Plain language summary
The human immune system changes with age, ultimately leading to a clinically evident, profound deterioration resulting in high morbidity and mortality rates attributed to infectious and chronic diseases. The aim of this study was to assess at high resolution the dynamics of older adults’ immune systems. The study uses multiple ‘omics’ technologies in a cohort of 135 adults (63 young adults and 72 older adults) of different ages who were sampled longitudinally over the course of 9 years to comprehensively capture population- and individual-level changes in the immune system over time. Results indicate that immune-cell frequencies changed at substantially different rates; some cell subsets show no directionality of change yet differ between young and old individuals, whereas other cell subsets continued changing (either increasing or decreasing) throughout the course of the study. Authors postulate that an individual’s immune age is a function of life history, namely environmental exposure coupled with genetic background. Thus, immune modulators may one day be identified that affect the position of an individual’s immune system along the immunological landscape.
Abstract
Immune responses generally decline with age. However, the dynamics of this process at the individual level have not been characterized, hindering quantification of an individual's immune age. Here, we use multiple 'omics' technologies to capture population- and individual-level changes in the human immune system of 135 healthy adult individuals of different ages sampled longitudinally over a nine-year period. We observed high inter-individual variability in the rates of change of cellular frequencies that was dictated by their baseline values, allowing identification of steady-state levels toward which a cell subset converged and the ordered convergence of multiple cell subsets toward an older adult homeostasis. These data form a high-dimensional trajectory of immune aging (IMM-AGE) that describes a person's immune status better than chronological age. We show that the IMM-AGE score predicted all-cause mortality beyond well-established risk factors in the Framingham Heart Study, establishing its potential use in clinics for identification of patients at risk.
Methodological quality
Jadad score
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Allocation concealment
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