Identification and Validation of Aging-related Genes in the Comorbidity of Coronary Heart Disease and Colorectal Cancer

Introduction: Coronary heart disease (CHD) and colorectal cancer (CRC) are common comorbidities among the elderly population. However, there is a lack of clinical prediction tools that utilize aging-related genes to forecast the onset and outcomes of these conditions in elderly patients. Methods: Gene expression data related to CHD and CRC were examined using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) of the National Center for Biotechnology Information (NCBI). The differentially expressed genes (DEGs) associated with aging, CHD, and CRC were identified. Predictive models for CHD diagnosis and prognostic risk prediction for CRC were constructed using the LASSO, Random Forest, and SVM-RFE techniques. Nomogram models have been developed to assess the prognosis of patients with CRC. Drug repositioning was performed to evaluate the shared predictive genes for diagnosing CHD and predicting CRC outcomes. Results: MYL9 and ULBP2 were identified as DEGs associated with aging, CHD, and CRC. Predictive models for CHD diagnosis and CRC risk prediction have been constructed. We developed a nomogram model to assess CRC prognosis and to identify MYL9 and ULBP2 as predictive genes. We assessed the potential of MYL9 and ULBP2 as therapeutic targets in elderly patients with CHD and CRC using a drug repositioning analysis. Conclusion: We identified MYL9 and ULBP2 as aging-related markers for the diagnosis of CHD and the prognosis of CRC. In addition, we developed clinical tool models to facilitate the diagnosis of CHD and predict the prognosis of CRC, specifically in the elderly population.