Title |
Comprehensive Research Synopsis and Systematic Meta-Analyses in Parkinson's Disease Genetics: The PDGene Database
|
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Published in |
PLoS Genetics, March 2012
|
DOI | 10.1371/journal.pgen.1002548 |
Pubmed ID | |
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., 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, The Genetic Epidemiology of Parkinson's Disease Consortium 23andMe, The International Parkinson's Disease Genomics Consortium, The Parkinson's Disease GWAS Consortium, The Wellcome Trust Case Control Consortium, Peter Young, Rudolph E. Tanzi, Muin J. Khoury, Frauke Zipp, Hans Lehrach, John P. A. Ioannidis, Lars Bertram |
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 Meta-analyses on 147 SNPs were supplemented by unpublished GWAS data from up to 16,452 PD cases and 48,810 controls.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. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Brazil | 1 | 25% |
United States | 1 | 25% |
Unknown | 2 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 2 | 50% |
Science communicators (journalists, bloggers, editors) | 1 | 25% |
Members of the public | 1 | 25% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 7 | 2% |
Germany | 6 | 1% |
United Kingdom | 4 | <1% |
Portugal | 1 | <1% |
Netherlands | 1 | <1% |
Australia | 1 | <1% |
South Africa | 1 | <1% |
Israel | 1 | <1% |
Colombia | 1 | <1% |
Other | 4 | <1% |
Unknown | 395 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 88 | 21% |
Student > Ph. D. Student | 79 | 19% |
Student > Master | 47 | 11% |
Student > Bachelor | 41 | 10% |
Professor | 22 | 5% |
Other | 81 | 19% |
Unknown | 64 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 106 | 25% |
Medicine and Dentistry | 73 | 17% |
Biochemistry, Genetics and Molecular Biology | 59 | 14% |
Neuroscience | 43 | 10% |
Computer Science | 12 | 3% |
Other | 44 | 10% |
Unknown | 85 | 20% |