RELATING TRANSCRIPTOMIC PROFILES OF HUMAN LUPUS NEPHRITIS AND GLOMERULONEPHRITIS IN LUPUS-PRONE MICE
Bibliographic record
Abstract
PV011 / #383 Poster Topic: AS02 - Animal Models Background/Purpose The presentation of lupus nephritis (LN) is heterogeneous, but is thought to initiate with immune complex deposition in the kidney and acute inflammation that develops into a chronic condition resulting in end-stage renal disease. We sought to better understand the molecular features of LN through gene expression profiling of human disease and its relationship to that of a well-defined murine model of LN. Methods Human subjects were control (CTL) patients without kidney pathology and patients with ISN/RPI class II-V LN. The NZM2328 lupus-prone mouse, an established model of human LN that progresses from predisease (CTL) to acute (AGN), transitional (TGN) and chronic (CGN) nephritis, was also assessed.[1] Gene expression was analyzed from glomerular (Glom) and tubulo-interstitial (TI) regions for enrichment of informative gene modules by Gene Set Variation Analysis (GSVA). Results GSVA and unsupervised k-means clustering identified 4 subsets of LN in the human Glom and TI, which were ordered from least to most severe based on abnormalities in molecular profile as compared to CTL subjects. In the Glom, subset specific changes in metabolism, kidney tissue, immune, endothelial cell and podocyte modules were noted (Figure 1a). Mouse orthologs of the human gene modules were applied to analysis of the Glom from lupus-prone mice (Figure 1b). In the mouse Glom, progression from CTL to AGN and TGN was accompanied by an increase in immune/inflammatory modules and decreases in metabolism and tissue modules. CGN mice were divided between Subsets 2-4 with some mice that exhibited an inflammatory profile and others that were de-enriched for all modules indicative of a post-inflammatory state. Analysis of the human and mouse TI revealed progressive abnormalities (Figure 2). The TI samples from human CTL patients were clustered in Subset 1 and exhibited minimal immune module enrichment, whereas metabolism and kidney tubule modules were prominent (Figure 2a). Subsets 2-3 had increased of immune and decreased metabolism and kidney tubule modules. Subset 4 had minimal inflammation, but decreased kidney tubule expression. The progression of disease severity in the TI of lupus-prone mice from predisease to chronic disease was highly aligned with the molecular subset of each mouse and consistent with changes in human disease (Figure 2b). Figure 1: Clustering of GSVA enrichment scores from human and mouse lupus kidney glomeruli. (a) GSVA heatmap of kidney glomeruli from human CTL and LN patients (GSE32591) with ISN/RPI classification for enrichment of immune, metabolism, and kidney tissue gene modules. (b) GSVA heatmap of kidney glomeruli from NZM2328 mice (GSE206806) with predefined disease stage annotation for enrichment of mouse orthologs of the modules in (a). Figure 2: Clustering of GSVA enrichment scores from human and mouse lupus kidney tubulo-interstitial tissue. (a) GSVA heatmaps of kidney tubulointerstitium from human (a) NZM2328 mice (b) as in Figure 1. Conclusions Human and mouse LN transcriptomic profiles were strikingly similar, such that the progression in human could be related to that of murine LN. Class II patients resembled CTL and AGN mice. Class III patients were akin to AGN and TGN mice. Class IV-V patients shared profiles of TGN and some CGN mice. Alignment of the transcriptomic profiles of human and mouse LN provides new evidence on the nature of progression of human disease and also confirms the utility of the NZM2328 model of LN in defining the molecular pathogenesis of human LN. References: [1.] Daamen AR. Front Immunol 2024;14:1282770.
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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) | 0.001 | 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".