# Host Metabolic Biosignatures for the Diagnosis of Lyme Disease

> **NIH NIH R01** · COLORADO STATE UNIVERSITY · 2021 · $753,386

## Abstract

PROJECT SUMMARY
Lyme disease is the most frequently reported vector-borne disease in the U.S., with 300,000 cases estimated to
occur annually. Current diagnosis of Lyme disease is based on recognition of an erythema migrans (EM) skin
lesion or positive two-tiered serological (antibody detection) testing in a patient with consistent clinical signs and
tick exposure in areas where Lyme disease occurs. It is estimated that 20 to 30% of patients do not present with
an EM, and the majority of patients do not recall a tick bite. Moreover, serologic tests are dependent on the host
humoral immune response and lack sensitivity in early Lyme disease (only 29-40% of patients with EM are
seropositive). Serological reactivity also may persist for years following antibiotic treatment and resolution of
symptoms. These limitations and the need for early diagnosis to facilitate rapid therapeutic intervention provide
strong rationale for the development of new Lyme disease diagnostic tests. We have undertaken a novel
approach of applying serum metabolomics to develop small molecule biosignatures that can be exploited as a
diagnostic test for early Lyme disease. These efforts resulted in a published candidate biosignature that provided
a sensitivity of 88% for early Lyme disease with a specificity of 95% for healthy controls and 93% for other
disease control populations. This approach was also able to differentiate early Lyme disease from Southern Tick
Associated Rash Illness (STARI), an illness with an EM-like skin lesion and similar non-specific symptoms of
early Lyme disease, and correctly classified these two patient groups with 98% accuracy for Lyme disease and
89% accuracy for STARI. Our preliminary data now provides strong evidence that metabolic profiles can
differentiate early LD from other tick transmitted diseases and distinguish between the various manifestations of
early Lyme disease (i.e., early localized versus early disseminated disease). Under this proposal, the
expertise of biochemists, microbiologists, mathematicians, statisticians and infectious disease
clinicians will be combined to perform studies that will significantly advance our previous efforts.
Specifically, we hypothesize that it is possible to create a diagnostic metabolic profile that accurately
distinguishes early Lyme disease patients from non-Lyme disease patients, and that can be applied in a
clinical laboratory, Importantly the non-Lyme disease patient group are those individuals suspected of Lyme
disease (patients who present for medical care and who undergo diagnostic testing for Lyme disease, but are
not diagnosed with Lyme disease), as well as those with other tick transmitted diseases. Our proposed efforts
take into account the heterogeneous symptoms of early Lyme disease and the non-Lyme disease populations.
The goal of diagnostic development will be facilitated through the application of state-of-the-art mathematical
modeling and well-characterized prospectively and retros...

## Key facts

- **NIH application ID:** 10199751
- **Project number:** 5R01AI141656-03
- **Recipient organization:** COLORADO STATE UNIVERSITY
- **Principal Investigator:** John T Belisle
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $753,386
- **Award type:** 5
- **Project period:** 2019-06-19 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10199751

## Citation

> US National Institutes of Health, RePORTER application 10199751, Host Metabolic Biosignatures for the Diagnosis of Lyme Disease (5R01AI141656-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10199751. Licensed CC0.

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