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1. Analysis of Genome-Wide Association Studies of Alzheimer Disease and of Parkinson Disease to Determine If These 2 Diseases Share a Common Genetic Risk

Author

Moskvina, Valentina, Harold, Denise, Nicolaou, Nayia, Simón-Sánchez, Javier, Gibbs, J Raphael, Schulte, Claudia, Durr, Alexandra, Guerreiro, Rita, Hernandez, Dena, Brice, Alexis, Stefánsson, Hreinn, Majamaa, Kari, Russo, GianCarlo, Gasser, Thomas, Heutink, Peter, Wood, Nick, Martinez, Maria, Singleton, Andrew B, Nalls, Michael A, Hardy, John, Owen, Michael J, O'Donovan, Michael C, Williams, Julie, Vedernikov, Alexey, Morris, Huw R, Williams, Nigel M, Investigators, IPDGC and GERAD, Dillman, Allissa, Brooks, Janet, Chong, Sean, Cookson, Mark R, Moore, Matthew, Keller, Margaux F, Sharma, Manu, Traynor, Bryan J, Arepalli, Sampath, Charlesworth, Gavin, Plagnol, Vincent, Ryten, Mina, Trabzuni, Daniah, Bras, Jose M, Saad, Mohamed, Sheerin, Una-Marie, Bhatia, Kailash, Saad, Mohamad, Bochdanovits, Zoltan, Rizzu, Patrizia, Vidailhet, Marie, Holmans, Peter, Corvol, Jen-Christophe, Curie, Pierre et Marie, Barker, Roger, Hunt, Sarah E, Gray, Emma, Edkins, Sarah, Tashakkori-Ghanbaria, Avazeh, Barrett, Jeffrey, Deloukasm, Panagiotis, Potter, Simon, Ben-Shlomo, Yoav, van Dijk, Karin D, Berendse, Henk W, Velseboer, Daan, de Bie, Rob M A, Biffi, Alessandro, Bloem, Bas, van deWarrenburg, Bart, Post, Bart, Bettella, Francesco, Riess, Olaf, Bonin, Michael, Burn, David J, Human genetics, NCA - neurodegeneration, Graduate School, ANS - Amsterdam Neuroscience, and Neurology

Subjects
Adult, Male, statistics & numerical data [Databases, Factual], Databases, Factual, Genotype, genetics [Alzheimer Disease], Single-nucleotide polymorphism, Genome-wide association study, Disease, In Vitro Techniques, Biology, Bioinformatics, Polymorphism, Single Nucleotide, Article, Gene Frequency, genetics [Parkinson Disease], Alzheimer Disease, Risk Factors, medicine, Humans, Dementia, Genetic Predisposition to Disease, ddc:610, genetics [Genetic Predisposition to Disease], Allele, Allele frequency, Aged, Genetic association, Aged, 80 and over, Genetics, Parkinson Disease, Middle Aged, medicine.disease, United States, Europe, Meta-analysis, genetics [Polymorphism, Single Nucleotide], Female, Neurology (clinical), Genome-Wide Association Study
Abstract

Importance Despite Alzheimer disease (AD) and Parkinson disease (PD) being clinically distinct entities, there is a possibility of a pathological overlap, with some genome-wide association (GWA) studies suggesting that the 2 diseases represent a biological continuum. The application of GWA studies to idiopathic forms of AD and PD have identified a number of loci that contain genetic variants that increase the risk of these disorders. Objective To assess the genetic overlap between PD and AD by testing for the presence of potentially pleiotropic loci in 2 recent GWA studies of PD and AD. Design Combined GWA analysis. Setting Data sets from the United Kingdom, Germany, France, and the United States. Participants Thousands of patients with AD or PD and their controls. Main Outcomes and Measures Meta-analysis of GWA studies of AD and PD. Methods To identify evidence for potentially pleiotropic alleles that increased the risk for both PD and AD, we performed a combined PD-AD meta-analysis and compared the results with those obtained in the primary GWA studies. We also tested for a net effect of potentially polygenic alleles that were shared by both disorders by performing a polygenic score analysis. Finally, we also performed a gene-based association analysis that was aimed at detecting genes that harbor multiple disease-causing single-nucleotide polymorphisms, some of which confer a risk of PD and some a risk of AD. Results Detailed interrogation of the single-nucleotide polymorphism, polygenic, and gene-based analyses resulted in no significant evidence that supported the presence of loci that increase the risk of both PD and AD. Conclusions and Relevance Our findings therefore imply that loci that increase the risk of both PD and AD are not widespread and that the pathological overlap could instead be “downstream” of the primary susceptibility genes that increase the risk of each disease.

