Multivariate analysis of 1.5 million people identifies genetic associations with traits related to self-regulation and addiction

Abstract

ehaviors related to self-regulation, such as substance use disorders or antisocial behaviors, have far-reaching consequences for affected individuals, their families, communities and society at large 1,2 . Collectively, this group of correlated traits are classified as externalizing 3 . Twin studies have demonstrated that externalizing liability is highly heritable (~80%) 4,5 . To date, however, no large-scale molecular genetic studies have utilized the extensive degree of genetic overlap among externalizing traits to aid gene discovery, as most studies have focused on individual disorders 6 . For many high-cost, high-risk behaviors with an externalizing component-opioid use disorder and suicide attempts 7 being salient examples-there are limited genotyped cases available for gene discovery 8,9 .A complementary strategy to the single-disease approach is to study the shared genetic architecture across traits in multivariate analyses, which boosts statistical power by pooling data across

Multivariate genetic analysis of personality and cognitive traits reveals abundant pleiotropy and improves prediction

“…Firstly, while large univariate GWAS have provided insights into the neurobiology of specific traits (Nagel et al, 2018a; Savage et al, 2018), future studies need to be aware of the lack of specificity of most variants associated with complex mental phenotypes. To fully characterise a given genetic variant, its effect should be evaluated beyond the specific phenotype of interest as it is likely to have pleiotropic effects across diverse domains (Karlsson Linnér et al, 2021; van der Meer et al, 2020a). Secondly, as statistical power increases, the relative effect size of a variant will likely be more informative with regards to specificity and relevance for a given phenotype than the presence or absence of a statistical association.…”

Alcohol and nicotine polygenic scores are associated with the development of alcohol and nicotine use problems from adolescence to young adulthood

“…Efforts to extend these findings to additional substances (e.g. cannabis) and to directly compare the effects of the SMK PGS to the EXT PGS [39] are under way.…”

“…The SMK PGS has also been associated with the use of multiple other substances (e.g. alcohol, cannabis, cocaine) [5], and has been found to load strongly onto a latent factor composed of externalizing (EXT) traits [39]. Using the same sample as in this report, we have also shown that these non‐specific effects extend beyond substance use to include externalizing problems (rule‐breaking and aggression) from ages 11 to 17 years (i.e.…”

Bench Research Informed by GWAS Results

“…At the time of this writing, 31 of the studies in the GWAS Catalog had a sample size exceeding one million participants, though most of the large studies are meta-analyses. Some examples of the largest studies to demonstrate the diversity of human phenotypes studied with GWAS include those focusing on: (1) Physiological traits such as blood pressure [34], cholesterol level [35] and concentration of liver enzymes in blood serum [36]; (2) medical conditions such as breast cancer [37], chronic renal failure [38], osteoporosis [39], Parkinson's disease [40], diabetes [41], cataract [42] and dental caries [43]; (3) anthropometric traits such as height [44], longevity [45], handedness [46], body fat distribution [47]; (4) lifestyle traits such as alcohol consumption [48], smoking [49] and chronotype [50]; (5) psychological traits such as self-reported depression [51], risk tolerance [52], intelligence [53], well-being [54], 'Big Five' personality traits [55] and even (6) socioeconomic traits such as educational attainment [56], family income [3] and being fired from work [57]. It is difficult to find a common human phenotype that has not yet been studied with GWAS.…”