TY - JOUR
T1 - Integrative Multi-omics Analysis of Childhood Aggressive Behavior
AU - Hagenbeek, Fiona A.
AU - van Dongen, Jenny
AU - Pool, René
AU - Roetman, Peter J.
AU - Harms, Amy C.
AU - Hottenga, Jouke Jan
AU - Kluft, Cornelis
AU - Colins, Olivier F.
AU - van Beijsterveldt, Catharina E.M.
AU - Fanos, Vassilios
AU - Ehli, Erik A.
AU - Hankemeier, Thomas
AU - Vermeiren, Robert R.J.M.
AU - Bartels, Meike
AU - Déjean, Sébastien
AU - Boomsma, Dorret I.
N1 - Publisher Copyright:
© 2022, The Author(s).
PY - 2023/3
Y1 - 2023/3
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.
AB - 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.
KW - Childhood aggression
KW - DNA methylation
KW - Genetic nurturing
KW - Metabolomics
KW - Multi-omics
KW - Polygenic scores
UR - https://www.scopus.com/pages/publications/85141470826
U2 - 10.1007/s10519-022-10126-7
DO - 10.1007/s10519-022-10126-7
M3 - Article
C2 - 36344863
AN - SCOPUS:85141470826
SN - 0001-8244
VL - 53
SP - 101
EP - 117
JO - Behavior Genetics
JF - Behavior Genetics
IS - 2
ER -