Association of Elevated Serum <scp>S100A8</scp> / <scp>A9</scp> Levels and Cognitive Impairment in Patients With Systemic Lupus Erythematosus
Bibliographic record
Abstract
OBJECTIVE: Cognitive impairment (CI) is common in patients with systemic lupus erythematosus (SLE). Despite its prevalence, the immune mechanisms are not well understood. We previously reported elevated serum levels of S100A8/A9 and matrix metalloproteinase 9 (MMP-9) in patients with SLE and CI. This study aims to validate those findings by examining the relationship between serum levels and CI in patients with SLE at baseline and after one year. METHODS: We assessed cognitive function in 112 patients with SLE using the adapted American College of Rheumatology-Neuropsychological Battery, defining CI as impairment in two or more domains. Serum S100A8/A9 and MMP-9 levels were measured by enzyme-linked immunosorbent assay. We compared serum levels between CI and non-CI groups, evaluated cognitive domain performance at baseline and one year, and explored associations between serum changes and cognitive status changes. RESULTS: At baseline, 48 patients (42.8%) had CI. After one year, the cognitive funtion remained stable in 55%, improved in 31.2%, and worsened in 13% of patients. Serum S100A8/A9 levels were significantly higher in CI patients at baseline (P = 0.0007, r = 0.413) and one year (P = 0.0045, r = 0.359), correlating inversely with multiple CI domains. The worsened group showed a significant increase in S100A8/A9 levels, whereas the improved group exhibited a reduction. CONCLUSION: In this large cohort of patients with well-characterized SLE, serum S100A8/A9 levels were elevated in those with CI and showed an inverse relationship with cognitive performance across multiple domains. Changes in S100A8/A9 levels corresponded with changes in cognitive status over one year. These findings warrant further investigation into the role of S100A8/A9 in CI within the context of 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".