Gut microbial features and circulating metabolomic signatures of frailty in older adults

代谢组学 肠道菌群 普氏粪杆菌 危险系数 基因组 老年学 置信区间 生理学 医学 内科学 生物 生物信息学 免疫学 生物化学 基因
作者
Yanni Pu,Zhonghan Sun,Hui Zhang,Qingxia Huang,Zhengdong Wang,Zhendong Mei,Peilu Wang,Mengmeng Kong,Wenjun Yang,Chenhao Lin,Xiaofeng Zhou,Shuchun Lin,Qiumin Huang,Lili Huang,Liang Sun,Changzheng Yuan,Qian Xu,Huiru Tang,Xiaofeng Wang,Yan Zheng
出处
期刊:Nature Aging 卷期号:4 (9): 1249-1262 被引量:6
标识
DOI:10.1038/s43587-024-00678-0
摘要

Frailty, a multidimensional indicator of suboptimal aging, reflects cumulative declines across multiple physiological systems. Although age-related changes have been reported in gut microbiota, their role in healthy aging remains unclear. In this study, we calculated frailty index (FI) from 33 health-related items to reflect the overall health status of 1,821 older adults (62–96 years, 55% female) and conducted multi-omics analysis using gut metagenomic sequencing data and plasma metabolomic data. We identified 18 microbial species and 17 metabolites shifted along with frailty severity, with stronger links observed in females. The associations of nine species, including various Clostridium species and Faecalibacterium prausnitzii, with FI were reproducible in two external populations. Plasma glycerol levels, white blood cell count and kidney function partially mediated these associations. A composite microbial score derived from FI significantly predicted 2-year mortality (adjusted hazard ratio across extreme quartiles, 2.86; 95% confidence interval, 1.38–5.93), highlighting the potential of microbiota-based strategies for risk stratification in older adults. This study reveals gut microbial and metabolomic features associated with the severity of frailty, demonstrating that these microbial features outperform traditional assessment tools in identifying individuals at high risk of frailty and mortality.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
111完成签到,获得积分10
1秒前
大力的契完成签到,获得积分10
1秒前
1秒前
QQ完成签到,获得积分10
1秒前
2秒前
2秒前
2秒前
上官若男应助嘟嘟采纳,获得10
2秒前
晨雨完成签到,获得积分10
3秒前
张志顺完成签到,获得积分10
3秒前
tyhg完成签到,获得积分10
3秒前
无辜洋葱发布了新的文献求助10
3秒前
ape完成签到,获得积分20
3秒前
马保国123发布了新的文献求助10
4秒前
归海紫翠完成签到,获得积分10
4秒前
4秒前
岑夜南完成签到,获得积分10
4秒前
uniphoton完成签到,获得积分10
4秒前
FashionBoy应助zzznznnn采纳,获得10
4秒前
4秒前
哈哈发布了新的文献求助10
4秒前
成就的山水完成签到,获得积分10
5秒前
5秒前
5秒前
尚可完成签到 ,获得积分10
5秒前
赖道之发布了新的文献求助10
6秒前
完美世界应助yuan采纳,获得10
6秒前
丘比特应助bluer采纳,获得10
6秒前
好运来发布了新的文献求助10
6秒前
榕俊完成签到,获得积分10
6秒前
7秒前
7秒前
7秒前
卡卡发布了新的文献求助10
7秒前
zouzou完成签到,获得积分10
8秒前
8秒前
CodeCraft应助FFF采纳,获得10
9秒前
冰河完成签到,获得积分10
9秒前
9秒前
领导范儿应助鱼雷采纳,获得10
9秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527723
求助须知:如何正确求助?哪些是违规求助? 3107826
关于积分的说明 9286663
捐赠科研通 2805577
什么是DOI,文献DOI怎么找? 1539998
邀请新用户注册赠送积分活动 716878
科研通“疑难数据库(出版商)”最低求助积分说明 709762