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Metabolomics facilitates the discovery of metabolic biomarkers and pathways for ischemic stroke: a systematic review

期刊

METABOLOMICS
卷 15, 期 12, 页码 -

出版社

SPRINGER
DOI: 10.1007/s11306-019-1615-1

关键词

Ischemic stroke; Metabolomics; Biomarker; Metabolic pathway; Pathogenesis

资金

  1. National Natural Science Foundation of China [81703316]
  2. Natural Science Foundation of Jiangsu Province [BK20170350]
  3. China Postdoctoral Science Foundation [2017M610353]

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Introduction Ischemic stroke (IS) is a major contributor to the global disease burden, and effective biomarkers for IS management in clinical practice are urgently needed. Metabolomics can detect metabolites that are small enough to cross the blood-brain barrier in a high-throughput manner, and thus represents a powerful tool for discovering biomarkers of IS. Objectives In this study, we conducted a systematic review to identify potential metabolic biomarkers and pathways that might facilitate risk predictions, clinical diagnoses, the recognition of complications, predictions of recurrence and an understanding of the pathogenesis of IS. Methods The PubMed and Web of Science databases were searched for relevant studies published between January 2000 and July 2019. The study objectives, study designs and reported metabolic biomarkers were systematically examined and compared. Pathway analysis was performed using the MetaboAnalyst online software. Results Twenty-eight studies were included in this systematic review. Many consistent metabolites, including isoleucine, leucine, valine, glycine, lysine, glutamate, LysoPC(16:0), LysoPC(18:2), serine, uric acid, citrate and palmitic acid, possess potential as biomarkers of IS. Metabolic pathways and dysregulations that are implicated in excitotoxicity, inflammation, apoptosis, oxidative stress, neuroprotection, energy failure, and elevation of intracellular Ca2+ levels, were indicated as playing important roles in the development and progression of IS. Conclusions This systematic review summarizes potential metabolic biomarkers and pathways related to IS, which may provide opportunities for the construction of diagnostic or predictive models for IS and the discovery of novel therapeutic targets.

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