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Genetic effects on alcohol use can vary over time but are often examined using longitudinal models that predict a distal outcome at a single time point. The vast majority of these studies predominately examine effects using White, European American (EA) samples or examine the etiology of genetic variants identified from EA samples in other racial/ethnic populations, leading to inconclusive findings about genetic effects on alcohol use. The current study examined how genetic influences on alcohol use varied by age across a 15 year period within a diverse ethnic/racial sample of adolescents. Using a multi-ethnic approach, polygenic risk scores were created for African American (AA, n  = 192) and EA samples ( n  = 271) based on racially/ethnically aligned genome wide association studies. Age-varying associations between polygenic scores and alcohol use were examined from age 16 to 30 using time-varying effect models separately for AA and EA samples. Polygenic risk for alcohol use was found to be associated with alcohol use from age 22–27 in the AA sample and from age 24.50 to 29 in the EA sample. Results are discussed relative to the intersection of alcohol use and developmental genetic effects in diverse populations.

Cigarette smoking is the leading cause of preventable morbidity and mortality. Genetic variation contributes to initiation, regular smoking, nicotine dependence, and cessation. We present a Fagerström Test for Nicotine Dependence (FTND)-based genome-wide association study in 58,000 European or African ancestry smokers. We observe five genome-wide significant loci, including previously unreported loci MAGI2/GNAI1 (rs2714700) and TENM2 (rs1862416), and extend loci reported for other smoking traits to nicotine dependence. Using the heaviness of smoking index from UK Biobank ( N  = 33,791), rs2714700 is consistently associated; rs1862416 is not associated, likely reflecting nicotine dependence features not captured by the heaviness of smoking index. Both variants influence nearby gene expression (rs2714700/ MAGI2-AS3 in hippocampus; rs1862416/ TENM2 in lung), and expression of genes spanning nicotine dependence-associated variants is enriched in cerebellum. Nicotine dependence (SNP-based heritability = 8.6%) is genetically correlated with 18 other smoking traits ( r g  = 0.40–1.09) and co-morbidities. Our results highlight nicotine dependence-specific loci, emphasizing the FTND as a composite phenotype that expands genetic knowledge of smoking. There is strong genetic evidence for cigarette smoking behaviors, yet little is known on nicotine dependence (ND). Here, the authors perform a genome-wide association study on ND in 58,000 smokers, identifying five genome-wide significant loci.

Considerable evidence supports the role of present-moment attention, a central feature of mindfulness, in subjective wellbeing maintenance and enhancement. Yet it is not clear why such a relation exists. This study examined the genetic and environmental contributions of present-moment attention to subjective wellbeing. Consistent with the “generalist genes hypothesis” and prior evidence, we hypothesized that presence and subjective wellbeing would show a substantial genetic correlation and smaller environmental correlation. Using a large epidemiological sample of healthy 16-year-old twins in the United Kingdom (N = 1136 monozygotic (MZ) and dizygotic (DZ) twin pairs), genetic overlap was found between presence and the cognitive component of subjective wellbeing (life satisfaction), and to a lesser extent, the affective component of subjective wellbeing (operationalized as happiness). The non-shared environmental overlap between these constructs was substantial. This study provides the first evidence known to us showing that present-centered attention, a primary component of mindfulness, has both genetic and environmental overlap with subjective wellbeing. The findings have implications for understanding mechanisms by which presence is associated with positive emotions and life satisfaction, and suggest, pending additional research, that mindfulness-based interventions to enhance wellbeing may be best suited to those with a genetic propensity toward mindful presence.

