Available for Licensing
John T Belisle
Claudia R Molins
Gary P Wormser
At a Glance
Researchers at Colorado State University have developed and patented a metabolic biosignature based on small molecule metabolites of serum for the diagnosis of early Lyme Disease. The biosignature consists of more than 44 molecular features (metabolites) that correctly diagnosed early Lyme patients and healthy controls with a sensitivity of 88% (84-95%) and a specificity of 95%. This is in comparison to the current CDC recommended diagnostic that correctly diagnoses the same patient group with 37-44% sensitivity and 95-100% specificity.
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Lyme disease (LD), caused by Borrelia burgdorferi, is the most commonly reported tick-borne disease in the United States and Europe. Recent studies suggest that 300,000 cases of LD may occur in the United States each year. Antibody-based diagnostics for LD are widely utilized in clinical practice, and the Centers for Disease Control and Prevention (CDC) recommends a 2-tier approach for serologic testing. The detection of antibodies to B. burgdorferi is highly specific and sensitive in patients with late manifestations of LD; however, the sensitivity in patients with early LD is unsatisfactory (29%–40%). Direct diagnostic testing using culture or nucleic acid amplification on peripheral blood samples also has low sensitivity (≤50%) for early LD. Thus, the diagnosis of early LD is usually based on recognition of the most common clinical manifestation, an erythema migrans (EM) skin lesion. Other skin lesions, however, such as tick-bite hypersensitivity reactions, STARI (southern tick associated rash illness), and certain cutaneous fungal infections, can be confused with EM.
Retrospective serum samples from patients with early Lyme disease, other diseases, and healthy controls were analyzed for small molecule metabolites by liquid chromatography-mass spectrometry (LC-MS). A metabolomics data workflow was applied to select a biosignature for classifying early Lyme disease and non-Lyme disease patients. A statistical model of the biosignature was trained using the patients’ LC-MS data, and subsequently applied as an experimental diagnostic tool with LC-MS data from additional patient sera. The accuracy of this method was compared with standard 2-tier serology.
- Ability to distinguish between active and inactive Lyme Disease
- Increased sensitivity without changing specificity
- Diagnostics for Lyme Disease(LD), specifically early LD
Last updated: March 2023