TY - JOUR
T1 - Aggregative trans-eQTL analysis detects trait-specific target gene sets in whole blood
AU - Dutta, Diptavo
AU - He, Yuan
AU - Saha, Ashis
AU - Arvanitis, Marios
AU - Battle, Alexis
AU - Chatterjee, Nilanjan
N1 - Publisher Copyright:
© 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - Large scale genetic association studies have identified many trait-associated variants and understanding the role of these variants in the downstream regulation of gene-expressions can uncover important mediating biological mechanisms. Here we propose ARCHIE, a summary statistic based sparse canonical correlation analysis method to identify sets of gene-expressions trans-regulated by sets of known trait-related genetic variants. Simulation studies show that compared to standard methods, ARCHIE is better suited to identify “core”-like genes through which effects of many other genes may be mediated and can capture disease-specific patterns of genetic associations. By applying ARCHIE to publicly available summary statistics from the eQTLGen consortium, we identify gene sets which have significant evidence of trans-association with groups of known genetic variants across 29 complex traits. Around half (50.7%) of the selected genes do not have any strong trans-associations and are not detected by standard methods. We provide further evidence for causal basis of the target genes through a series of follow-up analyses. These results show ARCHIE is a powerful tool for identifying sets of genes whose trans-regulation may be related to specific complex traits.
AB - Large scale genetic association studies have identified many trait-associated variants and understanding the role of these variants in the downstream regulation of gene-expressions can uncover important mediating biological mechanisms. Here we propose ARCHIE, a summary statistic based sparse canonical correlation analysis method to identify sets of gene-expressions trans-regulated by sets of known trait-related genetic variants. Simulation studies show that compared to standard methods, ARCHIE is better suited to identify “core”-like genes through which effects of many other genes may be mediated and can capture disease-specific patterns of genetic associations. By applying ARCHIE to publicly available summary statistics from the eQTLGen consortium, we identify gene sets which have significant evidence of trans-association with groups of known genetic variants across 29 complex traits. Around half (50.7%) of the selected genes do not have any strong trans-associations and are not detected by standard methods. We provide further evidence for causal basis of the target genes through a series of follow-up analyses. These results show ARCHIE is a powerful tool for identifying sets of genes whose trans-regulation may be related to specific complex traits.
UR - http://www.scopus.com/inward/record.url?scp=85134850581&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85134850581&partnerID=8YFLogxK
U2 - 10.1038/s41467-022-31845-9
DO - 10.1038/s41467-022-31845-9
M3 - Article
C2 - 35882830
AN - SCOPUS:85134850581
SN - 2041-1723
VL - 13
JO - Nature communications
JF - Nature communications
IS - 1
M1 - 4323
ER -