A variant OSR1 allele which disturbs OSR1 mRNA expression in renal progenitor cells is associated with reduction of newborn kidney size and function
Bibliographic record
Abstract
Human nephrons are formed during fetal life through an interaction between the branching ureteric bud and progenitor cells. The wide variation in final nephron number has been attributed to allelic variants of genes regulating ureteric bud arborization. Here, we hypothesize that dysfunctional variants of the Odd-Skipped Related 1 (OSR1) gene which compromise the renal progenitor cell pool might also limit newborn kidney size and function. We show that OSR1 is expressed in human mesenchymal stem cells, the blastemal component of Wilms tumors and CD24+/CD133+ progenitor cells isolated from the mature kidney. We identified an OSR1(rs12329305(T)) allele in 6% of normal Caucasians which alters an exon2 splice enhancer. This variant is predicted to reduce spliceosome-binding affinity and stability of the OSR1 mRNA. In cultured cells, the OSR1(rs12329305)(T) allele produced no identifiable transcript. Normal Caucasian newborns from Montreal with the OSR1(rs12329305)(T) allele had kidney volume 11.8% smaller (P= 0.006) and cord blood cystatin C levels 12.6% higher (P = 0.005) than those with wild-type genotype. Effects of the OSR1(rs12329305)(T) allele are additive with genes that alter ureteric bud branching. Kidney volume was reduced more in newborns bearing both RET(rs1800860)(A) and OSR1(rs12329305)(T) alleles (22%, P= 0.0008) and cystatin C was increased by 17% (P= 0.006) versus newborns with wild-type alleles. Although only two subjects had PAX2(rs11599825)(A) and OSR1(rs12329305)(T) alleles, kidney size was reduced by 27% and cystatin C was increased by 14% versus wild-types (P= NS).
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".