GBA Analysis in Next-Generation Era: Pitfalls, Challenges, and Possible Solutions

Area of Science:

• Genetics
• Molecular Biology
• Neurology

Background:

• Mutations in the acid β-glucosidase (GBA) gene cause Gaucher disease and are a primary genetic risk factor for Parkinson disease.
• Next-generation sequencing (NGS) is widely used for GBA gene analysis, but faces challenges due to a highly homologous pseudogene (GBAP1).
• Complex gene-pseudogene rearrangements can lead to misdetection of GBA mutations during NGS analysis.

Purpose of the Study:

• To validate a strategy for accurate GBA mutation identification using parallel massive sequencing.
• To provide an overview of challenges and solutions for GBA analysis via NGS.
• To develop a robust NGS workflow for detecting GBA alleles.

Main Methods:

• Implementation of a novel NGS workflow for GBA mutation analysis.
• Validation using a cohort of 38 Gaucher disease patients with known GBA alleles.
• Application of specific library preparation and data analysis procedures to mitigate pseudogene interference.

Main Results:

• The NGS workflow demonstrated robust performance, achieving 97% sensitivity and 100% specificity.
• Despite pseudogene interference, specific procedures ensured maximal repeatability and reproducibility.
• The strategy effectively addressed the challenges posed by GBA-GBAP1 rearrangements.

Conclusions:

• The described NGS pipeline offers a reliable approach for sequencing the GBA gene.
• This method enhances the accuracy of GBA mutation detection, crucial for Gaucher and Parkinson disease research.
• The validated strategy overcomes significant technical hurdles in GBA genetic analysis using NGS.