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Dubin RF, Deo R, Ren Y, Wang J, Pico AR, Mychaleckyj JC, Kozlitina J, Arthur V, Lee H, Shah A, Feldman H, Bansal N, Zelnick L, Rao P, Sukul N, Raj DS, Mehta R, Rosas SE, Bhat Z, Weir MR, He J, Chen J, Kansal M, Kimmel PL, Ramachandran VS, Waikar SS, Segal MR, Ganz P. Incident heart failure in chronic kidney disease: proteomics informs biology and risk stratification. Eur Heart J 2024:ehae288. [PMID: 38757788 DOI: 10.1093/eurheartj/ehae288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Revised: 04/09/2024] [Accepted: 04/25/2024] [Indexed: 05/18/2024] Open
Abstract
BACKGROUND AND AIMS Incident heart failure (HF) among individuals with chronic kidney disease (CKD) incurs hospitalizations that burden patients and health care systems. There are few preventative therapies, and the Pooled Cohort equations to Prevent Heart Failure (PCP-HF) perform poorly in the setting of CKD. New drug targets and better risk stratification are urgently needed. METHODS In this analysis of incident HF, SomaScan V4.0 (4638 proteins) was analysed in 2906 participants of the Chronic Renal Insufficiency Cohort (CRIC) with validation in the Atherosclerosis Risk in Communities (ARIC) study. The primary outcome was 14-year incident HF (390 events); secondary outcomes included 4-year HF (183 events), HF with reduced ejection fraction (137 events), and HF with preserved ejection fraction (165 events). Mendelian randomization and Gene Ontology were applied to examine causality and pathways. The performance of novel multi-protein risk models was compared to the PCP-HF risk score. RESULTS Over 200 proteins were associated with incident HF after adjustment for estimated glomerular filtration rate at P < 1 × 10-5. After adjustment for covariates including N-terminal pro-B-type natriuretic peptide, 17 proteins remained associated at P < 1 × 10-5. Mendelian randomization associations were found for six proteins, of which four are druggable targets: FCG2B, IGFBP3, CAH6, and ASGR1. For the primary outcome, the C-statistic (95% confidence interval [CI]) for the 48-protein model in CRIC was 0.790 (0.735, 0.844) vs. 0.703 (0.644, 0.762) for the PCP-HF model (P = .001). C-statistic (95% CI) for the protein model in ARIC was 0.747 (0.707, 0.787). CONCLUSIONS Large-scale proteomics reveal novel circulating protein biomarkers and potential mediators of HF in CKD. Proteomic risk models improve upon the PCP-HF risk score in this population.
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Affiliation(s)
- Ruth F Dubin
- Division of Nephrology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, H5.122E, Dallas, TX 75390, USA
| | - Rajat Deo
- Division of Cardiovascular Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Yue Ren
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jianqiao Wang
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Alexander R Pico
- Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, USA
| | - Josyf C Mychaleckyj
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Julia Kozlitina
- McDermott Center for Human Growth and Development, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Victoria Arthur
- Division of Cardiology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Hongzhe Lee
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Amil Shah
- Division of Cardiology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Harold Feldman
- Patient-Centered Outcomes Research Institute, Washington, DC, USA
| | - Nisha Bansal
- Division of Nephrology, University of Washington Medical Center, Seattle, WA, USA
| | - Leila Zelnick
- Division of Nephrology, University of Washington Medical Center, Seattle, WA, USA
| | - Panduranga Rao
- Division of Nephrology, University of Michigan, Ann Arbor, MI, USA
| | - Nidhi Sukul
- Division of Nephrology, University of Michigan, Ann Arbor, MI, USA
| | - Dominic S Raj
