Identification of Key Biomarkers in Systemic Lupus Erythematosus by a Multi-Cohort Analysis
Systemic lupus erythematosus (SLE) is an autoimmune disease that affects multiple body systems with heterogeneous clinical manifestations. Since gene expression analyses have been accomplished on diverse types of samples to specify SLE-related genes, single-cohort transcriptomics have not produced r...
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| Published in | Frontiers in immunology Vol. 13; p. 928623 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
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04.07.2022
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| Abstract | Systemic lupus erythematosus (SLE) is an autoimmune disease that affects multiple body systems with heterogeneous clinical manifestations. Since gene expression analyses have been accomplished on diverse types of samples to specify SLE-related genes, single-cohort transcriptomics have not produced reliable results. Using an integrated multi-cohort analysis framework, we analyzed whole blood cells from SLE patients from three transcriptomics cohorts (n=1222) and identified a five-gene signature that distinguished SLE patients from controls. We validated the diagnostic performance of this five-gene signature in six independent validation cohorts (n= 469), with an area under the receiver operating characteristic curve of 0.88 [95% CI 0.7 − 0.96]. This five-gene signature may be associated with the proportion of SLE immune cells, and generalizable across ages and sample types with real diagnostic value for clinical application. |
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| AbstractList | Systemic lupus erythematosus (SLE) is an autoimmune disease that affects multiple body systems with heterogeneous clinical manifestations. Since gene expression analyses have been accomplished on diverse types of samples to specify SLE-related genes, single-cohort transcriptomics have not produced reliable results. Using an integrated multi-cohort analysis framework, we analyzed whole blood cells from SLE patients from three transcriptomics cohorts (n=1222) and identified a five-gene signature that distinguished SLE patients from controls. We validated the diagnostic performance of this five-gene signature in six independent validation cohorts (n= 469), with an area under the receiver operating characteristic curve of 0.88 [95% CI 0.7 − 0.96]. This five-gene signature may be associated with the proportion of SLE immune cells, and generalizable across ages and sample types with real diagnostic value for clinical application. Systemic lupus erythematosus (SLE) is an autoimmune disease that affects multiple body systems with heterogeneous clinical manifestations. Since gene expression analyses have been accomplished on diverse types of samples to specify SLE-related genes, single-cohort transcriptomics have not produced reliable results. Using an integrated multi-cohort analysis framework, we analyzed whole blood cells from SLE patients from three transcriptomics cohorts (n=1222) and identified a five-gene signature that distinguished SLE patients from controls. We validated the diagnostic performance of this five-gene signature in six independent validation cohorts (n= 469), with an area under the receiver operating characteristic curve of 0.88 [95% CI 0.7 - 0.96]. This five-gene signature may be associated with the proportion of SLE immune cells, and generalizable across ages and sample types with real diagnostic value for clinical application.Systemic lupus erythematosus (SLE) is an autoimmune disease that affects multiple body systems with heterogeneous clinical manifestations. Since gene expression analyses have been accomplished on diverse types of samples to specify SLE-related genes, single-cohort transcriptomics have not produced reliable results. Using an integrated multi-cohort analysis framework, we analyzed whole blood cells from SLE patients from three transcriptomics cohorts (n=1222) and identified a five-gene signature that distinguished SLE patients from controls. We validated the diagnostic performance of this five-gene signature in six independent validation cohorts (n= 469), with an area under the receiver operating characteristic curve of 0.88 [95% CI 0.7 - 0.96]. This five-gene signature may be associated with the proportion of SLE immune cells, and generalizable across ages and sample types with real diagnostic value for clinical application. |
| Author | Wei, Meilin Xiong, Qin Wang, Junlong Dong, Qiguan Chen, Shaoqiu Yang, Hua |
| AuthorAffiliation | 2 Department of Oncology, General Hospital of Fushun Mining Bureau of Liaoning Health Industry Group , Fushun , China 4 Chaminade University of Honolulu , Honolulu, HI , United States 5 Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanchang University , Jiangxi , China 3 Molecular Biosciences and Bioengineering Program, College of Tropical Agriculture and Human Resources, University of Hawaii at Manoa , Honolulu, HI , United States 1 Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Nanchang University , Jiangxi , China |
| AuthorAffiliation_xml | – name: 3 Molecular Biosciences and Bioengineering Program, College of Tropical Agriculture and Human Resources, University of Hawaii at Manoa , Honolulu, HI , United States – name: 5 Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanchang University , Jiangxi , China – name: 1 Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Nanchang University , Jiangxi , China – name: 4 Chaminade University of Honolulu , Honolulu, HI , United States – name: 2 Department of Oncology, General Hospital of Fushun Mining Bureau of Liaoning Health Industry Group , Fushun , China |
| Author_xml | – sequence: 1 givenname: Meilin surname: Wei fullname: Wei, Meilin – sequence: 2 givenname: Qiguan surname: Dong fullname: Dong, Qiguan – sequence: 3 givenname: Shaoqiu surname: Chen fullname: Chen, Shaoqiu – sequence: 4 givenname: Junlong surname: Wang fullname: Wang, Junlong – sequence: 5 givenname: Hua surname: Yang fullname: Yang, Hua – sequence: 6 givenname: Qin surname: Xiong fullname: Xiong, Qin |
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| Cites_doi | 10.1002/art.22578 10.1038/ng.2231 10.14670/HH-22.465 10.1371/journal.pone.0227069 10.7759/cureus.23621 10.1093/nar/gkw797 10.1371/journal.pone.0137522 10.1093/rheumatology/kex260 10.1371/journal.pone.0156234 10.1371/journal.pone.0153252 10.1590/S0100-879X2008000900005 10.1142/9789813207813_0015 10.1136/annrheumdis-2015-208410 10.1080/07853890.2021.1995624 10.1007/s12038-013-9377-9 10.1002/acr.23292 10.3390/cells8101180 10.1016/j.jaut.2018.11.001 10.1093/bioinformatics/btz363 10.6061/clinics/2020/e1528 10.1016/j.autrev.2014.10.003 10.1016/S0140-6736(19)30237-5 |
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| Copyright | Copyright © 2022 Wei, Dong, Chen, Wang, Yang and Xiong. Copyright © 2022 Wei, Dong, Chen, Wang, Yang and Xiong 2022 Wei, Dong, Chen, Wang, Yang and Xiong |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Edited by: Xiaoyan Wang, Shanghai Jiao Tong University, China Reviewed by: Jian Yin Zou, Shanghai Jiao Tong University, China; Kaifeng Guo, Fudan University, China These authors have contributed equally to this work This article was submitted to Autoimmune and Autoinflammatory Disorders, a section of the journal Frontiers in Immunology |
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| References | Liang (B4) 2022; 14 Sturm (B12) 2019; 35 Haynes (B11) 2017 Rees (B2) 2017; 56 Yaniv (B5) 2015; 14 Okada (B14) 2012; 44 Li (B8) 2020; 75 Leuchten (B6) 2018; 70 Nagasawa (B16) 2016; 11 Toukap (B20) 2007; 56 Kwon (B9) 2019; 8 Tsujimura (B18) 2007; 22 Dou (B21) 2013; 38 Durcan (B1) 2019; 393 Huang (B17) 2022; 54 Matsuoka (B7) 2020; 15 Zhao (B15) 2016; 75 Wang (B22) 2015; 10 Sweeney (B10) 2017; 45 Bing (B13) 2016; 11 Fava (B3) 2019; 96 Gonzalez (B19) 2008; 41 |
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| Title | Identification of Key Biomarkers in Systemic Lupus Erythematosus by a Multi-Cohort Analysis |
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