4.7 Article

HFrEF subphenotypes based on 4210 repeatedly measured circulating proteins are driven by different biological mechanisms

Journal

EBIOMEDICINE
Volume 93, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.ebiom.2023.104655

Keywords

Netherlands; Proteomics; Biomarkers; Phenotypes; Unsupervised machine learning; Heart Failure

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This study identified four distinct subphenotypes of HFrEF based on circulating protein profiles, which had different prognosis and clinical characteristics. These findings can provide insights into the underlying biological mechanisms and personalized treatment opportunities for patients with HFrEF.
Background HFrEF is a heterogenous condition with high mortality. We used serial assessments of 4210 circulating proteins to identify distinct novel protein-based HFrEF subphenotypes and to investigate underlying dynamic biological mechanisms. Herewith we aimed to gain pathophysiological insights and fuel opportunities for personalised treatment. Methods In 382 patients, we performed trimonthly blood sampling during a median follow-up of 2.1 [IQR:1.1-2.6] years. We selected all baseline samples and two samples closest to the primary endpoint (PEP; composite of cardiovascular mortality, HF hospitalization, LVAD implantation, and heart transplantation) or censoring, and applied an aptamer-based multiplex proteomic approach. Using unsupervised machine learning methods, we derived clusters from 4210 repeatedly measured proteomic biomarkers. Sets of proteins that drove cluster allocation were analysed via an enrichment analysis. Differences in clinical characteristics and PEP occurrence were evaluated. Findings We identified four subphenotypes with different protein profiles, prognosis and clinical characteristics, including age (median [IQR] for subphenotypes 1-4, respectively:70 [64, 76], 68 [60, 79], 57 [47, 65], 59 [56, 66]years), EF (30 [26, 36], 26 [20, 38], 26 [22, 32], 33 [28, 37]%), and chronic renal failure (45%, 65%, 36%, 37%). Subphenotype allocation was driven by subsets of proteins associated with various biological functions, such as oxidative stress, inflammation and extracellular matrix organisation. Clinical characteristics of the subphenotypes were aligned with these associations. Subphenotypes 2 and 3 had the worst prognosis compared to subphenotype 1 (adjHR (95% CI):3.43 (1.76-6.69), and 2.88 (1.37-6.03), respectively). Interpretation Four circulating-protein based subphenotypes are present in HFrEF, which are driven by varying combinations of protein subsets, and have different clinical characteristics and prognosis.

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