ArticleBMC genomics2022
Integration of proteomic and metabolomic characterization in atrial fibrillation-induced heart failure.
Article in BMC genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 46 citations in OpenAlex.
- The Defect of iNKT Cells Mediates Mitochondrial Dysfunction Through IL-6/STAT3 Signaling to Induce Atrial Inflammation and Fibrosis to Aggravate Postoperative Atrial Fibrillation.Physiological research · 2026Article
- Biochemically Constrained Multi-Omics Integration Reveals Protein-Metabolite Dependencies Across Diseases.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Integrated transcriptomic, proteomic, and metabolomic analyses reveal molecular mechanisms underlying clutch length differences in goose ovaries.Poultry science · 2026Article
- The Use of Metabolomes in Risk Stratification of Patients with Heart Failure: A Scoping Review.Life (Basel, Switzerland) · 2026Review
- MicroRNAs in Heart Failure Pathogenesis and Progression: Mechanistic Control, Biomarker Potential, and Translational Perspectives.Life (Basel, Switzerland) · 2026Review
- Article
- Integrated Proteomics and Metabolomics Reveal Regulatory Pathways Underlying Quality Differences Between Wild and CultivatedJournal of fungi (Basel, Switzerland) · 2025Article
- The associations between circulating amino acids and arterial aneurysms and dissection: A bidirectional Mendelian randomization study.International journal of cardiology. Cardiovascular risk and prevention · 2025Article
- Identification of noval diagnostic biomarker for HFpEF based on proteomics and machine learning.Proteome science · 2025Article
- Exploring molecular characteristics and interactions of blood stasis syndrome in ischemic heart failure by integrated multi-omics.Frontiers in molecular biosciences · 2025Article
- Metabolomics in Atrial Fibrillation: Unlocking Novel Biomarkers and Pathways for Diagnosis, Prognosis, and Personalized Treatment.Journal of clinical medicine · 2024Review
- Integrative proteomic and metabolomic elucidation of cardiomyopathy with in vivo and in vitro models and clinical samples.Molecular therapy : the journal of the American Society of Gene Therapy · 2024Review
- Integrated proteomic and metabolomic profiling reveals novel insights on the inflammation and immune response in HFpEF.BMC genomics · 2024Article
- Using Omics to Identify Novel Therapeutic Targets in Heart Failure.Circulation. Genomic and precision medicine · 2024Review
- Atrial fibrillation: pathophysiology, genetic and epigenetic mechanisms.The Lancet regional health. Europe · 2024Review
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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.
methodsPlasma 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.
resultsWe 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.
conclusionsThis 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.