Novel Autoantibodies Related to Cell Death and DNA Repair Pathways in Systemic Lupus Erythematosus

Hui Luo, Ling Wang, Ding Bao, Li Wang, Hongjun Zhao, Yun Lian, Mei Yan, Chandra Mohan, Quan Zhen Li

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

Systemic lupus erythematosus (SLE) is a complex autoimmune syndrome characterized by various co-existing autoantibodies (autoAbs) in patients’ blood. However, the full spectrum of autoAbs in SLE has not been comprehensively elucidated. In this study, a commercial platform bearing 9400 antigens (ProtoArray) was used to identify autoAbs that were significantly elevated in the sera of SLE patients. By comparing the autoAb profiles of SLE patients with those of healthy controls, we identified 437 IgG and 1213 IgM autoAbs that the expression levels were significantly increased in SLE (P < 0.05). Use of the ProtoArray platform uncovered over 300 novel autoAbs targeting a broad range of nuclear, cytoplasmic, and membrane antigens. Molecular interaction network analysis revealed that the antigens targeted by the autoAbs were most significantly enriched in cell death, cell cycle, and DNA repair pathways. A group of autoAbs associated with cell apoptosis and DNA repair function, including those targeting APEX1, AURKA, POLB, AGO1, HMGB1, IFIT5, MAPKAPK3, PADI4, RGS3, SRP19, UBE2S, and VRK1, were further validated by ELISA and Western blot in a larger cohort. In addition, the levels of autoAbs against APEX1, HMGB1, VRK1, AURKA, PADI4, and SRP19 were positively correlated with the level of anti-dsDNA in SLE patients. Comprehensive autoAb screening has identified novel autoAbs, which may shed light on potential pathogenic pathways leading to lupus.

Original languageEnglish (US)
Pages (from-to)248-259
Number of pages12
JournalGenomics, Proteomics and Bioinformatics
Volume17
Issue number3
DOIs
StatePublished - Jun 2019

Keywords

  • Apoptosis
  • Autoantibodies
  • DNA repair
  • ProtoArray
  • Systemic lupus erythematosus

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Genetics
  • Computational Mathematics

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