Using multi-omics to explore the genetic causal relationship between colorectal cancer and heart failure in gastrointestinal tumors

Background Heart failure (HF) and colorectal cancer are significant public health concerns with substantial morbidity and mortality. Previous studies have indicated a close association between HF and various tumors, including colorectal cancer. Further understanding the potential causal relationship between them could provide insights into their shared pathophysiological mechanisms and inform strategies for prevention and treatment. Methods This study employed a bidirectional Mendelian randomization (MR) approach using genetic variants from large genome-wide association studies (GWAS) as instrumental variables (IVs). The inverse-variance weighted (IVW) method was employed for the MR analysis. Meta-analyses of IVW results from discovery and validation cohorts were performed to enhance the power of detecting causal effects. Sensitivity analyses, including heterogeneity analysis and tests for horizontal pleiotropy, were conducted to test the robustness of the conclusions. Results Results from the discovery cohort suggest HF is associated with an approximately 30% increased risk of colorectal cancer (OR 1.32, 95% CI 1.03-1.69, P=0.025), although this finding did not reach statistical significance in the validation cohort (OR 1.19, 95% CI 0.97-1.46, P=0.090). However, meta-analysis supports HF as a potential risk factor for colorectal cancer (Pooled OR 1.24, 95% CI 1.06-1.25, P=0.007). Reverse MR analysis found no evidence of colorectal cancer increasing HF risk (Pooled OR 1.03, 95% CI 0.99-1.07, P=0.121). Sensitivity analyses (all P>0.05) indicate robustness against heterogeneity and horizontal pleiotropy. Conclusion This comprehensive bidirectional MR study provides genetic evidence supporting a causal link between HF and colorectal cancer. The insights gained enhance understanding of their interconnectedness and may guide future research and clinical practices aimed at mitigating their risks through targeted interventions.