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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Comprehensive Research Synopsis and Systematic Meta-Analyses in Parkinson's Disease Genetics: The PDGene Database</title><author><name sortKey="Lill, Christina M" sort="Lill, Christina M" uniqKey="Lill C" first="Christina M." last="Lill">Christina M. Lill</name><affiliation><nlm:aff id="aff1"><addr-line>Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff2"><addr-line>Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, United States of America</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff3"><addr-line>Department of Neurology, Medical Center of the Johannes Gutenberg-University, Mainz, Germany</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff4"><addr-line>Department of Neurology, University Hospital, Münster, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Roehr, Johannes T" sort="Roehr, Johannes T" uniqKey="Roehr J" first="Johannes T." last="Roehr">Johannes T. Roehr</name><affiliation><nlm:aff id="aff1"><addr-line>Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff5"><addr-line>Department of Mathematics and Computer Science, Free University, Berlin, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Mcqueen, Matthew B" sort="Mcqueen, Matthew B" uniqKey="Mcqueen M" first="Matthew B." last="Mcqueen">Matthew B. Mcqueen</name><affiliation><nlm:aff id="aff6"><addr-line>Institute for Behavioral Genetics, University of Colorado, Boulder, Colorado, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Kavvoura, Fotini K" sort="Kavvoura, Fotini K" uniqKey="Kavvoura F" first="Fotini K." last="Kavvoura">Fotini K. Kavvoura</name><affiliation><nlm:aff id="aff7"><addr-line>Clinical and Molecular Epidemiology Unit, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff8"><addr-line>Centre for Diabetes and Endocrinology, Royal Berkshire Hospital, Reading, United Kingdom</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff9"><addr-line>Oxford Centre for Diabetes, Endocrinology, and Metabolism, Churchill Hospital, University of Oxford, Oxford, United Kingdom</addr-line></nlm:aff></affiliation></author><author><name sortKey="Bagade, Sachin" sort="Bagade, Sachin" uniqKey="Bagade S" first="Sachin" last="Bagade">Sachin Bagade</name><affiliation><nlm:aff id="aff2"><addr-line>Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Schjeide, Brit Maren M" sort="Schjeide, Brit Maren M" uniqKey="Schjeide B" first="Brit-Maren M." last="Schjeide">Brit-Maren M. Schjeide</name><affiliation><nlm:aff id="aff1"><addr-line>Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Schjeide, Leif M" sort="Schjeide, Leif M" uniqKey="Schjeide L" first="Leif M." last="Schjeide">Leif M. Schjeide</name><affiliation><nlm:aff id="aff1"><addr-line>Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Meissner, Esther" sort="Meissner, Esther" uniqKey="Meissner E" first="Esther" last="Meissner">Esther Meissner</name><affiliation><nlm:aff id="aff1"><addr-line>Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Zauft, Ute" sort="Zauft, Ute" uniqKey="Zauft U" first="Ute" last="Zauft">Ute Zauft</name><affiliation><nlm:aff id="aff1"><addr-line>Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Allen, Nicole C" sort="Allen, Nicole C" uniqKey="Allen N" first="Nicole C." last="Allen">Nicole C. Allen</name><affiliation><nlm:aff id="aff2"><addr-line>Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Liu, Tian" sort="Liu, Tian" uniqKey="Liu T" first="Tian" last="Liu">Tian Liu</name><affiliation><nlm:aff id="aff1"><addr-line>Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff10"><addr-line>Max Planck Institute for Human Development, Berlin, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Schilling, Marcel" sort="Schilling, Marcel" uniqKey="Schilling M" first="Marcel" last="Schilling">Marcel Schilling</name><affiliation><nlm:aff id="aff1"><addr-line>Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff5"><addr-line>Department of Mathematics and Computer Science, Free University, Berlin, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Anderson, Kari J" sort="Anderson, Kari J" uniqKey="Anderson K" first="Kari J." last="Anderson">Kari J. Anderson</name><affiliation><nlm:aff id="aff11"><addr-line>Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Beecham, Gary" sort="Beecham, Gary" uniqKey="Beecham G" first="Gary" last="Beecham">Gary Beecham</name><affiliation><nlm:aff id="aff12"><addr-line>John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Berg, Daniela" sort="Berg, Daniela" uniqKey="Berg D" first="Daniela" last="Berg">Daniela Berg</name><affiliation><nlm:aff id="aff13"><addr-line>Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff14"><addr-line>DZNE, German Center for Neurodegenerative Diseases, Tübingen, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Biernacka, Joanna M" sort="Biernacka, Joanna M" uniqKey="Biernacka J" first="Joanna M." last="Biernacka">Joanna M. Biernacka</name><affiliation><nlm:aff id="aff11"><addr-line>Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Brice, Alexis" sort="Brice, Alexis" uniqKey="Brice A" first="Alexis" last="Brice">Alexis Brice</name><affiliation><nlm:aff id="aff15"><addr-line>INSERM, UMR_S975, Paris, France</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff16"><addr-line>Université Pierre et Marie Curie-Paris, Centre de Recherche de l'Institut du Cerveau et de la Moelle épinière, UMR-S975, Paris, France</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff17"><addr-line>CNRS, UMR 7225, Paris, France</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff18"><addr-line>AP-HP, Pitié-Salpêtrière Hospital, Department of Genetics and Cytogenetics, Paris, France</addr-line></nlm:aff></affiliation></author><author><name sortKey="Destefano, Anita L" sort="Destefano, Anita L" uniqKey="Destefano A" first="Anita L." last="Destefano">Anita L. Destefano</name><affiliation><nlm:aff id="aff19"><addr-line>Department of Neurology, Boston University School of Medicine, Boston University, Boston, Massachusetts, United States of America</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff20"><addr-line>Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Do, Chuong B" sort="Do, Chuong B" uniqKey="Do C" first="Chuong B." last="Do">Chuong B. Do</name><affiliation><nlm:aff id="aff21"><addr-line>23andMe, Mountain View, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Eriksson, Nicholas" sort="Eriksson, Nicholas" uniqKey="Eriksson N" first="Nicholas" last="Eriksson">Nicholas Eriksson</name><affiliation><nlm:aff id="aff21"><addr-line>23andMe, Mountain View, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Factor, Stewart A" sort="Factor, Stewart A" uniqKey="Factor S" first="Stewart A." last="Factor">Stewart A. Factor</name><affiliation><nlm:aff id="aff22"><addr-line>Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Farrer, Matthew J" sort="Farrer, Matthew J" uniqKey="Farrer M" first="Matthew J." last="Farrer">Matthew J. Farrer</name><affiliation><nlm:aff id="aff23"><addr-line>Department of Medical Genetics, University of British Columbia, Vancouver, Canada</addr-line></nlm:aff></affiliation></author><author><name sortKey="Foroud, Tatiana" sort="Foroud, Tatiana" uniqKey="Foroud T" first="Tatiana" last="Foroud">Tatiana Foroud</name><affiliation><nlm:aff id="aff24"><addr-line>Indiana University School of Medicine, Indianapolis, Indiana, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Gasser, Thomas" sort="Gasser, Thomas" uniqKey="Gasser T" first="Thomas" last="Gasser">Thomas Gasser</name><affiliation><nlm:aff id="aff13"><addr-line>Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff14"><addr-line>DZNE, German Center for Neurodegenerative Diseases, Tübingen, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Hamza, Taye" sort="Hamza, Taye" uniqKey="Hamza T" first="Taye" last="Hamza">Taye Hamza</name><affiliation><nlm:aff id="aff25"><addr-line>New York State Department of Health Wadsworth Center, Albany, New York, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Hardy, John A" sort="Hardy, John A" uniqKey="Hardy J" first="John A." last="Hardy">John A. Hardy</name><affiliation><nlm:aff id="aff26"><addr-line>Department of Molecular Neuroscience, UCL Institute of Neurology, University College London, London, United Kingdom</addr-line></nlm:aff></affiliation></author><author><name sortKey="Heutink, Peter" sort="Heutink, Peter" uniqKey="Heutink P" first="Peter" last="Heutink">Peter Heutink</name><affiliation><nlm:aff id="aff27"><addr-line>Department of Clinical Genetics, Section of Medical Genomics, VU University Medical Centre, Amsterdam, The Netherlands</addr-line></nlm:aff></affiliation></author><author><name sortKey="Hill Burns, Erin M" sort="Hill Burns, Erin M" uniqKey="Hill Burns E" first="Erin M." last="Hill-Burns">Erin M. Hill-Burns</name><affiliation><nlm:aff id="aff25"><addr-line>New York State Department of Health Wadsworth Center, Albany, New York, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Klein, Christine" sort="Klein, Christine" uniqKey="Klein C" first="Christine" last="Klein">Christine Klein</name><affiliation><nlm:aff id="aff28"><addr-line>Section of Clinical and Molecular Neurogenetics, Department of Neurology, University of Lübeck, Lübeck, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Latourelle, Jeanne C" sort="Latourelle, Jeanne C" uniqKey="Latourelle J" first="Jeanne C." last="Latourelle">Jeanne C. Latourelle</name><affiliation><nlm:aff id="aff19"><addr-line>Department of Neurology, Boston University School of Medicine, Boston University, Boston, Massachusetts, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Maraganore, Demetrius M" sort="Maraganore, Demetrius M" uniqKey="Maraganore D" first="Demetrius M." last="Maraganore">Demetrius M. Maraganore</name><affiliation><nlm:aff id="aff29"><addr-line>Department of Neurology, NorthShore University Health System, Evanston, Illinois, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Martin, Eden R" sort="Martin, Eden R" uniqKey="Martin E" first="Eden R." last="Martin">Eden R. Martin</name><affiliation><nlm:aff id="aff12"><addr-line>John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Martinez, Maria" sort="Martinez, Maria" uniqKey="Martinez M" first="Maria" last="Martinez">Maria Martinez</name><affiliation><nlm:aff id="aff30"><addr-line>INSERM UMR 1043, CPTP, Toulouse, France</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff31"><addr-line>Paul Sabatier University, Toulouse, France</addr-line></nlm:aff></affiliation></author><author><name sortKey="Myers, Richard H" sort="Myers, Richard H" uniqKey="Myers R" first="Richard H." last="Myers">Richard H. Myers</name><affiliation><nlm:aff id="aff19"><addr-line>Department of Neurology, Boston University School of Medicine, Boston University, Boston, Massachusetts, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Nalls, Michael A" sort="Nalls, Michael A" uniqKey="Nalls M" first="Michael A." last="Nalls">Michael A. Nalls</name><affiliation><nlm:aff id="aff32"><addr-line>Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Pankratz, Nathan" sort="Pankratz, Nathan" uniqKey="Pankratz N" first="Nathan" last="Pankratz">Nathan Pankratz</name><affiliation><nlm:aff id="aff24"><addr-line>Indiana University School of Medicine, Indianapolis, Indiana, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Payami, Haydeh" sort="Payami, Haydeh" uniqKey="Payami H" first="Haydeh" last="Payami">Haydeh Payami</name><affiliation><nlm:aff id="aff25"><addr-line>New York State Department of Health Wadsworth Center, Albany, New York, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Satake, Wataru" sort="Satake, Wataru" uniqKey="Satake W" first="Wataru" last="Satake">Wataru Satake</name><affiliation><nlm:aff id="aff33"><addr-line>Division of Neurology/Molecular Brain Science, Kobe University Graduate School of Medicine, Kobe, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Scott, William K" sort="Scott, William K" uniqKey="Scott W" first="William K." last="Scott">William K. Scott</name><affiliation><nlm:aff id="aff12"><addr-line>John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Sharma, Manu" sort="Sharma, Manu" uniqKey="Sharma M" first="Manu" last="Sharma">Manu Sharma</name><affiliation><nlm:aff id="aff13"><addr-line>Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff14"><addr-line>DZNE, German Center for Neurodegenerative Diseases, Tübingen, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Singleton, Andrew B" sort="Singleton, Andrew B" uniqKey="Singleton A" first="Andrew B." last="Singleton">Andrew B. Singleton</name><affiliation><nlm:aff id="aff32"><addr-line>Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Stefansson, Kari" sort="Stefansson, Kari" uniqKey="Stefansson K" first="Kari" last="Stefansson">Kari Stefansson</name><affiliation><nlm:aff id="aff34"><addr-line>deCODE genetics, Reykjavik, Iceland</addr-line></nlm:aff></affiliation></author><author><name sortKey="Toda, Tatsushi" sort="Toda, Tatsushi" uniqKey="Toda T" first="Tatsushi" last="Toda">Tatsushi Toda</name><affiliation><nlm:aff id="aff33"><addr-line>Division of Neurology/Molecular Brain Science, Kobe University Graduate School of Medicine, Kobe, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Tung, Joyce Y" sort="Tung, Joyce Y" uniqKey="Tung J" first="Joyce Y." last="Tung">Joyce Y. Tung</name><affiliation><nlm:aff id="aff21"><addr-line>23andMe, Mountain View, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Vance, Jeffery" sort="Vance, Jeffery" uniqKey="Vance J" first="Jeffery" last="Vance">Jeffery Vance</name><affiliation><nlm:aff id="aff12"><addr-line>John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Wood, Nick W" sort="Wood, Nick W" uniqKey="Wood N" first="Nick W." last="Wood">Nick W. Wood</name><affiliation><nlm:aff id="aff35"><addr-line>UCL Genetics Institute, University College London, London, United Kingdom</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff36"><addr-line>Department of Molecular Neuroscience, UCL Institute of Neurology, University College London, London, United Kingdom</addr-line></nlm:aff></affiliation></author><author><name sortKey="Zabetian, Cyrus P" sort="Zabetian, Cyrus P" uniqKey="Zabetian C" first="Cyrus P." last="Zabetian">Cyrus P. Zabetian</name><affiliation><nlm:aff id="aff37"><addr-line>VA Puget Sound Health Care System and Department of Neurology, University of Washington, Seattle, Washington, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Young, Peter" sort="Young, Peter" uniqKey="Young P" first="Peter" last="Young">Peter Young</name><affiliation><nlm:aff id="aff4"><addr-line>Department of Neurology, University Hospital, Münster, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Tanzi, Rudolph E" sort="Tanzi, Rudolph E" uniqKey="Tanzi R" first="Rudolph E." last="Tanzi">Rudolph E. Tanzi</name><affiliation><nlm:aff id="aff2"><addr-line>Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Khoury, Muin J" sort="Khoury, Muin J" uniqKey="Khoury M" first="Muin J." last="Khoury">Muin J. Khoury</name><affiliation><nlm:aff id="aff38"><addr-line>Office of Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Zipp, Frauke" sort="Zipp, Frauke" uniqKey="Zipp F" first="Frauke" last="Zipp">Frauke Zipp</name><affiliation><nlm:aff id="aff3"><addr-line>Department of Neurology, Medical Center of the Johannes Gutenberg-University, Mainz, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Lehrach, Hans" sort="Lehrach, Hans" uniqKey="Lehrach H" first="Hans" last="Lehrach">Hans Lehrach</name><affiliation><nlm:aff id="aff1"><addr-line>Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Ioannidis, John P A" sort="Ioannidis, John P A" uniqKey="Ioannidis J" first="John P. A." last="Ioannidis">John P. A. Ioannidis</name><affiliation><nlm:aff id="aff7"><addr-line>Clinical and Molecular Epidemiology Unit, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff39"><addr-line>Biomedical Research Institute, Foundation for Research and Technology–Hellas, Ioannina, Greece</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff40"><addr-line>Center for Genetic Epidemiology and Modeling and Tufts Clinical and Translational Science Institute, Tufts University School of Medicine, Boston, Massachusetts, United