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Nascer e Crescer

versão impressa ISSN 0872-0754

Nascer e Crescer vol.24  supl.1 Porto fev. 2015

 

POSTER ABSTRACTS / RESUMOS DE POSTERS

 

P-14

Whole-exome sequencing analysis of adult patients with rare genetic diseases: what have we learned?

 

 

Jorge OliveiraI,IV; Luís NegrãoII; Rute PereiraIII,IV; Alberto BarrosV; Mário SousaIII,IV,V; Rosário SantosI,IV,VI

IUnidade de Genética Molecular, Centro Genética Médica Doutor Jacinto Magalhães, Centro Hospitalar do Porto - EPE, Porto, Portugal
IIConsulta de Doenças Neuromusculares, Hospitais da Universidade de Coimbra, Centro Hospitalar Universitário de Coimbra, Coimbra, Portugal
IIIDepartamento de Microscopia, Laboratório de Biologia Celular, Instituto de Ciências Biomédicas Abel Salazar, Universidade do Porto (ICBAS-UP), Porto, Portugal
IVUnidade Multidisciplinar de Investigação Biomédica (UMIB), Instituto de Ciências Biomédicas Abel Salazar (ICBAS), Universidade do Porto, Porto, Portugal
VCentro de Genética da Reprodução Prof. Alberto Barros, Porto, Portugal
VIUCIBIO/REQUIMTE, Departamento de Ciências Biológicas, Laboratório de Bioquímica, Faculdade de Farmácia, Universidade do Porto, Porto, Portugal

jorge.oliveira@chporto.min-saude.pt

 

 

Introduction: Next-generation sequencing (NGS) is accelerating clinical genetics research and diagnostics, given its capacity to generate genomic data in a faster and cheaper way. NGS may avoid the usual stepwise gene-by-gene analysis by performing targeted resequencing of several loci simultaneously (gene panels). Wider NGS applications, such as whole-exome sequencing (WES), may even enable the identifi                             of new genes associated with human diseases. Nevertheless, WES applicability is challenging considering the large number of variants obtained which require specifi analytical strategies and bioinformatic resources. The authors describe the use of WES in three adult patients, exemplifying its diagnostic potential but also diffi                                 encountered during analysis.

Materials and Methods: WES was  performed  using the Ion Proton system in five individuals: Case #1- a female patient with a childhood-onset progressive muscular dystrophy (35 years of clinical follow-up) and her parents; Case #2- an infertile male with situs-inversus and total sperm immotility; Case #3- a male patient presenting limb- girdle muscular dystrophy with onset during early adulthood. Bioinformatic analysis was  performed using several algorithms for variant annotation, filtering and to identify autozygosity through runs of homozygosity.

Results and discussion: In case #1, analysis assumed an autosomal recessive (AR) disease model and focused on genes implicated in hereditary myopathies. This analysis suggested the choline kinase beta (CHKB) gene as a possible candidate, where the detailed scrutiny of sequence alignments revealed the causal variant (c.1031+3G>C). Although the mutation was successfully detected its zygosity was incorrectly called suggesting a possible pitfall in WES.

A similar approach was used for case #2, resorting to candidate genes known to be associated with sperm immotility due to flagellar abnormalities. Variants in additional loci were also filtered by Gene Ontology. As a result, two novel variants were identified: a homozygous missense variant (p.Arg35Pro) in the CCDC103 gene and a novel frameshift variant in the INSL6 gene (c.262_263delCC).

The experience gathered in the study of these first two patients was important to delineate the analysis strategy for case #3, which shall be presented in this work. We propose a new bioinformatic pipeline for the analysis of AR diseases using WES, combining variant filtering and autozygosity mapping.

Concluding remarks: Considering the present state of the art, WES should be seen as a screening method. There are technical and analytical limitations to be properly addressed in WES before incorporating it in routine diagnostics. Our experience, in line with recent scientific reports, suggests that WES is presently one of the most efficient and cost-effective approaches to study highly heterogeneous rare diseases.