Background and Aims Residual cardiovascular risk remains substantial in patients with coronary artery disease (CAD) despite optimal secondary prevention. Clonal haematopoiesis of indeterminate potential (CHIP) contributes causally to this risk but requires sequencing for detection. Plasma infrared molecular fingerprinting (IMF), a spectroscopy-based assay, was evaluated as a sequencing-free tool for residual risk stratification and CHIP-aligned phenotyping. Methods The discovery cohort included 1341 patients with angiographically confirmed CAD (mean age 73 years, 76% male) followed for up to 10.7 years. Plasma IMF spectra, comprehensive clinical data, and targeted sequencing of 13 CHIP driver genes were measured. Penalized Cox models using IMF features were benchmarked against the guideline-recommended SMART2 score. Model performance was assessed by discrimination, reclassification, calibration, and decision curve analyses. External validation was performed in three independent cohorts (PRECAD2, 474 individuals; KORA, 3044 individuals; Lasers4Life, 2123 individuals). Results IMF+Age demonstrated superior mortality discrimination over SMART2 (C-index 0.79 vs 0.74, P < .01) and significant reclassification improvement. Decision curves showed greater net benefit across clinical thresholds. IMF-derived risk strata showed clear separation of Kaplan-Meier survival curves (log-rank P < .001), with mortality increasing from 3% (low-risk) to 27% (high-risk). Higher-risk strata were enriched for CHIP carriers, particularly spliceosome mutations. External validation reproduced expected risk patterns and comorbidity associations. Conclusions Plasma IMF provides rapid, low-cost, sequencing-free assessment of residual mortality risk in CAD, outperforming guideline-based scores while reflecting CHIP-associated biology. IMF offers a scalable phenotypic platform for precision secondary prevention and biology-guided trial design.
VerlagsortGreat Clarendon St, Oxford Ox2 6dp, England
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Institut(e)Institute of Epidemiology (EPI)
FörderungenDZG Innovation fund AMP FNIH Deutsches Herzzentrum Mnchen and Munich School of Robotics and Machine Learning Bavarian State Ministry of Health and Care Joint Research Center Swedish Research Council National Institutes of Health German Federal Ministry of Education and Research LMU Munich Centre for Advanced Laser Applications Fondation Leducq Bavarian State Ministry of Science and the Arts German Heart Foundation CMD Swedish Heart Lung Foundation