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Molecular Diagnosis of Glycogen Storage Disease and Disorders with Overlapping Clinical Symptoms by Massive Parallel Sequencing

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Molecular Diagnosis of Glycogen Storage Disease and Disorders with Overlapping Clinical Symptoms by Massive Parallel Sequencing © American College of Medical Genetics and Genomics ORIGINAL RESEARCH ARTICLE Molecular diagnosis of glycogen storage disease and disorders with overlapping clinical symptoms by massive parallel sequencing Ana I Vega, PhD1,2,3, Celia Medrano, BSc1,2,3, Rosa Navarrete, BSc1,2,3, Lourdes R Desviat, PhD1,2,3, Begoña Merinero, PhD1,2,3, Pilar Rodríguez-Pombo, PhD1,2,3, Isidro Vitoria, MD, PhD4, Magdalena Ugarte, PhD1,2,3, Celia Pérez-Cerdá, PhD1,2,3 and Belen Pérez, PhD1,2,3 Purpose: Glycogen storage disease (GSD) is an umbrella term for a Results: Pathogenic mutations were detected in 23 patients. group of genetic disorders that involve the abnormal metabolism of ­Twenty-two mutations were recognized (mostly loss-of-function glycogen; to date, 23 types of GSD have been identified. The nonspe- mutations), including 11 that were novel in GSD-associated genes. In cific clinical presentation of GSD and the lack of specific biomarkers addition, CES detected five patients with mutations in ALDOB, LIPA, mean that Sanger sequencing is now widely relied on for making a NKX2-5, CPT2, or ANO5. Although these genes are not involved in diagnosis. However, this gene-by-gene sequencing technique is both GSD, they are associated with overlapping phenotypic characteristics laborious and costly, which is a consequence of the number of genes such as hepatic, muscular, and cardiac dysfunction. to be sequenced and the large size of some genes. Conclusions: These results show that next-generation sequenc- ing, in combination with the detection of biochemical and clinical Methods: This work reports the use of massive parallel sequencing hallmarks, provides an accurate, high-throughput means of making to diagnose patients at our laboratory in Spain using either a cus- genetic diagnoses of GSD and related diseases. tomized gene panel (targeted exome sequencing) or the Illumina Genet Med advance online publication 25 February 2016 Clinical-Exome TruSight One Gene Panel (clinical exome sequenc- ing (CES)). Sequence variants were matched against biochemical and Key Words: clinical exome sequencing; glycogen storage disease; clinical hallmarks. massive parallel sequencing; targeted exome sequencing INTRODUCTION muscle- and heart-affecting GSD experience exercise intoler- The term “glycogen storage disease” (GSD) refers to a group ance, often followed by notable rhabdomyolysis.3 Interestingly, of disorders characterized by genetically determined errors of phenotypic variation is wide, and the disease may take differ- glycogen metabolism. Twenty-three types of GSD are currently ent clinical courses even though the same enzyme is involved. recognized, covering a broad clinical spectrum involving differ- Variation is also seen in the age of onset of symptoms and ent organs; however, the liver, skeletal muscle, heart, and some- morbidity and mortality; depending on the specific muta- times the central nervous system are those most commonly tion involved, the prognosis may be favorable or unfavorable. affected. They are classified depending on the organ affected Neonatal and infantile forms of GSD usually are more severe, and the enzyme deficiency involved. GSD types I, III, 0, XI, IX, whereas other forms are relatively asymptomatic or may cause VI, and IV affect the liver (80% of hepatic GSD is type I, III, only exercise intolerance. or IX 1,2), types II, IIIa, V, VII, IXd X, XII, XIII, and XIV affect Early diagnosis is important if quality of life is to be improved the muscles, and type IIA, IIb, and PRKAG2 deficiency involve and appropriate treatment is to be provided (when possible). myopathy/cardiomyopathy. Some GSD types can affect both Identifying the genetic background of patients with GSD may the liver and muscles (III and IXb).3 help in their counseling and that of their relatives. However, the The overall incidence of GSD in the population is estimated accurate classification of GSD is no easy task. Mutation screen- at 1 case per 2,000–43,000.1 Liver-affecting GSD types involve ing by conventional Sanger sequencing has been the gold stan- hepatomegaly and hypoglycemia, with the consequence of dard in this respect for many years. However, this method can poor glucose distribution throughout the body. Patients with only examine one gene at a time, exon by exon. Some clinical The first two authors and the last two authors contributed equally to this work. 1Centro de Diagnóstico de Enfermedades Moleculares, Centro de Biología ­Molecular-SO UAM-CSIC, Universidad Autónoma de Madrid, Campus de Cantoblanco, Madrid, Spain; 2Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Madrid, Spain; 