Clonal Hematopoiesis of Indeterminate Potential (CHIP) mutations in patients with coronary artery disease

Background Coronary artery disease (CAD) remains a leading cause of morbidity and mortality worldwide. Clonal hematopoiesis of indeterminate potential (CHIP) has been implicated in atherosclerosis through inflammation and immune dysregulation. CHIP mutations in genes such as DNMT3A, JAK2, ASXL1, and TET2 have been associated with an increased risk of cardiovascular events. However, their exact contribution to CAD pathogenesis remains incompletely understood. Objective This study aims to investigate the prevalence of CHIP mutations in CAD patients and assess their potential association with disease severity and clinical outcomes. Methods A case-control study was conducted with 131 CAD patients and 131 age- and gender-matched controls. DNA was extracted from peripheral blood samples and analyzed for CHIP mutations using polymerase chain reaction (PCR) and Sanger sequencing. Key biochemical markers, including hemoglobin, lipid profiles, and inflammatory markers such as high-sensitivity C-reactive protein (hsCRP) and lipoprotein(a) [Lp(a)], were measured. In-silico analysis was performed to explore molecular interactions among DNMT3A, JAK2, ASXL1, and TET2. Results 1. Mutation Analysis: Two missense mutations in DNMT3A were identified in CAD patients, while no mutations were detected in controls. 2. Biochemical Parameters: CAD patients exhibited significantly lower hemoglobin levels (12.4 ± 2.4 g/dL) compared to controls (13.9 ± 1.7 g/dL, p < 0.05). 3. Lipid Profile: Lower total cholesterol, high-density lipoprotein (HDL), and low-density lipoprotein (LDL) levels were observed in CAD patients. 4. Renal Function: Higher blood urea nitrogen (BUN), creatinine, and uric acid levels were noted in CAD patients. 5. Inflammatory Markers: Elevated hsCRP and Lp(a) levels correlated with the presence of CHIP mutations, suggesting an inflammatory link between CHIP and CAD progression. 6. In-Silico Analysis: Molecular interaction studies indicated a potential regulatory network among DNMT3A, TET2, JAK2, and ASXL1, which may contribute to CAD pathogenesis. Conclusion This study provides evidence supporting the role of CHIP mutations, particularly DNMT3A, in CAD pathogenesis. The findings highlight the potential of CHIP mutations as biomarkers for CAD risk assessment and suggest that anti-inflammatory interventions targeting CHIP-related pathways could be explored as therapeutic strategies. Future Direction: Further large-scale studies using next-generation sequencing (NGS) are needed to comprehensively map CHIP mutations and validate their association with CAD outcomes. Prospective trials evaluating anti-inflammatory therapies such as colchicine in CHIP-positive patients could provide insights into novel treatment strategies.