Identification of key indicators of colorectal cancer risk in patients with diabetes mellitus using machine learning and Mendelian randomization

INTRODUCTION: Previous studies have indicated that diabetes mellitus may increase the risk of colorectal cancer (CRC), yet the precise associationremains unclear. To identify critical clinical predictors of CRC risk in patients with type 2 diabetes mellitus (T2DM) using machinelearning (ML) and to subsequently evaluate their causal relationship with CRC via Mendelian randomization (MR) analysis. MATERIAL AND METHODS: A retrospective cohort design was adopted, analyzing clinical records from patients with T2DM and CRC and from those with T2DM alone. Significant predictors were determined using univariate and multivariate Cox regression analyses. Four MLmodels were developed, with essential indicators defined by the overlap of top-ranked clinical variables and risk factors. Mendelian randomizationanalysis was then applied to assess causality between the key indicators (exposures) and CRC (outcome), supplemented bysensitivity tests and Steiger analysis. Reverse MR analysis was conducted to examine potential reverse causality between CRC (exposure)and the identified indicators (outcomes). RESULTS: Univariate and multivariate Cox regression revealed that age [p < 0.05, hazard ratio (HR) = 1.041, 95% confidence interval(CI) = 1.022-1.062] and hemoglobin A1c (HbA1c, p < 0.05, HR = 1.176, 95% CI = 1.094-1.264) were significant risk factors. Logistic regressionwas ultimately identified as the most suitable model, from which two key indicators (age and HbA1c) were derived. Mendelianrandomization analysis demonstrated a causal effect of HbA1c on CRC, confirming HbA1c as a risk factor [odds ratio (OR) = 1.14, 95%CI = 1.01-1.28, p = 0.0336]. Sensitivity analyses and Steiger testing supported the robustness and directionality of these findings. Notably,reverse MR analysis indicated no significant causal effect of CRC on HbA1c [p inverse variance weighted = 0.07853). CONCLUSIONS: Age and HbA1c were identified as pivotal indicators, with HbA1c exhibiting a unidirectional causal association with CRC, thereby offering insights for potential therapeutic strategies.