Researchers at Colorado State University have developed a new blood-based method to distinguish early Lyme disease from Southern Tick-Associated Rash Illness (STARI). The approach analyzes small molecules in patient blood to detect unique disease signatures. It achieves up to 98% accuracy when classifying these conditions. This method provides a more reliable way to support early diagnosis and treatment decisions.
Lyme disease is the most commonly reported vector-borne illness in the United States and requires early diagnosis for effective treatment. Its hallmark rash can resemble that of STARI, a similar illness with no confirmed cause or standard diagnostic test. Because both conditions occur in overlapping regions, misdiagnosis is common. A reliable way to distinguish between them is critical for improving patient outcomes and guiding appropriate care.
This technology uses an unbiased metabolomics approach to analyze blood samples from patients and identify disease-specific metabolic profiles. By comparing patterns of small molecules present in the blood, the method detects consistent differences between early Lyme disease and STARI. These metabolic signatures are then used to train classification models that can assign new patient samples to the correct condition.
When tested on independent sample sets, the models achieved classification accuracy ranging from 85% to 98%, with particularly strong performance indicated by an area under the curve (AUC) of 0.986. This high level of accuracy demonstrates the method’s ability to reliably separate two clinically similar conditions that are otherwise difficult to distinguish using current diagnostic approaches.
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John Belisle
Claudia Molins
Gary Wormser
Jessy McGowan
Jessy.McGowan@colostate.edu
970-491-7100