Category: Parkinson's Disease: Genetics
Objective: We aim to implement a new cost-effective and reliable next-generation-sequencing-based technology to test GBA1 gene in Parkinson disease (PD) patients.
Background: Heterozygous variants in the GBA1 gene, encoding for the lysosomal enzyme β-glucocerebrosidase, are the most common genetic risk factor for PD, accounting for 5-15% of all PD cases. Sequencing of the whole GBA1 coding region (11 exons) is a burdensome task, both employing conventional techniques such as Sanger sequencing as well as more innovative strategies such as next-generation-sequencing (NGS). In particular, the high degree of homology (96-98%) between GBA1 and its pseudogene GBAP1 often leads to recombination events that eventually produce complex alleles which are misaligned and missed by the standard NGS pipeline.
Method: The NGS experiment was designed to start from a specific long-range PCR which amplifies a unique 7kb amplicon encompassing the GBA1 gene and excluding GBAP1. This was used as a template to create NGS libraries, which were amplified using Nextera technology and then run on an Illumina MiSeq instrument. A tailored bioinformatic pipeline was used, masking GBAP1 pseudogene on the reference sequence and forcing the alignment of sequencing reads against the GBA1 gene only. Positive and negative controls were also included in the analyses (n=500 PD patients already tested).
Results: The mean coverage depth of sequencing was ~500X. In positive controls, all known GBA1 variants were correctly called and identified using this approach. No false positives were identified in negative controls. In several PD patients resulting GBA1-negative with conventional strategies (Sanger sequencing and standard NGS approach) this novel method identified previously missed GBA1 pathogenic variants, particularly those originating from the pseudogene.
Conclusion: The proposed NGS-based approach appears to be a cost-effective and reliable alternative for GBA1 sequencing, holding promise to increase speed analysis and variant detection rate compared to conventional strategies.
To cite this abstract in AMA style:E. Monfrini, I. Palmieri, G. Cuconato, M. Percetti, P. Cortelli, A. Di Fonzo, EM. Valente. A newly implemented NGS-based method to detect GBA1 variants in patients with Parkinson’s disease [abstract]. Mov Disord. 2023; 38 (suppl 1). https://www.mdsabstracts.org/abstract/a-newly-implemented-ngs-based-method-to-detect-gba1-variants-in-patients-with-parkinsons-disease/. Accessed September 27, 2023.
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MDS Abstracts - https://www.mdsabstracts.org/abstract/a-newly-implemented-ngs-based-method-to-detect-gba1-variants-in-patients-with-parkinsons-disease/