- Division of Kidney Diseases and Hypertension, George Washington University School of Medicine, Washington, DC, USA
| | - Rupal Mehta
- Division of Nephrology and Hypertension, Northwestern University Feinberg School of Medicine, USA
| | - Sylvia E Rosas
- Joslin Diabetes Center, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Zeenat Bhat
- Division of Nephrology, University of Michigan, Ann Arbor, MI, USA
| | - Matthew R Weir
- Division of Nephrology, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Jiang He
- Department of Epidemiology, Tulane University, New Orleans, LA, USA
| | - Jing Chen
- Department of Epidemiology, Tulane University, New Orleans, LA, USA
| | - Mayank Kansal
- Division of Cardiology, University of Illinois College of Medicine, Chicago, IL, USA
| | - Paul L Kimmel
- Division of Kidney, Urologic, and Hematologic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Vasan S Ramachandran
- University of Texas School of Public Health San Antonio and the University of Texas Health Sciences Center in San Antonio, Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Sushrut S Waikar
- Section of Nephrology, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Mark R Segal
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Peter Ganz
- Division of Cardiology, University of California San Francisco, San Francisco, CA, USA
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Ren Y, Ruan P, Segal M, Dobre M, Schelling JR, Banerjee U, Shafi T, Ganz P, Dubin RF. Evaluation of a large-scale aptamer proteomics platform among patients with kidney failure on dialysis. PLoS One 2023; 18:e0293945. [PMID: 38079395 PMCID: PMC10712847 DOI: 10.1371/journal.pone.0293945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 10/22/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND Patients with kidney failure suffer high mortality, and we currently lack markers for risk stratification for these patients. We carried out a quality control study of a modified aptamer assay (SomaScan v.4.0) that measures ~ 5000 proteins, in preparation for a larger study using this platform in cohorts with kidney failure. METHODS Forty participants from the Cardiac, Endothelial Function and Arterial Stiffness in End-Stage Renal Disease (CERES study) were selected to analyze technical and short-term biological variability, orthogonal correlations and differential protein expression in plasma from patients who died during 2.5 year follow-up. Long-term (one year) variability was studied in 421 participants in the Chronic Renal Insufficiency Cohort. We evaluated 4849 aptamers (4607 unique proteins) using data formats including raw data and data formatted using Adaptive Normalization by Maximum Likelihood (ANML), an algorithm developed for SomaScan data in individuals with normal kidney function. RESULTS In ANML format, median[IQR] intra-assay coefficient of variation (CV) was 2.38%[1.76, 3.40] and inter-assay CV was 7.38%[4.61, 13.12]. Short-term within-subject CV was 5.76% [3.35, 9.72]; long-term CV was 8.71%[5.91, 13.37]. Spearman correlations between aptamer and traditional assays for PTH, NT-proBNP, FGF-23 and CRP were all > 0.7. Fold-change (FC) in protein levels among non-survivors, significant after Bonferroni correction, included SVEP1 (FC[95% CI] 2.14 [1.62, 2.82]), keratocan (1.74 [1.40, 2.15]) and LanC-like protein 1 (0.56 [0.45, 0.70]). Compared to raw aptamer data, technical and short-term biological variability in paired samples was lower in ANML-formatted data. ANML formatting had minimal impact on orthogonal correlations with traditional assays or the associations of proteins with the phenotype of mortality. CONCLUSIONS SomaScan had excellent technical variability and low within-subject short-term variability. ANML formatting could facilitate comparison of biomarker results with other studies that utilize this format. We expect SomaScan to provide novel and reproducible information in patients with kidney failure on dialysis.
