Dataset Information

Novel Urinary Peptidomic Classifier Predicts Incident Heart Failure.

ABSTRACT: BACKGROUND:Detection of preclinical cardiac dysfunction and prognosis of left ventricular heart failure (HF) would allow targeted intervention, and appears to be the most promising approach in its management. Novel biomarker panels may support this approach and provide new insights into the pathophysiology. METHODS AND RESULTS:A retrospective comparison of urinary proteomic profiles generated by mass spectrometric analysis from 49 HF patients, 36 patients who progressed to HF within 2.6±1.6 years, and 192 sex- and age-matched controls who did not progress to HF enabled identification of 96 potentially HF-specific peptide biomarkers. Based on these 96 peptides, the classifier called Heart Failure Predictor (HFP) was established by support vector machine modeling. The incremental prognostic value of HFP was subsequently evaluated in urine samples from 175 individuals with asymptomatic diastolic dysfunction from an independent population cohort. Within 4.8 years, 17 of these individuals progressed to overt HF. The area under receiver-operating characteristic curve was 0.70 (95% CI, 0.56-0.82); P=0.0047 for HFP and 0.57 (0.42-0.72; P=0.62) for N-terminal pro b-type natriuretic peptide. Hazard ratios were 1.63 (CI, 1.04-2.55; P=0.032) per 1-SD increment in HFP and 0.70 (CI, 0.35-1.41; P=0.32) for a doubling of the logarithmically transformed N-terminal pro b-type natriuretic peptide. CONCLUSIONS:HFP is a novel biomarker derived from the urinary proteome and might serve as a sensitive tool to improve risk stratification, patient management, and understanding of the pathophysiology of HF.

SUBMITTER: Zhang ZY

PROVIDER: S-EPMC5586413 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Novel Urinary Peptidomic Classifier Predicts Incident Heart Failure.

Zhang Zhen-Yu ZY Ravassa Susana S Nkuipou-Kenfack Esther E Yang Wen-Yi WY Kerr Shona M SM Koeck Thomas T Campbell Archie A Kuznetsova Tatiana T Mischak Harald H Padmanabhan Sandosh S Dominiczak Anna F AF Delles Christian C Staessen Jan A JA

Journal of the American Heart Association 20170807 8

<h4>Background</h4>Detection of preclinical cardiac dysfunction and prognosis of left ventricular heart failure (HF) would allow targeted intervention, and appears to be the most promising approach in its management. Novel biomarker panels may support this approach and provide new insights into the pathophysiology.<h4>Methods and results</h4>A retrospective comparison of urinary proteomic profiles generated by mass spectrometric analysis from 49 HF patients, 36 patients who progressed to HF with ...[more]

PMID: 28784649

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Project description:BackgroundCOVID-19 prediction models based on clinical characteristics, routine biochemistry and imaging, have been developed, but little is known on proteomic markers reflecting the molecular pathophysiology of disease progression.MethodsThe multicentre (six European study sites) Prospective Validation of a Proteomic Urine Test for Early and Accurate Prognosis of Critical Course Complications in Patients with SARS-CoV-2 Infection Study (Crit-COV-U) is recruiting consecutive patients (≥ 18 years) with PCR-confirmed SARS-CoV-2 infection. A urinary proteomic biomarker (COV50) developed by capillary-electrophoresis-mass spectrometry (CE-MS) technology, comprising 50 sequenced peptides and identifying the parental proteins, was evaluated in 228 patients (derivation cohort) with replication in 99 patients (validation cohort). Death and progression along the World Health Organization (WHO) Clinical Progression Scale were assessed up to 21 days after the initial PCR test. Statistical methods included logistic regression, receiver operating curve (ROC) analysis and comparison of the area under the curve (AUC).FindingsIn the derivation cohort, 23 patients died, and 48 developed worse WHO scores. The odds ratios (OR) for death per 1 standard deviation (SD) increment in COV50 were 3·52 (95% CI, 2·02-6·13, p <0·0001) unadjusted and 2·73 (1·25-5·95, p = 0·012) adjusted for sex, age, baseline WHO score, body mass index (BMI) and comorbidities. For WHO scale progression, the corresponding OR were 2·63 (1·80-3·85, p<0·0001) and 3·38 (1·85-6·17, p<0·0001), respectively. The area under the curve (AUC) for COV50 as a continuously distributed variable was 0·80 (0·72-0·88) for mortality and 0·74 (0·66-0·81) for worsening WHO score. The optimised COV50 thresholds for mortality and worsening WHO score were 0·47 and 0·04 with sensitivity/specificity of 87·0 (74·6%) and 77·1 (63·9%), respectively. On top of covariates, COV50 improved the AUC, albeit borderline for death, from 0·78 to 0·82 (p = 0·11) and 0·84 (p = 0·052) for mortality and from 0·68 to 0·78 (p = 0·0097) and 0·75 (p = 0·021) for worsening WHO score. The validation cohort findings were confirmatory.InterpretationThis first CRIT-COV-U report proves the concept that urinary proteomic profiling generates biomarkers indicating adverse COVID-19 outcomes, even at an early disease stage, including WHO stages 1-3. These findings need to be consolidated in an upcoming final dataset.FundingThe German Federal Ministry of Health funded the study.

Project description:Study Objectives:Heart failure has previously been linked to sleep disorders that are often associated with frequent disturbances to human rest/activity patterns. We tested whether fragmentation of sustained rest/activity patterns derived from actigraphic recordings at baseline predicts incident heart failure in community-based elderly individuals. Methods:We studied 1099 community-based elderly adults participating in the Rush Memory and Aging Project who had baseline motor activity monitoring up to 11 days and were followed annually for up to 14 years. Fragmentation was assessed using previously validated indexes, derived from the probability of transitions once sustained rest or activity has been established. Heart failure was recorded via a clinical interview during the annual follow-up. Cox proportional hazards models were constructed to examine the relationship between rest fragmentation index and incident heart failure. Covariates grouped in terms of demographics, lifestyle factors and co-morbidities and cardiovascular risk factors/diseases were included. Results:Increased rest fragmentation (but not activity fragmentation) was associated with higher risk for incident heart failure. Specifically, a subject with a rest fragmentation at the 90th percentile showed a 57% increased risk of developing incident heart failure compared to a subject at the 10th percentile in this cohort. This effect was equivalent to that of being over a decade older. These observations were consistent after adjusting for all covariates. Conclusion:Increased rest fragmentation, a potential surrogate for sleep fragmentation, is independently associated with a higher risk of developing heart failure in community-based elderly adults during up to 14 years of follow-up. Further work is required to examine the specific contributions from daytime napping versus nighttime sleep periods in the elderly, as well as the underlying autonomic and cardio-dynamic pathways that may explain the effects on heart function.

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Novel Urinary Peptidomic Classifier Predicts Incident Heart Failure.

Publications

Novel Urinary Peptidomic Classifier Predicts Incident Heart Failure.

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