Published
2013
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2. Using genome-wide complex trait analysis to quantify 'missing heritability' in Parkinson's disease

Author

Keller, Margaux F, Saad, Mohamad, Schulte, Claudia, Limousin, Patricia, Lopez, Grisel, Lorenz, Delia, McNeill, Alisdair, Moorby, Catriona, Moore, Matthew, Morris, Huw R, Morrison, Karen E, Mudanohwo, Ese, O'Sullivan, Sean S, Moskvina, Valentina, Pearson, Justin, Perlmutter, Joel S, Pétursson, Hjörvar, Pollak, Pierre, Post, Bart, Potter, Simon, Ravina, Bernard, Revesz, Tamas, Riess, Olaf, Rivadeneira, Fernando, Durr, Alexandra, Rizzu, Patrizia, Ryten, Mina, Sawcer, Stephen, Schapira, Anthony, Scheffer, Hans, Shaw, Karen, Shoulson, Ira, Sidransky, Ellen, Smith, Colin, Spencer, Chris C A, Holmans, Peter, Stefánsson, Hreinn, Steinberg, Stacy, Stockton, Joanna D, Strange, Amy, Talbot, Kevin, Tanner, Carlie M, Tashakkori-Ghanbaria, Avazeh, Tison, François, Trabzuni, Daniah, Traynor, Bryan J, Kilarski, Laura L, Uitterlinden, André G, Velseboer, Daan, Vidailhet, Marie, Walker, Robert, van de Warrenburg, Bart, Wickremaratchi, Mirdhu, Williams, Nigel, Williams-Gray, Caroline H, Winder-Rhodes, Sophie, Stefánsson, Kári, Guerreiro, Rita, Martinez, Maria, Sabatier, Paul, Hardy, John, Brice, Alexis, Singleton, Andrew B, Wood, Nicholas W, Donnelly, Peter, Barroso, Ines, Blackwell, Jenefer M, Bramon, Elvira, Hernandez, Dena G, Brown, Matthew A, Casas, Juan P, Corvin, Aiden, Deloukas, Panos, Duncanson, Audrey, Jankowski, Janusz, Markus, Hugh S, Mathew, Christopher G, Palmer, Colin N A, Plomin, Robert, Rautanen, Anna, Sawcer, Stephen J, Trembath, Richard C, Viswanathan, Ananth C, Band, Gavin, Bellenguez, Céline, Freeman, Colin, Hellenthal, Garrett, Ylikotila, Pauli, Giannoulatou, Eleni, Pirinen, Matti, Pearson, Richard, Su, Zhan, Vukcevic, Damjan, Langford, Cordelia, Hunt, Sarah E, Edkins, Sarah, Gwilliam, Rhian, Blackburn, Hannah, Bumpstead, Suzannah J, Dronov, Serge, Gillman, Matthew, Gray, Emma, Hammond, Naomi, Jayakumar, Alagurevathi, McCann, Owen T, Liddle, Jennifer, Bras, Jose, Majamaa, Kari, Potter, Simon C, Ravindrarajah, Radhi, Ricketts, Michelle, Waller, Matthew, Weston, Paul, Widaa, Sara, Whittaker, Pamela, Gasser, Thomas, Heutink, Peter, Nalls, Michael A, Bettella, Francesco, Consortium, International Parkinson's Disease Genomics, 2, Wellcome Trust Case Control Consortium, Plagnol, Vincent, Sheerin, Una-Marie, Simón-Sánchez, Javier, Lesage, Suzanne, Sveinbjörnsdóttir, Sigurlaug, Nicolaou, Nayia, Arepalli, Sampath, Ben-Shlomo, Yoav, Berendse, Henk W, Berg, Daniela, Bhatia, Kailash, de Bie, Rob M A, Biffi, Alessandro, Bloem, Bas, Bochdanovits, Zoltan, Bonin, Michael, Brockmann, Kathrin, Brooks, Janet, Burn, David J, Charlesworth, Gavin, Chen, Honglei, Chinnery, Patrick F, Chong, Sean, Clarke, Carl E, Cookson, Mark R, Mittag, Florian, Cooper, J Mark, Corvol, Jean Christophe, Counsell, Carl, Damier, Philippe, Dartigues, Jean-François, Segalen, Victor, Deuschl, Günther, Dexter, David T, van Dijk, Karin D, Büchel, Finja, Dillman, Allissa, Durif, Frank, Montpied, Gabriel, Evans, Jonathan R, Foltynie, Thomas, Gao, Jianjun, Gardner, Michelle, Gibbs, J Raphael, Goate, Alison, Sharma, Manu, Gústafsson, Omar, Harris, Clare, van Hilten, Jacobus J, Hofman, Albert, Hollenbeck, Albert, Holton, Janice, Hu, Michele, Huang, Xuemei, Huber, Heiko, Hudson, Gavin, Huttenlocher, Johanna, Illig, Thomas, Jónsson, Pálmi V, Lambert, Jean-Charles, Lees, Andrew, Lichtner, Peter, ANS - Amsterdam Neuroscience, Neurology, ACS - Amsterdam Cardiovascular Sciences, Graduate School, Human genetics, and NCA - Neurodegeneration

