Christina M. Lill 1 , 2 , 3 , 4 , Johannes T. Roehr 1 , 5 , Matthew B. McQueen 6 , Fotini K. Kavvoura 7 , 8 , 9 , Sachin Bagade 2 , Brit-Maren M. Schjeide 1 , Leif M. Schjeide 1 , Esther Meissner 1 , Ute Zauft 1 , Nicole C. Allen 2 , Tian Liu 1 , 10 , Marcel Schilling 1 , 5 , Kari J. Anderson 11 , Gary Beecham 12 , Daniela Berg 13 , 14 , Joanna M. Biernacka 11 , Alexis Brice 15 , 16 , 17 , 18 , Anita L. DeStefano 19 , 20 , Chuong B. Do 21 , Nicholas Eriksson 21 , Stewart A. Factor 22 , Matthew J. Farrer 23 , Tatiana Foroud 24 , Thomas Gasser 13 , 14 , Taye Hamza 25 , John A. Hardy 26 , Peter Heutink 27 , Erin M. Hill-Burns 25 , Christine Klein 28 , Jeanne C. Latourelle 19 , Demetrius M. Maraganore 29 , Eden R. Martin 12 , Maria Martinez 30 , 31 , Richard H. Myers 19 , Michael A. Nalls 32 , Nathan Pankratz 24 , Haydeh Payami 25 , Wataru Satake 33 , William K. Scott 12 , Manu Sharma 13 , 14 , Andrew B. Singleton 32 , Kari Stefansson 34 , Tatsushi Toda 33 , Joyce Y. Tung 21 , Jeffery Vance 12 , Nick W. Wood 35 , 36 , Cyrus P. Zabetian 37 , 23andMe, The Genetic Epidemiology of Parkinson's Disease (GEO-PD) Consortium, The International Parkinson's Disease Genomics Consortium (IPDGC), The Parkinson's Disease GWAS Consortium, The Wellcome Trust Case Control Consortium 2 (WTCCC2), Peter Young 4 , Rudolph E. Tanzi 2 , Muin J. Khoury 38 , Frauke Zipp 3 , Hans Lehrach 1 , John P. A. Ioannidis 7 , 39 , 40 , 41 , Lars Bertram 1 , 2 , *
15 March 2012
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 Meta-analyses on 147 SNPs were supplemented by unpublished GWAS data from up to 16,452 PD cases and 48,810 controls.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.
The genetic basis of Parkinson's disease is complex, i.e. it is determined by a number of different disease-causing and disease-predisposing genes. Especially the latter have proven difficult to find, evidenced by more than 800 published genetic association studies, typically showing discrepant results. To facilitate the interpretation of this large and continuously increasing body of data, we have created a freely available online database (“PDGene”: http://www.pdgene.org) which provides an exhaustive account of all published genetic association studies in PD. One particularly useful feature is the calculation and display of up-to-date summary statistics of published data for overlapping DNA sequence variants (polymorphisms). These meta-analyses revealed eleven gene loci that showed a statistically very significant ( P<5×10 −8; a.k.a. genome-wide significance) association with risk for PD: BST1, CCDC62/HIP1R, DGKQ/GAK, GBA, LRRK2, MAPT, MCCC1/LAMP3, PARK16, SNCA, STK39, SYT11/RAB25. In addition and purely by data-mining, we identified one novel PD susceptibility locus in a gene called ITGA8 (rs7077361, P = 1.3×10 −8). We note that our continuously updated database represents the most comprehensive research synopsis of genetic association studies in PD to date. In addition to vastly facilitating the work of other PD geneticists, our approach may serve as a valuable example for other complex diseases.