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Record W4411177564 · doi:10.1038/s43856-025-00942-3

Protection against APOE4-associated phenotypes with the longevity-promoting intervention 17α-estradiol in middle-aged male mice

2025· article· en· W4411177564 on OpenAlexaboutno aff
Cassandra McGill, Amy Christensen, Wenjie Qian, Max A. Thorwald, Jose Godoy Lugo, Sara Namvari, Caleb E. Finch, Bérénice A. Benayoun, Christian J. Pike

Bibliographic record

VenueCommunications Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsnot available
FundersNational Institute on AgingNational Institutes of HealthCure Alzheimer's Fund
KeywordsLongevityPhenotypeIntervention (counseling)MedicineGerontologyInternal medicineBiologyPhysiologyEndocrinologyDemographyGeneticsPsychiatryGeneSociology

Abstract

fetched live from OpenAlex

The apolipoprotein ε4 allele (APOE4) is associated with decreased longevity and increased vulnerability to age-related declines and disorders across multiple systems. Interventions that promote healthspan and lifespan represent a promising strategy to attenuate the development of APOE4-associated aging phenotypes. Here, we studied the ability of the longevity-promoting intervention 17α-estradiol (17αE2) to protect against impairments in APOE4 versus the predominant APOE3 genotype using early middle-aged mice with knock-in of human APOE alleles. Beginning at age 10 months, male APOE3 or APOE4 mice were treated for 20 weeks with 17αE2 or vehicle then compared body-wide for indices of middle-aged phenotypes. Across peripheral and neural measures, APOE4 associates with poorer outcomes. Notably, 17αE2 treatment generally improves outcomes in a genotype-dependent manner, favoring APOE4 mice, including reductions in body weight, plasma leptin, hepatic steatosis, learning and memory, and oxidative damage in the brain. Plasma lipidomics and microglial transcriptomics show reductions in genotype-specific differences with 17αE2 treatment. These findings demonstrate that APOE4 promotes systemic and neural aging phenotypes linked to AD and that 17αE2-mediated healthspan actions show a positive APOE4 bias. Collectively, the findings suggest that longevity-promoting interventions may be useful in mitigating deleterious age-related risks associated with the APOE4 genotype. People with a particular sequence in a part of their DNA called APOE (named APOE4) are more likely to have a reduced lifespan and have a higher risk of developing some age-related disorders, including Alzheimer’s disease. We tested whether a drug that extends lifespan and healthy aging in mice, called 17α-estradiol (17αE2), reduces the aging effects of APOE4. We compared male mice with different APOE sequences for 20 weeks during early middle age. As expected, we found that mice with the APOE4 sequence showed more signs of aging, but that 17αE2 improved several health-related measures, often with a bigger effect in mice with APOE4. These results suggest that treatments that promote healthy aging may be especially helpful for people with APOE4, potentially reducing their risk for age-related diseases such as Alzheimer’s disease. McGill et al. compare the effects of the longevity-promoting compound 17α-estradiol (17αE2) in male mice carrying the common human APOE3 allele versus the Alzheimer-associated APOE4 allele. Treatment with 17αE2 in early middle-age improves outcomes body-wide with greater benefits in APOE4 mice, suggesting genotype-specific healthspan effects.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.078
GPT teacher head0.345
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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