中国健康成年人外周血T淋巴细胞和NK淋巴细胞亚群的免疫衰老评估
Immune-Ageing Evaluation of Peripheral T and NK Lymphocyte Subsets in Chinese Healthy Adults.
作者信息
Jia Zhenghu, Ren Zhiyao, Ye Dongmei, Li Jiawei, Xu Yan, Liu Hui, Meng Ziyu, Yang Chengmao, Chen Xiaqi, Mao Xinru, Luo Xueli, Yang Zhe, Ma Lina, Deng Anyi, Li Yafang, Han Bingyu, Wei Junping, Huang Chongcheng, Xiang Zheng, Chen Guobing, Li Peiling, Ouyang Juan, Chen Peisong, Luo Oscar Junhong, Gao Yifang, Yin Zhinan
机构信息
Guangdong Provincial Key Laboratory of Tumor Interventional Diagnosis and Treatment, Zhuhai Institute of Translational Medicine Zhuhai People's Hospital Affiliated With Jinan University, Jinan University, Zhuhai, 519000 Guangdong China.
The Biomedical Translational Research Institute, Health Science Center (School of Medicine), Jinan University, Guangzhou, 510632 Guangdong China.
出版信息
Phenomics. 2023 May 23;3(4):360-374. doi: 10.1007/s43657-023-00106-0. eCollection 2023 Aug.
UNLABELLED
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.
SUPPLEMENTARY INFORMATION
The online version contains supplementary material available at 10.1007/s43657-023-00106-0.
未标注
衰老常伴随着免疫系统功能下降，导致免疫衰老。众多研究聚焦于疾病和免疫衰老中不同淋巴细胞亚群的变化。免疫表型的改变是疾病或健康状态的关键指标。然而，衰老引起的淋巴细胞数量和表型变化尚未得到全面分析。在此，我们分析了43096名年龄在20至88岁、无已知疾病的健康个体的T细胞和自然杀伤（NK）细胞亚群、表型及细胞分化状态。分析了36个免疫参数，并在以5年为间隔划分的不同年龄组中建立了这些亚群的参考范围。对数据进行随机森林机器学习以建立免疫衰老模型，并使用神经网络分析进行验证。我们的初步分析和机器学习预测表明，随着年龄增长，初始T细胞减少，而中央记忆T细胞（Tcm）和效应记忆T细胞（Tem）增加了分化簇（CD）28相关T细胞。这是在中国人群中调查年龄与免疫细胞功能相关性的最大规模研究，提供了有深刻见解的差异，表明健康成年人可能受到年龄和性别的显著影响。一个人的免疫系统年龄可能与其实际年龄不同。我们的免疫衰老建模研究是提供“免疫年龄”而非“生物年龄”见解的最大规模研究之一。通过机器学习，我们确定了衰老影响最大的免疫因素，并建立了免疫衰老预测模型。我们的研究不仅揭示了年龄对中国人群免疫参数差异的影响，还为临床实践中监测和预防某些疾病提供了新见解。
补充信息
在线版本包含可在10.1007/s43657-023-00106-0获取的补充材料。
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