Common Genetically Predicted Skipping of COL4A4 Exon 27 Is Associated with Hematuria and Albuminuria
Bibliographic record
Abstract
Background: Hematuria is an established sign of glomerular disease and can be associated with kidney failure, but there has been limited scientific study of this trait. Methods: Here, we combined genetic data from the UK Biobank with predicted gene expression and splicing from GTEx kidney cortex samples (n = 65) in a transcriptome-wide association study (TWAS) to identify additional biological mechanisms influencing hematuria. Results: Our TWAS using kidney cortex identified significant associations for 5 genes in terms of expression and 3 significant splicing events. Notably, we identified an association between hematuria and the skipping of COL4A4 exon 27, which is genetically predicted by intronic rs11898094 (minor allele frequency 13%). The association was also found with urinary albumin excretion. We found independent evidence supporting the existence of this skipping event in glomeruli-derived mRNA transcriptomics data (n = 245) from the NEPTUNE dataset. The functional significance of loss of exon 27 was demonstrated using the split NanoLuc-based type IV collagen α3α4α5(IV) heterotrimer assay, in which heterotrimer formation was quantified by luminescence. Conclusions: Altogether, our results highlight the value of investigating the role of non-coding sequence, an underexplored region, by integrating multiple data types to shed light on kidney traits and their underlying disease mechanisms. Funding: NIDDK SupportGenomic overview of the exon 27 skipping event of COL4A4.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".