Identification of Candidate Parkinson Disease Genes by Integrating Genome-Wide Association Study, Expression, and Epigenetic Data Sets
Authors: Demis A. Kia, David Zhang, Sebastian Guelfi, Claudia Manzoni, Leon Hubbard, Regina H. Reynolds, Juan Botía, Mina Ryten, Raffaele Ferrari, Patrick A. Lewis, Nigel Williams, Daniah Trabzuni, John Hardy, Nicholas W. Wood, Alastair J. Noyce, Rauan Kaiyrzhanov, Ben Middlehurst, Demis A. Kia, Manuela Tan, Henry Houlden, Huw R. Morris, Helene Plun-Favreau, Peter Holmans, John Hardy, Daniah Trabzuni, Jose Bras, John Quinn PhD, Kin Y. Mok, Kerri J. Kinghorn, Kimberley Billingsley, Nicholas W. Wood, Patrick Lewis, Sebastian Schreglmann, Rita Guerreiro, Ruth Lovering, Lea R'Bibo, Claudia Manzoni, Mie Rizig, Mina Ryten, Sebastian Guelfi, Valentina Escott-Price, Viorica Chelban, Thomas Foltynie, Nigel Williams, Alexis Brice, Fabrice Danjou, Suzanne Lesage, Jean-Christophe Corvol, Maria Martinez, Claudia Schulte, Kathrin Brockmann, Javier Simón-Sánchez, Peter Heutink, Patrizia Rizzu, Manu Sharma, Thomas Gasser, Aude Nicolas, Mark R. Cookson, Sara Bandres-Ciga, Cornelis Blauwendraat, David W. Craig, Faraz Faghri, J. Raphael Gibbs, Dena G. Hernandez, Kendall Van Keuren-Jensen, Joshua M. Shulman, Hampton L. Leonard, Mike A. Nalls, Laurie Robak, Steven Lubbe, Steven Finkbeiner, Niccolo E. Mencacci, Codrin Lungu, Andrew B Singleton, Sonja W. Scholz, Xylena Reed, Roy N. Alcalay, Ziv Gan-Or, Guy A. Rouleau, Lynne Krohn, Jacobus J. van Hilten, Johan Marinus, Astrid D. Adarmes-Gómez, Miquel Aguilar, Ignacio Alvarez, Victoria Alvarez, Francisco Javier Barrero, Jesús A. Bergareche Yarza, Inmaculada Bernal-Bernal, Marta Blazquez, Marta Bonilla-Toribio, Juan A. Botía, María T. Boungiorno, Dolores Buiza-Rueda, Ana Càmara, Fátima Carrillo, Mario Carrión-Claro, Debora Cerdan, Jordi Clarimón, Yaroslau Compta, Monica Diez-Fairen, Oriol Dols-Icardo, Jacinto Duarte, Raquel Duran, Francisco Escamilla-Sevilla, Mario Ezquerra, Cici Feliz, Manel Fernàndez, Rubén Fernàndez-Santiago, Ciara Garcia, Pedro García-Ruiz, Pilar Gómez-Garre, Maria J. Gomez Heredia, Isabel Gonzalez-Aramburu, Ana G. Pagola, Janet Hoenicka, Jon Infante, Adriano Jimenez-Escrig, Jaime Kulisevsky, Miguel A. Labrador-Espinosa, Jose Luis Lopez-Sendon, Adolfo López de Munain Arregui, Daniel Macias, Irene Martínez Torres, Juan Marín, Maria Jose Marti, Juan Carlos Martínez-Castrillo, Carlota Mèndez-del-Barrio, Manuel Menéndez González, Marina Mata Adolfo Mínguez, Pablo Mir, Elisabet Mondragon Rezola, Esteban Muñoz, Javier Pagonabarraga, Pau Pastor, Francisco Perez Errazquin, Teresa Perinán-Tocino, Javier Ruiz-Martínez, Clara Ruz, Antonio Sanchez Rodriguez, María Sierra, Esther Suarez-Sanmartin, Cesar Tabernero, Juan Pablo Tartari, Cristina Tejera-Parrado, Eduard Tolosa, Francesc Valldeoriola, Laura Vargas-González, Lydia Vela, Francisco Vives, Alexander Zimprich, Lasse Pihlstrom, Mathias Toft, Sulev Koks, Pille Taba, Sharon Hassin-Baer, Michael Weale, Adaikalavan Ramasamy, Colin Smith, Manuel Sebastian Guelfi, Karishma D'sa, Paola Forabosco, Juan A. Botiá
Journal: JAMA Neurology (2021)

<h3>Importance</h3> Substantial genome-wide association study (GWAS) work in Parkinson disease (PD) has led to the discovery of an increasing number of loci shown reliably to be associated with increased risk of disease. Improved understanding of the underlying genes and mechanisms at these loci will be key to understanding the pathogenesis of PD. <h3>Objective</h3> To investigate what genes and genomic processes underlie the risk of sporadic PD. <h3>Design and Setting</h3> This genetic association study used the bioinformatic tools Coloc and transcriptome-wide association study (TWAS) to integrate PD case-control GWAS data published in 2017 with expression data (from Braineac, the Genotype-Tissue Expression [GTEx], and CommonMind) and methylation data (derived from UK Parkinson brain samples) to uncover putative gene expression and splicing mechanisms associated with PD GWAS signals. Candidate genes were further characterized using cell-type specificity, weighted gene coexpression networks, and weighted protein-protein interaction networks. <h3>Main Outcomes and Measures</h3> It was hypothesized a priori that some genes underlying PD loci would alter PD risk through changes to expression, splicing, or methylation. Candidate genes are presented whose change in expression, splicing, or methylation are associated with risk of PD as well as the functional pathways and cell types in which these genes have an important role. <h3>Results</h3> Gene-level analysis of expression revealed 5 genes (<i>WDR6</i>[OMIM606031],<i>CD38</i>[OMIM107270],<i>GPNMB</i>[OMIM604368],<i>RAB29</i>[OMIM603949], and<i>TMEM163</i>[OMIM618978]) that replicated using both Coloc and TWAS analyses in both the GTEx and Braineac expression data sets. A further 6 genes (<i>ZRANB3</i>[OMIM615655],<i>PCGF3</i>[OMIM617543],<i>NEK1</i>[OMIM604588],<i>NUPL2</i>[NCBI11097],<i>GALC</i>[OMIM606890], and<i>CTSB</i>[OMIM116810]) showed evidence of disease-associated splicing effects. Cell-type specificity analysis revealed that gene expression was overall more prevalent in glial cell types compared with neurons. The weighted gene coexpression performed on the GTEx data set showed that<i>NUPL2</i>is a key gene in 3 modules implicated in catabolic processes associated with protein ubiquitination and in the ubiquitin-dependent protein catabolic process in the nucleus accumbens, caudate, and putamen.<i>TMEM163</i>and<i>ZRANB3</i>were both important in modules in the frontal cortex and caudate, respectively, indicating regulation of signaling and cell communication. Protein interactor analysis and simulations using random networks demonstrated that the candidate genes interact significantly more with known mendelian PD and parkinsonism proteins than would be expected by chance. <h3>Conclusions and Relevance</h3> Together, these results suggest that several candidate genes and pathways are associated with the findings observed in PD GWAS studies.