Phenome-Wide Association Study of Autoantibodies to Citrullinated and Noncitrullinated Epitopes in Rheumatoid Arthritis

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Objective. RA patients develop autoantibodies against a spectrum of antigens but their clinical significance is unclear. Using the phenome-wide association study (PheWAS) approach, we examined the association between autoantibodies and clinical subphenotypes of RA.

Methods. This study was conducted using a validated electronic medical record (EMR) RA cohort from 2 tertiary care centers. Using a published multiplex bead assay, we measured 36 autoantibodies targeting epitopes implicated in RA. We extracted all ICD-9 codes for each subject and grouped them using a published method into disease categories (PheWAS codes). We tested for the association of each autoantibody grouped by targeted protein with PheWAS codes. For significant associations (false discovery rate [FDR] ≤0.1), we reviewed 50 medical records of subjects with each PheWAS code to determine the positive predictive value (PPV).

Results. We studied 1006 RA subjects, mean age 61.0 years (SD 12.9) and 79.0% female. There were 3,568 unique ICD-9 codes grouped into 625 PheWAS codes; 206 PheWAS codes with a prevalence ≥3% were studied. PheWAS identified 24 significant associations of autoantibodies to epitopes at FDR≤0.1. Associations with the strongest associations and highest PPV for PheWAS code included autoantibodies against fibronectin with obesity (p=6.1x10−4, PPV 100%), and fibrinogen with pneumonopathy (p=2.7x10−4, PPV 96%). The latter included diagnoses for cryptogenic organizing pneumonia and obliterative bronchiolitis.

Conclusion. We demonstrated the application of a bioinformatics method, the PheWAS, to screen for clinical significance of RA-related autoantibodies. PheWAS identified potential significant links between variations in levels of autoantibodies and comorbidities of interest in RA. This article is protected by copyright. All rights reserved.


  • rheumatoid arthritis
  • Anti-citrullinated Protein Autoantibodies (ACPAs)
  • Autoantibody(ies)
  • Pulmonary
  • Bioinformatics

doi: 10.1002/art.39974

PMID: 27792870
Last updated on 05/16/2017