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Integration of Functional Genomics Data to Uncover Cell Type-specific Pathways Affected in Parkinson's Disease

Overview
Specialty Biochemistry
Date 2021 Sep 28
PMID 34581766
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Abstract

Parkinson's disease (PD) is the second most prevalent late-onset neurodegenerative disorder worldwide after Alzheimer's disease for which available drugs only deliver temporary symptomatic relief. Loss of dopaminergic neurons (DaNs) in the substantia nigra and intracellular alpha-synuclein inclusions are the main hallmarks of the disease but the events that cause this degeneration remain uncertain. Despite cell types other than DaNs such as astrocytes, microglia and oligodendrocytes have been recently associated with the pathogenesis of PD, we still lack an in-depth characterisation of PD-affected brain regions at cell-type resolution that could help our understanding of the disease mechanisms. Nevertheless, publicly available large-scale brain-specific genomic, transcriptomic and epigenomic datasets can be further exploited to extract different layers of cell type-specific biological information for the reconstruction of cell type-specific transcriptional regulatory networks. By intersecting disease risk variants within the networks, it may be possible to study the functional role of these risk variants and their combined effects at cell type- and pathway levels, that, in turn, can facilitate the identification of key regulators involved in disease progression, which are often potential therapeutic targets.

References
1.
Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J . STRING v10: protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Res. 2014; 43(Database issue):D447-52. PMC: 4383874. DOI: 10.1093/nar/gku1003. View

2.
Annese A, Manzari C, Lionetti C, Picardi E, Horner D, Chiara M . Whole transcriptome profiling of Late-Onset Alzheimer's Disease patients provides insights into the molecular changes involved in the disease. Sci Rep. 2018; 8(1):4282. PMC: 5844946. DOI: 10.1038/s41598-018-22701-2. View

3.
Sinnamon J, Torkenczy K, Linhoff M, Vitak S, Mulqueen R, Pliner H . The accessible chromatin landscape of the murine hippocampus at single-cell resolution. Genome Res. 2019; 29(5):857-869. PMC: 6499306. DOI: 10.1101/gr.243725.118. View

4.
Zeng W, Chen X, Duren Z, Wang Y, Jiang R, Wong W . DC3 is a method for deconvolution and coupled clustering from bulk and single-cell genomics data. Nat Commun. 2019; 10(1):4613. PMC: 6787340. DOI: 10.1038/s41467-019-12547-1. View

5.
Chen L, Ge B, Casale F, Vasquez L, Kwan T, Garrido-Martin D . Genetic Drivers of Epigenetic and Transcriptional Variation in Human Immune Cells. Cell. 2016; 167(5):1398-1414.e24. PMC: 5119954. DOI: 10.1016/j.cell.2016.10.026. View