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

ABSTRACT: Behaviors and disorders related to self-regulation, such as substance use, antisocial behavior and attention-deficit/hyperactivity disorder, are collectively referred to as externalizing and have shared genetic liability. We applied a multivariate approach that leverages genetic correlations among externalizing traits for genome-wide association analyses. By pooling data from ~1.5 million people, our approach is statistically more powerful than single-trait analyses and identifies more than 500 genetic loci. The loci were enriched for genes expressed in the brain and related to nervous system development. A polygenic score constructed from our results predicts a range of behavioral and medical outcomes that were not part of genome-wide analyses, including traits that until now lacked well-performing polygenic scores, such as opioid use disorder, suicide, HIV infections, criminal convictions and unemployment. Our findings are consistent with the idea that persistent difficulties in self-regulation can be conceptualized as a neurodevelopmental trait with complex and far-reaching social and health correlates.

SUBMITTER: Karlsson Linner R

PROVIDER: S-EPMC8484054 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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

Karlsson Linnér Richard R Mallard Travis T TT Barr Peter B PB Sanchez-Roige Sandra S Madole James W JW Driver Morgan N MN Poore Holly E HE de Vlaming Ronald R Grotzinger Andrew D AD Tielbeek Jorim J JJ Johnson Emma C EC Liu Mengzhen M Rosenthal Sara Brin SB Ideker Trey T Zhou Hang H Kember Rachel L RL Pasman Joëlle A JA Verweij Karin J H KJH Liu Dajiang J DJ Vrieze Scott S Kranzler Henry R HR Gelernter Joel J Harris Kathleen Mullan KM Tucker-Drob Elliot M EM Waldman Irwin D ID Palmer Abraham A AA Harden K Paige KP Koellinger Philipp D PD Dick Danielle M DM

Nature neuroscience 20210826 10

Behaviors and disorders related to self-regulation, such as substance use, antisocial behavior and attention-deficit/hyperactivity disorder, are collectively referred to as externalizing and have shared genetic liability. We applied a multivariate approach that leverages genetic correlations among externalizing traits for genome-wide association analyses. By pooling data from ~1.5 million people, our approach is statistically more powerful than single-trait analyses and identifies more than 500 ...[more]

PMID: 34446935

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Project description:BackgroundImmune traits are considered to serve as potential biomarkers for pig's health. Medium to high heritabilities have been observed for some of the immune traits suggesting genetic variability of these phenotypes. Consideration of previously established genetic correlations between immune traits can be used to identify pleiotropic genetic markers. Therefore, genome-wide association study (GWAS) approaches are required to explore the joint genetic foundation for health biomarkers. Usually, GWAS explores phenotypes in a univariate (uv), trait-by-trait manner. Besides two uv GWAS methods, four multivariate (mv) GWAS approaches were applied on combinations out of 22 immune traits for Landrace (LR) and Large White (LW) pig lines.ResultsIn total 433 (LR: 351, LW: 82) associations were identified with the uv approach implemented in PLINK and a Bayesian linear regression uv approach (BIMBAM) software. Single Nucleotide Polymorphisms (SNPs) that were identified with both uv approaches (n = 32) were mostly associated with immune traits such as haptoglobin, red blood cell characteristics and cytokines, and were located in protein-coding genes. Mv GWAS approaches detected 647 associations for different mv immune trait combinations which were summarized to 133 Quantitative Trait Loci (QTL). SNPs for different trait combinations (n = 66) were detected with more than one mv method. Most of these SNPs are associated with red blood cell related immune trait combinations. Functional annotation of these QTL revealed 453 immune-relevant protein-coding genes. With uv methods shared markers were not observed between the breeds, whereas mv approaches were able to detect two conjoint SNPs for LR and LW. Due to unmapped positions for these markers, their functional annotation was not clarified.ConclusionsThis study evaluated the joint genetic background of immune traits in LR and LW piglets through the application of various uv and mv GWAS approaches. In comparison to uv methods, mv methodologies identified more significant associations, which might reflect the pleiotropic background of the immune system more accurately. In genetic research of complex traits, the SNP effects are generally small. Furthermore, one genetic variant can affect several correlated immune traits at the same time, termed pleiotropy. As mv GWAS methods consider strong dependencies among traits, the power to detect SNPs can be boosted. Both methods revealed immune-relevant potential candidate genes. Our results indicate that one single test is not able to detect all the different types of genetic effects in the most powerful manner and therefore, the methods should be applied complementary.

Dataset Information

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

Publications

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

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