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

Christina M. Lill(Johannes Gutenberg University Mainz), Johannes T. Roehr(Max Planck Institute for Molecular Genetics), Matthew B. McQueen(University of Colorado Boulder), Fotini 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 Human Development), Marcel Schilling(Max Planck Institute for Molecular Genetics), Kari J. Anderson(Mayo Clinic in Florida), Gary W. Beecham(University of Miami), Daniela Berg(German Center for Neurodegenerative Diseases), Joanna M. Biernacka(Mayo Clinic in Florida), Alexis Brice(Centre National de la Recherche Scientifique), Anita L. DeStefano(Boston University), Chuong B. Do(23andMe (United States)), Nicholas Eriksson(23andMe (United States)), Stewart A. Factor(Emory University), Matthew J. Farrer(University of British Columbia), Tatiana Foroud(Indiana University School of Medicine), Thomas Gasser(German Center for Neurodegenerative Diseases), Taye H. Hamza(New York State Department of Health), John Hardy(University College London), Peter Heutink(Amsterdam UMC Location Vrije Universiteit Amsterdam), Gully Burns(New York State Department of Health), Christine Klein(University of Lübeck), Jeanne C. Latourelle(Boston University), Demetrius M. Maraganore(NorthShore University HealthSystem), Eden R. Martin(University of Miami), María Martínez(Université Toulouse III - Paul Sabatier), Richard H. Myers(Boston University), Michael A. Nalls(National Institutes of Health), 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(German Center for Neurodegenerative Diseases), Andrew Singleton(National Institutes of Health), Kāri Stefánsson(deCODE Genetics (Iceland)), Tatsushi Toda(Kobe University), Joyce Y. Tung(23andMe (United States)), Jeffery M. 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(Centers for Disease Control and Prevention), Frauke Zipp(Johannes Gutenberg University Mainz), Hans Lehrach(Max Planck Institute for Molecular Genetics), John P. A. Ioannidis(Tufts University), Lars Bertram(Massachusetts General Hospital)
PLoS Genetics
March 15, 2012
Cited by 543Open Access
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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.


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