<i>MERTK</i> mutation update in inherited retinal diseases
Bibliographic record
Abstract
MER tyrosine kinase (MERTK) encodes a surface receptor localized at the apical membrane of the retinal pigment epithelium. It plays a critical role in photoreceptor outer segment internalization prior to phagocytosis. Mutations in MERTK have been associated with severe autosomal recessive retinal dystrophies in the RCS rat and in humans. We present here a comprehensive review of all reported MERTK disease causing variants with the associated phenotype. In addition, we provide further data and insights of a large cohort of 1,195 inherited retinal dystrophies (IRD) index cases applying state-of-the-art genotyping techniques and summarize current knowledge. A total of 79 variants have now been identified underlying rod-cone dystrophy and cone-rod dystrophy including 11 novel variants reported here. The mutation spectrum in MERTK includes 33 missense, 12 nonsense, 12 splice defects, 12 small deletions, two small insertion-deletions, three small duplications, and two exonic and three gross deletions. Altogether, mutations in MERTK account for ∼2% of IRD cases with a severe retinal phenotype. These data are important for current and future therapeutic trials including gene replacement therapy or cell-based therapy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".