Risk of nephrolithiasis in primary hyperparathyroidism is associated with two polymorphisms of the calcium-sensing receptor gene
Bibliographic record
Abstract
AIMS: Two single-nucleotide polymorphisms (SNPs) at the calcium-sensing receptor (CASR) gene were previously associated with kidney stones in patients with primary hyperparathyroidism (PHPT): rs1501899, likely associated with a decrease in CASR expression, and Arg990Gly, causing a gain of CASR function. To evaluate the interaction of these two SNPs in the stone risk, we tested the association of stones with the genotype at both SNPs in PHPT patients and the association of rs1501899 with CASR expression as messenger RNA (mRNA) in human kidney samples. METHODS AND RESULTS: Two hundred and ninety-six PHPT patients were genotyped at the rs1501899 and Arg990Gly SNPs. Minor allele frequency at tested SNPs was higher in PHPT stone formers relative to non-stone forming patients. PHPT patients carrying one or two copies of the minor allele at both rs1501899 and Arg990Gly (n = 16) had the maximal risk of stones (odds ratio, OR 8.3) and higher serum ionized calcium compared with homozygous patients for the wild-type allele at both SNPs. CASR expression as mRNA was measured by real time polymerase chain reaction (PCR) in normal kidney medulla samples from 109 subjects. CASR mRNA was significantly lower in medulla samples from homozygotes for the minor allele at rs1501899 than in subjects with other genotypes. CONCLUSIONS: We conclude that the simultaneous presence of the minor allele at rs1501899 and Arg990Gly may amplify the kidney stone risk in PHPT patients, despite their apparently opposite effects on CASR function in the kidney.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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".