Selective detection of HbA1c using surface enhanced resonance Raman spectroscopy

Area of Science:

• Biochemistry
• Analytical Chemistry
• Spectroscopy

Background:

• Glycemic control monitoring is crucial for diabetic patient management.
• Hemoglobin A1c (HbA1c) is a primary biomarker for long-term glycemic control.
• Accurate and selective HbA1c detection methods are essential.

Purpose of the Study:

• To develop a selective detection method for HbA1c using surface-enhanced resonance Raman spectroscopy (SERRS).
• To investigate the spectral differences between HbA1c and hemoglobin A (HbA).
• To explore the potential of SERRS and silver nanoparticles (Ag NPs) for HbA1c separation and detection.

Main Methods:

• Utilized surface-enhanced resonance Raman spectroscopy (SERRS) for spectral analysis.
• Investigated SERRS spectra of HbA1c and hemoglobin A (HbA).
• Examined the effect of HbA and HbA1c on the aggregation of silver nanoparticles (Ag NPs) in colloidal solution.
• Employed electrophoresis for separation characterization.

Main Results:

• Identified a characteristic SERRS band (770-830 cm(-1)) specific to HbA1c, absent in HbA.
• Demonstrated that SERRS spectral features of HbA1c are similar to nonenzymatically glycosylated HbA.
• Observed differential aggregation of Ag NPs: significant aggregation with HbA, minimal aggregation with HbA1c.
• Successfully separated HbA and HbA1c mixtures using Ag NPs and SERRS analysis.

Conclusions:

• SERRS provides a selective method for HbA1c detection based on unique spectral signatures.
• The differential interaction of HbA and HbA1c with Ag NPs, likely due to hydrophilicity differences, facilitates their separation.
• The combination of Ag NPs and SERRS presents a promising approach for the selective detection and separation of HbA1c.