Autor: |
Kamil Borkowski, Ameer Y. Taha, Theresa L. Pedersen, Philip L. De Jager, David A. Bennett, Matthias Arnold, Rima Kaddurah-Daouk, John W. Newman |
Jazyk: |
angličtina |
Rok vydání: |
2021 |
Předmět: |
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Zdroj: |
Scientific Reports, Vol 11, Iss 1, Pp 1-12 (2021) |
Druh dokumentu: |
article |
ISSN: |
2045-2322 |
DOI: |
10.1038/s41598-021-98640-2 |
Popis: |
Abstract Cognitive decline is associated with both normal aging and early pathologies leading to dementia. Here we used quantitative profiling of metabolites involved in the regulation of inflammation, vascular function, neuronal function and energy metabolism, including oxylipins, endocannabinoids, bile acids, and steroid hormones to identify metabolic biomarkers of mild cognitive impairment (MCI). Serum samples (n = 212) were obtained from subjects with or without MCI opportunistically collected with incomplete fasting state information. To maximize power and stratify the analysis of metabolite associations with MCI by the fasting state, we developed an algorithm to predict subject fasting state when unknown (n = 73). In non-fasted subjects, linoleic acid and palmitoleoyl ethanolamide levels were positively associated with perceptual speed. In fasted subjects, soluble epoxide hydrolase activity and tauro-alpha-muricholic acid levels were negatively associated with perceptual speed. Other cognitive domains showed associations with bile acid metabolism, but only in the non-fasted state. Importantly, this study shows unique associations between serum metabolites and cognitive function in the fasted and non-fasted states and provides a fasting state prediction algorithm based on measurable metabolites. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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