Novel endotypes of antisynthetase syndrome identified independent of anti-aminoacyl transfer RNA synthetase antibody specificity that improve prognostic stratification.

ABSTRACT

OBJECTIVES: To systemically analyse the heterogeneity in the clinical manifestations and prognoses of patients with antisynthetase syndrome (ASS) and evaluate the transcriptional signatures related to different clinical phenotypes. METHODS: A total of 701 patients with ASS were retrospectively enrolled. The clinical presentation and prognosis were assessed in association with four anti-aminoacyl transfer RNA synthetase (ARS) antibodies anti-Jo1, anti-PL7, anti-PL12 and anti-EJ. Unsupervised machine learning was performed for patient clustering independent of anti-ARS antibodies. Transcriptome sequencing was conducted in clustered ASS patients and healthy controls. RESULTS: Patients with four different anti-ARS antibody subtypes demonstrated no significant differences in the incidence of rapidly progressive interstitial lung disease (RP-ILD) or prognoses. Unsupervised machine learning, independent of anti-ARS specificity, identified three endotypes with distinct clinical features and outcomes. Endotype 1 (RP-ILD cluster, 23.7%) was characterised by a high incidence of RP-ILD and a high mortality rate. Endotype 2 (dermatomyositis (DM)-like cluster, 14.5%) corresponded to patients with DM-like skin and muscle symptoms with an intermediate prognosis. Endotype 3 (arthritis cluster, 61.8%) was characterised by arthritis and mechanic's hands, with a good prognosis. Transcriptome sequencing revealed that the different endotypes had distinct gene signatures and biological processes. CONCLUSIONS: Anti-ARS antibodies were not significant in stratifying ASS patients into subgroups with greater homogeneity in RP-ILD and prognoses. Novel ASS endotypes were identified independent of anti-ARS specificity and differed in clinical outcomes and transcriptional signatures, providing new insights into the pathogenesis of ASS.