medRxivGenetic & Genomic MedicinePreprint
GBA in Parkinson's disease: variant detection and pathogenicity scoring matters
Carolin GabbertiD, Susen SchaakeiD, Theresa LüthiD, Christoph Much, Christine KleiniD, Jan Olav AaslyiD, Matthew James FarreriD, Joanne TrinhiD
Abstract
BackgroundGBA variants are the strongest genetic risk factor for Parkinsons disease (PD). However, the pathogenicity of GBA variants concerning PD is still not fully understood. Additionally, the frequency of GBA variants varies widely across populations. ObjectivesTo evaluate Oxford Nanopore sequencing as a strategy, to determine the frequency of GBA variants in Norwegian PD patients and controls, and to review the current literature on newly identified variants that add to pathogenicity determination. MethodsWe included 462 Norwegian PD patients and 367 healthy controls. We sequenced the full-length GBA gene on the Oxford Nanopore GridION as an 8.9 kb amplicon. Six analysis pipelines were compared using two aligners (NGMLR, Minimap2) and three variant callers (BCFtools, Clair3, Pepper-Margin-Deepvariant). Confirmation of GBA variants was performed by Sanger sequencing and the pathogenicity of variants was evaluated. ResultsWe found 95.8% (115/120) true-positive GBA variant calls, while 4.2% (5/120) variant calls were false-positive, with the NGMLR/Minimap2-BCFtools pipeline performing best. In total, 13 rare GBA variants were detected: two were predicted to be (likely) pathogenic and eleven were of uncertain significance. The odds of carrying one of the two most common GBA variants, p.L483P or p.N409S, in PD patients were estimated to be 4.11 times the odds of carrying one of these variants in controls (OR=4.11 [1.39, 12.12]). ConclusionsIn conclusion, we have demonstrated that Oxford long-read Nanopore sequencing, along with the NGMLR/Minimap2-BCFtools pipeline is an effective tool to investigate GBA variants. Further studies on the pathogenicity of GBA variants are needed to assess their effect on PD.
- organism: human
- assay: whole-genome sequencing
- research focus: variant calling
- approach: statistical model
- Citations
- 1
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