Serum proteome and metabolome uncover novel biomarkers for the assessment of disease activity and diagnosing of systemic lupus erythematosus

被引:7
|
作者
He, Jingquan [1 ]
Tang, Donger [2 ]
Liu, Dongzhou [2 ]
Hong, Xiaoping [2 ]
Ma, Chiyu [2 ]
Zheng, Fengping [2 ]
Zeng, Zhipeng [2 ]
Chen, Yumei [2 ]
Du, Jie [4 ]
Kang, Lin [4 ]
Yin, Lianghong [3 ]
Lu, Qianjin [5 ]
Dai, Yong [2 ]
机构
[1] Guangzhou Tradit Chinese Med Univ, Shenzhen Tradit Chinese Med Hosp, Forth Clin Med Coll, Dept Radiotherapy, Shenzhen 518033, Peoples R China
[2] Southern Univ Sci & Technol, Jinan Univ, Shenzhen Peoples Hosp, Affiliated Hosp 1,Clin Med Coll 2,Shenzhen Engn Re, Shenzhen 518020, Guangdong, Peoples R China
[3] First Affiliated Hosp Jinan Univ, Dept Nephrol, Guangzhou 510630, Peoples R China
[4] Biotree, Biotree Metabol Res Ctr, Jiading Dist, Shanghai 201800, Peoples R China
[5] Cent South Univ, Xiangya Hosp 2, Dept Dermatol, Hunan Key Lab Med Epigen, Changsha 410011, Hunan, Peoples R China
关键词
Systemic lupus erythematosus; Proteomics; Metabolomics; SLEDAI; Biomarker; CHRONIC KIDNEY-DISEASE; T-CELLS; CHROMATOGRAPHY; PROLIFERATION; RAPAMYCIN; SLE;
D O I
10.1016/j.clim.2023.109330
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
Systemic lupus erythematosus (SLE) is an autoimmune disease affecting thousands of people. There are still no effective biomarkers for SLE diagnosis and disease activity assessment. We performed proteomics and metabolomics analyses of serum from 121 SLE patients and 106 healthy individuals, and identified 90 proteins and 76 metabolites significantly changed. Several apolipoproteins and the metabolite arachidonic acid were significantly associated with disease activity. Apolipoprotein A-IV (APOA4), LysoPC(16:0), punicic acid and stearidonic acid were correlated with renal function. Random forest model using the significantly changed molecules identified 3 proteins including ATRN, THBS1 and SERPINC1, and 5 metabolites including cholesterol, palmitoleoylethanolamide, octadecanamide, palmitamide and linoleoylethanolamide, as potential biomarkers for SLE diagnosis. Those biomarkers were further validated in an independent cohort with high accuracy (AUC = 0.862 and 0.898 for protein and metabolite biomarkers respectively). This unbiased screening has led to the discovery of novel molecules for SLE disease activity assessment and SLE classification.
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页数:14
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