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Abou Kamar S, Andrzejczyk K, Petersen TB, Chin JF, Aga YS, de Bakker M, Akkerhuis KM, Geleijnse M, Brugts JJ, Sorop O, de Boer RA, Rizopoulos D, Asselbergs FW, Boersma E, den Ruijter H, van Dalen BM, Kardys I. The plasma proteome is linked with left ventricular and left atrial function parameters in patients with chronic heart failure. Eur Heart J Cardiovasc Imaging 2024; 25:1206-1215. [PMID: 38597740 PMCID: PMC11346355 DOI: 10.1093/ehjci/jeae098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 02/26/2024] [Accepted: 03/30/2024] [Indexed: 04/11/2024] Open
Abstract
AIMS Examining the systemic biological processes in the heterogeneous syndrome of heart failure with reduced ejection fraction (HFrEF), as reflected by circulating proteins, in relation to echocardiographic characteristics, may provide insights into heart failure pathophysiology. We investigated the link of 4210 repeatedly measured circulating proteins with repeatedly measured echocardiographic parameters as well as with elevated left atrial pressure (LAP), in patients with HFrEF, to provide insights into underlying mechanisms. METHODS AND RESULTS In 173 patients with HFrEF, we performed 6-monthly echocardiography and trimonthly blood sampling during a median follow-up of 2.7 (inter-quartile range: 2.5-2.8) years. We investigated circulating proteins in relation to echocardiographic parameters of left ventricular [left ventricular ejection fraction (LVEF), global longitudinal strain (GLS)] and left atrial function [left atrial reservoir strain (LASr)] and elevated LAP (E/e' ratio >15) and used gene enrichment analyses to identify underlying pathophysiological processes. We found 723, 249, 792, and 427 repeatedly measured proteins, with significant associations with LVEF, GLS, LASr, and E/e' ratio, respectively. Proteins associated with LASr reflected pathophysiological mechanisms mostly related to the extracellular matrix. Proteins associated with GLS reflected cardiovascular biological processes and diseases, whereas those associated with LVEF reflected processes involved in the sympathetic nervous system. Moreover, 49 proteins were associated with elevated LAP; after correction for LVEF, three proteins remained: cystatin-D, fibulin-5, and HSP40. CONCLUSION Circulating proteins show varying associations with different echocardiographic parameters in patients with HFrEF. These findings suggest that pathways involved in atrial and ventricular dysfunction, as reflected by the plasma proteome, are distinct.
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Affiliation(s)
- S Abou Kamar
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
- The Netherlands Heart Institute, Moreelsepark 1, 3511 EP Utrecht, The Netherlands
- Department of Cardiology, Franciscus Gasthuis & Vlietland, Kleiweg 500, 3045 PM Rotterdam, The Netherlands
| | - K Andrzejczyk
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
| | - T B Petersen
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
- Department of Biostatistics, University Medical Center Rotterdam, Erasmus University, Dr. Molewaterplein 40, 3000 CA Rotterdam, The Netherlands
| | - J F Chin
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
- Department of Cardiology, Franciscus Gasthuis & Vlietland, Kleiweg 500, 3045 PM Rotterdam, The Netherlands
| | - Y S Aga
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
- Department of Cardiology, Franciscus Gasthuis & Vlietland, Kleiweg 500, 3045 PM Rotterdam, The Netherlands
| | - M de Bakker
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
| | - K M Akkerhuis
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
| | - M Geleijnse
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
| | - J J Brugts
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
| | - O Sorop
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
| | - R A de Boer
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
| | - D Rizopoulos
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
- Department of Biostatistics, University Medical Center Rotterdam, Erasmus University, Dr. Molewaterplein 40, 3000 CA Rotterdam, The Netherlands
| | - F W Asselbergs
- Department of Cardiology, Amsterdam Medical Center, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - E Boersma
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
| | - H den Ruijter
- Laboratory of Experimental Cardiology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - B M van Dalen
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
- Department of Cardiology, Franciscus Gasthuis & Vlietland, Kleiweg 500, 3045 PM Rotterdam, The Netherlands
| | - I Kardys
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
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Hannemann A, Ameling S, Lehnert K, Dörr M, Felix SB, Nauck M, Al-Noubi MN, Schmidt F, Haas J, Meder B, Völker U, Friedrich N, Hammer E. Integrative Analyses of Circulating Proteins and Metabolites Reveal Sex Differences in the Associations with Cardiac Function among DCM Patients. Int J Mol Sci 2024; 25:6827. [PMID: 38999939 PMCID: PMC11241450 DOI: 10.3390/ijms25136827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 06/11/2024] [Accepted: 06/18/2024] [Indexed: 07/14/2024] Open
Abstract
Dilated cardiomyopathy (DCM) is characterized by reduced left ventricular ejection fraction (LVEF) and left or biventricular dilatation. We evaluated sex-specific associations of circulating proteins and metabolites with structural and functional heart parameters in DCM. Plasma samples (297 men, 71 women) were analyzed for proteins using Olink assays (targeted analysis) or LC-MS/MS (untargeted analysis), and for metabolites using LC MS/MS (Biocrates AbsoluteIDQ p180 Kit). Associations of proteins (n = 571) or metabolites (n = 163) with LVEF, measured left ventricular end diastolic diameter (LVEDDmeasured), and the dilation percentage of LVEDD from the norm (LVEDDacc. to HENRY) were examined in combined and sex-specific regression models. To disclose protein-metabolite relations, correlation analyses were performed. Associations between proteins, metabolites and LVEF were restricted to men, while associations with LVEDD were absent in both sexes. Significant metabolites were validated in a second independent DCM cohort (93 men). Integrative analyses demonstrated close relations between altered proteins and metabolites involved in lipid metabolism, inflammation, and endothelial dysfunction with declining LVEF, with kynurenine as the most prominent finding. In DCM, the loss of cardiac function was reflected by circulating proteins and metabolites with sex-specific differences. Our integrative approach demonstrated that concurrently assessing specific proteins and metabolites might help us to gain insights into the alterations associated with DCM.
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Affiliation(s)
- Anke Hannemann
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Ferdinand-Sauerbruch-Strasse, D-17475 Greifswald, Germany; (M.N.); (N.F.)
