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Objective: Increasingly large samples in genome-wide association studies (GWASs) for alcohol use behaviors (AUBs) have led to an influx of implicated genes, yet the clinical and functional understanding of these associations remains low, in part because most GWASs do not account for the complex and varied manifestations of AUBs. This study applied a multidimensional framework to investigate the latent genetic structure underlying heterogeneous dimensions of AUBs., Methods: Multimodal assessments (self-report, interview, electronic health records) were obtained from approximately 400,000 UK Biobank participants. GWAS was conducted for 18 distinct AUBs, including consumption, drinking patterns, alcohol problems, and clinical sequelae. Latent genetic factors were identified and carried forward to GWAS using genomic structural equation modeling, followed by functional annotation, genetic correlation, and enrichment analyses to interpret the genetic associations., Results: Four latent factors were identified: Problems, Consumption, BeerPref (declining alcohol consumption with a preference for drinking beer), and AtypicalPref (drinking fortified wine and spirits). The latent factors were moderately correlated (r g values, 0.12-0.57) and had distinct patterns of associations, with BeerPref in particular implicating many novel genomic regions. Patterns of regional and cell type-specific gene expression in the brain also differed between the latent factors., Conclusions: Deep phenotyping is an important next step to improve understanding of the genetic etiology of AUBs, in addition to increasing sample size. Further effort is required to uncover the genetic heterogeneity underlying AUBs using methods that account for their complex, multidimensional nature.

Autozygosity is associated with rare Mendelian disorders and clinically relevant quantitative traits. We investigated associations between the fraction of the genome in runs of homozygosity (F ROH ) and common diseases in Genes & Health (n = 23,978 British South Asians), UK Biobank (n = 397,184), and 23andMe. We show that restricting analysis to offspring of first cousins is an effective way of reducing confounding due to social/environmental correlates of F ROH . Within this group in G&H+UK Biobank, we found experiment-wide significant associations between F ROH and twelve common diseases. We replicated associations with type 2 diabetes (T2D) and post-traumatic stress disorder via within-sibling analysis in 23andMe (median n = 480,282). We estimated that autozygosity due to consanguinity accounts for 5%-18% of T2D cases among British Pakistanis. Our work highlights the possibility of widespread non-additive genetic effects on common diseases and has important implications for global populations with high rates of consanguinity., Competing Interests: Declaration of interests J.O. and members of the 23andMe Research Team are employed by and hold stock or stock options in 23andMe, Inc. H.C.M. is a member of Cell’s advisory board. D.A.v.H., S.F., and H.C.M. have received salary contributions via the Genes & Health Industry Consortium of AstraZeneca PLC, Bristol-Myers Squibb Company, GlaxoSmithKline Research and Development Limited, Maze Therapeutics Inc., Merck Sharp & Dohme LLC, Novo Nordisk A/S, Pfizer Inc., and Takeda Development Centre Americas Inc., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Psychiatric disorders are complex clinical conditions with large heterogeneity and overlap in symptoms, genetic liability and brain imaging abnormalities. Building on a dimensional conceptualization of mental health, previous studies have reported genetic overlap between psychiatric disorders and population-level mental health, and between psychiatric disorders and brain functional connectivity. Here, in 30,701 participants aged 45-82 from the UK Biobank we map the genetic associations between self-reported mental health and resting-state fMRI-based measures of brain network function. Multivariate Omnibus Statistical Test revealed 10 genetic loci associated with population-level mental symptoms. Next, conjunctional FDR identified 23 shared genetic variants between these symptom profiles and fMRI-based brain network measures. Functional annotation implicated genes involved in brain structure and function, in particular related to synaptic processes such as axonal growth (e.g. NGFR and RHOA). These findings provide further genetic evidence of an association between brain function and mental health traits in the population., (© 2023. The Author(s).)

The cell adhesion molecule 2 (CADM2) gene has appeared among the top associations in a wide range of genome-wide association studies (GWASs). This study aims to: (1) examine how widespread the role of CADM2 is in behavioural traits, and (2) investigate trait-specific effects on CADM2 expression levels across tissues. We conducted a phenome-wide association study in UK Biobank (N = 12,211-453,349) on 242 psycho-behavioral traits, both at the SNP and the gene-level. For comparison, we repeated the analyses for other large (and high LD) genes. We found significant associations between CADM2 and 50 traits (including cognitive, risk taking, and dietary traits), many more than for the comparison genes. We show that many trait associations are reduced when taking geographical stratification into account. S-Predixcan revealed that CADM2 expression in brain tissues was significantly associated with many traits; highly significant effects were also observed for lung, mammary, and adipose tissues. In conclusion, this study shows that the role of CADM2 extends to a wide range of psycho-behavioral traits, suggesting these traits may share a common biological denominator., (© 2022. The Author(s).)

