Biopsychosocial Phenogroups in Individuals with Coronary Artery Disease and their Associated Cardiovascular Mortality Risks

BackgroundPatients with stable coronary artery disease (CAD) represent a clinically heterogeneous group, with varying psychosocial, metabolic, and cardiovascular profiles that may differentially influence prognosis. We sought to identify distinct clinical phenogroups among patients with stable CAD and to evaluate their associations with cardiovascular disease (CVD)-specific and all-cause mortality. MethodsWe pooled data from 949 participants with stable CAD enrolled in two related studies. To identify distinct clinical phenogroups, we applied a model-based clustering approach using markers of autonomic dysfunction, psychosocial stress burden, myocardial injury and obstructive burden, left ventricular (LV) systolic dysfunction, and blood pressure. All variables were assessed at study enrollment. Hazard ratios (HRs) were estimated to examine the associations between the derived phenotypes and both CVD-specific and all-cause mortality. ResultsThe mean (SD) age of participants was 60 ({+/-}10) years; 34% were women and 41% were Black. We identified four phenogroups with differing sociodemographic and clinical profiles. Compared with phenogroup 2 (low-risk factor burden group), phenogroups 1 (cardiac autonomic dysfunction group) and 3 (ischemic cardiomyopathy group) had a 2 to 10-fold higher risk of CVD-specific and all-cause mortality over a median 5 years of follow-up. These associations remained strong and statistically significant in cluster 3 even after adjustment for demographic factors. Phenogroup 4 (high psychosocial burden group) showed a more modest but consistent 1.4 to 2.3-fold higher risk of CVD-specific and all-cause mortality compared with phenogroup 2, though this did not reach statistical significance. ConclusionsOur study identified novel phenogroups of CAD patients with clinically meaningful differences in risk for CVD-specific and all-cause mortality. Although more studies are warranted for this first-in-kind study, these results support a holistic model of CAD evaluation, with the promise of improving outcomes through targeted, personalized therapies that include behavioral interventions.