Constraint-based metabolic modelling of Parkinson’s disease: Investigating dysfunctional pathways and selective vulnerability in dopaminergic neurons

Parkinson’s disease (PD), the second most common neurodegenerative disorder, in volves complex molecular mechanisms, with dysfunctional metabolism emerging as a promising target for diagnosis and treatment. However, inconsistencies in reported metabolites complicate our understanding of PD pathogenesis. This thesis reviews 74 metabolomic studies of PD patients to identify consistently and inconsistently replicated metabolites, generating a metabolic model and map that elucidate dysfunctional PD pathways, which enable a prediction of potential PD biomarkers. Furthermore, evidence indicates that distinct metabolic characteristics, particularly bioenergetic differences between synaptic terminals and the soma, may underlie the selective vulnerability of dopaminergic neurons in PD. To investigate these differences, four thermodynamically flux-consistent models representing synaptic and non-synaptic components under con trol and PD conditions were generated. These models revealed that the synaptic PD model exhibits lower mitochondrial energy contributions and higher sensitivity to Com plex I inhibition. The increased flux of the mitochondrial ornithine transaminase reac tion (ORNTArm) was predicted to rescue bioenergetic failure and improve metabolite exchanges for both the synaptic and non-synaptic PD models. Additionally, the thesis refines the human metabolic network (Recon3D) by reconstructing flavoprotein-related reactions to enhance the representation of electron transfer pathways, particularly the electron transfer flavoprotein (ETF) coupling pathway. Overall, this thesis enhances our understanding of PD metabolism through constraint-based metabolic modelling and COBRA analysis, providing valuable insights into potential biomarkers and therapeutic targets for PD patients.

Publisher

University of Galway

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CC BY-NC-ND

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University of Galway Theses (PhD Theses)