Quinn S Wells1, Deepak K Gupta2, J Gustav Smith3, Sean P Collins4, Alan B Storrow4, Jane Ferguson1, Maya Landenhed Smith5, Jill M Pulley6, Sarah Collier6, Xiaoming Wang6, Dan M Roden7, Robert E Gerszten8, Thomas J Wang1. 1. Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University Medical Center, Nashville, Tennessee; Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, Tennessee. 2. Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University Medical Center, Nashville, Tennessee; Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, Tennessee. Electronic address: d.gupta@vanderbilt.edu. 3. Department of Cardiology, Clinical Sciences, Lund University and Skane University Hospital, Lund, Sweden. 4. Department of Emergency Medicine, Vanderbilt University Medical Center, Nashville, Tennessee. 5. Department of Cardiothoracic Surgery, Clinical Sciences, Lund University and Skane University Hospital, Lund, Sweden. 6. Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee. 7. Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, Tennessee; Departments of Medicine, Pharmacology, and Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee. 8. Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
Abstract
BACKGROUND: Circulating biomarkers can facilitate diagnosis and risk stratification for complex conditions such as heart failure (HF). Newer molecular platforms can accelerate biomarker discovery, but they require significant resources for data and sample acquisition. OBJECTIVES: The purpose of this study was to test a pragmatic biomarker discovery strategy integrating automated clinical biobanking with proteomics. METHODS: Using the electronic health record, the authors identified patients with and without HF, retrieved their discarded plasma samples, and screened these specimens using a DNA aptamer-based proteomic platform (1,129 proteins). Candidate biomarkers were validated in 3 different prospective cohorts. RESULTS: In an automated manner, plasma samples from 1,315 patients (31% with HF) were collected. Proteomic analysis of a 96-patient subset identified 9 candidate biomarkers (p < 4.42 × 10-5). Two proteins, angiopoietin-2 and thrombospondin-2, were associated with HF in 3 separate validation cohorts. In an emergency department-based registry of 852 dyspneic patients, the 2 biomarkers improved discrimination of acute HF compared with a clinical score (p < 0.0001) or clinical score plus B-type natriuretic peptide (p = 0.02). In a community-based cohort (n = 768), both biomarkers predicted incident HF independent of traditional risk factors and N-terminal pro-B-type natriuretic peptide (hazard ratio per SD increment: 1.35 [95% confidence interval: 1.14 to 1.61; p = 0.0007] for angiopoietin-2, and 1.37 [95% confidence interval: 1.06 to 1.79; p = 0.02] for thrombospondin-2). Among 30 advanced HF patients, concentrations of both biomarkers declined (80% to 84%) following cardiac transplant (p < 0.001 for both). CONCLUSIONS: A novel strategy integrating electronic health records, discarded clinical specimens, and proteomics identified 2 biomarkers that robustly predict HF across diverse clinical settings. This approach could accelerate biomarker discovery for many diseases.
BACKGROUND: Circulating biomarkers can facilitate diagnosis and risk stratification for complex conditions such as heart failure (HF). Newer molecular platforms can accelerate biomarker discovery, but they require significant resources for data and sample acquisition. OBJECTIVES: The purpose of this study was to test a pragmatic biomarker discovery strategy integrating automated clinical biobanking with proteomics. METHODS: Using the electronic health record, the authors identified patients with and without HF, retrieved their discarded plasma samples, and screened these specimens using a DNA aptamer-based proteomic platform (1,129 proteins). Candidate biomarkers were validated in 3 different prospective cohorts. RESULTS: In an automated manner, plasma samples from 1,315 patients (31% with HF) were collected. Proteomic analysis of a 96-patient subset identified 9 candidate biomarkers (p < 4.42 × 10-5). Two proteins, angiopoietin-2 and thrombospondin-2, were associated with HF in 3 separate validation cohorts. In an emergency department-based registry of 852 dyspneic patients, the 2 biomarkers improved discrimination of acute HF compared with a clinical score (p < 0.0001) or clinical score plus B-type natriuretic peptide (p = 0.02). In a community-based cohort (n = 768), both biomarkers predicted incident HF independent of traditional risk factors and N-terminal pro-B-type natriuretic peptide (hazard ratio per SD increment: 1.35 [95% confidence interval: 1.14 to 1.61; p = 0.0007] for angiopoietin-2, and 1.37 [95% confidence interval: 1.06 to 1.79; p = 0.02] for thrombospondin-2). Among 30 advanced HF patients, concentrations of both biomarkers declined (80% to 84%) following cardiac transplant (p < 0.001 for both). CONCLUSIONS: A novel strategy integrating electronic health records, discarded clinical specimens, and proteomics identified 2 biomarkers that robustly predict HF across diverse clinical settings. This approach could accelerate biomarker discovery for many diseases.
