Tu202 - Systems Immunology Framework and Centrality Metric Provide Improved Insight into Immune Aging

Abstract Text: The Immune System is a complex “Network of Networks”, in which various immune cell subsets interact and influence each other's functions, ultimately determine immune competence and the control or onset of disease. The coordinated interactions between these cell subsets determine whether the outcome is a normal physiological state or pathological condition. Established statistical procedures largely ignore the interactions between subsets and rely on statistically significant changes in the frequency of cell subsets.We developed CyNET (Cytometry Network)— an analysis platform based on a network science approach to understand the immune system holistically. CyNET enables us to we quantify the systems level and subsets level properties.We used CyNET to analyze the immune development along the chronological age gradient. Peripheral blood cells from healthy newborns (cord blood), adults (20 to 55 years), and elderly (70 years and above) human subjects were analysed using CyNET and scRNA sequencing. We show that changes in the centrality of the nodes (immune subsets) reflect better biological functions than changes in frequency alone. For e.g. frequency of CD28- CD8 T cells increases with aging; however, our findings demonstrated reduced centrality and diminished ligand-receptor mediated intracellular interaction potential explaining senescence and exhaustion of these cells. Furthermore, we found systems property such as network edge density, degree centralization, and assortativity score reflect the maturation and development of the immune system along the age axis, thus enabling the characterisation of the functional architecture of the Immunome and the identification of key functional hubs within the immune networks along the age axis.