Detection of genomic rearrangements from targeted resequencing data in Parkinson's disease patients

Spataro, Nino; Roca-Umbert, Ana; Cervera-Carles, Laura; Vallès, Mònica; Anglada, Roger; Pagonabarraga, Javier; Pascual-Sedano, Berta; Campolongo, Antònia; Kulisevsky, Jaime; Casals, Ferrán; Clarimón, Jordi; Bosch, Elena

doi:10.1002/mds.26845

Cited by 24 publications

(22 citation statements)

References 18 publications

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“…We were unable to detect any structural variants (SVs) (variations >50bp), despite previous studies reporting such variants in PD patients [3,24]. The latter study reported four individuals presenting copy-number variants (CNVs) along the GBA-GBAP1 region in a sporadic PD-cohort.…”

Section: Discussioncontrasting

confidence: 64%

Nanopore sequencing of the glucocerebrosidase (GBA) gene in a New Zealand Parkinson’s disease cohort

Graham

Pitcher

Liau

et al. 2019

Preprint

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Highlights:-Validated nanopore sequencing of the GBA gene for mutation detection.-9.2% of patients from a New Zealand Parkinson's disease cohort carry GBA mutations.-Significantly higher prevalence of dementia in patients carrying GBA mutations -Three novel mutations were detected including a putative splicing variant.-Single molecule reads of GBA amplicons revealed 74 different GBA haplotypes. Abstract Introduction:Mutations in the gene for glucocerebrosidase (GBA) cause Gaucher disease, an autosomal recessive lysosomal storage disorder. GBA mutation carriers have an elevated risk of Parkinson's disease (PD) compared with non-carriers and can experience a more aggressive disease. GBA analysis is technically challenging due to a related pseudogene and structural variations (SVs) that can occur at this locus. We have applied a recently developed nanopore sequencing method to analyze GBA variants in a clinically assessed New Zealand longitudinal cohort of PD. Method:We examined amplicons encompassing the coding region of GBA (8.9kb) from 229 PD cases using the GridION nanopore-sequencing platform. Mutations were Sanger validated. Results:We detected 23 mutations in 21 PD cases (9.2% of patients). We detected a strong PD risk allele p.N409S (rs76763715) in one case. Modest risk mutations included p.E365K (rs2230288) in 12 cases, and p.T408M (rs75548401) in seven cases, one of whom also had p.E365K. We additionally detected the possible risk alleles R78C (rs146774384) in one case, D179H (rs147138516) in one case which occurred on the same haplotype as an E365K allele, and one novel mutation p.L335=, that is predicted to impact splicing of GBA transcripts.Additionally, we found a higher prevalence of dementia among GBA mutation carriers. Conclusion:This work confirmed the utility of nanopore sequencing as a high-throughput method to identify known and novel GBA mutations, and to assign precise haplotypes. This work may contribute to understanding the effects of these mutations on disease pathogenesis, and to the development of more targeted treatments.

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Section: Discussioncontrasting

confidence: 64%

Nanopore sequencing of the glucocerebrosidase (GBA) gene in a New Zealand Parkinson’s disease cohort

Graham

Pitcher

Liau

et al. 2019

Preprint

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“…Among them, microdroplet-based PCR has been used for enrichment of a desired genomic region 60 and copy number variant detection has been used as an indicator of structural variants, such as large rearrangements. 38 In the specific case of the GBA gene, the presence of mutations originated from recombination events between the gene and the pseudogene, further complicating the analysis and leading to falsenegative results.…”

Section: Discussionmentioning

confidence: 99%

GBA Analysis in Next-Generation Era

Zampieri

Cattarossi

Bembi

et al. 2017

The Journal of Molecular Diagnostics

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Mutations in the gene encoding the lysosomal enzyme acid β-glucosidase (GBA) are responsible for Gaucher disease and represent the main genetic risk factor for developing Parkinson disease. In past years, next-generation sequencing (NGS) technology has been applied for the molecular analysis of the GBA gene, both as a single gene or as part of gene panels. However, the presence of complex gene-pseudogene rearrangements, resulting from the presence of a highly homologous pseudogene (GBAP1) located downstream of the GBA gene, makes NGS analysis of GBA challenging. Therefore, adequate strategies should be adopted to avoid misdetection of GBA recombinant mutations. Here, we validated a strategy for the identification of GBA mutations using parallel massive sequencing and provide an overview of the major drawbacks encountered during GBA analysis by NGS. We implemented a NGS workflow, using a set of 38 patients with Gaucher disease carrying different GBA alleles identified previously by Sanger sequencing. As expected, the presence of the pseudogene significantly affected data output. However, the combination of specific procedures for the library preparation and data analysis resulted in maximal repeatability and reproducibility, and a robust performance with 97% sensitivity and 100% specificity. In conclusion, the pipeline described here represents a useful approach to deal with GBA sequencing using NGS technology.

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“…The eXome hidden Markov model (XHMM) is one of several algorithms developed for the detection of CNVs through NGS data (Fromer & Purcell, 2014;Fromer et al, 2012). XHMM has identified (potential) causative CNVs in, for example, patients with Parkinson's disease, autism spectrum disorders, and rare diseases like Joubert syndrome and very early onset inflammatory bowel disease (Kelsen et al, 2015;Koyama et al, 2017;Poultney et al, 2013;Spataro et al, 2017). The aim of this study was to assess both the diagnostic yield of our panel of H-TAD-associated genes and the prevalence of CNVs in these genes.…”

Section: Introductionmentioning

confidence: 99%

Results of next-generation sequencing gene panel diagnostics including copy-number variation analysis in 810 patients suspected of heritable thoracic aortic disorders

et al. 2018

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Simultaneous analysis of multiple genes using next‐generation sequencing (NGS) technology has become widely available. Copy‐number variations (CNVs) in disease‐associated genes have emerged as a cause for several hereditary disorders. CNVs are, however, not routinely detected using NGS analysis. The aim of this study was to assess the diagnostic yield and the prevalence of CNVs using our panel of Hereditary Thoracic Aortic Disease (H‐TAD)‐associated genes. Eight hundred ten patients suspected of H‐TAD were analyzed by targeted NGS analysis of 21 H‐TAD associated genes. In addition, the eXome hidden Markov model (XHMM; an algorithm to identify CNVs in targeted NGS data) was used to detect CNVs in these genes. A pathogenic or likely pathogenic variant was found in 66 of 810 patients (8.1%). Of these 66 pathogenic or likely pathogenic variants, six (9.1%) were CNVs not detectable by routine NGS analysis. These CNVs were four intragenic (multi‐)exon deletions in MYLK, TGFB2, SMAD3, and PRKG1, respectively. In addition, a large duplication including NOTCH1 and a large deletion encompassing SCARF2 were detected. As confirmed by additional analyses, both CNVs indicated larger chromosomal abnormalities, which could explain the phenotype in both patients. Given the clinical relevance of the identification of a genetic cause, CNV analysis using a method such as XHMM should be incorporated into the clinical diagnostic care for H‐TAD patients.

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Detection of genomic rearrangements from targeted resequencing data in Parkinson's disease patients

Cited by 24 publications

References 18 publications

Nanopore sequencing of the glucocerebrosidase (GBA) gene in a New Zealand Parkinson’s disease cohort

Nanopore sequencing of the glucocerebrosidase (GBA) gene in a New Zealand Parkinson’s disease cohort

GBA Analysis in Next-Generation Era

Results of next-generation sequencing gene panel diagnostics including copy-number variation analysis in 810 patients suspected of heritable thoracic aortic disorders

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