402 Serum cytokine profiling reveals elevated levels of S100A8/A9 and MMP-9 in systemic lupus erythematosus patients with cognitive impairment independently of disease activity and inflammatory markers
Bibliographic record
Abstract
Background Cognitive impairment (CI) is one of the most common manifestations of neuropsychiatric lupus (NPSLE), which may occur in the absence of active Systemic Lupus Erythematosus (SLE) and negatively impacts patients’ daily functioning and health-related quality of life. Therefore, identifying patients at high risk of developing CI is essential to prevent the accrual of damage and disability. However, its pathogenesis is largely unknown, and currently, biomarkers for the risk of CI are lacking. Here we investigated whether SLE patients with CI have elevated serum levels of cytokines that previous studies have suggested to have a potential pathogenic role in NPSLE. Methods 291 individuals between 18-65 years old who met the 2019 EULAR/ACR classification criteria for SLE were included. Cognitive assessment was performed by a psychometrist and included the comprehensive 1-hour ACR Neuropsychological Battery (ACR-NB), which encompasses 19 cognitive tests representing six cognitive domains. The serum levels of nine cytokines (IL-10, IL-6, IFN-γ, TNF-α, TWEAK, MMP-9, S100 A8/A9, NGAL, and S100B) were determined using ELISA kits (R&D Systems). Differences in the serum levels of the cytokine profile between patients with and without CI (defined as a z-score of ≤-1.5 in two or more domains in the ACR-NB) were determined by the Mann-Whitney U test. Correlations were assessed using Spearman’s rank correlation coefficient and the association of the different cytokine levels with each CI test score by logistic regression. Results Forty percent of the patients (n=116) had CI. While no differences in the demographic characteristics and disease activity were observed between patients with and without CI, serum levels of S100A8/A9 and, to a lesser extent, MMP-9 were significantly higher in patients with CI (figure 1). When the ACR-NB’s domains were examined individually, patients with impaired simple attention and processing; visual-spatial construction; learning and memory; or executive function also had significantly higher S100A8/A9 than those without impairment (figure 2). Indicative of probable collinearity, S100A8/A9 and MMP-9 moderately correlated with each other (Rho=0.52, p<0.0001) and both correlated with NGAL (Rho=0.64, p<0.0001; Rho=0.56, p< 0.0001, respectively). S100A8/A9 had the strongest relationship with multiple CI tests by logistic regression. The serum levels of S100A8/A9 and MMP-9 did not correlate with TNF-α, IL-6, hs- CRP, or disease activity as determined by the SLE Disease Activity Index-2000 (SLEDAI-2K). Conclusion Among the multiple cytokines measured, only the heterodimer of the calcium- binding proteins S100A8 and S100A9 and MMP-9 were found to be increased in SLE patients with CI. The lack of correlation with the levels of other pro-inflammatory markers and its differential association with distinct cognitive domains may indicate that, in the setting of CI, S100A8/A9 mediates a regional neuroinflammatory response rather than systemic pro- inflammation. These results open new avenues to study the role of S100A8/A9 and MMP-9 in CI in adults with SLE.
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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 | 0.001 | 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".