Evidence map›Paper›PMID 41965096›Full record

ReviewThe Journal of clinical endocrinology and metabolism2026

Genetics of familial acromegaly and pituitary gigantism.

Sunita M C De Sousa, Adrian F Daly

Abstract readReview
In one paragraph

Review in The Journal of clinical endocrinology and metabolism, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Sunita M C De SousaAdelaide Medical School, University of Adelaide, Adelaide 5000, Australia.ORCID 0000-0003-0127-6482
Adrian F DalyDepartment of Endocrinology, Centre Hospitalier Universitaire de Liège, University of Liège, Liège 4000, Belgium.ORCID 0000-0001-6130-2975

Funding

Crinetics Pharmaceuticals, Inc
6 · The paper itself

Abstract

The subset of pituitary adenomas with a heritable genetic basis is small but clinically striking. Somatotropinomas are amongst the most frequent pituitary adenoma subtypes encountered in this setting, with germline variants being enriched in familial acromegaly kindreds and people with a childhood or adolescent history of GH hypersecretion manifesting as pituitary gigantism. The genetic causes of familial acromegaly and pituitary gigantism include variants in established pituitary adenoma predisposition genes (AIP, especially, but also MEN1, CDKN1B, MAX, and PRKAR1A), X-linked acrogigantism due to Xq26.3 microduplications, and McCune-Albright syndrome due to postzygotic gain-of-function GNAS variants. Potential associations include variants in emerging pituitary adenoma predisposition genes, including NF1, PRKACB, PAM, and CHEK2. Given the potential for gene-specific therapeutic implications in these diseases, multimodal genetic testing arranged by experienced pituitary subspecialists and conducted in expert, clinically accredited laboratories is needed to fully evaluate the genetic basis of disease. Key investigations include next-generation sequencing, chromosome microarray, and droplet digital polymerase chain reaction. Exploratory research-based genetic testing may help uncover new genetic causes of familial acromegaly kindreds and pituitary gigantism in people with negative results on standard testing, benefiting those being tested as well as advancing our understanding of the heritable basis of somatotropinomas.

Indexed as

AcromegalyAdenomaGigantismGrowth Hormone-Secreting Pituitary AdenomaPituitary NeoplasmsGenetic Predisposition to DiseaseGenetic TestingHumansacromegalyfamilialgeneticsgigantismmultiple endocrine neoplasiapituitary

Identifiers

PMID41965096
PMCPMC13235292

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.