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Background <p>Colorectal cancer (CRC) affects approximately 1.9&#xa0;million people globally each year. While CRC development involves complex genetic and environmental interactions, the underlying molecular mechanisms remain incompletely understood. This study integrated multi-omics data to investigate gene-CRC associations across methylation, expression, and protein levels.</p> Methods <p>We obtained summary statistics from methylation QTL (mQTL), expression QTL (eQTL), and protein QTL (pQTL) studies. CRC genetic associations were derived from a meta-analysis of 31 GWAS datasets (100,204 cases, 154,587 controls). Summary data-based Mendelian randomization (SMR) analysis assessed associations between molecular features and CRC risk, followed by colocalization analysis to identify shared causal variants. Functional enrichment analysis was performed using Gene Ontology (GO) and KEGG pathway databases.</p> Results <p>SMR analysis identified 2,387 methylation associations (837 genes) and 707 expression associations with CRC. Integration revealed 158 overlapping genes, with six proteins (CCM2, FTCD, ICAM1, LTA, PCSK7, TNFSF14) validated for CRC association. Four genes—CCM2, FTCD, ICAM1, and TNFSF14—showed consistent effects across expression and protein levels. Higher CCM2 and TNFSF14 levels were protective, while higher FTCD and ICAM1 levels increased CRC risk. Colocalization analysis confirmed that CCM2 (PPH4 = 0.857) and ICAM1 (PPH4 = 0.812) share genetic variants with CRC. Functional enrichment analysis revealed significant involvement in immune-related processes, including interferon-gamma signaling, antigen presentation, and NF-kappa B pathway, as well as cell adhesion and endoplasmic reticulum functions. </p> Conclusions <p>Our multi-omics integration identified CCM2 and ICAM1 as genes causally associated with CRC risk through shared genetic architecture. Functional analysis highlighted their roles in immune regulation and cell adhesion processes. These findings enhance understanding of CRC pathogenesis and highlight potential therapeutic targets.</p>

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Integrative multi-omics analysis identifies key genes and colocalized signals associated with colorectal cancer risk

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月25日

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  • Lianheng Xia,
  • Jiaxin Wang,
  • Jie Gao,
  • Xuan Cui,
  • Meiyu Song,
  • Wukun Ding,
  • Jiayuan Zhang

摘要

Background

Colorectal cancer (CRC) affects approximately 1.9 million people globally each year. While CRC development involves complex genetic and environmental interactions, the underlying molecular mechanisms remain incompletely understood. This study integrated multi-omics data to investigate gene-CRC associations across methylation, expression, and protein levels.

Methods

We obtained summary statistics from methylation QTL (mQTL), expression QTL (eQTL), and protein QTL (pQTL) studies. CRC genetic associations were derived from a meta-analysis of 31 GWAS datasets (100,204 cases, 154,587 controls). Summary data-based Mendelian randomization (SMR) analysis assessed associations between molecular features and CRC risk, followed by colocalization analysis to identify shared causal variants. Functional enrichment analysis was performed using Gene Ontology (GO) and KEGG pathway databases.

Results

SMR analysis identified 2,387 methylation associations (837 genes) and 707 expression associations with CRC. Integration revealed 158 overlapping genes, with six proteins (CCM2, FTCD, ICAM1, LTA, PCSK7, TNFSF14) validated for CRC association. Four genes—CCM2, FTCD, ICAM1, and TNFSF14—showed consistent effects across expression and protein levels. Higher CCM2 and TNFSF14 levels were protective, while higher FTCD and ICAM1 levels increased CRC risk. Colocalization analysis confirmed that CCM2 (PPH4 = 0.857) and ICAM1 (PPH4 = 0.812) share genetic variants with CRC. Functional enrichment analysis revealed significant involvement in immune-related processes, including interferon-gamma signaling, antigen presentation, and NF-kappa B pathway, as well as cell adhesion and endoplasmic reticulum functions.

Conclusions

Our multi-omics integration identified CCM2 and ICAM1 as genes causally associated with CRC risk through shared genetic architecture. Functional analysis highlighted their roles in immune regulation and cell adhesion processes. These findings enhance understanding of CRC pathogenesis and highlight potential therapeutic targets.