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Record W4415451234 · doi:10.1210/jendso/bvaf149.602

SAT-746 Gain-of-Function CASR variants Identified as a Major Genetic Contributor of Non-Surgical Hypoparathyroidism: Findings from Over 300 Participants in a Sponsored Genetic Testing Program

2025· article· en· W4415451234 on OpenAlexaboutno aff
Michael Mannstadt, Arun Mathew, Ananth Sridhar, Lyndsay Stapleton Smith, Mary Scott Roberts, Scott Adler

Bibliographic record

VenueJournal of the Endocrine Society · 2025
Typearticle
Languageen
FieldMedicine
TopicThyroid and Parathyroid Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsHypoparathyroidismGenetic testingExome sequencingGenetic variantsFamily historyCalcium-sensing receptorGene

Abstract

fetched live from OpenAlex

Abstract Disclosure: M. Mannstadt: Advisor and research grants Calcilytix, Takeda, Amolyt. A. Mathew: BridgeBio Employee. A. Sridhar: BridgeBio Employee. L.S. Smith: BridgeBio Employee. M. Roberts: BridgeBio Employee. S. Adler: BridgeBio Employee. Hypoparathyroidism is a rare condition characterized by insufficient production of parathyroid hormone, resulting in low serum calcium and an imbalance in mineral homeostasis. Hypoparathyroidism is most commonly caused by damage to or removal of parathyroid glands during surgery, however, genetic causes have become increasingly recognized with advances in genetic testing and growing awareness of non-surgical etiologies. Genetic forms of hypoparathyroidism can occur in isolation or as part of a syndrome, and include disorders related to the formation of parathyroid glands, secretion of parathyroid hormone, and autoimmune damage to the parathyroid glands. Individuals with a clinical diagnosis of non-surgical hypoparathyroidism, positive family history or suspicion of genetic hypoparathyroidism, are eligible to participate in a no-charge sponsored genetic testing program in the United States and Canada. The next-generation sequencing panel leveraging a whole exome backbone includes 26 genes associated with hypoparathyroidism: ACADM, AIRE, ATP1A1, CASR, CHD7, CLDN16, CLDN19, CNNM2, DHCR7, EGF, FAM111A, FXYD2, GATA3, GCM2, GNA11, HADHA, HADHB, KCNA1, NEBL, PTH, SEMA3E, SLC12A3, SOX3, TBCE, TBX1 and TRPM6. A total of 327 samples were tested over four years (2020 - 2024) from participants with a mean age of 26.7 years (range 0-81). 191 variants were identified in 149 individuals (46%) which were classified as pathogenic, likely pathogenic, or variants of uncertain significance. Among these 149 individuals with detected variants, CASR was the most frequently affected (35%), followed by AIRE (17%), GATA3 (10%), TBX1 (7%), HADHA (3%), GNA11 (3%), GCM2 (3%), SEMA3E (2%), SLC12A3 (2%), NEBL (2%), DHCR7 (2%), HADHB (2%), FAM111A (2%), CHD7 (2%), ACADM (1%), TRPM6 (1%), EGF (1%), PTH (1%), KCNA1 (1%), CNNM2 (1%), CLDN19 (1%), and TBCE (1%). Notably, 36 individuals had variants identified in multiple genes. Genetic etiologies should be considered in all patients with hypoparathyroidism without a history of neck surgery as the identification of a genetic etiology can impact patient management and guide further medical evaluation. In our data, the most common genetic form of hypoparathyroidism was found to be autosomal dominant hypocalcemia type 1 (ADH1), caused by gain-of-function variants in the CASR gene (18.4%; 60/327). An ongoing global Phase 3 study [NCT05680818] is investigating encaleret, an oral calcilytic, which has the potential to be the first targeted treatment for ADH1. The sponsored genetic testing program offers an efficient pathway for diagnosing genetic causes in patients with non-surgical hypoparathyroidism and, in accordance with consensus guidelines, enables improved care for those with an identified genetic etiology. Presentation: Saturday, July 12, 2025

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.460
Threshold uncertainty score0.823

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.311
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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