Biochemical Profiling of Iron Deficiency Anemia by Using SERS and Multivariate Analysis of Low Molecular Weight Fractions of Serum

Iron deficiency anemia (IDA) is a widespread, nutritional disorder characterized by reduced hemoglobin level and diminished oxygen supply to the body tissues. Disease detection at early stage is of paramount importance for preventing its progression. The major aim of this study is to analyze the fractionated low molecular weight fractions (LMWF), also known as disease-specific biomarkers. In this study, surface-enhanced Raman spectroscopy (SERS) has been performed on the 30-kDa filtrate portions of blood serum samples of IDA and control individuals for detecting the biochemical changes caused by IDA. For the effective investigation of biological changes associated with IDA, LMWF of serum samples were fractionated using an Amicon Ultra 2-ml centrifugal devices having cut-off points of 30 kDa. Multivariate statistical analysis tools like principal component analysis (PCA) and partial least squares regression analysis (PLSR) were employed for qualitative and quantitative analysis of SERS data sets of control and IDA patients. The characteristic SERS bands observed at 565, 647, 930, 959, 1407, 1540, and 1589 cm⁻¹ served as biomarkers for distinguishing the spectral data of IDA from the control/healthy samples. PLSR accurately predicts the concentration of unknown hemoglobin (Hb) levels from spectral data sets with values of root mean square error of calibration (RMSEC) as 0.69025 g/dL and root mean square error of prediction (RMSEP) as 0.789 g/dL, respectively. This explains the good fit of the model with coefficient of determination value of R² 0.93 g/dL.