We aimed to obtain reliable reference charts for sleep duration, estimate the prevalence of sleep complaints across the lifespan and identify risk indicators of poor sleep. Studies were identified through systematic literature search in Embase, Medline and Web of Science (9 August 2019) and through personal contacts. Eligible studies had to be published between 2000 and 2017 with data on sleep assessed with questionnaires including ≥100 participants from the general population. We assembled individual participant data from 200,358 people (aged 1-100 years, 55% female) from 36 studies from the Netherlands, 471,759 people (40-69 years, 55.5% female) from the United Kingdom and 409,617 people (≥18 years, 55.8% female) from the United States. One in four people slept less than age-specific recommendations, but only 5.8% slept outside of the 'acceptable' sleep duration. Among teenagers, 51.5% reported total sleep times (TST) of less than the recommended 8-10 h and 18% report daytime sleepiness. In adults (≥18 years), poor sleep quality (13.3%) and insomnia symptoms (9.6-19.4%) were more prevalent than short sleep duration (6.5% with TST < 6 h). Insomnia symptoms were most frequent in people spending ≥9 h in bed, whereas poor sleep quality was more frequent in those spending <6 h in bed. TST was similar across countries, but insomnia symptoms were 1.5-2.9 times higher in the United States. Women (≥41 years) reported sleeping shorter times or slightly less efficiently than men, whereas with actigraphy they were estimated to sleep longer and more efficiently than man. This study provides age- and sex-specific population reference charts for sleep duration and efficiency which can help guide personalized advice on sleep length and preventive practices.

Smoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants). In a subset of 112,811 participants, a further one million SNVs were also genotyped and tested for association with the four smoking behaviour traits. SNV-trait associations with P < 5 × 10 -8 in either analysis were taken forward for replication in up to 275,596 independent participants from UK Biobank. Lastly, a meta-analysis of the discovery and replication studies was performed. Sixteen SNVs were associated with at least one of the smoking behaviour traits (P < 5 × 10 -8 ) in the discovery samples. Ten novel SNVs, including rs12616219 near TMEM182, were followed-up and five of them (rs462779 in REV3L, rs12780116 in CNNM2, rs1190736 in GPR101, rs11539157 in PJA1, and rs12616219 near TMEM182) replicated at a Bonferroni significance threshold (P < 4.5 × 10 -3 ) with consistent direction of effect. A further 35 SNVs were associated with smoking behaviour traits in the discovery plus replication meta-analysis (up to 622,409 participants) including a rare SNV, rs150493199, in CCDC141 and two low-frequency SNVs in CEP350 and HDGFRP2. Functional follow-up implied that decreased expression of REV3L may lower the probability of smoking initiation. The novel loci will facilitate understanding the genetic aetiology of smoking behaviour and may lead to the identification of potential drug targets for smoking prevention and/or cessation.

Background Obesity has been associated with increased risk of accelerated cognitive decline and dementia, which suggests underlying neurobiological changes. Purpose To investigate the associations between obesity and brain structure (overall and regional brain volumes, and white matter microstructure) assessed at MRI in a sample of the general population. Materials and Methods Between March 2014 and January 2018, 12 087 participants (52.8% women [6381 of 12 087]; mean age, 62 years; age range, 45-76 years) in the prospective observational UK Biobank study underwent 3.0-T multiparametric (ie, three-dimensional T1-weighted diffusion tensor imaging [DTI]) brain imaging. Percentage of total body fat (TBF) was assessed by body impedance. Volumetric measures included brain volume, gray matter volume, white matter volume, volumes of subcortical gray matter structures, and regional cortical volumes. Global and tract-specific microstructure was assessed by fractional anisotropy (FA) and mean diffusivity (MD) by using DTI. Linear regression was performed by using TBF as determinant and brain measures as outcome variables, and effect estimates were expressed as standardized β values. Results Mean body mass index was 26.6 kg/m 2 ± 4.4 (standard deviation [SD]), mean TBF in men was 24.4% ± 5.5, and mean TBF in women was 35.5% ± 6.5. In men, TBF was negatively associated with all subcortical gray matter volumes (thalamus, caudate nucleus, putamen, globus pallidus, hippocampus, and nucleus accumbens) other than amygdala volume. In women, TBF was solely negatively associated with globus pallidus volume. In women and men, TBF was positively associated with global FA (women vs men, 0.05 vs 0.07 SD change in global FA per SD change in TBF; P < .001). TBF was negatively associated with global MD in women (-0.07 SD change in global MD per SD change in TBF; P < .001). Conclusion These findings provide evidence that obesity is associated with smaller subcortical gray matter volumes. In addition, obesity was associated with higher coherence but lower magnitude of white matter microstructure, which suggests differential influences of obesity on the geometric organization of white matter microstructure. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Caspers in this issue.