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Review
. 2023 Sep;13(9):968-983.
doi: 10.1016/j.jpha.2023.05.015. Epub 2023 Jun 3.

Metabolomics: A useful tool for ischemic stroke research

Affiliations
Review

Metabolomics: A useful tool for ischemic stroke research

Wentao Li et al. J Pharm Anal. 2023 Sep.

Abstract

Ischemic stroke (IS) is a multifactorial and heterogeneous disease. Despite years of studies, effective strategies for the diagnosis, management and treatment of stroke are still lacking in clinical practice. Metabolomics is a growing field in systems biology. It is starting to show promise in the identification of biomarkers and in the use of pharmacometabolomics to help patients with certain disorders choose their course of treatment. The development of metabolomics has enabled further and more biological applications. Particularly, metabolomics is increasingly being used to diagnose diseases, discover new drug targets, elucidate mechanisms, and monitor therapeutic outcomes and its potential effect on precision medicine. In this review, we reviewed some recent advances in the study of metabolomics as well as how metabolomics might be used to identify novel biomarkers and understand the mechanisms of IS. Then, the use of metabolomics approaches to investigate the molecular processes and active ingredients of Chinese herbal formulations with anti-IS capabilities is summarized. We finally summarized recent developments in single cell metabolomics for exploring the metabolic profiles of single cells. Although the field is relatively young, the development of single cell metabolomics promises to provide a powerful tool for unraveling the pathogenesis of IS.

Keywords: Biomarker; Ischemic stroke; Metabolomics; Precision medicine; Single cell metabolomics.

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Conflict of interest statement

The authors declare that there are no conflicts of interest.

Figures

Image 1
Graphical abstract
Fig. 1
Fig. 1
A systems biology approach with a focus on metabolomics.
Fig. 2
Fig. 2
The role of lncRNAs in the pathophysiology of ischemic stroke (IS). MALAT1: metastasis-associated lung adenocarcinoma tran 1; SNHG12: small nucleolar RNA host gene 12; ANRIL: antisense non-coding RNA in the INK4 locus; MEG3: maternally expressed gene 3; TUG1: taurine upregulated 1; KCNQ10T1: potassium voltage-gated channel subfamily Q member 1 opposite strand 1.
Fig. 3
Fig. 3
Examples of single cell metabolomics techniques. (A) matrix-assisted laser desorption-ionization mass spectrometry (MALDI MS), (B) secondary ionization mass spectrometry (SIMS), and (C) single probe mass spectrometry.

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