Profiling the microRNA signature of the peripheral sensory ganglia in experimental autoimmune encephalomyelitis (EAE)
Bibliographic record
Abstract
Abstract Background Multiple sclerosis is an autoimmune disease with a distinct female bias, as well as a high prevalence of neuropathic pain in both sexes. The dorsal root ganglia (DRG) contain the primary sensory neurons that give rise to pain, and damage to these neurons may lead to neuropathic pain. Here, we investigate the sex differences of the DRG transcriptome in a mouse model of MS. Methods Next-generation sequencing was used to establish RNA and microRNA profiles from the DRG of mice with MOG 35–55 -induced EAE, a model of CNS inflammation that mimics aspects of MS. Differential expression and multiple meta-analytic approaches were used to compare expression profiles in immunized female and male mice. Differential expression of relevant genes and microRNAs were confirmed by qPCR. Results Three thousand five hundred twenty genes and 29 microRNAs were differentially expressed in the DRG of female mice with MOG 35–55 -EAE, while only 189 genes and 3 microRNAs were differentially expressed in males with MOG 35–55 -EAE. Genes related to the immune system were uniquely regulated in immunized female mice. Direct comparison of sex within disease indicates significant differences in interferon and phagosomal pathways between the sexes. miR-21a-5p is the primary dysregulated microRNA in both sexes, with females having additional dysregulated microRNAs, including miR-122-5p. Conclusions This study provides evidence that females are uniquely affected by MOG 35–55 -EAE and that this difference may result from additional signaling not present in the male. The altered transcriptome of females correlates with other studies finding hyperactivity of pain-sensing neurons and suggests underlying sex-specific pathways for neuropathic pain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".