ArticlePloS one2018
Computational prediction of changes in brain metabolic fluxes during Parkinson's disease from mRNA expression.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed, 16 citations in OpenAlex.
- Multi-omics characterization of improved cognitive functions in Parkinson's disease patients after the combined metabolic activator treatment: a randomized, double-blinded, placebo-controlled phase II trial.Brain communications · 2025Trial
- Roles of lactate and protein lactylation in neurogenesis and neurodegenerative disease.Journal of translational medicine · 2026Review
- In vivo and in silico models of Drosophila for Parkinson's disease.The FEBS journal · 2025Review
- Transcriptome Analysis and CFEM Gene Overexpression inPathogens (Basel, Switzerland) · 2025Article
- Metabolomics in Parkinson's Disease and Correlation with Disease State.Metabolites · 2025Review
- A reversible state of hypometabolism in a human cellular model of sporadic Parkinson's disease.Nature communications · 2023Article
- Isotope-Assisted Metabolic Flux Analysis: A Powerful Technique to Gain New Insights into the Human Metabolome in Health and Disease.Metabolites · 2022Review
- Machine learning-based characterization of cuprotosis-related biomarkers and immune infiltration in Parkinson's disease.Frontiers in genetics · 2022Article
- Personalized Genome-Scale Metabolic Models Identify Targets of Redox Metabolism in Radiation-Resistant Tumors.Cell systems · 2021Article
- A Standardized Brain Molecular Atlas: A Resource for Systems Modeling and Simulation.Frontiers in molecular neuroscience · 2021Article
- Peripheral Glycolysis in Neurodegenerative Diseases.International journal of molecular sciences · 2020Review
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Authors and funding
2 authors at 2 institutions in 2 countries.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundParkinson's disease is a widespread neurodegenerative disorder which affects brain metabolism. Although changes in gene expression during disease are often measured, it is difficult to predict metabolic fluxes from gene expression data. Here we explore the hypothesis that changes in gene expression for enzymes tend to parallel flux changes in biochemical reaction pathways in the brain metabolic network. This hypothesis is the basis of a computational method to predict metabolic flux changes from post-mortem gene expression measurements in Parkinson's disease (PD) brain.
resultsWe use a network model of central metabolism and optimize the correspondence between relative changes in fluxes and in gene expression. To this end we apply the Least-squares with Equalities and Inequalities algorithm integrated with Flux Balance Analysis (Lsei-FBA). We predict for PD (1) decreases in glycolytic rate and oxygen consumption and an increase in lactate production in brain cortex that correspond with measurements (2) relative flux decreases in ATP synthesis, in the malate-aspartate shuttle and midway in the TCA cycle that are substantially larger than relative changes in glucose uptake in the substantia nigra, dopaminergic neurons and most other brain regions (3) shifts in redox shuttles between cytosol and mitochondria (4) in contrast to Alzheimer's disease: little activation of the gamma-aminobutyric acid shunt pathway in compensation for decreased alpha-ketoglutarate dehydrogenase activity (5) in the globus pallidus internus, metabolic fluxes are increased, reflecting increased functional activity.
conclusionOur method predicts metabolic changes from gene expression data that correspond in direction and order of magnitude with presently available experimental observations during Parkinson's disease, indicating that the hypothesis may be useful for some biochemical pathways. Lsei-FBA generates predictions of flux distributions in neurons and small brain regions for which accurate metabolic flux measurements are not yet possible.
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