Phenome-Wide Association Study of Autoantibodies to Citrullinated and Noncitrullinated Epitopes in Rheumatoid Arthritis.
Phenome-Wide Association Study of Autoantibodies to Citrullinated and Noncitrullinated Epitopes in Rheumatoid Arthritis.
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DOI：
10.1002/art.39974
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发表时间：
2017-04
期刊：
影响因子：
--
通讯作者：
Cai T
中科院分区：
文献类型：
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作者：
Liao KP;Sparks JA;Hejblum BP;Kuo IH;Cui J;Lahey LJ;Cagan A;Gainer VS;Liu W;Cai TT;Sokolove J;Cai T
类风湿性关节炎（RA）患者会产生针对一系列抗原的自身抗体，但这些自身抗体的临床意义尚不清楚。使用全表型关联研究（PheWAS）方法，我们检查了自身抗体与RA临床亚表型之间的关联。本研究在从2个三级医疗中心的电子病历（EMR）中识别的RA患者队列中进行。使用已发表的多重珠测定，我们测量了36个自身抗体靶向RA相关表位。我们提取了每个受试者的所有国际疾病分类第九版（ICD-9）代码，并使用已发表的方法将其分组为疾病类别（PheWAS代码）。我们测试了每种自身抗体（按靶蛋白分组）与PheWAS代码的相关性。为了确定显著相关性（错误发现率[FDR] ≤0.1），我们审查了50例具有每个PheWAS代码的患者的病历，以确定阳性预测值（PPV）。我们研究了1，006例RA患者;患者的平均± SD年龄为61.0 ± 12.9岁，79.0%为女性。共将3，568个唯一ICD-9代码分为625个PheWAS代码;研究了患病率≥3%的206个PheWAS代码。使用PheWAS方法，我们在FDR ≤0.1时鉴定了24种自身抗体与表位的显著相关性。对于PheWAS编码，最强且PPV最高的相关性是抗纤连蛋白的自身抗体和肥胖（P = 6.1 × 10−4，PPV 100%），以及纤维蛋白原和肺部疾病之间的相关性（P = 2.7 × 10−4，PPV 96%）。肺部疾病代码包括隐源性机化性肺炎和闭塞性细支气管炎的诊断。我们展示了生物信息学方法PheWAS在筛选RA相关自身抗体的临床意义中的应用。使用PheWAS方法，我们确定了RA中自身抗体水平变化与相关合并症之间的潜在显著联系。
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. 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). 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. 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.