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Comprehensive metabolomic and proteomic analyses reveal candidate biomarkers and related metabolic networks in atrial fibrillation

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Abstract

Introduction

Atrial fibrillation (AF) is an abnormal heart rhythm characterized by an irregular beating of the atria and is associated with an increased risk of heart failure, dementia, and stroke. Currently, the perturbation of plasma content due to AF disease onset is not well known.

Objectives

To investigate dysregulated molecules in blood plasma of untreated AF patients, with the goal of identifying biomarkers for disease screening and pathological studies.

Methods

LC-MS based untargeted metabolomics, lipidomics and proteomics analyses were performed to find candidate biomarkers. A targeted quantification assay and an ELISA were performed to validate the results of the omics analyses.

Results

We found that 24 metabolites, 16 lipids and 16 proteins were significantly dysregulated in AF patients. Pathway enrichment analysis showed that the purine metabolic pathway and fatty acid metabolism were perturbed by AF onset. FA 20:2 and FA 22:4 show great linear correlational relationship with the left atrial area and could be considered for AF disease stage monitoring or prognosis evaluation.

Conclusion

we used a comprehensive multiple-omics strategy to systematically investigate the dysregulated molecules in the plasma of AF patients, thereby revealing potential biomarkers for diagnosis and providing information for pathological studies.

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Abbreviations

AF:

Atrial fibrillation

ECG:

Electrocardiogram

LC–MS:

Liquid chromatography–mass spectrometry

DDA:

Data-dependent acquisition

PRM:

Parallel reaction monitoring

MS/MS:

Tandem mass spectrometry

QC:

Quality control

PCA:

Principle component analysis

FA:

Fatty acid

ACar:

Acylcarnitine

OxFA:

Oxidized fatty acid

GSS:

Glutathione synthetase

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Funding

This study was supported by the Fund for Fostering Young Scholars of Peking University Health Science Center (Grant No. BMU2018PY006) and the National Natural Science Foundation of China (Grant No. 81570235).

Author information

Author notes

  1. Juntuo Zhou and Lijie Sun have contributed equally to this study.

Authors and Affiliations

  1. Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital; Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Ministry of Health; Key Laboratory of Molecular Cardiovascular Science, Ministry of Education; Beijing Key Laboratory of Cardiovascular Receptors Research, No. 49, Hua Yuan North Rd, Hai Dian District, Beijing, 100191, China

    Lijie Sun, Liwen Chen, Shuwang Liu & Ming Cui

  2. Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing, 100083, China

    Juntuo Zhou

  3. Center of Medical and Health Analysis, Peking University Health Science Center, Beijing, 100191, China

    Lijun Zhong

Authors
  1. Juntuo Zhou
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  2. Lijie Sun
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  3. Liwen Chen
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  4. Shuwang Liu
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  5. Lijun Zhong
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Contributions

JZ, LS, LZ and MC designed the study. LS, LC and SL collected samples and performed clinical related analyses. JZ and LZ performed metabolomics and proteomics experiments. JZ analyzed the data. LC and SL reviewed statistical analyses. JZ and MC wrote the manuscript. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Lijun Zhong or Ming Cui.

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Conflict of interests

The authors declare that they have no conflict of interests.

Ethics approval

The study was approved by the Clinical Ethics Committee of Peking University Third Hospital and conforms to the principles in the Declaration of Helsinki. The samples were obtained only from patients who agreed to undergo the exam for the purpose of laboratory research, and informed consent was obtained from all patients who were asked to donate blood. All methods were performed in accordance with the relevant guidelines and regulations.

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Awritten informed consent was obtained from all the included patients.

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Zhou, J., Sun, L., Chen, L. et al. Comprehensive metabolomic and proteomic analyses reveal candidate biomarkers and related metabolic networks in atrial fibrillation. Metabolomics 15, 96 (2019). https://doi.org/10.1007/s11306-019-1557-7

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