Comprehensive Research Synopsis and Systematic Meta-Analyses in Parkinson's Disease Genetics: The PDGene Database

Abstract

More than 800 published genetic association studies have implicated dozens of potential risk loci in Parkinson's disease (PD). To facilitate the interpretation of these findings, we have created a dedicated online resource, PDGene, that comprehensively collects and meta-analyzes all published studies in the field. A systematic literature screen of ∼27,000 articles yielded 828 eligible articles from which relevant data were extracted. In addition, individual-level data from three publicly available genome-wide association studies (GWAS) were obtained and subjected to genotype imputation and analysis. Overall, we performed meta-analyses on more than seven million polymorphisms originating either from GWAS datasets and/or from smaller scale PD association studies. Meta-analyses on 147 SNPs were supplemented by unpublished GWAS data from up to 16,452 PD cases and 48,810 controls. Eleven loci showed genome-wide significant (P<5×10−8) association with disease risk: BST1, CCDC62/HIP1R, DGKQ/GAK, GBA, LRRK2, MAPT, MCCC1/LAMP3, PARK16, SNCA, STK39, and SYT11/RAB25. In addition, we identified novel evidence for genome-wide significant association with a polymorphism in ITGA8 (rs7077361, OR 0.88, P = 1.3×10−8). All meta-analysis results are freely available on a dedicated online database (www.pdgene.org), which is cross-linked with a customized track on the UCSC Genome Browser. Our study provides an exhaustive and up-to-date summary of the status of PD genetics research that can be readily scaled to include the results of future large-scale genetics projects, including next-generation sequencing studies.

From the Cover: Alterations in Optineurin Expression and Localization in Pre-clinical Parkinson’s Disease Models

“…Further, metaanalysis of genome-wide association studies shows that single nucleotide polymorphisms in OPTN may increase PD risk. Specifically, the M98K mutation, which likely affects OPTNmediated autophagy, causes glaucoma and was identified as a PD risk modulator (Lill et al, 2012;Sirohi et al, 2015). Thus, mechanistic and genetic data provide a strong rationale for investigation in PD.…”

Developing the “next generation” of genetic association databases for complex diseases

“…The databases developed by our group [for more details on these databases, see Allen et al, 2008;Bertram et al, 2007;Chatzinasiou et al, 2011;Lill et al, , 2012 aim to serve as an exhaustive and regularly updated resource of genetic association studies for the respective diseases. They do not only allow a qualitative overview of genetic association studies in each field, but also provide quantitative assessments of the cumulative evidence for association of individual polymorphisms by calculating and providing up-to-date meta-analyses on all eligible polymorphisms.…”

“…Also, data of obviously "poor" quality are excluded if apparent discrepancies could not be resolved after contacting the study authors (see below). For more details on background and methods, see Lill et al (2012).…”

“…To this end, the genetic databases developed by our team [Allen et al, 2008;Bertram et al, 2007;Chatzinasiou et al, 2011;Lill et al, , 2012 list all published GWAS in the respective diseases fields in a dedicated overview section, which provides demographic characteristics of the included samples and highlights those loci that have been "featured" as potential disease loci in the respective publications.…”

“…Along these lines, the HVP has emphasized the need for disease-specific genetic association databases that would systematically identify and collect the relevant data, quantitatively assess the impact of genetic variants on complex disorders, and make the results available in high-quality, user-friendly databases [Haworth et al, 2011;Cotton et al, 2007]. Independently from the HVP, our group has already developed and continues to maintain a number of such genetic association databases for neuropsychiatric diseases [Allen et al, 2008;Bertram et al, 2007;Lill et al, , 2012 such as AD, PD, ALS, MS, and schizophrenia. The approach behind these database projects represents the focus of this article as it may serve as one model to achieve the abovementioned goals outlined by the HVP.…”