TY  - JOUR
PY  - 2022//
TI  - Integrative multi-omics analysis of childhood aggressive behavior
JO  - Behavior genetics
A1  - Hagenbeek, Fiona A.
A1  - van Dongen, Jenny
A1  - Pool, René
A1  - Roetman, Peter J.
A1  - Harms, Amy C.
A1  - Hottenga, Jouke Jan
A1  - Kluft, Cornelis
A1  - Colins, Olivier F.
A1  - van Beijsterveldt, Catharina E. M.
A1  - Fanos, Vassilios
A1  - Ehli, Erik A.
A1  - Hankemeier, Thomas
A1  - Vermeiren, Robert R. J. M.
A1  - Bartels, Meike
A1  - Déjean, Sébastien
A1  - Boomsma, Dorret I.
SP  - ePub
EP  - ePub
VL  - ePub
IS  - ePub
N2  - 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.<p />  <p>Language: en</p>
LA  - en
SN  - 0001-8244
UR  - http://dx.doi.org/10.1007/s10519-022-10126-7
ID  - ref1
ER  -