Genetic Influences on the Covariance and Genetic Correlations in a Bivariate Twin Model: An Application to Well-Being

Twin Data Support a Sensitive Period for Singing Ability

As with many other musical traits, the social environment is a key influence on the development of singing ability. While the familial singing environment is likely to be formative, its role relative to other environmental influences such as training is unclear. We used structural equation modeling to test relationships among demographic characteristics, familial environmental variables (early and current singing with family), vocal training, and singing ability in a large, previously documented sample of Australian twins (N = 1163). Notably, early singing with family, and to a lesser extent vocal training, predicted singing ability, whereas current singing with family did not. Early familial singing also mediated the relationship between sex and singing ability, with men who sang less with family during childhood showing poorer ability. Bivariate twin models between early familial singing and singing ability showed the phenotypic correlation was largely explained by shared environmental influences. This raises the possibility of a sensitive period for singing ability, with sociocultural expectations around singing potentially differentiating the developmental trajectories of this skill for men and women.

Sex Differences in the Etiology of Victimization in Adulthood

Until relatively recently, the study of victimization has been largely outside the purview of behavioral geneticists and evolutionary psychologists. Recent victimology research, however, has shown that genetic and evolutionary forces are connected to the risk of victimization. The current study expands on these findings by examining whether genetic influences differentially explain victimization in males and females. To do so, we use a sample of sibling pairs drawn from the National Longitudinal Study of Adolescent to Adult Health (Add Health; N = 4,244). The analyses revealed no significant quantitative sex differences in the etiology of adult victimization. However, the results of this study do highlight the importance of accounting for genetic factors when studying the etiology of specific types of adult victimization. We conclude by discussing the implications of the current study for future research.

Identifying the top predictors of student well-being across cultures using machine learning and conventional statistics

Alongside academic learning, there is increasing recognition that educational systems must also cater to students' well-being. This study examines the key factors that predict adolescent students' subjective well-being, indexed by life satisfaction, positive affect, and negative affect. Data from 522,836 secondary school students from 71 countries/regions across eight different cultural contexts were analyzed. Underpinned by Bronfenbrenner's bioecological theory, both machine learning (i.e., light gradient-boosting machine) and conventional statistics (i.e., hierarchical linear modeling) were used to examine the roles of person, process, and context factors. Among the multiple predictors examined, school belonging and sense of meaning emerged as the common predictors of the various well-being dimensions. Different well-being dimensions also had distinct predictors. Life satisfaction was best predicted by a sense of meaning, school belonging, parental support, fear of failure, and GDP per capita. Positive affect was most strongly predicted by resilience, sense of meaning, school belonging, parental support, and GDP per capita. Negative affect was most strongly predicted by fear of failure, gender, being bullied, school belonging, and sense of meaning. There was a remarkable level of cross-cultural similarity in terms of the top predictors of well-being across the globe. Theoretical and practical implications are discussed.

A genetically informed longitudinal study of early-life temperament and childhood aggression

The present study examined the longitudinal associations between three dimensions of temperament - activity, affect-extraversion, and task orientation - and childhood aggression. Using 131 monozygotic and 173 dizygotic (86 same-sex) twin pairs from the Louisville Twin Study, we elucidated the ages, from 6 to 36 months, at which each temperament dimension began to correlate with aggression at age 7. We employed latent growth modeling to show that developmental increases (i.e., slopes) in activity were positively associated with aggression, whereas increases in affect-extraversion and task orientation were negatively associated with aggression. Genetically informed models revealed that correlations between temperament and aggression were primarily explained by common genetic variance, with nonshared environmental variance accounting for a small proportion of each correlation by 36 months. Genetic variance explained the correlations of the slopes of activity and task orientation with aggression. Nonshared environmental variance accounted for almost half of the correlation between the slopes of affect-extraversion and aggression. Exploratory analyses revealed quantitative sex differences in each temperament-aggression association. By establishing which dimensions of temperament correlate with aggression, as well as when and how they do so, our work informs the development of future child and family interventions for children at highest risk of aggression.

