Screening for potential undiagnosed Gaucher disease patients: Utilisation of the Gaucher earlier diagnosis consensus point-scoring system (GED-C PSS) in conjunction with electronic health record data, tissue specimens, and small nucleotide polymorphism (SNP) genotype data available in Finnish biobanks

Mol Genet Metab Rep. 2022 Aug 27;33:100911. doi: 10.1016/j.ymgmr.2022.100911.

PMID: 36092251

Minja Pehrsson, Hanna Heikkinen, Ulla Wartiovaara-Kautto

Highlights: These findings imply that the prevalence of diagnosed patients (~1:325,000) may indeed correspond the true prevalence of Gaucher disease (GD) in Finland.

Abstract

Background: In many nations, autosomal recessive Gaucher disease (GD) is probably underdiagnosed. It was assumed that there may be undiagnosed GD patients in Finland because the number of identified GD patients there is quite low, and the true frequency is still unknown. The earlier research established the usefulness of the Finnish Biobank data and specimens as well as the Gaucher Earlier Diagnosis Consensus point-scoring system (GED-C PSS; Mehta et al., 2019) for the automated point scoring of large populations. An indicative point-score range for Finnish GD patients was identified; however, undiagnosed patients could not be located, in part because of the high proportion of high-score participants and the dearth of diagnostically useful samples in the evaluated biobank population. The current study expanded the screening to a different biobank and assessed the viability of using the automated GED-C PSS in conjunction with small nucleotide polymorphism (SNP) chip genotype data from the FinnGen study of biobank sample donors to identify undiagnosed GD patients in Finland. Also, the viability of FFPE tissues and DNA restoration in the GBA gene's next-generation sequencing (NGS) were examined.

Methods: Finnish GD patients with prior diagnoses who were eligible for the study and up to 45,100 sample donors in the Helsinki Biobank (HBB) were point scored. The GED-C point scoring was automated and locally adjusted, with some manual verification for GD patients. Visual analysis was done on the SNP chip genotyping data for uncommon GBA variations. FFPE tissues from GD patients were obtained from the Northern Finland-based HBB and Biobank Borealis (BB).

Results: One patient who had previously had treatment for GD-related symptoms and three patients with a history of GD diagnosis were included. For the patient who was being treated for GD-related symptoms, a genetic diagnosis was verified. In the current study, the GED-C point score for the GD patients ranged from 12.5-22.5. Hence, each of the eight Finnish GD patients in the prior and present studies received a score of 6-22.5 points. The HBB subpopulation (N ≈ 45,100) had automatic point scoring, and the overall scores varied from 0 to 17.5, with 0.77% (346/45,100) of the individuals having ≥10 points. The SNP chip genotype data analysis was able to locate the diagnosed GD patients, but it could not find any probable undiagnosed patients with the GED-C score and/or the GBA genotype suggestive of GD. Pathogenic GBA variants were confirmed in five out of six unrestored and in all four restored FFPE DNA samples, which increased the quality of the GBA NGS.

Discussion: The results of this study suggest that the prevalence of people with GD who have been diagnosed (~1:325,000) may actually match to the true prevalence of GD in Finland. If the genotyping pipeline is adjusted for rare variations, the SNP chip genotype data is a useful tool that complements the screening with the GED-C PSS. Several uncommon genetic illnesses can be addressed using these proof-of-concept biobank techniques.

Keywords: BB, Biobank Borealis of Northern Finlan, Biobank study, DF4/DF5, Data freeze 4/5, EHR, Electronic health record