Aims: This work was designed to provide early diagnosis strategies for Alzheimer's disease (AD) based on the identification of blood metabolic biomarkers. Patients & methods: A total of 90 subjects aged 60 years or older were included in this study; 45 patients were assigned to the case group and control group, respectively. A total of 31 target metabolites were quantitatively analyzed by parallel reaction monitoring between the two groups. Results & conclusion: Three metabolites were screened out, including cystine, serine and alanine/sarcosine. Logistic regression and random forest analysis were used to establish AD diagnosis models, and the model combining metabolic biomarkers and demographic variables had higher detection efficiency (area under the curve = 0.869). A combination diagnostic model to provide a scientific reference for early screening and diagnosis of AD was constructed.
CITATION STYLE
Yang, L., Tan, Q., Wan, W., Bu, Z., Xuan, C., Yu, C., … Yan, J. (2023). A blood-based, metabolite and demographic characteristic markers panel for the diagnosis of Alzheimer’s disease. Bioanalysis, 15(20), 1247–1258. https://doi.org/10.4155/bio-2023-0043
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