Antiphospholipid Antibodies for the Diagnosis of Lyme Disease
Abstract
This proposal addresses the Fiscal Year 2021 Tick-Borne Disease Research Program Focus Area of Diagnosis and specifically seeks to develop a test capable of distinguishing active infection and previous exposure, and/or monitoring of response to treatment. Currently, the diagnosis of Lyme disease relies on the detection of the host immune response to the causative organism, Borrelia burgdorferi. This type of testing, called serologic testing, has several limitations. First, the host immune response typically takes some time to develop, resulting in a lag between the time someone is infected and the time serologic testing becomes positive. This can cause delays in initiating treatment that are associated with more severe disease and a higher risk of post-treatment Lyme disease symptoms. Another major issue with current serologic testing is once the test is positive, it stays positive for long periods of time, making it useless for tracking the success of treatment or for detecting reinfection. In the course of fundamental research on the metabolism of the Lyme disease bacteria, our lab has identified a series of antibodies that may arise earlier in infection and decline faster after treatment. These antibodies do not recognize bacterial proteins detected by currently available tests but are instead raised against host molecules (phospholipids) that B. burgdorferi co-opts for its own purposes. Normally, the host immune response suppresses the production of antibodies to its own molecules, but in the context of the bacterial infection, it now can recognize these targets. Also, because these targets have likely been seen by the immune system before, but were suppressed, antibodies may be ramped up and produced more quickly when they are recognized in conjunction with B. burgdorferi. In addition, because the host tries to limit antibodies that have the potential to damage itself, once the infection is cleared and the stimulus is removed, the immune system quickly shuts down further production of antibodies to these molecules. As such, testing for these anti-phospholipid antibodies to host molecules could address multiple key failings of the current diagnostic tests. Our preliminary studies show that anti-phospholipid antibody levels decline steadily in most patients after antibiotic treatment and return to baseline levels at time-points when antibodies used in traditional Lyme diagnostics remain very elevated. In addition, it appears that patients who remain symptomatic after antibiotic therapy have higher levels of these anti-phospholipid antibodies. This suggests that these types of autoantibodies may have a role in following the response of patients to antibiotic treatment and in differentiating symptoms that result from Lyme disease from other infections (e.g., long COVID). As part of this project, we will first broaden the search for different types of antiphospholipid autoantibodies to include a larger number of different lipids/phospholipids to find the combination of antigens with the best characteristics for a monitoring test. We will also determine if specific antibody classes (IgM, IgG subclasses, IgA) may be the most sensitive/specific for following resolution of disease. The experiments proposed here will examine the levels of each of the candidate antibodies throughout the multiple stages of Lyme disease using a sample from the extensive collections of Dr. Adriana Marques (National Institutes of Health) and Dr. John Aucott (Johns Hopkins University). We will test for specificity by studying samples from patients with other types of infection or autoimmune diseases. Using this information, we will design a diagnostic panel of antibodies optimized for a return to baseline levels after successful treatment and where elevation is most closely linked to persistent symptoms. Finally, we will assess the final test configuration using an independent validation panel of samples. The lack of a good
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 04, 2024
- Source ID
- HT94252310526
Entities
People
- Linden Hu
Organizations
- Tufts University School of Medicine
- United States Army