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Li Y, Ma C, Liao S, Qi S, Meng S, Cai W, Dai W, Cao R, Dong X, Krämer BK, Yun C, Hocher B, Hong X, Liu D, Tang D, He J, Yin L, Dai Y. Combined proteomics and single cell RNA-sequencing analysis to identify biomarkers of disease diagnosis and disease exacerbation for systemic lupus erythematosus. Front Immunol 2022; 13:969509. [PMID: 36524113 PMCID: PMC9746895 DOI: 10.3389/fimmu.2022.969509] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 11/15/2022] [Indexed: 12/02/2022] Open
Abstract
Introduction Systemic lupus erythematosus (SLE) is a chronic autoimmune disease for which there is no cure. Effective diagnosis and precise assessment of disease exacerbation remains a major challenge. Methods We performed peripheral blood mononuclear cell (PBMC) proteomics of a discovery cohort, including patients with active SLE and inactive SLE, patients with rheumatoid arthritis (RA), and healthy controls (HC). Then, we performed a machine learning pipeline to identify biomarker combinations. The biomarker combinations were further validated using enzyme-linked immunosorbent assays (ELISAs) in another cohort. Single-cell RNA sequencing (scRNA-seq) data from active SLE, inactive SLE, and HC PBMC samples further elucidated the potential immune cellular sources of each of these PBMC biomarkers. Results Screening of the PBMC proteome identified 1023, 168, and 124 proteins that were significantly different between SLE vs. HC, SLE vs. RA, and active SLE vs. inactive SLE, respectively. The machine learning pipeline identified two biomarker combinations that accurately distinguished patients with SLE from controls and discriminated between active and inactive SLE. The validated results of ELISAs for two biomarker combinations were in line with the discovery cohort results. Among them, the six-protein combination (IFIT3, MX1, TOMM40, STAT1, STAT2, and OAS3) exhibited good performance for SLE disease diagnosis, with AUC of 0.723 and 0.815 for distinguishing SLE from HC and RA, respectively. Nine-protein combination (PHACTR2, GOT2, L-selectin, CMC4, MAP2K1, CMPK2, ECPAS, SRA1, and STAT2) showed a robust performance in assessing disease exacerbation (AUC=0.990). Further, the potential immune cellular sources of nine PBMC biomarkers, which had the consistent changes with the proteomics data, were elucidated by PBMC scRNAseq. Discussion Unbiased proteomic quantification and experimental validation of PBMC samples from two cohorts of patients with SLE were identified as biomarker combinations for diagnosis and activity monitoring. Furthermore, the immune cell subtype origin of the biomarkers in the transcript expression level was determined using PBMC scRNAseq. These findings present valuable PBMC biomarkers associated with SLE and may reveal potential therapeutic targets.
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Affiliation(s)
- Yixi Li
- Institute of Nephrology and Blood Purification, the First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, China,Clinical Medical Research Center, The Second Clinical Medical College of Jinan University, Shenzhen People’s Hospital, Jinan University, Shenzhen, China
| | - Chiyu Ma
- Clinical Medical Research Center, The Second Clinical Medical College of Jinan University, Shenzhen People’s Hospital, Jinan University, Shenzhen, China
| | - Shengyou Liao
- Clinical Medical Research Center, The Second Clinical Medical College of Jinan University, Shenzhen People’s Hospital, Jinan University, Shenzhen, China
| | - Suwen Qi
- Clinical Medical Research Center, The Second Clinical Medical College of Jinan University, Shenzhen People’s Hospital, Jinan University, Shenzhen, China
| | - Shuhui Meng
- Clinical Medical Research Center, The Second Clinical Medical College of Jinan University, Shenzhen People’s Hospital, Jinan University, Shenzhen, China
| | - Wanxia Cai
- Clinical Medical Research Center, The Second Clinical Medical College of Jinan University, Shenzhen People’s Hospital, Jinan University, Shenzhen, China
| | - Weier Dai
- College of Natural Science, University of Texas at Austin, Austin, TX, United States
| | - Rui Cao
- Institute of Nephrology and Blood Purification, the First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, China
| | - Xiangnan Dong
