Microelectrode-Based Electrochemical Impedance Determination of Brain-Derived Neurotrophic Factor in Aqueous Humor for Diagnosis of Glaucoma

The abundance of brain-derived neurotrophic factor (BDNF) in aqueous humor (AH) is an ideal biomarker for the diagnosis of glaucoma, a chronic progressive optic neuropathy and the most frequent cause of irreversible blindness. The difficulty of AH-based BDNF detection is from the small amount of extracted AH in a paracentesis (<100 mu L) and the ultra-low abundance of BDNF. In this work, we systematically studied the non-specific adsorption of biofluids on the bare gold electrode by electrochemistry and Raman spectroscopy techniques, revealing the unexpected negative correlation of the extent of non-specific adsorption with the size of the electrode. Based on it, a simple microelectrodebased sensor without the introduction of the blocking layer was developed for the detection of BDNF in the AH sample. Using electrochemical impedance spectroscopy (EIS) and extracting the changes of electron-transfer resistance of the electrochemical probe [Fe(CN)6]3-/4-on the sensor surface, the BDNF was quantified. The dynamic range was from 0.5 to 50 pgmiddotmL-1, with a detection limit of 0.3 pgmiddotmL-1 and a sample consumption of 5 mu L. The real AH sample analysis confirmed the significant decrease of BDNF abundance in the AH of glaucoma patients. Our microelectrode-based EIS sensor displayed prominent advantages on simplified preparation, sensitive response, and low sample consumption. This AH-based BDNF analysis is expected to be used for the screening and diagnosis of glaucoma, especially for the high-risk population who have ocular diseases and have to undergo surgeries.

Automated summary

Through studying the non-specific adsorption of biofluids on a bare gold electrode, a simple microelectrode-based sensor was developed for the detection of brain-derived neurotrophic factor (BDNF) in aqueous humor (AH). The sensor showed advantages of simplified preparation, sensitive response, and low sample consumption.