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, D-17475 Greifswald, Germany; (S.A.); (K.L.); (M.D.); (S.B.F.); (U.V.); (E.H.)
| | - Sabine Ameling
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, D-17475 Greifswald, Germany; (S.A.); (K.L.); (M.D.); (S.B.F.); (U.V.); (E.H.)
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Felix-Hausdorff-Strasse 8, D-17475 Greifswald, Germany
| | - Kristin Lehnert
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, D-17475 Greifswald, Germany; (S.A.); (K.L.); (M.D.); (S.B.F.); (U.V.); (E.H.)
- Department of Internal Medicine B, University Medicine Greifswald, D-17475 Greifswald, Germany
| | - Marcus Dörr
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, D-17475 Greifswald, Germany; (S.A.); (K.L.); (M.D.); (S.B.F.); (U.V.); (E.H.)
- Department of Internal Medicine B, University Medicine Greifswald, D-17475 Greifswald, Germany
| | - Stephan B. Felix
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, D-17475 Greifswald, Germany; (S.A.); (K.L.); (M.D.); (S.B.F.); (U.V.); (E.H.)
- Department of Internal Medicine B, University Medicine Greifswald, D-17475 Greifswald, Germany
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Ferdinand-Sauerbruch-Strasse, D-17475 Greifswald, Germany; (M.N.); (N.F.)
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, D-17475 Greifswald, Germany; (S.A.); (K.L.); (M.D.); (S.B.F.); (U.V.); (E.H.)
| | - Muna N. Al-Noubi
- Proteomics Core, Weill Cornell Medicine-Qatar, Doha 24144, Qatar; (M.N.A.-N.); (F.S.)
| | - Frank Schmidt
- Proteomics Core, Weill Cornell Medicine-Qatar, Doha 24144, Qatar; (M.N.A.-N.); (F.S.)
| | - Jan Haas
- Institute for Cardiomyopathies Heidelberg (ICH), Heart Centre Heidelberg, University of Heidelberg, D-69121 Heidelberg, Germany; (J.H.); (B.M.)
- German Centre for Cardiovascular Research (DZHK), Partner Site Heidelberg/Mannheim, D-69121 Heidelberg, Germany
- Department of Medicine III, University of Heidelberg, INF 410, D-69120 Heidelberg, Germany
| | - Benjamin Meder
- Institute for Cardiomyopathies Heidelberg (ICH), Heart Centre Heidelberg, University of Heidelberg, D-69121 Heidelberg, Germany; (J.H.); (B.M.)
- German Centre for Cardiovascular Research (DZHK), Partner Site Heidelberg/Mannheim, D-69121 Heidelberg, Germany
- Department of Medicine III, University of Heidelberg, INF 410, D-69120 Heidelberg, Germany
| | - Uwe Völker
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, D-17475 Greifswald, Germany; (S.A.); (K.L.); (M.D.); (S.B.F.); (U.V.); (E.H.)
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Felix-Hausdorff-Strasse 8, D-17475 Greifswald, Germany
| | - Nele Friedrich
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Ferdinand-Sauerbruch-Strasse, D-17475 Greifswald, Germany; (M.N.); (N.F.)
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, D-17475 Greifswald, Germany; (S.A.); (K.L.); (M.D.); (S.B.F.); (U.V.); (E.H.)
| | - Elke Hammer
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, D-17475 Greifswald, Germany; (S.A.); (K.L.); (M.D.); (S.B.F.); (U.V.); (E.H.)
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Felix-Hausdorff-Strasse 8, D-17475 Greifswald, Germany
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Joo J, Shearer JJ, Wolska A, Remaley AT, Otvos JD, Connelly MA, Sampson M, Bielinski SJ, Larson NB, Park H, Conners KM, Turecamo S, Roger VL. Incremental Value of a Metabolic Risk Score for Heart Failure Mortality: A Population-Based Study. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2024; 17:e004312. [PMID: 38516784 PMCID: PMC11021175 DOI: 10.1161/circgen.123.004312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 03/10/2024] [Indexed: 03/23/2024]
Abstract
BACKGROUND Heart failure is heterogeneous syndrome with persistently high mortality. Nuclear magnetic resonance spectroscopy enables high-throughput metabolomics, suitable for precision phenotyping. We aimed to use targeted metabolomics to derive a metabolic risk score (MRS) that improved mortality risk stratification in heart failure. METHODS Nuclear magnetic resonance was used to measure 21 metabolites (lipoprotein subspecies, branched-chain amino acids, alanine, GlycA (glycoprotein acetylation), ketone bodies, glucose, and citrate) in plasma collected from a heart failure community cohort. The MRS was derived using least absolute shrinkage and selection operator penalized Cox regression and temporal validation. The association between the MRS and mortality and whether risk stratification was improved over the Meta-Analysis Global Group in Chronic Heart Failure clinical risk score and NT-proBNP (N-terminal pro-B-type natriuretic peptide) levels were assessed. RESULTS The study included 1382 patients (median age, 78 years, 52% men, 43% reduced ejection fraction) with a 5-year survival rate of 48% (95% CI, 46%-51%). The MRS included 9 metabolites measured. In the validation data set, a 1 standard deviation increase in the MRS was associated with a large increased rate of death (hazard ratio, 2.2 [95% CI, 1.9-2.5]) that remained after adjustment for Meta-Analysis Global Group in Chronic Heart Failure score and NT-proBNP (hazard ratio, 1.6 [95% CI, 1.3-1.9]). These associations did not differ by ejection fraction. The integrated discrimination and net reclassification indices, and Uno's C statistic, indicated that the addition of the MRS improved discrimination over Meta-Analysis Global Group in Chronic Heart Failure and NT-proBNP. CONCLUSIONS This MRS developed in a heart failure community cohort was associated with a large excess risk of death and improved risk stratification beyond an established risk score and clinical markers.