Genetic and shared environmental factors explain the association between adolescent polysubstance use and high school noncompletion

OBJECTIVE

Examine the nature of the relationship between adolescent polysubstance use and high school noncompletion.

METHOD

Among a sample of 9,579 adult Australian twins (58.63% female, Mage = 30.59), we examined the association between the number of substances used in adolescence and high school noncompletion within a discordant twin design and bivariate twin analysis.

RESULTS

In individual-level models controlling for parental education, conduct disorder symptoms, childhood major depression, sex, zygosity, and cohort, each additional substance used in adolescence was associated with a 30% increase in the odds of high school noncompletion (OR = 1.30 [1.18, 1.42]). Discordant twin models found that the potentially causal effect of adolescent use on high school noncompletion was nonsignificant (OR = 1.19 [0.96, 1.47]). Follow-up bivariate twin models suggested genetic (35.4%, 95% CI [24.5%, 48.7%]) and shared environmental influences (27.8%, 95% CI [12.7%, 35.1%]) each contributed to the covariation in adolescent polysubstance use and early school dropout.

CONCLUSIONS

The association between polysubstance use and early school dropout was largely accounted for by genetic and shared environmental factors, with nonsignificant evidence for a potentially causal association. Future research should examine whether underlying shared risk factors reflect a general propensity for addiction, a broader externalizing liability, or a combination of the two. More evidence using finer measurement of substance use is needed to rule out a causal association between adolescent polysubstance use and high school noncompletion. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Gene-environment interplays between family chaos and emotional problems among Nigerian adolescents: A twin study

Gene-environment correlations and interactions for the relationship between emotional problems (EP) and family environment in adolescents in low- to middle-income countries (LMIC) have been rarely investigated. In total, 3207 adolescent twins aged 12-18 (Mean = 14.6 ± 1.73) years attending public schools in Lagos State in Nigeria completed measures of EP and Family Chaos (FC). Model-fitting analyses suggested that genetic and non-shared environmental influences on EP were 21% and 71%, respectively, and the corresponding estimates were 23% and 71% for FC. Shared environmental influences were not significant (8% and 6% respectively). Phenotypic correlation between EP and FC was .30 (95% CI = .27-.34), which was significantly influenced by genetic (A - 49%, 95% CI: 0.01-0.97) and non-shared environmental factors (E - 32%, 95% CI: 0.10-0.54). Shared environmental influences were not significant (C - 19%, 95% CI: -0.13 to 0.50). Moderation effects were significant whereby as FC increased, A on EP decreased (βA = -0.07, 95% CI: -0.12 to -0.02) while E increased (βE = 0.06, 95% CI: 0.03-0.09). Our findings indicate that genetic and non-shared environmental risk factors may mediate the relationship between EP and FC, and that as FC increases, protective genetic influences on EP may be attenuated, whereas environmental influences may become stronger in adolescents in LMIC.

Genetic effects on variability in visual aesthetic evaluations are partially shared across visual domains

The aesthetic values that individuals place on visual images are formed and shaped over a lifetime. However, whether the formation of visual aesthetic value is solely influenced by environmental exposure is still a matter of debate. Here, we considered differences in aesthetic value emerging across three visual domains: abstract images, scenes, and faces. We examined variability in two major dimensions of ordinary aesthetic experiences: taste-typicality and evaluation-bias. We build on two samples from the Australian Twin Registry where 1547 and 1231 monozygotic and dizygotic twins originally rated visual images belonging to the three domains. Genetic influences explained 26% to 41% of the variance in taste-typicality and evaluation-bias. Multivariate analyses showed that genetic effects were partially shared across visual domains. Results indicate that the heritability of major dimensions of aesthetic evaluations is comparable to that of other complex social traits, albeit lower than for other complex cognitive traits. The exception was taste-typicality for abstract images, for which we found only shared and unique environmental influences. Our study reveals that diverse sources of genetic and environmental variation influence the formation of aesthetic value across distinct visual domains and provides improved metrics to assess inter-individual differences in aesthetic value.

