Integration of proteomic and metabolomic characterization in atrial fibrillation-induced heart failure

Abstract

Background The exact mechanism of atrial fibrillation (AF)-induced heart failure (HF) remains unclear. Proteomics and metabolomics were integrated to in this study, as to describe AF patients’ dysregulated proteins and metabolites, comparing patients without HF to patients with HF. Methods Plasma samples of 20 AF patients without HF and another 20 with HF were analyzed by multi-omics platforms. Proteomics was performed with data independent acquisition-based liquid chromatography-tandem mass spectrometry (LC-MS/MS), as metabolomics was performed with LC-MS/MS platform. Proteomic and metabolomic results were analyzed separately and integrated using univariate statistical methods, multivariate statistical methods or machine learning model. Results We found 35 up-regulated and 15 down-regulated differentially expressed proteins (DEPs) in AF patients with HF compared to AF patients without HF. Moreover, 121 up-regulated and 14 down-regulated differentially expressed metabolites (DEMs) were discovered in HF patients compared to AF patients without HF. An integrated analysis of proteomics and metabolomics revealed several significantly enriched pathways, including Glycolysis or Gluconeogenesis, Tyrosine metabolism and Pentose phosphate pathway. A total of 10 DEPs and DEMs selected as potential biomarkers provided excellent predictive performance, with an AUC of 0.94. In addition, subgroup analysis of HF classification was performed based on metabolomics, which yielded 9 DEMs that can distinguish between AF and HF for HF classification. Conclusions This study provides novel insights to understanding the mechanisms of AF-induced HF progression and identifying novel biomarkers for prognosis of AF with HF by using metabolomics and proteomics analyses.

Integrated proteomic and metabolomic profiling reveals novel insights on the inflammation and immune response in HFpEF

“…In recent times, proteomics and metabolomics have emerged as innovative tools not only for identifying new risk factors but also for elucidating the underlying mechanisms of cardiovascular disease [ 9 ]. Previous studies have revealed aberrant alterations in numerous proteins and metabolites among patients with HFpE [ 19 – 22 ].…”

“…The proteins were introduced into a mass spectrometer (Q Exactiv HF-X; Thermo Fisher, Germany) linked to a chromatography platform (EASY-nL 1200 UHPLC system; Thermo Fisher, Germany) with DIA mode selected for data collection. Differentially expressed proteins (DEPs) of significant interest were identified based on a fold-change of ≥ 1.5 or ≤ 0.67 and a t-test p -value of < 0.05 [ 9 ]. Subsequent mapping of DEPs and pathway analysis was facilitated utilizing the KEGG pathway database.…”

“…The Vanquish UHPLC system (ThermoFisher, Germany) was coupled with either an Orbitrap Q Exactive HF or an Orbitrap Q Exactive HF-X mass spectrometer (Thermo Fisher, Germany) for metabolite separation and identification. Differential expression of metabolites (DEMs) was assessed based on criteria including Variable Importance in Projection (VIP) > 1.0, Fold Change (FC) > 1.2 or FC < 0.833, and a significance level of P-value < 0.05 [ 9 ]. The metabolic pathways enriched in DEM were analyzed using the KEGG database.…”

“…Proteomics and metabolomics are ‘omics’ technologies that comprehensively analyze the entire proteome and metabolome within specific biological samples [ 9 ]. Unlike genetics, which focuses on the hereditary aspects of diseases, proteomics and metabolomics provide insights into the phenotype and progression of diseases [ 10 ].…”

Using Omics to Identify Novel Therapeutic Targets in Heart Failure

“…Some identified proteins were shared among multiple targeted proteomic studies, which improved the validity of those findings and would be a strength in any other omics findings. 66,[68][69][70] Zhang et al 68 identified and replicated 64 proteins associated with HFrEF hospitalization or cardiovascular death. The significantly associated proteins included a novel protein association, SVEP1 (Sushi, von Willebrand factor type A, EGF and pentraxin domain containing 1), an extracellular matrix protein expressed in vascular smooth muscle that promotes inflammation and atherosclerosis.…”