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Affiliation(s)
- Jungnam Joo
- Office of Biostatistics Research, National Heart, Lung, and Blood Inst
| | - Joseph J. Shearer
- Heart Disease Phenomics Laboratory, Epidemiology & Community Health Branch, National Heart, Lung, and Blood Inst
| | - Anna Wolska
- Lipoprotein Metabolism Laboratory, Translational Vascular Medicine Branch, National Heart, Lung, and Blood Inst
| | - Alan T. Remaley
- Lipoprotein Metabolism Laboratory, Translational Vascular Medicine Branch, National Heart, Lung, and Blood Inst
| | - James D. Otvos
- Lipoprotein Metabolism Laboratory, Translational Vascular Medicine Branch, National Heart, Lung, and Blood Inst
| | | | - Maureen Sampson
- Dept of Laboratory Medicine, Clinical Ctr, National Institutes of Health, Bethesda, MD
| | | | - Nicholas B. Larson
- Division of Clinical Trials & Biostatistics, Dept of Quantitative Health Sciences, Mayo Clinic College of Medicine & Science, Rochester, MN
| | - Hoyoung Park
- Dept of Statistics, Sookmyung Women’s University, Seoul, Korea
| | - Katherine M. Conners
- Heart Disease Phenomics Laboratory, Epidemiology & Community Health Branch, National Heart, Lung, and Blood Inst
| | - Sarah Turecamo
- Heart Disease Phenomics Laboratory, Epidemiology & Community Health Branch, National Heart, Lung, and Blood Inst
| | - Véronique L. Roger
- Heart Disease Phenomics Laboratory, Epidemiology & Community Health Branch, National Heart, Lung, and Blood Inst
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4
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Dib M, Levin MG, Zhao L, Diab A, Wang Z, Ebert C, Salman O, Azzo JD, Gan S, Zamani P, Cohen JB, Gill D, Burgess S, Zagkos L, van Empel V, Richards AM, Doughty R, Rietzschel ER, Kammerhoff K, Kvikstad E, Maranville J, Schafer P, Seiffert DA, Ramirez‐Valle F, Gordon DA, Chang C, Javaheri A, Mann DL, Cappola TP, Chirinos JA. Proteomic Associations of Adverse Outcomes in Human Heart Failure. J Am Heart Assoc 2024; 13:e031154. [PMID: 38420755 PMCID: PMC10944037 DOI: 10.1161/jaha.123.031154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 01/16/2024] [Indexed: 03/02/2024]
Abstract
BACKGROUND Identifying novel molecular drivers of disease progression in heart failure (HF) is a high-priority goal that may provide new therapeutic targets to improve patient outcomes. The authors investigated the relationship between plasma proteins and adverse outcomes in HF and their putative causal role using Mendelian randomization. METHODS AND RESULTS The authors measured 4776 plasma proteins among 1964 participants with HF with a reduced left ventricular ejection fraction enrolled in PHFS (Penn Heart Failure Study). Assessed were the observational relationship between plasma proteins and (1) all-cause death or (2) death or HF-related hospital admission (DHFA). The authors replicated nominally significant associations in the Washington University HF registry (N=1080). Proteins significantly associated with outcomes were the subject of 2-sample Mendelian randomization and colocalization analyses. After correction for multiple testing, 243 and 126 proteins were found to be significantly associated with death and DHFA, respectively. These included small ubiquitin-like modifier 2 (standardized hazard ratio [sHR], 1.56; P<0.0001), growth differentiation factor-15 (sHR, 1.68; P<0.0001) for death, A disintegrin and metalloproteinase with thrombospondin motifs-like protein (sHR, 1.40; P<0.0001), and pulmonary-associated surfactant protein C (sHR, 1.24; P<0.0001) for DHFA. In pathway analyses, top canonical pathways associated with death and DHFA included fibrotic, inflammatory, and coagulation pathways. Genomic analyses provided evidence of nominally significant associations between levels of 6 genetically predicted proteins with DHFA and 11 genetically predicted proteins with death. CONCLUSIONS This study implicates multiple novel proteins in HF and provides preliminary evidence of associations between genetically predicted plasma levels of 17 candidate proteins and the risk for adverse outcomes in human HF.
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Affiliation(s)
- Marie‐Joe Dib
- Division of Cardiovascular MedicineHospital of the University of PennsylvaniaPhiladelphiaPAUSA
- University of Pennsylvania Perelman School of MedicinePhiladelphiaPAUSA
| | - Michael G. Levin
- Division of Cardiovascular MedicineHospital of the University of PennsylvaniaPhiladelphiaPAUSA
- University of Pennsylvania Perelman School of MedicinePhiladelphiaPAUSA
| | - Lei Zhao
- Bristol‐Myers Squibb CompanyLawrencevilleNJUSA
| | - Ahmed Diab
- Washington University School of MedicineSt. LouisMOUSA
| | | | | | - Oday Salman
- University of Pennsylvania Perelman School of MedicinePhiladelphiaPAUSA
| | - Joe David Azzo
- University of Pennsylvania Perelman School of MedicinePhiladelphiaPAUSA
| | - Sushrima Gan
- Division of Cardiovascular MedicineHospital of the University of PennsylvaniaPhiladelphiaPAUSA
- University of Pennsylvania Perelman School of MedicinePhiladelphiaPAUSA
| | - Payman Zamani
- Division of Cardiovascular MedicineHospital of the University of PennsylvaniaPhiladelphiaPAUSA
- University of Pennsylvania Perelman School of MedicinePhiladelphiaPAUSA
| | - Jordana B. Cohen
- University of Pennsylvania Perelman School of MedicinePhiladelphiaPAUSA
- Renal‐Electrolyte and Hypertension Division, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPAUSA
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPAUSA
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public HealthImperial College LondonLondonUnited Kingdom
| | - Stephen Burgess
- MRC Integrative Epidemiology UnitUniversity of BristolUnited Kingdom
- Department of Public Health and Primary CareUniversity of CambridgeUnited Kingdom
| | - Loukas Zagkos
- Department of Epidemiology and Biostatistics, School of Public HealthImperial College LondonLondonUnited Kingdom
| | - Vanessa van Empel
- Department of CardiologyMaastricht University Medical CenterMaastrichtThe Netherlands
| | - A. Mark Richards
- Department of CardiologyMaastricht University Medical CenterMaastrichtThe Netherlands
- Cardiovascular Research InstituteNational University of SingaporeSingapore
| | - Rob Doughty
- Christchurch Heart InstituteUniversity of OtagoChristchurchNew Zealand
| | | | | | | | | | | | | | | | | | | | - Ali Javaheri
- Washington University School of MedicineSt. LouisMOUSA
- John J. Cochran Veterans HospitalSt. LouisMOUSA
| | | | - Thomas P. Cappola
- Division of Cardiovascular MedicineHospital of the University of PennsylvaniaPhiladelphiaPAUSA
- University of Pennsylvania Perelman School of MedicinePhiladelphiaPAUSA
| | - Julio A. Chirinos
