A-384 Development of a sensitive, quantitative C-peptide immunoassay on a dry-printed carbon nanotube electrochemical sensor
TL;DR
The C-peptide immunoassay built on CNT-based electrochemical sensors is capable of highly sensitive and robust quantification of C-peptide from patient urine samples and has the potential to be the core technology of a point-of-care diagnostic, which would improve patient outcomes and reduce health care costs.
Abstract
A key regulator of glucose homeostasis is insulin secretion from pancreatic beta-cells. C-peptide, a byproduct of insulin formation, is produced in equal amounts with insulin, and can be used as a biomarker for beta-cell function. Urinary C-peptide concentration has generated increasing interest as a reliable, non-invasive method for assessing insulin production. Here we present a point-of-care diagnostic concept for simple, reliable, and quantifiable C-peptide detection from urine samples on a carbon nanotube (CNT)-based electrochemical biosensor. This simplified diagnostic workflow would allow for end-user (patient) testing without requiring invasive blood draws, ultimately promoting continuity of care and decreasing health-care costs. We developed an electrochemical immunosensor on CNTs and tested the sensitivity of two immunoassay formats, competitive and sandwich. Urinary C-peptide levels from subjects without diabetes range from 40 to 150 ng/mL, where people living with type 1 diabetes have lower than normal levels and people with type 2 diabetes have higher levels. To ensure identification of clinically relevant low and high C-peptide levels, calibrators spanning 0 to 1000 ng/mL were used to assess the analytical performance. For testing in urine, five pooled urine sample standards were acquired from the BioPersMed Cohort (Medical University of Graz, Austria), and C-peptide was quantified for each pool using the ADVIA Centaur® system (4.6 – 127.6 ng/mL). C-peptide was detected on the CNT biosensor using a TMB-HRP redox reporter system, benchtop potentiostat (PalmSens, EMSTAT4 MUX), and an optimized chronoamperometry method. A custom python-based electrochemical analytical pipeline was developed in parallel to ensure that assay precision, sensitivity, and signal/noise ratios were integrated readouts of overall quantification of C-peptide during the assay development. Amperometric measurement results identified the sandwich assay format to be more robust across the relevant clinical range and more sensitive for clinically low sample concentrations (<40 ng/mL) than the competitive assay. Analytical electrochemical analyses demonstrated numerous valid and reproducible methods for quantifying current signals from chronoamperograms. These methods ranged from simple (e.g., a set window of time was used for all experiments) to complex (steady-current plateau identification based on a sliding-scale identifying the smallest standard deviation within subsequent current recordings). To date, steady-current identification appears to be a robust quantification method with improved signal/noise ratios seen across relevant clinical concentrations. The C-peptide immunoassay built on CNT-based electrochemical sensors is capable of highly sensitive and robust quantification of C-peptide from patient urine samples. Integrating analytical quantification methods into the assay development process allowed for improved assay precision and increased assay throughput. This assay has the potential to be the core technology of a point-of-care diagnostic, which would improve patient outcomes and reduce health care costs.