Excel · study · 2026
Genome-scale metabolic modelling uncovers cell-type specific signatures associated with APOE variants
Listed in NCBI GEO
Metabolic dysregulation is a key feature of Alzheimer’s disease (AD) pathogenesis.
Description
The ε4 variant of APOE gene (APOE4), coding for the lipid-transporter apolipoprotein E, is the strongest genetic risk factor for late-onset AD. Previous studies have investigated how APOE4 disrupts specific metabolic pathways within different cell types.
In this study, we followed a broad, metabolite-centric approach to investigate how APOE4 reshapes cellular metabolism in a cell type-specific manner based on transcriptome and metabolome data. We integrated transcriptomics data from an isogenic set of iPSC-derived neurons, astrocytes, and microglia harboring APOE3 or APOE4 genotypes into a human genome-scale metabolic model. From this model, we identified metabolic pathways that differed between APOE3 and APOE4 cells.
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We then used metabolomics data from the same iPSC-derived cell types to validate pathways identified by the transcriptomic analysis. In addition to confirming previous reports of disrupted cholesterol and fatty acid metabolism, we also identified bile acid biosynthesis, folate metabolism, and thyroid hormone metabolism as novel pathways dysregulated in APOE4 cells. Moreover, we were able to detect similar metabolic dysregulation in human post-mortem transcriptomic data.
By integrating transcriptomic and metabolomic data, our approach can enhance understanding of biological mechanisms associated with APOE4-associated metabolic dysregulation in AD.
Links
Get the data
- GEO FTP directory ftp.ncbi.nlm.nih.gov/geo/series/GSE305nnn/GSE305481 ↗
download · from NCBI GEO
Where it is published
- GEO accession page ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE305481 ↗
landing page · from NCBI GEO
Documentation and papers
- PRJNA1306066 ncbi.nlm.nih.gov/bioproject/PRJNA1306066 ↗
project · from NCBI GEO
- PubMed 42164526 pubmed.ncbi.nlm.nih.gov/42164526 ↗
publication · from NCBI GEO
Topics
- Stated by source
- Expression profiling by high throughput sequencing · Homo sapiens
- From keywords
- Life Sciences
- Inferred from text
- Disease 75%
Provenance · 1 source records, 8 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| NCBI GEO | GSE305481 | 15 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[disease].local:disease:disease | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].local:field:life-sciences | mapping · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[method].geo_series_type:expression-profiling-by-high-throughput-sequencing | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /gdstype |
| concepts[organism].NCBITaxon:9606 | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /taxon |
| description | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /summary |
| publication_date | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| title | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /title |