Increased Prevalence of the<i>GCM2</i>Polymorphism, Y282D, in Primary Hyperparathyroidism: Analysis of Three Italian Cohorts
Bibliographic record
Abstract
CONTEXT: Glial cells missing-2 (GCM2) is key for parathyroid gland organogenesis. Its persistent expression in the adult parathyroid raises the possibility that overactive forms play a role in the evolution of parathyroid hyperactivity or tumorigenesis. A GCM2 c.844T → G; p.Y282D missense variant has been described within a transactivation inhibitory domain (amino acids 263-352). OBJECTIVE: The aims of the study were to 1) assess the frequency of Y282D in Italian primary hyperparathyroidism (PHPT) and control (C) populations, 2) test for association of 282D with PHPT and its phenotypic features, and 3) compare the transactivation potency of GCM2 282D relative to wild-type Y282. SUBJECTS AND METHODS: Subjects included a large southern Italian cohort (310 PHPT and 433 C) and 2 replication cohorts from northern Italy. Association of 282D with PHPT was tested in all cohorts and with phenotypic features in the larger PHPT cohort. An in vitro GCM promoter-luciferase reporter assay was conducted in HEK293 cells. RESULTS: 282D was significantly increased in the PHPT group, with a minor allele frequency of 0.066 compared with 0.029 in the C group (P = .0008), in the discovery cohort and was more prevalent in the replication cohorts. Combined analysis (510 PHPT and 665 C) yielded a likelihood ratio of 2.27 (95% confidence interval = 1.50-3.42; P < .0001). The 282D variant was not associated with serum calcium, phosphate, creatinine, or PTH levels or with bone mineral density, fractures, or renal stones in the PHPT group. The 282D variant had significantly greater transcriptional activity than the wild-type Y282 (17× basal vs 12× basal; P < 0.05). CONCLUSION: The higher frequency of GCM2 282D in PHPT and enhanced transcriptional activity of this variant supports the notion that it could contribute causally to parathyroid tumorigenesis.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".