2026-04-17T07:39:33Zhttps://recercat.cat/oai/request

oai:recercat.cat:2445/2288592026-04-14T10:01:47Zcom_2072_1057col_2072_478798col_2072_478916

00925njm 22002777a 4500 dc Chen, Zhishan author Song, Wenqiang author Moreno Aguado, Víctor author Moratalla Navarro, Ferran author 2026-04-13T09:55:40Z 2026-04-13T09:55:40Z 2026-12-01 2026-04-13T09:55:41Z Susceptibility transcription factors (TF) whose DNA bindings are altered by genetic variants regulating colorectal cancer (CRC) risk genes remain poorly defined. Using generalized linear mixed models, we analyze 218 TF ChIP-Seq datasets alongside GWAS data from 100,204 CRC cases and 154,587 controls of East Asian and European ancestries. We identify 51 TFs and TF-cofactor interactions, including VDR-cofactors, as key regulators of CRC risk. Integrating these TF insights with transcriptome-wide association studies (TWAS), we further evaluate associations between genetically predicted gene expression, alternative splicing, and alternative polyadenylation with CRC risk, using RNA-seq data from 364 Asian-ancestry and 707 European-ancestry individuals. Multi-ancestry TWAS identify 222 risk genes, including 95 novel genes and 48 potentially druggable targets. Single-cell analysis provides additional functional evidence supporting ~45% of these genes, and experimental validation confirms oncogenic roles for RHPN2, IRS2, and TXN. Our findings elucidate key TF–gene regulatory networks and uncover novel CRC risk genes. https://hdl.handle.net/2445/228859 Genètica quantitativa Epidemiologia genètica Càncer colorectal Quantitative genetics Genetic epidemiology Colorectal cancer Mixed-model and transcriptome-wide association analyses identify transcription factors and genes associated with colorectal cancer susceptibility