Evidence map›Paper›PMID 42164526›Full record

ArticleiScience2026

Genome-scale metabolic modeling uncovers cell-type specific signatures associated with APOE variants.

Dilara Uzuner Odongo, Roxan A Stephenson, Linling Cheng, Linda G Yang, Priyanka S Narayan, Tunahan Çakır, Madhav Thambisetty

Abstract read
In one paragraph

Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Dilara Uzuner OdongoDepartment of Bioengineering, Gebze Technical University, Gebze, Kocaeli, Turkey.
Roxan A StephensonGenetics and Biochemistry Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA.
Linling ChengGenetics and Biochemistry Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA.
Linda G YangGenetics and Biochemistry Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA.
Priyanka S NarayanGenetics and Biochemistry Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA.
Tunahan ÇakırDepartment of Bioengineering, Gebze Technical University, Gebze, Kocaeli, Turkey.
Madhav ThambisettyIntramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabolic dysregulation is a key feature of Alzheimer's disease (AD) pathogenesis, with the APOE ε4 variant (APOE4) representing the strongest genetic risk factor. In this study, we utilized a metabolite-centric approach to investigate how APOE4 reshapes cellular metabolism across brain cell types. Transcriptomic data from isogenic iPSC-derived neurons, astrocytes, and microglia were integrated into a human genome-scale metabolic model to identify genotype-specific alterations. These findings were validated using metabolomics data from the same cell types. In addition to cholesterol and fatty acid dysregulation, we identified alterations in bile acid biosynthesis, folate metabolism, and thyroid hormone metabolism. Similar metabolic signatures were also detected in human postmortem transcriptomic data. Integrating transcriptomic and metabolomic data enhances the understanding of biological mechanisms underlying APOE4-associated metabolic dysregulation in AD.

Indexed as

OmicsSystems biology

Identifiers

PMID42164526
PMCPMC13185917

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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.