As we age, our immune system also ages. We become more susceptible to infections, vaccinations work less well and the risk of developing immune-related disorders such as autoimmune diseases increases. “In order to better understand how and where exactly the immune system changes with age and which factors trigger or accelerate aging processes, we need to focus on the players of our immune system - the immune cells,” says Prof. Yang Li, head of the department “Computation Biology for Individualised Medicine” and Director of the CiiM.
The research question that Yang Li's team pursued was: What does the aging process look like in different types of immune cell? For their study, the scientists used thousands of transcriptome datasets for five different immune cell types from freely accessible data and literature sources. The so-called transcriptome is the set of all active genes in a cell at a given time. In total, the researchers had access to data sets of over two million immune cells from blood samples taken from around 1000 healthy people aged between 18 and 97. They then used machine learning to create a computer model. They call this model the “Single-Cell Immune Aging Clock”.
"We were able to identify specific genes for each type of immune cell that are involved in important immunological processes and whose activity changes during the aging process. These serve as marker genes for the respective immune cell type and as a reference in the subsequent application of the model,” explains Yang Li. “Incidentally, the genes we identified play a decisive role in the development of inflammatory processes. It is well known that aging processes are particularly associated with inflammatory processes. We were able to confirm this once again with our study.”
The research team then applied the aging clock in two case studies using patient data. They wanted to find out how a SARS-CoV-2 infection or a tuberculosis vaccination affects the aging processes within the different immune cell types. In COVID-19 patients, aging processes were only evident in one type of immune cell, the so-called monocytes. However, in people with a mild course of the disease, aging was significantly less pronounced. “Our results suggest that severe infections can cause our immune cells to age more quickly,” says Yang Li. “But - and this is good news - these changes seem to be reversible: After about three weeks, as COVID-19 patients slowly recover, the monocytes start to return to their original age profile.”
In the second case study, the researchers used the aging clock to look at the age of different immune cell types in people who had been vaccinated against tuberculosis. Here, the team discovered an interesting correlation: The vaccination had very different effects within one immune cell type, the so-called CD8 T cells, depending on how much inflammation was going on in the body. However, in people with high levels of inflammation, the vaccination had a rejuvenating effect on the immune cells.
“The Single-Cell Immune Aging Clock opens up incredibly exciting insights into cellular aging processes within different immune cell types for the first time,” says Yang Li. “It is a powerful tool that could be used in the future to uncover further dynamics of immune aging, to better understand the effects of infections and vaccinations and to develop new approaches for therapies and preventive measures that promote healthy aging.”
The research team is making the “Single-Cell Immune Aging Clock” freely available so that it can be used for further research projects.
Text: Nicole Silbermann
