Risk and modifying factors in Frontotemporal Dementia
Understanding the molecular mechanisms underlying frontotemporal dementia (FTD) is essential for the development of successful therapies. Here, we present Phase 1 of a multi-omics, multi-model data resource for FTD research which will allows in-depth molecular research into these mechanisms. We have integrated and analysed data from the frontal lobe of FTD patients with mutations in MAPT, GRN and C9orf72 and detected common and distinct dysregulated cellular pathways. Our results highlight that excitatory neurons are the most vulnerable neuronal cell type and that vascular aberrations are a common hallmark in FTD. Via integration of multi-omics data, we detected several transcription factors and pathways which regulate the strong neuroinflammation observed in FTD-GRN. Finally, using small RNA-seq data and verification experiments in cellular models, we identified several up-regulated miRNAs that inhibit cellular trafficking pathways in FTD and lead to microglial activation. In this work we shed light on novel mechanistic and pathophysiological hallmarks of FTD. In addition, we believe that this comprehensive, multi-omics data resource will further mechanistic FTD research by the community.
- Type: Other
- Archiver: European Genome-Phenome Archive (EGA)
Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data
Dataset ID | Description | Technology | Samples |
---|---|---|---|
EGAD00001006842 | NextSeq 550 | 30 | |
EGAD00001006843 | Illumina HiSeq 2000 | 57 | |
EGAD00001006844 | NextSeq 550 | 15 | |
EGAD00001006845 | NextSeq 550 | 33 | |
EGAD00001006846 | NextSeq 550 | 9 | |
EGAD00001008014 | Illumina HiSeq 2500 NextSeq 550 | 47 | |
EGAD00010002055 | Illumina Infinium MethylationEPIC BeadChip | 47 |
Publications | Citations |
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Pathogen detection in RNA-seq data with Pathonoia.
BMC Bioinformatics 24: 2023 53 |
3 |