Associations between sleep medication use and alcohol consumption over 36 years in Finnish twins

BACKGROUND

Sleep medication use is an indicator of underlying sleep problems that might be induced by various factors such as alcohol use. However, the longitudinal relationship between drinking and sleep problems remains poorly understood. We investigated associations between sleep medication and alcohol use throughout adulthood, and examined the role of familial and potential confounding factors contributing to these associations.

METHODS

We used information of zygosity and self-report questionnaire data over a follow-up period of 36 years from the Older Finnish Twin Cohort (N=13,851).

RESULTS

Logistic regression analyses suggested consistent associations between sleep medication use and heavy/binge drinking at all four time points (OR range =1.36-3.18, P <0.05), implying that increased drinking is associated with increased sleep medication use over time. Cross-lagged path analyses suggested that moderate/heavy and binge drinking predict sleep medication use at most time points (OR range = 1.15-1.94, P <0.05), whilst sleep medication use predicts subsequent abstaining from alcohol (OR range =2.26-2.47, P <0.05). Within-pair analyses implied that familial factors play a role, and quantitative genetic modelling estimated genetic factors to explain approximately 80% of the lifetime association of sleep medication use with moderate/heavy and binge drinking.

CONCLUSIONS

Drinking is associated with sleep medication use throughout adulthood. Further, our results suggest that drinking is likely to predict sleep medication use, thereby potentially constituting a risk factor for sleep problems, and that genetic factors contribute to the association. These findings are important in terms of better understanding the development of sleep and alcohol use disorders.

Problematic technology use and sleep quality in young adulthood: novel insights from a nationally representative twin study

STUDY OBJECTIVES

Digital technology use is associated with poor sleep quality in adolescence and young adulthood although research findings have been mixed. No studies have addressed the association between the two using a genetically informative twin design which could extend our understanding of the etiology of this relationship. This study aimed to test: (1) the association between adolescents' perceived problematic use of digital technology and poor sleep quality, (2) whether the association between problematic use of technology and poor sleep quality remains after controlling for familial factors, and (3) genetic and environmental influences on the association between problematic use of technology and poor sleep quality.

METHODS

Participants were 2232 study members (18-year-old twins) of the Environmental Risk (E-Risk) Longitudinal Twin Study. The sample was 48.9% male, 90% white, and 55.6% monozygotic. We conducted regression and twin difference analyses and fitted twin models.

RESULTS

Twin differences for problematic use of technology were associated with differences for poor sleep quality in the whole sample (p < 0.001; B = 0.15) and also when we limited the analyses to identical twins only (p < 0.001; B = 0.21). We observed a substantial genetic correlation between problematic use of technology and sleep quality (rA = 0.31), whereas the environmental correlation was lower (rE = 0.16).

CONCLUSIONS

Adolescent reported problematic use of digital technology is associated with poor sleep quality-even after controlling for familial factors including genetic confounds. Our results suggest that the association between adolescents' sleep and problematic digital technology use is not accounted for by shared genetic liability or familial factors but could reflect a causal association. This robust association needs to be examined in future research designed to test causal associations.

Pleiotropic loci for cannabis use disorder severity in multi-ancestry high-risk populations

