II-12 CSF-1 and IL-34: distinct potential biomarkers for lupus
Bibliographic record
Abstract
Background A noninvasive means to predict the onset and recurrence of lupus is needed to optimise and individualise treatment. Macrophages (Mø) are prominent in inflamed tissues targeted for destruction in SLE. We hypothesised that the principal molecules required for Mø survival and proliferation are biomarkers for SLE. CSF-1 and IL-34 are promising candidates as both (i) bind to cFMS expressed by Mø, thereby promoting Mø survival and proliferation and (ii) promote destructive inflammation. However, IL-34 and CSF-1 have differing functions, which may be related to IL-34, not CSF-1, binding to a second receptor and distinct spatial temporal expressions. Materials and methods We analysed serum and urine CSF-1 and IL-34 levels in SLE patients with nephritis (LN), arthritis (LA), cutaneous and serositis compared with healthy controls in two large cohorts (ELISA). While serum and urine CSF-1 expression is elevated in each manifestation, CSF-1 is notably higher in LN. In contrast, serum IL-34 expression is dramatically higher in LA, not LN. Thus, we probed for CSF-1 and IL-34 expression in LN (kidney) and LA (synovium). Moreover, we longitudinally tracked serum CSF-1 and IL-34 prior to LN (biopsy proven), with disease activity including flares and during LA in comparison to disease activity Results LN. CSF-1 and IL-34 are expressed in the same and different renal tubular epithelial cells in LN. Elevated serum or urine CSF-1, not IL-34, levels correlate with increasing intra-renal CSF-1 expression and histopathology index. Longitudinally tracking serum CSF-1, not IL-34, levels heralds the initial onset of nephritis and a rise in serum or urine CSF-1 predicts LN recurrences before clinical evidence of renal dysfunction and conventional serologic measures. LA. IL-34, not CSF-1, expression is higher in synovial fluid and synovium in LA compared to osteoarthritis and healthy controls and correlates with magnitude of intra-synovial leukocytes. Moreover, intra-synovial IL-34 expression is similar in LA and rheumatoid arthritis. Longitudinally monitoring serum IL-34, not CSF-1, levels track with clinical disease activity in LA and RA. Conclusions Serial monitoring a rise in serum or urine CSF-1, not IL-34, in SLE reflects renal histopathology and clinical disease activity and the onset and reoccurrences of LN more accurately than conventional laboratory measures. While serial monitoring a rise in serum IL-34, not CSF-1, reflects clinical disease activity in LA. Thus, CSF-1 and IL-34 are inexpensive and accurate potential biomarkers for LN and LA, respectively.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".