Metabolomics and incident dementia in older Chinese adults: The Shanghai Aging Study. Issue 5 (8th April 2020)

• Record Type: Journal Article
• Authors: Cui, Mei; Jiang, Yanfeng; Zhao, Qianhua; Zhu, Zhen; Liang, Xiaoniu; Zhang, Kexun; Wu, Wanqing; Dong, Qiang; An, Yanpeng; Tang, Huiru; Ding, Ding; Chen, Xingdong
• Is Part Of: Alzheimer's & dementia. Volume 16:Issue 5(2020)
• Page Start: 779
• Page End: 788
• Publication Date: 2020-04-08
• Subjects: Alzheimer's disease -- dementia -- metabolomics -- metabolites -- nuclear magnetic resonance; Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.12074
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Introduction: Metabolomics provide a promising tool to understand the pathogenesis and to identify novel biomarkers of dementia. This study aimed to determine circulating metabolites associated with incident dementia in a Chinese cohort, and whether a selected metabolite panel could predict dementia. Methods: Thirty‐eight metabolites in baseline serum were profiled by nuclear magnetic resonance in 1440 dementia‐free participants followed 5 years in the Shanghai Aging Study. Results: Higher serum levels of glutamine and O ‐acetyl‐glycoproteins were associated with increased risk of dementia, whereas glutamate, tyrosine, acetate, glycine, and phenylalanine were negatively related to incident dementia. A panel of five metabolites selected by least absolute shrinkage and selection operator within cross‐validation regression analysis could predict incident dementia with an area under the receiver‐operating characteristic curve of 0.72. Discussion: We identified seven candidate serum metabolic biomarkers for dementia. These findings and the underlying biological mechanisms need to be further replicated and elucidated in future studies.