- Division of Cardiovascular MedicineHospital of the University of PennsylvaniaPhiladelphiaPAUSA
- University of Pennsylvania Perelman School of MedicinePhiladelphiaPAUSA
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Kuku KO, Oyetoro R, Hashemian M, Livinski AA, Shearer JJ, Joo J, Psaty BM, Levy D, Ganz P, Roger VL. Proteomics for heart failure risk stratification: a systematic review. BMC Med 2024; 22:34. [PMID: 38273315 PMCID: PMC10809595 DOI: 10.1186/s12916-024-03249-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 01/05/2024] [Indexed: 01/27/2024] Open
Abstract
BACKGROUND Heart failure (HF) is a complex clinical syndrome with persistently high mortality. High-throughput proteomic technologies offer new opportunities to improve HF risk stratification, but their contribution remains to be clearly defined. We aimed to systematically review prognostic studies using high-throughput proteomics to identify protein signatures associated with HF mortality. METHODS We searched four databases and two clinical trial registries for articles published from 2012 to 2023. HF proteomics studies measuring high numbers of proteins using aptamer or antibody-based affinity platforms on human plasma or serum with outcomes of all-cause or cardiovascular death were included. Two reviewers independently screened articles, extracted data, and assessed the risk of bias. A third reviewer resolved conflicts. We assessed the risk of bias using the Risk Of Bias In Non-randomized Studies-of Exposure tool. RESULTS Out of 5131 unique articles identified, nine articles were included in the review. The nine studies were observational; three used the aptamer platform, and six used the antibody platform. We found considerable heterogeneity across studies in measurement panels, HF definitions, ejection fraction categorization, follow-up duration, and outcome definitions, and a lack of risk estimates for most protein associations. Hence, we proceeded with a systematic review rather than a meta-analysis. In two comparable aptamer studies in patients with HF with reduced ejection fraction, 21 proteins were identified in common for the association with all-cause death. Among these, one protein, WAP four-disulfide core domain protein 2 was also reported in an antibody study on HFrEF and for the association with CV death. We proposed standardized reporting criteria to facilitate the interpretation of future studies. CONCLUSIONS In this systematic review of nine studies evaluating the association of proteomics with mortality in HF, we identified a limited number of proteins common across several studies. Heterogeneity across studies compromised drawing broad inferences, underscoring the importance of standardized approaches to reporting.
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Affiliation(s)
- Kayode O Kuku
- Heart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Rebecca Oyetoro
- Heart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Maryam Hashemian
- Heart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Alicia A Livinski
- Office of Research Services, Office of the Director, National Institutes of Health Library, National Institutes of Health, Bethesda, MD, USA
| | - Joseph J Shearer
- Heart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jungnam Joo
- Office of Biostatistics Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology and Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Daniel Levy
- Laboratory for Cardiovascular Epidemiology and Genomics, Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Peter Ganz
- Zuckerberg San Francisco General Hospital, University of California, San Francisco, San Francisco, CA, USA
| | - Véronique L Roger
- Heart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA.
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6
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Kuku KO, Shearer JJ, Hashemian M, Oyetoro R, Park H, Dulek B, Bielinski SJ, Larson NB, Ganz P, Levy D, Psaty BM, Joo J, Roger VL. Development and Validation of a Protein Risk Score for Mortality in Heart Failure : A Community Cohort Study. Ann Intern Med 2024; 177:39-49. [PMID: 38163367 PMCID: PMC10958437 DOI: 10.7326/m23-2328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND Heart failure (HF) is a complex clinical syndrome with high mortality. Current risk stratification approaches lack precision. High-throughput proteomics could improve risk prediction. Its use in clinical practice to guide the management of patients with HF depends on validation and evidence of clinical benefit. OBJECTIVE To develop and validate a protein risk score for mortality in patients with HF. DESIGN Community-based cohort. SETTING Southeast Minnesota. PARTICIPANTS Patients with HF enrolled between 2003 and 2012 and followed through 2021. MEASUREMENTS A total of 7289 plasma proteins in 1351 patients with HF were measured using the SomaScan Assay (SomaLogic). A protein risk score was derived using least absolute shrinkage and selection operator regression and temporal validation in patients enrolled between 2003 and 2007 (development cohort) and 2008 and 2012 (validation cohort). Multivariable Cox regression was used to examine the association between the protein risk score and mortality. The performance of the protein risk score to predict 5-year mortality risk was assessed using calibration plots, decision curves, and relative utility analyses and compared with a clinical model, including the Meta-Analysis Global Group in Chronic Heart Failure mortality risk score and N-terminal pro-B-type natriuretic peptide. RESULTS The development (n = 855; median age, 78 years; 50% women; 29% with ejection fraction <40%) and validation cohorts (n = 496; median age, 76 years; 45% women; 33% with ejection fraction <40%) were mostly similar. In the development cohort, 38 unique proteins were selected for the protein risk score. Independent of ejection fraction, the protein risk score demonstrated good calibration, reclassified mortality risk particularly at the extremes of the risk distribution, and showed greater clinical utility compared with the clinical model. LIMITATION Participants were predominantly of European ancestry, potentially limiting the generalizability of the findings to different patient populations. CONCLUSION Validation of the protein risk score demonstrated good calibration and evidence of predicted benefits to stratify the risk for death in HF superior to that of clinical methods. Further studies are needed to prospectively evaluate the score's performance in diverse populations and determine risk thresholds for interventions. PRIMARY FUNDING SOURCE Division of Intramural Research at the National Heart, Lung, and Blood Institute of the National Institutes of Health.
