Type 2 diabetes detection based on serum sample Raman spectroscopy.

In this work, we propose to the Raman spectroscopy as a new technique for the detection of the type 2 diabetes using blood serum samples. The serum samples were obtained from 15 patients who were clinically diagnosed with type 2 diabetes mellitus and 20 healthy volunteers. The average spectra showed equally intense peaks as, 695 cm-1, the doublet of tyrosine at 828 and 853 cm-1, phenylalanine at 1002 and 1028 cm-1, the phospholipid shoulder at 1300-1345 cm-1, and proteins (amide I) at 1654 cm-1. The major differences were found at 661 and 1404 cm-1 (glutathione), 714 (polysaccharides), 605 (Phe), 545 cm-1 (tryptophan), and the shoulder of amide III at 1230-1282 cm-1, where seem to disappear in the diabetes spectrum. On the contrary, the region that is more highlighted due to that diabetes peaks are clearly more intense was 897-955 cm-1. Principal component analysis and linear discriminate analysis were employed for developing discrimination method. The first three principal components provided a classification of the samples from healthy and diabetes patients with high sensitivity and specificity. In addition, when the first principal component was plotted as a function of the Raman shift, it revealed these shifts accounted for the greatest differences between control and diabetes samples, which coincided with the shifts of spectral differences shown by mean spectra. Our results demonstrated that serum sample Raman spectroscopy promises to become a non-invasive support tool of the currently applied techniques for type 2 diabetes detection, decreasing the false-positive cases.