Integrative genome-scale metabolic model of GABAergic neurons reveals metabolic signatures across the mild cognitive impairment - Alzheimer disease continuum.

Overview

1. Departamento de Nutrición y Bioquímica, Facultad de Ciencias, Pontificia Universidad Javeriana, Bogotá, Colombia
2. Laboratorio de Bioinformática y Biología de Sistemas, Universidad Nacional de Colombia Bogotá, Bogotá, Colombia
3. Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States
4. Department of Medicine, Division of Infectious Diseases and International Health, University of Virginia, Charlottesville, VA, United States
5. Department of Biochemistry & Molecular Genetics, University of Virginia, Charlottesville, VA, United States

Abstract

Introduction: Mild cognitive impairment (MCI) represents a prodromal stage of Alzheimer’s disease (AD), but the metabolic mechanisms underlying early neuronal dysfunction remain incompletely understood. GABAergic neurons, which maintain excitatory–inhibitory balance and network stability, exhibit early vulnerability during neurodegeneration, although the metabolic alterations associated with their dysfunction remain poorly characterized.

Methods: We developed a context-specific genome-scale metabolic model (GEM) of human GABAergic neurons across the MCI–AD continuum using deconvolved hippocampal transcriptomic data. By integrating transcriptomic deconvolution with constraint-based modeling, including flux balance analysis (FBA) and flux variability analysis (FVA), we inferred disease-stage-associated metabolic alterations under Control, early MCI (E-MCI), advanced MCI (A-MCI), and AD conditions.

Results: Our analyses suggest progressive remodeling of energy metabolism, the glutamate–glutamine–GABA cycle, redox homeostasis, lipid metabolism, and neuron–astrocyte metabolic interactions. FVA identified reaction-specific changes in feasible flux ranges, indicating remodeling of the feasible metabolic solution space rather than a uniform contraction across pathways. These predicted metabolic alterations were accompanied by transcriptional changes in GABAergic markers and showed qualitative agreement with independent metabolomic observations, supporting their biological plausibility.

Discussion: Overall, this work provides a systems-level computational framework linking transcriptomic alterations with predicted metabolic remodeling in GABAergic neurons and generates experimentally testable hypotheses regarding metabolic dysfunction during progression from MCI to AD.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Data

Datasets cited

• geo:GSE115565, at NCBI GEO; found in the text, “Gene expression mapping to metabolic reactions”

Data availability statement

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Recorded: type, language, journal, volume, pages, dates, 8 authors, 7 keywords, 72 references.

Cite

This paper

Angarita-Rodríguez, A., Largo-González, J. H., Pérez-Mejía, J., Balcazar, D., Vargas-López, V., Papin, J. A., Pinzón, A., & González, J. (2026). Integrative genome-scale metabolic model of GABAergic neurons reveals metabolic signatures across the mild cognitive impairment - Alzheimer disease continuum. Frontiers in systems biology, 6, 1897648. https://doi.org/10.3389/fsysb.2026.1897648

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