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Affiliation(s)
- Kayode O Kuku
- Heart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Joseph J. Shearer
- Heart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Maryam Hashemian
- Heart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Rebecca Oyetoro
- Heart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Hoyoung Park
- Heart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Brittany Dulek
- Integrated Data Science Section, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Suzette, J. Bielinski
- Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Nicholas B. Larson
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Peter Ganz
- Zuckerberg San Francisco General Hospital, University of California, San Francisco, San Francisco, CA, USA
| | - Daniel Levy
- Laboratory for Cardiovascular Epidemiology and Genomics, Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology and Health Systems and Population Health, University of Washington, Seattle, Washington, USA
| | - Jungnam Joo
- Office of Biostatistics Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Véronique L. Roger
- Heart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
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7
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Debbs J, Hannawi B, Peterson E, Gui H, Zeld N, Luzum JA, Sabbah HN, Snider J, Pinto YM, Williams LK, Lanfear DE. Evaluation of a New Aptamer-Based Array for Soluble Suppressor of Tumorgenicity (ST2) and N-terminal Pro-B-Type Natriuretic Peptide (NTproBNP) in Heart Failure Patients. J Cardiovasc Transl Res 2023; 16:1343-1348. [PMID: 37191882 PMCID: PMC10651796 DOI: 10.1007/s12265-023-10397-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 05/08/2023] [Indexed: 05/17/2023]
Abstract
BACKGROUND Recent advances in multi-marker platforms offer faster data generation, but the fidelity of these methods compared to the ELISA is not established. We tested the correlation and predictive performance of SOMAscan vs. ELISA methods for NTproBNP and ST2. METHODS Patients ≥ 18 years with heart failure and ejection fraction < 50% were enrolled. We tested the correlation between SOMA and ELISA for each biomarker and their association with outcomes. RESULTS There was good correlation of SOMA vs. ELISA for ST2 (ρ = 0.71) and excellent correlation for NTproBNP (ρ = 0.94). The two versions of both markers were not significantly different regarding survival association. The two ST2 assays and NTproBNP assays were similarly associated with all-cause mortality and cardiovascular mortality. These associations remained statistically significant when adjusted for MAGGIC risk score (all p < 0.05). CONCLUSION SOMAscan quantifications of ST2 and NTproBNP correlate to ELISA versions and carry similar prognosis.
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Affiliation(s)
- Joseph Debbs
- Center for Individualized and Genomic Medicine Research, Department of Internal Medicine, Henry Ford Hospital, Detroit, MI, USA
| | - Bashar Hannawi
- Heart and Vascular Institute, Henry Ford Hospital, Detroit, MI, USA
| | - Edward Peterson
- Department of Public Health Sciences, Henry Ford Hospital, Detroit, MI, USA
| | - Hongsheng Gui
- Center for Individualized and Genomic Medicine Research, Department of Internal Medicine, Henry Ford Hospital, Detroit, MI, USA
| | - Nicole Zeld
- Center for Individualized and Genomic Medicine Research, Department of Internal Medicine, Henry Ford Hospital, Detroit, MI, USA
| | - Jasmine A Luzum
- Center for Individualized and Genomic Medicine Research, Department of Internal Medicine, Henry Ford Hospital, Detroit, MI, USA
- Department of Clinical Pharmacy, University of Michigan College of Pharmacy, Ann Arbor, MI, USA
| | - Hani N Sabbah
- Heart and Vascular Institute, Henry Ford Hospital, Detroit, MI, USA
| | | | - Yigal M Pinto
- Department of Cardiology, University of Amsterdam, Amsterdam, the Netherlands
| | - L Keoki Williams
- Center for Individualized and Genomic Medicine Research, Department of Internal Medicine, Henry Ford Hospital, Detroit, MI, USA
| | - David E Lanfear
- Center for Individualized and Genomic Medicine Research, Department of Internal Medicine, Henry Ford Hospital, Detroit, MI, USA.
- Heart and Vascular Institute, Henry Ford Hospital, Detroit, MI, USA.
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8
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de Bakker M, Petersen TB, Rueten-Budde AJ, Akkerhuis KM, Umans VA, Brugts JJ, Germans T, Reinders MJT, Katsikis PD, van der Spek PJ, Ostroff R, She R, Lanfear D, Asselbergs FW, Boersma E, Rizopoulos D, Kardys I. Machine learning-based biomarker profile derived from 4210 serially measured proteins predicts clinical outcome of patients with heart failure. EUROPEAN HEART JOURNAL. DIGITAL HEALTH 2023; 4:444-454. [PMID: 38045440 PMCID: PMC10689916 DOI: 10.1093/ehjdh/ztad056] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 09/06/2023] [Accepted: 10/03/2023] [Indexed: 12/05/2023]
Abstract
Aims Risk assessment tools are needed for timely identification of patients with heart failure (HF) with reduced ejection fraction (HFrEF) who are at high risk of adverse events. In this study, we aim to derive a small set out of 4210 repeatedly measured proteins, which, along with clinical characteristics and established biomarkers, carry optimal prognostic capacity for adverse events, in patients with HFrEF. Methods and results In 382 patients, we performed repeated blood sampling (median follow-up: 2.1 years) and applied an aptamer-based multiplex proteomic approach. We used machine learning to select the optimal set of predictors for the primary endpoint (PEP: composite of cardiovascular death, heart transplantation, left ventricular assist device implantation, and HF hospitalization). The association between repeated measures of selected proteins and PEP was investigated by multivariable joint models. Internal validation (cross-validated c-index) and external validation (Henry Ford HF PharmacoGenomic Registry cohort) were performed. Nine proteins were selected in addition to the MAGGIC risk score, N-terminal pro-hormone B-type natriuretic peptide, and troponin T: suppression of tumourigenicity 2, tryptophanyl-tRNA synthetase cytoplasmic, histone H2A Type 3, angiotensinogen, deltex-1, thrombospondin-4, ADAMTS-like protein 2, anthrax toxin receptor 1, and cathepsin D. N-terminal pro-hormone B-type natriuretic peptide and angiotensinogen showed the strongest associations [hazard ratio (95% confidence interval): 1.96 (1.17-3.40) and 0.66 (0.49-0.88), respectively]. The multivariable model yielded a c-index of 0.85 upon internal validation and c-indices up to 0.80 upon external validation. The c-index was higher than that of a model containing established risk factors (P = 0.021). Conclusion Nine serially measured proteins captured the most essential prognostic information for the occurrence of adverse events in patients with HFrEF, and provided incremental value for HF prognostication beyond established risk factors. These proteins could be used for dynamic, individual risk assessment in a prospective setting. These findings also illustrate the potential value of relatively 'novel' biomarkers for prognostication. Clinical Trial Registration https://clinicaltrials.gov/ct2/show/NCT01851538?term=nCT01851538&draw=2&rank=1 24.
