TY - JOUR
T1 - A statistical method for image-mediated association studies discovers genes and pathways associated with four brain disorders
AU - He, Jingni
AU - Antonyan, Lilit
AU - Zhu, Harold
AU - Ardila, Karen
AU - Li, Qing
AU - Enoma, David
AU - Zhang, William
AU - Liu, Andy
AU - Chekouo, Thierry
AU - Cao, Bo
AU - MacDonald, M. Ethan
AU - Arnold, Paul D.
AU - Long, Quan
N1 - Publisher Copyright:
© 2023 American Society of Human Genetics
PY - 2024/1/4
Y1 - 2024/1/4
N2 - Brain imaging and genomics are critical tools enabling characterization of the genetic basis of brain disorders. However, imaging large cohorts is expensive and may be unavailable for legacy datasets used for genome-wide association studies (GWASs). Using an integrated feature selection/aggregation model, we developed an image-mediated association study (IMAS), which utilizes borrowed imaging/genomics data to conduct association mapping in legacy GWAS cohorts. By leveraging the UK Biobank image-derived phenotypes (IDPs), the IMAS discovered genetic bases underlying four neuropsychiatric disorders and verified them by analyzing annotations, pathways, and expression quantitative trait loci (eQTLs). A cerebellar-mediated mechanism was identified to be common to the four disorders. Simulations show that, if the goal is identifying genetic risk, our IMAS is more powerful than a hypothetical protocol in which the imaging results were available in the GWAS dataset. This implies the feasibility of reanalyzing legacy GWAS datasets without conducting additional imaging, yielding cost savings for integrated analysis of genetics and imaging.
AB - Brain imaging and genomics are critical tools enabling characterization of the genetic basis of brain disorders. However, imaging large cohorts is expensive and may be unavailable for legacy datasets used for genome-wide association studies (GWASs). Using an integrated feature selection/aggregation model, we developed an image-mediated association study (IMAS), which utilizes borrowed imaging/genomics data to conduct association mapping in legacy GWAS cohorts. By leveraging the UK Biobank image-derived phenotypes (IDPs), the IMAS discovered genetic bases underlying four neuropsychiatric disorders and verified them by analyzing annotations, pathways, and expression quantitative trait loci (eQTLs). A cerebellar-mediated mechanism was identified to be common to the four disorders. Simulations show that, if the goal is identifying genetic risk, our IMAS is more powerful than a hypothetical protocol in which the imaging results were available in the GWAS dataset. This implies the feasibility of reanalyzing legacy GWAS datasets without conducting additional imaging, yielding cost savings for integrated analysis of genetics and imaging.
KW - GWAS
KW - cerebellum
KW - image-derived phenotypes
KW - image-mediated association study
KW - neuropsychiatric disorders
UR - http://www.scopus.com/inward/record.url?scp=85181159424&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85181159424&partnerID=8YFLogxK
U2 - 10.1016/j.ajhg.2023.11.006
DO - 10.1016/j.ajhg.2023.11.006
M3 - Article
C2 - 38118447
AN - SCOPUS:85181159424
SN - 0002-9297
VL - 111
SP - 48
EP - 69
JO - American Journal of Human Genetics
JF - American Journal of Human Genetics
IS - 1
ER -