J Tromp1,2,3, W Ouwerkerk2,4, B G Demissei1, S D Anker5,6, J G Cleland7,8, K Dickstein9, G Filippatos10, P van der Harst1, H L Hillege1, C C Lang11, M Metra12, L L Ng13,14, P Ponikowski15,16, N J Samani13,14, D J van Veldhuisen1, F Zannad17, A H Zwinderman4, A A Voors1, P van der Meer1. 1. Department of Cardiology, University of Groningen, Hanzeplein 1, GZ, Groningen, the Netherlands. 2. National Heart Centre Singapore, 5 Hospital Drive, Singapore. 3. Duke-NUS Medical School, 8 College Road, Singapore. 4. Department of Epidemiology, Biostatistics & Bioinformatics, Academic Medical Center, Amsterdam, Meibergdreef 9, AZ, The Netherlands. 5. Division of Cardiology and Metabolism-Heart Failure, Cachexia & Sarcopenia, Department of Cardiology (CVK); Berlin-Brandenburg Center for Regenerative Therapies (BCRT), at Charité University Medicine, Charitépl. 1 Berlin, Germany. 6. Department of Cardiology and Pneumology, University Medicine Göttingen (UMG), DZHK (German Center for Cardiovascular Research), Robert-Koch-Straße 40, Göttingen, Germany. 7. National Heart & Lung Institute, Royal Brompton & Harefield Hospitals, Imperial College, Sydney St, Chelsea, London, UK. 8. Robertson Institute of Biostatistics and Clinical Trials Unit, University of Glasgow, University Avenue, Glasgow, UK. 9. University of Bergen, Stavanger University Hospital, Gerd-Ragna Bloch Thorsens gate 8, Stavanger, Norway. 10. School of Medicine, Department of Cardiology, Heart Failure Unit, Athens University Hospital Attikon, National and Kapodistrian University of Athens, 1, Rimini Str, Haidari, Athens Greece. 11. Division of Molecular & Clinical Medicine, University of Dundee, Dundee, UK. 12. Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, Institute of Cardiology, University of Brescia, Piazza del Mercato, 15, Brescia, Italy. 13. Department of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Groby Road, Leicester, UK. 14. NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Groby Road, Leicester, UK. 15. Department of Heart Diseases, Wroclaw Medical University, Rudolfa Weigla 5, Wroclaw, Poland. 16. Cardiology Department, Military Hospital, Rudolfa Weigla, Wroclaw, Poland. 17. CHU de Nancy, Inserm CIC 1433, Université de Lorrain, CHRU de Nancy, F-CRIN INI-CRCT Nancy, France.
Abstract
Aims: We sought to determine subtypes of patients with heart failure (HF) with a distinct clinical profile and treatment response, using a wide range of biomarkers from various pathophysiological domains. Methods and results: We performed unsupervised cluster analysis using 92 established cardiovascular biomarkers to identify mutually exclusive subgroups (endotypes) of 1802 patients with HF and reduced ejection fraction (HFrEF) from the BIOSTAT-CHF project. We validated our findings in an independent cohort of 813 patients. Based on their biomarker profile, six endotypes were identified. Patients with endotype 1 were youngest, less symptomatic, had the lowest N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels and lowest risk for all-cause mortality or hospitalization for HF. Patients with endotype 4 had more severe symptoms and signs of HF, higher NT-proBNP levels and were at highest risk for all-cause mortality or hospitalization for HF [hazard ratio (HR) 1.4; 95% confidence interval (CI) 1.1-1.8]. Patients with endotypes 2, 3, and 5 were better uptitrated to target doses of beta-blockers (P < 0.02 for all). In contrast to other endotypes, patients with endotype 5 derived no potential survival benefit from uptitration of angiotensin-converting enzyme-inhibitor/angiotensin-II receptor blocker and beta-blockers (Pinteraction <0.001). Patients with endotype 2 (HR 1.29; 95% CI 1.10-1.42) experienced possible harm from uptitration of beta-blockers in contrast to patients with endotype 4 and 6 that experienced benefit (Pinteraction for all <0.001). Results were strikingly similar in the independent validation cohort. Conclusion: Using unsupervised cluster analysis, solely based on biomarker profiles, six distinct endotypes were identified with remarkable differences in characteristics, clinical outcome, and response to uptitration of guideline directed medical therapy.
