Diminished SUV3 expression and its functional implications in the IFN-enriched monocyte subset of childhood Sjögren’s disease
Bibliographic record
Abstract
OBJECTIVES: This study investigates the molecular and functional implications of reduced Suv3-like RNA helicase (SUV3) expression in the interferon (IFN)-enriched subset of monocytes from childhood Sjögren's disease (cSjD). SUV3 is known to unwind double-stranded RNAs (dsRNAs) for homeostatic RNA decay within mitochondria. METHODS: Using single-cell RNA sequencing, we analysed highly inflammatory IFN-enriched CD14+ monocytes from cSjD patients. To model SUV3 deficiency, we performed SUV3 knockdown in monocytic cells and studied the origin, localization and accumulation of dsRNAs in the cytosol. Formaldehyde crosslinking immunoprecipitation (fCLIP)-qPCR identified an intracellular sensor of dsRNAs. We further examined patient monocytes using J2 anti-dsRNA antibodies and transmission electron microscopy (TEM) for subcellular localization. In vitro assays assessed the impact of SUV3 knockdown on oxidative stress, ATP production, migration and phagocytosis. RESULTS: SUV3 knockdown led to the accumulation of mitochondrial-dsRNAs (mt-dsRNAs) outside of the mitochondria, where they interacted with protein kinase R (PKR). This activated PKR, triggering a type I IFN signature and upregulating proinflammatory cytokines linked to fatigue. TEM revealed mt-dsRNAs in mitochondrial-derived vesicles and multi-vesicular bodies. Notably, cSjD monocytes had a significantly higher frequency of dsRNA-positive cells compared with controls (39% vs 0.08%, P < 0.002). SUV3 depletion also increased superoxide and ROS production, while impairing ATP synthesis, migration and phagocytosis, which are key innate immune functions. These defects were partially or fully reversed by co-knockdown of PKR. CONCLUSION: SUV3 is the key driver for defective innate immune functions through mt-dsRNA-mediated PKR activation, which enhances cellular stress, mitochondrial dysfunction and inflammatory signatures, uncovering a novel mechanism in cSjD pathogenesis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".