Summary
The increasing clinical and societal burden of metabolic-associated fatty liver disease (MAFLD) coupled with the current lack of therapies highlights the need for a better understanding of the mechanisms driving this disease. In recent years, studies, including my own, have identified that MAFLD is accompanied by a change in the T cell subsets present in the liver and blood. However, the functions and causes of these altered populations remain largely unknown. Conventional dendritic cells (cDCs) function to sample antigens in the periphery and subsequently migrate to the lymph nodes (LNs) where they induce the proliferation and polarisation of naïve T cells, which then home back to the periphery to perform their functions. As such, by manipulating cDC function, we could potentially alter the T cells present in MAFLD and hence improve disease outcome. To date, studies of cDC function in MAFLD have been hampered by our limited understanding of cDC heterogeneity and the lack of specific tools with which to manipulate them in vivo. Building on the cDC expertise of the host lab, the single cell technologies established to dissect heterogeneity, and access to more specific models to target these cells, here, I aim to dissect cDC heterogeneity in the fatty liver. To this end, I will combine the mouse models of the host lab, with my expertise working with human material to identify the conserved features across humans and mice. As MAFLD is associated with an increase in CD8+ T cells, I hypothesize that by manipulating the main cDC subset associated with cross-presentation of antigen to naïve CD8+ T cells, namely the cDC1s, I can manipulate disease progression. Using the novel XCR1-CRE mouse model to specifically target cDC1s in vivo, I will investigate the in vivo functions of these cells in MAFLD and determine their potential for therapeutic intervention to improve patient outcome.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101027833 |
| Start date: | 01-04-2021 |
| End date: | 31-03-2023 |
| Total budget - Public funding: | 166 320,00 Euro - 166 320,00 Euro |
Cordis data
Original description
The increasing clinical and societal burden of metabolic-associated fatty liver disease (MAFLD) coupled with the current lack of therapies highlights the need for a better understanding of the mechanisms driving this disease. In recent years, studies, including my own, have identified that MAFLD is accompanied by a change in the T cell subsets present in the liver and blood. However, the functions and causes of these altered populations remain largely unknown. Conventional dendritic cells (cDCs) function to sample antigens in the periphery and subsequently migrate to the lymph nodes (LNs) where they induce the proliferation and polarisation of naïve T cells, which then home back to the periphery to perform their functions. As such, by manipulating cDC function, we could potentially alter the T cells present in MAFLD and hence improve disease outcome. To date, studies of cDC function in MAFLD have been hampered by our limited understanding of cDC heterogeneity and the lack of specific tools with which to manipulate them in vivo. Building on the cDC expertise of the host lab, the single cell technologies established to dissect heterogeneity, and access to more specific models to target these cells, here, I aim to dissect cDC heterogeneity in the fatty liver. To this end, I will combine the mouse models of the host lab, with my expertise working with human material to identify the conserved features across humans and mice. As MAFLD is associated with an increase in CD8+ T cells, I hypothesize that by manipulating the main cDC subset associated with cross-presentation of antigen to naïve CD8+ T cells, namely the cDC1s, I can manipulate disease progression. Using the novel XCR1-CRE mouse model to specifically target cDC1s in vivo, I will investigate the in vivo functions of these cells in MAFLD and determine their potential for therapeutic intervention to improve patient outcome.Status
CLOSEDCall topic
MSCA-IF-2020Update Date
28-04-2024
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