Quantitative detection and metabolic profile analysis of metabolites of tricarboxylic acid cycle and amino acids in psoriasis serum before and after receiving monoclonal antibody treatment by one-pot GC-MS derivatization

Abstract Psoriasis is a common chronic inflammatory skin disease which may exhibit a variety of skin clinical manifestations associated with multiple comorbidities. However, its pathogenesis associated with metabolism has not yet been understood. The metabolites of tricarboxylic acid (TCA) cycle and amino acids are interlinked with each other and involve many physiological processes. This study determined 32 metabolites of TCA cycle and amino acids in psoriasis using an improved GC-MS method. This one-pot derivatization applied silanization and oximation simultaneously for easy, quick and sensitive quantitative detection of 32 metabolites in serum of patients with psoriasis. Through the established GC-MS method, 32 metabolites in serum were detected in a single run. The result of this preliminary study showed that there were significant alterations of the metabolites in tricarboxylic acid (TCA) cycle and amino acids before and after treatment. A shift towards healthy controls of these metabolites after treatment was observed using principal component analysis (PCA) as well. Receiver operating-characteristic curve (ROC) analysis of the analyzed 32 metabolites filtered 5 potential biomarkers of the clinical efficacy of the treatment. This result suggested the importance of these metabolites in the pathogenesis of psoriasis. To our best know, this is the first targeted metabolomics work to study the changes of TCA cycle metabolites and amino acids in the background of treatment of psoriasis.