RENAL (CD133+) PROGENITOR CELL POPULATION IS DECREASED IN LUPUS NEPHRITIS BIOPSIES.
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».