Absolute quantification and characterization of oxylipins in lupus nephritis and systemic lupus erythematosus
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 th...
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Frontiers Media S.A.
2022-10-01
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Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2022.964901/full |
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author | Jingquan He Jingquan He Chiyu Ma Donge Tang Shaoyun Zhong Xiaofang Yuan Fengping Zheng Zhipeng Zeng Yumei Chen Dongzhou Liu Xiaoping Hong Weier Dai Lianghong Yin Yong Dai |
author_facet | Jingquan He Jingquan He Chiyu Ma Donge Tang Shaoyun Zhong Xiaofang Yuan Fengping Zheng Zhipeng Zeng Yumei Chen Dongzhou Liu Xiaoping Hong Weier Dai Lianghong Yin Yong Dai |
author_sort | Jingquan He |
collection | DOAJ |
description | 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-γ-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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spelling | doaj.art-cccb131d14ae4cd988898722e70e1ee92022-12-22T04:29:28ZengFrontiers Media S.A.Frontiers in Immunology1664-32242022-10-011310.3389/fimmu.2022.964901964901Absolute quantification and characterization of oxylipins in lupus nephritis and systemic lupus erythematosusJingquan He0Jingquan He1Chiyu Ma2Donge Tang3Shaoyun Zhong4Xiaofang Yuan5Fengping Zheng6Zhipeng Zeng7Yumei Chen8Dongzhou Liu9Xiaoping Hong10Weier Dai11Lianghong Yin12Yong Dai13Department of Radiotherapy, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical School of Guangzhou University of Chinese Medicine, Shenzhen, ChinaClinical Medical Research Center, Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, Shenzhen Engineering Research Center of Autoimmune Disease, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen People’s Hospital, Shenzhen, ChinaClinical Medical Research Center, Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, Shenzhen Engineering Research Center of Autoimmune Disease, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen People’s Hospital, Shenzhen, ChinaClinical Medical Research Center, Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, Shenzhen Engineering Research Center of Autoimmune Disease, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen People’s Hospital, Shenzhen, ChinaBiotree Metabolomics Research Center, Biotree, Shanghai, ChinaBiotree Metabolomics Research Center, Biotree, Shanghai, ChinaClinical Medical Research Center, Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, Shenzhen Engineering Research Center of Autoimmune Disease, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen People’s Hospital, Shenzhen, ChinaClinical Medical Research Center, Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, Shenzhen Engineering Research Center of Autoimmune Disease, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen People’s Hospital, Shenzhen, ChinaClinical Medical Research Center, Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, Shenzhen Engineering Research Center of Autoimmune Disease, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen People’s Hospital, Shenzhen, ChinaClinical Medical Research Center, Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, Shenzhen Engineering Research Center of Autoimmune Disease, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen People’s Hospital, Shenzhen, ChinaClinical Medical Research Center, Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, Shenzhen Engineering Research Center of Autoimmune Disease, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen People’s Hospital, Shenzhen, ChinaCollege of Natural Science, University of Texas at Austin, Austin, TX, United StatesDepartment of Nephrology, The First Affiliated Hospital of Jinan University, Guangzhou, ChinaClinical Medical Research Center, Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, Shenzhen Engineering Research Center of Autoimmune Disease, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen People’s Hospital, Shenzhen, ChinaSystemic 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-γ-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.https://www.frontiersin.org/articles/10.3389/fimmu.2022.964901/fullsystemic lupus erythematosuslupus nephritispolyunsaturated fatty acidsoxylipinSLEDAI |
spellingShingle | Jingquan He Jingquan He Chiyu Ma Donge Tang Shaoyun Zhong Xiaofang Yuan Fengping Zheng Zhipeng Zeng Yumei Chen Dongzhou Liu Xiaoping Hong Weier Dai Lianghong Yin Yong Dai Absolute quantification and characterization of oxylipins in lupus nephritis and systemic lupus erythematosus Frontiers in Immunology systemic lupus erythematosus lupus nephritis polyunsaturated fatty acids oxylipin SLEDAI |
title | Absolute quantification and characterization of oxylipins in lupus nephritis and systemic lupus erythematosus |
title_full | Absolute quantification and characterization of oxylipins in lupus nephritis and systemic lupus erythematosus |
title_fullStr | Absolute quantification and characterization of oxylipins in lupus nephritis and systemic lupus erythematosus |
title_full_unstemmed | Absolute quantification and characterization of oxylipins in lupus nephritis and systemic lupus erythematosus |
title_short | Absolute quantification and characterization of oxylipins in lupus nephritis and systemic lupus erythematosus |
title_sort | absolute quantification and characterization of oxylipins in lupus nephritis and systemic lupus erythematosus |
topic | systemic lupus erythematosus lupus nephritis polyunsaturated fatty acids oxylipin SLEDAI |
url | https://www.frontiersin.org/articles/10.3389/fimmu.2022.964901/full |
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