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Affiliation(s)
- Marie de Bakker
- Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
| | - Teun B Petersen
- Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
- Department of Biostatistics, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
| | - Anja J Rueten-Budde
- Department of Biostatistics, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
| | - K Martijn Akkerhuis
- Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
| | - Victor A Umans
- Department of Cardiology, Northwest Clinics, Wilhelminalaan 12, 1815 JD, Alkmaar, The Netherlands
| | - Jasper J Brugts
- Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
| | - Tjeerd Germans
- Department of Cardiology, Northwest Clinics, Wilhelminalaan 12, 1815 JD, Alkmaar, The Netherlands
| | - Marcel J T Reinders
- Delft Bioinformatics Lab, Delft University of Technology, Van Mourik Broekmanweg 6, 2628 XE, Delft, The Netherlands
| | - Peter D Katsikis
- Department of Immunology, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
| | - Peter J van der Spek
- Department of Pathology, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
| | - Rachel Ostroff
- SomaLogic, Inc., 2945 Wilderness Pl., Boulder, CO 80301, USA
| | - Ruicong She
- Department of Public Health Sciences, Henry Ford Health System, 1 Ford Pl, Detroit, MI 48202, USA
| | - David Lanfear
- Center for Individualized and Genomic Medicine Research (CIGMA), Henry Ford Hospital, 2799 W. Grand Boulevard, Detroit MI, 48202, USA
- Heart and Vascular Institute, Henry Ford Hospital, 2799 W. Grand Boulevard, Detroit, MI 48202, USA
| | - Folkert W Asselbergs
- Amsterdam University Medical Centers, Department of Cardiology, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
- Health Data Research UK and Institute of Health Informatics, University College London, Gower St, London, WC1E 6BT, UK
| | - Eric Boersma
- Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
| | - Dimitris Rizopoulos
- Department of Biostatistics, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
| | - Isabella Kardys
- Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
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9
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Reitz CJ, Kuzmanov U, Gramolini AO. Multi-omic analyses and network biology in cardiovascular disease. Proteomics 2023; 23:e2200289. [PMID: 37691071 DOI: 10.1002/pmic.202200289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 08/11/2023] [Accepted: 08/22/2023] [Indexed: 09/12/2023]
Abstract
Heart disease remains a leading cause of death in North America and worldwide. Despite advances in therapies, the chronic nature of cardiovascular diseases ultimately results in frequent hospitalizations and steady rates of mortality. Systems biology approaches have provided a new frontier toward unraveling the underlying mechanisms of cell, tissue, and organ dysfunction in disease. Mapping the complex networks of molecular functions across the genome, transcriptome, proteome, and metabolome has enormous potential to advance our understanding of cardiovascular disease, discover new disease biomarkers, and develop novel therapies. Computational workflows to interpret these data-intensive analyses as well as integration between different levels of interrogation remain important challenges in the advancement and application of systems biology-based analyses in cardiovascular research. This review will focus on summarizing the recent developments in network biology-level profiling in the heart, with particular emphasis on modeling of human heart failure. We will provide new perspectives on integration between different levels of large "omics" datasets, including integration of gene regulatory networks, protein-protein interactions, signaling networks, and metabolic networks in the heart.
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Affiliation(s)
- Cristine J Reitz
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Translational Biology and Engineering Program, Ted Rogers Centre for Heart Research, Toronto, Ontario, Canada
| | - Uros Kuzmanov
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Translational Biology and Engineering Program, Ted Rogers Centre for Heart Research, Toronto, Ontario, Canada
| | - Anthony O Gramolini
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Translational Biology and Engineering Program, Ted Rogers Centre for Heart Research, Toronto, Ontario, Canada
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10
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Identification of patient subtypes based on protein expression for prediction of heart failure after myocardial infarction. iScience 2023; 26:106171. [PMID: 36915695 PMCID: PMC10006628 DOI: 10.1016/j.isci.2023.106171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 12/19/2022] [Accepted: 02/06/2023] [Indexed: 02/12/2023] Open
Abstract
This study investigates the ability of high-throughput aptamer-based platform to identify circulating biomarkers able to predict occurrence of heart failure (HF), in blood samples collected during hospitalization of patients suffering from a first myocardial infarction (MI). REVE-1 (derivation) and REVE-2 (validation) cohorts included respectively 254 and 238 patients, followed up respectively 9 · 2 ± 4 · 8 and 7 · 6 ± 3 · 0 years. A blood sample collected during hospitalization was used for quantifying 4,668 proteins. Fifty proteins were significantly associated with long-term occurrence of HF with all-cause death as the competing event. k-means, an unsupervised clustering method, identified two groups of patients based on expression levels of the 50 proteins. Group 2 was significantly associated with a higher risk of HF in both cohorts. These results showed that a subset of 50 selected proteins quantified during hospitalization of MI patients is able to stratify and predict the long-term occurrence of HF.
