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Background <p>Despite significantPlease check if article title presented correctly. advances made by genome-wide association studies (GWAS) in the genetic exploration of tumors such as prostate cancer (PCa), the precise pathogenic genes and underlying biological mechanisms of PCa remain unclear.</p> Methods <p>To address this complex issue, we used a cross-tissue transcriptome-wide association study (TWAS) strategy within the Unified Test for Molecular Signatures (UTMOST) framework. This approach integrated GWAS summary statistics from 122,188 PCa patients and 604,640 controls with extensive gene expression data from the Genotype-Tissue Expression (GTEx) project. We validated key gene discoveries using three complementary methods: FUSION, FOCUS, and Multi-marker Analysis of GenoMic Annotation (MAGMA). Additionally, MAGMA was used to examine the tissue and functional level enrichment of single nucleotide polymorphisms (SNPs) associated with PCa. Conditional and joint analysis, as well as fine mapping techniques, were employed to deepen our understanding of PCa’s genetic architecture. To establish causal relationships, we conducted Mendelian randomization analysis, while colocalization analysis was used to identify potential shared SNPs between key genes and PCa risk.</p> Results <p>Through the comprehensive application of four TWAS methods, we identified 13 potential susceptibility genes closely associated with PCa risk. Mendelian randomization analysis confirmed direct causal links between the <i>WDPCP</i>, <i>RIF1</i>, <i>POLI</i>, <i>HAAO</i>, <i>GGCX</i> and <i>CASP10</i> genes and PCa. Colocalization analysis further revealed that <i>CASP10</i> (rs6735656), <i>GGCX</i> (rs2028900) may share genetic signals between GWAS and expression quantitative trait loci (eQTL), indicating common pathways in PCa pathogenesis.</p> Conclusion <p>This study identified 13 new susceptibility genes significantly associated with PCa risk and provided new insights into the genetic basis of PCa, contributing to a more comprehensive understanding of its complex genetic structure.</p>

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Cross-tissue transcriptome-wide association studies identify genetic susceptibility genes for prostate cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月4日

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  • Jingqi Hua,
  • Yichen Qian,
  • Yuanchen Lu,
  • Qijie Zhang,
  • Hongliang Que,
  • Tengyue Zeng,
  • Quan Li,
  • Junpeng Deng,
  • Jianjun Xie

摘要

Background

Despite significantPlease check if article title presented correctly. advances made by genome-wide association studies (GWAS) in the genetic exploration of tumors such as prostate cancer (PCa), the precise pathogenic genes and underlying biological mechanisms of PCa remain unclear.

Methods

To address this complex issue, we used a cross-tissue transcriptome-wide association study (TWAS) strategy within the Unified Test for Molecular Signatures (UTMOST) framework. This approach integrated GWAS summary statistics from 122,188 PCa patients and 604,640 controls with extensive gene expression data from the Genotype-Tissue Expression (GTEx) project. We validated key gene discoveries using three complementary methods: FUSION, FOCUS, and Multi-marker Analysis of GenoMic Annotation (MAGMA). Additionally, MAGMA was used to examine the tissue and functional level enrichment of single nucleotide polymorphisms (SNPs) associated with PCa. Conditional and joint analysis, as well as fine mapping techniques, were employed to deepen our understanding of PCa’s genetic architecture. To establish causal relationships, we conducted Mendelian randomization analysis, while colocalization analysis was used to identify potential shared SNPs between key genes and PCa risk.

Results

Through the comprehensive application of four TWAS methods, we identified 13 potential susceptibility genes closely associated with PCa risk. Mendelian randomization analysis confirmed direct causal links between the WDPCP, RIF1, POLI, HAAO, GGCX and CASP10 genes and PCa. Colocalization analysis further revealed that CASP10 (rs6735656), GGCX (rs2028900) may share genetic signals between GWAS and expression quantitative trait loci (eQTL), indicating common pathways in PCa pathogenesis.

Conclusion

This study identified 13 new susceptibility genes significantly associated with PCa risk and provided new insights into the genetic basis of PCa, contributing to a more comprehensive understanding of its complex genetic structure.