% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Menden:266115,
      author       = {Menden, Kevin and Francescatto, Margherita and Nyima,
                      Tenzin and Blauwendraat, Cornelis and Dhingra, Ashutosh and
                      Castillo Lizardo, Melissa Gissel and Fernandes, Noémia and
                      Kaurani, Lalit and Kronenberg-Versteeg, Deborah and Atasu,
                      Burcu and Sadikoglou, Eldem and Borroni, Barbara and
                      Rodriguez-Nieto, Salvador and Simon Sanchez, Javier and
                      Fischer, Andre and Craig, David Wesley and Neumann, Manuela
                      and Bonn, Stefan and Rizzu, Patrizia and Heutink, Peter},
      title        = {{A} multi-omics dataset for the analysis of frontotemporal
                      dementia genetic subtypes.},
      journal      = {Scientific data},
      volume       = {10},
      number       = {1},
      issn         = {2052-4436},
      address      = {London},
      publisher    = {Nature Publ. Group},
      reportid     = {DZNE-2023-01109},
      pages        = {849},
      year         = {2023},
      abstract     = {Understanding the molecular mechanisms underlying
                      frontotemporal dementia (FTD) is essential for the
                      development of successful therapies. Systematic studies on
                      human post-mortem brain tissue of patients with genetic
                      subtypes of FTD are currently lacking. The Risk and Modyfing
                      Factors of Frontotemporal Dementia (RiMod-FTD) consortium
                      therefore has generated a multi-omics dataset for genetic
                      subtypes of FTD to identify common and distinct molecular
                      mechanisms disturbed in disease. Here, we present
                      multi-omics datasets generated from the frontal lobe of
                      post-mortem human brain tissue from patients with mutations
                      in MAPT, GRN and C9orf72 and healthy controls. This data
                      resource consists of four datasets generated with different
                      technologies to capture the transcriptome by RNA-seq, small
                      RNA-seq, CAGE-seq, and methylation profiling. We show
                      concrete examples on how to use the resulting data and
                      confirm current knowledge about FTD and identify new
                      processes for further investigation. This extensive
                      multi-omics dataset holds great value to reveal new research
                      avenues for this devastating disease.},
      keywords     = {Humans / Frontal Lobe / Frontotemporal Dementia: genetics /
                      Multiomics / Mutation},
      cin          = {AG Heutink / AG Rizzu / AG Fischer / AG Jucker / AG
                      Neumann},
      ddc          = {500},
      cid          = {I:(DE-2719)1210002 / I:(DE-2719)1210009 /
                      I:(DE-2719)1410002 / I:(DE-2719)1210001 /
                      I:(DE-2719)1210003},
      pnm          = {354 - Disease Prevention and Healthy Aging (POF4-354) / 352
                      - Disease Mechanisms (POF4-352)},
      pid          = {G:(DE-HGF)POF4-354 / G:(DE-HGF)POF4-352},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:38040703},
      pmc          = {pmc:PMC10692098},
      doi          = {10.1038/s41597-023-02598-x},
      url          = {https://pub.dzne.de/record/266115},
}