Cytokine profiles of lupus patients with or without nephritis
Bibliographic record
Abstract
It remains unclear why some patients with SLE develop lupus nephritis (LN) and others do not. A reasonable hypothesis is that the inflammatory/immunomodulatory mechanisms in patients with LN are either qualitatively different than in nonrenal (NR) lupus, or that similar pathways are activated but the magnitude of activation is greater in LN. Studies of individual or small groups of candidate cytokines support this idea. To test this hypothesis we examined baseline serum and peripheral blood mononuclear cell (PBMC) cytokine profiles of SLE patients with active LN or NR (mainly arthritis) lupus before entry into a clinical trial of Laquinimod (Teva Pharmaceuticals) as an adjunct anti-inflammatory agent for SLE. We sought to determine whether NR or LN was associated with a distinct pattern or level of cytokine expression. Serum and PBMC from 49 NR and 16 LN patients were collected. PBMC were cultured in medium with or without lipopolysaccharide (LPS), phytohemagglutinin (PHA), or tetanus toxoid (TT). PBMC proliferation was measured after 48 hours, and 38 cytokines were measured in the PBMC-conditioned supernatant by Luminex multiplexing. The same cytokines were measured in the sera. LN patients were younger (37 ± 9 vs. 47 ± 14, P < 0.006), had a higher serum creatinine (91.6 ± 28.6 vs. 69.6 ± 16.5 μmol/l, P < 0.0003), higher BILAG score (13.6 ± 8.2 vs. 7.2 ± 3.2, P < 0.0001), higher baseline corticosteroid dose (18.3 ± 1.3.3 vs. 8 ± 8 mg/day, P < 0.004), and were more likely to enter the study taking a concomitant immunosuppressive agent (MMF; 50 vs. 22%). There were no quantitative differences in NR and LN serum cytokine levels for most analytes that were within the limits of detection. Eotaxin and soluble TNF receptor II were greater in LN sera ( P = 0.037 and P = 0.022, respectively). Interestingly, IL-17 was not detectable in any LN sample, but was present in 17% of NR sera. LN and NR PBMC proliferated equally well to LPS and PHA, but in response to TT proliferation of NR PBMC was greater than LN PBMC ( P < 0.0001). TT did not induce LN PBMC cytokine production. LPS and PHA induced significant increases in production of 24 of the 38 measured cytokines from PBMC, but there were few differences between LN and NR. LPS-induced IL-7 and IL-12 levels were higher from LN PBMC ( P < 0.02), and PHA induced more IL-5 production by NR PBMC ( P = 0.008). Unexpectedly, no cytokine signature that distinctly separates LN from NR emerged from this survey. This may be due to the greater baseline level of immunosuppression in LN patients, but even with immunosuppression the LN was very active. It is intriguing to speculate that differences, perhaps genetic, in the kidney's response to inflammation, rather than differences in circulating proinflammatory cytokines, determine susceptibility to LN in SLE patients.
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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 | 0.001 |
| 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) | 0.002 | 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".