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. 2011 Aug 3:12:104.
doi: 10.1186/1471-2350-12-104.

Genome-wide association study identifies candidate genes for Parkinson's disease in an Ashkenazi Jewish population

Xinmin Liu  1 , Rong Cheng, Miguel Verbitsky, Sergey Kisselev, Andrew Browne, Helen Mejia-Sanatana, Elan D Louis, Lucien J Cote, Howard Andrews, Cheryl Waters, Blair Ford, Steven Frucht, Stanley Fahn, Karen Marder, Lorraine N Clark, Joseph H Lee
Affiliations

Genome-wide association study identifies candidate genes for Parkinson's disease in an Ashkenazi Jewish population

Xinmin Liu et al. BMC Med Genet. .

Abstract

Background: To date, nine Parkinson disease (PD) genome-wide association studies in North American, European and Asian populations have been published. The majority of studies have confirmed the association of the previously identified genetic risk factors, SNCA and MAPT, and two studies have identified three new PD susceptibility loci/genes (PARK16, BST1 and HLA-DRB5). In a recent meta-analysis of datasets from five of the published PD GWAS an additional 6 novel candidate genes (SYT11, ACMSD, STK39, MCCC1/LAMP3, GAK and CCDC62/HIP1R) were identified. Collectively the associations identified in these GWAS account for only a small proportion of the estimated total heritability of PD suggesting that an 'unknown' component of the genetic architecture of PD remains to be identified.

Methods: We applied a GWAS approach to a relatively homogeneous Ashkenazi Jewish (AJ) population from New York to search for both 'rare' and 'common' genetic variants that confer risk of PD by examining any SNPs with allele frequencies exceeding 2%. We have focused on a genetic isolate, the AJ population, as a discovery dataset since this cohort has a higher sharing of genetic background and historically experienced a significant bottleneck. We also conducted a replication study using two publicly available datasets from dbGaP. The joint analysis dataset had a combined sample size of 2,050 cases and 1,836 controls.

Results: We identified the top 57 SNPs showing the strongest evidence of association in the AJ dataset (p < 9.9 × 10(-5)). Six SNPs located within gene regions had positive signals in at least one other independent dbGaP dataset: LOC100505836 (Chr3p24), LOC153328/SLC25A48 (Chr5q31.1), UNC13B (9p13.3), SLCO3A1(15q26.1), WNT3(17q21.3) and NSF (17q21.3). We also replicated published associations for the gene regions SNCA (Chr4q21; rs3775442, p = 0.037), PARK16 (Chr1q32.1; rs823114 (NUCKS1), p = 6.12 × 10(-4)), BST1 (Chr4p15; rs12502586, p = 0.027), STK39 (Chr2q24.3; rs3754775, p = 0.005), and LAMP3 (Chr3; rs12493050, p = 0.005) in addition to the two most common PD susceptibility genes in the AJ population LRRK2 (Chr12q12; rs34637584, p = 1.56 × 10(-4)) and GBA (Chr1q21; rs2990245, p = 0.015).

Conclusions: We have demonstrated the utility of the AJ dataset in PD candidate gene and SNP discovery both by replication in dbGaP datasets with a larger sample size and by replicating association of previously identified PD susceptibility genes. Our GWAS study has identified candidate gene regions for PD that are implicated in neuronal signalling and the dopamine pathway.

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Figures

Figure 1
Figure 1
Quantile-Quantile plots for test statistics for SNPs passing quality control in each dataset. Figure shows -log10 (p-value) of observed association statistics in Y-axis, compared to -log10 (p-value) of the association statistics expected under the null hypothesis of no association in X-axis. The solid line represents concordance of observed and expected values. The genomic inflation factor, λ, is shown for each dataset. A) Ashkenazi Jewish (λ = 1.003), b) NINDS (λ = 1.026), and c) CIDR/Pankratz et al 2009(λ = 1.031).
Figure 2
Figure 2
Manhattan plot for results of GWAS. a) Ashkenazi Jewish, b) NINDS and c) CIDR/Pankratz et al 2009. Manhattan plot of GWAS results of testing for association with PD. Horizontal axis is the genomic position, and vertical axis is -log10 (p-value) in 3 datasets. Blue line indicates the threshold of genome-wide significance level (Ashkenazi Jewish, p = 9.5×10-8; NINDS, p = 9.7×10-8; CIDR/Pankratz et al 2009, p = 1.5×10-7).
Figure 3
Figure 3
Regional Association Plots for SNPs significant in the association analysis in the Ashkenazi Jewish dataset a) NSF and WNT3, b) LOC153228/SLC25A48, c) UNC13B, d) SLCO3A1. It shows -log10 (p-value) from association analysis for all SNPs in the region around the top SNP (surrounding 1000 kb total). X-axis shows position of the SNPs along chromosome; Y-axis gives -log10(p-value). P-values were obtained from GWAS in each dataset. Y-axis in the right shows recombination rate (cM/Mb). r2 shows measure of the LD between this SNP and target SNP.
Figure 4
Figure 4
Single point and haplotype analysis of MAPT-NSF region in a) Ashkenazi Jewish, b) NINDS and c) CIDR/Pankratz et al 2009 datasets. 2-SNP sliding window analysis the strongest p-value was present from the exhaustive search.
Figure 5
Figure 5
Association and haplotype analysis of GBA mutation (GBA N370S) and flanking SNPs in 3 datasets. a) Single point analysis plus 2 haplotype analyses: with vs. without the mutation in Ashkenazi Jewish. b) Single and haplotype analyses without mutation in NINDS. c) Single and haplotype analyses without mutation in CIDR/Pankratz et al 2009. 2-SNP sliding window, the strongest p-value was present from the exhaustive search.
Figure 6
Figure 6
Single point and haplotype analysis of PARK16 in Ashkenazi Jewish a), NINDS b) and CIDR/Pankratz et al 2009 c) datasets. 2-SNP sliding window, the strongest p-value was present from the exhaustive search.
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