and both twins aged 2.5-5.9 (x̄ = 4.0 ± 0.92) years from two towns using five strategies: direct and indirect contacts, radio adverts, cluster sampling (based on local administrative units) and snowball sampling. Participants were asked about their willingness to participate in future research including providing biological samples. These were supplemented with participant engagement activities before and after data collection. Snowball sampling was the most effective strategy while cluster sampling was the least effective (recruiting 46.3% and 8.3% of participants, respectively). Direct contacts and cluster sampling appeared prone to excluding under-represented participants. A large proportion of the participants (98-99%) were willing to participate in future studies. Challenges included grant administration (finance and ethical priorities) and desirability bias. Twin research is feasible in LAMI sub-Saharan Africa, with snowball sampling being an efficient means of recruiting a diverse sample. Participant involvement and engagement is useful to inform the execution of genetically-informative research in a LAMI context.

Reducing sugar intake is a key component of global health policies and dietary guidelines. However, individuals vary substantially in sweet-liking, commonly characterized by sweet-liking status (extreme sweet-likers, moderate sweet-likers, and sweet-dislikers), yet the heritability of these categories remains unexplored. Monozygotic and dizygotic twins from Finland (FinnTwin12; n = 468; 60% female, aged 21-24) and the UK (TwinsUK; n = 967; 90% female, aged 18-81) rated their liking and perceived intensity of a 20% (w/v) sucrose solution, reported their liking and consumption-frequency of food and beverages and completed additional behavioral, eating and personality measures. We estimated the contribution of additive genetic (A), nonadditive genetic (D), shared (C), and unshared environmental factors (E) in the variance and covariance of sweet-liking (defined ordinally through sweet-liking status and continuously) with related traits to see if they share similar proportions of genetic and environmental factors. Model-fitting indicated 30-48% of the variability in sweet-liking was attributed to (A) additive genetic factors and 52-70% to (E) environmental exposures not shared by siblings. Importantly, such AE models consistently fit best, regardless of sex, cohort, or sweet-liking assessment method. Broadly, correlations between sweet-liking and behavioral, eating, and personality measures were modest (-0.19 to 0.21), mostly positive and largely driven by shared genetic rather than environmental factors, with the strongest relationship seen for reported liking, consumption-frequency and craving for sweet foods. We demonstrate that unshared environment modulates individual differences in sweet-liking alongside a substantial genetic component that is partly shared with reported liking, consumption-frequency and craving for sweet foods.