Handedness has been extensively studied because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and the International Handedness Consortium, we conducted a genome-wide association meta-analysis of handedness ( N  = 1,766,671). We found 41 loci associated ( P  < 5 × 10 −8 ) with left-handedness and 7 associated with ambidexterity. Tissue-enrichment analysis implicated the CNS in the aetiology of handedness. Pathways including regulation of microtubules and brain morphology were also highlighted. We found suggestive positive genetic correlations between left-handedness and neuropsychiatric traits, including schizophrenia and bipolar disorder. Furthermore, the genetic correlation between left-handedness and ambidexterity is low ( r G  = 0.26), which implies that these traits are largely influenced by different genetic mechanisms. Our findings suggest that handedness is highly polygenic and that the genetic variants that predispose to left-handedness may underlie part of the association with some psychiatric disorders. A genome-wide association study of 1.7 million individuals identified 41 genetic variants associated with left-handedness and 7 associated with ambidexterity. The genetic correlation between the traits was low, thereby implying different aetiologies.

Alcohol use during adolescence poses a significant public health problem due to its potential long-term consequences on both physical and mental health and increased risk for developing substance use disorders later in life. Both individual (e.g., genetic liability, neural functioning, personality features) and environmental (e.g., parenting, school environment) features play an important role in accelerating or buffering the progression of early alcohol consumption. This study used data from the Adolescent Brain Cognitive Development (ABCD) study (Release 5.1; N  = 11,868) to provide a comprehensive examination of how genetic, neural, trait, and environmental factors are associated with risk for first sip of alcohol, first full drink, and the progression from first sip to full drink, both independently and uniquely. Cox proportional hazard models were used to examine the univariable associations between theoretically relevant genetic, neural, trait, and environmental variables and early alcohol use. Then, stepwise model-fitting was used to determine which indicators were uniquely associated with alcohol outcomes. Risk for early alcohol use was distributed across multiple domains highlighting the unique information provided by genetic, trait, and environmental variables. Results also indicated the importance of both environmental and genetic factors on time to first sip of alcohol, but that time to first full drink and the progression from sip to drink was most associated with genetic and trait factors rather than broad environmental influences. These findings highlight both potential etiological pathways driving early alcohol use as well as phenotypic and environmental process that can be targeted for early intervention efforts.

Previous research suggests that genetic risk factors may predispose to conduct problems and alcohol use in adolescence. Whether genetic risk factors interact with social contexts has not been well characterized among African American adolescents. Data came from a subsample of the Genes, Environment, and Neighborhood Initiative study comprising 501 African American adolescents, including 151 lifetime drinkers (56% female, mean age = 16.3, SD = 1.4). Genetic risk was assessed with polygenic risk scores for alcohol dependence. Analyses explored interactions between genetic risk and self-reported alcohol use, conduct problems, life stressors, and other covariates. The effects of two gene–environment interactions (G × E) were tested in the sample of alcohol exposed adolescents; one on conduct problems and the other on alcohol use. There were significant associations between polygenic risk for alcohol dependence and conduct problems. A significant G × E interaction showed the impact of genetic risk on conduct problems was stronger under conditions of high exposure to family and neighborhood stressors. Among this sample of African American adolescents, genetic risk for alcohol dependence was not directly associated with alcohol use but was related to more conduct problems. Further, the effect of genetic risk interacted with stressors from the family and neighborhood, so that the effect of genetic risk on conduct problems was stronger for individuals who reported greater stressors.

Genome-wide, polygenic risk scores (PRS) have emerged as a useful way to characterize genetic liability. There is growing evidence that PRS may prove useful for early identification of those at increased risk for certain diseases. The current potential of PRS for alcohol use disorders (AUD) remains an open question. Using data from both a population-based sample [the FinnTwin12 (FT12) study] and a high-risk sample [the Collaborative Study on the Genetics of Alcoholism (COGA)], we examined the association between PRSs derived from genome-wide association studies (GWASs) of (1) alcohol dependence/alcohol problems, (2) alcohol consumption, and (3) risky behaviors with AUD and other substance use disorder (SUD) criteria. These PRSs explain ~2.5–3.5% of the variance in AUD (across FT12 and COGA) when all PRSs are included in the same model. Calculations of area under the curve (AUC) show PRS provide only a slight improvement over a model with age, sex, and ancestral principal components as covariates. While individuals in the top 20, 10, and 5% of the PRS distribution had greater odds of having an AUD compared to the lower end of the continuum in both COGA and FT12, the point estimates at each threshold were statistically indistinguishable. Those in the top 5% reported greater levels of licit (alcohol and nicotine) and illicit (cannabis and opioid) SUD criteria. PRSs are associated with risk for SUD in independent samples. However, usefulness for identifying those at increased risk in their current form is modest, at best. Improvement in predictive ability will likely be dependent on increasing the size of well-phenotyped discovery samples.

