Innovative Blood-Based Biosensor Promises Improved PTSD Diagnosis

Scientists at the University of Tennessee, Knoxville, in collaboration with CFD Research Corporation, have developed a novel blood-based biosensor designed to accurately detect post-traumatic stress disorder (PTSD). This groundbreaking device leverages biomarkers found in blood to diagnose PTSD, a condition that affects approximately 6% of Americans, with even higher prevalence rates among military veterans who have encountered traumatic events such as combat and natural disasters. Traditional diagnosis relies heavily on subjective assessments, which can vary significantly from patient to patient. The new biosensor aims to provide an objective, rapid, and minimally invasive diagnostic tool.

Originally created to help diagnose diseases in livestock, the biosensor employs AC electrokinetics-integrated capacitive (AiCAP) technology. This method applies a specific alternating current signal to guide bioparticles toward sensors capable of detecting microbial and molecular signatures. Researchers Jayne Wu and Shigetoshi Eda adapted this technology to identify multiple biomarkers—proteins, fats, carbohydrates, and DNA sequences—linked to PTSD from just a single blood sample. Unlike conventional methods that require separate detectors for each biomarker, this multiomic approach can simultaneously analyze over a dozen PTSD-related biomarkers.

The collaboration with CFD Research focused on tailoring this technology for human medical applications. The device's ability to quickly analyze diverse biomarkers represents a significant advancement in personalized medicine, aiming to facilitate early diagnosis and intervention. Future plans include obtaining FDA approval, expanding to diagnose other conditions such as cancer, sepsis, and organ damage, and developing a user-friendly interface for use in primary care settings.

This innovative biosensor exemplifies the potential of multiomics in healthcare, promising a future where complex diseases can be diagnosed accurately and efficiently at the point of care, ultimately improving treatment outcomes and patient wellbeing.