PLoS Genetics (Jan 2012)

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

  • 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

DOI
https://doi.org/10.1371/journal.pgen.1002548
Journal volume & issue
Vol. 8, no. 3
p. e1002548

Abstract

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 Meta-analyses on 147 SNPs were supplemented by unpublished GWAS data from up to 16,452 PD cases and 48,810 controls.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