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Affiliation(s)
- Yue Ren
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Peifeng Ruan
- Peter O’Donnell Jr School of Public Health, UT Southwestern, Dallas, Texas, United States of America
| | - Mark Segal
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California, United States of America
| | - Mirela Dobre
- Division of Nephrology and Hypertension, University Hospitals Cleveland Medical Center, Cleveland, Ohio, United States of America
| | - Jeffrey R. Schelling
- Department of Physiology & Biophysics, Case Western Reserve University of School of Medicine, Cleveland, Ohio, United States of America
| | - Upasana Banerjee
- Department of Internal Medicine, Hurley Medical Center/Michigan State University, Flint, Michigan, United States of America
| | - Tariq Shafi
- Division of Kidney Diseases, Hypertension and Transplantation, Houston Methodist Hospital, Houston, Texas, United States of America
| | - Peter Ganz
- Division of Cardiology, University of California, San Francisco, San Francisco, California, United States of America
| | - Ruth F. Dubin
- Division of Nephrology, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America
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Chakraborty A, Peterson NG, King JS, Gross RT, Pla MM, Thennavan A, Zhou KC, DeLuca S, Bursac N, Bowles DE, Wolf MJ, Fox DT. Conserved chamber-specific polyploidy maintains heart function in Drosophila. Development 2023; 150:dev201896. [PMID: 37526609 PMCID: PMC10482010 DOI: 10.1242/dev.201896] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 07/24/2023] [Indexed: 08/02/2023]
Abstract
Developmentally programmed polyploidy (whole-genome duplication) of cardiomyocytes is common across evolution. Functions of such polyploidy are essentially unknown. Here, in both Drosophila larvae and human organ donors, we reveal distinct polyploidy levels in cardiac organ chambers. In Drosophila, differential growth and cell cycle signal sensitivity leads the heart chamber to reach a higher ploidy/cell size relative to the aorta chamber. Cardiac ploidy-reduced animals exhibit reduced heart chamber size, stroke volume and cardiac output, and acceleration of circulating hemocytes. These Drosophila phenotypes mimic human cardiomyopathies. Our results identify productive and likely conserved roles for polyploidy in cardiac chambers and suggest that precise ploidy levels sculpt many developing tissues. These findings of productive cardiomyocyte polyploidy impact efforts to block developmental polyploidy to improve heart injury recovery.
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Affiliation(s)
- Archan Chakraborty
- Department of Pharmacology & Cancer Biology, Duke University School of Medicine, Durham, NC 27710, USA
- Duke Regeneration Center, Duke University School of Medicine, Durham, NC 27710, USA
| | - Nora G. Peterson
- Department of Pharmacology & Cancer Biology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Juliet S. King
- Department of Pharmacology & Cancer Biology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Ryan T. Gross
- Department of Surgery, Duke University, Durham, NC 27710, USA
| | | | - Aatish Thennavan
- Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77230, USA
| | - Kevin C. Zhou
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA
| | - Sophia DeLuca
- Department of Biomedical Engineering, Duke University, Durham, NC 27710, USA
| | - Nenad Bursac
- Duke Regeneration Center, Duke University School of Medicine, Durham, NC 27710, USA
- Department of Biomedical Engineering, Duke University, Durham, NC 27710, USA
| | - Dawn E. Bowles
- Department of Surgery, Duke University, Durham, NC 27710, USA
| | - Matthew J. Wolf
- Department of Medicine, University of Virginia, Charlottesville, VA 22903, USA
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, VA 22903, USA
| | - Donald T. Fox
- Department of Pharmacology & Cancer Biology, Duke University School of Medicine, Durham, NC 27710, USA
- Duke Regeneration Center, Duke University School of Medicine, Durham, NC 27710, USA
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Chakraborty A, Peterson NG, King JS, Gross RT, Pla MM, Thennavan A, Zhou KC, DeLuca S, Bursac N, Bowles DE, Wolf MJ, Fox DT. Conserved Chamber-Specific Polyploidy Maintains Heart Function in Drosophila. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.10.528086. [PMID: 36798187 PMCID: PMC9934670 DOI: 10.1101/2023.02.10.528086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Developmentally programmed polyploidy (whole-genome-duplication) of cardiomyocytes is common across evolution. Functions of such polyploidy are essentially unknown. Here, we reveal roles for precise polyploidy levels in cardiac tissue. We highlight a conserved asymmetry in polyploidy level between cardiac chambers in Drosophila larvae and humans. In Drosophila , differential Insulin Receptor (InR) sensitivity leads the heart chamber to reach a higher ploidy/cell size relative to the aorta chamber. Cardiac ploidy-reduced animals exhibit reduced heart chamber size, stroke volume, cardiac output, and acceleration of circulating hemocytes. These Drosophila phenotypes mimic systemic human heart failure. Using human donor hearts, we reveal asymmetry in nuclear volume (ploidy) and insulin signaling between the left ventricle and atrium. Our results identify productive and likely conserved roles for polyploidy in cardiac chambers and suggest precise ploidy levels sculpt many developing tissues. These findings of productive cardiomyocyte polyploidy impact efforts to block developmental polyploidy to improve heart injury recovery.
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