Latent class analysis of cardiac structure and function and association with premature cardiovascular disease: The Coronary Artery Risk Development in Young Adults (CARDIA) study

• Main Authors: Michael C. Wang (Author), Toluwalase Awoyemi (Author), Norrina B. Allen (Author), Ravi Shah (Author), Matthew Nayor (Author), Yuan Luo (Author), Joao A.C. Lima (Author), Donald M. Lloyd-Jones (Author), Sadiya S. Khan (Author)
• Format: Book
• Published: Elsevier, 2024-12-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 2666-6677; 10.1016/j.ajpc.2024.100889
• Keywords: Echocardiogram; Latent class analysis; Phenogroup; Cardiovascular disease; Diseases of the circulatory (Cardiovascular) system; RC666-701; Public aspects of medicine; RA1-1270
• Source: American Journal of Preventive Cardiology, Vol 20, Iss , Pp 100889- (2024)

Objective: To generate data-driven phenogroups of cardiac structure and function based on echocardiographic measures assessed in asymptomatic middle-aged adults free of CVD, and examine associations between these newly defined phenogroups and incident premature cardiovascular disease (CVD). Methods: Data were analyzed from participants in the Coronary Artery Risk Development in Young Adults (CARDIA) cohort study free of CVD who underwent an echocardiogram at the Year 25 (2010-2011) in-person examination. Continuous echocardiographic measures of left heart structure, left ventricular systolic function (including strain) and diastolic function, right ventricular systolic function, and hemodynamic measures were included in latent class analysis to generate novel phenogroups. Associations between data-driven phenogroups and risk of premature CVD (coronary artery disease, stroke, or heart failure) were estimated using Cox proportional hazards regression adjusted for traditional CVD risk factors. Results: Among 3361 participants, mean (standard deviation) age was 50.1 (3.6) years, 57% were female, and 46% were non-Hispanic Black. Three overall phenogroups were identified and labeled as: (1) optimal cardiac mechanics (36.2%); (2) suboptimal systolic function (38.2%); and (3) suboptimal diastolic function (25.6%). Over a median 8.9 years of follow-up, 121 premature CVD events occurred. Risk of CVD was higher in the suboptimal diastolic function group (unadjusted hazard ratio [HR] 4.08 [95% CI: 2.48, 6.71] and adjusted HR 1.95 [1.12, 3.40]) compared with the optimal group. The suboptimal systolic function group had a higher unadjusted risk of CVD (1.86 [1.10, 3.15]), which was attenuated after adjustment for CVD risk factors (1.36 [0.79, 2.36]). Conclusions and relevance: Unbiased, data-driven clustering of echocardiographic measures in middle-aged adults identified distinct patterns of cardiac remodeling that were associated with risk of premature CVD. Premature CVD risk was highest with the pattern of suboptimal diastolic function. This suggests potential utility of a composite echocardiography-based index for prioritizing prevention strategies earlier in the life course.