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Novel autoantibodies identified in ACPA-negative rheumatoid arthritis


Objectives Lack of effective biomarkers in anti-citrullinated protein antibody (ACPA)-negative rheumatoid arthritis (RA) impedes early diagnosis and treatment. This study aimed to identify novel autoantibodies in RA and verify their diagnostic values in ACPA-negative RA based on protein microarray technology.

Methods A total of 1011 sera from 559 RA (276 ACPA-positive and 283 ACPA-negative), 239 disease controls (DCs) and 213 healthy controls (HCs) were collected and sampled on two sequential microarrays and ELISA and western blot (WB) detection, for novel autoantibodies discovery, validation and verification, respectively. The high-density protein microarray printed with a broad spectrum of recombinant human proteins was first employed to screen candidate autoantibodies, then focused microarrays composed of candidate autoantigens were used for validation, followed by ELISA and WB to verify the presence of the most promising candidates in ACPA-negative RA.

Results Nine novel autoantibodies were identified by two sequential microarrays with positivity 17.93%–27.59% and specificities >90% in ACPA-negative RA. Among these, anti-PTX3 and anti-DUSP11 autoantibodies presented with the highest sensitivity and were consistently verified by ELISA and WB. Pooling samples of all cohorts, the positivities of anti-PTX3 and anti-DUSP11 in ACPA-negative RA were 27.56% and 31.80%, respectively, similar to those in ACPA-positive RA, and significantly higher than in HCs (4.69% and 2.35%) and DCs (10.04% and 8.49%) (p<0.0001). Combination of anti-PTX3 with anti-DUSP11 significantly increased the diagnostic sensitivity (38.00%) with specificity of 88.72%, regardless of ACPA status.

Conclusion Anti-PTX3 and anti-DUSP11 autoantibodies are newly identified biomarkers for diagnosis of ACPA-negative RA.

  • arthritis
  • rheumatoid
  • autoantibodies
  • anti-citrullinated protein antibodies

Data availability statement

Data are available upon reasonable request. All data relevant to the study are included in the article or uploaded as supplementary information. Data are available from the corresponding author (email: ORCID: upon reasonable request.

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