Genomic influences on self-reported childhood maltreatment

• Authors: Shareefa Dalvie, University of Cape Town; Adam X. Maihofer, University of California San Diego; Jonathan R. I. Coleman, Kings College London; Bekh Bradley-Davino, Emory University; Gerome Breen, Kings College London; Leslie Brick, Emory University; Chia-Yen Chen, Massachusetts General Hospital; Karmel W. Choi, Harvard University; Laramie E. Duncan, Stanford University; Kerry Ressler, Emory University
• Journal Title: Translational Psychiatry
• Volume: Volume 10, Number 1
• Publisher: Nature Publishing Group | 2020-01-27, Pages 38-38
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.1038/s41398-020-0706-0
• Subjects: Biology, Genetics; Psychology, Psychobiology; Psychology, Developmental; Psychology, Behavioral
• Keywords: Science & Technology; Life Sciences & Biomedicine; Psychiatry; Gene environment correlation; Adult depression; Major depression; Wide association; Adversity; Metaanalysis; Disorder; Trauma; Health; Experiences

Abstract

Childhood maltreatment is highly prevalent and serves as a risk factor for mental and physical disorders. Self-reported childhood maltreatment appears heritable, but the specific genetic influences on this phenotype are largely unknown. The aims of this study were to (1) identify genetic variation associated with self-reported childhood maltreatment, (2) estimate SNP-based heritability (h2snp), (3) assess predictive value of polygenic risk scores (PRS) for childhood maltreatment, and (4) quantify genetic overlap of childhood maltreatment with mental and physical health-related phenotypes, and condition the top hits from our analyses when such overlap is present. Genome-wide association analysis for childhood maltreatment was undertaken, using a discovery sample from the UK Biobank (UKBB) (n = 124,000) and a replication sample from the Psychiatric Genomics Consortium-posttraumatic stress disorder group (PGC-PTSD) (n = 26,290). h2snp for childhood maltreatment and genetic correlations with mental/physical health traits were calculated using linkage disequilibrium score regression. PRS was calculated using PRSice and mtCOJO was used to perform conditional analysis. Two genome-wide significant loci associated with childhood maltreatment (rs142346759, p = 4.35 × 10−8, FOXP1; rs10262462, p = 3.24 × 10−8, FOXP2) were identified in the discovery dataset but were not replicated in PGC-PTSD. h2snp for childhood maltreatment was ~6% and the PRS derived from the UKBB was significantly predictive of childhood maltreatment in PGC-PTSD (r2 = 0.0025; p = 1.8 × 10−15). The most significant genetic correlation of childhood maltreatment was with depressive symptoms (rg = 0.70, p = 4.65 × 10−40), although we show evidence that our top hits may be specific to childhood maltreatment. This is the first large-scale genetic study to identify specific variants associated with self-reported childhood maltreatment. Speculatively, FOXP genes might influence externalizing traits and so be relevant to childhood maltreatment. Alternatively, these variants may be associated with a greater likelihood of reporting maltreatment. A clearer understanding of the genetic relationships of childhood maltreatment, including particular abuse subtypes, with a range of phenotypes, may ultimately be useful in in developing targeted treatment and prevention strategies.