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. Author manuscript; available in PMC: 2019 Feb 19.
Published in final edited form as: Mov Disord. 2018 Oct 9;33(11):1821–1823. doi: 10.1002/mds.103

Coding Variation in GBA Explains the Majority of the SYT11-GBA Parkinson’s Disease GWAS Locus

Cornelis Blauwendraat 1, Jose M Bras 2, Mike A Nalls 2,3, Patrick A Lewis 4,5, Dena G Hernandez 1, Andrew B Singleton 1,*; International Parkinson’s Disease Genomics Consortium
PMCID: PMC6379910  NIHMSID: NIHMS1001164  PMID: 30302829

A landmark discovery in the genetics of Parkinson’s disease (PD) was the determination that mutations in the gene encoding glucocerebrosidase (GBA) convey risk for PD and dementia with Lewy bodies.1,2 Mutations in GBA are also causing the autosomal-recessive disorder Gaucher’s disease (GD). GD is a lysosomal storage disorder that presents with a variety of features, including parkinsonism. Although it has been clear that some GD-causing GBA mutations such as p.N409S are risk factors for PD, there has been some controversy regarding GBA mutations that do not cause GD and the risk for PD. Resolving this issue and the effect of such mutations on, for example, glucocerebrosidase activity will have important implications for our understanding of the pathobiology of PD.

We present here a large genetic assessment of GBA using NeuroX genotyping of 6249 PD cases and 6032 controls.3 In total, we detected 11 GBA coding variants. No large deletions or duplications at the GBA locus were identified. As expected p.N409S and p.E365K were enriched in cases compared with controls (Table 1). Unfortunately, another relatively common disease associated, L483P, could not be genotyped.1 Interestingly, variant p.T408M, reported as uncertain pathological significance, was also significantly overrepresented in cases. In total, the majority of identified GBA variants were more common in cases compared with controls, the exception being p.K13R, which is also reported as benign (Table 1). Although some individuals were carrying multiple GBA mutations, no high linkage disequilibrium patterns were identified between coding variants (Supplementary Results).

Table 1.

GBA variant frequencies in cases and controls

Amino acid GRCh38 (bp) rs Number Clinvar HGMD pathogenicity Cases
Controls
ExAC (EUR)
M/M M/W W/W MAF M/M M/W W/W MAF M/M MAF OR P
K13R (K-27R) 155240707 rs150466109 Benign DM? 0 0 6249 0 0 2 6030 0.00017 0 0.00021 NA 0.999
C62Y (C23Y) 155240008 rs145888253 na na 0 1 6248 0.00008 0 0 6032 0 0 0.00001 NA 1
E150K (E111K) 155239622 none na DM? 0 1 6248 0.00008 0 0 6031 0 0 0 NA 0.9993
F255Y (F216Y) 155237576 rs74500255 Likely Pathogenic 0 2 6247 0.00016 0 1 6031 0.00008 0 0 NA 0.5827
F298L (F259L) 155237446 none na pathogenic 0 1 6248 0.00008 0 0 5990 0 0 0 NA 0.9993
A348V (A309V) 155236426 rs78396650 Pathogenic Pathogenic 0 5 6244 0.00040 0 0 6032 0 0 0 NA 0.9984
E365K (E326K) 155236376 rs2230288 Conflicting interpretations DM? 4 256 5989 0.02158 0 121 5911 0.01013 7 0.01196 2.037 1.64E-09
T408M (T369M) 155236246 rs75548401 Conflicting interpretations DM? 2 169 6078 0.01404 0 107 5925 0.00895 5 0.00976 1.53 0.001188
N409S (N370S) 155235843 rs76763715 Likely pathogenic Pathogenic 0 87 6161 0.00701 0 41 5991 0.00341 1 0.00363 1.882 0.002014
D419N/Y 155235814 none na Pathogenic 0 2 6247 0.00016 0 0 6032 0 0 0 NA 0.9991
(D380N/Y) E427K (E388K) 155235790 rs149171124 Uncertain significance DM? 0 10 6239 0.00080 0 5 6027 0.00041 0 0.00031 NA 0.2157
na 155390201 rs71628662 na na 1 187 6059 0.01513 0 88 5935 0.007305 na na 2.07 1.324E-07
na 154925709 rs114138760 na na 1 166 6082 0.01344 0 107 5925 0.008869 na na 1.52 0.0001853

Indicated are uncorrected P values (Bonferroni correction for 0.05 lies at > 0.0045) and odds ratios. Tests were carried out in plink using logistic regression with covariates age, sex, first 20 principal components based on genome-wide genotype data, and sample provenance.

Na, not applicable; bp, base pair; W, wild type; M, mutant; MAF, minor allele frequency; EUR, European; ExAC, Exorne Aggregation Consortium (http://exac.broadinstitute.org/); OR, odds ratio; HGMD, Human Gene Mutation Database.

In previous PD genome-wide association studies (GWAS), a locus approximately 150 kb from GBA was implicated as a risk factor for PD (nominated as SYT11-GBA).4 Analysis of the non-coding variant rs71628662, previously implicated, revealed a strong association for disease (Table 1). Previous analyses suggested that this was independent of known GD-causing mutations, and the mechanism of action at this locus was therefore unclear. Conditioned analysis of rs71628662 on each of the identified coding variants revealed that the association at p. E365K completely accounted for the previously identified GWAS signal (conditional p.E365K rs71628662, P = 0.6234). Within the current data set, the linkage disequilibrium between p.E365K and rs7168662 is very high (D′ = 0.987, r2 = 0.84).

Previously, another noncoding variant (rs114138760) was also identified as an independent signal.5 In the NeuroX data set, this variant also showed association with disease (P = 0.0001853) and remained significant following adjustment for the primary GWAS variant (P = 0.0001511). In addition, this signal also remained significant following adjustment for p.E365K, p.N409S, and p.T408M (P > 0.007146), and of the 15 rs114138760 risk variant carriers, none carry p.L483P.

In summary, this work affirms that functional alleles within GBA (p.E365K and p.T408M) that are insufficient to cause GD variants are robustly associated with PD. Further, we have shown that a previously reported GWAS signal at this locus can be largely explained by protein coding variability within GBA. These data are consistent with p.E365K being the functional effector allele underlying the original GWA locus (GBA-SYT11 locus), as suggested previously.6 The results from this current study suggest that efforts directed at replacing or augmenting glucocerebrosidase activity already under way for PD may have wider-ranging applicability than just for individuals with GD-associated mutations in glucocerebrosidase.

Supplementary Material

Supplemental Data

Acknowledgments

Funding agencies: This work was supported in part by the Intramural Research Programs of the National Institute of Neurological Disorders and Stroke (NINDS), the National Institute on Aging (NIA) both part of the National Institutes of Health, Department of Health and Human Services; project numbers 1ZIA-NS003154andZ01-AG000949–02.

Footnotes

Relevant conflicts of interest/financial disclosures: Drs. Nalls, Blauwendraat, Lewis, Hernandez, Bras, and Singleton have nothing to disclose.

Supporting Data

Additional Supporting Information may be found in the online version of this article at the publisher’s website.

References

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