Downstream Analysis of Genetic Variation in Parkinson's Disease
While GWAS have identified many common variants associated with complex diseases like PD, it is follow-up analyses that have started to decode GWAS results, and more downstream analysis is needed to unravel the implications of observed genetic variation in PD. Three types of analysis were the focus for the downstream analyses of the genetic variation topics, including colocalization, variant interaction, and network generation and visualization. Colocalization analysis allows the calculation and estimation of the correlation between a GWAS locus and an expression quantitative trait locus (eQTL). Variant interaction, or epistasis, is an interaction of genetic variation at two or more loci to produce a phenotypic outcome that is not predicted by the additive combination of effects attributable to the individual loci14 (link). Its importance in humans continues to be a matter of debate15 (link),16 (link), but it may explain some of the “missing heritability” underlying complex diseases such as PD16 (link)–18 (link). In addition to investigating individual variant effects with colocalization and epistasis, visualizing biological networks can help with understanding complex molecular relationships and interactions. In PD research, genetic and gene expression data has been used in community network analysis to nominate pathways and genes for drug target and functional prioritization19 (link),20 (link).
Leonard H.L., Murtadha R., Martinez-Carrasco A., Jama A., Müller-Nedebock A.C., Gil-Martinez A.L., Illarionova A., Moore A., Bustos B.I., Jadhav B., Huxford B., Storm C., Towns C., Vitale D., Chetty D., Yu E., Grenn F.P., Salazar G., Rateau G., Iwaki H., Elsayed I., Foote I.F., Jansen van Rensburg Z., Kim J.J., Yuan J., Lake J., Brolin K., Senkevich K., Wu L., Tan M.M., Periñán M.T., Makarious M.B., Ta M., Pillay N.S., Betancor O.L., Reyes-Pérez P.R., Alvarez Jerez P., Saini P., al-Ouran R., Sivakumar R., Real R., Reynolds R.H., Hu R., Abrahams S., Rao S.C., Antar T., Leal T.P., Iankova V., Scotton W.J., Song Y., Singleton A., Nalls M.A., Dey S., Bandres-Ciga S., Blauwendraat C, & Noyce A.J. (2023). The IPDGC/GP2 Hackathon - an open science event for training in data science, genomics, and collaboration using Parkinson’s disease data. NPJ Parkinson's Disease, 9, 33.
Publication 2023
Biological Drug targetGene expressionGenes Genetic Genetic variation Gwas Humans Interaction variation Phenotypic Quantitative trait locus
Corresponding Organization : National Institutes of Health
Other organizations :
National Institute of Neurological Disorders and Stroke, University College London, National Hospital for Neurology and Neurosurgery, Stellenbosch University, German Center for Neurodegenerative Diseases, Northwestern University, Child Health and Development Institute, Queen Mary University of London, McGill University, Institut du Cerveau, University of Gezira, Brigham and Women's Hospital, Harvard University, Lund University, Hospital Universitario Virgen del Rocío, Instituto de Biomedicina de Sevilla, Universidad de Sevilla, South African Medical Research Council, University of the Western Cape, South African National Biodiversity Institute, VA Puget Sound Health Care System, Universidad Nacional Autónoma de México, Baylor College of Medicine, University of Southern California, Cleveland Clinic, Ludwig-Maximilians-Universität München
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