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

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 a...

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Autores principales: Petersen, Teun B., de Bakker, Marie, Asselbergs, Folkert W., Harakalova, Magdalena, Akkerhuis, K. Martijn, Brugts, Jasper J., van Ramshorst, Jan, Lumbers, R. Thomas, Ostroff, Rachel M., Katsikis, Peter D., van der Spek, Peter J., Umans, Victor A., Boersma, Eric, Rizopoulos, Dimitris, Kardys, Isabella
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10279550/
https://www.ncbi.nlm.nih.gov/pubmed/37327673
http://dx.doi.org/10.1016/j.ebiom.2023.104655
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author Petersen, Teun B.
de Bakker, Marie
Asselbergs, Folkert W.
Harakalova, Magdalena
Akkerhuis, K. Martijn
Brugts, Jasper J.
van Ramshorst, Jan
Lumbers, R. Thomas
Ostroff, Rachel M.
Katsikis, Peter D.
van der Spek, Peter J.
Umans, Victor A.
Boersma, Eric
Rizopoulos, Dimitris
Kardys, Isabella
author_facet Petersen, Teun B.
de Bakker, Marie
Asselbergs, Folkert W.
Harakalova, Magdalena
Akkerhuis, K. Martijn
Brugts, Jasper J.
van Ramshorst, Jan
Lumbers, R. Thomas
Ostroff, Rachel M.
Katsikis, Peter D.
van der Spek, Peter J.
Umans, Victor A.
Boersma, Eric
Rizopoulos, Dimitris
Kardys, Isabella
author_sort Petersen, Teun B.
collection PubMed
description 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: NCT01851538https://clinicaltrials.gov/ct2/show/NCT01851538. FUNDING: EU/10.13039/100013322EFPIA IMI2JU BigData@Heart grant n°116074, Jaap Schouten Foundation and Noordwest Academie.
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spelling pubmed-102795502023-06-21 HFrEF subphenotypes based on 4210 repeatedly measured circulating proteins are driven by different biological mechanisms Petersen, Teun B. de Bakker, Marie Asselbergs, Folkert W. Harakalova, Magdalena Akkerhuis, K. Martijn Brugts, Jasper J. van Ramshorst, Jan Lumbers, R. Thomas Ostroff, Rachel M. Katsikis, Peter D. van der Spek, Peter J. Umans, Victor A. Boersma, Eric Rizopoulos, Dimitris Kardys, Isabella eBioMedicine Articles 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: NCT01851538https://clinicaltrials.gov/ct2/show/NCT01851538. FUNDING: EU/10.13039/100013322EFPIA IMI2JU BigData@Heart grant n°116074, Jaap Schouten Foundation and Noordwest Academie. Elsevier 2023-06-14 /pmc/articles/PMC10279550/ /pubmed/37327673 http://dx.doi.org/10.1016/j.ebiom.2023.104655 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Articles
Petersen, Teun B.
de Bakker, Marie
Asselbergs, Folkert W.
Harakalova, Magdalena
Akkerhuis, K. Martijn
Brugts, Jasper J.
van Ramshorst, Jan
Lumbers, R. Thomas
Ostroff, Rachel M.
Katsikis, Peter D.
van der Spek, Peter J.
Umans, Victor A.
Boersma, Eric
Rizopoulos, Dimitris
Kardys, Isabella
HFrEF subphenotypes based on 4210 repeatedly measured circulating proteins are driven by different biological mechanisms
title HFrEF subphenotypes based on 4210 repeatedly measured circulating proteins are driven by different biological mechanisms
title_full HFrEF subphenotypes based on 4210 repeatedly measured circulating proteins are driven by different biological mechanisms
title_fullStr HFrEF subphenotypes based on 4210 repeatedly measured circulating proteins are driven by different biological mechanisms
title_full_unstemmed HFrEF subphenotypes based on 4210 repeatedly measured circulating proteins are driven by different biological mechanisms
title_short HFrEF subphenotypes based on 4210 repeatedly measured circulating proteins are driven by different biological mechanisms
title_sort hfref subphenotypes based on 4210 repeatedly measured circulating proteins are driven by different biological mechanisms
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10279550/
https://www.ncbi.nlm.nih.gov/pubmed/37327673
http://dx.doi.org/10.1016/j.ebiom.2023.104655
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