Evidence map›Paper›PMID 42427581›Full record

ArticlebioRxiv : the preprint server for biology2026

Ontological Analysis of Brain Proteostasis Highlights the Sex-Dependent Trajectory of ApoE Isoform-Specific Regulation.

Ariel E A Denos, Elise Clark, Noah E Earls, Nazanin Paymard, Jared M Elison, Benjamin S Jones, Ethan G Smith, Esteban G Colman, Coleman O Nielsen, Martin Sorensen and 12 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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

22 authors.

Ariel E A DenosDepartment of Chemistry and Biochemistry, College of Computational, Physical, and Mathematical Sciences, Brigham Young University, Provo, Utah, United States of America.
Elise ClarkDepartment of Statistics, College of Computational, Physical, and Mathematical Sciences, Brigham Young University, Provo, Utah, United States of America.
Noah E EarlsDepartment of Chemistry and Biochemistry, College of Computational, Physical, and Mathematical Sciences, Brigham Young University, Provo, Utah, United States of America.
Nazanin PaymardDepartment of Chemistry and Biochemistry, College of Computational, Physical, and Mathematical Sciences, Brigham Young University, Provo, Utah, United States of America.
Jared M ElisonDepartment of Chemistry and Biochemistry, College of Computational, Physical, and Mathematical Sciences, Brigham Young University, Provo, Utah, United States of America.
Benjamin S JonesDepartment of Chemistry and Biochemistry, College of Computational, Physical, and Mathematical Sciences, Brigham Young University, Provo, Utah, United States of America.
Ethan G SmithDepartment of Chemistry and Biochemistry, College of Computational, Physical, and Mathematical Sciences, Brigham Young University, Provo, Utah, United States of America.
Esteban G ColmanDepartment of Chemistry and Biochemistry, College of Computational, Physical, and Mathematical Sciences, Brigham Young University, Provo, Utah, United States of America.
Coleman O NielsenDepartment of Chemistry and Biochemistry, College of Computational, Physical, and Mathematical Sciences, Brigham Young University, Provo, Utah, United States of America.
Martin SorensenDepartment of Chemistry and Biochemistry, College of Computational, Physical, and Mathematical Sciences, Brigham Young University, Provo, Utah, United States of America.
Noah G MoranDepartment of Chemistry and Biochemistry, College of Computational, Physical, and Mathematical Sciences, Brigham Young University, Provo, Utah, United States of America.
Jason G WellsDepartment of Chemistry and Biochemistry, College of Computational, Physical, and Mathematical Sciences, Brigham Young University, Provo, Utah, United States of America.
Rebecca S BurlettDepartment of Chemistry and Biochemistry, College of Computational, Physical, and Mathematical Sciences, Brigham Young University, Provo, Utah, United States of America.
Eleni S VickersDepartment of Chemistry and Biochemistry, College of Computational, Physical, and Mathematical Sciences, Brigham Young University, Provo, Utah, United States of America.
Christian T GarrardDepartment of Chemistry and Biochemistry, College of Computational, Physical, and Mathematical Sciences, Brigham Young University, Provo, Utah, United States of America.
Joshua R BrownDepartment of Chemistry and Biochemistry, College of Computational, Physical, and Mathematical Sciences, Brigham Young University, Provo, Utah, United States of America.
Katherine L BrownDepartment of Chemistry and Biochemistry, College of Computational, Physical, and Mathematical Sciences, Brigham Young University, Provo, Utah, United States of America.
Jossue D MatuteDepartment of Chemistry and Biochemistry, College of Computational, Physical, and Mathematical Sciences, Brigham Young University, Provo, Utah, United States of America.
Wejdene DaouahiDepartment of Chemistry and Biochemistry, College of Computational, Physical, and Mathematical Sciences, Brigham Young University, Provo, Utah, United States of America.
Mitchell F PoulsonDepartment of Chemistry and Biochemistry, College of Computational, Physical, and Mathematical Sciences, Brigham Young University, Provo, Utah, United States of America.
H Dennis TolleyDepartment of Statistics, College of Computational, Physical, and Mathematical Sciences, Brigham Young University, Provo, Utah, United States of America.
J C PriceDepartment of Chemistry and Biochemistry, College of Computational, Physical, and Mathematical Sciences, Brigham Young University, Provo, Utah, United States of America.ORCID 0000-0002-6780-5247

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Apolipoprotein E (ApoE) is the strongest genetic predictor of Alzheimer's disease (AD) risk, with ApoE4 increasing and ApoE2 decreasing risk relative to ApoE3. Using a global LC-MS proteomic approach, we integrated protein abundance and kinetics in Human-APOE knock-in mice for young (3-month) and aged (18-month) cohorts to quantify the changes in steady-state proteostasis. By mapping 6,052 identified proteins and 3,986 associated turnover rates into ontological groups, we observed that vesicle trafficking and mitochondrial dysregulation occur as early as 3 months in ApoE4 mice accompanied by hyperactive metabolism that eventually reduces with age. In contrast, young and old ApoE2 mice retain similar signatures to ApoE3 mice in metabolic, mitochondrial, cellular regulation, and membrane trafficking ontologies. We found that females had more isoform-induced ontological changes relative to ApoE3, providing insight into sex-dependent vulnerabilities. Our global proteomic approach for ApoE proteostasis crucially unifies independent literature observations while providing turnover kinetics to uncover the underlying mechanism behind abundance changes. Data are available via ProteomeXchange with identifier PXD079261.

Indexed as

AgingApoE isoformsBrain ProteostasisMitochondriaProtein kineticsProteomicsSex-dependent regulationSNARE proteins

Identifiers

PMID42427581
PMCPMC13345070

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.