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Several body functions deteriorate with age. The external signs of aging are easily identifiable. For example, the skin becomes dry, less elastic, and thins out, forming wrinkles. The skin of the face begins to appear looser due to a decrease in the levels of elastic and collagen fibers in the connective tissue. Additionally, melanin production in the hair follicle decreases with age, resulting in gray hair. Moreover, the senses of sight and hearing decline, so glasses and hearing aids may...
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Large-Scale and Comprehensive Immune Profiling and Functional Analysis of Normal Human Aging.

Chan C Whiting1, Janet Siebert2, Aaron M Newman3

  • 1Institute for Immunity, Transplantation, and Infection, Stanford School of Medicine, Stanford University, Stanford, CA, United States of America; Division of Rheumatology and Immunology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, United States of America.

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Summary
This summary is machine-generated.

This study defines key immune system metrics for aging. Researchers identified specific blood analytes that can predict a person's age, highlighting the importance of a comprehensive approach to understanding immune aging.

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Area of Science:

  • Immunology
  • Gerontology
  • Biostatistics

Background:

  • Immune system function declines with age, a process known as immune aging.
  • Existing metrics for immune aging are not comprehensive, hindering accurate assessment.
  • Understanding immune aging is crucial for maintaining health in older adults.

Purpose of the Study:

  • To establish a comprehensive set of metrics for assessing immune aging in healthy adults.
  • To identify key immune parameters that change with age, sex, and cytomegalovirus (CMV) status.
  • To develop a predictive model for age based on immune system readouts.

Main Methods:

  • Collected data from 243 healthy adults aged 40-97.
  • Measured clinical parameters, serum cytokines, peripheral blood mononuclear cell (PBMC) phenotypes, gene expression, and cytokine-stimulated signaling.
  • Utilized elastic net regression for multivariate analysis and age prediction.

Main Results:

  • Significant age-related trends were observed across various immune assays, though individual heterogeneity was high.
  • Age, followed by sex and CMV status, demonstrated the most substantial impact on immune parameters.
  • An elastic net regression model accurately predicted age using 14 selected immune analytes.

Conclusions:

  • A multivariate approach is essential for defining a healthy immune system profile.
  • The study provides a valuable reference dataset for researchers studying immune parameters in aging populations.
  • Specific immune analytes can serve as reliable biomarkers for immune aging.