MRI-based multi-organ clocks for healthy aging and disease assessment

孟德尔随机化 健康衰老 可药性 医学 疾病 生物信息学 认知功能衰退 糖尿病 生物 生物标志物 生物年龄 认知老化 老年学 精密医学 临床试验 衰老的大脑 孟德尔遗传 基因检测 基因 痴呆 计算生物学 齿轮 百岁老人 2型糖尿病 LRRK2 全基因组关联研究 肾脏疾病 遗传学 候选基因 认知 生理学
作者
Huizi Cao,Zhiyuan Song,Michael R. Duggan,Güray Erus,Dhivya Srinivasan,Ye Tian,Wenjia Bai,Michael S. Rafii,Paul Aisen,Daniel W. Belsky,Keenan A. Walker,Andrew Zalesky,Luigi Ferrucci,Christos Davatzikos,Junhao Wen
出处
期刊:Nature Medicine [Nature Portfolio]
卷期号:32 (1): 82-92 被引量:12
标识
DOI:10.1038/s41591-025-03999-8
摘要

Biological aging clocks across organ systems and tissues have advanced understanding of human aging and disease. In this study, we expand this framework to develop seven magnetic resonance imaging-based multi-organ biological age gaps (MRIBAGs), including the brain, heart, liver, adipose tissue, spleen, kidney and pancreas. Using data from 313,645 individuals curated by the MULTI Consortium, we link the seven MRIBAGs to 2,923 plasma proteins, 327 metabolites and 6,477,810 common genetic variants. Genome-wide associations identify 53 MRIBAG−locus pairs (P < 5 × 10−8). Genetic correlation and Mendelian randomization analyses support organ-specific and cross-organ interconnection, including 24 non-MRI biological aging clocks and 525 disease endpoints. Through functional gene mapping and Bayesian co-localization multi-omics evidence, we prioritize nine druggable genes as targets for future anti-aging treatments. Furthermore, the seven MRIBAGs are linked to future risk of systemic disease endpoints (for example, diabetes mellitus) and all-cause mortality. Finally, participants with more youthful versus more aged brain profiles exhibited distinct cognitive decline trajectories over 240 weeks of treatment with the Alzheimer’s disease drug solanezumab, although this heterogeneity cannot be fully attributed to the drug. In summary, we developed seven MRIBAGs that enhance the existing multi-organ biological aging framework, and we demonstrate their clinical potential to advance aging research. A new study combines MRI data with proteomic, metabolomic and RNA data to develop and examine seven organ-specific MRI-based aging clocks, uncovering links to overall mortality and organ-specific diseases.
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