Research Project
10297703
PROJECT SUMMARY Metabolic syndrome is on the rise as the leading cause of morbidity and mortality, affecting more than a third of all U.S. adults. If untreated, patients who develop type 2 diabetes mellitus (T2D) are at high-risk for major adverse cardiovascular events, including stroke, myocardial infarction, and cardiovascular related deaths. Despite chronic screening and monitoring for patient-specific prediction and prevention for cardiometabolic disease, there remains a bottleneck to detect and monitor the metabolic risk factors underlying the rising epidemic of obesity-associated with hyperlipidemia, hypertension, and diabetes. For these reasons, developing wearable molecular sensors, which allow for seamless screening, monitoring, and potentially enables timely intervention, is clinically significant to confront the rising endemic of cardiometabolic disorders. In this project, we propose to continuously monitor a panel of key metabolic biomarkers including glucose, uric acid, branched-chain amino acids (BCAAs: leucine, isoleucine, and valine), and insulin using an integrated Molecular Sensing System (iMSS). We hypothesize that seamless detection of cardiometabolic biomarkers accelerates our capacity to identify metabolic risk factors in our prediabetic patients with obesity for early nutrition intervention to reduce health disparities in the U.S. In addition to integrating with our existing glucose and uric acid sensors, we propose to develop novel laser-engraved wearable sensors for continuous monitoring of BCAAs and insulin based on a novel nanobiosensing approach that combines high-throughput laser-fabricated graphene, molecular imprinting based ?artificial antibody?, and in situ sensor regeneration technique. This approach will enable large-scale, low-cost fabrication of highly sensitive and selective sensors for continuous monitoring of clinical meaningful cardiometabolic analytes in human sweat at ultralow concentrations (such as BCAAs). The use of laser-induced microfluidics and numerical simulation-guided design optimization enables efficient fluid sampling with minimized effects from the sensing delay and fluid evaporation. Harnessing the power of concurrent multiplexed cardiometabolic sensing, adjusted electrochemical measurements based on pH, electrolytes, temperature, and sweat rate calibration minimize the systematic uncertainties persisted in the current generation of wearable sensing systems. We will validate the correlation of the sweat/blood biomarkers in healthy subjects using the iMSS and deploy these epidermal sensors to the high-risk patients. We envision that the iMSS system will provide an entry point to identify pre- diabetes and obesity at risk for conversion to T2D, and will have translational significance to mitigate clinical manifestation of major adverse cardiovascular events.
