Abstract 6142: Interactions of processed meat and red meat intake with pathway-based polygenic risk scores for colorectal cancer: A novel approach for PRSs construction

Abstract

Abstract Introduction: Colorectal cancer (CRC) is the third most common cancer, and second cause of cancer death worldwide. Established CRC risk factors (E) include high red meat and processed meat intake. Genome-wide association studies (GWAS) have reported over 200 genetic variants associated with CRC risk. We used functional annotation data to identify subsets of GWAS variants within known pathways and constructed corresponding pathway Polygenic Risk Scores (pPRS). We evaluated pPRS by E interactions to determine whether genes within specific pathways interacted with meat intake to impact CRC risk. Methods: A pooled sample of 54,531 CRC controls and 48,260 cases of European ancestry from 27 studies were analyzed. Study-specific quartiles for red and processed meat intake were generated through in-person interviews and structured self-administered questionnaires. Variants were imported to AnnoQ for annotation (n=203) and analyzed for overrepresentation in PANTHER-reported pathways with Fisher’s exact test. Standard approaches were used to compute polygenic risk score weights relating the 203 variants to CRC. The subset of weights corresponding to each of five pathways were then used to compute the corresponding pPRS. Covariate-adjusted logistic regression models evaluated pPRSxE interactions with red meat and processed meat intake. Results: A total of 34 unique variants were overrepresented in five pathways: Apoptosis signaling, Alzheimer disease-presenilin, Wnt-signaling, Gonadotropin-releasing hormone receptor, and TGF-beta signaling. We found a statistically significant interaction between TGF-beta-pPRS and red meat intake (p = 0.0012). Stratified analyses reported a dose-response trend in the red meat and CRC risk association, with decreasing estimates of red meat and CRC risk association, comparing first to fourth quartiles of meat intake, with increasing quartiles of TGF-beta-pPRS: 13% (Q1), 12% (Q2), 7% (Q3), and 6% (Q4). This association remained significant after adjustment for all other variants (p = 0.0013), and all other pPRS with variants that did not overlap with the TGF-beta-pPRS (p = 0.0012). Independent GxE interaction models for individual variants that were included in the TGF-beta pathway showed significant interactions with red meat for rs2337113 (intron SMAD7 gene, Chr18), and rs2208603 (intergenic region BMP5, Chr6) (p = 0.013 & 0.0108, respectively). We did not find significant pPRS x red meat interactions for the other four pathways or with any pPRS x processed meat. Conclusion: This pathway-based interaction analysis revealed a statistical interaction between SNPs in the TGF-beta 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. Citation Format: Joel Sanchez Mendez, Mariana C. Stern, Yubo Fu, John Morrison, Juan P. Lewinger, Eric Kawaguchi, Bryan Queme, Huaiyu Mi, Flora Qu, Ulrike Peters, Li Hsu, Stephen B. Gruber, Li Li, Michelle Cotterchio, Loic Le Marchand, Andrew J. Pellat, Elizabeth A. Platz, W James Gauderman. Interactions of processed meat and red meat intake with pathway-based polygenic risk scores for colorectal cancer: A novel approach for PRSs construction [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6142.