RENAL (CD133+) PROGENITOR CELL POPULATION IS DECREASED IN LUPUS NEPHRITIS BIOPSIES.
Bibliographic record
Abstract
PV136 / #489 Poster Topic: AS16 - Lupus Nephritis-Pathogenesis Background/Purpose Lupus nephritis (LN) leads to end-stage renal disease in up to 10% of patients. While much attention has been paid to the immunological mechanisms underlying the disease, mechanisms of renal repair in the aftermath of flares are under-investigated. Renal progenitor cells (RPCs), which line the Bowman’s capsule of glomeruli, are thought to play a key role in renal repair after kidney injury. We sought to analyze the abundance and distribution of these cells in lupus nephritis kidneys. Methods Paired renal biopsies from 13 patients, taken at diagnosis (baseline, T0) and 1 year of treatment (T12), were analyzed. Biopsies from 4 kidney transplants were used as controls. Serial 5µm FFPE sections were stained for: : a) Multiplex fluorescence immunohistochemistry (IHC) Panel 1: Hoechst (nuclei), CD133 (an RPC marker), podocin (podocytes) and CD31 (endothelial cells); b) Multiplex fluorescence IHC Panel 2: Hoechst (nuclei), CD68 (pan-macrophage), CD3 (pan-T cell) and CD8 (CD8 + T cells); c) IHC for p16 INK4a (a marker of cellular senescence), and d) PicroSirius Red (staining collagen I and III, reflecting fibrosis). Images were scanned, and semiquantitative and quantitative analyses were performed using QuPath software v0.5.1. For each patient, pertinent clinical, biological and histological data were collected from medical files and pathological reports. Results At baseline, 11 patients were diagnosed with proliferative lupus nephritis (class III/IV), 1 patient with class II, and 1 with class V. The number of CD133 positive cells per glomerulus was significantly decreased among lupus patients as compared to controls, at both T0 and T12 (median 855 (IQR 687-1067) CD133 + cells/mm 2 in controls, vs . 141 (IQR 0-326) in LN biopsies at T0 and 188 (IQR 0-421) in LN biopsies atT12, p < 0.001 , Figure 1). We did not observe any significant correlation between the number of glomerular CD133 + cells and Activity Index or Chronicity Index. Surprisingly, the number of CD133 + cells at baseline was lower among patients with good long-term outcome (estimated glomerular filtration rate (eGFR) 5 years after diagnosis), showing an inverse correlation (Figure 2). At baseline, we did not observe any significant correlation between the number of CD133 + cells and the number of senescent (p16 + ) cells; neither did we observe a correlation with the number of CD8 + or CD68 + cells infiltrating glomeruli or within a 30-µm radius around glomeruli. Taken together, we hypothesize that CD133 + cells undergo differentiation to repair glomeruli in the aftermath of an LN episode and lose the expression of this marker in the process. This could explain why patients with lower numbers of CD133 + cells have better outcomes. Further studies are required to confirm this finding and understand the (RPC-intrinsic and/or -extrinsic) mechanisms underlying differential RPC differentiation/repopulation capacity among individuals. Figure 1: Number of CD133 positive cells in glomeruli, across all biopsies, grouped by sample type. Each dot represents a glomerulus. p -values: ANOVA with Tukey’s correction for multiple comparisons. Figure 2: Estimated glomerular filtration rate (eGFR) vs the number of CD133 positive cells in glomeruli, in baseline (T0) LN biopsies. Each dot represents a patient. R² value and p -value: Pearson linear regression analysis. Conclusions CD133 staining is drastically decreased in biopsies from lupus nephritis patients as compared to controls. Nevertheless, it is inversely correlated with eGFR at 5 years, suggesting that loss of CD133 expression may reflect differentiation of RPCs to repair kidney, and thus be predictive of good outcome.
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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) | 0.004 | 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".