3Instituto de Investigación La Paz (IdiPAZ), Madrid, Spain; 4Unidad de Nutrición y Metabolopatías, Hospital La Fe, Valencia, Spain.Correspondence: Belen Pérez ([email protected]) Submitted 23 July 2015; accepted 17 December 2015; advance online publication 25 February 2016. doi:10.1038/gim.2015.217 GEnEticS in mEdicinE | Volume 18 | Number 10 | October 2016 1037 ORIGINAL RESEARCH ARTICLE VEGA et al | Molecular diagnosis of glycogen storage disease laboratories still rely on even less reliable and time-consuming Technologies, Santa Clara, CA) of 111 genes involved in meta- assays of glycogen-processing enzymes. For some forms of bolic disorders, including 22 GSD-associated genes (AGL, GSD, these assays can be performed using enzymes from ALDOA, ENO3, G6PC, GAA, GBE1, LDHA, GYG1, GYS1, fibroblasts, erythrocytes, or lymphocytes (type IIb, II, IIIa, IV, GYS2, PFKM, PGAM2, PGM1, PHKA1, PHKA2, PHKB, or VII), but for others, liver or muscle biopsies must be per- PHKG1, PHKG2, PYGL, PYGM, SLC37A4, SLC2A2). The DNA formed. Molecular methods therefore provide the best way of samples were only examined for GSD genes or genes related to diagnosing and classifying GSD, but they need to be more rapid its pathological phenotypes. Incidental findings in genes unre- and cost-effective. lated to the clinical/biochemical phenotypes were ignored. A Fortunately, recent developments in high-throughput total of 346 GSD exons plus 50 bp of their flanking introns were sequence capture have made next-generation sequencing feasi- captured. The minimum coverage achieved was 20× for 95% of ble for use in routine genetic diagnosis.4 This very cost-effective the targeted bases; for AGL, GBE1, GYS2, and PHKA1, how- technology is particularly appropriate for screening for muta- ever, <20× coverage was achieved for 10% of the targeted bases. tions in disorders with highly heterogeneous genetic back- All the uncovered regions belonged to intronic sequences. The grounds, such as GSD, congenital disorder of glycosylation, mean depth of coverage was 440× (range: 173–921×; Table 1). lysosomal disorders, and mitochondrial disorders5–8 In addi- Each patient showed an average 1,200 sequence variants. tion, its ability to detect mutations in large genes and to identify To improve the diagnostic yield, 43 patients (including copy number variations is very advantageous. The implemen- 12 previously analyzed by TES plus 31 consecutive samples tation of massive parallel sequencing has begun to revolution- received for genetic diagnosis) were examined by CES using ize the field of genetic diagnosis. For example, for a large gene the Illumina Clinical-Exome Sequencing TruSight One Gene such as AGL, which has clear hallmarks, conventional genetic Panel. This panel includes all the known disease-associated analysis involves the amplification of 34 exons plus the corre- genes described in the OMIM database until 2013, and captures sponding contamination controls and plus subsequent bidi- 62,000 exons and their flanking intronic regions. A minimum rectional Sanger sequencing. Massive parallel sequencing, in coverage of 20× was achieved for 99% of the GSD targeted bases contrast, allows all exons to be sequenced at once, reducing (mean depth of coverage of 83.6×). An average of 8,300 variants costs and the time involved. Massive parallel sequencing tech- was identified per patient. nology generates large amounts of sequence data, and adding In both TES and CES, the libraries generated were sequenced specific sequence tags (DNA bar codes) to each sample allows using 250-bp paired-end reads using the Illumina MiSeq or for pooled testing; this further reduces costs and time require- Nextseq500 next-generation sequencing platforms. The Fastq ments, although, of course, pooling requires several patients files produced were examined using the DNAnexus platform be sequenced together with different disorders. The captured (https://platform.dnanexus.com) to allow subsequent mapping data are prioritized by matching them against patient clinical and the generation of variant calling files. These variant calling and biochemical hallmarks; without phenotype information, files were analyzed using VariantStudio Data Analysis Software genome analysis would be of limited medical value.9 (Illumina, San Diego, CA). Synonymous variants and those with This article reports the genetic analysis of a cohort of 47 patients minor allele frequencies (>1% in dbSNP) were excluded. The whose blood was sent to our laboratory for genetic diagnosis of remaining single-nucleotide variants were prioritized as follows: suspected GSD. Massive parallel sequencing—via targeted exome (i) variants in genes previously associated with the observed phe- sequencing (TES) or clinical exome sequencing (CES)—detected notype and that showed the expected pattern of inheritance; (ii) pathogenic mutations in 23 patients, 18 in previously described variants
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