Surface-enhanced Raman spectroscopy of centrifuged blood serum samples of diabetic type II patients by using 50KDa filter devices

Spectrochim Acta A Mol Biomol Spectrosc. 2023 May 15:293:122457. doi: 10.1016/j.saa.2023.122457. Epub 2023 Feb 6.

Abstract

Blood serum contains essential biochemical information which are used for early disease diagnosis. Blood serum consisted of higher molecular weight fractions (HMWF) and lower molecular weight fractions (LMWF). The disease biomarkers are lower molecular weight fraction proteins, and their contribution to disease diagnosis is suppressed due to higher molecular weight fraction proteins. To diagnose diabetes in early stages are difficult because of the presence of huge amount of these HMWF. In the current study, surface-enhanced Raman spectroscopy (SERS) are employed to diagnose diabetes after centrifugation of serum samples using Amicon ultra filter devices of 50 kDa which produced two fractions of whole blood serum of filtrate, low molecular weight fraction, and residue, high molecular weight fraction. Furthermore SERS is employed to study the LMW fractions of healthy and diseased samples. Some prominent SERS bands are observed at 725 cm-1, 842 cm-1, 1025 cm-1, 959 cm-1, and 1447 cm-1 due to small molecular weight proteins, and these biomarkers helped to diagnose the disease early stage. Moreover, chemometric techniques such as principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) are employed to check the potential of surface-enhanced Raman spectroscopy for the differentiation and classifications of the blood serum samples. SERS can be employed for the early diagnosis and screening of biochemical changes during type II diabetes.

Keywords: Centrifugal filtration; Filtrate portions of blood serum samples; Multivariate data analysis; Type II diabetes; surface-enhanced Raman spectroscopy.

MeSH terms

  • Biomarkers
  • Diabetes Mellitus, Type 2*
  • Discriminant Analysis
  • Humans
  • Principal Component Analysis
  • Serum*
  • Spectrum Analysis, Raman / methods

Substances

  • Biomarkers