Picosensor-Optical Microarray Technology for Clinical Diagnosis of Type of Diabetes

Electrochemical sensors offer the unique advantages of simplicity, high sensitivity, low-cost, miniaturization, and scalability to array-based detection formats. We present here an electrochemical insulin-mass sensor coupled to an optical surface plasmon resonance (SPR) microarray imager for detecting insulin-levels in clinical matrices and identify the type of diabetes rapidly (type-1, type-2, or gestational diabetes). Diabetes is emerging as an epidemic condition worldwide, and some of its causes include obesity, autoimmune disorder, and lack of physical activity. The 2011 National Diabetes Fact Sheet released by the American Diabetes Association revealed that nearly 26 million adults and children in the United States had diabetes (8.3 % population), and about 80 million people were estimated to have the pre-diabetic condition (a condition before type-2 diabetes). The World Health Organization (WHO) has reported the occurrence of about 80% of deaths as caused by the diabetes led serious lethal complications such as heart diseases, kidney failure, and acute immune disorders. Hence, it is imperative to diagnose and constantly monitor insulin levels to intake timely medications and lead a normal life.  A glucometer device can measure the levels of glucose in blood and identify a diabetes disorder, but cannot detail the type of diabetes present to aid in the required treatment procedures. Hence, measuring the levels of insulin is important.

The presence of ultra-low levels of insulin (picomolar) in blood demands the need for highly sensitive, reliable, and user-friendly novel analytical sensors to diagnose the type of diabetes, and thus aid doctors in deciding a treatment plan promptly. While absorbance, chemiluminescence, and radio-label based immunoassays for serum insulin detection are currently available, these methods require chemical labels and their tedious conjugation to antibodies along with the specific needs for substrate, reagents, and instruments, to only yield the indirect insulin measurements. Thus, increasing the simplicity of insulin detection by a label-free immunoassay with high sensitivity is very advantageous.

Our group has designed an insulin-sensor based on magnetic nanoparticles conjugation of insulin in serum and blood, and detected the insulin levels using a surface immobilized antibody. We initially constructed the sensor on gold coated quartz crystals to optimize the experimental and assay conditions, and detected the insulin levels based on oscillation frequency and impedance signal changes. We then extended the detection mode to insulin-oxidation signals measured by a square wave voltammetry, which needed a high surface area carbon nanostructured electrodes. Following this, we transferred the sensor approach into a gold-array system to detect insulin levels by an optical-microarray imager.  Our approach is highly sensitive that enabled the detection of clinically relevant pM levels. The analytical figure-of-merit of the described insulin-sensor and microarray system offering multi-independent detection modes will be discussed. We propose that the presented methods are generic to detecting other clinically important biomarkers with the required detection sensitivity.

Acknowledgements. Financial support by Oklahoma State University is greatly acknowledged.