A study published in Nature maps how immune profiles change across adulthood, offering a reference point for interpreting age-related differences in serology, cellular phenotyping, and vaccine responses.
Investigators profiled peripheral immunity in more than 300 healthy adults (ages 25 to 90) using a multi-omic approach comprising single-cell RNA sequencing, plasma proteomics, and flow cytometry. A subset of 96 participants was followed longitudinally for two years around seasonal influenza vaccination.
The dataset comprises more than 16 million single cells spanning 71 immune subsets and reveals non-linear, age-associated transcriptional reprogramming most prominently within T cells. Notably, these shifts were not explained by systemic inflammation or cytomegalovirus status in midlife, and were linked to a T helper 2 (TH2) bias in memory T cells associated with altered B-cell vaccine responses.
Circulating protein profiles showed persistent age-associated differences, including increases in markers such as CXCL17, WNT9A, and GDF15. However, classic inflammatory cytokines (TNF, IL-6, IL-1B) were not elevated in this cohort prior to advanced age. These patterns remained stable over one year, suggesting that commonly used inflammatory readouts might not capture early immune aging.
Analysis of more than 13 million single immune cells showed that T cells undergo the most pronounced molecular changes with age. These changes were different from those related to sex, cytomegalovirus infection, or recent vaccination. Researchers developed an RNA Age Metric (RAM) – a combined measure of gene activity that reflects “immune age.” In older adults, this score stayed consistently higher over a two-year period, suggesting it could be a useful way to assess immune system aging beyond simply counting cell types.
A second group of 234 adults (ages 40 to over 90) confirmed these findings. With age, naïve CD8 cells decreased, while age-associated B cells increased. The RNA Age Metric also rose across different T-cell types, following a non-linear pattern. Certain genes, such as PTGER2 and SESN3, were more active with age. Similar changes appeared in lymph node T cells, indicating that these molecular shifts occur throughout the immune system – not just in the blood. The same pattern was seen in people at risk of rheumatoid arthritis, suggesting that the RNA Age Metric could help identify early immune aging even before disease develops.
Influenza vaccination analyses highlighted diagnostic nuances: older adults showed fewer high responders for the repeatedly boosted B/Phuket strain, despite broadly intact responses otherwise. Transcriptomic and protein data pointed to reduced activation and IgG class switching in CD27– effector memory B cells, with a skewed IgG2/IgG3 ratio in older adults. These B-cell features correlated with T-cell reprogramming and an increased TH2-like state in CD4 central memory cells with age.
The study showed that age affects many immune measurements, including baseline protein levels, the mix of immune cell types, and how antibody types change after vaccination. These shifts can occur even without signs of inflammation, such as increased cytokines. The authors suggest that using age-adjusted reference data and combined molecular measures – like the RNA Age Metric – could help laboratories and clinicians interpret immune tests more accurately, improve vaccine response evaluation, and detect early signs of immune dysfunction in adults.
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