Integrative Multi-omics Analysis of Childhood Aggressive Behavior

Behavior Genetics - Tập 53 - Trang 101-117 - 2022
Fiona A. Hagenbeek1,2, Jenny van Dongen1,2,3, René Pool1,2, Peter J. Roetman4, Amy C. Harms5,6, Jouke Jan Hottenga1, Cornelis Kluft7, Olivier F. Colins4,8, Catharina E. M. van Beijsterveldt1, Vassilios Fanos9, Erik A. Ehli10, Thomas Hankemeier5,6, Robert R. J. M. Vermeiren4,11, Meike Bartels1,2, Sébastien Déjean12, Dorret I. Boomsma1,2,3
1Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
2Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
3Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, The Netherlands
4Department of Child and Adolescent Psychiatry, LUMC-Curium, Leiden University Medical Center, Leiden, The Netherlands
5Division of Analytical Biosciences, Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands
6The Netherlands Metabolomics Centre, Leiden, The Netherlands
7Good Biomarker Sciences, Leiden, The Netherlands
8Department Special Needs Education, Ghent University, Ghent, Belgium
9Department of Surgical Sciences, University of Cagliari and Neonatal Intensive Care Unit, Cagliari, Italy
10Avera Institute for Human Genetics, Sioux Falls, USA
11Youz, Parnassia Psychiatric Institute, The Hague, The Netherlands
12Toulouse Mathematics Institute, University of Toulouse, CNRS, Toulouse, France

Tóm tắt

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.

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