Understanding the interplay between the immune system’s dynamics and the natural aging process is crucial for developing potential strategies to mitigate age-related health challenges. Here, we investigated how immunophenotypic profiles vary with the natural aging process, daily practices, and physiological characteristics within a general population of 605 healthy individuals from the Central China Cohort. Utilizing mass cytometry on peripheral blood mononuclear cell (PBMC) samples, we acquired over 57 million single-cell data in total from this cohort. These cells were clustered into 50 distinct immune cell subsets. Additionally, we gathered detailed questionnaires from every participant with 764 questions concerning their physical and physiological metrics, lifestyles, and socioeconomic status. By leveraging bootstrap lasso and logit regression models, we endeavored to forecast age and gender based on immunophenotypic profiles. Our investigations unveiled significant correlations between chronological age and specific immune cell clusters such as CD27+CD28+ naïve T and γδ T cells and CD38+ pDCs, showcasing discernible age-related patterns. Furthermore, we established immune ages through the regression models and calculated the age differentials relative to the chronological age, which shed light on the relationships between younger or older immune ages and various body metrics and lifestyles. By offering a comprehensive overview of immune cell profiles in a sizable healthy cohort through mass cytometry, this data resource advances our comprehension of the roles played by immune systems and lifestyles in the aging process.
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Li et al. (2026) studied this question.
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