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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Main Authors: 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
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-10-01
Series:Frontiers in Immunology
Subjects:
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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