Large-Scale and Comprehensive Immune Profiling and Functional Analysis of Normal Human Aging

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.