Diabetes is an emerging 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 pre-diabetes (a condition before type-2 diabetes). Challengingly, the presence of ultra-low levels of insulin in blood serum (on the order of pM) even under healthy conditions demands the need for highly sensitive assay methods to measure serum or blood insulin and diagnose the presence of type of diabetes. The commercial glucometers can only infer the levels of glucose in blood and presence of a diabetes condition, but cannot identify the type of diabetes and the associated obesity, heart/immune diseases, for which the detection of insulin levels is necessary. S sensitivity, simplicity of detection protocol and ability to detect insulin present in a complex clinical matrix are crucial. The commercial serum insulin immunoassays based on absorbance, fluorescence, chemiluminescence, and radiometric detection methods require special, chemically labeled detection antibodies, which involve difficult time consuming preparations and separation procedures, along with the need for expensive materials and special instruments. These properties add to the high-cost of such assay kits. Thus, there exists a critical need to provide the diabetes clinical centers with sensor that are robust in operation, highly sensitive, simple-to- use, and involve label-free detection of serum and blood insulin levels. To accomplish this, the PI's objective in this R15 application is t develop a novel sensor that can selectively measure clinically relevant pM serum and blood insulin levels with high specificity based on signal changes in frequency, impedance, and insulin- oxidation currents in a single assay, and additionally enable the coupling to an optical microarray imager based detection for the first time. The proposed label-free sensor research is innovative because it involves the direct measurements of insulin in both the serum and whole blood with multi-detection features, offering unprecedented precision and accuracy. In the absence of such advanced insulin sensors, the specific identification of the type of diabetes and the associated management plan will likely remain problematic. By c completing the proposed plan of work and the proposed outreach activities of the PI on research exposure to Native American students in Oklahoma, it is expected that this application will strengthen the research environment of Oklahoma State University, create an independent health-related research career for the PI, and deliver an innovative, simple, reliable, and highly sensitive insulin-sensor to significantly improve the present diagnostic procedures in identifying the diabetes-type in clinical samples.

Public Health Relevance

The proposed research is relevant to the mission of the National Institute of Health, because it is expected to deliver an innovative multimode insulin-sensor coupled with an optical microarray imager for reliable clinical diagnosis of the type of diabetes in serum and whole blood.

National Institute of Health (NIH)
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Academic Research Enhancement Awards (AREA) (R15)
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Special Emphasis Panel (ZRG1-BST-F (80))
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Arreaza-Rubin, Guillermo
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Oklahoma State University Stillwater
Schools of Arts and Sciences
United States
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Singh, Vini; Krishnan, Sadagopan (2018) Electrochemical and surface plasmon insulin assays on clinical samples. Analyst 143:1544-1555
Premaratne, Gayan; Farias, Sabrina; Krishnan, Sadagopan (2017) Pyrenyl carbon nanostructures for ultrasensitive measurements of formaldehyde in urine. Anal Chim Acta 970:23-29
Premaratne, Gayan; Coats, Leslie; Krishnan, Sadagopan (2017) NanoArmoring of Enzymes by Polymer-Functionalized Iron Oxide Nanoparticles. Methods Enzymol 590:225-257
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Singh, Vini; Rodenbaugh, Cassandra; Krishnan, Sadagopan (2016) Magnetic Optical Microarray Imager for Diagnosing Type of Diabetes in Clinical Blood Serum Samples. ACS Sens 1:437-443
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Nerimetla, Rajasekhara; Krishnan, Sadagopan (2015) Electrocatalysis by subcellular liver fractions bound to carbon nanostructures for stereoselective green drug metabolite synthesis. Chem Commun (Camb) 51:11681-4

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