(714) Brain Fog in Infection-Associated Chronic Illnesses (IACI): Novel Insights from Neurocognitive and Molecular Profiling of the MAESTRO Clinical Study

Introduction/Rationale: There is a complex interplay between the host immune system and pathogens in Infection-Associated Chronic Illnesses (IACI), including those following Lyme disease and COVID-19, which pose a growing public health concern with limited diagnostic and therapeutic options. Among their most debilitating and least understood symptoms is “brain fog.” Objective measures of neurocognitive dysfunction remain insufficient. The MIT MAESTRO study addresses this gap through a comprehensive, multi-dimensional approach to characterize neurocognitive and physiological changes in IACI.

Methods: The MAESTRO Study profiles individuals with IACI from Lyme and COVID through neurological assessments and commercially available neurocognitive tests, including eye movement tracking, EEG, and cognitive test battery. Additional assessments include autonomic dysfunction, proxy cerebral blood flow, capillaroscopy, hypermobility testing, integrated with extensive surveys and deep biological profiling (urine, sweat, saliva, blood, vaginal, and rectal swabs) for pathogen loads, dysbiosis, genomics, metabolomics, and proteomics, aiming to uncover molecular and neuroimmune signatures underlying these complex conditions.

Results: We found significant neurocognitive differences unique to individuals with IACI. Greater symptom burden correlated with objective outcomes. Reaction times across modalities were consistently slower in IACI participants than controls. Preliminary results suggest that barrier permeability may relate to cognitive dysfunction. Protemotic findings suggest associations between neuroinflammatory features and reaction time, indicating potential physiological links to neurocognitive function.

Conclusion: Using commercially available tools to objectively assess neurocognitive impairments may improve clinical care for individuals with IACI. Integrating neurocognitive, physiological, and molecular data could help identify early changes and enable longitudinal follow up and tracking.