ArticlePloS one2025
Weight trajectories in aging humanized APOE mice with translational validity to human Alzheimer's risk population: A retrospective analysis.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- Humanized APOE mouse brain volume increases over age irrespective of sex and APOE genotype: implications for translational validity to the human.Frontiers in neuroscience · 2026Article
- Humanized APOE mouse brain volume increases over age irrespective of sex and APOE genotype: Implications for translational validity to the human.bioRxiv : the preprint server for biology · 2025Article
- Humanized APP is the primary determinant of regional brain volume in humanized APOE knock-in mice: a cross-sectional ex vivo MRI study.Alzheimer's & dementia (New York, N. Y.)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Translational validity of mouse models of Alzheimer's disease (AD) is variable. Because change in weight is a well-documented precursor of AD, we investigated whether diversity of human AD risk weight phenotypes was evident in a longitudinally characterized cohort of 1,196 female and male humanized APOE (hAPOE) mice, monitored up to 28 months of age which is equivalent to 81 human years. Autoregressive Hidden Markov Model (AHMM) incorporating age, sex, and APOE genotype was employed to identify emergent weight trajectories and phenotypes. In the hAPOE-AD mouse cohort, five distinct weight trajectories emerged: three trajectories were associated with a weight loss phenotype (36% of mice, n = 426), one with weight gain (13% of mice, n = 152), and one trajectory of no change in weight (34% of mice, n = 403). The AHMM model findings were validated with post-hoc survival analyses, revealing differences in survival rates across the five identified phenotypes. Further validation was performed using body composition and plasma β-amyloid data from mice within the identified gain, loss and stable weight trajectories. Weight gain trajectory was associated with elevated plasma β-amyloid levels, higher body fat composition, lower survival rates and a greater proportion of APOE4/4 carriers. In contrast, weight loss was associated with greater proportion of hAPOE3/4 carriers, better survival rates and was predominantly male. The association between weight change and AD risk observed in humans was mirrored in the hAPOE-AD mouse model. Weight trajectories of APOE3/3 mice were equally distributed across weight gain, loss and stability. Surprisingly, despite genetic uniformity, comparable housing, diet and handling, distinct weight trajectories and divergence points emerged for subpopulations. These data are consistent with the heterogeneity observed in the human population for change in body weight during aging and highlight the importance of longitudinal phenotypic characterization of mouse aging to advance the translational validity of preclinical AD mouse models.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.