Enhancing the robustness of Mendelian randomization studies: lessons from a two-sample analysis of viral infections and colorectal cancer

Abstract

Abstract This Matters Arising article critically examines the study “Genetic susceptibility association between viral infection and colorectal cancer risk: a two-sample Mendelian randomization analysis” by Li et al., highlighting both its contributions and methodological limitations. Their study employed two-sample Mendelian randomization (MR) to explore potential causal links between viral infections and colorectal cancer (CRC), identifying significant associations with infections such as herpes simplex virus and measles. However, several aspects of the methodology warrant scrutiny, including the relaxation of instrumental variable selection thresholds, the handling of potential pleiotropy, and the interpretation of biologically implausible findings. While leveraging advanced MR techniques such as MR-RAPS, cML, ConMix, and dIVW to address challenges like pleiotropy and weak instruments, the study encountered issues related to heterogeneity, insufficient exploration of biological plausibility, and a lack of detailed reporting on instrumental variable (IV) selection and preprocessing. This Matters Arising calls for more rigorous sensitivity analyses, improved transparency in IV selection criteria and harmonization of genome-wide association study (GWAS) datasets, particularly in addressing differences between self-reported and clinically diagnosed infections. Additionally, the Matters Arising article calls for a deeper exploration of biological mechanisms, such as the role of immune modulation and inflammation, to better interpret the observed associations. By addressing these limitations, future MR studies can enhance methodological rigor, improve reproducibility, and provide more robust insights into the causal pathways linking viral infections to CRC risk.

Keywords

• Mendelian randomization
• Colorectal cancer
• Viral infections
• Instrumental variables
• Genetic epidemiology