Proteomic-based biomarker discovery reveals panels of diagnostic biomarkers for early identification of heart failure subtypes
Abstract Background Limited access to echocardiography can delay the diagnosis of suspected heart failure (HF), which in turn postpones the initiation of optimal guideline-directed medical therapy. Although natriuretic peptides like B-type natriuretic peptide (BNP) are valuable biomarkers for diagno...
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| Format: | Article |
| Language: | English |
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BMC
2025-05-01
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| Series: | Journal of Translational Medicine |
| Online Access: | https://doi.org/10.1186/s12967-025-06563-7 |
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| author | Narainrit Karuna Claire Tonry Mark Ledwidge Nadezhda Glezeva Joe Gallagher Ken McDonald Chris J. Watson |
| author_facet | Narainrit Karuna Claire Tonry Mark Ledwidge Nadezhda Glezeva Joe Gallagher Ken McDonald Chris J. Watson |
| author_sort | Narainrit Karuna |
| collection | DOAJ |
| description | Abstract Background Limited access to echocardiography can delay the diagnosis of suspected heart failure (HF), which in turn postpones the initiation of optimal guideline-directed medical therapy. Although natriuretic peptides like B-type natriuretic peptide (BNP) are valuable biomarkers for diagnosing and managing HF, the utility of combining BNP with other blood-based biomarkers to predict subtypes of new-onset HF remains underexplored. Objectives This study sought to investigate and evaluate the diagnostic significance of adding blood-based biomarkers to BNP for identifying heart failure with preserved ejection fraction (HFpEF) or reduced ejection fraction (HFrEF), with the goal of enhancing diagnostic assays beyond BNP measurements. Methods We identified candidate blood protein biomarkers using untargeted proteomics workflows from a cohort of individuals recruited to the STOP-HF trial who were at risk of HF and subsequently developed either HFpEF or HFrEF over time (“HF progressors”; n = 40). Candidate biomarkers were verified in an independent cohort (n = 52) from a community-based rapid access HF diagnostic clinic. The biological processes associated with these proteins were assessed, and the diagnostic values of biomarker panels were evaluated using a machine learning approach. Results Within HF progressors, we identified 3 proteins associated with HFpEF development: vascular cell adhesion protein 1 (VCAM1), insulin-like growth factor 2 (IGF2), and inter-alpha-trypsin inhibitor heavy chain 3 (ITIH3). Additionally, 4 proteins were linked to HFrEF development: C-reactive protein (CRP), interleukin-6 receptor subunit beta (IL6RB), phosphatidylinositol-glycan-specific phospholipase D (PHLD), and noelin (NOE1). These findings were verified in an independent cohort to distinguish HF subtypes from controls. Moreover, a random forest algorithm demonstrated that combining these candidate biomarkers with BNP measurement significantly improved the prediction of HF subtypes. Conclusions We identified candidate proteins linked to HFpEF and HFrEF in a longitudinal HF progressor cohort and validated them in a community-based cohort. Adding these proteins to BNP led to a significant improvement in HF subtype prediction. Study results have clinical implications for blood-based screening of HF subtypes using panels of biomarkers, particularly in resource-limited settings. |
| format | Article |
| id | doaj-art-804a69eb60ea4be6a1328d81a6cb2570 |
| institution | Kabale University |
| issn | 1479-5876 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Translational Medicine |
