Comprehensive research synopsis and systematic meta-analyses in Parkinson's disease genetics: The PDGene database.

• Main Authors: Christina M Lill, Johannes T Roehr, Matthew B McQueen, Fotini K Kavvoura, Sachin Bagade, Brit-Maren M Schjeide, Leif M Schjeide, Esther Meissner, Ute Zauft, Nicole C Allen, Tian Liu, Marcel Schilling, Kari J Anderson, Gary Beecham, Daniela Berg, Joanna M Biernacka, Alexis Brice, Anita L DeStefano, Chuong B Do, Nicholas Eriksson, Stewart A Factor, Matthew J Farrer, Tatiana Foroud, Thomas Gasser, Taye Hamza, John A Hardy, Peter Heutink, Erin M Hill-Burns, Christine Klein, Jeanne C Latourelle, Demetrius M Maraganore, Eden R Martin, Maria Martinez, Richard H Myers, Michael A Nalls, Nathan Pankratz, Haydeh Payami, Wataru Satake, William K Scott, Manu Sharma, Andrew B Singleton, Kari Stefansson, Tatsushi Toda, Joyce Y Tung, Jeffery Vance, Nick W Wood, Cyrus P Zabetian, 23andMe Genetic Epidemiology of Parkinson's Disease Consortium, International Parkinson's Disease Genomics Consortium, Parkinson's Disease GWAS Consortium, Wellcome Trust Case Control Consortium 2), Peter Young, Rudolph E Tanzi, Muin J Khoury, Frauke Zipp, Hans Lehrach, John P A Ioannidis, Lars Bertram
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2012-01-01
• Series: PLoS Genetics
• Online Access: https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22438815/pdf/?tool=EBI

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 Meta-analyses on 147 SNPs were supplemented by unpublished GWAS data from up to 16,452 PD cases and 48,810 controls.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.