Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies

Abstract

Background Genome-wide association studies (GWASs) in Parkinson's disease (PD) have increased the scope of biological knowledge about the disease over the past decade. We sought to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into disease etiology. Methods We performed the largest meta-GWAS of PD to date, involving the analysis of 7.8M SNPs in 37.7K cases, 18.6K UK Biobank proxy-cases (having a first degree relative with PD), and 1.4M controls. We carried out a meta-analysis of this GWAS data to nominate novel loci. We then evaluated heritable risk estimates and predictive models using this data. We also utilized large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type and biological pathway enrichments for the identified risk factors. Additionally we examined shared genetic risk between PD and other phenotypes of interest via genetic correlations followed by Mendelian randomization. Findings We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16-36% of the heritable risk of PD depending on prevalence. Integrating methylation and expression data within a Mendelian randomization framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested PD loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes, smoking status, and educational attainment. Mendelian randomization between cognitive performance and PD risk showed a robust association. Interpretation These data provide the most comprehensive understanding of the genetic architecture of PD to date by revealing many additional PD risk loci, providing a biological context for these risk factors, and demonstrating that a considerable genetic component of this disease remains unidentified. Funding See supplemental materials (Text S2). lead to earlier detection and refined diagnostics, which may help improve clinical trials (4). The generation of copious amounts of public summary statistics created by this effort relating to both the GWAS and subsequent analyses of gene expression and methylation patterns may be of use to investigators planning follow-up functional studies in stem cells or other cellular screens, allowing them to prioritize targets more efficiently using our data as additional evidence. We hope our findings may have some downstream clinical impact in the future such as improved patient stratification for clinical trials and genetically informed drug targets.

17q21.31 sub-haplotypes underlying H1-associated risk for Parkinson’s disease are associated with LRRC37A/2 expression in astrocytes

“…When Stage 1 and Stage 2 data were pooled together, the H1c tag SNP rs242557 became the top SNP with a strengthened association p-value compared to Stage 1 data alone (p = 2.57x10 -13 , OR 1.39 (95% CI 1.28-1.51)) ( Fig 1B, SI Fig 2, SI Table 2). H1 homozygote 17q21.31 locus LD patterns are altered in PSP compared to controls 7 In both Stage 1 and Stage 2 data, as well as in the merged dataset, we observed a striking loss of LD in PSP cases in the region of 17q21. 31 where we see the genetic association ( Fig 1C, SI Fig 3), consistent with our finding that variation in this region is contributing to PSP risk.…”

MIDN locus structural variants and Parkinson's Disease risk

“…Consequently, we did not identify an association with risk of PD at this locus based on common SNP variants ( Fig. S1) 3 . In addition, we analyzed whole genome sequencing data (WGS) from eight cohorts totaling 3868 individuals (2742 PD cases and 1126 controls of European ancestry).…”

Parkinson’s disease determinants, prediction and gene-environment interactions in the UK Biobank

“…Over the last decade, large genome-wide association studies (GWAS) of sporadic PD have extended our understanding of the genetic architecture of PD to include 90 independent signals, which collectively explain ~22% of overall PD liability 4 .…”