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Mixed-model and transcriptome-wide association analyses identify transcription factors and genes associated with colorectal cancer susceptibility

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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.

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Nature Communications, 2026, vol. 17, num.1, 1377

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cc-by-nc-nd (c) Chen, Zhishan et al., 2026

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Articles publicats en revistes (Ciències Clíniques)

# metadata.dc.title[].value
Mixed-model and transcriptome-wide association analyses identify transcription factors and genes associated with colorectal cancer susceptibility