Cannabis use disorder (CUD) is common and has in part a genetic basis. The risk factors underlying its development likely involve multiple genes that are polygenetic and interact with each other and the environment to ultimately lead to the disorder. Co-morbidity and genetic correlations have been identified between CUD and other disorders and traits in select populations primarily of European descent. If two or more traits, such as CUD and another disorder, are affected by the same genetic locus, they are said to be pleiotropic. The present study aimed to identify specific pleiotropic loci for the severity level of CUD in three high-risk population cohorts: American Indians (AI), Mexican Americans (MA), and European Americans (EA). Using a previously developed computational method based on a machine learning technique, we leveraged the entire GWAS catalog and identified 114, 119, and 165 potentially pleiotropic variants for CUD severity in AI, MA, and EA respectively. Ten pleiotropic loci were shared between the cohorts although the exact variants from each cohort differed. While majority of the pleiotropic genes were distinct in each cohort, they converged on numerous enriched biological pathways. The gene ontology terms associated with the pleiotropic genes were predominately related to synaptic functions and neurodevelopment. Notable pathways included Wnt/β-catenin signaling, lipoprotein assembly, response to UV radiation, and components of the complement system. The pleiotropic genes were the most significantly differentially expressed in frontal cortex and coronary artery, up-regulated in adipose tissue, and down-regulated in testis, prostate, and ovary. They were significantly up-regulated in most brain tissues but were down-regulated in the cerebellum and hypothalamus. Our study is the first to attempt a large-scale pleiotropy detection scan for CUD severity. Our findings suggest that the different population cohorts may have distinct genetic factors for CUD, however they share pleiotropic genes from underlying pathways related to Alzheimer's disease, neuroplasticity, immune response, and reproductive endocrine systems.

Behaviour genetics and sleep: A narrative review of the last decade of quantitative and molecular genetic research in humans

During the last decade quantitative and molecular genetic research on sleep has increased considerably. New behavioural genetics techniques have marked a new era for sleep research. This paper provides a summary of the most important findings from the last ten years, on the genetic and environmental influences on sleep and sleep disorders and their associations with health-related variables (including anxiety and depression) in humans. In this review we present a brief summary of the main methods in behaviour genetic research (such as twin and genome-wide association studies). We then discuss key research findings on: genetic and environmental influences on normal sleep and sleep disorders, as well as on the association between sleep and health variables (highlighting a substantial role for genes in individual differences in sleep and their associations with other variables). We end by discussing future lines of enquiry and drawing conclusions, including those focused on problems and misconceptions associated with research of this type. In this last decade our knowledge about genetic and environmental influences on sleep and its disorders has expanded. Both, twin and genome-wide association studies show that sleep and sleep disorders are substantially influenced by genetic factors and for the very first time multiple specific genetic variants have been associated with sleep traits and disorders.

Unraveling the Relation Between Personality and Well-Being in a Genetically Informative Design

In the current study, common and unique genetic and environmental influences on personality and a broad range of well-being measures were investigated. Data on the Big Five, life satisfaction, quality of life, self-rated health, loneliness, and depression from 14,253 twins and their siblings (age M: 31.82, SD: 14.41, range 16–97) from the Netherlands Twin Register were used in multivariate extended twin models. The best-fitting theoretical model indicated that genetic variance in personality and well-being traits can be decomposed into effects due to one general, common factor ( Mdn: 60%, range 15%–89%), due to personality-specific ( Mdn: 2%, range 0%–78%) and well-being-specific ( Mdn: 12%, range 4%–35%) factors, and trait-specific effects ( Mdn: 18%, range 0%–65%). Significant amounts of non-additive genetic influences on the traits’ (co)variances were found, while no evidence was found for quantitative or qualitative sex differences. Taken together, our study paints a fine-grained, complex picture of common and unique genetic and environmental effects on personality and well-being. Implications for the interpretation of shared variance, inflated phenotypic correlations between traits and future gene finding studies are discussed.

Quantifying the heritability of belief formation

Individual differences in behaviour, traits and mental-health are partially heritable. Traditionally, studies have focused on quantifying the heritability of high-order characteristics, such as happiness or education attainment. Here, we quantify the degree of heritability of lower-level mental processes that likely contribute to complex traits and behaviour. In particular, we quantify the degree of heritability of cognitive and affective factors that contribute to the generation of beliefs about risk, which drive behavior in domains ranging from finance to health. Monozygotic and dizygotic twin pairs completed a belief formation task. We first show that beliefs about risk are associated with vividness of imagination, affective evaluation and learning abilities. We then demonstrate that the genetic contribution to individual differences in these processes range between 13.5 and 39%, with affect evaluation showing a particular robust heritability component. These results provide clues to which mental factors may be driving the heritability component of beliefs formation, which in turn contribute to the heritability of complex traits.

