Qiong Zhang1,2, Xin Li1, Xiaofeng Yin1, Haifang Wang1, Chen Fu1, Hongxia Wang1, Kaifei Li1, Yao Li3, Xiaohe Zhang1, Huijun Liang1, Kui Li4, Haixia Li1, Yurong Qiu1,4. 1. Laboratory Medicine Center, Nanfang Hospital, Southern Medical University, Guangdong, Guangdong, P.R. China. 2. Clinic Laboratory, Zhuzhou Central Hospital, Hunan, China. 3. Clinic Laboratory, Foshan Traditional Chinese Medicine Hospital, Guangdong, P.R. China. 4. Huayin Medical Laboratory Center Co., Ltd, Guangdong, P.R. China.
Abstract
OBJECTIVE: The spectrum of clinical manifestations and serological phenomena of SLE is heterogeneous among patients and even changes over time unpredictably in individual patients. For this reason, clinical diagnosis especially in complicated or atypical cases is often difficult or delayed leading to poor prognosis. Despite the medical progress nowadays in the understanding of SLE pathogenesis, disease-specific biomarkers for SLE remain an outstanding challenge. Therefore, we undertook this study to investigate potential biomarkers for SLE diagnosis. METHODS: Serum samples from 32 patients with SLE and 25 gender-matched healthy controls (HCs) were analysed by metabolic profiling based on liquid chromatography-tandem mass spectrometry metabolomics platform. The further validation for the potential biomarker was performed in an independent set consisting of 36 SLE patients and 30 HCs. RESULTS: The metabolite profiles of serum samples allowed differentiation of SLE patients from HCs. The levels of arachidonic acid, sphingomyelin (SM) 24:1, monoacylglycerol (MG) 17:0, lysophosphatidyl ethanolamine (lysoPE) 18:0, lysoPE 16:0, lysophosphatidyl choline (lysoPC) 20:0, lysoPC 18:0 and adenosine were significantly decreased in SLE patients, and the MG 20:2 and L-pyroglutamic acid were significantly increased in SLE group. In addition, L-pyroglutamic acid achieved an area under the receiver-operating characteristic curve of 0.955 with high sensitivity (97.22%) and specificity (83.33%) at the cut-off of 61.54 μM in the further targeted metabolism, indicating diagnostic potential. CONCLUSION: Serum metabolic profiling is differential between SLE patients and HCs and depicts increased L-pyroglutamic acid as a promising bitformatomarker for SLE.
OBJECTIVE: The spectrum of clinical manifestations and serological phenomena of SLE is heterogeneous among patients and even changes over time unpredictably in individual patients. For this reason, clinical diagnosis especially in complicated or atypical cases is often difficult or delayed leading to poor prognosis. Despite the medical progress nowadays in the understanding of SLE pathogenesis, disease-specific biomarkers for SLE remain an outstanding challenge. Therefore, we undertook this study to investigate potential biomarkers for SLE diagnosis. METHODS: Serum samples from 32 patients with SLE and 25 gender-matched healthy controls (HCs) were analysed by metabolic profiling based on liquid chromatography-tandem mass spectrometry metabolomics platform. The further validation for the potential biomarker was performed in an independent set consisting of 36 SLEpatients and 30 HCs. RESULTS: The metabolite profiles of serum samples allowed differentiation of SLEpatients from HCs. The levels of arachidonic acid, sphingomyelin (SM) 24:1, monoacylglycerol (MG) 17:0, lysophosphatidyl ethanolamine (lysoPE) 18:0, lysoPE 16:0, lysophosphatidyl choline (lysoPC) 20:0, lysoPC 18:0 and adenosine were significantly decreased in SLEpatients, and the MG 20:2 and L-pyroglutamic acid were significantly increased in SLE group. In addition, L-pyroglutamic acid achieved an area under the receiver-operating characteristic curve of 0.955 with high sensitivity (97.22%) and specificity (83.33%) at the cut-off of 61.54 μM in the further targeted metabolism, indicating diagnostic potential. CONCLUSION: Serum metabolic profiling is differential between SLEpatients and HCs and depicts increased L-pyroglutamic acid as a promising bitformatomarker for SLE.