Kynurenic Acid Electrochemical Immunosensor: Blood-Based Diagnosis of Alzheimer's Disease

Abstract

Alzheimer's disease (AD) is a neurodegenerative disorder, characterized by a functional deterioration of the brain. Currently, there are selected biomarkers for its diagnosis in cerebrospinal fluid. However, its extraction has several disadvantages for the patient. Therefore, there is an urgent need for a detection method using sensitive and selective blood-based biomarkers. Kynurenic acid (KYNA) is a potential biomarker candidate for this purpose. The alteration of the KYNA levels in blood has been related with inflammatory processes in the brain, produced as a protective function when neurons are damaged. This paper describes a novel electrochemical immunosensor for KYNA detection, based on successive functionalization multi-electrode array. The resultant sensor was characterized by cyclic voltammetry (CV), chronoamperometry (CA), and electrochemical impedance spectroscopy (EIS). The proposed biosensor detects KYNA within a linear calibration range from 10 pM to 100 nM using CA and EIS, obtaining a limit of detection (LOD) of 16.9 pM and 37.6 pM in buffer, respectively, being the lowest reported LOD for this biomarker. Moreover, to assess our device closer to the real application, the developed immunosensor was also tested under human serum matrix, obtaining an LOD of 391.71 pM for CA and 278.8 pM for EIS with diluted serum.

Keywords: Alzheimer’s disease (AD); blood analysis; chronoamperometry (CA); electrochemical biosensor; electrochemical impedance spectroscopy (EIS); immunosensor; in vitro diagnosis (IVD); kynurenic acid (KYNA); point of care diagnosis (PoC).

Figure 1

Schematic representation of the electrochemical impedance spectroscopy (EIS) electrochemical characterization of the functionalized sensor. (A) Nyquist plot for each respective immobilization (blue: bare Au, red: SAM, purple: BSA-pseudo-KYNA, black: KYNA-Ab, fuchsia: secondary-Ab).

Figure 2

Chronoamperometry (CA) and EIS characterization of the optimization of the biosensor’s different layers. (A,B) BSA-pseudo-KYNA concentration optimization for sensor functionalization, characterized by CA and EIS, respectively; (C) KYNA-Ab concentration optimization using EIS in the characterization; (D) secondary-Ab concentration optimization characterized with CA.

Figure 3

KYNA immunosensor selectivity test characterized with CA. A scheme of the results represents the possible molecules on the sensor surface and washed out after incubation.

Figure 4

KYNA immunosensor sensitivity test in buffer. The calibration curves were performed with CA (A) and EIS (B). The concentrations considered were 0, 10 pM, 100 pM 1 nM, 10 nM, 100 nM, and 1000 nM (n = 5).

Figure 5

KYNA immunosensor sensitivity test. (A,B) Calibration curves in undiluted human serum, using CA and EIS, respectively, and (C,D) calibration curves in 1/10 diluted human serum in phosphate-buffered saline (PBS), using CA and EIS, respectively. The concentrations considered were 0, 10 pM, 100 pM 1 nM, 10 nM, 100 nM, and 1000 nM (n = 5).