Gene-by-Crisis Interaction for Optimism and Meaning in Life: The Effects of the COVID-19 Pandemic

The corona virus disease 2019 (COVID-19) pandemic and the restrictions to reduce the spread of the virus has had a large impact on daily life. We investigated the individual differences in the effect of the COVID-19 pandemic and first lockdown on optimism and meaning in life in a sample from the Netherlands Twin Register. Participants completed surveys before (N = 9964, Mean age: 48.2, SD = 14.4) and during the first months of the pandemic (i.e. April–May 2020, N = 17,464, Mean age: 44.6 SD = 14.8), with a subsample completing both surveys (N = 6461, Mean age T1: 48.8, SD = 14.5). We applied genetic covariance structure models to twin data to investigate changes in the genetic architecture of the outcome traits due to the pandemic and the interaction of genes with the environmental exposure. Although 56% and 35% of the sample was negatively affected by the pandemic in their optimism and meaning in life, many participants were stable (32% and 43%) or even showed increased optimism and meaning in life (11% and 22%). Subgroups, specifically women, higher educated people, and people with poorer health, experienced larger negative effects. During the first months of the pandemic, slightly lower heritability estimates for optimism and meaning in life (respectively 20% and 25%) were obtained compared to pre-pandemic (respectively 26% and 32%), although confidence intervals overlap. The lower than unity genetic correlations across time (.75 and .63) suggest gene-environment interactions, where the expression of genes that influence optimism and meaning in life differs before and during the pandemic. The COVID-19 pandemic is a strong exposure that leads to imbalanced effects on the well-being of individuals. Some people decrease in well-being, while others get more optimistic and consider their lives as more meaningful during the pandemic. These differences are partly explained by individual differences in genetic sensitivity to extreme environmental change. More knowledge on the person-specific response to specific environmental variables underlying these individual differences is urgently needed to prevent further inequality.

Genetic evidence for a large overlap and potential bidirectional causal effects between resilience and well-being

Resilience and well-being are strongly related. People with higher levels of well-being are more resilient after stressful life events or trauma and vice versa. Less is known about the underlying sources of overlap and causality between the constructs. In a sample of 11.304 twins and 2.572 siblings from the Netherlands Twin Register, we investigated the overlap and possible direction of causation between resilience (i.e. the absence of psychiatric symptoms despite negative life events) and well-being (i.e. satisfaction with life) using polygenic score (PGS) prediction, twin-sibling modelling, and the Mendelian Randomization Direction of Causality (MR-DoC) model. Longitudinal twin-sibling models showed significant phenotypic correlations between resilience and well-being (.41/.51 at time 1 and 2). Well-being PGS were predictive for both well-being and resilience, indicating that genetic factors influencing well-being also predict resilience. Twin-sibling modeling confirmed this genetic correlation (0.71) and showed a strong environmental correlation (0.93). In line with causality, both genetic (51%) and environmental (49%) factors contributed significantly to the covariance between resilience and well-being. Furthermore, the results of within-subject and MZ twin differences analyses were in line with bidirectional causality. Additionally, we used the MR-DoC model combining both molecular and twin data to test causality, while correcting for pleiotropy. We confirmed the causal effect from well-being to resilience, with the direct effect of well-being explaining 11% (T1) and 20% (T2) of the variance in resilience. Data limitations prevented us to test the directional effect from resilience to well-being with the MR-DoC model. To conclude, we showed a strong relation between well-being and resilience. A first attempt to quantify the direction of this relationship points towards a bidirectional causal effect. If replicated, the potential mutual effects can have implications for interventions to lower psychopathology vulnerability, as resilience and well-being are both negatively related to psychopathology.