Lee Lee Wong1, Ruiyang Zou2, Lihan Zhou2, Jia Yuen Lim1, Dominic C Y Phua3, Chengcheng Liu3, Jenny P C Chong1, Jessica Y X Ng1, Oi Wah Liew1, Siew Pang Chan1, Yei-Tsung Chen4, Michelle M Y Chan5, Poh Shuan D Yeo6, Tze Pin Ng7, Lieng H Ling8, David Sim9, Kui Toh G Leong10, Hean Y Ong11, Fazlur Jaufeerally12, Raymond Wong13, Ping Chai13, Adrian F Low8, Mayanna Lund14, Gerry Devlin15, Richard Troughton16, Vicky A Cameron16, Robert N Doughty17, Carolyn S P Lam18, Heng Phon Too19, Arthur Mark Richards20. 1. Cardiovascular Research Institute, National University Health System, Singapore; Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore. 2. Bioprocessing Technology Institute, A*STAR, Singapore; MiRXES Pted Ltd, Singapore. 3. ETPL-DxD, A*STAR, Singapore. 4. Cardiovascular Research Institute, National University Health System, Singapore; Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Life Sciences and Institute of Genome Sciences National Yang-Ming University, Taipei, Taiwan. 5. Duke-NUS Graduate Medical School, Singapore. 6. Department of Cardiology, Tan Tock Seng Hospital, Singapore; Apex Heart Clinic, Gleneagles Hospital, Singapore. 7. Department of Psychological Medicine, National University of Singapore, Singapore. 8. Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Cardiac Department, National University Health System, Singapore. 9. National Heart Centre, Singhealth, Singapore. 10. Department of Cardiology, Changi General Hospital, Singapore. 11. Department of Cardiology, Khoo Teck Puat Hospital, Singapore. 12. Duke-NUS Graduate Medical School, Singapore; Department of Internal Medicine, Singapore General Hospital, Singapore. 13. Cardiac Department, National University Health System, Singapore; National University Heart Centre, National University Hospital, Singapore. 14. Middlemore Hospital, Otahuhu, Auckland, New Zealand. 15. Waikato Hospital, Hamilton, New Zealand. 16. Christchurch Heart Institute, University of Otago, Christchurch, New Zealand. 17. Heart Health Research Group, University of Auckland, Auckland, New Zealand. 18. National Heart Centre Singapore and Duke-National University of Singapore, Singapore. 19. Bioprocessing Technology Institute, A*STAR, Singapore; Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore. 20. Cardiovascular Research Institute, National University Health System, Singapore; Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Cardiac Department, National University Health System, Singapore; Christchurch Heart Institute, University of Otago, Christchurch, New Zealand. Electronic address: arthur_mark_richards@nuhs.edu.sg.
Abstract
BACKGROUND: Clinicians need improved tools to better identify nonacute heart failure with preserved ejection fraction (HFpEF). OBJECTIVES: The purpose of this study was to derive and validate circulating microRNA signatures for nonacute heart failure (HF). METHODS: Discovery and validation cohorts (N = 1,710), comprised 903 HF and 807 non-HF patients from Singapore and New Zealand (NZ). MicroRNA biomarker panel discovery in a Singapore cohort (n = 546) was independently validated in a second Singapore cohort (Validation 1; n = 448) and a NZ cohort (Validation 2; n = 716). RESULTS: In discovery, an 8-microRNA panel identified HF with an area under the curve (AUC) 0.96, specificity 0.88, and accuracy 0.89. Corresponding metrics were 0.88, 0.66, and 0.77 in Validation 1, and 0.87, 0.58, and 0.74 in Validation 2. Combining microRNA panels with N-terminal pro-B-type natriuretic peptide (NT-proBNP) clearly improved specificity and accuracy from AUC 0.96, specificity 0.91, and accuracy 0.90 for NT-proBNP alone to corresponding metrics of 0.99, 0.99, and 0.93 in the discovery and 0.97, 0.96, and 0.93 in Validation 1. The 