States of America</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff41"><addr-line>Stanford Prevention Research Center, Department of Medicine and Department of Health Research and Policy, Stanford University School of Medicine, Stanford, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Bertram, Lars" sort="Bertram, Lars" uniqKey="Bertram L" first="Lars" last="Bertram">Lars Bertram</name><affiliation><nlm:aff id="aff1"><addr-line>Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff2"><addr-line>Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, United States of America</addr-line></nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">22438815</idno><idno type="pmc">3305333</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3305333</idno><idno type="RBID">PMC:3305333</idno><idno type="doi">10.1371/journal.pgen.1002548</idno><date when="2012">2012</date><idno type="wicri:Area/Pmc/Corpus">000796</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000796</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Comprehensive Research Synopsis and Systematic Meta-Analyses in Parkinson's Disease Genetics: The PDGene Database</title><author><name sortKey="Lill, Christina M" sort="Lill, Christina M" uniqKey="Lill C" first="Christina M." last="Lill">Christina M. Lill</name><affiliation><nlm:aff id="aff1"><addr-line>Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff2"><addr-line>Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, United States of America</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff3"><addr-line>Department of Neurology, Medical Center of the Johannes Gutenberg-University, Mainz, Germany</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff4"><addr-line>Department of Neurology, University Hospital, Münster, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Roehr, Johannes T" sort="Roehr, Johannes T" uniqKey="Roehr J" first="Johannes T." last="Roehr">Johannes T. Roehr</name><affiliation><nlm:aff id="aff1"><addr-line>Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff5"><addr-line>Department of Mathematics and Computer Science, Free University, Berlin, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Mcqueen, Matthew B" sort="Mcqueen, Matthew B" uniqKey="Mcqueen M" first="Matthew B." last="Mcqueen">Matthew B. Mcqueen</name><affiliation><nlm:aff id="aff6"><addr-line>Institute for Behavioral Genetics, University of Colorado, Boulder, Colorado, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Kavvoura, Fotini K" sort="Kavvoura, Fotini K" uniqKey="Kavvoura F" first="Fotini K." last="Kavvoura">Fotini K. Kavvoura</name><affiliation><nlm:aff id="aff7"><addr-line>Clinical and Molecular Epidemiology Unit, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff8"><addr-line>Centre for Diabetes and Endocrinology, Royal Berkshire Hospital, Reading, United Kingdom</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff9"><addr-line>Oxford Centre for Diabetes, Endocrinology, and Metabolism, Churchill Hospital, University of Oxford, Oxford, United Kingdom</addr-line></nlm:aff></affiliation></author><author><name sortKey="Bagade, Sachin" sort="Bagade, Sachin" uniqKey="Bagade S" first="Sachin" last="Bagade">Sachin Bagade</name><affiliation><nlm:aff id="aff2"><addr-line>Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Schjeide, Brit Maren M" sort="Schjeide, Brit Maren M" uniqKey="Schjeide B" first="Brit-Maren M." last="Schjeide">Brit-Maren M. Schjeide</name><affiliation><nlm:aff id="aff1"><addr-line>Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Schjeide, Leif M" sort="Schjeide, Leif M" uniqKey="Schjeide L" first="Leif M." last="Schjeide">Leif M. Schjeide</name><affiliation><nlm:aff id="aff1"><addr-line>Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Meissner, Esther" sort="Meissner, Esther" uniqKey="Meissner E" first="Esther" last="Meissner">Esther Meissner</name><affiliation><nlm:aff id="aff1"><addr-line>Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Zauft, Ute" sort="Zauft, Ute" uniqKey="Zauft U" first="Ute" last="Zauft">Ute Zauft</name><affiliation><nlm:aff id="aff1"><addr-line>Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Allen, Nicole C" sort="Allen, Nicole C" uniqKey="Allen N" first="Nicole C." last="Allen">Nicole C. Allen</name><affiliation><nlm:aff id="aff2"><addr-line>Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Liu, Tian" sort="Liu, Tian" uniqKey="Liu T" first="Tian" last="Liu">Tian Liu</name><affiliation><nlm:aff id="aff1"><addr-line>Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff10"><addr-line>Max Planck Institute for Human Development, Berlin, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Schilling, Marcel" sort="Schilling, Marcel" uniqKey="Schilling M" first="Marcel" last="Schilling">Marcel Schilling</name><affiliation><nlm:aff id="aff1"><addr-line>Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff5"><addr-line>Department of Mathematics and Computer Science, Free University, Berlin, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Anderson, Kari J" sort="Anderson, Kari J" uniqKey="Anderson K" first="Kari J." last="Anderson">Kari J. Anderson</name><affiliation><nlm:aff id="aff11"><addr-line>Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Beecham, Gary" sort="Beecham, Gary" uniqKey="Beecham G" first="Gary" last="Beecham">Gary Beecham</name><affiliation><nlm:aff id="aff12"><addr-line>John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Berg, Daniela" sort="Berg, Daniela" uniqKey="Berg D" first="Daniela" last="Berg">Daniela Berg</name><affiliation><nlm:aff id="aff13"><addr-line>Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff14"><addr-line>DZNE, German Center for Neurodegenerative Diseases, Tübingen, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Biernacka, Joanna M" sort="Biernacka, Joanna M" uniqKey="Biernacka J" first="Joanna M." last="Biernacka">Joanna M. Biernacka</name><affiliation><nlm:aff id="aff11"><addr-line>Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Brice, Alexis" sort="Brice, Alexis" uniqKey="Brice A" first="Alexis" last="Brice">Alexis Brice</name><affiliation><nlm:aff id="aff15"><addr-line>INSERM, UMR_S975, Paris, France</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff16"><addr-line>Université Pierre et Marie Curie-Paris, Centre de Recherche de l'Institut du Cerveau et de la Moelle épinière, UMR-S975, Paris, France</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff17"><addr-line>CNRS, UMR 7225, Paris, France</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff18"><addr-line>AP-HP, Pitié-Salpêtrière Hospital, Department of Genetics and Cytogenetics, Paris, France</addr-line></nlm:aff></affiliation></author><author><name sortKey="Destefano, Anita L" sort="Destefano, Anita L" uniqKey="Destefano A" first="Anita L." last="Destefano">Anita L. Destefano</name><affiliation><nlm:aff id="aff19"><addr-line>Department of Neurology, Boston University School of Medicine, Boston University, Boston, Massachusetts, United States of America</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff20"><addr-line>Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Do, Chuong B" sort="Do, Chuong B" uniqKey="Do C" first="Chuong B." last="Do">Chuong B. Do</name><affiliation><nlm:aff id="aff21"><addr-line>23andMe, Mountain View, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Eriksson, Nicholas" sort="Eriksson, Nicholas" uniqKey="Eriksson N" first="Nicholas" last="Eriksson">Nicholas Eriksson</name><affiliation><nlm:aff id="aff21"><addr-line>23andMe, Mountain View, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Factor, Stewart A" sort="Factor, Stewart A" uniqKey="Factor S" first="Stewart A." last="Factor">Stewart A. Factor</name><affiliation><nlm:aff id="aff22"><addr-line>Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Farrer, Matthew J" sort="Farrer, Matthew J" uniqKey="Farrer M" first="Matthew J." last="Farrer">Matthew J. Farrer</name><affiliation><nlm:aff id="aff23"><addr-line>Department of Medical Genetics, University of British Columbia, Vancouver, Canada</addr-line></nlm:aff></affiliation></author><author><name sortKey="Foroud, Tatiana" sort="Foroud, Tatiana" uniqKey="Foroud T" first="Tatiana" last="Foroud">Tatiana Foroud</name><affiliation><nlm:aff id="aff24"><addr-line>Indiana University School of Medicine, Indianapolis, Indiana, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Gasser, Thomas" sort="Gasser, Thomas" uniqKey="Gasser T" first="Thomas" last="Gasser">Thomas Gasser</name><affiliation><nlm:aff id="aff13"><addr-line>Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff14"><addr-line>DZNE, German Center for Neurodegenerative Diseases, Tübingen, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Hamza, Taye" sort="Hamza, Taye" uniqKey="Hamza T" first="Taye" last="Hamza">Taye Hamza</name><affiliation><nlm:aff id="aff25"><addr-line>New York State Department of Health Wadsworth Center, Albany, New York, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Hardy, John A" sort="Hardy, John A" uniqKey="Hardy J" first="John A." last="Hardy">John A. Hardy</name><affiliation><nlm:aff id="aff26"><addr-line>Department of Molecular Neuroscience, UCL Institute of Neurology, University College London, London, United Kingdom</addr-line></nlm:aff></affiliation></author><author><name sortKey="Heutink, Peter" sort="Heutink, Peter" uniqKey="Heutink P" first="Peter" last="Heutink">Peter Heutink</name><affiliation><nlm:aff id="aff27"><addr-line>Department of Clinical Genetics, Section of Medical Genomics, VU University Medical Centre, Amsterdam, The Netherlands</addr-line></nlm:aff></affiliation></author><author><name sortKey="Hill Burns, Erin M" sort="Hill Burns, Erin M" uniqKey="Hill Burns E" first="Erin M." last="Hill-Burns">Erin M. Hill-Burns</name><affiliation><nlm:aff id="aff25"><addr-line>New York State Department of Health Wadsworth Center, Albany, New York, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Klein, Christine" sort="Klein, Christine" uniqKey="Klein C" first="Christine" last="Klein">Christine Klein</name><affiliation><nlm:aff id="aff28"><addr-line>Section of Clinical and Molecular Neurogenetics, Department of Neurology, University of Lübeck, Lübeck, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Latourelle, Jeanne C" sort="Latourelle, Jeanne C" uniqKey="Latourelle J" first="Jeanne C." last="Latourelle">Jeanne C. Latourelle</name><affiliation><nlm:aff id="aff19"><addr-line>Department of Neurology, Boston University School of Medicine, Boston University, Boston, Massachusetts, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Maraganore, Demetrius M" sort="Maraganore, Demetrius M" uniqKey="Maraganore D" first="Demetrius M." last="Maraganore">Demetrius M. Maraganore</name><affiliation><nlm:aff id="aff29"><addr-line>Department of Neurology, NorthShore University Health System, Evanston, Illinois, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Martin, Eden R" sort="Martin, Eden R" uniqKey="Martin E" first="Eden R." last="Martin">Eden R. Martin</name><affiliation><nlm:aff id="aff12"><addr-line>John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Martinez, Maria" sort="Martinez, Maria" uniqKey="Martinez M" first="Maria" last="Martinez">Maria Martinez</name><affiliation><nlm:aff id="aff30"><addr-line>INSERM UMR 1043, CPTP, Toulouse, France</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff31"><addr-line>Paul Sabatier University, Toulouse, France</addr-line></nlm:aff></affiliation></author><author><name sortKey="Myers, Richard H" sort="Myers, Richard H" uniqKey="Myers R" first="Richard H." last="Myers">Richard H. Myers</name><affiliation><nlm:aff id="aff19"><addr-line>Department of Neurology, Boston University School of Medicine, Boston University, Boston, Massachusetts, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Nalls, Michael A" sort="Nalls, Michael A" uniqKey="Nalls M" first="Michael A." last="Nalls">Michael A. Nalls</name><affiliation><nlm:aff id="aff32"><addr-line>Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Pankratz, Nathan" sort="Pankratz, Nathan" uniqKey="Pankratz N" first="Nathan" last="Pankratz">Nathan Pankratz</name><affiliation><nlm:aff id="aff24"><addr-line>Indiana University School of Medicine, Indianapolis, Indiana, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Payami, Haydeh" sort="Payami, Haydeh" uniqKey="Payami H" first="Haydeh" last="Payami">Haydeh Payami</name><affiliation><nlm:aff id="aff25"><addr-line>New York State Department of Health Wadsworth Center, Albany, New York, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Satake, Wataru" sort="Satake, Wataru" uniqKey="Satake W" first="Wataru" last="Satake">Wataru Satake</name><affiliation><nlm:aff id="aff33"><addr-line>Division of Neurology/Molecular Brain Science, Kobe University Graduate School of Medicine, Kobe, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Scott, William K" sort="Scott, William K" uniqKey="Scott W" first="William K." last="Scott">William K. Scott</name><affiliation><nlm:aff id="aff12"><addr-line>John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Sharma, Manu" sort="Sharma, Manu" uniqKey="Sharma M" first="Manu" last="Sharma">Manu Sharma</name><affiliation><nlm:aff id="aff13"><addr-line>Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff14"><addr-line>DZNE, German Center for Neurodegenerative Diseases, Tübingen, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Singleton, Andrew B" sort="Singleton, Andrew B" uniqKey="Singleton A" first="Andrew B." last="Singleton">Andrew B. Singleton</name><affiliation><nlm:aff id="aff32"><addr-line>Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Stefansson, Kari" sort="Stefansson, Kari" uniqKey="Stefansson K" first="Kari" last="Stefansson">Kari Stefansson</name><affiliation><nlm:aff id="aff34"><addr-line>deCODE genetics, Reykjavik, Iceland</addr-line></nlm:aff></affiliation></author><author><name sortKey="Toda, Tatsushi" sort="Toda, Tatsushi" uniqKey="Toda T" first="Tatsushi" last="Toda">Tatsushi Toda</name><affiliation><nlm:aff id="aff33"><addr-line>Division of Neurology/Molecular Brain Science, Kobe University Graduate School of Medicine, Kobe, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Tung, Joyce Y" sort="Tung, Joyce Y" uniqKey="Tung J" first="Joyce Y." last="Tung">Joyce Y. Tung</name><affiliation><nlm:aff id="aff21"><addr-line>23andMe, Mountain View, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Vance, Jeffery" sort="Vance, Jeffery" uniqKey="Vance J" first="Jeffery" last="Vance">Jeffery Vance</name><affiliation><nlm:aff id="aff12"><addr-line>John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Wood, Nick W" sort="Wood, Nick W" uniqKey="Wood N" first="Nick W." last="Wood">Nick W. Wood</name><affiliation><nlm:aff id="aff35"><addr-line>UCL Genetics Institute, University College London, London, United Kingdom</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff36"><addr-line>Department of Molecular Neuroscience, UCL Institute of Neurology, University College London, London, United Kingdom</addr-line></nlm:aff></affiliation></author><author><name sortKey="Zabetian, Cyrus P" sort="Zabetian, Cyrus P" uniqKey="Zabetian C" first="Cyrus P." last="Zabetian">Cyrus P. Zabetian</name><affiliation><nlm:aff id="aff37"><addr-line>VA Puget Sound Health Care System and Department of Neurology, University of Washington, Seattle, Washington, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Young, Peter" sort="Young, Peter" uniqKey="Young P" first="Peter" last="Young">Peter Young</name><affiliation><nlm:aff id="aff4"><addr-line>Department of Neurology, University Hospital, Münster, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Tanzi, Rudolph E" sort="Tanzi, Rudolph E" uniqKey="Tanzi R" first="Rudolph E." last="Tanzi">Rudolph E. Tanzi</name><affiliation><nlm:aff id="aff2"><addr-line>Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Khoury, Muin J" sort="Khoury, Muin J" uniqKey="Khoury M" first="Muin J." last="Khoury">Muin J. Khoury</name><affiliation><nlm:aff id="aff38"><addr-line>Office of Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Zipp, Frauke" sort="Zipp, Frauke" uniqKey="Zipp F" first="Frauke" last="Zipp">Frauke Zipp</name><affiliation><nlm:aff id="aff3"><addr-line>Department