Using genome-wide complex trait analysis to quantify 'missing heritability' in Parkinson's disease
Year: 2012
Type: review
Study design: Observational Study
Abstract: 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.
Source: Human Molecular Genetics
DOI: 10.1093/hmg/dds335
Authors: M. F. Keller, M. Saad, J. Bras, F. Bettella, N. Nicolaou, J. Simon-Sanchez, F. Mittag, F. Buchel, M. Sharma, J. R. Gibbs, C. Schulte, V. Moskvina, A. Durr, P. Holmans, L. L. Kilarski, R. Guerreiro, D. G. Hernandez, A. Brice, P. Ylikotila, H. Stefansson, K. Majamaa, H. R. Morris, N. Williams, T. Gasser, P. Heutink, N. W. Wood, J. Hardy, M. Martinez, A. B. Singleton, M. A. Nalls
Institutions: National Institutes of Health, National Institute on Aging, Temple University, Université Toulouse III - Paul Sabatier, Inserm, Centre de Physiopathologie de Toulouse-Purpan, UCL Queen Square Institute of Neurology, deCODE Genetics (Iceland), Amsterdam UMC Location Vrije Universiteit Amsterdam, German Center for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, Cardiff University, Medical Research Council, Centre National de la Recherche Scientifique, Assistance Publique – Hôpitaux de Paris, Pitié-Salpêtrière Hospital, Institut du Cerveau, Université Pierre-et-Marie-Curie, University of Turku, Turku University Hospital, University of Oulu, University College London
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
Funders: Wellcome Trust, National Institute for Health and Care Research, Parkinson's UK, National Institutes of Health, Medical Research Council, National Institute on Aging, National Institute of Neurological Disorders and Stroke, National Institute of Environmental Health Sciences, National Center for Research Resources, National Center for Advancing Translational Sciences
Awards: G1859083642, G20482478, Prospective studies on Parkinson's disease, Washington University Center for Translational Neuroscience, G3945394334, G4467312596, G4635709268, G4653495942, WTCCC Part Two., G5138458822, MECHANISMS OF DEEP BRAIN STIMULATION, G695839759, Understanding the genetic basis of common human diseases: core funding for the Wellcome Trust Centre for Human Genetics., Investigations of Dementia in Parkinson Disease, Washington University Institute of Clinical and Translational Sciences, G7310981802, G7433172200, G7642341095, Washington University Institute of Clinical and Translational Sciences (UL1), Genome wide SNP analysis in Parkinson's disease, A systematic investigation into the pathogenesis and course of Parkinson's syndrome., G9000082987, G992107779
OpenAlex ID: W2132869184