A protein panel including IGSF1, IGHG1, PTX3, and 55kDa erythrocyte membrane protein differentiated HFimpEF from HFrEF with 90% AUC accuracy.
Does serum proteome profiling identify biomarkers that can discriminate HFimpEF from HFrEF?
A novel 4-protein serum biomarker panel demonstrates high diagnostic precision for distinguishing heart failure with improved ejection fraction from heart failure with reduced ejection fraction.
Tasa de eventos absoluta: 0% vs 0%
Abstract Background Heart failure (HF) with improved ejection fraction (HFimpEF) has emerged as a distinct HF subtype, characterized by left ventricular reverse modeling and myocardial recovery. However, the underlying pathophysiological mechanisms remain unclear, and the specific diagnostic and predictive biomarkers are still lacking. Objectives This study analyzed the difference in serum proteomic profiles of HFimpEF and HF with reduced ejection fraction (HFrEF) patients, aiming to identify biomarkers indicating myocardial recovery potential and reveal novel molecular targets to improve cardiac function. Methods This study performed untargeted serum proteome profiling using data-independent acquisition-based label-free quantitative liquid chromatography–tandem mass spectrometry in 55 patients with HFimpEF, as compared with 33 HFrEF patients. Differentially expressed proteins (DEP) between the 2 groups were analyzed and were further classified using the Boruta algorithm. The proteins’ diagnostic performance was evaluated by area under the curve (AUC) and validated using the 10-fold cross-validation. Gene Ontology (GO) and pathway enrichment analysis were performed to identify significantly enriched biological functions and pathways associated with the DEP. Results Quantitative proteomic analysis identified 2,461 serum proteins across 88 patients with HFimpEF or HFrEF. Of these, 1,712 proteins showed high detection consistency (≥60% prevalence) and were retained for comparative analysis, resulting in a total of 35 DEP. Specifically, HFimpEF patients exhibited 33 up-regulated and 2 down-regulated proteins compared to those with HFrEF. The Boruta machine learning algorithm prioritized 9 signature proteins as key discriminators between the two phenotypes. The combination of immunoglobulin superfamily member 1, immunoglobulin heavy constant gamma 1, pentraxin-related protein PTX3, and 55 kDa erythrocyte membrane protein exhibited the best diagnostic precision (AUC: 0.90; 95% CI: 0.83-0.97) to distinguish patients with HFimpEF from HFrEF. Salient biologic themes related to thrombosis, immune regulation, cellular motility and membrane integrity were predominant in HFimpEF. Conclusions Characterized differences existed in serum proteomic profiles between HFrEF and HFimpEF patients. These newly identified proteins warrant further evaluation to establish their role in the restoration of myocardial function, and their diagnostic perspective to predict the incidence of HFimpEF.ROC Curve GO Analysis
Yang et al. (Sat,) reported a other. A protein panel including IGSF1, IGHG1, PTX3, and 55kDa erythrocyte membrane protein differentiated HFimpEF from HFrEF with 90% AUC accuracy.
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