During the past 30 years, notable advances have been made in understanding the etiologic agent, Borrelia burgdorferi (Bb), and the illness that it causes. While ~30,000 cases are reported to the CDC each year, the overall number of Bb-infected patients in the US is estimated to approach 400,000, suggesting that Lyme disease is becoming an epidemic. Signs and symptoms of infection range in severity and most patients recover fully after antimicrobial treatment; however, chronic serious illness and even deaths can still occur. Lyme disease is usually diagnosed by clinical observation of erythema migrans (bulls-eye rash), however, some patients do not develop erythema migrans. Why certain patients have no accompanying symptoms at time of presentation whereas others have numerous symptoms has not been elucidated. Many studies have been published detailing progress in expanding the knowledge base on the microbiology of Bb and on the ecology and epidemiology, pathogenesis and clinical aspects but laboratory-based diagnosis of Lyme disease is severely lagging behind. It is been estimated that more than 2.7 million serum samples are tested each year for the presence of Borrelia burgdorferi-specific antibodies in the United States alone. To meet the demand for laboratory-based diagnosis, various new tests for direct detection of the etiologic agent, or for detection of post-infection specific antibodies by using whole-cell lysates, recombinant antigens, or peptide antigens in enzyme immunoassays (EIA), have been introduced into the clinical laboratory. However, the currently available Lyme disease diagnostics do not meet the specifications for an ideal test, which would be rapid, sensitive, specific, and point-of-care. Currently, the two step FDA approved diagnostic test will only detect the post-infection immune response to Lyme disease pathogen, Bb, and with limited sensitivity and specificity. An ideal Lyme disease diagnostic is a test that is specific for Bb, simple, non-invasive and relies only on readily available samples such as blood or urine. Our proposal will provide specific targets detectable in blood at the earliest time point upon Bb infection. To develop these tests, we have constructed an extensive proteogenomic resource of Bb isolates and provide a publically accessible ?Borrelia PeptideAtlas. Using our novel study design incorporating broad quantitative surface exposed pathogen protein detection and comprehensive targeted peptide quantitation in complex host proteome backgrounds, we will deploy novel highly specific and high sensitivity diagnostic assays targeting Bb protein remnants for both early and treatment phase Lyme disease detection. The outcome of this proposal will have great impact by reducing disproportionate determinations of Lyme disease through the establishment of novel biomarkers for diagnostic test development in early stage Lyme disease.

Public Health Relevance

Statement of relevance to human health None of the currently available Lyme disease diagnostics meet the specifications of an ideal test, which would be rapid, sensitive, specific, and point-of-care. Currently, the two step FDA approved diagnostic test will only detect an immune response to the Lyme disease pathogen, Borrelia burgdorferi, and with limited sensitivity and specificity. An ideal Lyme disease diagnostic is a test that is simple, non-invasive and relies only on readily available Lyme disease suspect patient samples such as blood or urine to detect Borrelia burgdorferi infection at the earliest time point upon infection using high sensitivity diagnostic assays targeting Borrelia burgdorferi protein remnants for both early and treatment-phase Lyme disease detection.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21AI142302-02
Application #
9825501
Study Section
Enabling Bioanalytical and Imaging Technologies Study Section (EBIT)
Program Officer
Ilias, Maliha R
Project Start
2018-11-20
Project End
2020-10-31
Budget Start
2019-11-01
Budget End
2020-10-31
Support Year
2
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Institute for Systems Biology
Department
Type
DUNS #
135646524
City
Seattle
State
WA
Country
United States
Zip Code
98109