Authors: J Gustav Smith; Christopher Newton-Cheh; Peter Almgren; Joachim Struck; Nils G Morgenthaler; Andreas Bergmann; Pyotr G Platonov; Bo Hedblad; Gunnar Engström; Thomas J Wang; Olle Melander Journal: J Am Coll Cardiol Date: 2010-11-16 Impact factor: 24.094
Authors: Roland R van Kimmenade; James L Januzzi; Patrick T Ellinor; Umesh C Sharma; Jaap A Bakker; Adrian F Low; Abelardo Martinez; Harry J Crijns; Calum A MacRae; Paul P Menheere; Yigal M Pinto Journal: J Am Coll Cardiol Date: 2006-08-28 Impact factor: 24.094
Authors: D M Roden; J M Pulley; M A Basford; G R Bernard; E W Clayton; J R Balser; D R Masys Journal: Clin Pharmacol Ther Date: 2008-05-21 Impact factor: 6.875
Authors: Blanche Schroen; Stephane Heymans; Umesh Sharma; W Matthijs Blankesteijn; Saraswati Pokharel; Jack P M Cleutjens; J Gordon Porter; Chris T A Evelo; Rudy Duisters; Rick E W van Leeuwen; Ben J A Janssen; Jacques J M Debets; Jos F M Smits; Mat J A P Daemen; Harry J G M Crijns; Paul Bornstein; Yigal M Pinto Journal: Circ Res Date: 2004-07-29 Impact factor: 17.367
Authors: Aun Yeong Chong; Graham J Caine; Bethan Freestone; Andrew D Blann; Gregory Y H Lip Journal: J Am Coll Cardiol Date: 2004-02-04 Impact factor: 24.094
Authors: Melissa Swinnen; Davy Vanhoutte; Geert C Van Almen; Nazha Hamdani; Mark W M Schellings; Jan D'hooge; Jolanda Van der Velden; Matthew S Weaver; E Helene Sage; Paul Bornstein; Fons K Verheyen; Thierry VandenDriessche; Marinee K Chuah; Dirk Westermann; Walter J Paulus; Frans Van de Werf; Blanche Schroen; Peter Carmeliet; Yigal M Pinto; Stephane Heymans Journal: Circulation Date: 2009-10-05 Impact factor: 29.690
Authors: Larry Gold; Deborah Ayers; Jennifer Bertino; Christopher Bock; Ashley Bock; Edward N Brody; Jeff Carter; Andrew B Dalby; Bruce E Eaton; Tim Fitzwater; Dylan Flather; Ashley Forbes; Trudi Foreman; Cate Fowler; Bharat Gawande; Meredith Goss; Magda Gunn; Shashi Gupta; Dennis Halladay; Jim Heil; Joe Heilig; Brian Hicke; Gregory Husar; Nebojsa Janjic; Thale Jarvis; Susan Jennings; Evaldas Katilius; Tracy R Keeney; Nancy Kim; Tad H Koch; Stephan Kraemer; Luke Kroiss; Ngan Le; Daniel Levine; Wes Lindsey; Bridget Lollo; Wes Mayfield; Mike Mehan; Robert Mehler; Sally K Nelson; Michele Nelson; Dan Nieuwlandt; Malti Nikrad; Urs Ochsner; Rachel M Ostroff; Matt Otis; Thomas Parker; Steve Pietrasiewicz; Daniel I Resnicow; John Rohloff; Glenn Sanders; Sarah Sattin; Daniel Schneider; Britta Singer; Martin Stanton; Alana Sterkel; Alex Stewart; Suzanne Stratford; Jonathan D Vaught; Mike Vrkljan; Jeffrey J Walker; Mike Watrobka; Sheela Waugh; Allison Weiss; Sheri K Wilcox; Alexey Wolfson; Steven K Wolk; Chi Zhang; Dom Zichi Journal: PLoS One Date: 2010-12-07 Impact factor: 3.240
Authors: Dean Ho; Stephen R Quake; Edward R B McCabe; Wee Joo Chng; Edward K Chow; Xianting Ding; Bruce D Gelb; Geoffrey S Ginsburg; Jason Hassenstab; Chih-Ming Ho; William C Mobley; Garry P Nolan; Steven T Rosen; Patrick Tan; Yun Yen; Ali Zarrinpar Journal: Trends Biotechnol Date: 2020-01-21 Impact factor: 19.536
Authors: Luigi Adamo; Jinsheng Yu; Cibele Rocha-Resende; Ali Javaheri; Richard D Head; Douglas L Mann Journal: J Am Coll Cardiol Date: 2020-10-27 Impact factor: 24.094
Authors: Matthew Nayor; Meghan I Short; Humaira Rasheed; Honghuang Lin; Christian Jonasson; Qiong Yang; Kristian Hveem; Janine F Felix; Alanna C Morrison; Philipp S Wild; Michael P Morley; Thomas P Cappola; Mark D Benson; Debby Ngo; Sumita Sinha; Michelle J Keyes; Dongxiao Shen; Thomas J Wang; Martin G Larson; Ben M Brumpton; Robert E Gerszten; Torbjørn Omland; Ramachandran S Vasan Journal: Circ Heart Fail Date: 2020-05-15 Impact factor: 8.790
Authors: Daniel H Katz; Usman A Tahir; Debby Ngo; Mark D Benson; Yan Gao; Xu Shi; Matthew Nayor; Michelle J Keyes; Martin G Larson; Michael E Hall; Adolfo Correa; Sumita Sinha; Dongxiao Shen; Matthew Herzig; Qiong Yang; Jeremy M Robbins; Zsu-Zsu Chen; Daniel E Cruz; Bennet Peterson; Ramachandran S Vasan; Thomas J Wang; James G Wilson; Robert E Gerszten Journal: Circ Genom Precis Med Date: 2021-05-21