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11
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Kreft IC, Hoogendijk AJ, van der Zwaan C, van Alphen FPJ, Boon-Spijker M, Prinsze F, Meijer AB, de Korte D, van den Hurk K, van den Biggelaar M. Mass spectrometry-based analysis on the impact of whole blood donation on the global plasma proteome. Transfusion 2023; 63:564-573. [PMID: 36722460 DOI: 10.1111/trf.17254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 12/27/2022] [Accepted: 12/27/2022] [Indexed: 02/02/2023]
Abstract
BACKGROUND Biomonitoring may provide important insights into the impact of a whole blood donation for individual blood donors. STUDY DESIGN AND METHODS Here, we used unbiased mass spectrometry (MS)-based proteomics to assess longitudinal changes in the global plasma proteome, after a single blood donation for new and regular donors. Subsequently, we compared plasma proteomes of 76 male and female whole blood donors, that were grouped based on their ferritin and hemoglobin (Hb) levels. RESULTS The longitudinal analysis showed limited changes in the plasma proteomes of new and regular donors after a whole blood donation during a 180-day follow-up period, apart from a significant short-term decrease in fibronectin. No differences were observed in the plasma proteomes of donors with high versus low Hb and/or ferritin levels. Plasma proteins with the highest variation between and within donors included pregnancy zone protein, which was associated with sex, Alfa 1-antitrypsin which was associated with the allelic variation, and Immunoglobulin D. Coexpression analysis revealed clustering of proteins that are associated with platelet, red cell, and neutrophil signatures as well as with the complement system and immune responses, including a prominent correlating cluster of immunoglobulin M (IgM), immunoglobulin J chain (JCHAIN), and CD5 antigen-like (CD5L). DISCUSSION Overall, our proteomic approach shows that whole blood donation has a limited impact on the plasma proteins measured. Our findings suggest that plasma profiling can be successfully employed to consistently detect proteins and protein complexes that reflect the functionality and integrity of platelets, red blood cells, and immune cells in blood donors and thus highlights its potential use for donor health monitoring.
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Affiliation(s)
- Iris C Kreft
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
| | - Arie J Hoogendijk
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
| | - Carmen van der Zwaan
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
| | - Floris P J van Alphen
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
| | - Mariette Boon-Spijker
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
| | - Femmeke Prinsze
- Donor Studies, Department of Donor Medicine Research, Sanquin Research, Amsterdam, The Netherlands
| | - Alexander B Meijer
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
- Department of Biomolecular Mass Spectrometry and Proteomics, Utrecht Institute for Pharmaceutical Sciences (UIPS), Utrecht University, Utrecht, The Netherlands
| | - Dirk de Korte
- Department of Blood Cell Research, Sanquin Research, Amsterdam, The Netherlands
- Department of Product and Process Development, Sanquin Blood Bank, Amsterdam, The Netherlands
| | - Katja van den Hurk
- Donor Studies, Department of Donor Medicine Research, Sanquin Research, Amsterdam, The Netherlands
| | - Maartje van den Biggelaar
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
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12
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Javaheri A, Diab A, Zhao L, Qian C, Cohen JB, Zamani P, Kumar A, Wang Z, Ebert C, Maranville J, Kvikstad E, Basso M, van Empel V, Richards AM, Doughty R, Rietzschell E, Kammerhoff K, Gogain J, Schafer P, Seiffert DA, Gordon DA, Ramirez-Valle F, Mann DL, Cappola TP, Chirinos JA. Proteomic Analysis of Effects of Spironolactone in Heart Failure With Preserved Ejection Fraction. Circ Heart Fail 2022; 15:e009693. [PMID: 36126144 PMCID: PMC9504263 DOI: 10.1161/circheartfailure.121.009693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND The TOPCAT trial (Treatment of Preserved Cardiac Function Heart Failure With an Aldosterone Antagonist Trial) suggested clinical benefits of spironolactone treatment among patients with heart failure with preserved ejection fraction enrolled in the Americas. However, a comprehensive assessment of biologic pathways impacted by spironolactone therapy in heart failure with preserved ejection fraction has not been performed. METHODS We conducted aptamer-based proteomic analysis utilizing 5284 modified aptamers to 4928 unique proteins on plasma samples from TOPCAT participants from the Americas (n=164 subjects with paired samples at baseline and 1 year) to identify proteins and pathways impacted by spironolactone therapy in heart failure with preserved ejection fraction. Mean percentage change from baseline was calculated for each protein. Additionally, we conducted pathway analysis of proteins altered by spironolactone. RESULTS Spironolactone therapy was associated with proteome-wide significant changes in 7 proteins. Among these, CARD18 (caspase recruitment domain-containing protein 18), PKD2 (polycystin 2), and PSG2 (pregnancy-specific glycoprotein 2) were upregulated, whereas HGF (hepatic growth factor), PLTP (phospholipid transfer protein), IGF2R (insulin growth factor 2 receptor), and SWP70 (switch-associated protein 70) were downregulated. CARD18, a caspase-1 inhibitor, was the most upregulated protein by spironolactone (-0.5% with placebo versus +66.5% with spironolactone, P<0.0001). The top canonical pathways that were significantly associated with spironolactone were apelin signaling, stellate cell activation, glycoprotein 6 signaling, atherosclerosis signaling, liver X receptor activation, and farnesoid X receptor activation. Among the top pathways, collagens were a consistent theme that increased in patients receiving placebo but decreased in patients randomized to spironolactone. CONCLUSIONS Proteomic analysis in the TOPCAT trial revealed proteins and pathways altered by spironolactone, including the caspase inhibitor CARD18 and multiple pathways that involved collagens. In addition to effects on fibrosis, our studies suggest potential antiapoptotic effects of spironolactone in heart failure with preserved ejection fraction, a hypothesis that merits further exploration.