| spelling | doaj-art-804a69eb60ea4be6a1328d81a6cb25702025-08-20T03:48:02ZengBMCJournal of Translational Medicine1479-58762025-05-0123111510.1186/s12967-025-06563-7Proteomic-based biomarker discovery reveals panels of diagnostic biomarkers for early identification of heart failure subtypesNarainrit Karuna0Claire Tonry1Mark Ledwidge2Nadezhda Glezeva3Joe Gallagher4Ken McDonald5Chris J. Watson6Wellcome-Wolfson Institute for Experimental Medicine, Queen’s University BelfastWellcome-Wolfson Institute for Experimental Medicine, Queen’s University BelfastUCD Conway Institute and Research and Innovation Programme for Chronic Disease, School of Medicine, University College DublinUCD Conway Institute and Research and Innovation Programme for Chronic Disease, School of Medicine, University College DublinUCD Conway Institute and Research and Innovation Programme for Chronic Disease, School of Medicine, University College DublinUCD Conway Institute and Research and Innovation Programme for Chronic Disease, School of Medicine, University College DublinWellcome-Wolfson Institute for Experimental Medicine, Queen’s University BelfastAbstract Background Limited access to echocardiography can delay the diagnosis of suspected heart failure (HF), which in turn postpones the initiation of optimal guideline-directed medical therapy. Although natriuretic peptides like B-type natriuretic peptide (BNP) are valuable biomarkers for diagnosing and managing HF, the utility of combining BNP with other blood-based biomarkers to predict subtypes of new-onset HF remains underexplored. Objectives This study sought to investigate and evaluate the diagnostic significance of adding blood-based biomarkers to BNP for identifying heart failure with preserved ejection fraction (HFpEF) or reduced ejection fraction (HFrEF), with the goal of enhancing diagnostic assays beyond BNP measurements. Methods We identified candidate blood protein biomarkers using untargeted proteomics workflows from a cohort of individuals recruited to the STOP-HF trial who were at risk of HF and subsequently developed either HFpEF or HFrEF over time (“HF progressors”; n = 40). Candidate biomarkers were verified in an independent cohort (n = 52) from a community-based rapid access HF diagnostic clinic. The biological processes associated with these proteins were assessed, and the diagnostic values of biomarker panels were evaluated using a machine learning approach. Results Within HF progressors, we identified 3 proteins associated with HFpEF development: vascular cell adhesion protein 1 (VCAM1), insulin-like growth factor 2 (IGF2), and inter-alpha-trypsin inhibitor heavy chain 3 (ITIH3). Additionally, 4 proteins were linked to HFrEF development: C-reactive protein (CRP), interleukin-6 receptor subunit beta (IL6RB), phosphatidylinositol-glycan-specific phospholipase D (PHLD), and noelin (NOE1). These findings were verified in an independent cohort to distinguish HF subtypes from controls. Moreover, a random forest algorithm demonstrated that combining these candidate biomarkers with BNP measurement significantly improved the prediction of HF subtypes. Conclusions We identified candidate proteins linked to HFpEF and HFrEF in a longitudinal HF progressor cohort and validated them in a community-based cohort. Adding these proteins to BNP led to a significant improvement in HF subtype prediction. Study results have clinical implications for blood-based screening of HF subtypes using panels of biomarkers, particularly in resource-limited settings.https://doi.org/10.1186/s12967-025-06563-7 |
| spellingShingle | Narainrit Karuna Claire Tonry Mark Ledwidge Nadezhda Glezeva Joe Gallagher Ken McDonald Chris J. Watson Proteomic-based biomarker discovery reveals panels of diagnostic biomarkers for early identification of heart failure subtypes Journal of Translational Medicine |
| title | Proteomic-based biomarker discovery reveals panels of diagnostic biomarkers for early identification of heart failure subtypes |
| title_full | Proteomic-based biomarker discovery reveals panels of diagnostic biomarkers for early identification of heart failure subtypes |
| title_fullStr | Proteomic-based biomarker discovery reveals panels of diagnostic biomarkers for early identification of heart failure subtypes |
| title_full_unstemmed | Proteomic-based biomarker discovery reveals panels of diagnostic biomarkers for early identification of heart failure subtypes |
| title_short | Proteomic-based biomarker discovery reveals panels of diagnostic biomarkers for early identification of heart failure subtypes |
| title_sort | proteomic based biomarker discovery reveals panels of diagnostic biomarkers for early identification of heart failure subtypes |
| url | https://doi.org/10.1186/s12967-025-06563-7 |
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