Evidence map›Paper›PMID 40708007›Full record

ArticleGenome medicine2025

Developing a novel aging assessment model to uncover heterogeneity in organ aging and screening of aging-related drugs.

Yingqi Xu, Maohao Li, Congxue Hu, Yawen Luo, Xing Gao, Xinyu Li, Xia Li, Yunpeng Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genome medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Hematopoietic Aging and Leukemia: Mechanistic and Therapeutic Insights.International journal of molecular sciences · 2026
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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

8 authors.

Yingqi Xu *College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Maohao Li *College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Congxue Hu *College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Yawen LuoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Xing GaoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Xinyu LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Xia LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China. lixia@hrbmu.edu.cn.
Yunpeng ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China. zhangyp@hrbmu.edu.cn.

Funding

Key Research and Development Program of Heilongjiang Province 2024ZX12C27National Natural Science Foundation of China 62172131National Natural Science Foundation of China 62472131National Science and Technology Major Program 2024ZD0530500STI2030-Major Projects 2021ZD0202400
6 · The paper itself

Abstract

backgroundThe decline in organ function due to aging significantly impacts the health and quality of life of the elderly. Assessing and delaying aging has become a major societal concern. Previous studies have largely focused on differences between young and old individuals, often overlooking the complexity and gradual nature of aging.

methodsIn this study, we constructed a comprehensive multi-organ aging atlas in mice and systematically analyzed the aging trajectories of 16 organs to elucidate their functional specificity and identify organ-specific aging trend genes. Cross-organ association analysis was employed to identify global aging regulatory genes, leading to the development of a multi-organ aging assessment model, hereafter referred to as the 2A model. The model's validity was confirmed using single-cell RNA sequencing data from aging mouse lungs, cross-species gene expression profiles, and pharmacogenomic data. Furthermore, a random walk algorithm and a weighted integration approach combining gene set enrichment analysis were implemented to systematically screen potential drugs for mitigating multi-organ aging.

resultsThe 2A model effectively assessed aging states in both human and mouse tissues and demonstrated predictive capability for senescent cell clearance rates. Compared to the sc-ImmuAging and SCALE clocks, the 2A model exhibited superior predictive accuracy at the single-cell level. Organ-specific analyses identified the lungs and kidneys as particularly susceptible to aging, with immune dysfunction and programmed cell death emerging as key contributors. Notably, single-cell data confirmed that plasma cell accumulation and naive-like cell reduction showed linear changes during organ aging. Aging trend genes identified in each organ were significantly enriched in aging-related functional pathways, enabling precise assessment of the aging process and determination of organ-specific aging milestones. Additionally, drug screening identified Fostamatinib, Ranolazine, and Metformin as potential modulators of multi-organ aging, with mechanisms involving key pathways such as longevity regulation and circadian rhythm.

conclusionsThe 2A model represents a significant advancement in aging assessment by integrating multi-dimensional validation strategies, enhancing its accuracy and applicability. The identification of organ-specific aging pathways and candidate pharmacological interventions provides a theoretical foundation and translational framework for precision anti-aging therapies.

Indexed as

AgingAnimalsCellular SenescenceDrug Evaluation, PreclinicalHumansLungMiceOrgan SpecificitySingle-Cell AnalysisAging assessment modelDrug screeningOrgan agingSingle-cell sequencing

Identifiers

PMID40708007
PMCPMC12288260

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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.