Decades-long elevation of interferon-α drives a Sjögren disease endotype: an interdisciplinary study
Bibliographic record
Abstract
SUMMARY BACKGROUND Mechanistic heterogeneity is a major obstacle to the development of effective treatment for Sjögren disease (SjD) and there is a pressing need to stratify SjD according to precision medicine principles. Aberrant activation of the type I interferon (IFN) pathway represents a leading candidate pathway, but a causal role of elevated IFN-α in driving a Sjögren disease endotype remains to be established. METHODS We used ultrasensitive single molecule ELISA, and an oligoprotein interferon signature score (derived from broad capture proteomics), to study the role of IFN-α in Sjögren disease. We analysed samples from the UK Primary Sjögren Syndrome Registry (UKPSSR, n=177) and UK Biobank Plasma Proteomics Project (n=47606 without Sjögren, n=257 with Sjögren, including 137 individuals sampled prior to diagnosis) to determine the timecourse and immune endotype associated with elevated IFN-α. To address causality we created a new transgenic mouse model of IFN-α overexpression to establish whether chronically elevated IFN-α drives this immune endotype. FINDINGS Oligoprotein interferon signatures can be detected at least 14 years prior to diagnosis of Sjögren disease in the UK Biobank-PPP. IFN-α concentrations are elevated in 60% of Sjögren disease patients in the UKPSSR. Individuals with elevated IFN-α display a distinct immunological endotype characterised by cytopenias, hypergammaglobulinaemia, multiple autoantibodies and autoimmunity against the Sjögren autoantigen TRIM21/Ro52. To address the key question of causal direction, we created a new mouse model of systemic chronic IFN-α elevation, in which Ifn α 4 is overexpressed by conventional dendritic cells. This model recapitulates key features of the endotype and can be partially reversed by IFNAR1 blockade. INTERPRETATION Elevation of IFN-α drives an immune endotype of Sjögren disease, originating over a decade prior to diagnosis. SjD patients with elevated IFN-α concentrations are broadly clinically similar to those with normal IFN-α concentrations, yet are immunologically distinct. This highlights the mechanistic heterogeneity of SjD and the need for immunological stratification along precision medicine principles, using high resolution biomarkers. As well as demonstrating causal direction, biological modelling shows that chronic IFN-α elevation over the lifecourse has the potential to establish persistent immune dysregulation which responds only partially to interferon receptor blockade. These findings provide insights into SjD and other “interferonopathic” rheumatological disorders. Research in context Evidence before this study We searched MEDLINE for “Sjögren’s Syndrome/Disease” and “interferon”, including the terms “subsets”, “sub-groups”, “phenotypes”, and “endotypes”, filtering by “clinical trial”, “stratification”, and “immune-mediated inflammatory”. We also included major review articles from noted experts. We identified reports of associations between IFN-α and SjD, usually using indirect or imprecise measures of IFN-α. None of these studies included prediagnostic samples and causal inference was limited. Added value of this study This study shows that IFN-α, when measured directly using ultrasensitive single molecule ELISA approaches (uniquely optimised to determine healthy control concentrations), is elevated in a subset of people with SjD with a specific immunological endotype. Analysis of prediagnostic proteomics shows this elevation can be detected up to 14 years before diagnosis. We show that IFN-α drives this endotype (as opposed to vice versa) by recapitulating key endotype features in a novel and unambiguous experimental mouse model of chronic IFN-α elevation. We also show that the pathogenic consequences of IFN-α elevation over long periods of time can only be partially reversed using IFNAR blockade. Implications of all the available evidence These data have important implications for future research, clinical practice, trial design, and therapeutic development. First, our findings provide clinical evidence, supported by unambiguous preclinical evidence, that decades-long elevated IFNα can cause and drive a SjD endotype – and accurately defines the level of heterogeneity. Secondly, we provide biomarkers which may be of use in stratifying clinical trial design and also for early identification of at-risk individuals. Thirdly we provide biological proof of principle that longstanding and potentially undiagnosed elevation of IFN-α can establish persistent immune dysregulation which may respond only partially to IFNAR blockade. Together these findings inform precision medicine approaches and future trial design.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".