Searchable abstracts of presentations at key conferences in endocrinology
Endocrine Abstracts (2013) 31 P254 | DOI: 10.1530/endoabs.31.P254

1King’s College London, London, UK; 2Department of Endocrinology, Queen Mary University of London, London, UK; 3Department of Medical Genetics, Institute of Mother and Child, Warsaw, Poland; 4University of Bristol, Bristol, UK; 5Department of Molecular Genetics, Royal Devon and Exeter Foundation Trust, Exeter, UK.


Locus-specific databases (LSDBs) have been recently developed in response to the increasing number of genetic changes reported in the human genome. LSDBs have been created for several genes implicated in endocrine syndromes, for example MEN1, VHL, RET, GNAS, PRKAR1A and the SDH subunits. Mutations in AIP are found in about 20% of familial isolated pituitary adenoma (FIPA) patients.

The aim of this project is to collect all the variants found worldwide in FIPA cohorts accompanied by their clinical information in order to improve our knowledge about this syndrome. We have developed a curated, free-to-use AIP-LSDB, available at http://aip.fipapatients.org/.

The database is registered in Orphanet, the reference portal for rare diseases. AIP variants are named according to the locus reference genomic (LRG) 460, a standard reference sequence generated in collaboration with the NCBI and EBI, following Human Genome Variation Society recommendations. Variants submission by other centres is allowed after free registration via a provided clinical description form.

The database is displayed as a graphic view of AIP. The number and type of variants in each region (i.e. exons and introns) are reported in a pop-up window while passing with the mouse over the corresponding fragment. By clicking on the region of interest the nucleotide and amino acid sequence appear and all the reported variants are showed underneath as dots. Clicking on each dot enables to see the genetic and clinical details reported in the patients harbouring that variant. A flexible data selection tool is implemented for statistical analysis, but data can also be exported to perform further analyses.

This database will assist clinicians and researchers in the interpretation of AIP variants, thus improving genetic counselling and reducing unnecessary testing, and will help to examine the structure–function and the genotype-phenotype correlations, if any, in AIP mutated patients.

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