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Journal Article Epublish

PubMed: 40708007 DOI: 10.1186/s13073-025-01501-0

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

Genome Med 17(1):83

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

Affiliations

  • College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
  • College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
  • College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.

Abstract

BACKGROUND

The 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.

METHODS

In 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.

RESULTS

The 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.

CONCLUSIONS

The 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.

MeSH

Cells, Genes, Genomics, Lung, Pharmaceutical Preparations, Aging, Multiple Chronic Conditions