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Affiliation(s)
- Ali Javaheri
- Washington University School of Medicine, St. Louis, MO
| | - Ahmed Diab
- Washington University School of Medicine, St. Louis, MO
| | - Lei Zhao
- Bristol Myers Squibb Company, Lawrenceville, NJ
| | - Chenao Qian
- Perelman School of Medicine. University of Pennsylvania School of Medicine/Hospital of the University of Pennsylvania. Philadelphia, PA
| | - Jordana B. Cohen
- Perelman School of Medicine. University of Pennsylvania School of Medicine/Hospital of the University of Pennsylvania. Philadelphia, PA
| | - Payman Zamani
- Perelman School of Medicine. University of Pennsylvania School of Medicine/Hospital of the University of Pennsylvania. Philadelphia, PA
| | - Anupam Kumar
- Perelman School of Medicine. University of Pennsylvania School of Medicine/Hospital of the University of Pennsylvania. Philadelphia, PA
| | | | | | | | | | | | - Vanessa van Empel
- Department of Cardiology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - A. Mark Richards
- Cardiovascular Research Institute, National University of Singapore, Singapore
- Christchurch Heart Institute, University of Otago, Christchurch, New Zealand
| | - Rob Doughty
- Christchurch Heart Institute, University of Otago, Christchurch, New Zealand
| | - Ernst Rietzschell
- Department of Cardiovascular Diseases, Ghent University Hospital, Ghent, Belgium
| | | | | | | | | | | | | | | | - Thomas P. Cappola
- Perelman School of Medicine. University of Pennsylvania School of Medicine/Hospital of the University of Pennsylvania. Philadelphia, PA
| | - Julio A. Chirinos
- Perelman School of Medicine. University of Pennsylvania School of Medicine/Hospital of the University of Pennsylvania. Philadelphia, PA
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13
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Girerd N, Cleland J, Anker SD, Byra W, Lam CSP, Lapolice D, Mehra MR, van Veldhuisen DJ, Bresso E, Lamiral Z, Greenberg B, Zannad F. Inflammation and remodeling pathways and risk of cardiovascular events in patients with ischemic heart failure and reduced ejection fraction. Sci Rep 2022; 12:8574. [PMID: 35595781 PMCID: PMC9123183 DOI: 10.1038/s41598-022-12385-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Accepted: 03/21/2022] [Indexed: 12/22/2022] Open
Abstract
Patients with heart failure (HF) and coronary artery disease (CAD) have a high risk for cardiovascular (CV) events including HF hospitalization, stroke, myocardial infarction (MI) and sudden cardiac death (SCD). The present study evaluated associations of proteomic biomarkers with CV outcome in patients with CAD and HF with reduced ejection fraction (HFrEF), shortly after a worsening HF episode. We performed a case-control study within the COMMANDER HF international, double-blind, randomized placebo-controlled trial investigating the effects of the factor-Xa inhibitor rivaroxaban. Patients with the following first clinical events: HF hospitalization, SCD and the composite of MI or stroke were matched with corresponding controls for age, sex and study drug. Plasma concentrations of 276 proteins with known associations with CV and cardiometabolic mechanisms were analyzed. Results were corrected for multiple testing using false discovery rate (FDR). In 485 cases and 455 controls, 49 proteins were significantly associated with clinical events of which seven had an adjusted FDR < 0.001 (NT-proBNP, BNP, T-cell immunoglobulin and mucin domain containing 4 (TIMD4), fibroblast growth factor 23 (FGF-23), growth differentiation factor-15 (GDF-15), pulmonary surfactant-associated protein D (PSP-D) and Spondin-1 (SPON1)). No significant interactions were identified between the type of clinical event (MI/stroke, SCD or HFH) and specific biomarkers (all interaction FDR > 0.20). When adding the biomarkers significantly associated with the above outcome to a clinical model (including NT-proBNP), the C-index increase was 0.057 (0.033-0.082), p < 0.0001 and the net reclassification index was 54.9 (42.5 to 67.3), p < 0.0001. In patients with HFrEF and CAD following HF hospitalization, we found that NT-proBNP, BNP, TIMD4, FGF-23, GDF-15, PSP-D and SPON1, biomarkers broadly associated with inflammation and remodeling mechanistic pathways, were strong but indiscriminate predictors of a variety of individual CV events.
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Affiliation(s)
- Nicolas Girerd
- Université de Lorraine, Centre d'Investigation Clinique-Plurithématique Inserm CIC-P 1433, Inserm U1116, CHRU Nancy Brabois, F-CRIN INI-CRCT (Cardiovascular and Renal Clinical Trialists), Nancy, France
| | - John Cleland
- Robertson Centre for Biostatistics and Clinical Trials, University of Glasgow, Glasgow, Scotland
| | - Stefan D Anker
- Department of Cardiology (CVK), and Berlin Institute of Health Center for Regenerative Therapies (BCRT), German Centre for Cardiovascular Research (DZHK) Partner Site Berlin, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - William Byra
- Janssen Research and Development, Raritan, NJ, USA
| | - Carolyn S P Lam
- National Heart Centre Singapore, Duke-National University of Singapore, Singapore, Singapore
| | | | - Mandeep R Mehra
- Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Dirk J van Veldhuisen
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Emmanuel Bresso
- Université de Lorraine, Centre d'Investigation Clinique-Plurithématique Inserm CIC-P 1433, Inserm U1116, CHRU Nancy Brabois, F-CRIN INI-CRCT (Cardiovascular and Renal Clinical Trialists), Nancy, France
| | - Zohra Lamiral
- Université de Lorraine, Centre d'Investigation Clinique-Plurithématique Inserm CIC-P 1433, Inserm U1116, CHRU Nancy Brabois, F-CRIN INI-CRCT (Cardiovascular and Renal Clinical Trialists), Nancy, France
| | - Barry Greenberg
- Cardiology Division, Department of Medicine, University of California, La Jolla, San Diego, USA
| | - Faiez Zannad
- Université de Lorraine, Centre d'Investigation Clinique-Plurithématique Inserm CIC-P 1433, Inserm U1116, CHRU Nancy Brabois, F-CRIN INI-CRCT (Cardiovascular and Renal Clinical Trialists), Nancy, France.
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14
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Recent Developments in Clinical Plasma Proteomics—Applied to Cardiovascular Research. Biomedicines 2022; 10:biomedicines10010162. [PMID: 35052841 PMCID: PMC8773619 DOI: 10.3390/biomedicines10010162] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 01/05/2022] [Accepted: 01/12/2022] [Indexed: 01/27/2023] Open
Abstract
The human plasma proteome mirrors the physiological state of the cardiovascular system, a fact that has been used to analyze plasma biomarkers in routine analysis for the diagnosis and monitoring of cardiovascular diseases for decades. These biomarkers address, however, only a very limited subset of cardiovascular diseases, such as acute myocardial infarct or acute deep vein thrombosis, and clinical plasma biomarkers for the diagnosis and stratification cardiovascular diseases that are growing in incidence, such as heart failure and abdominal aortic aneurysm, do not exist and are urgently needed. The discovery of novel biomarkers in plasma has been hindered by the complexity of the human plasma proteome that again transforms into an extreme analytical complexity when it comes to the discovery of novel plasma biomarkers. This complexity is, however, addressed by recent achievements in technologies for analyzing the human plasma proteome, thereby facilitating the possibility for novel biomarker discoveries. The aims of this article is to provide an overview of the recent achievements in technologies for proteomic analysis of the human plasma proteome and their applications in cardiovascular medicine.
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