The predictive value of C-reactive protein-triglyceride-glucose index and clonal hematopoiesis of indeterminate potential among patients with STEMI---from a prospective cohort study

Background and Aim Acute coronary syndrome (ACS) remains a leading cause of global morbidity and mortality despite advances in primary percutaneous coronary intervention (PCI). Current risk stratification tools lack precision in predicting recurrent cardiovascular events, highlighting the need for novel biomarkers. This study aimed to evaluate the synergistic prognostic utility of clonal hematopoiesis of indeterminate potential (CHIP) mutations and C-reactive protein-triglyceride-glucose index (CTI) in ACS patients undergoing PCI. Methods In this prospective, longitudinal cohort study, we enrolled ACS patients and performed deep targeted sequencing of 42 CHIP-associated genes alongside CTI quantification. Results In a prospective cohort of 1,388 ACS patients, CTI combined with CHIP identified a high-risk phenotype. Patients with high CTI (≥cutoff) and any CHIP mutation had a significantly higher incidence of major adverse cardiovascular events (MACE) compared to those with no CHIP (58.1% vs. 35.9%, p=0.020). Multivariable analysis revealed that in the low-CTI cohort, CHIP mutations—particularly common CHIP, TET2, and ASXL1 mutations—were independently associated with increased all-cause mortality (adjusted HR up to 1.94 for common CHIP mutation, 95% CI 1.09–3.45, p=0.024). Conversely, no significant association between CHIP and mortality was observed in the high-CTI cohort. When analyzed as a continuous parameter, a higher CTI per standard deviation increment was an independent predictor of MACE. This association was significantly modified by the presence of CHIP mutations, type 2 diabetes (p for interaction=0.022), and chronic kidney disease (p for interaction=0.014). Kaplan-Meier analysis confirmed significantly worse survival and higher mortality (log-rank p<0.001), MACE rates (log-rank p=0.023)and cardiac death (log-rank p=0.019) in patients with concomitant high CTI and CHIP mutations. Conclusion Our findings advocate for integrating CHIP and CTI into risk models to guide personalized post-PCI management, while future studies should explore targeted anti-inflammatory therapies for CHIP-positive ACS patients and validate these biomarkers in diverse populations.