Transcriptome analysis of the NR1H3 mouse model of multiple sclerosis reveals a pro-inflammatory phenotype with dysregulation of lipid metabolism and immune response genes
Bibliographic record
Abstract
ABSTRACT Background The development of effective treatments for multiple sclerosis (MS), and in particular its progressive forms, is hampered by the lack of etiologically relevant cellular and animal models of human disease. Models that recapitulate the biological and pathological processes leading to the onset and progression of MS in patients are likely to afford better translational efficacy. Following the discovery of the NR1H3 p.Arg415Gln pathogenic mutation for progressive MS in two Canadian families, we developed a knock-in mouse model harboring a homologous mutation in the endogenous gene to provide a more physiologically relevant model of human MS. Methods Gene expression was evaluated in constitutive heterozygote (which recapitulates the human disease genotype) and homozygote Nr1h3 p.Arg413Gln knock-in mice on a C57BL/6 background, and compared to wild-type littermates. AmpliSeq Transcriptome Mouse Gene Expression kits analyzed on an Ion Proton sequencer were used to generate the gene expression profiles of spleen, liver, brain and spinal cord tissue from three-month-old male and female mice. Differential expression between genotypes was assessed with DESeq2, and Gene Ontologies pathways enrichment analysis performed with DAVID v6.8. Benjamini-Hochberg false discovery rate (FDR) correction for multiple testing was applied. Results Transcriptome analysis of spleen tissue from Nr1h3 p.Arg413Gln mice revealed 23 significantly dysregulated genes (FDR<0.05) with greater than a two-fold change in expression. These include CD5 antigen-like ( Cd5l ), complement component 6 ( C6 ), procollagen C-endopeptidase enhancer 2 ( Pcolce2 ), interleukin 22 receptor, alpha 2 ( Il22ra2 ), and T cell immunoglobulin and mucin domain containing 4 ( Timd4 ). Gene Ontology enrichment analysis support upregulation of cell cycle pathways and downregulation of immune system response in splenic cells. The liver transcriptome identified 27 significantly dysregulated genes with greater than a two-fold change in expression compared to wild-type littermates. Cd5l , Timd4 , C-C motif chemokine receptor 3 ( Ccr3 ), ADAM metallopeptidase domain 11 ( Adam11 ) and macrophage expressed 1 ( Mpeg1 ) were amongst those most significantly dysregulated. Enrichment analysis supported altered immune function with upregulation of sterol and steroid metabolic processes and downregulation of fatty acid biosynthesis and inflammatory and immune system responses. Although brain and spinal cord transcriptome profiles identified several genes significantly dysregulated in Nr1h3 mice compared to wild-type littermates (FDR<0.05), none presented greater than two-fold changes in gene expression. Discussion The analysis of the Nr1h3 p.Arg413Gln mouse model of MS suggests that the predominance of a pro-inflammatory over a healing or reparative phenotype, combined with deficiencies in myelination and remyelination, are the biological mechanisms implicated in the onset of MS and the development of a more severe progressive disease course observed in patients with NR1H3 mutations. Association of NR1H3 common variants with MS risk indicates that the disruption of these biological and immunological processes is not only informative for familial forms of disease but MS patients at large. Differences in transcriptome profiles underline the value of this model for the development and validation of novel therapeutic strategies and ultimately treatments with the potential to delay or even halt the onset of progressive MS and to ameliorate the severity of clinical symptoms.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".