Quantitative proteomic analysis of human serum using tandem mass tags to predict cardiovascular risks in patients with psoriasis

Abstract

Although biomarker candidates associated with psoriasis have been suggested, those for predicting the risk of cardiovascular disease (CVD) early in patients with psoriasis are lacking. We aimed to identify candidate biomarkers that can predict the occurrence of CVD in psoriasis patients. We pursued quantitative proteomic analysis of serum samples composed of three groups: psoriasis patients with and those without CVD risk factors, and healthy controls. Age/Sex-matched serum samples were selected and labeled with 16-plex tandem mass tag (TMT) and analyzed using liquid chromatography-mass spectrometry and subsequent verification with ELISA. Of the 184 proteins that showed statistical significance (P-value < 0.05) among the three groups according to TMT-based quantitative analysis, 98 proteins showed significant differences (> 2.0-fold) between the psoriasis groups with and without CVD risk factors. Verification by ELISA revealed that caldesmon (CALD1), myeloid cell nuclear differentiation antigen (MNDA), and zyxin (ZYX) levels were significantly increased in the psoriasis group with CVD risk factors. Further network analysis identified pathways including integrin signaling, which could be related to platelet aggregation, and actin cytoskeleton signaling. Three novel candidates (MNDA, ZYX, and CALD1) could be potential biomarkers for predicting CVD risks in psoriasis patients. We expect these biomarker candidates can be used to predict CVD risk in psoriasis patients in clinical settings although further studies including large validation are needed.