of Neurology, Medical Center of the Johannes Gutenberg-University, Mainz, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Lehrach, Hans" sort="Lehrach, Hans" uniqKey="Lehrach H" first="Hans" last="Lehrach">Hans Lehrach</name><affiliation><nlm:aff id="aff1"><addr-line>Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany</addr-line></nlm:aff></affiliation></author><author><name sortKey="Ioannidis, John P A" sort="Ioannidis, John P A" uniqKey="Ioannidis J" first="John P. A." last="Ioannidis">John P. A. Ioannidis</name><affiliation><nlm:aff id="aff7"><addr-line>Clinical and Molecular Epidemiology Unit, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff39"><addr-line>Biomedical Research Institute, Foundation for Research and Technology–Hellas, Ioannina, Greece</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff40"><addr-line>Center for Genetic Epidemiology and Modeling and Tufts Clinical and Translational Science Institute, Tufts University School of Medicine, Boston, Massachusetts, United States of America</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff41"><addr-line>Stanford Prevention Research Center, Department of Medicine and Department of Health Research and Policy, Stanford University School of Medicine, Stanford, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Bertram, Lars" sort="Bertram, Lars" uniqKey="Bertram L" first="Lars" last="Bertram">Lars Bertram</name><affiliation><nlm:aff id="aff1"><addr-line>Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff2"><addr-line>Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, United States of America</addr-line></nlm:aff></affiliation></author></analytic><series><title level="j">PLoS Genetics</title><idno type="ISSN">1553-7390</idno><idno type="eISSN">1553-7404</idno><imprint><date when="2012">2012</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>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 (<italic>P</italic><5×10<sup>−8</sup>) association with disease risk: <italic>BST1</italic>, <italic>CCDC62/HIP1R</italic>, <italic>DGKQ/GAK</italic>, <italic>GBA</italic>, <italic>LRRK2</italic>, <italic>MAPT</italic>, <italic>MCCC1/LAMP3</italic>, PARK16, <italic>SNCA</italic>, <italic>STK39</italic>, and <italic>SYT11/RAB25</italic>. In addition, we identified novel evidence for genome-wide significant association with a polymorphism in <italic>ITGA8</italic> (rs7077361, OR 0.88, <italic>P</italic> = 1.3×10<sup>−8</sup>). All meta-analysis results are freely available on a dedicated online database (<ext-link ext-link-type="uri" xlink:href="http://www.pdgene.org">www.pdgene.org</ext-link>), 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.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="De Lau, Lml" uniqKey="De Lau L">LML de Lau</name></author><author><name sortKey="Breteler, Mmb" uniqKey="Breteler M">MMB Breteler</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Hardy, J" uniqKey="Hardy J">J Hardy</name></author><author><name sortKey="Lewis, P" uniqKey="Lewis P">P Lewis</name></author><author><name sortKey="Revesz, T" uniqKey="Revesz T">T Revesz</name></author><author><name sortKey="Lees, A" uniqKey="Lees A">A Lees</name></author><author><name sortKey="Paisan Ruiz, C" uniqKey="Paisan Ruiz C">C Paisan-Ruiz</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Vilari O Guell, C" uniqKey="Vilari O Guell C">C Vilariño-Güell</name></author><author><name sortKey="Wider, C" uniqKey="Wider C">C Wider</name></author><author><name sortKey="Ross, Oa" uniqKey="Ross O">OA Ross</name></author><author><name sortKey="Dachsel, Jc" uniqKey="Dachsel J">JC Dachsel</name></author><author><name sortKey="Kachergus, Jm" uniqKey="Kachergus J">JM Kachergus</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Zimprich, A" uniqKey="Zimprich A">A Zimprich</name></author><author><name sortKey="Benet Pages, A" uniqKey="Benet Pages A">A Benet-Pagès</name></author><author><name sortKey="Struhal, W" uniqKey="Struhal W">W Struhal</name></author><author><name sortKey="Graf, E" uniqKey="Graf E">E Graf</name></author><author><name sortKey="Eck, Sh" uniqKey="Eck S">SH Eck</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Chartier Harlin, M C" uniqKey="Chartier Harlin M">M-C Chartier-Harlin</name></author><author><name sortKey="Dachsel, Jc" uniqKey="Dachsel J">JC Dachsel</name></author><author><name sortKey="Vilari O Guell, C" uniqKey="Vilari O Guell C">C Vilariño-Güell</name></author><author><name sortKey="Lincoln, Sj" uniqKey="Lincoln S">SJ Lincoln</name></author><author><name sortKey="Lepretre, F" uniqKey="Lepretre F">F Leprêtre</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Maraganore, Dm" uniqKey="Maraganore D">DM Maraganore</name></author><author><name sortKey="De Andrade, M" uniqKey="De Andrade M">M de Andrade</name></author><author><name sortKey="Elbaz, A" uniqKey="Elbaz A">A Elbaz</name></author><author><name sortKey="Farrer, Mj" uniqKey="Farrer M">MJ Farrer</name></author><author><name sortKey="Ioannidis, Jp" uniqKey="Ioannidis J">JP Ioannidis</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Zabetian, Cp" uniqKey="Zabetian C">CP Zabetian</name></author><author><name sortKey="Yamamoto, M" uniqKey="Yamamoto M">M 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<front><journal-meta><journal-id journal-id-type="nlm-ta">PLoS Genet</journal-id><journal-id journal-id-type="iso-abbrev">PLoS Genet</journal-id><journal-id journal-id-type="publisher-id">plos</journal-id><journal-id journal-id-type="pmc">plosgen</journal-id><journal-title-group><journal-title>PLoS Genetics</journal-title></journal-title-group><issn pub-type="ppub">1553-7390</issn><issn pub-type="epub">1553-7404</issn><publisher><publisher-name>Public Library of Science</publisher-name><publisher-loc>San Francisco, USA</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">22438815</article-id><article-id pub-id-type="pmc">3305333</article-id><article-id pub-id-type="publisher-id">PGENETICS-D-11-02212</article-id><article-id pub-id-type="doi">10.1371/journal.pgen.1002548</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Medicine</subject><subj-group><subject>Epidemiology</subject></subj-group><subj-group><subject>Neurology</subject></subj-group></subj-group></article-categories><title-group><article-title>Comprehensive Research Synopsis and Systematic Meta-Analyses in Parkinson's Disease Genetics: The PDGene Database</article-title><alt-title alt-title-type="running-head">The PDGene Database</alt-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Lill</surname><given-names>Christina M.</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="aff" rid="aff2"><sup>2</sup></xref><xref ref-type="aff" rid="aff3"><sup>3</sup></xref><xref ref-type="aff" rid="aff4"><sup>4</sup></xref></contrib><contrib contrib-type="author"><name><surname>Roehr</surname><given-names>Johannes T.</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="aff" 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contrib-type="author"><name><surname>Meissner</surname><given-names>Esther</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author"><name><surname>Zauft</surname><given-names>Ute</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author"><name><surname>Allen</surname><given-names>Nicole C.</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author"><name><surname>Liu</surname><given-names>Tian</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="aff" rid="aff10"><sup>10</sup></xref></contrib><contrib contrib-type="author"><name><surname>Schilling</surname><given-names>Marcel</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="aff" rid="aff5"><sup>5</sup></xref></contrib><contrib contrib-type="author"><name><surname>Anderson</surname><given-names>Kari 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contrib-type="author"><name><surname>DeStefano</surname><given-names>Anita L.</given-names></name><xref ref-type="aff" rid="aff19"><sup>19</sup></xref><xref ref-type="aff" rid="aff20"><sup>20</sup></xref></contrib><contrib contrib-type="author"><name><surname>Do</surname><given-names>Chuong B.</given-names></name><xref ref-type="aff" rid="aff21"><sup>21</sup></xref></contrib><contrib contrib-type="author"><name><surname>Eriksson</surname><given-names>Nicholas</given-names></name><xref ref-type="aff" rid="aff21"><sup>21</sup></xref></contrib><contrib contrib-type="author"><name><surname>Factor</surname><given-names>Stewart A.</given-names></name><xref ref-type="aff" rid="aff22"><sup>22</sup></xref></contrib><contrib contrib-type="author"><name><surname>Farrer</surname><given-names>Matthew J.</given-names></name><xref ref-type="aff" rid="aff23"><sup>23</sup></xref></contrib><contrib contrib-type="author"><name><surname>Foroud</surname><given-names>Tatiana</given-names></name><xref ref-type="aff" rid="aff24"><sup>24</sup></xref></contrib><contrib contrib-type="author"><name><surname>Gasser</surname><given-names>Thomas</given-names></name><xref ref-type="aff" rid="aff13"><sup>13</sup></xref><xref ref-type="aff" rid="aff14"><sup>14</sup></xref></contrib><contrib contrib-type="author"><name><surname>Hamza</surname><given-names>Taye</given-names></name><xref ref-type="aff" rid="aff25"><sup>25</sup></xref></contrib><contrib contrib-type="author"><name><surname>Hardy</surname><given-names>John A.</given-names></name><xref ref-type="aff" rid="aff26"><sup>26</sup></xref></contrib><contrib contrib-type="author"><name><surname>Heutink</surname><given-names>Peter</given-names></name><xref ref-type="aff" rid="aff27"><sup>27</sup></xref></contrib><contrib contrib-type="author"><name><surname>Hill-Burns</surname><given-names>Erin M.</given-names></name><xref ref-type="aff" rid="aff25"><sup>25</sup></xref></contrib><contrib 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ref-type="aff" rid="aff19"><sup>19</sup></xref></contrib><contrib contrib-type="author"><name><surname>Nalls</surname><given-names>Michael A.</given-names></name><xref ref-type="aff" rid="aff32"><sup>32</sup></xref></contrib><contrib contrib-type="author"><name><surname>Pankratz</surname><given-names>Nathan</given-names></name><xref ref-type="aff" rid="aff24"><sup>24</sup></xref></contrib><contrib contrib-type="author"><name><surname>Payami</surname><given-names>Haydeh</given-names></name><xref ref-type="aff" rid="aff25"><sup>25</sup></xref></contrib><contrib contrib-type="author"><name><surname>Satake</surname><given-names>Wataru</given-names></name><xref ref-type="aff" rid="aff33"><sup>33</sup></xref></contrib><contrib contrib-type="author"><name><surname>Scott</surname><given-names>William K.</given-names></name><xref ref-type="aff" rid="aff12"><sup>12</sup></xref></contrib><contrib contrib-type="author"><name><surname>Sharma</surname><given-names>Manu</given-names></name><xref ref-type="aff" rid="aff13"><sup>13</sup></xref><xref ref-type="aff" rid="aff14"><sup>14</sup></xref></contrib><contrib contrib-type="author"><name><surname>Singleton</surname><given-names>Andrew B.</given-names></name><xref ref-type="aff" rid="aff32"><sup>32</sup></xref></contrib><contrib contrib-type="author"><name><surname>Stefansson</surname><given-names>Kari</given-names></name><xref ref-type="aff" rid="aff34"><sup>34</sup></xref></contrib><contrib contrib-type="author"><name><surname>Toda</surname><given-names>Tatsushi</given-names></name><xref ref-type="aff" rid="aff33"><sup>33</sup></xref></contrib><contrib contrib-type="author"><name><surname>Tung</surname><given-names>Joyce Y.</given-names></name><xref ref-type="aff" rid="aff21"><sup>21</sup></xref></contrib><contrib contrib-type="author"><name><surname>Vance</surname><given-names>Jeffery</given-names></name><xref ref-type="aff" rid="aff12"><sup>12</sup></xref></contrib><contrib contrib-type="author"><name><surname>Wood</surname><given-names>Nick W.</given-names></name><xref ref-type="aff" rid="aff35"><sup>35</sup></xref><xref ref-type="aff" rid="aff36"><sup>36</sup></xref></contrib><contrib contrib-type="author"><name><surname>Zabetian</surname><given-names>Cyrus P.</given-names></name><xref ref-type="aff" rid="aff37"><sup>37</sup></xref></contrib><contrib contrib-type="author"><collab>23andMe, The Genetic Epidemiology of Parkinson's Disease (GEO-PD) Consortium</collab><xref ref-type="author-notes" rid="fn1"><sup>¶</sup></xref></contrib><contrib contrib-type="author"><collab>The International Parkinson's Disease Genomics Consortium (IPDGC)</collab><xref ref-type="author-notes" rid="fn1"><sup>¶</sup></xref></contrib><contrib contrib-type="author"><collab>The Parkinson's Disease GWAS Consortium</collab><xref ref-type="author-notes" rid="fn1"><sup>¶</sup></xref></contrib><contrib contrib-type="author"><collab>The Wellcome Trust Case Control Consortium 2 (WTCCC2)</collab><xref ref-type="author-notes" rid="fn1"><sup>¶</sup></xref></contrib><contrib contrib-type="author"><name><surname>Young</surname><given-names>Peter</given-names></name><xref ref-type="aff" rid="aff4"><sup>4</sup></xref></contrib><contrib contrib-type="author"><name><surname>Tanzi</surname><given-names>Rudolph E.</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author"><name><surname>Khoury</surname><given-names>Muin J.</given-names></name><xref ref-type="aff" rid="aff38"><sup>38</sup></xref></contrib><contrib contrib-type="author"><name><surname>Zipp</surname><given-names>Frauke</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author"><name><surname>Lehrach</surname><given-names>Hans</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author"><name><surname>Ioannidis</surname><given-names>John P. A.</given-names></name><xref ref-type="aff" rid="aff7"><sup>7</sup></xref><xref ref-type="aff" rid="aff39"><sup>39</sup></xref><xref ref-type="aff" rid="aff40"><sup>40</sup></xref><xref ref-type="aff" rid="aff41"><sup>41</sup></xref></contrib><contrib contrib-type="author"><name><surname>Bertram</surname><given-names>Lars</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="aff" rid="aff2"><sup>2</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib></contrib-group><aff id="aff1"><label>1</label><addr-line>Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany</addr-line></aff><aff id="aff2"><label>2</label><addr-line>Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, United States of America</addr-line></aff><aff id="aff3"><label>3</label><addr-line>Department of Neurology, Medical Center of the Johannes Gutenberg-University, Mainz, Germany</addr-line></aff><aff id="aff4"><label>4</label><addr-line>Department of Neurology, University Hospital, Münster, Germany</addr-line></aff><aff id="aff5"><label>5</label><addr-line>Department of Mathematics and Computer Science, Free University, Berlin, Germany</addr-line></aff><aff id="aff6"><label>6</label><addr-line>Institute for Behavioral Genetics, University of Colorado, Boulder, Colorado, United States of America</addr-line></aff><aff id="aff7"><label>7</label><addr-line>Clinical and Molecular Epidemiology Unit, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece</addr-line></aff><aff id="aff8"><label>8</label><addr-line>Centre for Diabetes and Endocrinology, Royal Berkshire Hospital, Reading, United Kingdom</addr-line></aff><aff id="aff9"><label>9</label><addr-line>Oxford Centre for Diabetes, Endocrinology, and Metabolism, Churchill Hospital, University of Oxford, Oxford, United Kingdom</addr-line></aff><aff id="aff10"><label>10</label><addr-line>Max Planck Institute for Human Development, Berlin, Germany</addr-line></aff><aff id="aff11"><label>11</label><addr-line>Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America</addr-line></aff><aff id="aff12"><label>12</label><addr-line>John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America</addr-line></aff><aff id="aff13"><label>13</label><addr-line>Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany</addr-line></aff><aff id="aff14"><label>14</label><addr-line>DZNE, German Center for Neurodegenerative Diseases, Tübingen, Germany</addr-line></aff><aff id="aff15"><label>15</label><addr-line>INSERM, UMR_S975, Paris, France</addr-line></aff><aff id="aff16"><label>16</label><addr-line>Université Pierre et Marie Curie-Paris, Centre de Recherche de l'Institut du Cerveau et de la Moelle épinière, UMR-S975, Paris, France</addr-line></aff><aff