Urinary Extracellular Vesicle Profiling to Identify Borrelia-Associated Neuroimmune Subtypes in Long COVID

Project Summary

This project uses urinary extracellular vesicles (uEVs) as a noninvasive platform to detect microbial and host-derived signals in Long COVID, with a focus on identifying a distinct subgroup of patients influenced by Borrelia infection and neuroimmune dysfunction. uEVs carry pathogen antigens and tissue-specific injury markers, enabling simultaneous measurement of infection-associated signals and organ-level biology from a simple urine sample.

To operationalize this approach, the team will combine optimized uEV isolation workflows with mass spectrometry proteomics and targeted immunoassays to detect Borrelia-associated antigens alongside markers of neural injury, autonomic dysfunction, mast cell activation, and multi-organ stress. By integrating microbial detection with host response profiling, the project aims to define biomarker signatures that stratify Long COVID patients into biologically meaningful subgroups and inform future precision diagnostics and clinical trials.

Project Background

A subset of Long COVID patients exhibit symptoms consistent with peripheral neuroimmune and autonomic dysfunction, including neuropathic pain, fatigue, and dysautonomia—features that overlap with symptoms driven by tick-borne/vectorborne pathogens such as Borrelia, the causative agent of Lyme disease.. This raises the possibility that prior Borrelia exposure or persistent antigenic debris may contribute to disease biology in a subset of patients, particularly in endemic regions. However, current approaches lack scalable, noninvasive tools to detect these signals and link them to clinical phenotypes.

This project builds on evidence that Borrelia-derived proteins can be detected in urinary EVs and correlate with symptom severity, and that uEVs also capture organ-specific injury signals from systems including the nervous system, lung, heart, liver, and gut. By applying both unbiased proteomics and targeted biomarker panels, the team will map how microbial antigens co-segregate with neuroimmune and tissue injury markers, establishing biomarker-informed patient stratification. This framework creates a scalable path toward diagnosing infection-associated subtypes of Long COVID and guiding targeted evaluation and intervention strategies.