Astrocyte Metabolic Model Predictions for Alzheimer's Disease Progression

10.8 KB of tabular data from a study integrating transcriptomic profiles from hippocampal CA1 tissue (GSE28146) with genome-scale metabolic modeling. The dataset, authored by Andrea Angarita-Rodríguez and last updated in June 2026, contains predictions from flux balance and variability analyses across control, early MCI, advanced MCI, and Alzheimer's disease conditions.

Use Cases

• Analyzing stage-dependent metabolic flux changes based on inferred astrocyte-associated expression programs.
• Investigating metabolic flexibility in pathways like glutamate-glutamine cycling and glutathione metabolism based on flux variability analysis results.
• Validating computational predictions of astrocyte metabolic reprogramming against independent single-nucleus RNA-seq datasets mentioned in the description.

Strengths

• Data is derived from a specific, named transcriptomic dataset (GSE28146).
• Analysis covers four distinct clinical conditions (control, early MCI, advanced MCI, AD).
• Results are integrated with a curated human astrocyte genome-scale metabolic model.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The 10.8 KB file size suggests a very limited scope, likely containing summary results rather than raw data.

Provenance

Source

Transcriptomic profiles from hippocampal CA1 tissue (GSE28146).

Collection Method

Integrated transcriptomic analysis and genome-scale metabolic modeling using flux balance analysis (FBA) and flux variability analysis (FVA).

Freshness

Last updated 2026-06-02 05:45:32; freshness should be verified.