Abstract 817: Probing the diabetes - colorectal cancer link using gene - environment interaction analyses

Abstract

Abstract Background: Type 2 diabetes mellitus (T2D) is an established risk factor for colorectal cancer. However, the mechanisms underlying this relationship are unclear and it is not known if the association is modified by genetic variants. To provide insights into the molecular pathways potentially linking diabetes and colorectal cancer, we undertook a large-scale gene-environment interaction analysis (GxE). Methods: We tested multiplicative statistical interactions between approximately 7 million common (allele frequency >1%) genetic variants and T2D status in 31,529 colorectal cancer cases and 42,861 controls of European ancestry from 3 genetic consortia (GECCO/CCFR/CORECT). Statistical methods included traditional case-control logistic regression, case-only analyses, joint tests (2df/3df), and two-step approaches. We also explored additive and multiplicative interactions between polygenic risk score (PRS) of the known genome-wide significant loci for colorectal cancer and T2D. Results: Overall, T2D was positively associated with colorectal cancer risk [odds ratio [OR]: 1.25 (95% confidence interval [CI]: 1.14-1.36)]. A statistically significant interaction was identified between T2D status and an intronic variant in LRCH1 (rs9526201) and colorectal cancer risk using the 2-d.f. joint test (p-value:1.44x10-8). A statistically significant additive scale interaction between PRS for colorectal cancer and T2D was found (p-value: 1.8x10-10) such that the observed risk of developing colorectal cancer for individuals with T2D and a 1 standard deviation (SD) higher increment of PRS compared to non-diabetics with the lowest PRS was 0.184 more than if there was no interaction between T2D and PRS. Conclusion: These results suggest that variation in a gene related to immune function may modify the association of T2D with colorectal cancer and potentially provide novel insights into the biology underlying this relationship. Furthermore, our data show that genetic risk prediction models for CRC may need to consider non-genetic risk factors. Citation Format: Niki Dimou, Andre E. Kim, Orlagh Flanagan, Neil Murphy, Emmanouil Bouras, Peter T. Campbell, Graham Casey, Steven Gallinger, Stephen B. Gruber, Li Hsu, Mark A. Jenkins, Yi Lin, Victor Moreno, Conghui Qu, Edward Ruiz-Narvaez, Mariana C. Stern, Yu Tian, Kostas Tsilidis, W. James Gauderman, Marc J. Gunter, Ulrike Peters. Probing the diabetes - colorectal cancer link using gene - environment interaction analyses [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 817.