ALTERATIONS IN INNATE IMMUNE POPULATIONS DURING SYSTEMIC AUTOIMMUNE RHEUMATIC DISEASE DEVELOPMENT
Bibliographic record
Abstract
O022 / #466 Topic: AS14 - Innate Immunity ABSTRACT CONCURRENT SESSION 03: INNATE AND ADAPTIVE IMMUNITY IN SLE 22-05-2025 1:40 PM - 2:40 PM Background/Purpose Systemic autoimmune rheumatic diseases (SARD) are a group of chronic diseases characterized by the presence of antinuclear antibodies (ANAs). However, ANAs cannot reliably be used as a diagnostic tool because a subset of healthy women are ANA + (~20%) and the majority of these individuals will not progress to SARD. Why some individuals progress while others remain asymptomatic is unknown. Previous work suggests that monocytes/DCs may support immunological disturbances observed in SARD, including a shift toward a T helper (Th) 17 cell phenotype with a concurrent decrease in Tregs. Our objective is to evaluate functional alterations in innate immune populations during SARD development. Methods Experiments have been completed to examine the composition of innate immune cells in PBMCs using CITE-seq. Samples were used from 5 ANA - healthy controls, 11 ANA + asymptomatic (5 progressors sampled prior to progression, 6 nonprogressors) and 8 early SARD patients (4 SLE, 4 Sjogren’s disease). Five million freshly thawed PBMCs were depleted of T and B cells by negative selection, and stained with a panel of oligo-conjugated antibodies for the identification of DC/monocyte populations. 9000 cells were sequenced at a depth of 50000 reads for gene expression and 5000 reads for CITE-seq. Results Using both gene and surface protein expression, we identified 11 distinct DC and monocyte populations (Figure 1A). Proportional analysis revealed an expansion of nonclassical and activated nonclassical monocytes in progressor and SARD patients (Figure 1B). SARD patients also exhibited higher proportions of cDC3s, VCAN+ monocytes and MME+ DCs than ANA + individuals regardless of progression status (Figure 1B), suggesting a role for these cells in active disease. Comparing asymptomatic ANA + individuals, we found that classical, intermediate, and nonclassical monocytes were expanded in progressors while cDC1s, cDC2s and pDCs were expanded in nonprogressors (Figure 1B). Differential analysis showed high expression of interferon (IFN) stimulated genes in progressors and SARD patients (Figure 1C), implicating these proinflammatory cytokines in the transition to SARD. Interestingly, nonprogressors exclusively had elevated expression of heat shock proteins (Figure 1C), which have been shown to promote immunologic tolerance and may play a role in preventing progression to SARD. In contrast, progressors had elevated HLA expression (Figure 1C), suggesting enhanced antigen presentation capacity. These differences in gene expression were observed across cell types, but intermediate monocytes are shown as representative cells due to their role in antigen presentation. Several genes were differentially expressed between progressors and SARD (Figure 1C), potentially highlighting distinct roles for genes in initiating and driving disease. Further analysis will be done to examine pathways associated with these genes. Figure 1. A) UMAP of 11 annotated monocyte and DC clusters. B) Proportional analysis showing each cluster for control, non-progressor, progressor and SARD groups. Data was normalized to account for differences in cell counts per cluster and per patient sample. C) Heatmap showing differentially expressed genes between patient groups, with intermediate monocytes as a representative cell cluster (log2FC = |1.0|, Q > 0.05, min.pct = 0.1). Similar trends were seen in the remaining cell types. Genes and patients were clustered in an unsupervised manner. Genes of interest are indicated with pink representing genes elevated in progressors and green representing genes elevated in non-progressors. Conclusions Our data reveals differences in proportions and gene expression between progressors, nonprogressors and SARD patients. Importantly, ANA + progressors show expanded monocyte populations and functional differences compared to nonprogressors prior to progression, highlighting immune disturbances even in the asymptomatic, preclinical stage of SARD. The results provide insight into the immune mechanisms that drive progression from asymptomatic autoimmunity to disease in SARD.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".