Evidence map›Paper›PMID 42783755›Full record

ArticleMetabolites2026

Targeted Quantitative Metabolomics and Lipidomics Reveal Dysregulated Metabolic Networks and a Serum Candidate Biomarker for Atrial Fibrillation.

Yuqing Zhang, Yunpeng Xie, Xinyu Liu, Zhen Ning, Guowang Xu, Yunlong Xia, Xinjie Zhao

Abstract read
In one paragraph

Article in Metabolites, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Yuqing ZhangMetabolomics Subcenter of the National Genomics Data Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.ORCID 0009-0001-9974-5859
Yunpeng XieThe First Affiliated Hospital of Dalian Medical University, Dalian 116011, China.ORCID 0000-0002-0140-1055
Xinyu LiuMetabolomics Subcenter of the National Genomics Data Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.ORCID 0000-0002-0564-7167
Zhen NingThe First Affiliated Hospital of Dalian Medical University, Dalian 116011, China.
Guowang XuMetabolomics Subcenter of the National Genomics Data Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.ORCID 0000-0003-4298-3554
Yunlong XiaThe First Affiliated Hospital of Dalian Medical University, Dalian 116011, China.
Xinjie ZhaoMetabolomics Subcenter of the National Genomics Data Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.

Funding

Dalian Institute of Chemical Physics DICP I202004National Natural Science Foundation of China 22274151
6 · The paper itself

Abstract

backgroundAtrial fibrillation (AF) is the most prevalent clinical arrhythmia with severe cardiovascular complications, yet its metabolic molecular mechanisms remain poorly defined. Omics-based metabolic profiling provides a powerful strategy to systematically decode AF-associated metabolic disorders.

methodsIn this work, high-coverage targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) metabolomics and lipidomics were applied to absolutely quantify 746 serum metabolites from AF patients and healthy controls.

resultsWe systematically characterized global metabolic perturbations in AF serum, including impaired fatty acid metabolism, suppressed mitochondrial β-oxidation, myocardial lipotoxic lipid accumulation, and systemic depletion of glycerophospholipids. Global multiscale embedded correlation network analysis (MECNA) further identified 11 AF-specific dysregulated metabolic modules and core hub metabolites driving metabolic remodeling. Leveraging binary logistic regression, we constructed and independently validated a two-molecule diagnostic biomarker panel to distinguish AF patients from healthy subjects. The combined biomarkers Phe-Trp and FA 22:5 achieved outstanding diagnostic performance, with area under the curve (AUC) values of 0.964 in the discovery cohort and 0.993 in the validation cohort.

conclusionsCollectively, this study adopts high-depth targeted quantitative omics to comprehensively map AF metabolic signatures, dissect disease-relevant metabolic networks, and establish a robust serum biomarker panel with great translational potential for non-invasive AF clinical diagnosis.

Indexed as

atrial fibrillationlipidomicsmetabolic networkmetabolomicsserum biomarker

Identifiers

PMID42783755
PMCPMC13609185

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