AIMS: Urine proteome analysis (UPA) has already provided accurate discriminatory patterns of urinary peptides for renal disease, coronary artery disease, and asymptomatic LV diastolic dysfunction. UPA has now been used to characterize a discriminatory peptide biomarker pattern and establish a diagnostic classifier for heart failure patients with reduced ejection fraction (HFrEF) in the presence of chronic kidney disease (CKD). METHODS AND RESULTS: We analysed the urine proteome profiles obtained by capillary electrophoresis online coupled to micro-TOF (time of flight) mass spectrometry of 126 individuals, 59 HFrEF patients and 67 controls matched for age, sex, and renal function. In total, 107 significant discriminatory peptides were identified and used to establish a support vector machine-based classifier that was successfully applied to a test set of 25 HFrEF patients and 33 controls, achieving 84% sensitivity and 91% specificity. The majority of sequenced peptides were fragments of collagen type I and III. CONCLUSION: UPA was able to identify a set of HFrEF-specific urinary peptide biomarkers on a background of CKD that were successfully utilized to establish a syndrome's classifier.
AIMS: Urine proteome analysis (UPA) has already provided accurate discriminatory patterns of urinary peptides for renal disease, coronary artery disease, and asymptomatic LV diastolic dysfunction. UPA has now been used to characterize a discriminatory peptide biomarker pattern and establish a diagnostic classifier for heart failurepatients with reduced ejection fraction (HFrEF) in the presence of chronic kidney disease (CKD). METHODS AND RESULTS: We analysed the urine proteome profiles obtained by capillary electrophoresis online coupled to micro-TOF (time of flight) mass spectrometry of 126 individuals, 59 HFrEF patients and 67 controls matched for age, sex, and renal function. In total, 107 significant discriminatory peptides were identified and used to establish a support vector machine-based classifier that was successfully applied to a test set of 25 HFrEF patients and 33 controls, achieving 84% sensitivity and 91% specificity. The majority of sequenced peptides were fragments of collagen type I and III. CONCLUSION: UPA was able to identify a set of HFrEF-specific urinary peptide biomarkers on a background of CKD that were successfully utilized to establish a syndrome's classifier.
Authors: Wouter C Meijers; Antoni Bayes-Genis; Alexandre Mebazaa; Johann Bauersachs; John G F Cleland; Andrew J S Coats; James L Januzzi; Alan S Maisel; Kenneth McDonald; Thomas Mueller; A Mark Richards; Petar Seferovic; Christian Mueller; Rudolf A de Boer Journal: Eur J Heart Fail Date: 2021-10-10 Impact factor: 17.349
Authors: Thong H Cao; Donald J L Jones; Adriaan A Voors; Paulene A Quinn; Jatinderpal K Sandhu; Daniel C S Chan; Helen M Parry; Mohapradeep Mohan; Ify R Mordi; Iziah E Sama; Stefan D Anker; John G Cleland; Kenneth Dickstein; Gerasimos Filippatos; Hans L Hillege; Marco Metra; Piotr Ponikowski; Nilesh J Samani; Dirk J Van Veldhuisen; Faiez Zannad; Chim C Lang; Leong L Ng Journal: Eur J Heart Fail Date: 2019-11-06 Impact factor: 15.534
Authors: Ayman S Bannaga; Jochen Metzger; Ioannis Kyrou; Torsten Voigtländer; Thorsten Book; Jesus Melgarejo; Agnieszka Latosinska; Martin Pejchinovski; Jan A Staessen; Harald Mischak; Michael P Manns; Ramesh P Arasaradnam Journal: EBioMedicine Date: 2020-11-05 Impact factor: 8.143