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Updated: May 10, 2026

In Vivo Modeling of the Morbid Human Genome using Danio rerio
Published on: August 24, 2013
Genotype-phenotype correlation and challenges in mutation detection in McCune-Albright syndrome: A retrospective
Camille Giannetti1, Karine Aouchiche2, Arnaud Lagarde1
1Laboratory of Molecular Biology GEnOPé, Assistance-Publique des Hôpitaux de Marseille (AP-HM), Hôpital de la Timone, 13385 Marseille, France.
Background:
McCune-Albright syndrome MAS is a rare mosaic disorder caused by post-zygotic GNAS activating mutations. MAS is characterized by fibrous dysplasia (FD) of the skeleton, café-au-lait skin macules, and hyperfunctioning endocrinopathies such as precocious puberty, thyroid disease, growth hormone excess, and FGF23-mediated phosphate wasting. Mosaicism leads to marked clinical heterogeneity and complicates molecular diagnosis.
Methods:
We retrospectively analyzed clinical and genotyping data of patients referred for suspected or clinically diagnosed MAS in a single French center (2014-2025). GNAS R201C and R201H mutations were detected by digital droplet PCR using peripheral blood as first-line samples, with additional testing of circulating cell-free, saliva, or tissue when indicated.
Results:
We included 405 patients, from which 89 (22%) carried a GNAS mutation (52 R201C, 37 R201H). No significant clinical differences were observed between R201C and R201H. Among 578 analyzed samples, mutation detection varied by sample type, with the highest rates in tissue. Mutant allele frequency (MAF) in blood DNA was higher in patients with polyostotic than in monostotic FD (P=0.0055), but was not associated with the overall MAS-related lesion number. No correlation was found between MAF and age at diagnosis.
Conclusions:
MAS shows substantial clinical and molecular heterogeneity without clear genotype-phenotype differences between R201 variants. Mutation detection strongly depends on sample type, reflecting disease mosaicism. A multimodal diagnostic strategy and larger collaborative cohorts are needed to optimize molecular diagnosis and refine genotype-phenotype correlations in MAS patients.
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