Molecular Phenogroups in Heart Failure: Large-Scale Proteomics in a Population-Based Cohort.

Background: Heart failure (HF) is a heterogeneous syndrome with high mortality. The need for a new taxonomy of HF is recognized; up to now, such phenomapping efforts have primarily used clinical data. Proteomics offers potential for more precise phenotypic identification and mechanistic insights. However, few phenomapping studies have used this approach, and all have focused on targeted cardiovascular proteomics panels and a restricted HF ejection fraction group.

Methods: We measured over 7000 plasma proteins in a population-based cohort of 1351 patients with HF, used k-means clustering to identify distinct phenogroups, and compared their clinical characteristics and all-cause mortality.

Results: Three proteomics-defined phenogroups were identified, with substantial differences in survival (phenogroup 1 5-year survival probability, 65% [95% CI, 61%-68%]; phenogroup 2, 45% [40%-51%]; phenogroup 3, 26% [22%-30%]), independent of clinical characteristics. Phenogroups also exhibited differences in several measures suggesting poorer health, including NT-proBNP (N-terminal pro-B-type natriuretic peptide), kidney function, and Meta-Analysis Global Group in Chronic Heart Failure scores, but did not differ by ejection fraction or New York Heart Association class.

Conclusions: Our study demonstrates that molecular phenomapping can stratify patients with HF into distinct subgroups that go beyond predefined clinical classifications.