Disrupting the Repeat Domain of Premelanosome Protein (PMEL) Produces Dysamyloidosis and Dystrophic Ocular Pigment Reflective of Pigmentary Glaucoma
Bibliographic record
Abstract
Pigmentary glaucoma has recently been associated with missense mutations in PMEL that are dominantly inherited and enriched in the protein’s fascinating repeat domain. PMEL pathobiology is intriguing because PMEL forms functional amyloid in healthy eyes, and this PMEL amyloid acts to scaffold melanin deposition. This is an informative contradistinction to prominent neurodegenerative diseases where amyloid formation is neurotoxic and mutations cause a toxic gain of function called “amyloidosis”. Preclinical animal models have failed to model this PMEL “dysamyloidosis” pathomechanism and instead cause recessively inherited ocular pigment defects via PMEL loss of function; they have not addressed the consequences of disrupting PMEL’s repetitive region. Here, we use CRISPR to engineer a small in-frame mutation in the zebrafish homolog of PMEL that is predicted to subtly disrupt the protein’s repetitive region. Homozygous mutant larvae displayed pigmentation phenotypes and altered eye morphogenesis similar to presumptive null larvae. Heterozygous mutants had disrupted eye morphogenesis and disrupted pigment deposition in their retinal melanosomes. The deficits in the pigment deposition of these young adult fish were not accompanied by any detectable glaucomatous changes in intraocular pressure or retinal morphology. Overall, the data provide important in vivo validation that subtle PMEL mutations can cause a dominantly inherited pigment pathology that aligns with the inheritance of pigmentary glaucoma patient pedigrees. These in vivo observations help to resolve controversy regarding the necessity of PMEL’s repeat domain in pigmentation. The data foster an ongoing interest in an antithetical dysamyloidosis mechanism that, akin to the amyloidosis of devastating dementias, manifests as a slow progressive neurodegenerative disease.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".