Subjects
Adult, Male, medicine.medical_specialty, Multifactorial Inheritance, Parkinson's disease, Functional Neurogenomics Human Movement & Fatigue [DCN 2], Single-nucleotide polymorphism, Genome-wide association study, Quantitative trait locus, Biology, Genome, White People, 03 medical and health sciences, Quantitative Trait, Heritable, 0302 clinical medicine, genetics [Parkinson Disease], Missing heritability problem, Molecular genetics, ddc:570, medicine, Genetics, Humans, Genetic Predisposition to Disease, Molecular Biology, Genetics (clinical), Aged, 030304 developmental biology, Genetic association, Aged, 80 and over, 0303 health sciences, Association Studies Articles, Genetic Variation, Family aggregation, Parkinson Disease, General Medicine, Middle Aged, Heritability, medicine.disease, Corrigenda, 3. Good health, genetics [European Continental Ancestry Group], Human Movement & Fatigue [DCN MP - Plasticity and memory NCEBP 10], Female, Trait analysis, 030217 neurology & neurosurgery, Imputation (genetics), Genome-Wide Association Study
Abstract

Contains fulltext : 110130.pdf (Publisher’s version ) (Closed access) Genome-wide association studies (GWASs) have been successful at identifying single-nucleotide polymorphisms (SNPs) highly associated with common traits; however, a great deal of the heritable variation associated with common traits remains unaccounted for within the genome. Genome-wide complex trait analysis (GCTA) is a statistical method that applies a linear mixed model to estimate phenotypic variance of complex traits explained by genome-wide SNPs, including those not associated with the trait in a GWAS. We applied GCTA to 8 cohorts containing 7096 case and 19 455 control individuals of European ancestry in order to examine the missing heritability present in Parkinson's disease (PD). We meta-analyzed our initial results to produce robust heritability estimates for PD types across cohorts. Our results identify 27% (95% CI 17-38, P = 8.08E - 08) phenotypic variance associated with all types of PD, 15% (95% CI -0.2 to 33, P = 0.09) phenotypic variance associated with early-onset PD and 31% (95% CI 17-44, P = 1.34E - 05) phenotypic variance associated with late-onset PD. This is a substantial increase from the genetic variance identified by top GWAS hits alone (between 3 and 5%) and indicates there are substantially more risk loci to be identified. Our results suggest that although GWASs are a useful tool in identifying the most common variants associated with complex disease, a great deal of common variants of small effect remain to be discovered.

Published
2012
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