Investigation into potential mechanisms of metabolic syndrome by integrative analysis of metabolomics and proteomics

PLoS One. 2022 Jul 5;17(7):e0270593. doi: 10.1371/journal.pone.0270593. eCollection 2022.

Abstract

Metabolic syndrome (MetS) is a complex syndrome cluster of metabolic disorders, which greatly increases the risks of diabetic and cardiovascular diseases. Although it has become a significantly worldwide public health burden, its pathogenesis largely remains unknown. In this study, we first performed an integrated analysis of proteomic and metabonomic data of liver tissues of rats between MetS and control groups to reveal possible mechanisms of MetS. A total of 16 significantly perturbed pathways were identified, of which three pathways were shared by patients with MetS and diabetes identified by analysis of serum samples, including alanine, aspartate and glutamate metabolism, valine, leucine and isoleucine biosynthesis, and glycine, serine and threonine metabolism. Additionally, it was found that 18 differential metabolites were closely related with 36 differential proteins, which were considered as significantly discriminant metabolites and proteins between two groups and were mainly involved in metabolic processes of gamma-aminobutyric acid and acetyl-CoA, biosynthetic processes of cholesterol and amino acids. The results of PPI network analysis and topological parameter calculation of four methods revealed that 16 proteins can serve as hub proteins of MetS. Followed by searching the PubMed database and molecular docking of Cyp7a1 and Got1, we concluded that atorvastatin and resveratrol may be potential drugs for MetS.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Amino Acids / metabolism
  • Animals
  • Metabolic Syndrome*
  • Metabolomics / methods
  • Molecular Docking Simulation
  • Proteomics
  • Rats

Substances

  • Amino Acids

Grants and funding

Chen M. received Fujian Provincial Natural Science fund subject of China (2022J01361, 2019J01347) and Natural Science fund subject of Fujian University of traditional Chinese Medicine (X2021018-emphasis); Li C., Yang Z., Gan H. and Wang Y. received National Natural Science Foundation programs of China (U1705286, 81973751, 81873237 and 82004257), respectively. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.