id="aff17"><label>17</label><addr-line>CNRS, UMR 7225, Paris, France</addr-line></aff><aff id="aff18"><label>18</label><addr-line>AP-HP, Pitié-Salpêtrière Hospital, Department of Genetics and Cytogenetics, Paris, France</addr-line></aff><aff id="aff19"><label>19</label><addr-line>Department of Neurology, Boston University School of Medicine, Boston University, Boston, Massachusetts, United States of America</addr-line></aff><aff id="aff20"><label>20</label><addr-line>Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America</addr-line></aff><aff id="aff21"><label>21</label><addr-line>23andMe, Mountain View, California, United States of America</addr-line></aff><aff id="aff22"><label>22</label><addr-line>Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, United States of America</addr-line></aff><aff id="aff23"><label>23</label><addr-line>Department of Medical Genetics, University of British Columbia, Vancouver, Canada</addr-line></aff><aff id="aff24"><label>24</label><addr-line>Indiana University School of Medicine, Indianapolis, Indiana, United States of America</addr-line></aff><aff id="aff25"><label>25</label><addr-line>New York State Department of Health Wadsworth Center, Albany, New York, United States of America</addr-line></aff><aff id="aff26"><label>26</label><addr-line>Department of Molecular Neuroscience, UCL Institute of Neurology, University College London, London, United Kingdom</addr-line></aff><aff id="aff27"><label>27</label><addr-line>Department of Clinical Genetics, Section of Medical Genomics, VU University Medical Centre, Amsterdam, The Netherlands</addr-line></aff><aff id="aff28"><label>28</label><addr-line>Section of Clinical and Molecular Neurogenetics, Department of Neurology, University of Lübeck, Lübeck, Germany</addr-line></aff><aff id="aff29"><label>29</label><addr-line>Department of Neurology, NorthShore University Health System, Evanston, Illinois, United States of America</addr-line></aff><aff id="aff30"><label>30</label><addr-line>INSERM UMR 1043, CPTP, Toulouse, France</addr-line></aff><aff id="aff31"><label>31</label><addr-line>Paul Sabatier University, Toulouse, France</addr-line></aff><aff id="aff32"><label>32</label><addr-line>Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></aff><aff id="aff33"><label>33</label><addr-line>Division of Neurology/Molecular Brain Science, Kobe University Graduate School of Medicine, Kobe, Japan</addr-line></aff><aff id="aff34"><label>34</label><addr-line>deCODE genetics, Reykjavik, Iceland</addr-line></aff><aff id="aff35"><label>35</label><addr-line>UCL Genetics Institute, University College London, London, United Kingdom</addr-line></aff><aff id="aff36"><label>36</label><addr-line>Department of Molecular Neuroscience, UCL Institute of Neurology, University College London, London, United Kingdom</addr-line></aff><aff id="aff37"><label>37</label><addr-line>VA Puget Sound Health Care System and Department of Neurology, University of Washington, Seattle, Washington, United States of America</addr-line></aff><aff id="aff38"><label>38</label><addr-line>Office of Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America</addr-line></aff><aff id="aff39"><label>39</label><addr-line>Biomedical Research Institute, Foundation for Research and Technology–Hellas, Ioannina, Greece</addr-line></aff><aff id="aff40"><label>40</label><addr-line>Center for Genetic Epidemiology and Modeling and Tufts Clinical and Translational Science Institute, Tufts University School of Medicine, Boston, Massachusetts, United States of America</addr-line></aff><aff id="aff41"><label>41</label><addr-line>Stanford Prevention Research Center, Department of Medicine and Department of Health Research and Policy, Stanford University School of Medicine, Stanford, California, United States of America</addr-line></aff><contrib-group><contrib contrib-type="editor"><name><surname>Myers</surname><given-names>Amanda J.</given-names></name><role>Editor</role><xref ref-type="aff" rid="edit1"></xref></contrib></contrib-group><aff id="edit1">University of Miami, United States of America</aff><author-notes><corresp id="cor1">* E-mail: <email>lbertram@molgen.mpg.de</email></corresp><fn fn-type="con"><p>Conceived and designed the experiments: CM Lill, MB McQueen, JPA Ioannidis, L Bertram. Performed the experiments: CM Lill, JT Roehr, S Bagade, B-M Schjeide, E Meissner, U Zauft, NC Allen, KJ Anderson, G Beecham, D Berg, JM Biernacka, A Brice, AL DeStefano, CB Do, N Eriksson, SA Factor, MJ Farrer, T Foroud, T Gasser, T Hamza, JA Hardy, P Heutink, C Klein, JC Latourelle, DM Maraganore, ER Martin, M Martinez, RH Myers, H Payami, WK Scott, M Sharma, AB Singleton, K Stefansson, T Toda, JY Tung, J Vance, NW Wood, CP Zabetian, 23andMe, GEO-PD, IPDGC, Parkinson's Disease GWAS, WTCC2. Analyzed the data: CM Lill, JT Roehr, MB McQueen, FK Kavvoura, L Bertram. Wrote the paper: CM Lill, JPA Ioannidis, L Bertram. Helped write the manuscript: E Meissner, MJ Farrer, T Foroud, T Gasser, C Klein, DM Maraganore, H Payami, AB Singleton, M Sharma, F Zipp, H Lehrach. Helped analyze the data: S Bagade, T Liu, M Schilling, CB Do, N Eriksson, T Hamza, EM Hill-Burns, MA Nalls, N Pankratz, W Satake, M Sharma. Interpretation of results: CM Lill, JPA Ioannidis, L Bertram. Study coordination: CM Lill, T Foroud, JA Hardy, H Payami, AB Singleton, P Young, RE Tanzi, MJ Khoury, F Zipp, H Lehrach, JPA Ioannidis, L Bertram. Literature searches and data entry: CM Lill, S Bagade, B-M Schjeide, E Meissner, U Zauft, N Allen.</p></fn><fn id="fn1" fn-type="other"><p>¶ Memberships of the consortia are provided in Text S1.</p></fn></author-notes><pub-date pub-type="collection"><month>3</month><year>2012</year></pub-date><pub-date pub-type="epub"><day>15</day><month>3</month><year>2012</year></pub-date><volume>8</volume><issue>3</issue><elocation-id>e1002548</elocation-id><history><date date-type="received"><day>16</day><month>10</month><year>2011</year></date><date date-type="accepted"><day>5</day><month>1</month><year>2012</year></date></history><permissions><copyright-statement>This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.</copyright-statement><copyright-year>2012</copyright-year><license xlink:href="https://creativecommons.org/publicdomain/zero/1.0/"><license-p>This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.</license-p></license></permissions><abstract><p>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 (<italic>P</italic><5×10<sup>−8</sup>) association with disease risk: <italic>BST1</italic>, <italic>CCDC62/HIP1R</italic>, <italic>DGKQ/GAK</italic>, <italic>GBA</italic>, <italic>LRRK2</italic>, <italic>MAPT</italic>, <italic>MCCC1/LAMP3</italic>, PARK16, <italic>SNCA</italic>, <italic>STK39</italic>, and <italic>SYT11/RAB25</italic>. In addition, we identified novel evidence for genome-wide significant association with a polymorphism in <italic>ITGA8</italic> (rs7077361, OR 0.88, <italic>P</italic> = 1.3×10<sup>−8</sup>). All meta-analysis results are freely available on a dedicated online database (<ext-link ext-link-type="uri" xlink:href="http://www.pdgene.org">www.pdgene.org</ext-link>), 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.</p></abstract><abstract abstract-type="summary"><title>Author Summary</title><p>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”: <ext-link ext-link-type="uri" xlink:href="http://www.pdgene.org">http://www.pdgene.org</ext-link>) 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 (<italic>P</italic><5×10<sup>−8</sup>; a.k.a. genome-wide significance) association with risk for PD: <italic>BST1</italic>, <italic>CCDC62/HIP1R</italic>, <italic>DGKQ/GAK</italic>, <italic>GBA</italic>, <italic>LRRK2</italic>, <italic>MAPT</italic>, <italic>MCCC1/LAMP3</italic>, PARK16, <italic>SNCA</italic>, <italic>STK39</italic>, <italic>SYT11/RAB25</italic>. In addition and purely by data-mining, we identified one novel PD susceptibility locus in a gene called <italic>ITGA8</italic> (rs7077361, <italic>P</italic> = 1.3×10<sup>−8</sup>). 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.</p></abstract><counts><page-count count="10"></page-count></counts></article-meta></front><body><sec id="s1"><title>Introduction</title><p>Parkinson's disease (PD) is the second most common neurodegenerative disease with a prevalence of ∼1% over 60 years of age <xref rid="pgen.1002548-deLau1" ref-type="bibr">[1]</xref>. Approximately 5–10% of the patients show an autosomal dominant or recessive mode of inheritance, and several causative genes have been identified, e.g. <italic>SNCA</italic>, <italic>LRRK2</italic>, <italic>PARK2</italic>, and <italic>PINK1</italic> (for review see ref. <xref rid="pgen.1002548-Hardy1" ref-type="bibr">[2]</xref>). Recently, two other novel autosomal dominant PD genes, <italic>VPS35</italic> and <italic>EIF4G1</italic><xref rid="pgen.1002548-VilarioGell1" ref-type="bibr">[3]</xref>–<xref rid="pgen.1002548-ChartierHarlin1" ref-type="bibr">[5]</xref>, have been identified, the former via application of next-generation sequencing techniques. It can be anticipated that causal mutations in additional genes will emerge within the next years. However, the vast majority of patients suffer from non-Mendelian forms of PD, which are likely caused by the combined effects of genetic and environmental factors. In order to decipher the genetic architecture underlying PD susceptibility, more than 800 genetic association studies have been performed over the past 20 years. While early candidate gene studies and subsequent meta-analyses provided conclusive evidence showing that polymorphisms in <italic>SNCA</italic><xref rid="pgen.1002548-Maraganore1" ref-type="bibr">[6]</xref> (encoding alpha-synuclein), <italic>LRRK2</italic><xref rid="pgen.1002548-Zabetian1" ref-type="bibr">[7]</xref> (leucine-rich repeat kinase 2), <italic>MAPT</italic><xref rid="pgen.1002548-Goris1" ref-type="bibr">[8]</xref> (microtubule-associated protein tau), and <italic>GBA</italic><xref rid="pgen.1002548-Sidransky1" ref-type="bibr">[9]</xref> (acid beta-glucosidase) significantly impact PD susceptibility, most association studies in the field provided inconclusive or even conflicting results.</p><p>During the last few years, genome-wide association studies (GWAS) <xref rid="pgen.1002548-Maraganore2" ref-type="bibr">[10]</xref>–<xref rid="pgen.1002548-SimnSnchez2" ref-type="bibr">[19]</xref> have postulated additional PD loci. While the early GWAS and a GWAS-meta-analysis <xref rid="pgen.1002548-Evangelou1" ref-type="bibr">[20]</xref> were of limited sample sizes and yielded mostly inconsistent results, more recent studies have identified a number of loci that were independently confirmed in follow-up studies (e.g. <italic>GAK</italic>, <italic>BST1</italic>, and PARK16, see <xref ref-type="table" rid="pgen-1002548-t001">Table 1</xref> for all proposed GWAS findings across GWAS publications). Very recently, a GWAS meta-analysis <xref rid="pgen.1002548-Nalls1" ref-type="bibr">[21]</xref> implicated several other new putative PD loci which currently await further validation. Despite this progress, approximately 40% or more of the population-attributable risk probably remains unexplained by today's most promising PD loci <xref rid="pgen.1002548-Nalls1" ref-type="bibr">[21]</xref>. To this end, genetic association studies remain one of the mainstays of PD genetics research. However, GWAS and other large-scale association studies typically only highlight the most promising results and often do not provide data on variants showing suggestive evidence for association, or previously implied variants that could not be confirmed in the GWAS setting. As a result, the cumulative genetic evidence in favor of or against association with certain variants in the PD field is becoming increasingly difficult to follow, evaluate and interpret. To address this problem, we have comprehensively collected, catalogued and systematically meta-analyzed the data from all genetic association studies published in the field of non-Mendelian PD, including GWAS, and made all results publicly available on a regularly updated online database, “PDGene” (<ext-link ext-link-type="uri" xlink:href="http://www.pdgene.org">http://www.pdgene.org</ext-link>).</p><table-wrap id="pgen-1002548-t001" position="float"><object-id pub-id-type="doi">10.1371/journal.pgen.1002548.t001</object-id><label>Table 1</label><caption><title>Overview of genome-wide association studies (GWAS) published in PD until March 31, 2011.</title></caption><alternatives><graphic id="pgen-1002548-t001-1" xlink:href="pgen.1002548.t001"></graphic><table frame="hsides" rules="groups"><colgroup span="1"><col align="left" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col></colgroup><thead><tr><td align="left" rowspan="1" colspan="1">GWAS</td><td align="left" rowspan="1" colspan="1">Design GWAS (Follow-up)</td><td align="left" rowspan="1" colspan="1">Population GWAS (Follow-up)</td><td align="left" rowspan="1" colspan="1"># SNPs</td><td align="left" rowspan="1" colspan="1"># PD GWAS (Follow-up)</td><td align="left" rowspan="1" colspan="1"># CTRL GWAS (Follow-up)</td><td align="left" rowspan="1" colspan="1">“Featured” genetic loci</td></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1">Maraganore, 2005 (ref. 9)</td><td align="left" rowspan="1" colspan="1">Family-based (case-control)</td><td align="left" rowspan="1" colspan="1">USA-LEAPS (USA)</td><td align="left" rowspan="1" colspan="1">198,345</td><td align="left" rowspan="1" colspan="1">443 (332)</td><td align="left" rowspan="1" colspan="1">443 (332)</td><td align="left" rowspan="1" colspan="1"><italic>CDCP2</italic>, <italic>GALNT3</italic>, <italic>GWA_2q36.3</italic>, <italic>GWA_4q28.1</italic>, <italic>GWA_4q28.3</italic>, <italic>GWA_5p15.32</italic>, <italic>GWA_7p14.2</italic>, <italic>GWA_10q21.1</italic>, <italic>PASD1</italic>, <italic>PRDM2</italic>, <italic>SEMA5A</italic></td></tr><tr><td align="left" rowspan="1" colspan="1">Fung, 2006 (ref. 10)</td><td align="left" rowspan="1" colspan="1">Case-control (-)</td><td align="left" rowspan="1" colspan="1">USA-NINDS</td><td align="left" rowspan="1" colspan="1">408,803</td><td align="left" rowspan="1" colspan="1">267 (-)</td><td align="left" rowspan="1" colspan="1">270 (-)</td><td align="left" rowspan="1" colspan="1"><italic>BRDG</italic>, <italic>DLG2</italic>, <italic>GLT25D2</italic>, <italic>GWA_4q35.2</italic>, <italic>GWA_7p12</italic>, <italic>GWA_10q11.21</italic>, <italic>GWA_11q11</italic>, <italic>GWA_16q23.1</italic>, <italic>GWA_22q13</italic>, <italic>NEGR1</italic>, <italic>ULK2</italic>, <italic>ZNF313</italic></td></tr><tr><td align="left" rowspan="1" colspan="1">Pankratz, 2009 (ref. 11)</td><td align="left" rowspan="1" colspan="1">Case-control (-)</td><td align="left" rowspan="1" colspan="1">USA-PROGENI/GenePD (-)</td><td align="left" rowspan="1" colspan="1">328,189</td><td align="left" rowspan="1" colspan="1">857 (-)</td><td align="left" rowspan="1" colspan="1">867 (-)</td><td align="left" rowspan="1" colspan="1"><bold><italic>DGKQ/GAK</italic></bold>, <italic>GPRIN3</italic>, <bold><italic>MAPT</italic></bold>, <bold><italic>SNCA</italic></bold></td></tr><tr><td align="left" rowspan="1" colspan="1">Simon-Sanchez, 2009 (ref. 12)</td><td align="left" rowspan="1" colspan="1">Case-control (case-control)</td><td align="left" rowspan="1" colspan="1">USA-NINDS, Germany(USA, Germany, UK)</td><td align="left" rowspan="1" colspan="1">463,185</td><td align="left" rowspan="1" colspan="1">1,745 (3,452)</td><td align="left" rowspan="1" colspan="1">4,047 (4,756)</td><td align="left" rowspan="1" colspan="1"><bold><italic>LRRK2</italic></bold>, <bold><italic>MAPT</italic></bold>, <bold>PARK16</bold>, <bold><italic>SNCA</italic></bold></td></tr><tr><td align="left" rowspan="1" colspan="1">Satake, 2009 (ref. 13)</td><td align="left" rowspan="1" colspan="1">Case-control (case-control)</td><td align="left" rowspan="1" colspan="1">Japan (Japan)</td><td align="left" rowspan="1" colspan="1">435,470</td><td align="left" rowspan="1" colspan="1">1,078 (993)</td><td align="left" rowspan="1" colspan="1">2,628 (15,753)</td><td