Pathological Autoantibodies Contribute to Immune Suppression in Sepsis - PROJECT SUMMARY/ABSTRACT Sepsis is a severe illness associated with high morbidity and mortality in the US and globally. Complications of multi-organ dysfunction, acute respiratory distress syndrome, and infections have a significant impact on late survival. With limited therapeutic interventions, it is essential to understand the fundamental biology of sepsis. Immune dysfunction and immunosuppression are characteristic of sepsis, especially with late complications where lymphopenia predicts a poor prognosis. Gaps remain, however, in the understanding of the mechanisms underlying prolonged immune suppression. Recently, there has been a greater appreciation of autoimmune antibodies that lead to pathological immune consequences in the setting of critical illness. For example, sepsis due to COVID-19 leads to anti-cytokine autoantibodies (ACAAs) that correlate with greater disease severity. In our preliminary data we have also defined ACAAs post-COVID along with ACAAs in ICU patients with sepsis. We have also made the novel discovery of anti-Fas autoantibodies (FasAAs) induced during sepsis, representing a novel mechanism for lymphopenia associated with critical illness. Our overarching hypothesis is that severe conditions like sepsis induce pathological autoimmunity that alters immune function and increases infections. Our hypothesis predicts that sepsis patients with higher levels of autoantibodies will have more immune dysregulation and secondary infectious complications. The objective of this proposal is to determine the prevalence of ACAAs, define mechanism(s) by which they contribute to immunosuppression, and identify sites where their activity could be disrupted for therapeutic purposes. We propose using complementary immune and computational approaches to identify autoantibodies from the blood of sepsis patients and how they correlate with clinical status. We will investigate the biological function of these antibodies on human cytokines and human cells in vitro, along with developing strategies to interfere with deleterious autoantibodies. To address these issues, we have obtained over 350 serum specimens for this study to discriminate between the effects of preexisting autoantibodies and those with a net increase during sepsis. In addition, we have access to deep RNA-seq data from over 100 sepsis patients for computational studies. The long-term objective is to apply this information to assess prognosis of sepsis patients and create precision therapeutics to sustain and restore immune function.
