Systems modeling of metabolic dysregulation in neurodegenerative diseases

Abstract

Neurodegenerative diseases (NDDs) encompass a wide range of conditions that arise owing to progressive degeneration and the ultimate loss of nerve cells in the brain and peripheral nervous system. NDDs such as Alzheimer's, Parkinson's, and Huntington's diseases negatively impact both length and quality of life, due to lack of effective disease-modifying treatments. Herein, we review the use of genome-scale metabolic models, network-based approaches, and integration with multiomics data to identify key biological processes that characterize NDDs. We describe powerful systems biology approaches for modeling NDD pathophysiology by leveraging in silico models that are informed by patient-derived multiomics data. These approaches can enable mechanistic insights into NDD-specific metabolic dysregulations that can be leveraged to identify potential metabolic markers of disease and predisease states.

Keywords: Neurodegenerative diseases, Metabolic modeling, Multiomics analysis, Network approaches.

Figure 1:

A systems approach for investigating metabolic changes in the brain. Brain cell type-specific and region-specific data has been used to generate metabolic networks and identify metabolic dysregulation in NDDs.

Figure 2:

Genome-scale TRN model of brain. Brain-specific DNase footprinting data and comprehensive TF-gene co-expression datasets have been used for generating the TRN model for identifying TF-target genes implicated in NDDs.