align="left" rowspan="1" colspan="1"><bold><italic>BST1</italic></bold>, <bold><italic>LRRK2</italic></bold>, <bold>PARK16</bold>, <bold><italic>SNCA</italic></bold></td></tr><tr><td align="left" rowspan="1" colspan="1">Edwards, 2010 (ref. 14)</td><td align="left" rowspan="1" colspan="1">Case-control (-)</td><td align="left" rowspan="1" colspan="1">USA-HIHG (-)</td><td align="left" rowspan="1" colspan="1">491,376</td><td align="left" rowspan="1" colspan="1">604 (-)</td><td align="left" rowspan="1" colspan="1">619 (-)</td><td align="left" rowspan="1" colspan="1"><bold><italic>MAPT</italic></bold>, <bold><italic>SNCA</italic></bold></td></tr><tr><td align="left" rowspan="1" colspan="1">Hamza, 2010 (ref. 15)</td><td align="left" rowspan="1" colspan="1">Case-control (-)</td><td align="left" rowspan="1" colspan="1">USA-NGRC (-)</td><td align="left" rowspan="1" colspan="1">811,597</td><td align="left" rowspan="1" colspan="1">2,000 (-)</td><td align="left" rowspan="1" colspan="1">1,986 (-)</td><td align="left" rowspan="1" colspan="1"><bold><italic>GAK/DGKQ</italic></bold><italic>, HLA</italic> locus, <bold><italic>MAPT</italic></bold>, <bold><italic>SNCA</italic></bold></td></tr><tr><td align="left" rowspan="1" colspan="1">Spencer, 2011 (ref. 16)</td><td align="left" rowspan="1" colspan="1">Case-control (case-control)</td><td align="left" rowspan="1" colspan="1">UK-WTCCC2 (France)</td><td align="left" rowspan="1" colspan="1">1,733,533</td><td align="left" rowspan="1" colspan="1">1,705 (1,039)</td><td align="left" rowspan="1" colspan="1">5,175 (1,984)</td><td align="left" rowspan="1" colspan="1"><bold><italic>BST1</italic></bold><bold>, </bold><bold><italic>GAK/DGKQ</italic></bold><bold>, </bold><bold><italic>MAPT</italic></bold><bold>, PARK16, </bold><bold><italic>SNCA</italic></bold></td></tr><tr><td align="left" rowspan="1" colspan="1">Saad, 2011 (ref. 17)</td><td align="left" rowspan="1" colspan="1">Case-control (case-control)</td><td align="left" rowspan="1" colspan="1">France (UK-WTCCC2, Australia)</td><td align="left" rowspan="1" colspan="1">492,929</td><td align="left" rowspan="1" colspan="1">1,039 (3,232)</td><td align="left" rowspan="1" colspan="1">1,984 (7,064)</td><td align="left" rowspan="1" colspan="1"><bold><italic>BST1</italic></bold><italic>, GWA_12q24, </italic><bold><italic>SNCA</italic></bold></td></tr><tr><td align="left" rowspan="1" colspan="1">Simon-Sanchez, 2011 (ref. 18)</td><td align="left" rowspan="1" colspan="1">Case-control (case-control)</td><td align="left" rowspan="1" colspan="1">Netherlands</td><td align="left" rowspan="1" colspan="1">514,799</td><td align="left" rowspan="1" colspan="1">772 (-)</td><td align="left" rowspan="1" colspan="1">2024 (-)</td><td align="left" rowspan="1" colspan="1"><bold><italic>BST1</italic></bold>, <italic>HLA</italic> locus, <bold><italic>GAK/DGKQ</italic></bold><bold>, </bold><bold><italic>MAPT</italic></bold><bold>, </bold><bold><italic>SNCA</italic></bold></td></tr></tbody></table></alternatives><table-wrap-foot><fn id="nt101"><label></label><p>The overview is based on content on the PDGene website (<ext-link ext-link-type="uri" xlink:href="http://www.pdgene.org">http://www.pdgene.org</ext-link>; current on March 31<sup>st</sup>, 2011). Studies are listed in order of publication date. ‘# PD GWAS’ and ‘# CTRL GWAS’ refers to sample sizes used in the initial GWAS datasets, whereas ‘Follow-up’ refers to the total number of replication samples where applicable. ‘Featured genes’ are those genes/loci that were declared as ‘associated’ in the original publication; note that criteria for declaring association varies across studies. Genetic loci in bold font denote genes showing genome-wide significant results (<italic>P</italic><5×10<sup>−8</sup>) in the PDGene meta-analyses.</p></fn></table-wrap-foot></table-wrap></sec><sec id="s2"><title>Results</title><sec id="s2a"><title>Database content</title><p>The results of this research synopsis are based on a freeze of the PDGene database content on March 31<sup>st</sup> 2011 (available upon request from the authors). At that time, PDGene included details on 828 individual studies across more than 50 different countries and six continents reporting on 3,382 polymorphisms in 890 genetic loci. Data for more than 2,000 SNPs were supplemented by results derived from up to three publicly available GWAS datasets <xref rid="pgen.1002548-Maraganore2" ref-type="bibr">[10]</xref>, <xref rid="pgen.1002548-Pankratz1" ref-type="bibr">[12]</xref>, <xref rid="pgen.1002548-SimnSnchez1" ref-type="bibr">[13]</xref> following extensive quality control and imputation. Ultimately, this procedure yielded a total of 867 polymorphisms across ∼300 genetic loci that met our criteria for meta-analysis (see <xref ref-type="sec" rid="s4">Methods</xref>). Additional independent GWAS data for 147 SNPs yielding <italic>P</italic> values of ≤0.1 in these initial meta-analyses were provided by researchers of all remaining currently published Caucasian GWAS datasets <xref rid="pgen.1002548-SimnSnchez1" ref-type="bibr">[13]</xref>, <xref rid="pgen.1002548-Edwards1" ref-type="bibr">[15]</xref>–<xref rid="pgen.1002548-SimnSnchez2" ref-type="bibr">[19]</xref>, <xref rid="pgen.1002548-Do1" ref-type="bibr">[22]</xref>. Following the identification of genome-wide significant association with an intronic SNP (rs7077361) in <italic>ITGA8</italic> after addition of these data, we obtained additional data from the same GWAS datasets on ∼1,400 SNPs in the chromosomal region encompassing <italic>ITGA8</italic> (chr10:15346353–15801533, hg18). Finally, independent replication data in Caucasian and Asian populations from the GEO-PD consortium <xref rid="pgen.1002548-Sharma1" ref-type="bibr">[23]</xref> generated for ten recently described PD loci <xref rid="pgen.1002548-Nalls1" ref-type="bibr">[21]</xref> were made available for inclusion. As a result, we were able to substantially increase the sample size (up to 16,452 PD cases and 48,810 controls) for a large number of some of the most promising PD loci. For instance, we were able to add data from up to 48,861 previously not analyzed combined cases and controls to meta-analyses of some of the recently proposed PD loci <xref rid="pgen.1002548-Nalls1" ref-type="bibr">[21]</xref> (median sample size 14,896, see <xref ref-type="table" rid="pgen-1002548-t002">Table 2</xref> and <xref ref-type="supplementary-material" rid="pgen.1002548.s005">Table S1</xref> for details). In addition to these focused analyses, PDGene displays meta-analysis results for more than seven million additional SNPs originating from up to three publicly available GWAS datasets <xref rid="pgen.1002548-Maraganore2" ref-type="bibr">[10]</xref>, <xref rid="pgen.1002548-Pankratz1" ref-type="bibr">[12]</xref>, <xref rid="pgen.1002548-SimnSnchez1" ref-type="bibr">[13]</xref>. The results are available online (e.g. as summarized in <ext-link ext-link-type="uri" xlink:href="http://www.pdgene.org/largescalemeta.asp">http://www.pdgene.org/largescalemeta.asp</ext-link>), where they are cross-linked to a customized and fully browsable track on the UCSC Genome Browser.</p><table-wrap id="pgen-1002548-t002" position="float"><object-id pub-id-type="doi">10.1371/journal.pgen.1002548.t002</object-id><label>Table 2</label><caption><title>Genome-wide significant summary meta-analysis results of the PDGene database in populations of Caucasian and Asian decent.</title></caption><alternatives><graphic id="pgen-1002548-t002-2" xlink:href="pgen.1002548.t002"></graphic><table frame="hsides" rules="groups"><colgroup span="1"><col align="left" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col></colgroup><thead><tr><td colspan="12" align="left" rowspan="1">Caucasian ethnicity</td></tr><tr><td align="left" rowspan="1" colspan="1">Locus</td><td align="left" rowspan="1" colspan="1">Polymorphism</td><td align="left" rowspan="1" colspan="1">Location (hg18)</td><td align="left" rowspan="1" colspan="1">MAF</td><td align="left" rowspan="1" colspan="1">Allele contrast</td><td align="left" rowspan="1" colspan="1">N datasets</td><td align="left" rowspan="1" colspan="1">N samples</td><td align="left" rowspan="1" colspan="1">OR (95% CI)</td><td align="left" rowspan="1" colspan="1"><italic>P</italic>-value</td><td align="left" rowspan="1" colspan="1"><italic>I</italic><sup>2</sup> (95% CI)</td><td align="left" rowspan="1" colspan="1">HuGENet</td><td align="left" rowspan="1" colspan="1">BF</td></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1"><italic>GBA</italic></td><td align="left" rowspan="1" colspan="1">N370S</td><td align="left" rowspan="1" colspan="1">chr1:153451576</td><td align="left" rowspan="1" colspan="1">0.01</td><td align="left" rowspan="1" colspan="1">G vs. A</td><td align="left" rowspan="1" colspan="1">15</td><td align="left" rowspan="1" colspan="1">44,851</td><td align="left" rowspan="1" colspan="1">3.51 (2.55–4.83)</td><td align="left" rowspan="1" colspan="1">1.44×10<sup>−14</sup></td><td align="left" rowspan="1" colspan="1">38 (0–66)</td><td align="left" rowspan="1" colspan="1">A</td><td align="left" rowspan="1" colspan="1">6.6</td></tr><tr><td align="left" rowspan="1" colspan="1"><italic>SYT11/RAB25</italic></td><td align="left" rowspan="1" colspan="1">chr1:154105678</td><td align="left" rowspan="1" colspan="1">chr1:154105678</td><td align="left" rowspan="1" colspan="1">0.02</td><td align="left" rowspan="1" colspan="1">T vs. C</td><td align="left" rowspan="1" colspan="1">6</td><td align="left" rowspan="1" colspan="1">17,300</td><td align="left" rowspan="1" colspan="1">1.73 (1.48–2.02)</td><td align="left" rowspan="1" colspan="1">2.35×10<sup>−12</sup></td><td align="left" rowspan="1" colspan="1">0 (0–52)</td><td align="left" rowspan="1" colspan="1">B*</td><td align="left" rowspan="1" colspan="1">8.2</td></tr><tr><td align="left" rowspan="1" colspan="1">PARK16</td><td align="left" rowspan="1" colspan="1">rs947211</td><td align="left" rowspan="1" colspan="1">chr1:204019288</td><td align="left" rowspan="1" colspan="1">0.23</td><td align="left" rowspan="1" colspan="1">A vs. G</td><td align="left" rowspan="1" colspan="1">12</td><td align="left" rowspan="1" colspan="1">69,262</td><td align="left" rowspan="1" colspan="1">0.91 (0.88–0.94)</td><td align="left" rowspan="1" colspan="1">8.00×10<sup>−10</sup></td><td align="left" rowspan="1" colspan="1">0 (0–66)</td><td align="left" rowspan="1" colspan="1">A</td><td align="left" rowspan="1" colspan="1">6.8</td></tr><tr><td align="left" rowspan="1" colspan="1"><italic>STK39</italic></td><td align="left" rowspan="1" colspan="1">rs2390669</td><td align="left" rowspan="1" colspan="1">chr2:168800188</td><td align="left" rowspan="1" colspan="1">0.13</td><td align="left" rowspan="1" colspan="1">C vs. A</td><td align="left" rowspan="1" colspan="1">14</td><td align="left" rowspan="1" colspan="1">35,159</td><td align="left" rowspan="1" colspan="1">1.19 (1.12–1.25)</td><td align="left" rowspan="1" colspan="1">1.37×10<sup>−09</sup></td><td align="left" rowspan="1" colspan="1">18 (0–56)</td><td align="left" rowspan="1" colspan="1">A</td><td align="left" rowspan="1" colspan="1">4.9*</td></tr><tr><td align="left" rowspan="1" colspan="1"><italic>MCCC1/LAMP3</italic></td><td align="left" rowspan="1" colspan="1">rs11711441</td><td align="left" rowspan="1" colspan="1">chr3:184303969</td><td align="left" rowspan="1" colspan="1">0.14</td><td align="left" rowspan="1" colspan="1">A vs. G</td><td align="left" rowspan="1" colspan="1">25</td><td align="left" rowspan="1" colspan="1">46,502</td><td align="left" rowspan="1" colspan="1">0.86 (0.82–0.91)</td><td align="left" rowspan="1" colspan="1">9.20×10<sup>−10</sup></td><td align="left" rowspan="1" colspan="1">18 (0–50)</td><td align="left" rowspan="1" colspan="1">A</td><td align="left" rowspan="1" colspan="1">6.8</td></tr><tr><td align="left" rowspan="1" colspan="1"><italic>DGKQ</italic></td><td align="left" rowspan="1" colspan="1">rs11248060</td><td align="left" rowspan="1" colspan="1">chr4:954359</td><td align="left" rowspan="1" colspan="1">0.12</td><td align="left" rowspan="1" colspan="1">T vs. C</td><td align="left" rowspan="1" colspan="1">10</td><td align="left" rowspan="1" colspan="1">57,716</td><td align="left" rowspan="1" colspan="1">1.21 (1.15–1.27)</td><td align="left" rowspan="1" colspan="1">3.04×10<sup>−12</sup></td><td align="left" rowspan="1" colspan="1">11 (0–52)</td><td align="left" rowspan="1" colspan="1">A</td><td align="left" rowspan="1" colspan="1">9.2</td></tr><tr><td align="left" rowspan="1" colspan="1"><italic>BST1</italic></td><td align="left" rowspan="1" colspan="1">rs11724635</td><td align="left" rowspan="1" colspan="1">chr4:15346199</td><td align="left" rowspan="1" colspan="1">0.43</td><td align="left" rowspan="1" colspan="1">C vs. A</td><td align="left" rowspan="1" colspan="1">26</td><td align="left" rowspan="1" colspan="1">46,586</td><td align="left" rowspan="1" colspan="1">0.88 (0.84–0.91)</td><td align="left" rowspan="1" colspan="1">1.87×10<sup>−10</sup></td><td align="left" rowspan="1" colspan="1">43 (10–64)</td><td align="left" rowspan="1" colspan="1">A</td><td align="left" rowspan="1" colspan="1">7.5</td></tr><tr><td align="left" rowspan="1" colspan="1"><italic>SNCA</italic></td><td align="left" rowspan="1" colspan="1">rs356219</td><td align="left" rowspan="1" colspan="1">chr4:90856624</td><td align="left" rowspan="1" colspan="1">0.41</td><td align="left" rowspan="1" colspan="1">G vs. A</td><td align="left" rowspan="1" colspan="1">31</td><td align="left" rowspan="1" colspan="1">79,494</td><td align="left" rowspan="1" colspan="1">1.29 (1.25–1.33)</td><td align="left" rowspan="1" colspan="1">6.06×10<sup>−65</sup></td><td align="left" rowspan="1" colspan="1">16 (0–46)</td><td align="left" rowspan="1" colspan="1">A</td><td align="left" rowspan="1" colspan="1">61.0</td></tr><tr><td align="left" rowspan="1" colspan="1"><italic>ITGA8</italic></td><td align="left" rowspan="1" colspan="1">rs7077361</td><td align="left" rowspan="1" colspan="1">chr10:15601549</td><td align="left" rowspan="1" colspan="1">0.12</td><td align="left" rowspan="1" colspan="1">C vs. T</td><td align="left" rowspan="1" colspan="1">11</td><td align="left" rowspan="1" colspan="1">61,036</td><td align="left" rowspan="1" colspan="1">0.88 (0.84–0.92)</td><td align="left" rowspan="1" colspan="1">1.51×10<sup>−08</sup></td><td align="left" rowspan="1" colspan="1">0 (0–55)</td><td align="left" rowspan="1" colspan="1">A</td><td align="left" rowspan="1" colspan="1">5.7</td></tr><tr><td align="left" rowspan="1" colspan="1"><italic>LRRK2</italic></td><td align="left" rowspan="1" colspan="1">rs1491942</td><td align="left" rowspan="1" colspan="1">chr12:38907075</td><td align="left" rowspan="1" colspan="1">0.21</td><td align="left" rowspan="1" colspan="1">G vs. C</td><td align="left" rowspan="1" colspan="1">21</td><td align="left" rowspan="1" colspan="1">34,123</td><td align="left" rowspan="1" colspan="1">1.17 (1.13–1.22)</td><td align="left" rowspan="1" colspan="1">6.44×10<sup>−15</sup></td><td align="left" rowspan="1" colspan="1">0 (0–38)</td><td align="left" rowspan="1" colspan="1">A</td><td align="left" rowspan="1" colspan="1">11.8</td></tr><tr><td align="left" rowspan="1" colspan="1"><italic>CCDC62/HIP1R</italic></td><td align="left" rowspan="1" colspan="1">rs10847864</td><td align="left" rowspan="1" colspan="1">chr12:121892551</td><td align="left" rowspan="1" colspan="1">0.39</td><td align="left" rowspan="1" colspan="1">T vs. G</td><td align="left" rowspan="1" colspan="1">23</td><td align="left" rowspan="1" colspan="1">38,367</td><td align="left" rowspan="1" colspan="1">1.15 (1.11–1.18)</td><td align="left" rowspan="1" colspan="1">4.37×10<sup>−17</sup></td><td align="left" rowspan="1" colspan="1">0 (0–35)</td><td align="left" rowspan="1" colspan="1">A</td><td align="left" rowspan="1" colspan="1">14.4</td></tr><tr><td align="left" rowspan="1" colspan="1"><italic>MAPT/STH</italic></td><td align="left" rowspan="1" colspan="1">H1H2</td><td align="left" rowspan="1" colspan="1">chr17:42131818–41149582</td><td align="left" rowspan="1" colspan="1">0.20</td><td align="left" rowspan="1" colspan="1">H2 vs. H1</td><td align="left" rowspan="1" colspan="1">37</td><td align="left" rowspan="1" colspan="1">50,389</td><td align="left" rowspan="1" colspan="1">0.78 (0.75–0.80)</td><td align="left" rowspan="1" colspan="1">7.97×10<sup>−52</sup></td><td align="left" rowspan="1" colspan="1">0 (0–29)</td><td align="left" rowspan="1" colspan="1">A</td><td align="left" rowspan="1" colspan="1">48.1</td></tr></tbody></table><table frame="hsides" rules="groups"><colgroup span="1"><col align="left" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col></colgroup><thead><tr><td colspan="12" align="left" rowspan="1">Asian ethnicity</td></tr><tr><td align="left" rowspan="1" colspan="1">Locus</td><td align="left" rowspan="1" colspan="1">Polymorphism</td><td align="left" rowspan="1" colspan="1">Location (hg18)</td><td align="left" rowspan="1" colspan="1">MAF</td><td align="left" rowspan="1" colspan="1">Allele contrast</td><td align="left" rowspan="1" colspan="1">N datasets</td><td align="left" rowspan="1" colspan="1">N samples</td><td align="left" rowspan="1" colspan="1">OR (95% CI)</td><td align="left" rowspan="1" colspan="1"><italic>P</italic>-value</td><td align="left" rowspan="1" colspan="1"><italic>I</italic><sup>2</sup> (95% CI)</td><td align="left" rowspan="1" colspan="1">HuGENet</td><td align="left" rowspan="1" colspan="1">BF</td></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1">PARK16</td><td align="left" rowspan="1" colspan="1">rs823156</td><td align="left" rowspan="1" colspan="1">chr1:204031263</td><td align="left" rowspan="1" colspan="1">0.17</td><td align="left" rowspan="1" colspan="1">G vs. A</td><td align="left" rowspan="1" colspan="1">5</td><td align="left" rowspan="1" colspan="1">22,870</td><td align="left" rowspan="1" colspan="1">0.74 (0.68–0.81)</td><td align="left" rowspan="1" colspan="1">2.09×10<sup>−12</sup></td><td align="left" rowspan="1" colspan="1">0 (0–58)</td><td align="left" rowspan="1" colspan="1">A</td><td align="left" rowspan="1" colspan="1">9.2</td></tr><tr><td align="left" rowspan="1" colspan="1"><italic>BST1</italic></td><td align="left" rowspan="1" colspan="1">rs4538475</td><td align="left" rowspan="1" colspan="1">chr4:15347035</td><td align="left" rowspan="1" colspan="1">0.38</td><td align="left" rowspan="1" colspan="1">G vs. A</td><td align="left" rowspan="1" colspan="1">3</td><td align="left" rowspan="1" colspan="1">20,393</td><td align="left" rowspan="1" colspan="1">0.80 (0.75–0.86)</td><td align="left" rowspan="1" colspan="1">9.53×10<sup>−10</sup></td><td align="left" rowspan="1" colspan="1">0 (-)</td><td align="left" rowspan="1" colspan="1">A</td><td align="left" rowspan="1" colspan="1">6.8</td></tr><tr><td align="left" rowspan="1" colspan="1"><italic>SNCA</italic></td><td align="left" rowspan="1" colspan="1">rs6532194</td><td align="left" rowspan="1" colspan="1">chr4:90999925</td><td align="left" rowspan="1" colspan="1">0.40</td><td align="left" rowspan="1" colspan="1">T vs. C</td><td align="left" rowspan="1" colspan="1">5</td><td align="left" rowspan="1" colspan="1">22,844</td><td align="left" rowspan="1" colspan="1">1.29 (1.20–1.39)</td><td align="left" rowspan="1" colspan="1">4.91×10<sup>−11</sup></td><td align="left" rowspan="1" colspan="1">31 (0–74)</td><td align="left" rowspan="1" colspan="1">A</td><td align="left" rowspan="1" colspan="1">8.0</td></tr><tr><td align="left" rowspan="1" colspan="1"><italic>LRRK2</italic></td><td align="left" rowspan="1" colspan="1">rs34778348</td><td align="left" rowspan="1" colspan="1">chr12:39043595</td><td align="left" rowspan="1" colspan="1">0.04</td><td align="left" rowspan="1" colspan="1">A vs. G</td><td align="left" rowspan="1" colspan="1">13</td><td align="left" rowspan="1" colspan="1">10,441</td><td align="left" rowspan="1" colspan="1">2.23 (1.89–2.63)</td><td align="left" rowspan="1" colspan="1">2.97×10<sup>−21</sup></td><td align="left" rowspan="1" colspan="1">0 (0–53)</td><td align="left" rowspan="1" colspan="1">B*</td><td align="left" rowspan="1" colspan="1">15.2</td></tr></tbody></table></alternatives><table-wrap-foot><fn id="nt102"><label></label><p>Whenever multiple polymorphisms showed genome-wide significant association in the same locus, only the variant with the smallest <italic>P</italic>-value is listed here. Note that, overall, 103 PDGene meta-analyses results across the 12 loci listed above yield genome-wide significant evidence for association with PD. For a complete list of these as well as the non-genome-wide significant meta-analysis results performed for the datafreeze, see <xref ref-type="supplementary-material" rid="pgen.1002548.s005">Table S1</xref>. MAF = minor allele frequency in cases and controls combined; N = Number, OR = Odds Ratio; CI = confidence interval; <italic>I</italic><sup>2</sup> = estimate of percentage of between-study heterogeneity that is beyond chance. BF = Bayes factor. *Note that additional polymorphisms in these loci showing genome-wide significant association with PD yield are graded with “strong epidemiologic credibility” (grade A) according to the HuGENet criteria <xref rid="pgen.1002548-Ioannidis2" ref-type="bibr">[26]</xref>, <xref rid="pgen.1002548-Khoury1" ref-type="bibr">[27]</xref>, and a Bayes Factor >5 <xref rid="pgen.1002548-Ioannidis1" ref-type="bibr">[25]</xref>, respectively (see <xref ref-type="supplementary-material" rid="pgen.1002548.s005">Table S1</xref> for more details).</p></fn></table-wrap-foot></table-wrap></sec><sec id="s2b"><title>PDGene meta-analysis results</title><p>The PDGene meta-analyses of the 867 core polymorphisms were based on a median of 7,680 subjects (interquartile range 4,612–16,726). Additional meta-analyses were performed after stratification for Caucasian and Asian ancestry (for details on sample size and included ethnicities for individual meta-analyses see <xref ref-type="supplementary-material" rid="pgen.1002548.s005">Table S1</xref>). In addition, we also performed random-effects meta-analyses across all three publicly available GWAS datasets <xref rid="pgen.1002548-Maraganore2" ref-type="bibr">[10]</xref>, <xref rid="pgen.1002548-Pankratz1" ref-type="bibr">[12]</xref>, <xref rid="pgen.1002548-SimnSnchez1" ref-type="bibr">[13]</xref> following genotype imputation using data from the International HapMap Consortium and 1000 Genomes Project. Ultimately this yielded 7,123,920 SNPs that could be meta-analyzed across at least two GWAS datasets (see <xref ref-type="supplementary-material" rid="pgen.1002548.s001">Figure S1</xref> for a quantile-to-quantile plot of the GWAS-only meta-analyses). All 867 core meta-analysis results are available online on PDGene as forest plots, summarizing the relative contributions of each dataset to the most current summary effect estimate, and in the form of cumulative plots, illustrating how summary ORs evolve over time. All meta-analysis results are plotted in <xref ref-type="fig" rid="pgen-1002548-g001">Figure 1</xref> (green dots) alongside the GWAS-only meta-analysis results (black and grey dots).</p><fig id="pgen-1002548-g001" position="float"><object-id pub-id-type="doi">10.1371/journal.pgen.1002548.g001</object-id><label>Figure 1</label><caption><title>Manhattan plot of all meta-analysis results performed in PDGene.</title><p>This summary combines association results from 7,123,986 random-effects meta-analyses based on the March 31<sup>st</sup> 2011 datafreeze of the PDGene database. Results are plotted as −log<sub>10</sub><italic>P</italic>-values (y-axis) against physical chromosomal location (x-axis). Black and grey dots indicate results originating exclusively from the three fully publicly available GWAS datasets <xref rid="pgen.1002548-Maraganore2" ref-type="bibr">[10]</xref>, <xref rid="pgen.1002548-Pankratz1" ref-type="bibr">[12]</xref>, <xref rid="pgen.1002548-SimnSnchez1" ref-type="bibr">[13]</xref> (see <xref ref-type="sec" rid="s4">Methods</xref>), while green dots are based on a combination of smaller scale studies, supplemented by GWAS datasets (where applicable). Gene annotations are provided for genes highlighted in the main text.</p></caption><graphic xlink:href="pgen.1002548.g001"></graphic></fig><p>One-hundred-three meta-analyses across 12 genetic loci (<italic>BST1</italic>, <italic>CCDC62/HIP1R</italic>, <italic>DGKQ/GAK</italic>, <italic>GBA</italic>, <italic>ITGA8</italic>, <italic>LRRK2</italic>, <italic>MAPT</italic>, <italic>MCCC1/LAMP3</italic>, PARK16, <italic>SNCA</italic>, <italic>STK39</italic>, <italic>SYT11/RAB25</italic>) yielded summary ORs suggesting a genome-wide significant (<italic>P</italic>≤5×10<sup>−8</sup>) increase or decrease in PD risk in all ethnicities and/or after stratification for ethnic ancestry (<xref ref-type="table" rid="pgen-1002548-t002">Table 2</xref>, <xref ref-type="supplementary-material" rid="pgen.1002548.s005">Table S1</xref>, and <xref ref-type="supplementary-material" rid="pgen.1002548.s002">Figure S2</xref> [forest plots]). None of these loci contained more than one SNP independently associated at genome-wide significance (as judged by pair-wise linkage disequilibrium assessments using ‘SNAP’ and r<sup>2</sup>-values of 0.2 as cut off <ext-link ext-link-type="uri" xlink:href="http://www.broadinstitute.org/mpg/snap/">http://www.broadinstitute.org/mpg/snap/</ext-link>). The majority of polymorphisms tested in the genome-wide significant loci do not show evidence for publication bias (<xref ref-type="supplementary-material" rid="pgen.1002548.s005">Table S1</xref>). Finally, all genome-wide significant signals were robust against potential undetected sample overlap using a recently proposed procedure <xref rid="pgen.1002548-Lin1" ref-type="bibr">[24]</xref> (see <xref ref-type="supplementary-material" rid="pgen.1002548.s006">Table S2</xref> for more details). Combined sample sizes for all 12 loci were substantially larger here as compared to any previously published meta-analysis (<xref ref-type="supplementary-material" rid="pgen.1002548.s005">Table S1</xref>), providing unequivocal evidence for an involvement of these loci in PD susceptibility. While power to detect genome-wide significance was excellent for most of these loci (>80% based on an OR of 1.15, and a minor allele frequency down to 0.05 using the Genetic Power Calculator, <ext-link ext-link-type="uri" xlink:href="http://pngu.mgh.harvard.edu/~purcell/gpc/">http://pngu.mgh.harvard.edu/~purcell/gpc/</ext-link>), power was less for a large number of other meta-analyses due to smaller sample sizes and allele frequencies (see <xref ref-type="supplementary-material" rid="pgen.1002548.s005">Table S1</xref> for details). Thus, no simple statistic can summarize the overall power of our study.</p><p>The above list includes an intronic polymorphism in <italic>ITGA8</italic> located on chromosome 10p13 for which we identified novel evidence for genome-wide association with PD risk (OR 0.88, <italic>P</italic> = 1.3×10<sup>−8</sup>, <italic>I</italic><sup>2</sup> = 0, see <xref ref-type="table" rid="pgen-1002548-t002">Table 2</xref>, and <xref ref-type="fig" rid="pgen-1002548-g002">Figure 2</xref>). This SNP had previously been proposed to be associated with PD risk at sub-genome-wide significance by Simon-Sanchez et al <xref rid="pgen.1002548-SimnSnchez1" ref-type="bibr">[13]</xref>. After obtaining and meta-analyzing GWAS data from ∼1,400 additional SNPs in this region derived from all Caucasians GWAS datasets <xref rid="pgen.1002548-Maraganore2" ref-type="bibr">[10]</xref>, <xref rid="pgen.1002548-Pankratz1" ref-type="bibr">[12]</xref>, <xref rid="pgen.1002548-SimnSnchez1" ref-type="bibr">[13]</xref>, <xref rid="pgen.1002548-Edwards1" ref-type="bibr">[15]</xref>–<xref rid="pgen.1002548-SimnSnchez2" ref-type="bibr">[19]</xref>, <xref rid="pgen.1002548-Nalls1" ref-type="bibr">[21]</xref>, <xref rid="pgen.1002548-Do1" ref-type="bibr">[22]</xref>, rs7077361 remained the most significantly associated SNP in this region (<xref ref-type="supplementary-material" rid="pgen.1002548.s003">Figure S3</xref>).</p><fig id="pgen-1002548-g002" position="float"><object-id pub-id-type="doi">10.1371/journal.pgen.1002548.g002</object-id><label>Figure 2</label><caption><title>Forest plot of the meta-analysis of rs7077361 in <italic>ITGA8</italic>.</title><p>Study-specific allelic odds ratios (ORs, black squares) and 95% confidence intervals (CIs, lines) were calculated for each included dataset. The summary OR and CI was calculated using the DerSimonian Laird random-effects model (grey diamond) <xref rid="pgen.1002548-DerSimonian1" ref-type="bibr">[31]</xref>. C = Caucasian ancestry.</p></caption><graphic xlink:href="pgen.1002548.g002"></graphic></fig><p>In addition to using random-effects models, we also performed exploratory fixed-effect meta-analyses on all eligible polymorphisms. These analyses did not reveal genome-wide significant effect sizes for any additional locus, except <italic>ACMSD/TMEM163</italic> (most significant SNP rs6723108, OR 0.91, <italic>P</italic> = 1.3×10<sup>−9</sup>, <italic>I</italic><sup>2</sup> = 46% [95% CI 0–73%], <xref ref-type="supplementary-material" rid="pgen.1002548.s004">Figure S4</xref>, panel 1) and <italic>HLA</italic> (most significant SNP chr6:32609909, OR 0.78, <italic>P</italic> = 8.8×10<sup>−15</sup>, <italic>I</italic><sup>2</sup> = 84% [95% CI 70–91%], <xref ref-type="supplementary-material" rid="pgen.1002548.s004">Figure S4</xref>, panel 2), both of which were reported to be associated with PD risk at genome-wide significance in previous work <xref rid="pgen.1002548-Hamza1" ref-type="bibr">[16]</xref>, <xref rid="pgen.1002548-Nalls1" ref-type="bibr">[21]</xref>. In both instances, the lack of genome-wide significance in the random-effects models (<xref ref-type="supplementary-material" rid="pgen.1002548.s005">Table S1</xref>) was due to relatively pronounced heterogeneity of effect estimates across studies. However, the heterogeneity across the 11 datasets in the <italic>ACMSD/TMEM163</italic> meta-analysis is almost entirely due to variance of effect size estimates in the same direction (see <xref ref-type="supplementary-material" rid="pgen.1002548.s004">Figure S4</xref>, panel 1), making it likely that <italic>ACMSD/TMEM163</italic> represents a genuine PD risk locus. For the SNP tested in the <italic>HLA</italic> locus (chr6:32609909, <xref ref-type="supplementary-material" rid="pgen.1002548.s004">Figure S4</xref>, panel 2), heterogeneity is more pronounced and more complex owing to ORs on either side of 1. This could be due to a number of reasons, e.g. subtle and uncorrected population substructure and/or different LD patterns between the analyzed SNP and the actual functional variant(s) <xref rid="pgen.1002548-Hamza1" ref-type="bibr">[16]</xref>. Thus, although the evidence is currently not as conclusive as for <italic>ACMSD/TMEM163</italic> it still appears quite possible that there is one or more PD association signals in the <italic>HLA</italic> region. Regardless of these considerations, additional data are needed to more firmly assess the role of both loci in contributing to PD susceptibility.</p></sec><sec id="s2c"><title>Ethnicity-specific meta-analysis results</title><p><italic>SNCA</italic>, <italic>LRRK2</italic>, <italic>BST1</italic>, and PARK16 show evidence for genome-wide significance in meta-analyses restricted to Caucasian and Asian populations (<xref ref-type="table" rid="pgen-1002548-t002">Table 2</xref>). Furthermore, data obtained from the GEO-PD consortium <xref rid="pgen.1002548-Sharma1" ref-type="bibr">[23]</xref> suggest that the effect estimates for some of the recently discovered PD loci (i.e. <italic>CCDC62</italic>/<italic>HIP1R</italic>, <italic>MCC1</italic>, and <italic>STK39</italic>) <xref rid="pgen.1002548-Nalls1" ref-type="bibr">[21]</xref> may be comparable in Caucasian and Asian populations (<xref ref-type="supplementary-material" rid="pgen.1002548.s005">Table S1</xref>), although additional datasets are needed to establish genome-wide significance in populations of Asian-descent for these loci. Conversely, only insufficient data are currently available to assess the effect sizes of <italic>GAK</italic> and <italic>SYT11/RAB25</italic> on PD risk in Asians: <italic>GAK</italic> rs6599388 violated Hardy-Weinberg equilibrium in Asian datasets from the GEO-PD consortium and was thus excluded from further analyses on that ethnic group <xref rid="pgen.1002548-Sharma1" ref-type="bibr">[23]</xref>. <italic>SYT11/RAB25</italic> chr1:154105678 was excluded from all analyses due to technical reasons in the study by the GEO-PD consortium <xref rid="pgen.1002548-Sharma1" ref-type="bibr">[23]</xref>. Moreover, none of the reported <italic>SYT11/RAB25</italic> and <italic>GAK</italic> SNPs from the recent GWAS meta-analysis <xref rid="pgen.1002548-Nalls1" ref-type="bibr">[21]</xref> were captured directly or by proxy (with an r<sup>2</sup>≥0.8) in the Japanese GWAS dataset <xref rid="pgen.1002548-Satake1" ref-type="bibr">[14]</xref>, <xref rid="pgen.1002548-Sharma1" ref-type="bibr">[23]</xref>. Finally, Asian-descent populations cannot be appropriately assessed for PD association with the <italic>MAPT</italic>-H1/H2 haplotype, rs10928513 in <italic>ACMSD</italic>, and rs7077361 in <italic>ITGA8</italic> owing to monomorphicity at these sites <xref rid="pgen.1002548-Satake1" ref-type="bibr">[14]</xref>, <xref rid="pgen.1002548-Sharma1" ref-type="bibr">[23]</xref>.