Discovery of New Serum Biomarker Panels for Systemic Lupus Erythematosus Diagnosis

Hua-Zhi Ling; Shu-Zhen Xu; Rui-Xue Leng; Jun Wu1, Hai-Feng Pan; Yin-Guang Fan; Bin Wang; Yuan-Rui Xia; Qian Huang; Zong-Wen Shuai; Dong-Qing Ye


Rheumatology. 2020;59(6):1416-1425. 

In This Article

Abstract and Introduction


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.


SLE is generally a chronic, inflammatory disease that causes multi-organ injury, including damage to the kidneys, blood, brain and skin.[1–3] Features of SLE include periods of flare-up and remission, dysregulation of the immune system and development of autoantibodies.[4] The diagnosis of SLE is challenging due to the heterogeneity of its clinical course, symptoms and disease severity.[5–7] Serum biomarkers used in the diagnosis of SLE are mainly autoantibodies specific for intracellular antigens located in the cell nucleus or cytoplasm. About 180 autoantibodies have been identified in SLE patients, 102 of which are reported to have an organ-specific correlation with SLE disease activity.[8] However, with the exception of autoantibodies such as ANA, anti-dsDNA, anti-Sm and aPL, currently proposed by the ACR[9] and SLICC[10] for the diagnosis of SLE, most of these autoantibodies lack sufficient sensitivity and/or specificity for use in clinical diagnosis. Discovery of additional autoantibodies with high sensitivity and specificity is important for early diagnosis and assessment of the prognosis of SLE.

Protein microarrays have been widely used in the diagnosis, prediction and prognosis of many diseases and have contributed greatly in the development of modern medicine. The HuProt human proteome microarray, developed at John Hopkins University, is the most comprehensive and high-throughput human proteome microarray currently available and has been used to identify many new biomarkers for different diseases.[11–13] A small study using HuProt to identify biomarkers for neuropsychiatric SLE demonstrated the potential of this proteome microarray for discovering novel autoantibodies suitable for the diagnosis of SLE.[14] However, additional reports on systematic screening and validation of autoantibodies for SLE are lacking. Here we applied a previously reported two-phase strategy[11] to comprehensively discover and then validate autoantibodies that may be good biomarkers for use in the diagnosis of SLE. We then validated one of the previously unreported autoantibodies, anti-MAK16, using ELISA.