Urinary proteome analysis in hypertensive patients with left ventricular diastolic dysfunction

Abstract

AimsDespite the significant heart failure (HF) burden on society, easily applicable screening techniques, particularly for the early detection of asymptomatic left ventricular (LV) dysfunction, are lacking. The present study aimed to identify and test a set of urinary polypeptides that may indicate early LV diastolic dysfunction as defined by echocardiography in hypertensive patients in a cross-sectional case -control study nested within the FLEMish study on ENvironment, Genes and Health Outcome (FLEMENGHO). Methods and resultsTo identify potentially discriminating urinary biomarkers for LV diastolic dysfunction, we applied capillary electrophoresis coupled to mass spectrometry. In the discovery set, we compared 19 hypertensive patients with asymptomatic LV diastolic dysfunction with 19 healthy controls. In the absence of adjustment for multiple testing, 85 urinary peptides were different between cases and controls at a P-value of ,0.033. With adjustment for multiple testing, three potential biomarkers remained significantly different between cases and controls (P ≤ 0.02). We combined the 85 potential biomarkers in a high-dimensional model (classifier), which we applied in a blinded manner to an independent test set of 16 hypertensive patients with symptomatic HF and 16 healthy controls. Upon unblinding, the area under the receiver operating characteristic curve (AUC) of the HF classification was 0.84 (95% CI: 0.70 -0.98; P ¼ 0.001). ConclusionIn asymptomatic hypertensive patients with LV diastolic dysfunction, we identified a set of urinary polypeptides specific for essential hypertension with LV diastolic dysfunction that subsequently distinguished hypertensive patients with overt HF from healthy controls.--

Left ventricular diastolic function in relation to the urinary proteome: a proof-of-concept study in a general population

“…In line with this concept, we identified in a preliminary case-control study 85 urinary peptides, mainly up-or down-regulated collagen fragments, that discriminated between 19 hypertensive patients with asymptomatic diastolic LV dysfunction and 19 controls [11]. With adjustments applied for multiple testing three urinary peptide biomarkers remained significant [11]. In an attempt to find ways to facilitate the diagnosis of asymptomatic diastolic LV dysfunction, we evaluated in a Flemish population sample the association of diastolic LV function, analysed as a continuous or categorical variable, with urinary proteomic biomarkers combined in a high-dimensional model (classifier).…”

“…Whatever the underlying mechanism, modification in the extracellular myocardial matrix and collagen turnover are hallmarks of diastolic LV dysfunction. In line with this concept, we identified in a preliminary case-control study 85 urinary peptides, mainly up-or down-regulated collagen fragments, that discriminated between 19 hypertensive patients with asymptomatic diastolic LV dysfunction and 19 controls [11]. With adjustments applied for multiple testing three urinary peptide biomarkers remained significant [11].…”

Development and Validation of Urine-based Peptide Biomarker Panels for Detecting Bladder Cancer in a Multi-center Study

“…12,22). The MosaCluster software tool allows for the classification of samples in the high dimensional parameter space by using SVM algorithms, previously shown to be particularly effective in analyzing high dimensional proteomics datasets (22,23). The software generates a classifier, based on predefined peptides.…”

“…23). The data files were analyzed using Proteome Discoverer 1.2 (activation type: HCD; min-max precursor mass: 790-6,000 Da; precursor mass tolerance: 10 ppm; fragment mass tolerance: 0.05 Da; S/N threshold: (i) and were searched against the Uniprot human nonredundant database without enzyme specificity.…”

Use of Biomarkers in the Evaluation and Treatment of Hypertensive Patients

“…Multidimensional biomarkers that are based on omics techniques have again the potential to overcome the limitations of single biomarkers and there is already some evidence that proteomic signatures associated with early functional cardiac changes are predictive of development of overt heart failure [108]. Clearly such approaches are not yet ready for the clinic but with technology developing so rapidly omics based biomarkers may not only get more precise but also less expensive in the near future [29].…”