</p></sec><sec id="s2d"><title>Evaluating the credibility of significant associations</title><p>To estimate the epidemiologic credibility of associations with polymorphisms showing sub-genome-wide significant association with PD (<italic>P</italic>>5×10<sup>−8</sup>), we applied two “credibility” measures for each such result. First, we calculated Bayes factors (BF, expressed here as log<sub>10</sub>-values, “logBF”) assuming an average non-null odds ratio of 1.15, as approximation of a typical “complex disease effect size”, and a spike and smear prior distribution of effects <xref rid="pgen.1002548-Ioannidis1" ref-type="bibr">[25]</xref>. Our second assessment was based on the Human Genome Epidemiology Network's (HuGENet) interim criteria for the assessment of cumulative epidemiologic evidence in genetic association studies <xref rid="pgen.1002548-Ioannidis2" ref-type="bibr">[26]</xref>, <xref rid="pgen.1002548-Khoury1" ref-type="bibr">[27]</xref>. The results of these analyses are summarized in <xref ref-type="supplementary-material" rid="pgen.1002548.s005">Table S1</xref>.</p><p>There was strong epidemiologic support in both assessments for all loci showing genome-wide significant association. This included several additional polymorphisms in these same loci that only showed sub-genome-wide significant association. However, there was no additional sub-genome-wide significantly associated locus that received unequivocally strong support from both credibility assessments (<xref ref-type="supplementary-material" rid="pgen.1002548.s005">Table S1</xref>). In this list, the strongest support was assigned to SNP chr6:32588205 in the <italic>HLA</italic> locus receiving the best possible grade in the HuGENet criteria (grade A), but more moderate support in the Bayesian analyses (logBF = 4.4). However, the relevance of this assessment needs to be evaluated as the underlying analysis was only based on four GWAS datasets.</p></sec></sec><sec id="s3"><title>Discussion</title><p>The PDGene database represents a comprehensive, regularly updated and freely available online research synopsis of genetic association studies in PD. Detailed summaries of the most compelling findings are provided within an easy-to-use, dedicated online framework, displaying forest plots, cumulative meta-analyses, and an up-to-date ranking of “Top Results”. To allow comparison of PDGene results with association findings from other complex diseases and to facilitate their interpretation with respect to functional genetics data, all meta-analysis results have been ported as a customized track onto the UCSC Genome Browser. This will also allow for a integration and visualization <xref rid="pgen.1002548-Kent1" ref-type="bibr">[28]</xref> of association results from large-scale resequencing data (e.g. from whole-exome or whole-genome studies) into PDGene once these become available.</p><p>To the best of our knowledge, our study represents the most comprehensive research synopsis in the field of PD genetics. In addition, it represents the first disease-specific genetic database that allows a systematic and exhaustive inclusion of GWAS data, and may serve as a model for similar databases in other complex genetic diseases. Owing to our multi-pronged data retrieval and analysis protocol we were able to perform meta-analyses on the vast majority of PD risk-gene candidates, including those “featured” as top association results in all published GWAS. In particular, this includes the five novel loci recently featured in the recent GWAS meta-analysis <xref rid="pgen.1002548-Nalls1" ref-type="bibr">[21]</xref>. Through collaboration with other PD genetics laboratories we obtained independent summary data for these and 142 additional SNPs, substantially extending the hitherto available evidence. Taken together, our analyses provide unequivocal evidence that <italic>BST1</italic>, <italic>CCDC62/HIP1R</italic>, <italic>DGKQ/GAK</italic>, <italic>GBA</italic>, <italic>ITGA8</italic>, <italic>LRRK2</italic>, <italic>MAPT</italic>, <italic>MCCC1/LAMP3</italic>, PARK16, <italic>SNCA</italic>, <italic>STK39</italic>, <italic>SYT11/RAB25</italic> represent genuine PD risk loci, while the role of several other loci (e.g. <italic>ACMSD/TMEM163</italic>, and the <italic>HLA</italic> locus) remains to be determined. The unpublished data aggregated here from various PD genetics groups for selected candidate genes represents the first step towards a systematic meta-analysis across the full GWAS datasets from the same populations. Once completed, the results of this “mega” meta-analysis will be posted on the PDGene database, allowing users to browse the complete results via the customized genome browser track already in place.</p><p>Of particular interest are loci with unusually large effect sizes. While most loci in PDGene have only small effects on PD risk (with ORs ranging from 1.10 to 1.35, which are typical for complex diseases), for some loci much larger ORs were estimated (i.e. <italic>GBA</italic> [OR 3.51 in Caucasians], <italic>LRRK2</italic> [OR 2.23 in Asians], and <italic>SYT11</italic>/<italic>RAB25</italic> [OR 1.73 in Caucasians], see <xref ref-type="table" rid="pgen-1002548-t002">Table 2</xref>). The risk-allele frequencies at these polymorphisms are typically rather small (i.e. below 0.05), resulting in low population attributable risks for these loci (for the above mentioned loci individually less than 2%).</p><p>Interestingly, the meta-analysis results of <italic>GBA</italic> N370S as well as the <italic>LRRK2</italic> rs34778348 are solely based on candidate-gene approaches since these SNPs are not on any of the current GWAS arrays or imputation reference panels. Thus, even in the “GWAS era” smaller-scale, non-GWAS but “focused” genetic studies, will likely continue to play an important role. This is also true when it comes to providing independent replication of proposed disease associations and/or when validating imputation-derived results by direct genotyping in sufficiently sized datasets. PDGene systematically concatenates all these different types of data into one database framework, vastly facilitating an assessment of the overall evidence for any given SNP or locus.</p><p>The strength of our approach is further exemplified by the identification of genome-wide significant association between disease risk and a SNP in <italic>ITGA8</italic>, which was not featured as a relevant PD gene in any previous study. <italic>ITGA8</italic> (encoding integrin alpha 8, a type-I transmembrane protein) is functionally interesting as it is expressed in brain <xref rid="pgen.1002548-Myers1" ref-type="bibr">[29]</xref>, mediates cell-cell interactions and regulates neurite outgrowth of sensory and motor neurons <xref rid="pgen.1002548-VarnumFinney1" ref-type="bibr">[30]</xref>. Additional studies are needed to further assess the potential role of this gene in PD pathogenesis. Furthermore, PDGene shows that two additional loci, not highlighted by the recent GWAS meta-analysis <xref rid="pgen.1002548-Nalls1" ref-type="bibr">[21]</xref>, yield genome-wide signficiant results in the PDGene meta-analyses, i.e. PARK16, originally implicated as a PD susceptibility locus in an Asian GWAS <xref rid="pgen.1002548-Satake1" ref-type="bibr">[14]</xref> but not highlighted in the recent GWAS meta-analysis on Caucasian samples <xref rid="pgen.1002548-Nalls1" ref-type="bibr">[21]</xref> and <italic>GBA</italic>, a gene that was found soley by candidate-gene approaches. Another strength of our study is that it combines genetic data from currently more than 50 different countries allowing a systematic assessment of genetic associations across populations of different ethnic descent. For instance, these analyses suggest that variants in <italic>BST1</italic>, <italic>LRRK2</italic>, the PARK16 locus, and <italic>SNCA</italic> show genome-wide significant association with PD risk in both Caucasian and Asian-descent samples. Furthermore, the recently described Caucasian GWAS loci <italic>CCDC62</italic>/<italic>HIP1R</italic>, <italic>MCC1</italic>, and <italic>STK39</italic><xref rid="pgen.1002548-Nalls1" ref-type="bibr">[21]</xref> also show similar effect size estimates in populations of Asian-descent <xref rid="pgen.1002548-Sharma1" ref-type="bibr">[23]</xref>. PD association data originating from other ethnic groups are still relatively scarce. However, they could easily be added to the already existing data on the respective polymorphisms available on PDGene.</p><p>In summary, we have created a continuously updated online resource for genetic association studies in the field of PD. Synthesizing essentially all available data in the field led to the identification of <italic>ITGA8</italic> as a novel potential PD risk locus. Our quantitative approach to data integration across a multitude of different study designs can be readily scaled to include large-scale resequencing efforts that will emerge over the coming years, making the complex field of PD genetics accessible to a broad range of investigators.</p></sec><sec sec-type="methods" id="s4"><title>Methods</title><p>Note that the following section only provides a brief summary of the methods applied to our study. A much more detailed description can be found in <xref ref-type="supplementary-material" rid="pgen.1002548.s007">Text S1</xref>.</p><sec id="s4a"><title>Literature searches</title><sec id="s4a1"><title>Inclusion criteria</title><p>For inclusion in PDGene, a study has to meet three criteria: 1) It must evaluate the association between a bi-allelic genetic polymorphism (minor allele frequency ≥0.01 in the healthy control population of at least one study) and Parkinson's disease (PD) risk in datasets comprised of both affected (defined as clinically and/or neuropathologically diagnosed “Parkinson's disease”) and unaffected individuals; 2) it must be published in a peer-reviewed journal; 3) it must be published in English. For this manuscript, we also included data on ten SNPs generated in the GEO-PD Consortium datasets <xref rid="pgen.1002548-Satake1" ref-type="bibr">[14]</xref>, <xref rid="pgen.1002548-Sharma1" ref-type="bibr">[23]</xref> and obtained data for the newly identified SNP rs7077361 in <italic>ITGA8</italic> from the Japanese GWAS dataset <xref rid="pgen.1002548-Satake1" ref-type="bibr">[14]</xref>.</p></sec><sec id="s4a2"><title>Exclusion criteria</title><p>In brief, genetic association data of the following studies were excluded from the meta-analyses (see <xref ref-type="supplementary-material" rid="pgen.1002548.s007">Text S1</xref> for details): family-based studies without available subject-level data (however, unrelated case-control data enriched for familial cases were not excluded), studies investigating only disease controls, multi-allelic polymorphisms, and studies of polymorphisms in mitochondrial DNA. We also excluded genetic data of apparently “poor” quality if discrepancies could not be resolved after contacting the study authors (e.g. inadequate genotyping/sequencing protocols or discrepancies in terms of allele names or frequencies when compared with public databases; more details can be found in <xref ref-type="supplementary-material" rid="pgen.1002548.s007">Text S1</xref>).</p></sec><sec id="s4a3"><title>Search strategies</title><p>Our literature searches until March 31<sup>st</sup>, 2011, yielded 27,210 articles, which were screened for eligibility using the title, abstract, or full-papers, as necessary. Additional screening of bibliographies in reviews, published meta-analyses, and original genetic association studies were also performed. Overall, full text versions of 1,534 articles were obtained. Following the inclusion and exclusion criteria outlined above, 828 articles were included in PDGene until March 31<sup>st</sup> 2011 (also see <xref ref-type="fig" rid="pgen-1002548-g003">Figure 3</xref>).</p><fig id="pgen-1002548-g003" position="float"><object-id pub-id-type="doi">10.1371/journal.pgen.1002548.g003</object-id><label>Figure 3</label><caption><title>Flowchart of literature search, data extraction, and analysis strategies applied for PDGene.</title></caption><graphic xlink:href="pgen.1002548.g003"></graphic></fig></sec></sec><sec id="s4b"><title>Statistical analyses</title><sec id="s4b1"><title>Meta-analyses</title><p>Random-effects allelic meta-analyses <xref rid="pgen.1002548-DerSimonian1" ref-type="bibr">[31]</xref> were performed if a minimum of four independent datasets existed per polymorphism. Summary odds ratios [ORs] and 95% confidence intervals [CIs] were calculated irrespective of ethnic descent as well as for distinct ethnic groups (i.e. Caucasians, and Asians) if sufficient data were available. In addition, we performed a number of sensitivity analyses (excluding the initial studies and datasets in which HWE was violated in control individuals), systematically assessed between-study heterogeneity (via <italic>I</italic><sup>2</sup>), and assessed the credibility of each at least nominally significant meta-analysis result by calculating Bayes factors (BF; here expressed as log10(BF)="logBF”) <xref rid="pgen.1002548-Ioannidis1" ref-type="bibr">[25]</xref> and by determining a grading score developed by the Human Genome Epidemiology Network (HuGENet) <xref rid="pgen.1002548-Ioannidis2" ref-type="bibr">[26]</xref>, <xref rid="pgen.1002548-Khoury1" ref-type="bibr">[27]</xref>.</p></sec><sec id="s4b2"><title>Assessment of small-study bias/publication bias</title><p>This is of particular importance in meta-analyses of published association data and was carefully addressed here: First, we added <italic>publicly</italic> available GWAS data <xref rid="pgen.1002548-Maraganore2" ref-type="bibr">[10]</xref>, <xref rid="pgen.1002548-Pankratz1" ref-type="bibr">[12]</xref>, <xref rid="pgen.1002548-SimnSnchez1" ref-type="bibr">[13]</xref> to the vast majority of SNPs. Since these data are typically unbiased, this should decrease the potential for small-study bias/publication bias. Secondly, for 147 SNPs of the core PDGene meta-analyses that showed statistically suggestive results (<italic>P</italic>≤0.1), we obtained additional data from all currently published, but <italic>not publicly</italic> available GWAS datasets, further decreasing a potential impact of small-study bias/publication bias. Thirdly, we directly assessed the evidence for small study bias by applying a recently proposed regression test <xref rid="pgen.1002548-Harbord1" ref-type="bibr">[32]</xref> on all nominally significant (<italic>P</italic><0.05) meta-analysis results. The results of these analyses are fully displayed in <xref ref-type="supplementary-material" rid="pgen.1002548.s005">Table S1</xref>.