Our objective was to design a genotyping platform that would allow rapid genetic characterization of samples in the context of genetic mutations and risk factors associated with common neurodegenerative diseases. The platform needed to be relatively affordable, rapid to deploy, and use a common and accessible technology. Central to this project, we wanted to make the content of the platform open to any investigator without restriction. In designing this array we prioritized a number of types of genetic variability for inclusion, such as known risk alleles, disease-causing mutations, putative risk alleles, and other functionally important variants. The array was primarily designed to allow rapid screening of samples for disease-causing mutations and large population studies of risk factors. Notably, an explicit aim was to make this array widely available to facilitate data sharing across and within diseases. The resulting array, NeuroX, is a remarkably cost and time effective solution for high-quality genotyping. NeuroX comprises a backbone of standard Illumina exome content of approximately 240,000 variants, and over 24,000 custom content variants focusing on neurologic diseases. Data are generated at approximately $50-$60 per sample using a 12-sample format chip and regular Infinium infrastructure; thus, genotyping is rapid and accessible to many investigators. Here, we describe the design of NeuroX, discuss the utility of NeuroX in the analyses of rare and common risk variants, and present quality control metrics and a brief primer for the analysis of NeuroX derived data.

We conducted a meta-analysis of Parkinson's disease genome-wide association studies using a common set of 7,893,274 variants across 13,708 cases and 95,282 controls. Twenty-six loci were identified as having genome-wide significant association; these and 6 additional previously reported loci were then tested in an independent set of 5,353 cases and 5,551 controls. Of the 32 tested SNPs, 24 replicated, including 6 newly identified loci. Conditional analyses within loci showed that four loci, including GBA, GAK-DGKQ, SNCA and the HLA region, contain a secondary independent risk variant. In total, we identified and replicated 28 independent risk variants for Parkinson's disease across 24 loci. Although the effect of each individual locus was small, risk profile analysis showed substantial cumulative risk in a comparison of the highest and lowest quintiles of genetic risk (odds ratio (OR) = 3.31, 95% confidence interval (CI) = 2.55-4.30; P = 2 × 10(-16)). We also show six risk loci associated with proximal gene expression or DNA methylation.

Objective

The aim of this study was to search for genes/variants that modify the effect of LRRK2 mutations in terms of penetrance and age-at-onset of Parkinson's disease.

Methods

We performed the first genomewide association study of penetrance and age-at-onset of Parkinson's disease in LRRK2 mutation carriers (776 cases and 1,103 non-cases at their last evaluation). Cox proportional hazard models and linear mixed models were used to identify modifiers of penetrance and age-at-onset of LRRK2 mutations, respectively. We also investigated whether a polygenic risk score derived from a published genomewide association study of Parkinson's disease was able to explain variability in penetrance and age-at-onset in LRRK2 mutation carriers.

Results

A variant located in the intronic region of CORO1C on chromosome 12 (rs77395454; p value = 2.5E-08, beta = 1.27, SE = 0.23, risk allele: C) met genomewide significance for the penetrance model. Co-immunoprecipitation analyses of LRRK2 and CORO1C supported an interaction between these 2 proteins. A region on chromosome 3, within a previously reported linkage peak for Parkinson's disease susceptibility, showed suggestive associations in both models (penetrance top variant: p value = 1.1E-07; age-at-onset top variant: p value = 9.3E-07). A polygenic risk score derived from publicly available Parkinson's disease summary statistics was a significant predictor of penetrance, but not of age-at-onset.

Interpretation

This study suggests that variants within or near CORO1C may modify the penetrance of LRRK2 mutations. In addition, common Parkinson's disease associated variants collectively increase the penetrance of LRRK2 mutations. ANN NEUROL 2021;90:82-94.

Objective

To identify genetic variants that play a role in the pathogenesis of multiple system atrophy (MSA), we undertook a genome-wide association study (GWAS).

Methods

We performed a GWAS with >5 million genotyped and imputed single nucleotide polymorphisms (SNPs) in 918 patients with MSA of European ancestry and 3,864 controls. MSA cases were collected from North American and European centers, one third of which were neuropathologically confirmed.

Results

We found no significant loci after stringent multiple testing correction. A number of regions emerged as potentially interesting for follow-up at p < 1 × 10^-6, including SNPs in the genes FBXO47, ELOVL7, EDN1, and MAPT. Contrary to previous reports, we found no association of the genes SNCA and COQ2 with MSA.

Conclusions

We present a GWAS in MSA. We have identified several potentially interesting gene loci, including the MAPT locus, whose significance will have to be evaluated in a larger sample set. Common genetic variation in SNCA and COQ2 does not seem to be associated with MSA. In the future, additional samples of well-characterized patients with MSA will need to be collected to perform a larger MSA GWAS, but this initial study forms the basis for these next steps.

Background

PD is a complex polygenic disorder. In recent years, several genes from the endocytic membrane-trafficking pathway have been suggested to contribute to disease etiology. However, a systematic analysis of pathway-specific genetic risk factors is yet to be performed.

Objectives

To comprehensively study the role of the endocytic membrane-trafficking pathway in the risk of PD.

Methods

Linkage disequilibrium score regression was used to estimate PD heritability explained by 252 genes involved in the endocytic membrane-trafficking pathway including genome-wide association studies data from 18,869 cases and 22,452 controls. We used pathway-specific single-nucleotide polymorphisms to construct a polygenic risk score reflecting the cumulative risk of common variants. To prioritize genes for follow-up functional studies, summary-data based Mendelian randomization analyses were applied to explore possible functional genomic associations with expression or methylation quantitative trait loci.

Results

The heritability estimate attributed to endocytic membrane-trafficking pathway was 3.58% (standard error = 1.17). Excluding previously nominated PD endocytic membrane-trafficking pathway genes, the missing heritability was 2.21% (standard error = 0.42). Random heritability simulations were estimated to be 1.44% (standard deviation = 0.54), indicating that the unbiased total heritability explained by the endocytic membrane-trafficking pathway was 2.14%. Polygenic risk score based on endocytic membrane-trafficking pathway showed a 1.25 times increase of PD risk per standard deviation of genetic risk. Finally, Mendelian randomization identified 11 endocytic membrane-trafficking pathway genes showing functional consequence associated to PD risk.

Conclusions

We provide compelling genetic evidence that the endocytic membrane-trafficking pathway plays a relevant role in disease etiology. Further research on this pathway is warranted given that critical effort should be made to identify potential avenues within this biological process suitable for therapeutic interventions. © 2019 International Parkinson and Movement Disorder Society.

The genetic basis of Lewy body dementia (LBD) is not well understood. Here, we performed whole-genome sequencing in large cohorts of LBD cases and neurologically healthy controls to study the genetic architecture of this understudied form of dementia, and to generate a resource for the scientific community. Genome-wide association analysis identified five independent risk loci, whereas genome-wide gene-aggregation tests implicated mutations in the gene GBA. Genetic risk scores demonstrate that LBD shares risk profiles and pathways with Alzheimer's disease and Parkinson's disease, providing a deeper molecular understanding of the complex genetic architecture of this age-related neurodegenerative condition.

Background

Genome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease.

Methods

We did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used 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 Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation.

Findings

Between Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. 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 Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10^-7).

Interpretation

These data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data.

Funding

The National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources).