Absolute quantification and characterization of oxylipins in lupus nephritis and systemic lupus erythematosus

被引:9
作者
He, Jingquan [1 ,2 ]
Ma, Chiyu [2 ]
Tang, Donge [2 ]
Zhong, Shaoyun [3 ]
Yuan, Xiaofang [3 ]
Zheng, Fengping [2 ]
Zeng, Zhipeng [2 ]
Chen, Yumei [2 ]
Liu, Dongzhou [2 ]
Hong, Xiaoping [2 ]
Dai, Weier [4 ]
Yin, Lianghong [5 ]
Dai, Yong [2 ]
机构
[1] Guangzhou Univ Chinese Med, Shenzhen Tradit Chinese Med Hosp, Dept Radiotherapy, Clin Med Sch 4, Shenzhen, Peoples R China
[2] Jinan Univ, Affiliated Hosp 1, Shenzhen Peoples Hosp, Clin Med Res Ctr,Clin Med Coll 2,Southern Univ Sci, Shenzhen, Peoples R China
[3] Biotree, Biotree Metabol Res Ctr, Shanghai, Peoples R China
[4] Univ Texas Austin, Coll Nat Sci, Austin, TX USA
[5] Jinan Univ, Dept Nephrol, Affiliated Hosp 1, Guangzhou, Peoples R China
来源
FRONTIERS IN IMMUNOLOGY | 2022年 / 13卷
关键词
systemic lupus erythematosus; lupus nephritis; polyunsaturated fatty acids; oxylipin; SLEDAI; DISEASE-ACTIVITY; LINOLENIC ACID; STRESS; CELLS;
D O I
10.3389/fimmu.2022.964901
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 a chronic autoimmune disease with multi-organ inflammation and defect, which is linked to many molecule mediators. Oxylipins as a class of lipid mediator have not been broadly investigated in SLE. Here, we applied targeted mass spectrometry analysis to screen the alteration of oxylipins in serum of 98 SLE patients and 106 healthy controls. The correlation of oxylipins to lupus nephritis (LN) and SLE disease activity, and the biomarkers for SLE classification, were analyzed. Among 128 oxylipins analyzed, 92 were absolutely quantified and 26 were significantly changed. They were mainly generated from the metabolism of several polyunsaturated fatty acids, including arachidonic acid (AA), linoleic acid (LA), docosahexanoic acid (DHA), eicosapentanoic acid (EPA) and dihomo-gamma-linolenic acid (DGLA). Several oxylipins, especially those produced from AA, showed different abundance between patients with and without lupus nephritis (LN). The DGLA metabolic activity and DGLA generated PGE1, were significantly associated with SLE disease activity. Random forest-based machine learning identified a 5-oxylipin combination as potential biomarker for SLE classification with high accuracy. Seven individual oxylipin biomarkers were also identified with good performance in distinguishing SLE patients from healthy controls (individual AUC > 0.7). Interestingly, the biomarkers for differentiating SLE patients from healthy controls are distinct from the oxylipins differentially expressed in LN patients vs. non-LN patients. This study provides possibilities for the understanding of SLE characteristics and the development of new tools for SLE classification.
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页数:12
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