Recessive variants in the intergenic NOS1AP-C1orf226 locus cause monogenic kidney disease responsive to anti-proteinuric treatment
Bibliographic record
Abstract
In genetic disease, an accurate expression landscape of disease genes and faithful animal models can facilitate genetic diagnoses and therapeutic advances respectively. Previously, we found that variants in NOS1AP, the gene that encodes nitric oxide synthase 1 adaptor protein, cause monogenic nephrotic syndrome. Here, we determine that an intergenic splice product of NOS1AP/Nos1ap and neighboring C1orf226/Gm7694, which prevents NOS1AP from binding to nitric oxide synthase 1, is the predominant isoform in mammalian kidney transcriptional and proteomic data. Gm7694−/− mice, whose allele exclusively disrupts the intergenic product, develop nephrotic syndrome phenotypes. In two male human subjects with nephrotic syndrome, we identify causative NOS1AP splice variants, including one predicted to abrogate intergenic splicing but initially misclassified as benign based on the canonical transcript. Finally, by modifying genetic background, we generate a faithful mouse model of NOS1AP-associated monogenic nephrotic syndrome that responds to anti-proteinuric treatment. Variants in NOS1AP can cause monogenic nephrotic syndrome. Here, the authors show that disrupting the intergenic NOS1AP splice isoform that is more prevalent in podocytes leads to monogenic kidney disease responsive to RAAS inhibition.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".