Quantifiable Blood TCR Repertoire Components Associated with Immune Aging
Li, B.; Hu, J.; Pan, M.; Reid, B.; Tworoger, S.
Show abstract
T cell senescence results in decayed adaptive immune protection in older individuals, with decreased or increased abundance of certain T cell phenotypic subpopulations. However, no study has linked aging to the dynamic changes of T cell clones. Through a newly develop computational framework, Repertoire Functional Units (RFU), we investigated over 6,500 TCR repertoire sequencing samples from multiple human cohorts. Our analysis identified age-associated RFUs repeatedly and consistently across different cohorts. Quantification of RFU decreases with aging revealed accelerated loss under immunosuppressive conditions. Systematic analysis of age-associated RFUs in clinical samples manifested a potential link between these RFUs and improved clinical outcomes during acute viral infections, such as lower ICU admission and reduced risk of developing complications. Finally, our investigation of bone-marrow transplantation patients indicated a secondary expansion of the age-associated clones upon receiving stem cells from younger donors. Together, our results suggest the existence of certain clones or a TCR clock that could reflect the immune functions in aging populations.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- Post-infectious inflammatory disease in MIS-C features elevated cytotoxicity signatures and autoreactivity that correlates with severity 95%
- Soluble CTLA-4 mainly produced by Treg cells inhibits type 1 inflammation without hindering type 2 immunity to allow for inflammation resolution 94%
- p16High immune cell - controlled disease tolerance as a broad defense and healthspan extending strategy 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.