Summary
Alzheimer’s disease (AD) has far-reaching societal and economic consequences, emphasizing the urgent need for effective treatment solutions. However, to date, over 99% of AD clinical trials have failed. Inadequate patient stratification is a key contributing factor due to the enormous clinical and pathological heterogeneity in AD. AD is characterized by the aggregation of pathogenic proteins, with tau aggregates being a key player. Tau-related pathological processes lead to synaptic dysfunction, neurodegeneration, and eventually dementia. It is thus of paramount importance to decipher the mechanisms of tau deposition and spread. Emerging evidence suggests that tau tangles accumulate along specific macroscale brain networks, lending support to the hypothesis of tau spreading through communicating neurons. Network-based spreading models have provided insights along this line. I aim to contribute to a leap in network-based modelling of tau spread, by developing a novel patient-specific network model, coupled with a diffusion framework to study tau spread. The model will be individualised, in contrast to previously used group-averaged designs, and will be hybrid, in two respects. First, the model will integrate global functional and structural connectivity. Second, it will integrate data on regional vulnerability of brain tissue for generating tau based on gene expression profiles from an atlas. Results will provide mechanistic insights into spread of tau. The model and its subtypes will then be used to define an optimal sample stratification scheme, to enhance patient selection in clinical trial designs. Importantly, designs and analysis methods developed as part of this action will be released as a unified open-source software package to allow replication, expansion, and increased impact. Altogether, this proposal will provide novel scientific outcomes and will provide me with critical training in scientific and transferable skills that will largely advance my career.
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| Web resources: | https://cordis.europa.eu/project/id/101153323 |
| Start date: | 01-05-2024 |
| End date: | 30-04-2026 |
| Total budget - Public funding: | - 222 727,00 Euro |
Cordis data
Original description
Alzheimer’s disease (AD) has far-reaching societal and economic consequences, emphasizing the urgent need for effective treatment solutions. However, to date, over 99% of AD clinical trials have failed. Inadequate patient stratification is a key contributing factor due to the enormous clinical and pathological heterogeneity in AD. AD is characterized by the aggregation of pathogenic proteins, with tau aggregates being a key player. Tau-related pathological processes lead to synaptic dysfunction, neurodegeneration, and eventually dementia. It is thus of paramount importance to decipher the mechanisms of tau deposition and spread. Emerging evidence suggests that tau tangles accumulate along specific macroscale brain networks, lending support to the hypothesis of tau spreading through communicating neurons. Network-based spreading models have provided insights along this line. I aim to contribute to a leap in network-based modelling of tau spread, by developing a novel patient-specific network model, coupled with a diffusion framework to study tau spread. The model will be individualised, in contrast to previously used group-averaged designs, and will be hybrid, in two respects. First, the model will integrate global functional and structural connectivity. Second, it will integrate data on regional vulnerability of brain tissue for generating tau based on gene expression profiles from an atlas. Results will provide mechanistic insights into spread of tau. The model and its subtypes will then be used to define an optimal sample stratification scheme, to enhance patient selection in clinical trial designs. Importantly, designs and analysis methods developed as part of this action will be released as a unified open-source software package to allow replication, expansion, and increased impact. Altogether, this proposal will provide novel scientific outcomes and will provide me with critical training in scientific and transferable skills that will largely advance my career.Status
SIGNEDCall topic
HORIZON-MSCA-2023-PF-01-01Update Date
23-11-2024
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