Pixel array-based urine biosensor for detection of trimethylamine N-oxide and glucose for early detection of diabetic kidney disease

Abstract

Trimethylamine N-oxide (TMAO) serves as a crucial biomarker for early detection and prevention of cardiovascular and chronic kidney diseases. In this study, we design and implement a novel pixel array-based urine biosensor to explore the relationship between TMAO levels and glucose in urine and the urine albumin-creatinine ratio (UACR). The urine biosensor, incorporating a specialized readout circuit, measures TMAO across various UACR ranges, revealing a linear correlation with a slope of 8.5 mV per mg/g up to 1100 mg/g UACR. Although glucose levels also rise with UACR, significant discrepancies occur beyond 30 mg/g, indicating that glucose does not consistently correlate with UACR increases. The biosensor demonstrates a sensitivity of 41 ADC counts/μM (4.5 mV/μM), a 10-s response time, 98 % reproducibility, and a drift of 0.3 mV over extended periods. It requires only 5 μL of urine for a comprehensive analysis of TMAO and glucose. This approach significantly improves time efficiency, offering a faster and more convenient solution for monitoring the risk for chronic kidney disease, such as those with diabetes.