Novel <i>Grm6</i> Variant in a <i>no b-wave (nob)</i> Mouse Model: Phenotype Characterization and Gene Therapy
Bibliographic record
Abstract
Purpose: To characterize a no b-wave (nob) mouse model of congenital stationary night blindness (CSNB) caused by a Grm6 variant that disrupts photoreceptor-to-bipolar cell signaling. Additionally, we aim to evaluate the efficacy of gene therapy in restoring visual function. Methods: The nob mouse was generated through selective breeding to regenerate the nob phenotype. Adeno-associated viruses encoding Grm6 and GFP, driven by two promoters (hGRM6 and CMV), were administered to nob mice at postnatal days 5 (P5) and 30 (P30), respectively. Electroretinography and spectral domain optical coherence tomography (SD-OCT) were conducted three months after gene therapy. Results: The nob phenotype was successfully regenerated, and a homozygous missense variant c.1037G>A (p.Arg346His) in Grm6 was identified as the causal variant. Scotopic b waves were absent, whereas a waves remained normal, indicating intact rod function but impaired bipolar cell function. SD-OCT revealed thinning of the retinal nerve fiber layer and outer plexiform layer (OPL) in affected mice. Immunofluorescence and immunoblotting revealed decreased mGluR6 levels and associated signaling proteins. Gene therapy restored mGluR6 expression and reestablished synaptic protein localization in the OPL, although improvements in b/a ratios and OPL thickness were modest. Notably, the hGRM6 promoter at P5 was more effective at restoring OPL. Conclusions: We identified a new nob mouse model that mimics the CSNB phenotype in human patients. Whereas gene therapy successfully restored mGluR6 expression, functional improvements were limited. Early treatment using a specific promoter is critical, and increasing transduction efficiency may improve gene therapy strategies.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 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".