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

• Authors: Christina M. Lill, Max Planck Institute for Molecular Genetics; Johannes T. Roehr, Max Planck Institute for Molecular Genetics; Matthew B. McQueen, University of Colorado; Folini K. Kavvoura, University of Ioannina; Sachin Bagade, Massachusetts General Hospital; Brit-Maren M. Schjeide, Max Planck Institute for Molecular Genetics; Leif M. Schjeide, Max Planck Institute for Molecular Genetics; Esther Meissner, Max Planck Institute for Molecular Genetics; Ute Zauft, Max Planck Institute for Molecular Genetics; Nicole C. Allen, Massachusetts General Hospital; Tian Liu, Max Planck Institute for Molecular Genetics; Marcel Schilling, Max Planck Institute for Molecular Genetics; Kari J. Anderson, Mayo Clinic; Gary Beecham, University of Miami; Daniela Berg, University of Tübingen; Joanna M. Biernacka, Mayo Clinic; Alexis Brice, INSERM; Anita L. DeStefano, Boston University; Chuong B. Do, 23andMe; Nicholas Eriksson, 23andMe; Stewart Factor, Emory University; Matthew J. Farrer, University of British Columbia; Tatiana Foroud, Indiana University School of Medicine; Thomas Gasser, University of Tübingen; Taye Hamza, New York State Department of Health; John A. Hardy, University College London; Peter Heutink, VU University Medical Centre, Amsterdam; Erin M. Hill-Burns, New York State Department of Health; Christine Klein, University of Lübeck; Jeanne C. Latourelle, Boston University; Demetrius M. Maraganore, NorthShore University Health System; Eden R. Martin, University of Miami; Maria Martinez, INSERM; Richard H. Myers, Boston University; Michael A. Nalls, National Institute on Aging; Nathan Pankratz, Indiana University School of Medicine; Haydeh Payami, New York State Department of Health; Wataru Satake, Kobe University; William K. Scott, University of Miami; Manu Sharma, University of Tübingen; Andrew B. Singleton, National Institute on Aging; Kari Stefansson, deCODE genetics; TAtsushi Toda, Kobe University; Joyce Y. Tung, 23andMe; Jeffery Vance, University of Miami; Nick W. Wood, University College London; CYrus P. Zabetian, University of Washington; Peter Young, University Hospital, Münster; Rudolph E. Tanzi, Massachusetts General Hospital; Muin J. Khoury, Emory University; Frauke Zipp, Johannes Gutenberg University of Mainz; Hans Lehrach, Max Planck Institute for Molecular Genetics; John P. A. Ioannidis, University of Ioannina; Lars Bertram, Max Planck Institute for Molecular Genetics
• Journal Title: PLoS Genetics
• Volume: Volume 8, Number 3
• Publisher: Public Library of Science | 2012-03-01, Pages e1002548-e1002548
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.1371/journal.pgen.1002548
• Subjects: Biology, Neuroscience; Biology, Genetics
• Keywords: Science & Technology; Life Sciences & Biomedicine; Genetics & Heredity; GENETICS & HEREDITY; GENOME-WIDE ASSOCIATION; ALPHA-SYNUCLEIN; RISK-FACTORS; MUTATIONS; VARIANTS; SUSCEPTIBILITY; DATASETS; TRIALS; REGION; VPS35

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.