Evidence map›Paper›PMID 42311824›Full record

ArticleFrontiers in bioinformatics2026

Transcriptome-informed metabolic modeling reveals astrocyte-specific vulnerabilities in mild cognitive impairment and Alzheimer's disease progression.

Andrea Angarita-Rodríguez, Viviana Vargas-López, Andrés Pinzón, Adrián Sandoval-Hernandez, Kai Kang, Leping Li, Jason Papin, Pedro Puentes-Rozo, Andrés Felipe Aristizábal, Janneth González

Erratum issuedAbstract read
In one paragraph

Article in Frontiers in bioinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Andrea Angarita-RodríguezDepartamento de Nutrición y Bioquímica, Facultad de Ciencias, Pontificia Universidad Javeriana, Bogotá, Colombia.
Viviana Vargas-LópezDepartamento de Nutrición y Bioquímica, Facultad de Ciencias, Pontificia Universidad Javeriana, Bogotá, Colombia.
Andrés PinzónLaboratorio de Bioinformática y Biología de Sistemas, Universidad Nacional de Colombia Bogotá, Bogotá, Colombia.
Adrián Sandoval-HernandezGrupo de Neurociencias y Muerte Celular, Instituto de Genética, Universidad Nacional de Colombia, Bogotá, Colombia.
Kai KangDepartment of Mathematics and Statistics, University of North Carolina Wilmington, Wilmington, NC, United States.
Leping LiBiostatistics and Computational Biology Branch at NIEHS, Bethesda, MD, United States.
Jason PapinDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States.
Pedro Puentes-RozoGrupo de Neurociencias del Caribe, Unidad de Neurociencias Cognitivas, Universidad Simón Bolívar, Barranquilla, Colombia.
Andrés Felipe AristizábalDepartamento de Nutrición y Bioquímica, Facultad de Ciencias, Pontificia Universidad Javeriana, Bogotá, Colombia.
Janneth GonzálezDepartamento de Nutrición y Bioquímica, Facultad de Ciencias, Pontificia Universidad Javeriana, Bogotá, Colombia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Astrocytes are essential for maintaining neuronal homeostasis, yet their stage-specific contribution to mild cognitive impairment (MCI) and Alzheimer's disease (AD) remains insufficiently understood. This study aimed to investigate astrocyte-associated transcriptional and metabolic alterations across the control-MCI-AD continuum using integrated transcriptomic and genome-scale metabolic modeling approaches. Methods: Transcriptomic profiles from hippocampal CA1 tissue (GSE28146) were analyzed across four clinical conditions (control, early MCI, advanced MCI, and AD). Astrocyte-associated expression programs were inferred using the unsupervised deconvolution algorithm CDSeq and validated through canonical marker enrichment, correlation with external reference signatures, and comparison with an independent single-nucleus RNA-seq astrocyte pseudobulk dataset. The inferred profiles were integrated into a curated human astrocyte genome-scale metabolic model to generate condition-specific models, which were analyzed using flux balance analysis (FBA) and flux variability analysis (FVA). Results: The analyses supported stage-dependent remodeling of astrocyte-associated transcriptional and metabolic programs during disease progression. Early MCI was associated with signaling and stress-adaptation changes, whereas advanced MCI and AD showed broader disruption of synaptic support, redox homeostasis, and inflammatory-related programs. Model predictions indicated a progressive reduction in a biomass-derived maintenance proxy from control to advanced MCI, followed by a partial rebound in AD, suggesting a compensatory shift toward reactive-like astrocyte states rather than full functional recovery. Flux variability analysis revealed reduced metabolic flexibility across disease stages, particularly in glutamate-glutamine cycling, glutathione/redox metabolism, glycolysis-pyruvate metabolism, cholesterol handling, and one-carbon/folate metabolism. Discussion: These findings support the view that astrocytes undergo progressive, stage-specific metabolic reprogramming during the transition from healthy aging to AD. Early alterations in redox regulation, neurotransmitter cycling, and mitochondrial function may contribute to early neuronal vulnerability. This work highlights astrocyte-centered pathways as potential targets for future experimental validation and therapeutic exploration.

Indexed as

Alzheimer’s diseaseastrocytedeconvolutionflux balance analysisgenome-scale metabolic modelsmetabolic reprogrammingmild cognitive impairmenttranscriptome

Identifiers

PMID42311824
PMCPMC13269292

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.