TY - JOUR
T1 - The Genetic and Neural Substrates of Externalizing Behavior
AU - Baselmans, Bart M. L.
AU - Hammerschlag, Anke R.
AU - Noordijk, Stephany
AU - Ip, Hill F.
AU - van der Zee, Matthijs D.
AU - de Geus, Eco J.
AU - Abdellaoui, Abdel
AU - Treur, Jorien L.
AU - van 't Ent, Dennis
N1 - © 2021 The Authors.
PY - 2022/10/1
Y1 - 2022/10/1
N2 - Background: To gain more insight into the biological factors that mediate vulnerability to display externalizing behaviors, we leveraged genome-wide association study summary statistics on 13 externalizing phenotypes. Methods: After data classification based on genetic resemblance, we performed multivariate genome-wide association meta-analyses and conducted extensive bioinformatic analyses, including genetic correlation assessment with other traits, Mendelian randomization, and gene set and gene expression analyses. Results: The genetic data could be categorized into disruptive behavior (DB) and risk-taking behavior (RTB) factors, and subsequent genome-wide association meta-analyses provided association statistics for DB and RTB (Neff = 523,150 and 1,506,537, respectively), yielding 50 and 257 independent genetic signals. The statistics of DB, much more than RTB, signaled genetic predisposition to adverse cognitive, mental health, and personality outcomes. We found evidence for bidirectional causal influences between DB and substance use behaviors. Gene set analyses implicated contributions of neuronal cell development (DB/RTB) and synapse formation and transcription (RTB) mechanisms. Gene-brain mapping confirmed involvement of the amygdala and hypothalamus and highlighted other candidate regions (cerebellar dentate, cuneiform nucleus, claustrum, paracentral cortex). At the cell-type level, we noted enrichment of glutamatergic neurons for DB and RTB. Conclusions: This bottom-up, data-driven study provides new insights into the genetic signals of externalizing behaviors and indicates that commonalities in genetic architecture contribute to the frequent co-occurrence of different DBs and different RTBs, respectively. Bioinformatic analyses supported the DB versus RTB categorization and indicated relevant biological mechanisms. Generally similar gene-brain mappings indicate that neuroanatomical differences, if any, escaped the resolution of our methods.
AB - Background: To gain more insight into the biological factors that mediate vulnerability to display externalizing behaviors, we leveraged genome-wide association study summary statistics on 13 externalizing phenotypes. Methods: After data classification based on genetic resemblance, we performed multivariate genome-wide association meta-analyses and conducted extensive bioinformatic analyses, including genetic correlation assessment with other traits, Mendelian randomization, and gene set and gene expression analyses. Results: The genetic data could be categorized into disruptive behavior (DB) and risk-taking behavior (RTB) factors, and subsequent genome-wide association meta-analyses provided association statistics for DB and RTB (Neff = 523,150 and 1,506,537, respectively), yielding 50 and 257 independent genetic signals. The statistics of DB, much more than RTB, signaled genetic predisposition to adverse cognitive, mental health, and personality outcomes. We found evidence for bidirectional causal influences between DB and substance use behaviors. Gene set analyses implicated contributions of neuronal cell development (DB/RTB) and synapse formation and transcription (RTB) mechanisms. Gene-brain mapping confirmed involvement of the amygdala and hypothalamus and highlighted other candidate regions (cerebellar dentate, cuneiform nucleus, claustrum, paracentral cortex). At the cell-type level, we noted enrichment of glutamatergic neurons for DB and RTB. Conclusions: This bottom-up, data-driven study provides new insights into the genetic signals of externalizing behaviors and indicates that commonalities in genetic architecture contribute to the frequent co-occurrence of different DBs and different RTBs, respectively. Bioinformatic analyses supported the DB versus RTB categorization and indicated relevant biological mechanisms. Generally similar gene-brain mappings indicate that neuroanatomical differences, if any, escaped the resolution of our methods.
KW - Disruptive behavior
KW - Externalizing behavior
KW - GWAS
KW - Gene set analysis
KW - Genetic correlation
KW - Mendelian randomization
KW - N-GWAMA
KW - Risk-taking behavior
KW - Stratified LD-score regression
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85148553338&origin=inward
UR - https://www.ncbi.nlm.nih.gov/pubmed/36324656
UR - https://pure.hva.nl/ws/files/45478315/1-s2.0-S2667174321001154-mmc1.pdf
UR - https://pure.hva.nl/ws/files/45478317/1-s2.0-S2667174321001154-mmc2.xlsx
U2 - https://doi.org/10.1016/j.bpsgos.2021.09.007
DO - https://doi.org/10.1016/j.bpsgos.2021.09.007
M3 - Article
C2 - 36324656
SN - 2667-1743
VL - 2
SP - 389
EP - 399
JO - Biological Psychiatry Global Open Science
JF - Biological Psychiatry Global Open Science
IS - 4
ER -