Jia Y Wan1, Karen L Edwards1, Carolyn M Hutter1, Ignacio F Mata2, Ali Samii2, John W Roberts3, Pinky Agarwal4, Harvey Checkoway5, Federico M Farin6, Dora Yearout2, Cyrus P Zabetian7. 1. Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA. 2. Veterans Affairs Puget Sound Health Care System, Seattle, WA, USA; Department of Neurology, University of Washington School of Medicine, Seattle, WA, USA. 3. Virginia Mason Medical Center, Seattle, WA, USA. 4. Booth Gardner Parkinson's Care Center, Evergreen Hospital Medical Center, Kirkland, WA, USA. 5. Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA; Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, WA, USA. 6. Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, WA, USA. 7. Veterans Affairs Puget Sound Health Care System, Seattle, WA, USA; Department of Neurology, University of Washington School of Medicine, Seattle, WA, USA. Electronic address: zabetian@u.washington.edu.
Abstract
BACKGROUND: Previous studies indicate that as many as six genes within the PARK10 region (RNF11, UQCRH, HIVEP3, EIF2B3, USP24, ELAVL4) might modify susceptibility or age at onset in Parkinson's disease (PD). METHODS: We sought to identify new PD susceptibility genes and to validate previously nominated candidate genes within the PARK10 region using a two-stage design. We used data from a large, publicly-available genome-wide association study (GWAS) in the discovery stage (n = 2000 cases and 1986 controls) and data from three independent studies for the replication stage (total n = 2113 cases and 2095 controls). Marker density was increased by imputation using HapMap 3 and 1000 Genomes reference panels, and over 40,000 single nucleotide polymorphisms (SNPs) were used in the final analysis. The association between each SNP and PD was modeled using logistic regression with an additive allele dosage effect and adjusted for sex, age, and axes of geographical variation. RESULTS: Although the discovery stage yielded promising findings for SNPs in several novel genes, including DAB1, none of the results were validated in the replication stage. Furthermore, in meta-analyses across all datasets no genes within PARK10 reached significance after accounting for multiple testing. CONCLUSION: Our results suggest that common variation in the PARK10 region is not associated with PD risk. However, additional studies are needed to assess the role of PARK10 in modifying age at onset and to determine whether rare variants in this region might affect PD susceptibility. Published by Elsevier Ltd.
BACKGROUND: Previous studies indicate that as many as six genes within the PARK10 region (RNF11, UQCRH, HIVEP3, EIF2B3, USP24, ELAVL4) might modify susceptibility or age at onset in Parkinson's disease (PD). METHODS: We sought to identify new PD susceptibility genes and to validate previously nominated candidate genes within the PARK10 region using a two-stage design. We used data from a large, publicly-available genome-wide association study (GWAS) in the discovery stage (n = 2000 cases and 1986 controls) and data from three independent studies for the replication stage (total n = 2113 cases and 2095 controls). Marker density was increased by imputation using HapMap 3 and 1000 Genomes reference panels, and over 40,000 single nucleotide polymorphisms (SNPs) were used in the final analysis. The association between each SNP and PD was modeled using logistic regression with an additive allele dosage effect and adjusted for sex, age, and axes of geographical variation. RESULTS: Although the discovery stage yielded promising findings for SNPs in several novel genes, including DAB1, none of the results were validated in the replication stage. Furthermore, in meta-analyses across all datasets no genes within PARK10 reached significance after accounting for multiple testing. CONCLUSION: Our results suggest that common variation in the PARK10 region is not associated with PD risk. However, additional studies are needed to assess the role of PARK10 in modifying age at onset and to determine whether rare variants in this region might affect PD susceptibility. Published by Elsevier Ltd.
