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Identification of metabolic biomarkers in atrial fibrillation patients via the integrated application of proteomics and metabolomics
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  • Xiao-ying Chao,
  • Yun-jing Xu,
  • Hong Zhang,
  • Na Xing,
  • Chi Shu,
  • Francis Chanda,
  • Abdallah Chaurembo,
  • Hui-juan Zhang,
  • Jian-yuan Huang,
  • Li-dan Fu,
  • Guo-qiang Zhong,
  • Han-bin Lin,
  • Kai-xuan Lin
Xiao-ying Chao
The First Affiliated Hospital of Guangxi Medical University
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Yun-jing Xu
Shanghai Institute of Materia Medica Chinese Academy of Sciences
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Hong Zhang
Zhongshan Hospital of Traditional Chinese Medicine Affiliated to Guangzhou University of Chinese Medicine
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Na Xing
Zhongshan Institute for Drug Discovery, SIMM, CAS, Zhongshan Guangdong, China

Corresponding Author:[email protected]

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Chi Shu
Shenyang Agricultural University
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Francis Chanda
Shanghai Institute of Materia Medica Chinese Academy of Sciences
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Abdallah Chaurembo
Shanghai Institute of Materia Medica Chinese Academy of Sciences
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Hui-juan Zhang
Zunyi Medical University
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Jian-yuan Huang
Southern Medical University School of Pharmaceutical Sciences
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Li-dan Fu
Zunyi Medical University
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Guo-qiang Zhong
The First Affiliated Hospital of Guangxi Medical University
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Han-bin Lin
Shanghai Institute of Materia Medica Chinese Academy of Sciences
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Kai-xuan Lin
Zhongshan Hospital of Traditional Chinese Medicine Affiliated to Guangzhou University of Chinese Medicine
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Abstract

Atrial fibrillation (AF) is a prevalent clinical arrhythmia characterized by an irregular cardiac rhythm, increasing the risk of developing stroke and heart failure. In order to explore the potential role of serum indicators, the study employed a combination of targeted metabolomics and Tandem Mass Tag (TMT) based proteomics to examine metabolic characteristics and biomarkers in the serum of patients with AF. Furthermore, the verification of protein expressions with diagnostic significance for AF was conducted in patients of larger sample sizes by ELISA. Proteomics and metabolomics identified 174 differentially expressed proteins (DEPs) and 294 differentially metabolites (DMs) in AF patients, respectively. The clustering and functional enrichment analysis identified the complement and coagulation cascade as the primary pathway dysregulating DEPs. According to the integrated study, the most enriched proteomics and metabolomics pathways were platelet activation and cholesterol metabolism. lactate dehydrogenase A (LDHA), lactate dehydrogenase B (LDHB), and transgelin 2 (TAGLN2) were significantly expressed in AF patients, while plasminogen (PLG) was low. In conclusion, the current study found that platelet activation, cholesterol metabolism, and the complement and coagulation cascade pathways may affect AF progression. The study also showed that LDHA, LDHB, TAGLN2, and PLG may be potential AF biomarkers.