Dementia as a multifactorial disease has no known cure. The degenerative biological processes inside the patientís brain progress on large timescales and are probably initiated years before the disease onset. The development of safe treatments and a reliable early diagnosis of dementia can be valuably supported by a systemic understanding of the complex metabolic processes and the metabolic interdependencies in the human brain, which is carrying several thousands of different metabolites. Beside this, it is accepted that genetic, lifestyle, and environmental factors are connected to the progression of dementia, which consequently have to be included in a capacious system model. To our knowledge, a model covering the integration of genetic, biochemical, environmental and lifestyle data of the human brain has not been developed yet. A network model approach is suitable to analyse this highly branched system.
The metabolic processes of the human brain have been investigated intensively forming an increasingly accurate picture. Thus, the first goal of this WP is the development of a consistent knowledge base about dementia-related metabolites in the brain and their interdependencies. Hereafter, a sound modelling platform will be build that can organize the vast amount of input data concerning patient-specific brain metabolism and genetic/environmental/lifestyle data. On one hand, the focus of this WP is to gather and utilize accepted knowledge connected to dementia related metabolic reactions. On the other hand, investigations in promising research fields, like the application-oriented modelling of the Aβ and tau cascades and their related biomarkers, i.e. the lipid membrane composition as well as the dementia related lipid/peptide interactions will complete the metabolism model. Ideally, the resulting key metabolites are traceable through modern medical diagnosis to allow for a wide application. Collectively, this WP aims at the development and integration of genetic, biochemical and metabolic pathway modelling approaches that will allow for the identification of pathways leading to the neurodegenerative disease and will enable the user to investigate effects following the alteration of certain model components, i.e. by medication or through life style changes. This knowledge will be converted into computational models to build a clinically applicable method of disease assessment and differential diagnosis.
- The assessment and selection of available biomarkers and their integration into the models.
- Development of a biochemical Aβ and tau cascade model to characterise dementia diseases
- Development of an energy metabolism model that is applicable to dementia-related alterations.
- Development of a genome-scale metabolic model and their interaction with the genetic factors associated with the dementia diseases
- Development of an atomic-scale lipid/peptide interaction model.
- Development of a connective network model for dementia prediction capturing biomarkers, environmental and lifestyle factors.
- Transfer of metabolic modelling results to the application module.
- Assessment and integration of personalised biomarkers, genetic and environmental data
- Modelling of A? and tau cascades, as well as brain energy metabolism
- Genome-scale metabolic modelling of central metabolism using constraint-based methods
- Modelling of lipid membranes, membrane/peptide interaction
- Dementia-specific metabolic network modelling linking biomarkers and environmental factors