Authors: Alkes L Price; Nick J Patterson; Robert M Plenge; Michael E Weinblatt; Nancy A Shadick; David Reich Journal: Nat Genet Date: 2006-07-23 Impact factor: 38.330
Authors: Shaun Purcell; Benjamin Neale; Kathe Todd-Brown; Lori Thomas; Manuel A R Ferreira; David Bender; Julian Maller; Pamela Sklar; Paul I W de Bakker; Mark J Daly; Pak C Sham Journal: Am J Hum Genet Date: 2007-07-25 Impact factor: 11.025
Authors: Yonghong Li; Steven Schrodi; Charles Rowland; Kristina Tacey; Joseph Catanese; Andrew Grupe Journal: Hum Mutat Date: 2006-10 Impact factor: 4.878
Authors: Kristoffer Haugarvoll; Mathias Toft; Owen A Ross; Jeremy T Stone; Michael G Heckman; Linda R White; Timothy Lynch; John Mark Gibson; Zbigniew K Wszolek; Ryan J Uitti; Jan O Aasly; Matthew J Farrer Journal: Mov Disord Date: 2007-03-15 Impact factor: 10.338
Authors: Anita L DeStefano; Jeanne Latourelle; Mark F Lew; Oksana Suchowersky; Christine Klein; Lawrence I Golbe; Margery H Mark; John H Growdon; G Fredrick Wooten; Ray Watts; Mark Guttman; Brad A Racette; Joel S Perlmutter; Lynn Marlor; Holly A Shill; Carlos Singer; Stefano Goldwurm; Gianni Pezzoli; Marie H Saint-Hilaire; Audrey E Hendricks; Adam Gower; Sally Williamson; Michael W Nagle; Jemma B Wilk; Tiffany Massood; Karen W Huskey; Kenneth B Baker; Ilia Itin; Irene Litvan; Garth Nicholson; Alastair Corbett; Martha Nance; Edward Drasby; Stuart Isaacson; David J Burn; Patrick F Chinnery; Peter P Pramstaller; Jomana Al-Hinti; Anette T Moller; Karen Ostergaard; Scott J Sherman; Richard Roxburgh; Barry Snow; John T Slevin; Franca Cambi; James F Gusella; Richard H Myers Journal: Hum Genet Date: 2008-06-29 Impact factor: 4.132
Authors: Javier Simón-Sánchez; Claudia Schulte; Jose M Bras; Manu Sharma; J Raphael Gibbs; Daniela Berg; Coro Paisan-Ruiz; Peter Lichtner; Sonja W Scholz; Dena G Hernandez; Rejko Krüger; Monica Federoff; Christine Klein; Alison Goate; Joel Perlmutter; Michael Bonin; Michael A Nalls; Thomas Illig; Christian Gieger; Henry Houlden; Michael Steffens; Michael S Okun; Brad A Racette; Mark R Cookson; Kelly D Foote; Hubert H Fernandez; Bryan J Traynor; Stefan Schreiber; Sampath Arepalli; Ryan Zonozi; Katrina Gwinn; Marcel van der Brug; Grisel Lopez; Stephen J Chanock; Arthur Schatzkin; Yikyung Park; Albert Hollenbeck; Jianjun Gao; Xuemei Huang; Nick W Wood; Delia Lorenz; Günther Deuschl; Honglei Chen; Olaf Riess; John A Hardy; Andrew B Singleton; Thomas Gasser Journal: Nat Genet Date: 2009-11-15 Impact factor: 38.330
Authors: Jeanne C Latourelle; Nathan Pankratz; Alexandra Dumitriu; Jemma B Wilk; Stefano Goldwurm; Gianni Pezzoli; Claudio B Mariani; Anita L DeStefano; Cheryl Halter; James F Gusella; William C Nichols; Richard H Myers; Tatiana Foroud Journal: BMC Med Genet Date: 2009-09-22 Impact factor: 2.103
Authors: Nathan Pankratz; Jemma B Wilk; Jeanne C Latourelle; Anita L DeStefano; Cheryl Halter; Elizabeth W Pugh; Kimberly F Doheny; James F Gusella; William C Nichols; Tatiana Foroud; Richard H Myers Journal: Hum Genet Date: 2008-11-06 Impact factor: 4.132
Authors: Xin Wang; Nuomin Li; Nian Xiong; Qi You; Jie Li; Jinlong Yu; Hong Qing; Tao Wang; Heather J Cordell; Ole Isacson; Jeffery M Vance; Eden R Martin; Ying Zhao; Bruce M Cohen; Edgar A Buttner; Zhicheng Lin Journal: Mol Neurobiol Date: 2016-03-28 Impact factor: 5.590