Multiplex single-tier LymeSeek test improves sensitivity during the diagnostic gray zone of early Lyme disease

Lyme disease, caused by the spirochete Borrelia burgdorferi, is the most common vector-borne disease in the U.S. and a growing public health concern due to the clinically challenging nature of the disease. Prompt antibiotic treatment early in the infection results in the best patient outcomes, while delayed treatment increases the risk of developing debilitating chronic symptoms. Because standard-of-care diagnostic tests (standardized and modified two-tier tests) have low sensitivity during the first few weeks of infection, current recommendations for diagnosing early Lyme disease rely heavily on observation and recognition of erythema migrans (EM). However, a significant proportion of Lyme disease patients develop an atypical-appearing rash, or no rash is observed. To improve diagnostic accuracy, we developed LymeSeek, a microbead-based multiplex flow immunoassay performed as a single test that detects binding of IgM and IgG antibodies to a novel combination of eight B. burgdorferi antigens. Fluorescent signals from bound antibodies are translated into a disease probability and a single test result-either detected or not detected. Overall test sensitivity across all disease stages was over 90%, with no loss of specificity. The LymeSeek test performed well in blinded panels, correctly differentiating serologically positive cases from both disease and non-disease controls. The test also identified early Lyme disease cases, with and without an observed EM rash, that were negative on the current standard-of-care two-tier serological tests. The LymeSeek test has the potential to increase diagnostic accuracy and improve patient outcomes, particularly during the diagnostic gray zone of early Lyme disease.IMPORTANCEStandard and modified two-tier serological tests for Lyme disease are not sensitive enough to diagnose patients within the first few weeks of infection, when antibiotic treatment is recognized as being most effective. This report describes a single-tier multiplex immunoassay that utilizes detection of 16 diagnostic antibodies against eight Borrelia antigens and interpretation by a machine learning-developed algorithm that demonstrates sensitivity high enough to accurately diagnose over 90% of Lyme disease cases, including those in the early diagnostic gray zone period when diagnostic uncertainty is highest. Specificity is high enough to eliminate the need for a second-tier test.