Unlocking serology’s secrets: harnessing novel immune biomarkers to predict Lyme disease progression and recovery

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There are currently an estimated 476,000 cases of Lyme disease annually in the United States, caused by the bacteria Borrelia burgdorferi (Bb) and more cases every year. At least 10% of people with Lyme disease experience persistent symptoms after standard antibiotic treatment. Currently, there are no tools to predict Lyme disease illness trajectories; a significant barrier to research progress. A primary goal of this research proposal is to identify a biomarker that accurately predicts which patients go on to recover, and to advance understanding of host immune responses and disease pathomechanisms contributing to persistent symptoms. While there historically has been a significant focus in the field on using bulk IgG and IgM antibodies to diagnose Lyme, instead we quantified all the different IgG subtypes, IgE, and IgA isotypes of antibodies. We found that the plasma of acute Lyme patients who went on to fully recover after antibiotics contained opposite levels of subtypes and isotypes than patients who developed persistent symptoms. We identified a novel protective immune profiling ratio of the different antibody types in patients who went on to recover. We hypothesize that this antibody ratio is a biomarker that can predict who recovers from Lyme disease post-antibiotics and who will go on to have persistent symptoms. To further explore this, we developed a new FLow-based Immune Profiling technology that we call FLIP to better profile the isotypes and subtypes of antibodies that bind to Bb. The FLIP innovatively uses live Bb as bait to precipitate out pathogen specific antibodies. Next, we propose to conduct deep analysis into immune mechanisms contributing to persistent symptoms. This includes testing the downstream immune effector functions of IgG subtypes and different isotypes like IgA and IgE that have previously been largely overlooked in Lyme research. This is important because we found concerningly high levels of IgE that binds to Bb in a third of people experiencing persistent symptoms. In mice this IgE triggers mast cell degranulation. This could indicate the development of an allergy type response to Bb or parts of Bb that are also found in other bacteria, and point to treatment options used for allergies. We propose to further refine our novel predictive immune biomarker ratio and test our new FLIP technology on multiple patient cohorts including acute Lyme patients, patients with persistent symptoms, and healthy controls. We are proposing to turn our current cross-sectional study into a new prospective study so that we can test if our antibody ratio is truly predictive and accurate. There is immense field-wide significance for this research. Creating the ability for scientists and physicians to predict illness trajectories can enable smaller and more cost-efficient clinical trials by focusing on those at the highest risk of not recovering. In the future, it could inform clinical care and enable new targeted therapeutics that prevent long term illness by helping immune systems match the protective antibody ratio we found, and more effectively respond to Borrelia burgdorferi.