Type 2 diabetes and colorectal cancer: genetic causality explored via Mendelian randomization

• Published in: Discover. Oncology 2024-11, Vol.15 (1), p.721-8
• Main Authors: Ke, Qiuhong, Huang, Yongbing, Cheng, Libin, Lin, Chaolin, Zhao, Linhua, Huang, Wulong, Chen, Zhisheng, Xu, Yimin, Huang, Yipiao, Cai, Lanlan, Lin, Bin, Tang, Rui
• Format: Article
• Language: English
• Subjects: Analysis; Cancer Research; Causality; Clinical medicine; Colorectal cancer; Colorectal neoplasms; Confidence intervals; Diabetes; Diabetes mellitus; Genome-wide association study; Genomes; Internal Medicine; Medicine; Medicine & Public Health; Mendelian randomization analysis; Meta-analysis; Molecular Medicine; Oncology; Public health; Radiotherapy; Surgical Oncology; Type 2
• ISSN: 2730-6011; 2730-6011
• DOI: 10.1007/s12672-024-01621-w

Background The global burden of type 2 diabetes (T2D) and colorectal cancer (CRC) continues to rise. Observational studies have suggested a link between T2D and an elevated risk of CRC. However, these studies are often susceptible to confounding factors and reverse causation, leading to inconsistent findings. There is a specific gap in knowledge regarding the causal nature of the relationship between T2D and CRC, which this study aims to address using a more robust approach. To fill this gap, we employed Mendelian randomization (MR), a method that uses genetic variants as instrumental variables (IVs) to infer causality, providing clearer insight into the genetic links between T2D and CRC. Methods A bidirectional MR study was conducted to investigate the causal links between T2D and CRC. Genetic instruments for T2D were derived from two large genome-wide association studies (GWAS) with a total sample size of X individuals, and CRC genetic instruments were obtained from a GWAS with Y individuals. The MR analysis utilized the inverse-variance weighted (IVW) method as the primary analysis, alongside sensitivity analyses such as heterogeneity and pleiotropy analysis to account for potential pleiotropy and bias. Additionally, to enhance the robustness of the findings and minimize the influence of data from different GWAS sources, we performed a meta-analysis of the IVW results. Results The MR analysis and meta-analysis revealed that genetically predicted T2D is associated with an increased risk of CRC (Pooled OR IVW  = 1.07, 95% CI 1.02–1.12, P = 0.003). However, the reverse analysis did not indicate a causal effect of genetically predicted CRC on T2D risk (Pooled OR IVW  = 1.02, 95% CI 0.96–1.09, P = 0.469). Sensitivity analyses supported the robustness of these findings, indicating no evidence of heterogeneity or pleiotropic effects that could bias the results (all P > 0.05). Conclusion Our bidirectional MR study and meta-analysis provide evidence that T2D increases the risk of colorectal cancer. However, there is no evidence to support a reverse causal relationship. These findings highlight the importance of monitoring and managing T2D as part of CRC prevention strategies.