Metabolomics-based screening of salivary biomarkers for early diagnosis of Alzheimer's disease

Abstract

Early diagnosis of Alzheimer's disease (AD) is an attractive strategy to increase the survival rate of patients. Metabolomics has a great potential for identifying useful biomarkers for early diagnosis, and prognosis. In this work, faster ultra-performance liquid chromatography (FUPLC) mass spectrometry (MS) coupled with multivariate statistical method were employed to find the metabolic changes of the salivary metabolome from AD patients. Saliva samples were obtained from patients with AD (n = 256) and age-matched healthy controls (n = 218). The metabolic differences among AD and control subjects were identified based on principal component analysis (PCA). Sphinganine-1-phosphate, ornithine, phenyllactic acid, inosine, 3-dehydrocarnitine, and hypoxanthine in the AD subjects were significantly different from the control subjects. To demonstrate the utility of salivary biomarkers for the early diagnosis of AD, 3 metabolites (AUC > 0.8) comprising sphinganine-1-phosphate, ornithine, and phenyllactic acid were selected as candidate biomarkers. The major contributor to the predictive model was sphinganine-1-phosphate, which was upregulated in AD, yielded satisfactory accuracy (AUC = 0.998), sensitivity (99.4%) and specificity (98.2%), indicating potential diagnosis in the AD. Our data provided highlights the potential advantages of the application of salivary metabolomics in clinical setting for the diagnosis of AD.