- Institute of Nephrology and Blood Purification, the First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, China
| | - Bernhard K. Krämer
- Fifth Department of Medicine, University Medical Centre Mannheim, University of Heidelberg, Heidelberg, Germany
| | - Chen Yun
- Department of Nephrology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Berthold Hocher
- Fifth Department of Medicine, University Medical Centre Mannheim, University of Heidelberg, Heidelberg, Germany,Key Laboratory of Study and Discovery of Small Targeted Molecules of Hunan Province, School of Medicine, Hunan Normal University, Changsha, China,Reproductive and Genetic Hospital of China International Trust and Investment Corporation (CITIC)-Xiangya, Changsha, China,Institute of Medical Diagnostics (IMD), Berlin, Germany
| | - Xiaoping Hong
- Department of Rheumatology and Immunology, The Second Clinical Medical College of Jinan University, Shenzhen People’s Hospital, Jinan University, Shenzhen, China
| | - Dongzhou Liu
- Department of Rheumatology and Immunology, The Second Clinical Medical College of Jinan University, Shenzhen People’s Hospital, Jinan University, Shenzhen, China
| | - Donge Tang
- Clinical Medical Research Center, The Second Clinical Medical College of Jinan University, Shenzhen People’s Hospital, Jinan University, Shenzhen, China,*Correspondence: Yong Dai, ; Lianghong Yin, ; Jingquan He, ; Donge Tang,
| | - Jingquan He
- Clinical Medical Research Center, The Second Clinical Medical College of Jinan University, Shenzhen People’s Hospital, Jinan University, Shenzhen, China,*Correspondence: Yong Dai, ; Lianghong Yin, ; Jingquan He, ; Donge Tang,
| | - Lianghong Yin
- Institute of Nephrology and Blood Purification, the First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, China,Guangzhou Enttxs Medical Products Co., Ltd, Guangzhou, Guangzhou, China,*Correspondence: Yong Dai, ; Lianghong Yin, ; Jingquan He, ; Donge Tang,
| | - Yong Dai
- Clinical Medical Research Center, The Second Clinical Medical College of Jinan University, Shenzhen People’s Hospital, Jinan University, Shenzhen, China,*Correspondence: Yong Dai, ; Lianghong Yin, ; Jingquan He, ; Donge Tang,
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Zeng Z, Wang Y, Xiao Y, Zheng J, Liu R, He X, Yu J, Tang B, Qiu X, Tang R, Shi Y, Xiao R. Overexpression of OASL upregulates TET1 to induce aberrant activation of CD4+ T cells in systemic sclerosis via IRF1 signaling. Arthritis Res Ther 2022; 24:50. [PMID: 35183246 PMCID: PMC8857842 DOI: 10.1186/s13075-022-02741-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 02/08/2022] [Indexed: 12/31/2022] Open
Abstract
Background Systemic sclerosis (SSc), an autoimmune disease with unknown etiology and pathogenesis, is characterized by abnormal autoimmunity, vascular dysfunction, and progressive fibrosis of skin and organs. Studies have shown that a key factor in the pathogenesis of SSc is aberrant activation of CD4+ T cells. Our previous studies have shown that a global hypomethylation state of CD4+ T cells is closely related to aberrant activation. However, the exact mechanism of hypomethylation in CD4+T cells is not yet clear. Methods Illumina HiSeq 2500 Platform was used to screen differentially expressed genes and explore the role of OASL, TET1, and IRF1 in the abnormal activation of CD4+T cells in SSc. Finally, double luciferase reporter gene experiments were used to analyze the interaction between IRF1 and TET1. Results OASL overexpression could upregulate TET1 to increase the hydroxymethylation levels of CD4+ T cells and induce high expression of functional proteins (CD40L and CD70), thus promoting CD4+T cell aberrant activation. Moreover, OASL upregulated TET1 via IRF1 signaling activation, and a double luciferase reporter gene experiment revealed that IRF1 can bind to the TET1 promoter region to regulate its expression. Conclusions OASL participates in the regulation of abnormal hypomethylation of CD4+ T cells in SSc, which implies a pivotal role for IFN signaling in the pathogenesis of SSc. Regulating DNA methylation and IFN signaling may serve as therapeutic treatments in SSc. Supplementary Information The online version contains supplementary material available at 10.1186/s13075-022-02741-w.
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