Frontiers in Neuroscience (Apr 2019)

Metabolomics in the Development and Progression of Dementia: A Systematic Review

  • Yanfeng Jiang,
  • Yanfeng Jiang,
  • Zhen Zhu,
  • Zhen Zhu,
  • Jie Shi,
  • Yanpeng An,
  • Kexun Zhang,
  • Kexun Zhang,
  • Yingzhe Wang,
  • Shuyuan Li,
  • Li Jin,
  • Li Jin,
  • Li Jin,
  • Weimin Ye,
  • Weimin Ye,
  • Mei Cui,
  • Xingdong Chen,
  • Xingdong Chen,
  • Xingdong Chen

DOI
https://doi.org/10.3389/fnins.2019.00343
Journal volume & issue
Vol. 13

Abstract

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Dementia has become a major global public health challenge with a heavy economic burden. It is urgently necessary to understand dementia pathogenesis and to identify biomarkers predicting risk of dementia in the preclinical stage for prevention, monitoring, and treatment. Metabolomics provides a novel approach for the identification of biomarkers of dementia. This systematic review aimed to examine and summarize recent retrospective cohort human studies assessing circulating metabolite markers, detected using high-throughput metabolomics, in the context of disease progression to dementia, including incident mild cognitive impairment, all-cause dementia, and cognitive decline. We systematically searched the PubMed, Embase, and Cochrane databases for retrospective cohort human studies assessing associations between blood (plasma or serum) metabolomics profile and cognitive decline and risk of dementia from inception through October 15, 2018. We identified 16 studies reporting circulating metabolites and risk of dementia, and six regarding cognitive performance change. Concentrations of several blood metabolites, including lipids (higher phosphatidylcholines, sphingomyelins, and lysophophatidylcholine, and lower docosahexaenoic acid and high-density lipoprotein subfractions), amino acids (lower branched-chain amino acids, creatinine, and taurine, and higher glutamate, glutamine, and anthranilic acid), and steroids were associated with cognitive decline and the incidence or progression of dementia. Circulating metabolites appear to be associated with the risk of dementia. Metabolomics could be a promising tool in dementia biomarker discovery. However, standardization and consensus guidelines for study design and analytical techniques require future development.

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