Francis P Grenn1, Jonggeol J Kim1, Mary B Makarious1, Hirotaka Iwaki1,2, Anastasia Illarionova3, Kajsa Brolin4, Jillian H Kluss1, Artur F Schumacher-Schuh5, Hampton Leonard1,2, Faraz Faghri1,2, Kimberley Billingsley1, Lynne Krohn6, Ashley Hall7, Monica Diez-Fairen8, Maria Teresa Periñán9, Jia Nee Foo10,11, Cynthia Sandor12, Caleb Webber12, Brian K Fiske13, J Raphael Gibbs1, Mike A Nalls1,2, Andrew B Singleton1, Sara Bandres-Ciga1, Xylena Reed1, Cornelis Blauwendraat1. 1. Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA. 2. Data Tecnica International, Glen Echo, Maryland, USA. 3. German Center for Neurodegenerative Diseases, Tubingen, Germany. 4. Lund University, Translational Neurogenetics Unit, Department of Experimental Medical Science, Lund, Sweden. 5. Universidade Federal do Rio Grande do Sul, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil. 6. Department of Human Genetics, McGill University, Montreal, Quebec, Canada. 7. Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK. 8. Fundació Docència i Recerca Mútua Terrassa and Movement Disorders Unit, Department of Neurology, University Hospital Mútua Terrassa, Barcelona, Spain. 9. Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain. 10. Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore. 11. Human Genetics, Genome Institute of Singapore, A*STAR, Singapore, Singapore. 12. UK Dementia Research Institute, Cardiff University, Cardiff, UK. 13. The Michael J. Fox Foundation for Parkinson's Research, Grand Central Station, New York, NY, USA.
Abstract
BACKGROUND: Parkinson's disease (PD) is a neurodegenerative disease with an often complex component identifiable by genome-wide association studies. The most recent large-scale PD genome-wide association studies have identified more than 90 independent risk variants for PD risk and progression across more than 80 genomic regions. One major challenge in current genomics is the identification of the causal gene(s) and variant(s) at each genome-wide association study locus. The objective of the current study was to create a tool that would display data for relevant PD risk loci and provide guidance with the prioritization of causal genes and potential mechanisms at each locus. METHODS: We included all significant genome-wide signals from multiple recent PD genome-wide association studies including themost recent PD risk genome-wide association study, age-at-onset genome-wide association study, progression genome-wide association study, and Asian population PD risk genome-wide association study. We gathered data for all genes 1 Mb up and downstream of each variant to allow users to assess which gene(s) are most associated with the variant of interest based on a set of self-ranked criteria. Multiple databases were queried for each gene to collect additional causal data. RESULTS: We created a PD genome-wide association study browser tool (https://pdgenetics.shinyapps.io/GWASBrowser/) to assist the PD research community with the prioritization of genes for follow-up functional studies to identify potential therapeutic targets. CONCLUSIONS: Our PD genome-wide association study browser tool provides users with a useful method of identifying potential causal genes at all known PD risk loci from large-scale PD genome-wide association studies. We plan to update this tool with new relevant data as sample sizes increase and new PD risk loci are discovered.
BACKGROUND: Parkinson's disease (PD) is a neurodegenerative disease with an often complex component identifiable by genome-wide association studies. The most recent large-scale PD genome-wide association studies have identified more than 90 independent risk variants for PD risk and progression across more than 80 genomic regions. One major challenge in current genomics is the identification of the causal gene(s) and variant(s) at each genome-wide association study locus. The objective of the current study was to create a tool that would display data for relevant PD risk loci and provide guidance with the prioritization of causal genes and potential mechanisms at each locus. METHODS: We included all significant genome-wide signals from multiple recent PD genome-wide association studies including themost recent PD risk genome-wide association study, age-at-onset genome-wide association study, progression genome-wide association study, and Asian population PD risk genome-wide association study. We gathered data for all genes 1 Mb up and downstream of each variant to allow users to assess which gene(s) are most associated with the variant of interest based on a set of self-ranked criteria. Multiple databases were queried for each gene to collect additional causal data. RESULTS: We created a PD genome-wide association study browser tool (https://pdgenetics.shinyapps.io/GWASBrowser/) to assist the PD research community with the prioritization of genes for follow-up functional studies to identify potential therapeutic targets. CONCLUSIONS: Our PD genome-wide association study browser tool provides users with a useful method of identifying potential causal genes at all known PD risk loci from large-scale PD genome-wide association studies. We plan to update this tool with new relevant data as sample sizes increase and new PD risk loci are discovered.
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