Mendez Joel Sanchez, Queme Bryan, Fu Yubo, Morrison John, Lewinger Juan P, Kawaguchi Eric, Mi Huaiyu, Obón-Santacana Mireia, Moratalla-Navarro Ferran, Martín Vicente, Moreno Victor, Lin Yi, Bien Stephanie A, Qu Conghui, Su Yu-Ru, White Emily, Harrison Tabitha A, Huyghe Jeroen R, Tangen Catherine M, Newcomb Polly A, Phipps Amanda I, Thomas Claire E, Conti David V, Wang Jun, Platz Elizabeth A, Keku Temitope O, Newton Christina C, Um Caroline Y, Kundaje Anshul, Shcherbina Anna, Murphy Neil, Gunter Marc J, Dimou Niki, Papadimitriou Nikos, Bézieau Stéphane, van Duijnhoven Franzel Jb, Männistö Satu, Rennert Gad, Wolk Alicja, Hoffmeister Michael, Brenner Hermann, Chang-Claude Jenny, Tian Yu, Le Marchand Loïc, Cotterchio Michelle, Tsilidis Konstantinos K, Bishop D Timothy, Melaku Yohannes Adama, Lynch Brigid M, Buchanan Daniel D, Ulrich Cornelia M, Ose Jennifer, Peoples Anita R, Pellatt Andrew J, Li Li, Devall Matthew Am, Campbell Peter T, Albanes Demetrius, Weinstein Stephanie J, Berndt Sonja I, Gruber Stephen B, Ruiz-Narvaez Edward, Song Mingyang, Joshi Amit D, Drew David A, Petrick Jessica L, Chan Andrew T, Giannakis Marios, Hsu Li, Peters Ulrike, Gauderman W James, Stern Mariana C
Department of Population and Public Health Sciences & USC Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
Division of Biostatistics, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, USA.
medRxiv. 2025 Jun 16:2025.06.13.25329599. doi: 10.1101/2025.06.13.25329599.
High intake of red and/or processed meat are established colorectal cancer (CRC) risk factors. Genome-wide association studies (GWAS) have reported 204 variants (G) associated with CRC risk. We used functional annotation data to identify subsets of variants within known pathways and constructed pathway-based Polygenic Risk Scores (pPRS) to model pPRS x environment (E) interactions.
A pooled sample of 30,812 cases and 40,504 CRC controls of European ancestry from 27 studies were analyzed. Quantiles for red and processed meat intake were constructed. The 204 GWAS variants were annotated to genes with AnnoQ and assessed for overrepresentation in PANTHER-reported pathways. pPRS's were constructed from significantly overrepresented pathways. Covariate-adjusted logistic regression models evaluated pPRSxE interactions with red or processed meat intake in relation to CRC risk.
A total of 30 variants were overrepresented in four pathways: Alzheimer disease-presenilin, Cadherin/WNT-signaling, Gonadotropin-releasing hormone receptor, and TGF-β signaling. We found a significant interaction between TGF-β-pPRS and red meat intake (p = 0.003). When variants in the TGF-β pathway were assessed, significant interactions with red meat for rs2337113 (intron gene, Chr18), and rs2208603 (intergenic region , Chr6) (p = 0.013 & 0.011, respectively) were observed. We did not find evidence of pPRS x red meat interactions for other pathways or with processed meat.
This pathway-based interaction analysis revealed a significant interaction between variants in the TGF-β pathway and red meat consumption that impacts CRC risk.
These findings shed light into the possible mechanistic link between CRC risk and red meat consumption.
大量摄入红肉和/或加工肉类是已确定的结直肠癌（CRC）风险因素。全基因组关联研究（GWAS）报告了204个与CRC风险相关的变异（G）。我们使用功能注释数据来识别已知途径内的变异子集，并构建基于途径的多基因风险评分（pPRS）以模拟pPRS与环境（E）的相互作用。
对来自27项研究的30812例欧洲血统的CRC病例和40504例对照的汇总样本进行分析。构建红肉和加工肉类摄入量的分位数。使用AnnoQ将204个GWAS变异注释到基因，并评估其在PANTHER报告的途径中的过度代表性。从显著过度代表性的途径构建pPRS。协变量调整的逻辑回归模型评估pPRS与红肉或加工肉类摄入量与CRC风险的相互作用。
共有30个变异在四个途径中过度代表性：阿尔茨海默病-早老素、钙黏蛋白/WNT信号传导、促性腺激素释放激素受体和TGF-β信号传导。我们发现TGF-β-pPRS与红肉摄入量之间存在显著相互作用（p = 0.003）。当评估TGF-β途径中的变异时，观察到rs2337113（内含子基因，Chr18）和rs2208603（基因间区域，Chr6）与红肉有显著相互作用（分别为p = 0.013和0.011）。我们未发现其他途径或与加工肉类的pPRS与红肉相互作用的证据。
这种基于途径的相互作用分析揭示了TGF-β途径中的变异与红肉消费之间的显著相互作用，这会影响CRC风险。
这些发现揭示了CRC风险与红肉消费之间可能的机制联系。
