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10.1002/art.39974

http://scihub22266oqcxt.onion/10.1002/art.39974
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C5378622!5378622!27792870
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suck abstract from ncbi


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pmid27792870      Arthritis+Rheumatol 2017 ; 69 (4): 742-9
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  • Phenome?Wide Association Study of Autoantibodies to Citrullinated and Noncitrullinated Epitopes in Rheumatoid Arthritis #MMPMID27792870
  • Liao KP; Sparks JA; Hejblum BP; Kuo I; Cui J; Lahey LJ; Cagan A; Gainer VS; Liu W; Cai TT; Sokolove J; Cai T
  • Arthritis Rheumatol 2017[Apr]; 69 (4): 742-9 PMID27792870show ga
  • Objective: Patients with rheumatoid arthritis (RA) develop autoantibodies against a spectrum of antigens, but the clinical significance of these autoantibodies is unclear. Using a phenome?wide association study (PheWAS) approach, we examined the association between autoantibodies and clinical subphenotypes of RA. Methods: This study was conducted in a cohort of RA patients identified from the electronic medical records (EMRs) of 2 tertiary care centers. Using a published multiplex bead assay, we measured 36 autoantibodies targeting epitopes implicated in RA. We extracted all International Classification of Diseases, Ninth Revision (ICD?9) codes for each subject and grouped them into disease categories (PheWAS codes), using a published method. We tested for the association of each autoantibody (grouped by the targeted protein) with PheWAS codes. To determine significant associations (at a false discovery rate [FDR] of ?0.1), we reviewed the medical records of 50 patients with each PheWAS code to determine positive predictive values (PPVs). Results: We studied 1,006 RA patients; the mean?±?SD age of the patients was 61.0?±?12.9 years, and 79.0% were female. A total of 3,568 unique ICD?9 codes were grouped into 625 PheWAS codes; the 206 PheWAS codes with a prevalence of ?3% were studied. Using the PheWAS method, we identified 24 significant associations of autoantibodies to epitopes at an FDR of ?0.1. The associations that were strongest and had the highest PPV for the PheWAS code were autoantibodies against fibronectin and obesity (P?=?6.1 × 10?4, PPV 100%), and that between fibrinogen and pneumonopathy (P?=?2.7 × 10?4, PPV 96%). Pneumonopathy codes included diagnoses for cryptogenic organizing pneumonia and obliterative bronchiolitis. Conclusion: We demonstrated application of a bioinformatics method, the PheWAS, to screen for the clinical significance of RA?related autoantibodies. Using the PheWAS approach, we identified potentially significant links between variations in the levels of autoantibodies and comorbidities of interest in RA.
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