Xu Yingqi, Li Maohao, Hu Congxue, Luo Yawen, Gao Xing, Li Xinyu, Li Xia, Zhang Yunpeng
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Genome Med. 2025 Jul 24;17(1):83. doi: 10.1186/s13073-025-01501-0.
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.
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.
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.
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.
衰老导致的器官功能衰退对老年人的健康和生活质量有显著影响。评估和延缓衰老已成为社会主要关注的问题。以往的研究主要集中在年轻人和老年人之间的差异，常常忽略了衰老的复杂性和渐进性。
在本研究中，我们构建了小鼠多器官衰老综合图谱，并系统分析了16个器官的衰老轨迹，以阐明其功能特异性并确定器官特异性衰老趋势基因。采用跨器官关联分析来识别全局衰老调控基因，从而开发出一种多器官衰老评估模型，以下简称2A模型。使用来自衰老小鼠肺的单细胞RNA测序数据、跨物种基因表达谱和药物基因组数据证实了该模型的有效性。此外，实施了随机游走算法和结合基因集富集分析的加权整合方法，以系统筛选减轻多器官衰老的潜在药物。
2A模型有效地评估了人类和小鼠组织中的衰老状态，并显示出对衰老细胞清除率的预测能力。与sc-ImmuAging和SCALE时钟相比，2A模型在单细胞水平上表现出更高的预测准确性。器官特异性分析确定肺和肾特别容易衰老，免疫功能障碍和程序性细胞死亡是关键因素。值得注意的是，单细胞数据证实浆细胞积累和幼稚样细胞减少在器官衰老过程中呈线性变化。在每个器官中鉴定出的衰老趋势基因在与衰老相关的功能途径中显著富集，能够精确评估衰老过程并确定器官特异性衰老里程碑。此外，药物筛选确定福司他替尼、雷诺嗪和二甲双胍为多器官衰老的潜在调节剂，其作用机制涉及寿命调节和昼夜节律等关键途径。
2A模型通过整合多维度验证策略，在衰老评估方面取得了重大进展，提高了其准确性和适用性。器官特异性衰老途径的鉴定和候选药物干预措施为精准抗衰老治疗提供了理论基础和转化框架。