8-microRNA discovery panel distinguished HFpEF from HF with reduced ejection fraction with AUC 0.81, specificity 0.66, and accuracy 0.72. Corresponding metrics were 0.65, 0.41, and 0.56 in Validation 1 and 0.65, 0.41, and 0.62 in Validation 2. For phenotype categorization, combined markers achieved AUC 0.87, specificity 0.75, and accuracy 0.77 in the discovery with corresponding metrics of 0.74, 0.59, and 0.67 in Validation 1 and 0.72, 0.52, and 0.68 in Validation 2, as compared with NT-proBNP alone of AUC 0.71, specificity 0.46, and accuracy 0.62 in the discovery; with corresponding metrics of 0.72, 0.44, and 0.57 in Validation 1 and 0.69, 0.48, and 0.66 in Validation 2. Accordingly, false negative (FN) (81% Singapore and all NZ FN cases were HFpEF) as classified by a guideline-endorsed NT-proBNP ruleout threshold, were correctly reclassified by the 8-microRNA panel in the majority (72% and 88% of FN in Singapore and NZ, respectively) of cases. CONCLUSIONS: Multi-microRNA panels in combination with NT-proBNP are highly discriminatory and improved specificity and accuracy in identifying nonacute HF. These findings suggest potential utility in the identification of nonacute HF, where clinical assessment, imaging, and NT-proBNP may not be definitive, especially in HFpEF.
BACKGROUND: Clinicians need improved tools to better identify nonacute heart failure with preserved ejection fraction (HFpEF). OBJECTIVES: The purpose of this study was to derive and validate circulating microRNA signatures for nonacute heart failure (HF). METHODS: Discovery and validation cohorts (N = 1,710), comprised 903 HF and 807 non-HF patients from Singapore and New Zealand (NZ). MicroRNA biomarker panel discovery in a Singapore cohort (n = 546) was independently validated in a second Singapore cohort (Validation 1; n = 448) and a NZ cohort (Validation 2; n = 716). RESULTS: In discovery, an 8-microRNA panel identified HF with an area under the curve (AUC) 0.96, specificity 0.88, and accuracy 0.89. Corresponding metrics were 0.88, 0.66, and 0.77 in Validation 1, and 0.87, 0.58, and 0.74 in Validation 2. Combining microRNA panels with N-terminal pro-B-type natriuretic peptide (NT-proBNP) clearly improved specificity and accuracy from AUC 0.96, specificity 0.91, and accuracy 0.90 for NT-proBNP alone to corresponding metrics of 0.99, 0.99, and 0.93 in the discovery and 0.97, 0.96, and 0.93 in Validation 1. The 8-microRNA discovery panel distinguished HFpEF from HF with reduced ejection fraction with AUC 0.81, specificity 0.66, and accuracy 0.72. Corresponding metrics were 0.65, 0.41, and 0.56 in Validation 1 and 0.65, 0.41, and 0.62 in Validation 2. For phenotype categorization, combined markers achieved AUC 0.87, specificity 0.75, and accuracy 0.77 in the discovery with corresponding metrics of 0.74, 0.59, and 0.67 in Validation 1 and 0.72, 0.52, and 0.68 in Validation 2, as compared with NT-proBNP alone of AUC 0.71, specificity 0.46, and accuracy 0.62 in the discovery; with corresponding metrics of 0.72, 0.44, and 0.57 in Validation 1 and 0.69, 0.48, and 0.66 in Validation 2. Accordingly, false negative (FN) (81% Singapore and all NZ FN cases were HFpEF) as classified by a guideline-endorsed NT-proBNP ruleout threshold, were correctly reclassified by the 8-microRNA panel in the majority (72% and 88% of FN in Singapore and NZ, respectively) of cases. CONCLUSIONS: Multi-microRNA panels in combination with NT-proBNP are highly discriminatory and improved specificity and accuracy in identifying nonacute HF. These findings suggest potential utility in the identification of nonacute HF, where clinical assessment, imaging, and NT-proBNP may not be definitive, especially in HFpEF.
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