Symptom-based stratification of patients with primary Sjögren's syndrome: multi-dimensional characterisation of international observational cohorts and reanalyses of randomised clinical trials

Abstract

Background Heterogeneity is a major obstacle to developing effective treatments for patients with primary Sjögren's syndrome. We aimed to develop a robust method for stratification, exploiting heterogeneity in patient-reported symptoms, and to relate these differences to pathobiology and therapeutic response. MethodsWe did hierarchical cluster analysis using five common symptoms associated with primary Sjögren's syndrome (pain, fatigue, dryness, anxiety, and depression), followed by multinomial logistic regression to identify subgroups in the UK Primary Sjögren's Syndrome Registry (UKPSSR). We assessed clinical and biological differences between these subgroups, including transcriptional differences in peripheral blood. Patients from two independent validation cohorts in Norway and France were used to confirm patient stratification. Data from two phase 3 clinical trials were similarly stratified to assess the differences between subgroups in treatment response to hydroxychloroquine and rituximab. FindingsIn the UKPSSR cohort (n=608), we identified four subgroups: Low symptom burden (LSB), high symptom burden (HSB), dryness dominant with fatigue (DDF), and pain dominant with fatigue (PDF). Significant differences in peripheral blood lymphocyte counts, anti-SSA and anti-SSB antibody positivity, as well as serum IgG, κ-free light chain, β2-microglobulin, and CXCL13 concentrations were observed between these subgroups, along with differentially expressed transcriptomic modules in peripheral blood. Similar findings were observed in the independent validation cohorts (n=396). Reanalysis of trial data stratifying patients into these subgroups suggested a treatment effect with hydroxychloroquine in the HSB subgroup and with rituximab in the DDF subgroup compared with placebo.Interpretation Stratification on the basis of patient-reported symptoms of patients with primary Sjögren's syndrome revealed distinct pathobiological endotypes with distinct responses to immunomodulatory treatments. Our data have important implications for clinical management, trial design, and therapeutic development. Similar stratification approaches might be useful for patients with other chronic immune-mediated diseases.

Improvement of Severe Fatigue Following Nuclease Therapy in Patients With Primary Sjögren’s Syndrome: A Randomized Clinical Trial

“…In another observational study of 2 European cohorts of patients with primary SS, fatigue was observed to decrease as systemic IFN activity increased (24). In a third large observational study from the UK, conducted in 608 patients with primary SS, patients with the lowest symptom burden had the highest expression of IFN‐inducible genes (25). In a recent clinical study of hydroxychloroquine for the treatment of primary SS, it was observed that hydroxychloroquine treatment resulted in a significant decrease in IFN‐inducible gene expression, but no clinical improvement (26).…”

OUP accepted manuscript

“…Different strategies in subgrouping patients with pSS can be applied. A recent study defined four different subgroups based on patient-reported outcome measures of levels of pain, dryness, fatigue, depression and anxiety [ 6 ]. The subgroups differed in laboratory parameters and gene expression as well as response in clinical trials in retrospective analysis of pain, dryness and fatigue scores, and salivary flow measurements.…”

“…Given the heterogeneity in clinical presentation of what is currently referred to as pSS, selecting patients and evaluating outcomes in clinical trials has proven difficult. A recent study suggested patient-reported outcome measures to classify patients with pSS into different subtypes [ 6 ]. Variation in clinical manifestations or outcome based on presence or absence of particular biomarkers has also been highlighted [ 1 , 7 ].…”

Physiological System Dysregulation in Gene Expression Correlates Negatively with Age

“…In order to have appropriate age distributions, datasets that did not include individuals older than 75 years old or had narrow age distributions were also discarded. A total of five datasets listed in Table 1 were therefore included in the analysis ( Beutner et al, 2011 ; Sood et al, 2015 ; Wingo and Gibson, 2015 ; Peters et al, 2015 ; Tarn et al, 2019 ). Age ranges are large for all datasets, and one dataset (UKPSSR) is composed of almost exclusively female samples ( Appendix 1 Figure 1 ).…”