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- Title
High-dimensional analysis of the aging immune system: Verification of age-associated differences in immune signaling responses in healthy donors.
- Authors
Longo, Diane M.; Louie, Brent; Ptacek, Jason; Friedland, Greg; Evensen, Erik; Putta, Santosh; Atallah, Michelle; Spellmeyer, David; Ena Wang; Pos, Zoltan; Marincola, Francesco M.; Schaeffer, Andrea; Lukac, Suzanne; Railkar, Radha; Beals, Chan R.; Cesano, Alessandra; Carayannopoulos, Leonidas N.; Hawtin, Rachael E.
- Abstract
Background Single-cell network profiling (SCNP) is a multiparametric flow cytometry-based approach that simultaneously measures evoked signaling in multiple cell subsets. Previously, using the SCNP approach, age-associated immune signaling responses were identified in a cohort of 60 healthy donors. Methods In the current study, a high-dimensional analysis of intracellular signaling was performed by measuring 24 signaling nodes in 7 distinct immune cell subsets within PBMCs in an independent cohort of 174 healthy donors [144 elderly (>65 yrs); 30 young (25-40 yrs)]. Results Associations between age and 9 immune signaling responses identified in the previously published 60 donor cohort were confirmed in the current study. Furthermore, within the current study cohort, 48 additional immune signaling responses differed significantly between young and elderly donors. These associations spanned all profiled modulators and immune cell subsets. Conclusions These results demonstrate that SCNP, a systems-based approach, can capture the complexity of the cellular mechanisms underlying immunological aging. Further, the confirmation of age associations in an independent donor cohort supports the use of SCNP as a tool for identifying reproducible predictive biomarkers in areas such as vaccine response and response to cancer immunotherapies.
- Subjects
IMMUNE system; FLOW cytometry; AGING; CANCER immunotherapy; VACCINATION
- Publication
Journal of Translational Medicine, 2014, Vol 12, Issue 1, p1
- ISSN
1479-5876
- Publication type
Article
- DOI
10.1186/1479-5876-12-178