Calcium-Sensing Receptor (CASR) Mutations in Hypercalcemic States: Studies from a Single Endocrine Clinic Over Three Years
Bibliographic record
Abstract
CONTEXT: Inactivating mutations of the calcium-sensing receptor (CASR) are implicated in different hypercalcemic syndromes, including familial hypocalciuric hypercalcemia (FHH), primary hyperparathyroidism (PHPT), and familial isolated hyperparathyroidism (FIHP). However, molecular diagnostics applied to large nonselected hypercalcemic cohorts from a single center have not been reported. OBJECTIVE: Our objective was to describe the prevalence, type, and potential pathogenicity of CASR mutations in a series of cases with FHH (n = 17), PHPT (n = 165), and FIHP (n = 3) and controls (n = 198) presenting at a single endocrine clinic. SUBJECTS: All were prospectively evaluated at the "Casa Sollievo della Sofferenza" Hospital in southern Italy over a 3-yr period. METHODS: CASR screening was conducted by denaturing HPLC. The variant CASRs were functionally characterized by transient transfection studies in kidney cells in vitro. RESULTS: A single novel missense variant was identified in one PHPT case. However, in FHH probands, mutations were found in eight of 17 (47%). With a hypercalcemic family member, mutation detection rate in FHH rose to seven of eight (87%), whereas only one of nine sporadic cases was positive, and none of the three FIHP cases had detectable CASR mutations. Five missense variant CASRs, identified in control subjects, performed as wild type in functional assays, whereas the missense mutant CASRs identified in the FHH patients, and in the one PHPT case, exhibited significant impairment. A novel intronic mutation (IVS4-19a-->c) found in one FHH family, created an abnormally spliced product in an in vitro minigene assay. CONCLUSION: CASR testing, with functional analysis, provides critical confirmatory evidence in the differential diagnosis of hypercalcemic states.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".