Develop tools that use genetic data to better classify complex human diseases
This project aims to develop novel statistical tools for classifying heterogeneous diseases like epilepsy and schizophrenia using genetic information to enhance precision medicine.
Projectdetails
Introduction
Many common diseases are highly heterogeneous, meaning that two individuals can be diagnosed with the same disease but have very different progressions or respond very differently to the same medication. These heterogeneous diseases affect a sizeable proportion of the population. For example, approximately one in four people will develop a heterogeneous brain disorder (e.g., a neurological condition such as epilepsy or Parkinson’s Disease, or a psychiatric condition such as depression or schizophrenia).
Need for Accurate Classification
To effectively treat a patient with a heterogeneous disease, it is necessary to quickly and accurately identify their subtype. At present, patient subtypes are decided using only clinical observations, and the process is highly suboptimal.
- The available subtypes are often incomplete or poorly defined.
- Many patients are wrongly classified or cannot be classified at all.
Incorporating Genetic Information
Previous research indicates that for many heterogeneous diseases, the classification of patients can be improved by incorporating genetic information. However, for this to become a reality, it requires statistical tools that do not yet exist.
Project Goals
My project will develop novel statistical tools for classifying heterogeneous diseases based on genetic information.
- The project will prioritize classification of two heterogeneous diseases: epilepsy and schizophrenia.
- I will ensure that my new tools are general, freely available, and easy to use.
- Other groups will be able to construct classification models for many other diseases.
Potential Impact
Overall, my project has the potential to revolutionize how patients with heterogeneous diseases are treated and to facilitate more widespread use of precision medicine.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 1.975.333 |
Totale projectbegroting | € 1.975.333 |
Tijdlijn
Startdatum | 1-8-2023 |
Einddatum | 31-7-2028 |
Subsidiejaar | 2023 |
Partners & Locaties
Projectpartners
- AARHUS UNIVERSITETpenvoerder
Land(en)
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Subtype as a key to reduce heterogeneity of treatment effects in major depressive disorder
SUBTREAT aims to enhance treatment for major depressive disorder by identifying subtypes through advanced data science, exploring their causes, and developing predictive algorithms for tailored therapies.
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GenDrug aims to develop innovative algorithms integrating genomic and real-world data to identify drug targets and accelerate drug development for neglected non-communicable diseases.
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Deciphering Alzheimer’s disease molecular subtypes to advance treatment development.
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