Predictive models for recovering from alcohol use disorder (AUD) and identifying related predisposition biomarkers can have a tremendous impact on addiction treatment outcomes and cost reduction. Our sample (N = 1376) included individuals of European (EA) and African (AA) ancestry from the Collaborative Study on the Genetics of Alcoholism (COGA) who were initially assessed as having AUD (DSM-5) and reassessed years later as either having AUD or in remission. To predict this difference in AUD recovery status, we analyzed the initial data using multimodal, multi-features machine learning applications including EEG source-level functional brain connectivity, Polygenic Risk Scores (PRS), medications, and demographic information. Sex and ancestry age-matched stratified analyses were performed with supervised linear Support Vector Machine application and were calculated twice, once when the ancestry was defined by self-report and once defined by genetic data. Multifeatured prediction models achieved higher accuracy scores than models based on a single domain and higher scores in male models when the ancestry was based on genetic data. The AA male group model with PRS, EEG functional connectivity, marital and employment status features achieved the highest accuracy of 86.04%. Several discriminative features were identified, including collections of PRS related to neuroticism, depression, aggression, years of education, and alcohol consumption phenotypes. Other discriminated features included being married, employed, medication, lower default mode network and fusiform connectivity, and higher insula connectivity. Results highlight the importance of increasing genetic homogeneity of analyzed groups, identifying sex, and ancestry-specific features to increase prediction scores revealing biomarkers related to AUD remission.

Genetic predispositions and environmental influences both play an important role in adolescent externalizing behavior; however, they are not always independent. To elucidate gene–environment interplay, we examined the interrelationships between externalizing polygenic risk scores, parental knowledge, and peer substance use in impacting adolescent externalizing behavior across two time-points in a high-risk longitudinal sample of 1,200 adolescents (764 European and 436 African ancestry; Mage = 12.99) from the Collaborative Study on the Genetics of Alcoholism. Results from multivariate path analysis indicated that externalizing polygenic scores were directly associated with adolescent externalizing behavior but also indirectly via peer substance use, in the European ancestry sample. No significant polygenic association nor indirect effects of genetic risk were observed in the African ancestry group, likely due to more limited power. Our findings underscore the importance of gene–environment interplay and suggest peer substance use may be a mechanism through which genetic risk influences adolescent externalizing behavior.

Genetic factors explain a major proportion of human height variation, but differences in mean stature have also been found between socio-economic categories suggesting a possible effect of environment. By utilizing a classical twin design which allows decomposing the variation of height into genetic and environmental components, we tested the hypothesis that environmental variation in height is greater in offspring of lower educated parents. Twin data from 29 cohorts including 65,978 complete twin pairs with information on height at ages 1 to 69 years and on parental education were pooled allowing the analyses at different ages and in three geographic-cultural regions (Europe, North America and Australia, and East Asia). Parental education mostly showed a positive association with offspring height, with significant associations in mid-childhood and from adolescence onwards. In variance decomposition modeling, the genetic and environmental variance components of height did not show a consistent relation to parental education. A random-effects meta-regression analysis of the aggregate-level data showed a trend towards greater shared environmental variation of height in low parental education families. In conclusion, in our very large dataset from twin cohorts around the globe, these results provide only weak evidence for the study hypothesis.