Aims: We sought to determine subtypes of patients with heart failure (HF) with a distinct clinical profile and treatment response, using a wide range of biomarkers from various pathophysiological domains. Methods and results: We performed unsupervised cluster analysis using 92 established cardiovascular biomarkers to identify mutually exclusive subgroups (endotypes) of 1802 patients with HF and reduced ejection fraction (HFrEF) from the BIOSTAT-CHF project. We validated our findings in an independent cohort of 813 patients. Based on their biomarker profile, six endotypes were identified. Patients with endotype 1 were youngest, less symptomatic, had the lowest N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels and lowest risk for all-cause mortality or hospitalization for HF. Patients with endotype 4 had more severe symptoms and signs of HF, higher NT-proBNP levels and were at highest risk for all-cause mortality or hospitalization for HF [hazard ratio (HR) 1.4; 95% confidence interval (CI) 1.1-1.8]. Patients with endotypes 2, 3, and 5 were better uptitrated to target doses of beta-blockers (P < 0.02 for all). In contrast to other endotypes, patients with endotype 5 derived no potential survival benefit from uptitration of angiotensin-converting enzyme-inhibitor/angiotensin-II receptor blocker and beta-blockers (Pinteraction <0.001). Patients with endotype 2 (HR 1.29; 95% CI 1.10-1.42) experienced possible harm from uptitration of beta-blockers in contrast to patients with endotype 4 and 6 that experienced benefit (Pinteraction for all <0.001). Results were strikingly similar in the independent validation cohort. Conclusion: Using unsupervised cluster analysis, solely based on biomarker profiles, six distinct endotypes were identified with remarkable differences in characteristics, clinical outcome, and response to uptitration of guideline directed medical therapy.
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: M Marcinkiewicz-Siemion; M Kaminski; M Ciborowski; K Ptaszynska-Kopczynska; A Szpakowicz; A Lisowska; M Jasiewicz; E Tarasiuk; A Kretowski; B Sobkowicz; K A Kaminski Journal: Sci Rep Date: 2020-01-10 Impact factor: 4.379
Authors: Jasper Tromp; Liselotte M Boerman; Iziah E Sama; Saskia W M C Maass; John H Maduro; Yoran M Hummel; Marjolein Y Berger; Geertruida H de Bock; Jourik A Gietema; Annette J Berendsen; Peter van der Meer Journal: Eur J Heart Fail Date: 2020-02-20 Impact factor: 15.534
Authors: Iziah E Sama; Rebecca J Woolley; Jan F Nauta; Simon P R Romaine; Jasper Tromp; Jozine M Ter Maaten; Peter van der Meer; Carolyn S P Lam; Nilesh J Samani; Leong L Ng; Marco Metra; Kenneth Dickstein; Stefan D Anker; Faiez Zannad; Chim C Lang; John G F Cleland; Dirk J van Veldhuisen; Hans L Hillege; Adriaan A Voors Journal: Eur J Heart Fail Date: 2020-04-03 Impact factor: 15.534
Authors: Charlotte Andersson; Asya Lyass; Vanessa Xanthakis; Martin G Larson; Gary F Mitchell; Susan Cheng; Ramachandran S Vasan Journal: PLoS One Date: 2019-10-15 Impact factor: 3.240
Authors: C Shi; H H van der Wal; H H W Silljé; M M Dokter; F van den Berg; L Huizinga; M Vriesema; J Post; S D Anker; J G Cleland; L L Ng; N J Samani; K Dickstein; F Zannad; C C Lang; P L van Haelst; J A Gietema; M Metra; P Ameri; M Canepa; D J van Veldhuisen; A A Voors; R A de Boer Journal: J Intern Med Date: 2020-05-05 Impact factor: 8.989