Identification of novel biomarkers for frailty diagnosis via serum amino acids metabolomic analysis using UPLC-MS/MS

Purpose: This study was aimed to analyze serum amino acid metabolite profiles in frailty patients, gain a better understanding of the metabolic mechanisms in frailty, and assess the diagnostic value of metabolomics-based biomarkers of frailty.Experimental DesignThis study utilized the ultra-performance liquid chromatography tandem mass spectrometry to examine amino acids associated with frailty. Additionally, we employed multivariate statistical methods, metabolomic data analysis, receiver operating characteristic (ROC) curve analysis, and pathway enrichment analysis. Results: Among the assayed amino acid metabolites, we identified biomarkers for frailty. ROC curve analysis for frailty diagnosis based on the modified Fried's frailty index showed that the areas under ROC curve of tryptophan, phenylalanine, aspartic acid, and combination were 0.775, 0.679, 0.667, and 0.807, respectively. ROC curve analysis for frailty diagnosis based on Frail Scale showed that the areas under ROC curve of cystine, phenylalanine, and combination of amino acids (cystine, L-Glutamine, citrulline, tyrosine, kynurenine, phenylalanine, glutamin acid) were 0.834, 0.708, and 0.854 respectively. Conclusion and Clinical Relevance: In this study, we explored the serum amino acid metabolite profiles in frailty patients. These present metabolic analyses may provide valuable information on the potential biomarkers and the possible pathogenic mechanisms of frailty. Clinical Significance: Frailty is a clinical syndrome, as a consequence it is challenging to identify at early course of the disease, even based on the existing frailty scales. Early diagnosis and appropriate patient management are the key to improve the survival and limit disabilities in frailty patients. Proven by the extensive laboratory and clinical studies on frailty, comprehensive analysis of metabolic levels in frail patients, identification of biomarkers and study of pathogenic pathways of metabolites contribute to the prediction and early diagnosis of frailty. In this study, we explored the serum amino acid metabolite profiles in frailty patients. These present metabolic analyses may provide valuable information on the potential biomarkers and the possible pathogenic mechanisms of frailty.