Systematic Ocular Phenotyping of Knockout Mouse Lines Identifies Genes Associated With Age-Related Corneal Dystrophies
Bibliographic record
Abstract
Purpose: This study investigates genes contributing to late-adult corneal dystrophies (LACDs) in aged mice, with potential implications for late-onset corneal dystrophies (CDs) in humans. Methods: The International Mouse Phenotyping Consortium (IMPC) database, containing data from 8901 knockout mouse lines, was filtered to include late-adult mice (49+ weeks) with significant (P < 0.0001) CD phenotypes. Candidate genes were mapped to human orthologs using the Mouse Genome Informatics group, with expression analyzed via PLAE and a literature review for prior CD associations. Comparative analyses of LACD genes from IMPC and established human CD genes from IC3D included protein interactions (STRING), biological processes (PANTHER), and molecular pathways (KEGG). Results: Analysis identified 14 genes linked to late-adult abnormal corneal phenotypes. Of these, 2 genes were previously associated with CDs in humans, while 12 were novel. Seven of the 14 genes (50%) were expressed in the human cornea based on single-cell transcriptomics. Protein-protein interactions via STRING showed several significant interactions with known human CD genes. PANTHER analysis identified six biological processes shared with established human CD genes. Two genes (Rgs2 and Galnt9) were involved in pathways related to human corneal diseases, including cGMP-PKG signaling, mucin-type O-glycan biosynthesis, and oxytocin signaling. Other candidates were implicated in pathways such as pluripotency of stem cells, MAPK signaling, WNT signaling, actin cytoskeleton regulation, and cellular senescence. Conclusions: This study identified 14 genes linked to LACD in knockout mice, 12 of which are novel in corneal biology. These genes may serve as potential therapeutic targets for treating corneal diseases in aging human populations.
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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 | 0.002 | 0.001 |
| 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".