USH2A variants causing retinitis pigmentosa or Usher syndrome provoke differential retinal phenotypes in disease-specific organoids
Bibliographic record
Abstract
There is an emblematic clinical and genetic heterogeneity associated with inherited retinal diseases (IRDs). The most common form is retinitis pigmentosa (RP), a rod-cone dystrophy caused by pathogenic variants in over 80 different genes. Further complexifying diagnosis, different variants in individual RP genes can also alter the clinical phenotype. USH2A is the most prevalent gene for autosomal recessive RP and also one of the most challenging due to its large size and, hence, large number of variants. Moreover, USH2A variants give rise to both non-syndromic and syndromic RP, known as Usher syndrome (USH) type 2, which associates vision and hearing loss. The lack of a clear genotype-phenotype correlation or prognostic models renders diagnosis highly challenging. We report here, a long-awaited differential non-syndromic RP and USH phenotype in three human disease-specific models: fibroblasts, induced pluripotent stem cells (iPSCs), and mature iPSC-derived retinal organoids. Moreover, we identified distinct retinal phenotypes in organoids from multiple RP and USH individuals, which were validated by isogenic-corrected controls. Non-syndromic RP organoids showed a compromised photoreceptor differentiation, whereas USH organoids showed a striking and unexpected cone phenotype. Furthermore, complementary clinical investigations identified a macular atrophy in a high proportion of USH compared to RP individuals, further validating our observations that USH2A variants differentially affect cones. Overall, the identification of distinct non-syndromic RP and USH phenotypes in multiple models provides valuable and robust read-outs for testing the pathogenicity of USH2A variants, as well as the efficacy of therapeutic approaches in complementary cell types.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".