DecOmPress | Decoding spatio-temporal omics in progressive neuroinflammation

Summary
Multiple sclerosis (MS) is a paradigmatic progressive neuroinflammatory disease characterized by multiple lesions across the entire central nervous system including both gray and white matter areas. Deconvoluting the spatio-temporal cellular and molecular landscape is therefore key to understanding underlying disease mechanisms and to develop cell-type specific therapies. The DecOmPress proposal is about integrative human and mouse single-cell genomic strategies to track-down reactive cellular states in compartmentalized progressive neuroinflammation. DecOmPress has two major research tracks (RTs).

RT1 is an MS tissue discovery pipeline utilizing single-nucleus RNA and open chromatin sequencing. RT1 is about developing novel integrative computational tools to process sequencing data from different anatomical lesion areas implementing a large multiplex single-nucleus genomic dataset from the anterior visual system. RT1 is also about decoding compartmentalized inflammation in meningeal versus perivascular tissue niches.

RT2 is a functional validation pipeline utilizing complex transgenic and disease mouse models as well as human organoids in combination with single-cell physiology and genomics. RT2 is about dissecting glial-intrinsic mechanisms at the chronically inflamed white matter lesion rim focusing on MS-specific oligodendrocyte and microglia subtypes. RT2 is also about decoding neuron subtype specific pathologies focusing on projection neurons and the contribution of local (meningeal) and distant (white matter tracts) inflammation and demyelination to cell-type specific neurodegeneration.

In summary, DecOmPress is a highly innovative and fully translational multidisciplinary proposal aiming at identifying novel cell-type specific disease mechanisms and therapeutic targets.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/950584
Start date: 01-01-2021
End date: 31-12-2025
Total budget - Public funding: 1 500 000,00 Euro - 1 500 000,00 Euro
Cordis data

Original description

Multiple sclerosis (MS) is a paradigmatic progressive neuroinflammatory disease characterized by multiple lesions across the entire central nervous system including both gray and white matter areas. Deconvoluting the spatio-temporal cellular and molecular landscape is therefore key to understanding underlying disease mechanisms and to develop cell-type specific therapies. The DecOmPress proposal is about integrative human and mouse single-cell genomic strategies to track-down reactive cellular states in compartmentalized progressive neuroinflammation. DecOmPress has two major research tracks (RTs).

RT1 is an MS tissue discovery pipeline utilizing single-nucleus RNA and open chromatin sequencing. RT1 is about developing novel integrative computational tools to process sequencing data from different anatomical lesion areas implementing a large multiplex single-nucleus genomic dataset from the anterior visual system. RT1 is also about decoding compartmentalized inflammation in meningeal versus perivascular tissue niches.

RT2 is a functional validation pipeline utilizing complex transgenic and disease mouse models as well as human organoids in combination with single-cell physiology and genomics. RT2 is about dissecting glial-intrinsic mechanisms at the chronically inflamed white matter lesion rim focusing on MS-specific oligodendrocyte and microglia subtypes. RT2 is also about decoding neuron subtype specific pathologies focusing on projection neurons and the contribution of local (meningeal) and distant (white matter tracts) inflammation and demyelination to cell-type specific neurodegeneration.

In summary, DecOmPress is a highly innovative and fully translational multidisciplinary proposal aiming at identifying novel cell-type specific disease mechanisms and therapeutic targets.

Status

SIGNED

Call topic

ERC-2020-STG

Update Date

27-04-2024
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Horizon 2020
H2020-EU.1. EXCELLENT SCIENCE
H2020-EU.1.1. EXCELLENT SCIENCE - European Research Council (ERC)
ERC-2020
ERC-2020-STG