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Alteration of metabolic profile and potential biomarkers in the plasma of Alzheimer's disease
Author(s) -
Le Weidong
Publication year - 2020
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1002/alz.042799
Subject(s) - metabolite , disease , cohort , medicine , chenodeoxycholic acid , cholic acid , metabolomics , polyunsaturated fatty acid , biomarker , physiology , bile acid , bioinformatics , gastroenterology , endocrinology , chemistry , biochemistry , fatty acid , biology
Background The expending of elderly population worldwide leads to a dramatical rising in the incidence of chronic diseases including Alzheimer’s Disease (AD) in the elderly. The inadequate understanding of the mechanisms underlying AD is deemed the greatest stumbling block against progress in definitive diagnosis and curative intervention of this disease. Efforts have been made towards the discovery of reliable AD biomarkers, but they are either invasive based on neuropathological markers in cerebrospinal fluid (CSF) or expensive using emission tomography scanning or magnetic resonance imaging techniques. With the emergence of high‐throughput technology that could detect and catalogue larger numbers of small metabolites, metabolomics offers hope for a better understanding of AD and subsequent identification of biomarkers. Method Herein, using untargeted ultra‐performance liquid chromatography‐mass spectrometry we firstly measured concentrations of plasma metabolites in a cohort of AD subjects (n=44) and cognitively normal controls (Ctrl, n=94). Result We found remarkable reductions of polyunsaturated fatty acids (PUFAs), acyl‐carnitines, tryptophan degradation related metabolites and elevated levels of bile acids in AD compared to Ctrl. Followed by repeated validation in an independent cohort including AD (n=30), mild cognitive impairment (MCI, n=13), Ctrl (n=43) and non‐AD neurological disease controls (NDC, n=31), we further identified a metabolite panel consisting of five metabolites including cholic acid, chenodeoxycholic acid, allocholic acid, indolelactic acid and tryptophan that can distinguish AD from both Ctrl and NDC with satisfactory sensitivity and specificity. Conclusion Notably, the concentrations of these metabolites are significantly correlated with disease severity. Our results also suggested the altered bile acid profiles in AD and MCI might provide clues for early risk of AD. Following further validation in larger cohorts, these findings are expected to provide new approaches for diagnosis of AD and offer novel insights into AD pathogenesis.