Matthew Nayor1,2, Meghan I Short3,4, Humaira Rasheed5,6, Honghuang Lin7, Christian Jonasson5, Qiong Yang3, Kristian Hveem5, Janine F Felix8, Alanna C Morrison9, Philipp S Wild10, Michael P Morley11, Thomas P Cappola11,12, Mark D Benson13, Debby Ngo14, Sumita Sinha13, Michelle J Keyes13, Dongxiao Shen13, Thomas J Wang15, Martin G Larson1,3, Ben M Brumpton5,6,16, Robert E Gerszten13, Torbjørn Omland17, Ramachandran S Vasan1,18. 1. Framingham Heart Study, Framingham, MA (M.N., M.G.L, R.S.V). 2. Cardiology Division, Department of Medicine, Massachusetts General Hospital (M.N.), Harvard Medical School, Boston, MA. 3. Department of Biostatistics, Boston University School of Public Health, Boston, MA (M.I.S., Q.Y., M.G.L.). 4. Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, TX (M.I.S.). 5. K.G. Jebsen Centre for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Norway (H.R., C.J., K.H., B.M.B.). 6. MRC Integrative Epidemiology Unit, University of Bristol, UK (H.R., B.M.B). 7. Section of Computational Medicine (H.L.), Department of Medicine, Boston University School of Medicine, Boston, MA. 8. Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands (J.F.F.). 9. Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas (A.C.M.). 10. DZHK (German Center for Cardiovascular Research), partner site RhineMain, Mainz, Germany (P.S.W.). 11. The Cardiovascular Institute (M.P.M., T.P.C.), Perelman School of Medicine, University of Pennsylvania, PA. 12. Division of Cardiovascular Medicine (T.P.C.), Perelman School of Medicine, University of Pennsylvania, PA. 13. Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center (M.D.B., S.S., M.J.K., D.S., R.E.G.), Harvard Medical School, Boston, MA. 14. Division of Pulmonary and Critical Care Medicine, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA (D.N.). 15. Division of Cardiovascular Medicine, Vanderbilt University, Nashville, TN (T.J.W.). 16. Clinic of Thoracic and Occupational Medicine, St. Olavs Hospital, Trondheim University Hospital, Norway (B.M.B.). 17. Department of Cardiology, Akershus University Hospital, Lørenskog, and Center for Heart Failure Research, Institute of Clinical Medicine, University of Oslo, Norway (T.O.). 18. Sections of Preventive Medicine & Epidemiology, and Cardiology (R.S.V.), Department of Medicine, Boston University School of Medicine, Boston, MA.
Abstract
BACKGROUND: We used a large-scale, high-throughput DNA aptamer-based discovery proteomic platform to identify circulating biomarkers of cardiac remodeling and incident heart failure (HF) in community-dwelling individuals. METHODS: We evaluated 1895 FHS (Framingham Heart Study) participants (age 55±10 years, 54% women) who underwent proteomic profiling and echocardiography. Plasma levels of 1305 proteins were related to echocardiographic traits and to incident HF using multivariable regression. Statistically significant protein-HF associations were replicated in the HUNT (Nord-Trøndelag Health) study (n=2497, age 63±10 years, 43% women), and results were meta-analyzed. Genetic variants associated with circulating protein levels (pQTLs) were related to echocardiographic traits in the EchoGen (n=30 201) and to incident HF in the CHARGE (n=20 926) consortia. RESULTS: Seventeen proteins associated with echocardiographic traits in cross-sectional analyses (false discovery rate <0.10), and 8 of these proteins had pQTLs associated with echocardiographic traits in EchoGen (P<0.0007). In Cox models adjusted for clinical risk factors, 29 proteins demonstrated associations with incident HF in FHS (174 HF events, mean follow-up 19 [limits, 0.2-23.7] years). In meta-analyses of FHS and HUNT, 6 of these proteins were associated with incident HF (P<3.8×10-5; 3 with higher risk: NT-proBNP [N-terminal proB-type natriuretic peptide], TSP2 [thrombospondin-2], MBL [mannose-binding lectin]; and 3 with lower risk: ErbB1 [epidermal growth factor receptor], GDF-11/8 [growth differentiation factor-11/8], and RGMC [hemojuvelin]). For 5 of the 6 proteins, pQTLs were associated with echocardiographic traits (P<0.0006) in EchoGen, and for RGMC, a protein quantitative trait loci was associated with incident HF (P=0.001). CONCLUSIONS: A large-scale proteomics approach identified new predictors of cardiac remodeling and incident HF. Future studies are warranted to elucidate how biological pathways represented by these proteins may mediate cardiac remodeling and HF risk and to assess if these proteins can improve HF risk prediction.
BACKGROUND: We used a large-scale, high-throughput DNA aptamer-based discovery proteomic platform to identify circulating biomarkers of cardiac remodeling and incident heart failure (HF) in community-dwelling individuals. METHODS: We evaluated 1895 FHS (Framingham Heart Study) participants (age 55±10 years, 54% women) who underwent proteomic profiling and echocardiography. Plasma levels of 1305 proteins were related to echocardiographic traits and to incident HF using multivariable regression. Statistically significant protein-HF associations were replicated in the HUNT (Nord-Trøndelag Health) study (n=2497, age 63±10 years, 43% women), and results were meta-analyzed. Genetic variants associated with circulating protein levels (pQTLs) were related to echocardiographic traits in the EchoGen (n=30 201) and to incident HF in the CHARGE (n=20 926) consortia. RESULTS: Seventeen proteins associated with echocardiographic traits in cross-sectional analyses (false discovery rate <0.10), and 8 of these proteins had pQTLs associated with echocardiographic traits in EchoGen (P<0.0007). In Cox models adjusted for clinical risk factors, 29 proteins demonstrated associations with incident HF in FHS (174 HF events, mean follow-up 19 [limits, 0.2-23.7] years). In meta-analyses of FHS and HUNT, 6 of these proteins were associated with incident HF (P<3.8×10-5; 3 with higher risk: NT-proBNP [N-terminal proB-type natriuretic peptide], TSP2 [thrombospondin-2], MBL [mannose-binding lectin]; and 3 with lower risk: ErbB1 [epidermal growth factor receptor], GDF-11/8 [growth differentiation factor-11/8], and RGMC [hemojuvelin]). For 5 of the 6 proteins, pQTLs were associated with echocardiographic traits (P<0.0006) in EchoGen, and for RGMC, a protein quantitative trait loci was associated with incident HF (P=0.001). CONCLUSIONS: A large-scale proteomics approach identified new predictors of cardiac remodeling and incident HF. Future studies are warranted to elucidate how biological pathways represented by these proteins may mediate cardiac remodeling and HF risk and to assess if these proteins can improve HF risk prediction.
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