Integrative Multi-omics Analysis of Childhood Aggressive Behavior

Hagenbeek, Fiona A;van Dongen, Jenny;Pool, René;Roetman, Peter J;Harms, Amy C;Hottenga, Jouke Jan;Kluft, Cornelis;Colins, Olivier F;van Beijsterveldt, Catharina E M;Fanos, Vassilios;Ehli, Erik A;Hankemeier, Thomas;Vermeiren, Robert R J M;Bartels, Meike;Déjean, Sébastien;Boomsma, Dorret I

2022-01-01

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Abstract

This study introduces and illustrates the potential of an integrated multi-omics approach in investigating the underlying biology of complex traits such as childhood aggressive behavior. In 645 twins (cases = 42%), we trained single- and integrative multi-omics models to identify biomarkers for subclinical aggression and investigated the connections among these biomarkers. Our data comprised transmitted and two non-transmitted polygenic scores (PGSs) for 15 traits, 78,772 CpGs, and 90 metabolites. The single-omics models selected 31 PGSs, 1614 CpGs, and 90 metabolites, and the multi-omics model comprised 44 PGSs, 746 CpGs, and 90 metabolites. The predictive accuracy for these models in the test (N = 277, cases = 42%) and independent clinical data (N = 142, cases = 45%) ranged from 43 to 57%. We observed strong connections between DNA methylation, amino acids, and parental non-transmitted PGSs for ADHD, Autism Spectrum Disorder, intelligence, smoking initiation, and self-reported health. Aggression-related omics traits link to known and novel risk factors, including inflammation, carcinogens, and smoking.