Clinical Characteristics of Anti-Synthetase Syndrome: Analysis From the Classification Criteria for Anti-Synthetase Syndrome Project

Abstract

Objective: Anti-synthetase syndrome (ASSD) is a rare systemic autoimmune rheumatic disease (SARD) with significant heterogeneity and no shared classification criteria. We aimed to identify clinical and serological features associated with ASSD that may be suitable for inclusion in the data-driven classification criteria for ASSD.

Methods: We used a large, international, multicenter "Classification Criteria for Anti-synthetase Syndrome" (CLASS) project database, which includes both patients with ASSD and controls with mimicking conditions, namely, SARDs and/or interstitial lung disease (ILD). The local diagnoses of ASSD and controls were confirmed by project team members. We employed univariable logistic regression and multivariable Ridge regression to evaluate clinical and serological features associated with an ASSD diagnosis in a randomly selected subset of the cohort.

Results: Our analysis included 948 patients with ASSD and 1,077 controls. Joint, muscle, lung, skin, and cardiac involvement were more prevalent in patients with ASSD than in controls. Specific variables associated with ASSD included arthritis, diffuse myalgia, muscle weakness, muscle enzyme elevation, ILD, mechanic's hands, secondary pulmonary hypertension due to ILD, Raynaud phenomenon, and unexplained fever. In terms of serological variables, Jo-1 and non-Jo-1 anti-synthetase autoantibodies, antinuclear antibodies with cytoplasmic pattern, and anti-Ro52 autoantibodies were associated with ASSD. In contrast, isolated arthralgia, dysphagia, electromyography/magnetic resonance imaging/muscle biopsy findings suggestive of myopathy, inflammatory rashes, myocarditis, and pulmonary arterial hypertension did not differentiate between patients with ASSD and controls or were inversely associated with ASSD.

Conclusion: We identified key clinical and serological variables associated with ASSD, which will help clinicians and offer insights into the development of data-driven classification criteria for ASSD.

Figure 1

Clinical and serological variables included in each domain. ANA, antinuclear autoantibody; ANCA, anti–neutrophil cytoplasmic antibody; CCP, cyclic citrullinated peptide; DAD, diffuse alveolar damage; dsDNA, double‐stranded DNA; EMG, electromyography; HMGCR, 3‐hydroxy‐3‐methylglutaryl‐CoA reductase; HRCT, high‐resolution computed tomography; ILD, interstitial lung disease; LIP, lymphoid interstitial pneumonia; MDA5, melanoma differentiation–associated gene 5; MPO, myeloperoxidase; MRI, magnetic resonance imaging; NSIP, nonspecific interstitial pneumonia; NXP2, nuclear matrix protein 2; OP, organizing pneumonia; PH, pulmonary hypertension; PR3, proteinase 3; SAE, small ubiquitin‐like modifier‐1 activating enzyme; SRP, signal recognition peptide; TIF1‐γ, transcription intermediary factor 1‐γ; UIP, usual interstitial pneumonia; WHO, World Health Organization.

Figure 2

Prevalence of variables in cases and controls and the association of each variable with ASSD diagnosis. ANA, antinuclear autoantibody; ARS, aminoacyl‐transfer RNA synthetase; ASSD, anti‐synthetase syndrome; EMG, electromyography; HRCT, high‐resolution computed tomography; ILD, interstitial lung disease; MAA, myositis‐associated autoantibody; MRI, magnetic resonance imaging; MSA, myositis‐specific autoantibody; NSIP, nonspecific interstitial pneumonia; OP, organizing pneumonia; OR, odds ratio; PAH, pulmonary arterial hypertension; PH, pulmonary hypertension; UIP, usual interstitial pneumonia. Color figure can be viewed in the online issue, which is available at http://onlinelibrary.wiley.com/doi/10.1002/art.43038/abstract.