HFrEF subphenotypes based on 4210 repeatedly measured circulating proteins are driven by different biological mechanismsResearch in context
Teun B. Petersen,
Marie de Bakker,
Folkert W. Asselbergs,
Magdalena Harakalova,
K. Martijn Akkerhuis,
Jasper J. Brugts,
Jan van Ramshorst,
R. Thomas Lumbers,
Rachel M. Ostroff,
Peter D. Katsikis,
Peter J. van der Spek,
Victor A. Umans,
Eric Boersma,
Dimitris Rizopoulos,
Isabella Kardys
Affiliations
Teun B. Petersen
Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, Rotterdam, the Netherlands; Department of Biostatistics, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, Rotterdam, the Netherlands
Marie de Bakker
Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, Rotterdam, the Netherlands
Folkert W. Asselbergs
Amsterdam University Medical Centers, Department of Cardiology, University of Amsterdam, Meibergdreef 9, Amsterdam, the Netherlands; Health Data Research UK and Institute of Health Informatics, University College London, Gower St, London, United Kingdom
Magdalena Harakalova
Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, University of Utrecht, Heidelberglaan 100, Utrecht, the Netherlands; Regenerative Medicine Center Utrecht, University Medical Center Utrecht, University of Utrecht, Heidelberglaan 100, Utrecht, the Netherlands
K. Martijn Akkerhuis
Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, Rotterdam, the Netherlands
Jasper J. Brugts
Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, Rotterdam, the Netherlands
Jan van Ramshorst
Department of Cardiology, Northwest Clinics, Wilhelminalaan 12, Alkmaar, the Netherlands
R. Thomas Lumbers
British Heart Foundation Research Accelerator, University College London, Gower St, London, UK; Institute of Health Informatics, University College London, Gower St, London, UK; Health Data Research UK London, University College London, Gower St, London, UK
Rachel M. Ostroff
SomaLogic, Inc., 2945 Wilderness Pl, Boulder, United States
Peter D. Katsikis
Department of Immunology, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, Rotterdam, the Netherlands
Peter J. van der Spek
Department of Pathology, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, Rotterdam, the Netherlands
Victor A. Umans
Department of Cardiology, Northwest Clinics, Wilhelminalaan 12, Alkmaar, the Netherlands
Eric Boersma
Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, Rotterdam, the Netherlands
Dimitris Rizopoulos
Department of Biostatistics, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, Rotterdam, the Netherlands
Isabella Kardys
Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, Rotterdam, the Netherlands; Corresponding author. Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Room Na-316, P.O. Box 2040, 3000 CA Rotterdam, the Netherlands.
Summary: 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. Clinical Trial Registration: ClinicalTrials.gov Identifier: NCT01851538 https://clinicaltrials.gov/ct2/show/NCT01851538. Funding: EU/EFPIA IMI2JU BigData@Heart grant n°116074, Jaap Schouten Foundation and Noordwest Academie.
