Immune-Ageing Evaluation of Peripheral T and NK Lymphocyte Subsets in Chinese Healthy Adults

免疫衰老 老化 免疫系统 免疫学 生物 淋巴细胞 T细胞 人口 自然杀伤细胞 表型 细胞毒性T细胞 医学 遗传学 体外 环境卫生 基因
作者
Zhen Jia,Zhiyao Ren,Dongmei Ye,Jiawei Li,Yu Xu,Hui Liu,Zhen Meng,Chengmao Yang,X.P. Chen,Xinru Mao,Xingguang Luο,Zhe Yang,Li Ma,Anyi Deng,Yafang Li,Baohui Han,Junping Wei,Chao‐Song Huang,Zheng Xiang,Guobing Chen,Peiling Li,Juan Ouyang,Peisong Chen,Oscar Junhong Luo,Yifang Gao,Zhinan Yin
出处
期刊:Phenomics [Springer Nature]
卷期号:3 (4): 360-374 被引量:1
标识
DOI:10.1007/s43657-023-00106-0
摘要

Ageing is often accompanied with a decline in immune system function, resulting in immune ageing. Numerous studies have focussed on the changes in different lymphocyte subsets in diseases and immunosenescence. The change in immune phenotype is a key indication of the diseased or healthy status. However, the changes in lymphocyte number and phenotype brought about by ageing have not been comprehensively analysed. Here, we analysed T and natural killer (NK) cell subsets, the phenotype and cell differentiation states in 43,096 healthy individuals, aged 20-88 years, without known diseases. Thirty-six immune parameters were analysed and the reference ranges of these subsets were established in different age groups divided into 5-year intervals. The data were subjected to random forest machine learning for immune-ageing modelling and confirmed using the neural network analysis. Our initial analysis and machine modelling prediction showed that naïve T cells decreased with ageing, whereas central memory T cells (Tcm) and effector memory T cells (Tem) increased cluster of differentiation (CD) 28-associated T cells. This is the largest study to investigate the correlation between age and immune cell function in a Chinese population, and provides insightful differences, suggesting that healthy adults might be considerably influenced by age and sex. The age of a person's immune system might be different from their chronological age. Our immune-ageing modelling study is one of the largest studies to provide insights into 'immune-age' rather than 'biological-age'. Through machine learning, we identified immune factors influencing the most through ageing and built a model for immune-ageing prediction. Our research not only reveals the impact of age on immune parameter differences within the Chinese population, but also provides new insights for monitoring and preventing some diseases in clinical practice.The online version contains supplementary material available at 10.1007/s43657-023-00106-0.
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
刚刚
zZ发布了新的文献求助10
刚刚
qi完成签到,获得积分10
1秒前
标致缘郡发布了新的文献求助10
1秒前
miawei完成签到,获得积分10
2秒前
2秒前
wangfu发布了新的文献求助10
2秒前
明理依云完成签到,获得积分10
2秒前
2秒前
3秒前
二世小卒完成签到 ,获得积分10
3秒前
和谐乌龟完成签到,获得积分10
4秒前
阳尧完成签到,获得积分10
4秒前
帅气惜霜发布了新的文献求助10
4秒前
4秒前
kkkklo发布了新的文献求助30
6秒前
传奇3应助润润轩轩采纳,获得10
6秒前
6秒前
8秒前
和谐乌龟发布了新的文献求助10
8秒前
zZ完成签到,获得积分10
8秒前
科研小白完成签到,获得积分10
8秒前
LYY发布了新的文献求助10
9秒前
wangfu完成签到,获得积分10
9秒前
ding应助Dddd采纳,获得10
10秒前
yin发布了新的文献求助10
10秒前
大模型应助张张采纳,获得10
10秒前
Akim应助吾问无为谓采纳,获得10
11秒前
11秒前
神勇的冰姬完成签到,获得积分10
12秒前
13秒前
13秒前
13秒前
13秒前
14秒前
tony完成签到,获得积分10
14秒前
Uynaux发布了新的文献求助30
14秒前
SONG完成签到,获得积分10
14秒前
SYLH应助干秋白采纳,获得10
15秒前
15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 3527884
求助须知:如何正确求助?哪些是违规求助? 3108006
关于积分的说明 9287444
捐赠科研通 2805757
什么是DOI,文献DOI怎么找? 1540033
邀请新用户注册赠送积分活动 716904
科研通“疑难数据库(出版商)”最低求助积分说明 709794