Label‐free spectrochemical probe for determination of hemoglobin glycation in clinical blood samples. Issue 10 (19th June 2018)

• Record Type: Journal Article
• Authors: Pandey, Rishikesh; Singh, Surya P.; Zhang, Chi; Horowitz, Gary L.; Lue, Niyom; Galindo, Luis; Dasari, Ramachandra R.; Barman, Ishan
• Is Part Of: Journal of biophotonics. Volume 11:Issue 10(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-06-19
• Subjects: diabetes -- glycated hemoglobin -- HbA1c -- label‐free -- Raman spectroscopy; Photonics -- Periodicals; Optical materials -- Periodicals; Optics -- Periodicals; Medical instruments and apparatus -- Periodicals; 621.3605
• DOI: 10.1002/jbio.201700397
• Languages: English
• ISSNs: 1864-063X

Abstract

Abstract : Glycated hemoglobin, HbA1c, is an important biomarker that reveals the average value of blood glucose over the preceding 3 months. While significant recent attention has been focused on the use of optical and direct molecular spectroscopic methods for determination of HbA1c, a facile test that minimizes sample preparation needs and turnaround time still remains elusive. Here, we report a label‐free approach for identifying low, mid and high‐HbA1c groups in hemolysate and in whole blood samples featuring resonance Raman (RR) spectroscopy and support vector machine (SVM)‐based classification of spectral patterns. The diagnostic power of RR measurements stems from its selective enhancement of hemoglobin‐specific features, which simultaneously minimizes the blood matrix spectral interference and permits detection in the native solution. In this pilot study, our spectroscopic observations reveal that glycation of hemoglobin results in subtle but reproducible changes even when detected in the whole blood matrix. Leveraging SVM analysis of the principal component scores determined from the RR spectra, we show high degree of accuracy in classifying clinical specimen. We envisage that the promising findings will pave the way for more extensive clinical specimen investigations with the ultimate goal of translating molecular spectroscopy for routine point‐of‐care testing. Abstract : In this article, we report a label‐free approach for determining HbA1c in hemolysate and in whole blood samples featuring resonance Raman spectroscopy and support vector machine. Our spectroscopic observations reveal that glycation of hemoglobin results in subtle but reproducible changes. The results show high degree of accuracy in classifying low, mid and high‐HbA1c groups in clinical blood samples.