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@ARTICLE{Bressan:257318,
      author       = {Bressan, Elisangela and Reed, Xylena and Bansal, Vikas and
                      Hutchins, Elizabeth and Cobb, Melanie M and Webb, Michelle G
                      and Alsop, Eric and Grenn, Francis P and Illarionova,
                      Anastasia and Savytska, Natalia and Violich, Ivo and Bröer,
                      Stefanie and Alves Fernandes, Noemia Rita and Sivakumar,
                      Ramiyapriya and Beilina, Alexandra and Billingsley,
                      Kimberley J and Berghausen, Joos and Pantazis, Caroline B
                      and Pitz, Vanessa and Patel, Dhairya and Daida, Kensuke and
                      Meechoovet, Bessie and Reiman, Rebecca and Courtright-Lim,
                      Amanda and Logemann, Amber and Antone, Jerry and Barch,
                      Mariya and Kitchen, Robert and Li, Yan and Dalgard, Clifton
                      L and Rizzu, Patrizia and Hernandez, Dena Michelle Godwin
                      and Hjelm, Brooke E and Nalls, Mike and Gibbs, J Raphael and
                      Finkbeiner, Steven and Cookson, Mark R and Van
                      Keuren-Jensen, Kendall and Craig, David W and Singleton,
                      Andrew B and Heutink, Peter and Blauwendraat, Cornelis},
      collaboration = {Center, American Genome},
      title        = {{T}he {F}oundational {D}ata {I}nitiative for {P}arkinson
                      {D}isease: {E}nabling efficient translation from genetic
                      maps to mechanism.},
      journal      = {Cell genomics},
      volume       = {3},
      number       = {3},
      issn         = {2666-979X},
      address      = {Amsterdam},
      publisher    = {Elsevier},
      reportid     = {DZNE-2023-00387},
      pages        = {100261},
      year         = {2023},
      note         = {CC BY},
      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.},
      keywords     = {Parkinson disease (Other) / dopaminergic neurons (Other) /
                      genetic risk (Other) / induced pluripotent stem cell (Other)
                      / omics single-cell RNA sequencing single-cell ATAC
                      sequencing SNCA LRRK2 GBA1 (Other)},
      cin          = {AG Heutink 1 / AG Rizzu / Core ICRU},
      ddc          = {610},
      cid          = {I:(DE-2719)1210002 / I:(DE-2719)1210009 /
                      I:(DE-2719)1240005},
      pnm          = {354 - Disease Prevention and Healthy Aging (POF4-354)},
      pid          = {G:(DE-HGF)POF4-354},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:36950378},
      pmc          = {pmc:PMC10025424},
      doi          = {10.1016/j.xgen.2023.100261},
      url          = {https://pub.dzne.de/record/257318},
}