Mike A Nalls1, Cornelis Blauwendraat2, Costanza L Vallerga3, Karl Heilbron4, Sara Bandres-Ciga2, Diana Chang5, Manuela Tan6, Demis A Kia6, Alastair J Noyce7, Angli Xue8, Jose Bras9, Emily Young10, Rainer von Coelln11, Javier Simón-Sánchez12, Claudia Schulte12, Manu Sharma13, Lynne Krohn14, Lasse Pihlstrøm15, Ari Siitonen16, Hirotaka Iwaki17, Hampton Leonard18, Faraz Faghri19, J Raphael Gibbs2, Dena G Hernandez2, Sonja W Scholz20, Juan A Botia21, Maria Martinez22, Jean-Christophe Corvol23, Suzanne Lesage23, Joseph Jankovic10, Lisa M Shulman11, Margaret Sutherland24, Pentti Tienari25, Kari Majamaa16, Mathias Toft26, Ole A Andreassen27, Tushar Bangale5, Alexis Brice23, Jian Yang8, Ziv Gan-Or28, Thomas Gasser12, Peter Heutink12, Joshua M Shulman29, Nicholas W Wood6, David A Hinds4, John A Hardy30, Huw R Morris31, Jacob Gratten32, Peter M Visscher8, Robert R Graham5, Andrew B Singleton2. 1. Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA; Data Tecnica International, Glen Echo, MD, USA. Electronic address: mike@datatecnica.com. 2. Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA. 3. Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia. 4. 23andMe, Sunnyvale, CA, USA. 5. Department of Human Genetics, Genentech, South San Francisco, CA, USA. 6. Department of Molecular Neuroscience, UCL Queen Square Institute of Neurology, London, UK; Department of Clinical and Movement Neuroscience and UCL Movement Disorders Centre, UCL Queen Square Institute of Neurology, London, UK. 7. Department of Molecular Neuroscience, UCL Queen Square Institute of Neurology, London, UK; Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, UK. 8. Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia; Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia. 9. Department of Neurodegenerative Diseases, UCL Queen Square Institute of Neurology, London, UK; Center for Neurodegenerative Science, Van Andel Research Institute, Grand Rapids, MI, USA. 10. Department of Neurology, Baylor College of Medicine, Houston, TX, USA. 11. Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA. 12. Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany; German Center for Neurodegenerative Diseases, Tübingen, Germany. 13. Centre for Genetic Epidemiology, Institute for Clinical Epidemiology and Applied Biometry, University of Tübingen, Tübingen, Germany. 14. Department of Human Genetics, McGill University, Montreal, QC, Canada; Montreal Neurological Institute, McGill University, Montreal, QC, Canada. 15. Department of Neurology, Oslo University Hospital, Oslo, Norway. 16. Institute of Clinical Medicine, Department of Neurology, University of Oulu, Oulu, Finland; Department of Neurology and Medical Research Center, Oulu University Hospital, Oulu, Finland. 17. Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA; Data Tecnica International, Glen Echo, MD, USA; The Michael J Fox Foundation, New York, NY, USA. 18. Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA; Data Tecnica International, Glen Echo, MD, USA. 19. Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA; Department of Computer Science, University of Illinois Urbana-Champaign, Champaign, IL, USA. 20. National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA. 21. Department of Molecular Neuroscience, UCL Queen Square Institute of Neurology, London, UK; Departamento de Ingeniería de la Información y las Comunicaciones, Universidad de Murcia, Spain. 22. Institut national de la santé et de la recherche médicale Unité mixte de recherche 1220, Toulouse, France; Paul Sabatier University, Toulouse, France. 23. Institut national de la santé et de la recherche médicale U1127, CNRS UMR 7225, Paris, France; Sorbonne Université centre national de la recherche médicale, unité mixte de recherche 1127, Paris, France; Assistance Publique Hôpitaux de Paris, Paris, France; Institut du Cerveau et de la Moelle épinière, Paris, France. 24. National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA. 25. Clinical Neurosciences, Neurology, University of Helsinki, Helsinki, Finland; Helsinki University Hospital, Helsinki, Finland. 26. Department of Neurology, Oslo University Hospital, Oslo, Norway; Institute of Clinical Medicine, University of Oslo, Oslo, Norway. 27. Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Jebsen Centre for Psychosis Research, University of Oslo, Oslo, Norway. 28. Department of Human Genetics, McGill University, Montreal, QC, Canada; Montreal Neurological Institute, McGill University, Montreal, QC, Canada; Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada. 29. Department of Neurology, Baylor College of Medicine, Houston, TX, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA; Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA; Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA. 30. Department of Molecular Neuroscience, UCL Queen Square Institute of Neurology, London, UK. 31. Department of Clinical and Movement Neuroscience and UCL Movement Disorders Centre, UCL Queen Square Institute of Neurology, London, UK. 32. Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia; Mater Research Institute, The University of Queensland, Brisbane, QLD, Australia.
Abstract
BACKGROUND: Genome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease. METHODS: We did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type, and biological pathway enrichments for the identified risk factors. Additionally, we examined shared genetic risk between Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation. FINDINGS: Between Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16-36% of the heritable risk of Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10-7). INTERPRETATION: These data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data. FUNDING: The National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources).
BACKGROUND: Genome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease. METHODS: We did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type, and biological pathway enrichments for the identified risk factors. Additionally, we examined shared genetic risk between Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation. FINDINGS: Between Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16-36% of the heritable risk of Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10-7). INTERPRETATION: These data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data. FUNDING: The National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources).
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Authors: Michael A Nalls; Vincent Plagnol; Dena G Hernandez; Manu Sharma; Una-Marie Sheerin; Mohamad Saad; J Simón-Sánchez; Claudia Schulte; Suzanne Lesage; Sigurlaug Sveinbjörnsdóttir; Kári Stefánsson; Maria Martinez; John Hardy; Peter Heutink; Alexis Brice; Thomas Gasser; Andrew B Singleton; Nicholas W Wood Journal: Lancet Date: 2011-02-01 Impact factor: 79.321
Authors: Hon-Chung Fung; Sonja Scholz; Mar Matarin; Javier Simón-Sánchez; Dena Hernandez; Angela Britton; J Raphael Gibbs; Carl Langefeld; Matt L Stiegert; Jennifer Schymick; Michael S Okun; Ronald J Mandel; Hubert H Fernandez; Kelly D Foote; Ramón L Rodríguez; Elizabeth Peckham; Fabienne Wavrant De Vrieze; Katrina Gwinn-Hardy; John A Hardy; Andrew Singleton Journal: Lancet Neurol Date: 2006-11 Impact factor: 44.182
Authors: Lynne Krohn; Francis P Grenn; Mary B Makarious; Jonggeol Jeffrey Kim; Sara Bandres-Ciga; Dorien A Roosen; Ziv Gan-Or; Mike A Nalls; Andrew B Singleton; Cornelis Blauwendraat Journal: Neurobiol Aging Date: 2020-03-10 Impact factor: 4.673