</p></sec><sec id="s4b3"><title>GWAS-only meta-analyses</title><p>We obtained individual-level genotype data for all publicly available PD GWAS datasets from NCBI's “dbGAP” database (a total of three <xref rid="pgen.1002548-Maraganore2" ref-type="bibr">[10]</xref>, <xref rid="pgen.1002548-Pankratz1" ref-type="bibr">[12]</xref>, <xref rid="pgen.1002548-SimnSnchez1" ref-type="bibr">[13]</xref> at the time of the datafreeze, March 31<sup>st</sup>, 2011). Genotype data were cleaned using standard procedures, followed by imputation of untested genotypes (using reference panels from HapMap and the 1000 Genomes Project), and association analyses incorporating imputation uncertainty (case-control datasets only), age, sex, and population stratification. Overall, this procedure led to a total of 7,723,931 unique SNPs, 7,123,920 of which were present in at least two, and 711,271 in at least three datasets. Meta-analyses (either combining test-statistics and standard errors using random-effects models, or by combining P-values weighted by sample size, see <xref ref-type="supplementary-material" rid="pgen.1002548.s007">Text S1</xref> for more details) were performed on the 7,123,920 SNPs present in at least two of the GWAS datasets.</p></sec></sec><sec id="s4c"><title>Online database</title><p>After completion of all data-management and analysis steps, all study-specific variables, genotype data (except for GWAS), and meta-analysis plots are posted on a dedicated, publicly available, online adaptation of the PDGene database using the same software and code as our databases for Alzheimer's disease <xref rid="pgen.1002548-Bertram1" ref-type="bibr">[33]</xref> and schizophrenia <xref rid="pgen.1002548-Allen1" ref-type="bibr">[34]</xref>. The online database is hosted by the “Alzheimer Research Forum” and can be accessed via its own designated URL (<ext-link ext-link-type="uri" xlink:href="http://www.pdgene.org">http://www.pdgene.org</ext-link>).</p></sec><sec id="s4d"><title>Database code</title><p>The database software can easily be ported to other genetically complex diseases and will be made available on a collaborative basis to interested researchers upon request.</p></sec></sec><sec sec-type="supplementary-material" id="s5"><title>Supporting Information</title><supplementary-material content-type="local-data" id="pgen.1002548.s001"><label>Figure S1</label><caption><p>QQ plots showing the distribution of expected versus observed P-values for the GWAS-only meta-analysis results. Analyses were performed using the METAL software (ref. <xref rid="pgen.1002548-Nalls1" ref-type="bibr">[21]</xref> in <xref ref-type="supplementary-material" rid="pgen.1002548.s007">Text S1</xref>). The excess of observed <italic>P</italic>-values (<xref ref-type="supplementary-material" rid="pgen.1002548.s001">Figure S1</xref>, panel 1) is entirely due to association signals in the <italic>SNCA</italic>, <italic>MAPT</italic>, <italic>LRRK2</italic>, and <italic>DGKQ</italic>/<italic>GAK</italic> loci as can be seen in <xref ref-type="supplementary-material" rid="pgen.1002548.s001">Figure S1</xref>, panel 2 that showcases the <italic>P</italic>-value distributions after removal of 18,622 SNPs in these regions (lambda = 1.007).</p><p>(TIF)</p></caption><media xlink:href="pgen.1002548.s001.tif"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pgen.1002548.s002"><label>Figure S2</label><caption><p>Forest plots of allelic meta-analyses for SNPs showing genome-wide significant association (P<5×10−8) with PD susceptibility in the March 31<sup>st</sup> 2011 datafreeze. Study-specific allelic odds ratios (ORs, black squares) and 95% confidence intervals (CIs, lines) were calculated for each included dataset. The summary OR and CI was calculated using random-effects models (grey diamond). Whenever multiple polymorphisms showed genome-wide significant association in the same locus, only the variant with the smallest P-value is listed here for meta-analysis results after stratification for Caucasian and Asian ancestries. For a complete list of meta-analyses performed for the datafreeze, see <xref ref-type="supplementary-material" rid="pgen.1002548.s005">Table S1</xref>. <xref ref-type="supplementary-material" rid="pgen.1002548.s001">Figure S1</xref>, panel 1-S1, panel 12 and S1, panel 13-S1, panel 16 display the SNP showing the most significant genome-wide association in datasets of Caucasian ancestry and Asian ancestry, respectively. Details and references of all included studies displayed here can be found on the PDGene database (<ext-link ext-link-type="uri" xlink:href="http://www.pdgene.org">http://www.pdgene.org</ext-link>). I2 = estimate of percentage of between-study heterogeneity that is beyond chance, “excl initial” = summary OR and 95%CI after meta-analysis after exclusion of the initial study, C = Caucasian ancestry, A = Asian ancestry, H = Hispanic descent, D = African descent, “•” = initial study (applies to candidate-gene studies), “†” = no data provided or data was not eligible for inclusion in meta-analysis, “‡” = study excluded due to overlap, “#” = HWE violation in controls (P<0.05, not applicable to quality-controlled GWAS datasets, see <xref ref-type="supplementary-material" rid="pgen.1002548.s007">Text S1</xref>), “i” = SNP monomorphic in the respective dataset, “ø” = meta-analysis after excluding initial study not applicable.</p><p>(PDF)</p></caption><media xlink:href="pgen.1002548.s002.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pgen.1002548.s003"><label>Figure S3</label><caption><p>Locus plot of the ITGA8 region on chromosome 10p13 (15346353–15801533 bp, hg18). The figure displays association results for ∼1,400 SNPs in the <italic>ITGA8</italic> region including at least four independent datasets. SNPs are color-coded based on linkage disequilibrium (r<sup>2</sup>) estimates from the CEU 1000G dataset (release June 2010). All LD estimates refer to the most significantly associated SNP rs7077361. SNPs color-coded in grey indicate missing LD estimates in the CEU dataset. Recombination rates were estimated based on the CEU dataset, and are displayed as blue line in the background. Gene annotations are based on RefSeq and the UCSC Genome browser. Locus plots were generated using the LocusZoom Stand-alone package (<ext-link ext-link-type="uri" xlink:href="http://genome.sph.umich.edu/wiki/LocusZoom_Standalone">http://genome.sph.umich.edu/wiki/LocusZoom_Standalone</ext-link>).</p><p>(TIF)</p></caption><media xlink:href="pgen.1002548.s003.tif"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pgen.1002548.s004"><label>Figure S4</label><caption><p>Forest plots of fixed-effect meta-analyses for SNP rs6723108 in the ACMSD/TMEM163 locus and chr6:32609909 in the HLA locus. Symbols are the same as for <xref ref-type="supplementary-material" rid="pgen.1002548.s002">Figure S2</xref> (see above).</p><p>(TIF)</p></caption><media xlink:href="pgen.1002548.s004.tif"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pgen.1002548.s005"><label>Table S1</label><caption><p>Overview of all 867 polymorphisms meta-analyzed in the March 31<sup>st</sup> 2011 datafreeze using random-effects allelic models. Random-effects allelic meta-analyses were performed on polymorphisms for which four or more independent datasets were available. Meta-analyses after stratification for different ethnic descent were performed if at least three independent datasets were available in the respective stratum (applicable only to samples of European and Asian descent). Each nominally significant meta-analysis result (<italic>P</italic><0.05) was graded according to the HuGENet interim criteria. For details on how these criteria are applied, see <xref ref-type="supplementary-material" rid="pgen.1002548.s007">Text S1</xref>. Meta-analysis results in this table are ordered by genomic location. OR = Odds Ratio, CI = confidence interval, N minor = number of minor alleles, Ethnicities: C = Caucasian, A = Asian, D = African Descent, H = Hispanic, O = Other/Mixed, Low OR = OR<1.15 or ≥0.87, respectively, F = loss of significance in the respective meta-analysis after exclusion of the first study, HWE = loss of significance after excluding studies violating HWE (<italic>P</italic><0.05), Regr = evidence for small-study/publication bias using a modified regression test (see <xref ref-type="supplementary-material" rid="pgen.1002548.s007">Text S1</xref>), A = Grade A (‘strong’ epidemiologic credibility), B = Grade B (‘modest’ epidemiologic credibility), C = Grade C (‘weak’ epidemiologic credibility), logBF = Bayes Factor (see <xref ref-type="supplementary-material" rid="pgen.1002548.s007">Text S1</xref>). “*” denotes SNPs that have been supplemented by additional data after the datafreeze (in total this applies to 147 SNPs, see <xref ref-type="supplementary-material" rid="pgen.1002548.s007">Text S1</xref> for the description of included datasets).</p><p>(XLS)</p></caption><media xlink:href="pgen.1002548.s005.xls"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pgen.1002548.s006"><label>Table S2</label><caption><p>Investigation of the extent of statistical inflation assuming sample overlaps of 1%, 5%, and 10% across cases and controls in datasets originating from the same countries. Hypothetical sample overlap across datasets was assumed between different candidate-gene/replication studies and between candidate-gene/replication studies and GWAS datasets if they originated from the same country. These analyses were performed applying random-effects models and adding the sum of weighted co-variances of overlapping datasets to the overall study variance (see ref. <xref rid="pgen.1002548-Lin1" ref-type="bibr">[24]</xref> in the main text). Note that the assumption of undetected overlapping samples does not apply (and was therefore not modeled here) to overlap between individual GWAS as duplicate samples in these datasets were removed prior to meta-analysis. It also does not apply to independent datasets used in the same publication where duplicate samples had been removed by the authors prior to analysis and publication. We emphasize that this table describes hypothetical scenarios, because the geographical origin of each study had been investigated extensively and potentially overlapping datasets had been excluded as part of PDGene's data inclusion protocol. Thus, the extent of overlap across geographically distinct datasets within the same countries is reduced to accidental recruitment of the same subjects more than once in different datasets throughout the respective countries, and can be expected to be less than ∼1%. This estimate is based on data of the GEO-PD consortium, where sufficient data were centrally available of 6,072 subjects from 20 geographically distinct sites in 13 countries that had been investigated for potentially duplicate samples across sites, but no duplicate subjects (neither between not within countries) were identified when matching on ethnicity, birth, sex, and genotype. The investigation of overlap was not applicable here for Asian datasets, as they originated from different countries and/or were cleaned by the respective authors prior to publication.</p><p>(DOC)</p></caption><media xlink:href="pgen.1002548.s006.doc"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pgen.1002548.s007"><label>Text S1</label><caption><p>Supplementary material. This file includes supplementary methods and references as well as the list of members of the GWAS consortia, the GEO-PD Consortium, and consortia-specific acknowledgements.</p><p>(PDF)</p></caption><media xlink:href="pgen.1002548.s007.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material></sec></body><back><ack><p>23andMe acknowledges Elizabeth Dorfman, Amy K. Kiefer, Emily M. Drabant, Uta Francke, Joanna L. Mountain, David Hinds, and Anne Wojcicki from 23andMe, as well as Samuel M. Goldman, Caroline M. Tanner, and J. William Langston from the Parkinson's Institute, Sunnyvale, CA, USA. We also acknowledge the contribution of Mitsutoshi Yamamoto, Nobutaka Hattori, and Miho Murata for sample collection in the Japanese GWAS 1.0 <xref rid="pgen.1002548-Satake1" ref-type="bibr">[14]</xref>. We are grateful to the Alzheimer Research Forum—in particular to June Kinoshita, Colin Knep, Paula Noyes, and Gabrielle Ströbel—for hosting PDGene on their website. We also thank the many PD researchers who have kindly provided us with genotype data and helpful information beyond those included in the original publications. Finally, we would like to thank the many PD patients and control subjects who volunteered to participate in the individual studies.</p></ack><fn-group><fn fn-type="COI-statement"><p>CB Do, N Eriksson, and JY Tung are employed by 23andMe and own stock options in the company. MJ Farrer and Mayo Foundation received royalties from H.Lundbeck A/S and Isis Pharmaceuticals. In addition, MJ Farrer has received an honorarium for a seminar at Genzyme. T Gasser has received consultancy fees from Cephalon and Merck-Serono, grants from Novartis, payments for lectures including service on speakers' bureaus from Boehringer Ingelheim, Merck-Serono, UCB, and Valean, and holds patents NGFN2 and KASPP. JA Hardy has received consulting fees or honoraria from Eisai and his institute has received consulting fees or honoraria from Merck-Serono. DM Maraganore has received extramural research funding support from the National Institutes of Health (2R01 ES10751), the Michael J. Fox Foundation (Linked Efforts to Accelerate Parkinson Solutions Award, Edmond J. Safra Global Genetics Consortia Award), and from Alnylam Pharmaceuticals and Medtronic (observational studies of Parkinson's disease). DM Maraganore has also received intramural research funding support from the Mayo Clinic and from NorthShore University Health System. DM Maraganore filed a provisional patent for a method to predict Parkinson's disease. This provisional patent is unlicensed. He also filed a provisional patent for a method to treat neurodegenerative disorders. That provisional patent has been licensed to Alnylam Pharmaceuticals and DM Maraganore has received royalty payments in total of less than $20,000. K Stefansson has received grants from deCODE.</p></fn><fn fn-type="financial-disclosure"><p>The main funding for this study was provided by the Michael J. Fox Foundation for Parkinson's Disease (MJFF) with additional financial support by the Cure Alzheimer's Fund (CAF), the National Alliance for Research on Schizophrenia and Depression (NARSAD), Prize4Life, and EMD Serono (all to L Bertram). CM Lill was supported by a fellowship from the Deutscher Akademischer Austauschdienst (DAAD) and Fidelity Biosciences Research Initiative (FBRI). L Bertram is also supported by the German Ministry for Education and Research (BMBF). JPA Ioannidis was supported through the Tufts Clinical and Translational Science Institute (Tufts CTSI) under funding from the National Institute of Health/National Center for Research Resources (UL1 RR025752). Points of view or opinions in this paper are those of the authors and do not necessarily represent the official position or policies of the Tufts CTSI. M Sharma was supported by the Michael J. Fox Foundation. The NeuroGenetics Research Consortium GWAS [15] was funded by the Edmond J. Safra Michael J. Fox Foundation Global Genetics Consortium Initiative and NIH R01 NS 036960. The work of the International Parkinson's Disease Genomics Consortium (IPDGC) was supported in part by the Intramural Research Programs of the National Institute on Aging, National Institute of Neurological Disorders and Stroke, National Institute of Environmental Health Sciences, National Human Genome Research Institute, National Institutes of Health, Department of Health and Human Services: project numbers Z01 AG000949-02 and Z01-ES101986. In addition the work of the IPDGC was supported by the U.S. Department of Defense, award number W81XWH-09-2-0128. Portions of the work of the IPDGC utilized the high-performance computational capabilities of the Biowulf Linux cluster at the National Institutes of Health, Bethesda, Md. (<ext-link ext-link-type="uri" xlink:href="http://biowulf.nih.gov">http://biowulf.nih.gov</ext-link>). T Foroud received funds from the National Institutes of Health (R01CA141668 and R01NS37167). C Klein is the recipient of a career development award from the Volkswagen Foundation and from the Hermann and Lilly Schilling Foundation. DM Maraganore acknowledges active funding support from the National Institutes of Health (2R01 ES10751), Alnylam Pharmaceuticals, Medtronic, and NorthShore University Health System. 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