Publication:
A multi-omics dataset for the analysis of frontotemporal dementia genetic subtypes

dc.bibliographiccitation.issue1
dc.bibliographiccitation.journalScientific Data
dc.bibliographiccitation.volume10
dc.contributor.authorMenden, Kevin
dc.contributor.authorFrancescatto, Margherita
dc.contributor.authorNyima, Tenzin
dc.contributor.authorBlauwendraat, Cornelis
dc.contributor.authorDhingra, Ashutosh
dc.contributor.authorCastillo-Lizardo, Melissa
dc.contributor.authorFernandes, Noémia
dc.contributor.authorKaurani, Lalit
dc.contributor.authorKronenberg-Versteeg, Deborah
dc.contributor.authorAtasu, Burcu
dc.contributor.authorHeutink, Peter
dc.date.accessioned2024-01-14T22:44:30Z
dc.date.available2024-01-14T22:44:30Z
dc.date.issued2023
dc.description.abstractAbstract 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.
dc.description.sponsorshipNOMIS Stiftung https://doi.org/10.13039/501100008483
dc.description.sponsorshipEU Joint Programme – Neurodegenerative Disease Research https://doi.org/10.13039/100013278
dc.identifier.doi10.1038/s41597-023-02598-x
dc.identifier.pii2598
dc.identifier.urihttps://resolver.sub.uni-goettingen.de/purl?gro-2/139716
dc.item.fulltextNo Fulltext
dc.language.isoen
dc.notes.internDOI-Import GROB-726
dc.relation.eissn2052-4463
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.titleA multi-omics dataset for the analysis of frontotemporal dementia genetic subtypes
dc.typejournal_article
dc.type.internalPublicationyes
dspace.entity.typePublication

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