The Foundational Data Initiative for Parkinson Disease: Enabling efficient translation from genetic maps to mechanism

帕金森病基础数据计划:实现从基因图谱到机制的高效转化

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作者:Elisangela Bressan ,Xylena Reed ,Vikas Bansal ,Elizabeth Hutchins ,Melanie M Cobb ,Michelle G Webb ,Eric Alsop ,Francis P Grenn ,Anastasia Illarionova ,Natalia Savytska ,Ivo Violich ,Stefanie Broeer ,Noémia Fernandes ,Ramiyapriya Sivakumar ,Alexandra Beilina ,Kimberley J Billingsley ,Joos Berghausen ,Caroline B Pantazis ,Vanessa Pitz ,Dhairya Patel ,Kensuke Daida ,Bessie Meechoovet ,Rebecca Reiman ,Amanda Courtright-Lim ,Amber Logemann ,Jerry Antone ,Mariya Barch ,Robert Kitchen ,Yan Li ,Clifton L Dalgard ,Dena G Hernandez ,Brooke E Hjelm ,Mike Nalls ,J Raphael Gibbs ,Steven Finkbeiner ,Mark R Cookson ,Kendall Van Keuren-Jensen ,David W Craig ,Andrew B Singleton ,Peter Heutink ,Cornelis Blauwendraat

Abstract

The Foundational Data Initiative for Parkinson Disease (FOUNDIN-PD) is an international collaboration producing fundamental resources for Parkinson disease (PD). FOUNDIN-PD generated a multi-layered molecular dataset in a cohort of induced pluripotent stem cell (iPSC) lines differentiated to dopaminergic (DA) neurons, a major affected cell type in PD. The lines were derived from the Parkinson's Progression Markers Initiative study, which included participants with PD carrying monogenic PD variants, variants with intermediate effects, and variants identified by genome-wide association studies and unaffected individuals. We generated genetic, epigenetic, regulatory, transcriptomic, and longitudinal cellular imaging data from iPSC-derived DA neurons to understand molecular relationships between disease-associated genetic variation and proximate molecular events. These data reveal that iPSC-derived DA neurons provide a valuable cellular context and foundational atlas for modeling PD genetic risk. We have integrated these data into a FOUNDIN-PD data browser as a resource for understanding the molecular pathogenesis of PD.

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