Recent advances and perspectives of metabolomics-based investigations in Parkinson's disease

Yaping Shao, Weidong Le

Research output: Contribution to journalArticlepeer-review

159 Scopus citations

Abstract

Parkinson's disease (PD) is the second most prevalent neurodegenerative disease of the central nervous system (CNS), which affects mostly older adults. In recent years, the incidence of PD has been dramatically increasing with the aging population expanding. Due to the lack of effective biomarkers, the accurate diagnosis and precise treatment of PD are currently compromised. Notably, metabolites have been considered as the most direct reflection of the physiological and pathological conditions in individuals and represent attractive candidates to provide deep insights into disease phenotypes. By profiling the metabolites in biofluids (cerebrospinal fluid, blood, urine), feces and brain tissues, metabolomics has become a powerful and promising tool to identify novel biomarkers and provide valuable insights into the etiopathogenesis of neurological diseases. In this review, we will summarize the recent advancements of major analytical platforms implemented in metabolomics studies, dedicated to the improvement and extension of metabolome coverage for in-depth biological research. Based on the current metabolomics studies in both clinical populations and experimental PD models, this review will present new findings in metabolomics biomarkers research and abnormal metabolic pathways in PD, and will discuss the correlation between metabolomic changes and clinical conditions of PD. A better understanding of the biological underpinning of PD pathogenesis might offer novel diagnostic, prognostic, and therapeutic approaches to this devastating disease.

Original languageEnglish (US)
Article number3
JournalMolecular Neurodegeneration
Volume14
Issue number1
DOIs
StatePublished - Jan 11 2019

Keywords

  • Biomarker
  • Metabolic pathway
  • Metabolomics
  • Parkinson's disease

ASJC Scopus subject areas

  • Molecular Biology
  • Clinical Neurology
  • Cellular and Molecular Neuroscience

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