Towards a general indicator of immune responsiveness: A baseline blood transcriptomic signature that correlates with vaccination response and lupus disease activity

Authors

• R Sparks
• Y Kotliarov
• Y Lu
• M Goswami
• L Kardava
• AJ Martins
• CC Liu
• S Moir
• JS Tsang

Abstract

Understanding inter-individual differences in immune system states and responsiveness is a fundamental goal of human immunology. A previous NIH study of the response to seasonal influenza vaccine in healthy individuals identified frequencies of temporally-stable CD20+ B-cells expressing high levels of CD38 as predictors of antibody response (Tsang et al., Cell 2014). To assess whether these cells are predictive in different vaccination cohorts that did not measure our cells of interest, we developed a 10-gene signature for these specific B-cells (CD20+ CD19+ CD38++). Our gene signature was able to differentiate between high and low vaccine responders in several publicly available (inactivated) influenza and (live attenuated) yellow fever vaccination datasets (AUC >= 0.80). As these vaccines are immunologically different, it suggested that our signature may be reflective of the immune system’s propensity to respond to an antigenic challenge. If true, our baseline signature could also be indicative of responsiveness to self-antigens, often manifested clinically as autoimmune diseases. We tested this hypothesis in a longitudinal pediatric systemic lupus erythematosus (SLE) dataset (Banchereau, Cell 2016), specifically asking whether our baseline signature evaluated during clinically quiescent periods correlated with the magnitude of flares associated with plasmablast increases. Our results suggested that for a subset of SLE patients (with disease activity associated with plasmablast changes), this was indeed the case. Taken together, our study shows the utility of comprehensive immune state characterization, both at baseline and in perturbed/disease states, and postulates that there may exist “common” immune responsiveness setpoints.

Scientific Focus Area: Systems Biology

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