A blood-based, metabolite and demographiccharacteristic markers panel for thediagnosis of Alzheimer’s disease: supplementary material

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 targetmetabolites 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.