Functional validation of a human CAPN5 exome variant by lentiviral transduction into mouse retina
Bibliographic record
Abstract
Exome sequencing indicated that the gene encoding the calpain-5 protease, CAPN5, is the likely cause of retinal degeneration and autoimmune uveitis in human patients with autosomal dominant neovascular inflammatory vitreoretinopathy (ADNIV, OMIM #193235). To explore the mechanism of ADNIV, a human CAPN5 disease allele was expressed in mouse retinas with a lentiviral vector created to express either the wild-type human (h) CAPN5 or the ADNIV mutant hCAPN5-R243L allele under a rhodopsin promoter with tandem green fluorescent protein (GFP) expression. Vectors were injected into the subretinal space of perinatal mice. Mouse phenotypes were analyzed using electroretinography, histology and inflammatory gene expression profiling. Mouse calpain-5 showed high homology to its human ortholog with >98% sequence identity that includes the ADNIV mutant residue. Calpain-5 protein was expressed in the inner and outer segments of the photoreceptors and in the outer plexiform layer. Expression of the hCAPN5-R243L allele caused loss of the electroretinogram b-wave, photoreceptor degeneration and induction of immune cell infiltration and inflammatory genes in the retina, recapitulating major features of the ADNIV phenotype. Intraocular neovascularization and fibrosis were not observed during the study period. Our study shows that expression of the hCAPN5-R243L disease allele elicits an ADNIV-like disease in mice. It further suggests that ADNIV is due to CAPN5 gain-of-function rather than haploinsufficiency, and retinal expression may be sufficient to generate an autoimmune response. Genetic models of ADNIV in the mouse can be used to explore protease mechanisms in retinal degeneration and inflammation as well as preclinical therapeutic testing.
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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) | 0.001 | 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 | 0.001 | 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".