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Meta-Analysis
. 2022 Nov;27(11):4453-4463.
doi: 10.1038/s41380-022-01793-3. Epub 2022 Oct 25.

Uncovering the genetic architecture of broad antisocial behavior through a genome-wide association study meta-analysis

Jorim J Tielbeek  1 Emil Uffelmann  2 Benjamin S Williams  3 Lucía Colodro-Conde  4 Éloi Gagnon  5 Travis T Mallard  6 Brandt E Levitt  7 Philip R Jansen  2 Ada Johansson  8 Hannah M Sallis  9 Giorgio Pistis  10 Gretchen R B Saunders  11 Andrea G Allegrini  12 Kaili Rimfeld  12 Bettina Konte  13 Marieke Klein  14 Annette M Hartmann  13 Jessica E Salvatore  15 Ilja M Nolte  16 Ditte Demontis  17 Anni L K Malmberg  18 S Alexandra Burt  19 Jeanne E Savage  2 Karen Sugden  3 Richie Poulton  20 Kathleen Mullan Harris  21 Scott Vrieze  11 Matt McGue  11 William G Iacono  11 Nina Roth Mota  14 Jonathan Mill  22 Joana F Viana  23 Brittany L Mitchell  24 Jose J Morosoli  4 Till F M Andlauer  25 Isabelle Ouellet-Morin  26 Richard E Tremblay  27 Sylvana M Côté  28 Jean-Philippe Gouin  29 Mara R Brendgen  30 Ginette Dionne  5 Frank Vitaro  31 Michelle K Lupton  24 Nicholas G Martin  24 COGA ConsortiumSpit for Science Working GroupEnrique Castelao  10 Katri Räikkönen  18 Johan G Eriksson  32 Jari Lahti  18 Catharina A Hartman  33 Albertine J Oldehinkel  33 Harold Snieder  16 Hexuan Liu  34 Martin Preisig  10 Alyce Whipp  35 Eero Vuoksimaa  35 Yi Lu  36 Patrick Jern  8 Dan Rujescu  13 Ina Giegling  13 Teemu Palviainen  35 Jaakko Kaprio  35 Kathryn Paige Harden  37 Marcus R Munafò  9 Geneviève Morneau-Vaillancourt  5 Robert Plomin  12 Essi Viding  38 Brian B Boutwell  39 Fazil Aliev  40 Danielle M Dick  40 Arne Popma  41 Stephen V Faraone  42 Anders D Børglum  17 Sarah E Medland  4 Barbara Franke  43 Michel Boivin  5 Jean-Baptiste Pingault  44 Jeffrey C Glennon  45 J C Barnes  34 Simon E Fisher  46 Terrie E Moffitt  3 Avshalom Caspi  3 Tinca J C Polderman  41 Danielle Posthuma  2
Collaborators, Affiliations
Meta-Analysis

Uncovering the genetic architecture of broad antisocial behavior through a genome-wide association study meta-analysis

Jorim J Tielbeek et al. Mol Psychiatry. 2022 Nov.

Abstract

Despite the substantial heritability of antisocial behavior (ASB), specific genetic variants robustly associated with the trait have not been identified. The present study by the Broad Antisocial Behavior Consortium (BroadABC) meta-analyzed data from 28 discovery samples (N = 85,359) and five independent replication samples (N = 8058) with genotypic data and broad measures of ASB. We identified the first significant genetic associations with broad ASB, involving common intronic variants in the forkhead box protein P2 (FOXP2) gene (lead SNP rs12536335, p = 6.32 × 10-10). Furthermore, we observed intronic variation in Foxp2 and one of its targets (Cntnap2) distinguishing a mouse model of pathological aggression (BALB/cJ strain) from controls (BALB/cByJ strain). Polygenic risk score (PRS) analyses in independent samples revealed that the genetic risk for ASB was associated with several antisocial outcomes across the lifespan, including diagnosis of conduct disorder, official criminal convictions, and trajectories of antisocial development. We found substantial genetic correlations of ASB with mental health (depression rg = 0.63, insomnia rg = 0.47), physical health (overweight rg = 0.19, waist-to-hip ratio rg = 0.32), smoking (rg = 0.54), cognitive ability (intelligence rg = -0.40), educational attainment (years of schooling rg = -0.46) and reproductive traits (age at first birth rg = -0.58, father's age at death rg = -0.54). Our findings provide a starting point toward identifying critical biosocial risk mechanisms for the development of ASB.

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Figures

Fig. 1
Fig. 1. SNP-based results from the GWAS meta-analysis (N = 85,359) on broad antisocial behavior.
a Manhattan plot of the GWAS meta-analysis, showing the negative log10-transformed p value for each SNP. SNP two-sided p values from a linear model were calculated using METAL [24], weighting SNP associations by sample size. b Regional association plot around chromosome 7:114043159 with functional annotations of SNPs in LD of lead SNP rs12536335 (shown in purple). The plot displays GWAS p value plotted against its chromosomal position, where colors represent linkage disequilibrium and r2 values with the most significantly associated SNP. c The plot displays CADD scores (Combined Annotation Dependent Depletion) and RegulomeDB scores of these SNPs. d PheWAS plot showing the significance of associations of common variation in the FOXP2 gene with a wide range of traits and diagnoses based on MAGMA gene-based tests (with Bonferroni-corrected p value: 1.05e–5), as obtained from GWASAtlas (https://atlas.ctglab.nl).
Fig. 2
Fig. 2. Bar charts illustrating the proportion of variance (incremental R2, or ΔR2) explained by the PRSs.
PRSs are shown for broad ASB associated with childhood ASB in the Dunedin Longitudinal Study (A), with externalizing behavior in the E-Risk Study (B), with Conduct Disorder (C) and Oppositional Defiant Disorder (D) in the Philadelphia Neurodevelopmental Cohort Study, with ASB in the Quebec Longitudinal Study of Children’s Development Study (E), and with time-aggregated ASB in the Quebec Newborn Twin Study (F). Asterisks (*) show statistical significance after applying a Bonferroni correction on the 22 tested phenotypes at p < 0.0023.
Fig. 3
Fig. 3. Significant genetic correlations of ASB with previously published results of other traits and diseases, computed using cross-trait LD score regression in LDHub, Bonferroni-corrected p value: 0.00068 (bars represent 95% confidence intervals).
For traits with significant correlations with ASB in multiple studies (see Supplementary Table 15), we report the most recent study here.

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