Identifying photoreceptors in blind eyes caused by <i>RPE65</i> mutations: Prerequisite for human gene therapy success
Bibliographic record
Abstract
Mutations in RPE65, a gene essential to normal operation of the visual (retinoid) cycle, cause the childhood blindness known as Leber congenital amaurosis (LCA). Retinal gene therapy restores vision to blind canine and murine models of LCA. Gene therapy in blind humans with LCA from RPE65 mutations may also have potential for success but only if the retinal photoreceptor layer is intact, as in the early-disease stage-treated animals. Here, we use high-resolution in vivo microscopy to quantify photoreceptor layer thickness in the human disease to define the relationship of retinal structure to vision and determine the potential for gene therapy success. The normally cone photoreceptor-rich central retina and rod-rich regions were studied. Despite severely reduced cone vision, many RPE65-mutant retinas had near-normal central microstructure. Absent rod vision was associated with a detectable but thinned photoreceptor layer. We asked whether abnormally thinned RPE65-mutant retina with photoreceptor loss would respond to treatment. Gene therapy in Rpe65(-/-) mice at advanced-disease stages, a more faithful mimic of the humans we studied, showed success but only in animals with better-preserved photoreceptor structure. The results indicate that identifying and then targeting retinal locations with retained photoreceptors will be a prerequisite for successful gene therapy in humans with RPE65 mutations and in other retinal degenerative disorders now moving from proof-of-concept studies toward clinical trials.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".