A NEW multiplex protein microarray has shown promise in accurately detecting a wide range of tick-borne infections in a single test run, offering clinicians a valuable tool for faster and more reliable diagnosis.
In this evaluation study, researchers designed a microarray capable of holding up to 400 antigens, including whole cell lysates, recombinant proteins, and peptides from multiple infectious agents. The array was specifically built to detect both IgM and IgG antibodies against various microbes, including Borrelia burgdorferi, the causative agent of Lyme disease. Comparative performance analysis was conducted against existing gold standard diagnostic methods, assessing both analytical and clinical performance. The goal was to demonstrate improved sensitivity and specificity for detecting exposure to multiple tick-borne pathogens simultaneously, addressing a major limitation in current diagnostic testing.
The results showed that the new multiplex assay improved both IgM and IgG sensitivity and specificity across several microbes when compared to conventional single-pathogen tests. Unlike standard testing procedures that often require multiple individual assays for different pathogens, the new platform achieved broad-spectrum detection in a single run. This not only enhanced diagnostic efficiency but also helped avoid misdiagnosis caused by overlapping symptoms of tick-borne illnesses. The ability to detect exposure to numerous infectious agents in parallel represents a significant step forward, particularly for non-Lyme infections that are often underreported due to diagnostic challenges.
This study highlights the clinical potential of a flexible, high-throughput diagnostic platform that improves accuracy while reducing turnaround time. Broader adoption of such multiplex tools could substantially aid early diagnosis and reporting of tick-borne infections.
Reference
Krishnamurthy HK et al. A customizable multiplex protein microarray for antibody testing and its application for tick-borne and other infectious diseases. Sci Rep. 2025;15(1):2527.
