ArticlePhenomics (Cham, Switzerland)2023
Immune-Ageing Evaluation of Peripheral T and NK Lymphocyte Subsets in Chinese Healthy Adults.
Article in Phenomics (Cham, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed, 26 citations in OpenAlex.
- Single-cell mapping of thymus-dependent naïve t-cell regeneration reveals CD61-associated states after hematopoietic stem cell transplantation.Experimental hematology & oncology · 2026Article
- Association between pan-immune-inflammation value and prognosis in lung cancer patients: a systematic review and meta-analysis.Translational cancer research · 2026Article
- The Evolving Landscape of Clinical Aging Clocks: From Epigenetic to Multi-Omics Integration.Aging cell · 2026Review
- Peripheral CD8⁺ T cell subsets and physical frailty in community-dwelling older Thai adults: the role of age and multimorbidity.BMC geriatrics · 2026Article
- scMOVIR: a single-cell multi-omics database for human viral infections and immune responses.Nucleic acids research · 2026Article
- Distribution and function of human long-lasting T cells in aging and non-small cell lung cancer.Frontiers in immunology · 2026Review
- A novel study to calculate immune-aging from peripheral blood T lymphocyte subsets and their mitochondrial parameters in healthy Chinese subjects.Frontiers in immunology · 2026Article
- Exercise interventions remodel the aging microenvironment to improve prognosis in older patients with cancer.Frontiers in immunology · 2026Review
- Artificial intelligence and machine learning in immunosenescence: from biomarker discovery to clinical translation.Frontiers in aging · 2026Review
- Review
- Immunophenotyping of Mouse Colonic Unconventional T Cells by Mapping Cell Phenomics With 22-Color Flow Cytometry Assays.Phenomics (Cham, Switzerland) · 2025Article
- Characterizing age-related features for assessing biological age and characteristics in Xinjiang Brown cattle.BMC genomics · 2025Article
- Immune status assessment based on plasma proteomics with meta graph convolutional networks.BMC genomics · 2025Article
- NK Cell Senescence in Cancer: From Molecular Mechanisms to Therapeutic Opportunities.Aging and disease · 2025Review
- An in-depth understanding of the role and mechanisms of T cells in immune organ aging and age-related diseases.Science China. Life sciences · 2025Review
- Hyperglycemic milieu impairs Vγ9Vδ2 T cell functions in tuberculosis patients and prolongs M.tb negative conversion time.iScience · 2025Article
- Single-cell analysis of peripheral blood and pleural effusion reveals functional diversity of γδ T cells in tuberculosis infection.Frontiers in immunology · 2025Article
- How to properly define immunological nonresponse to antiretroviral therapy in people living with HIV? an integrative review.Frontiers in immunology · 2025Review
- Review
- GREM1 may be a biological indicator and potential target of bladder cancer.Scientific reports · 2024Article
Corrections and comments
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Authors and funding
26 authors at 7 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.