Quantifying glucose and lipid components in human serum by Raman spectroscopy and multivariate statistics.

Abstract

Raman spectroscopy has been employed in the quantitative analysis of biochemical components in human serum. This study aimed to develop a spectral model to estimate the concentration of glucose and lipid fractions in human serum, thus evaluating the feasibility of Raman spectroscopy technique for diagnostic purposes. A total of 44 samples of blood serum were collected from volunteers submitted to routine blood biochemical assay analysis. The biochemical concentrations of glucose, triglycerides, cholesterol, and high-density and low-density lipoproteins (HDL and LDL) were obtained by colorimetric method. Serum samples (200μL) were submitted to Raman spectroscopy (830nm, 250mW, 50-s accumulation). The spectra of sera present peaks related to the main constituents, particularly proteins and lipids. A quantitative model based on partial least squares (PLS) regression has been developed to estimate the concentration of these compounds, taking the biochemical concentrations assayed by the colorimetric method as sample's actual concentrations. The PLS model based on leave-one-out cross-validation approach estimated the concentration of triglycerides and cholesterol with r = 0.98 and 0.96, and root mean square error of 35.4 and 15.9mg/dL, respectively. For the other biochemicals, the r was ranging from 0.75 to 0.86. These results evidenced the possibility of performing biochemical assay in blood serum samples by Raman spectroscopy and PLS regression and may be employed as a means of diagnosis in routine clinical analysis.