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UMD-MEN1 database: an overview of the 370 MEN1 variants present in 1,676 patients from the French population

  • Romanet, Pauline
  • Mohamed, Amira
  • Giraud, Sophie
  • Odou, Marie-Françoise
  • North, Marie-Odile
  • Pertuit, Morgane
  • Pasmant, Eric
  • Coppin, Lucie
  • Guien, Celine
  • Calender, Alain
  • Borson-Chazot, Françoise
  • Béroud, Christophe
  • Goudet, Pierre
  • Barlier, Anne
Publication Date
Mar 01, 2019
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Context: Multiple Endocrine Neoplasia type 1 (MEN1) is an autosomal dominant disease caused by mutations in the MEN1 gene characterized by a broad spectrum of clinical manifestations, of which the most frequent are primary hyperparathyroidism, pituitary adenomas, and neuroendocrine tumors. Objective: The aim of this work is to facilitate interpretation of variants and improve the genetic counseling and medical care of MEN1-patients’ families. Design, Setting, and Patients: The TENGEN network (French oncogenetics network of neuroendocrine tumors) has interpreted and collected all allelic variants and clinical characteristics of the MEN1-positive patients identified through genetic testing performed in the French population from 1997 to 2015. They were registered in a locus-specific database called the UMD-MEN1 database ( Main Outcomes: variant classification, age-related penetrance, odds ratio. Results: Three hundred seventy distinct variants reported in 1,676 patients, including 181 unpublished variants, have currently been registered. This database analysis pointed out the low frequency of benign or likely benign missense variants in MEN1 (only 6.6%). Eight families (1.9%) presented a familial isolated hyperparathyroidism and harbored the same mutation found in authentic MEN1-families. An association exists between large rearrangements and an earlier onset of the disease, whereas no difference was observed between truncating and non-truncating variants. Conclusion: UMD-MEN1 database provides an exhaustive overview of the MEN1 variants present in the French population. For each variant, a classification is publicly available. Clinical data collections allow the determination of genotype-phenotype correlation and age-related penetrance of lesions in the cohort.

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