Literature DB >> 33410562

Functional characterization of ABCC8 variants of unknown significance based on bioinformatics predictions, splicing assays, and protein analyses: Benefits for the accurate diagnosis of congenital hyperinsulinism.

Cécile Saint-Martin1, Marine Cauchois-Le Mière2,3, Emily Rex4, Omar Soukarieh2, Jean-Baptiste Arnoux5, Julien Buratti1, Delphine Bouvet1, Thierry Frébourg2,3, Pascaline Gaildrat2, Show-Ling Shyng4, Christine Bellanné-Chantelot1, Alexandra Martins2.   

Abstract

ABCC8 encodes the SUR1 subunit of the β-cell ATP-sensitive potassium channel whose loss of function causes congenital hyperinsulinism (CHI). Molecular diagnosis is critical for optimal management of CHI patients. Unfortunately, assessing the impact of ABCC8 variants on RNA splicing remains very challenging as this gene is poorly expressed in leukocytes. Here, we performed bioinformatics analysis and cell-based minigene assays to assess the impact on splicing of 13 ABCC8 variants identified in 20 CHI patients. Next, channel properties of SUR1 proteins expected to originate from minigene-detected in-frame splicing defects were analyzed after ectopic expression in COSm6 cells. Out of the analyzed variants, seven induced out-of-frame splicing defects and were therefore classified as recessive pathogenic, whereas two led to skipping of in-frame exons. Channel functional analysis of the latter demonstrated their pathogenicity. Interestingly, the common rs757110 SNP increased exon skipping in our system suggesting that it may act as a disease modifier factor. Our strategy allowed determining the pathogenicity of all selected ABCC8 variants, and CHI-inheritance pattern for 16 out of the 20 patients. This study highlights the value of combining RNA and protein functional approaches in variant interpretation and reveals the minigene splicing assay as a new tool for CHI molecular diagnostics.
© 2021 Wiley Periodicals LLC.

Entities:  

Keywords:  ABCC8; KATP channel SUR1 subunit; congenital hyperinsulinism; in silico predictions; minigene splicing assays; variants of unknown significance

Mesh:

Substances:

Year:  2021        PMID: 33410562      PMCID: PMC8049974          DOI: 10.1002/humu.24164

Source DB:  PubMed          Journal:  Hum Mutat        ISSN: 1059-7794            Impact factor:   4.878


  51 in total

1.  Functional analysis of a large set of BRCA2 exon 7 variants highlights the predictive value of hexamer scores in detecting alterations of exonic splicing regulatory elements.

Authors:  Daniela Di Giacomo; Pascaline Gaildrat; Anna Abuli; Julie Abdat; Thierry Frébourg; Mario Tosi; Alexandra Martins
Journal:  Hum Mutat       Date:  2013-09-18       Impact factor: 4.878

2.  Correction to: Splicing mutations in human genetic disorders: examples, detection, and confirmation.

Authors:  Anna Abramowicz; Monika Gos
Journal:  J Appl Genet       Date:  2019-05       Impact factor: 3.240

3.  Congenital hyperinsulinism: pancreatic [18F]fluoro-L-dihydroxyphenylalanine (DOPA) positron emission tomography and immunohistochemistry study of DOPA decarboxylase and insulin secretion.

Authors:  Pascale de Lonlay; Aurore Simon-Carre; Maria-João Ribeiro; Nathalie Boddaert; Irina Giurgea; Kathleen Laborde; Christine Bellanné-Chantelot; Virginie Verkarre; Michel Polak; Jacques Rahier; André Syrota; David Seidenwurm; Claire Nihoul-Fékété; Jean-Jacques Robert; Francis Brunelle; Francis Jaubert
Journal:  J Clin Endocrinol Metab       Date:  2006-01-10       Impact factor: 5.958

4.  The added value of [18F]fluoro-L-DOPA PET in the diagnosis of hyperinsulinism of infancy: a retrospective study involving 49 children.

Authors:  Maria-João Ribeiro; Nathalie Boddaert; Christine Bellanné-Chantelot; Sandrine Bourgeois; Vassili Valayannopoulos; Thierry Delzescaux; Francis Jaubert; Claire Nihoul-Fékété; Francis Brunelle; Pascale De Lonlay
Journal:  Eur J Nucl Med Mol Imaging       Date:  2007-07-28       Impact factor: 9.236

5.  Large-scale comparative evaluation of user-friendly tools for predicting variant-induced alterations of splicing regulatory elements.

Authors:  Hélène Tubeuf; Camille Charbonnier; Omar Soukarieh; André Blavier; Arnaud Lefebvre; Hélène Dauchel; Thierry Frebourg; Pascaline Gaildrat; Alexandra Martins
Journal:  Hum Mutat       Date:  2020-08-16       Impact factor: 4.878

6.  Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology.

Authors:  Sue Richards; Nazneen Aziz; Sherri Bale; David Bick; Soma Das; Julie Gastier-Foster; Wayne W Grody; Madhuri Hegde; Elaine Lyon; Elaine Spector; Karl Voelkerding; Heidi L Rehm
Journal:  Genet Med       Date:  2015-03-05       Impact factor: 8.822

Review 7.  Application of CRISPR Tools for Variant Interpretation and Disease Modeling in Inherited Retinal Dystrophies.

Authors:  Carla Fuster-García; Belén García-Bohórquez; Ana Rodríguez-Muñoz; José M Millán; Gema García-García
Journal:  Genes (Basel)       Date:  2020-04-27       Impact factor: 4.096

8.  Clinical and molecular characterisation of 300 patients with congenital hyperinsulinism.

Authors:  Ritika R Kapoor; Sarah E Flanagan; Ved Bhushan Arya; Julian P Shield; Sian Ellard; Khalid Hussain
Journal:  Eur J Endocrinol       Date:  2013-03-15       Impact factor: 6.664

9.  Exonic Splicing Mutations Are More Prevalent than Currently Estimated and Can Be Predicted by Using In Silico Tools.

Authors:  Omar Soukarieh; Pascaline Gaildrat; Mohamad Hamieh; Aurélie Drouet; Stéphanie Baert-Desurmont; Thierry Frébourg; Mario Tosi; Alexandra Martins
Journal:  PLoS Genet       Date:  2016-01-13       Impact factor: 5.917

10.  ABCA4 midigenes reveal the full splice spectrum of all reported noncanonical splice site variants in Stargardt disease.

Authors:  Riccardo Sangermano; Mubeen Khan; Stéphanie S Cornelis; Valerie Richelle; Silvia Albert; Alejandro Garanto; Duaa Elmelik; Raheel Qamar; Dorien Lugtenberg; L Ingeborgh van den Born; Rob W J Collin; Frans P M Cremers
Journal:  Genome Res       Date:  2017-11-21       Impact factor: 9.043

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