Hua-Zhi Ling1,2,3, Shu-Zhen Xu1,3, Rui-Xue Leng1,3, Jun Wu1, Hai-Feng Pan1,3, Yin-Guang Fan1, Bin Wang1, Yuan-Rui Xia1, Qian Huang3, Zong-Wen Shuai4, Dong-Qing Ye1,3. 1. Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical UniversityHefei, Anhui, China. 2. Department of Clinical Laboratory, the First Affiliated Hospital of Anhui Medical UniversityHefei, Anhui, China. 3. Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, China. 4. Department of Rheumatology and Immunology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Abstract
OBJECTIVE: Clinical diagnosis of SLE is currently challenging due to its heterogeneity. Many autoantibodies are associated with SLE and are considered potential diagnostic markers, but systematic screening and validation of such autoantibodies is lacking. This study aimed to systematically discover new autoantibodies that may be good biomarkers for use in SLE diagnosis. METHODS: Sera from 15 SLE patients and 5 healthy volunteers were analysed using human proteome microarrays to identify candidate SLE-related autoantibodies. The results were validated by screening of sera from 107 SLE patients, 94 healthy volunteers and 60 disease controls using focussed arrays comprised of autoantigens corresponding to the identified candidate antibodies. Logistic regression was used to derive and validate autoantibody panels that can discriminate SLE disease. Extensive ELISA screening of sera from 294 SLE patients and 461 controls was performed to validate one of the newly discovered autoantibodies. RESULTS: A total of 31, 11 and 18 autoantibodies were identified to be expressed at significantly higher levels in the SLE group than in the healthy volunteers, disease controls and healthy volunteers plus disease control groups, respectively, with 25, 7 and 13 of these differentially expressed autoantibodies being previously unreported. Diagnostic panels comprising anti-RPLP2, anti-SNRPC and anti-PARP1, and anti-RPLP2, anti-PARP1, anti-MAK16 and anti- RPL7A were selected. Performance of the newly discovered anti-MAK16 autoantibody was confirmed by ELISA. Some associations were seen with clinical characteristics of SLE patients, such as disease activity with the level of anti-PARP1 and rash with the level of anti-RPLP2, anti-MAK16 and anti- RPL7A. CONCLUSION: The combined autoantibody panels identified here show promise for the diagnosis of SLE and for differential diagnosis of other major rheumatic immune diseases.
OBJECTIVE: Clinical diagnosis of SLE is currently challenging due to its heterogeneity. Many autoantibodies are associated with SLE and are considered potential diagnostic markers, but systematic screening and validation of such autoantibodies is lacking. This study aimed to systematically discover new autoantibodies that may be good biomarkers for use in SLE diagnosis. METHODS: Sera from 15 SLEpatients and 5 healthy volunteers were analysed using human proteome microarrays to identify candidate SLE-related autoantibodies. The results were validated by screening of sera from 107 SLEpatients, 94 healthy volunteers and 60 disease controls using focussed arrays comprised of autoantigens corresponding to the identified candidate antibodies. Logistic regression was used to derive and validate autoantibody panels that can discriminate SLE disease. Extensive ELISA screening of sera from 294 SLEpatients and 461 controls was performed to validate one of the newly discovered autoantibodies. RESULTS: A total of 31, 11 and 18 autoantibodies were identified to be expressed at significantly higher levels in the SLE group than in the healthy volunteers, disease controls and healthy volunteers plus disease control groups, respectively, with 25, 7 and 13 of these differentially expressed autoantibodies being previously unreported. Diagnostic panels comprising anti-RPLP2, anti-SNRPC and anti-PARP1, and anti-RPLP2, anti-PARP1, anti-MAK16 and anti- RPL7A were selected. Performance of the newly discovered anti-MAK16 autoantibody was confirmed by ELISA. Some associations were seen with clinical characteristics of SLEpatients, such as disease activity with the level of anti-PARP1 and rash with the level of anti-RPLP2, anti-MAK16 and anti- RPL7A. CONCLUSION: The combined autoantibody panels identified here show promise for the diagnosis of SLE and for differential diagnosis of other major rheumatic immune diseases.