A rapid quantification method for the screening indicator for β-thalassemia with near-infrared spectroscopy

Near-infrared (NIR) spectroscopy combined with chemometrics was applied to rapidly analyse haemoglobin A2 (HbA₂) for β-thalassemia screening in human haemolysate samples. The relative content indicator HbA₂ was indirectly quantified by simultaneous analysis of two absolute content indicators (Hb and Hb∙HbA₂). According to the comprehensive prediction effect of the multiple partitioning of calibration and prediction sets, the parameters were optimized to achieve modelling stability, and the preferred models were validated using the samples not involved in modelling. Savitzky-Golay smoothing was firstly used for the spectral pretreatment. The absorbance optimization partial least squares (AO-PLS) was used to eliminate high-absorption wave-bands appropriately. The equidistant combination PLS (EC-PLS) was further used to optimize wavelength models. The selected optimal models were I=856nm, N=16, G=1 and F=6 for Hb and I=988nm, N=12, G=2 and F=5 for Hb∙HbA₂. Through independent validation, the root-mean-square errors and correlation coefficients for prediction (RMSEP, R_P) were 3.50gL^-1 and 0.977 for Hb and 0.38gL^-1 and 0.917 for Hb∙HbA₂, respectively. The predicted values of relative percentage HbA₂ were further calculated, and the calculated RMSEP and R_P were 0.31% and 0.965, respectively. The sensitivity and specificity for β-thalassemia both reached 100%. Therefore, the prediction of HbA₂ achieved high accuracy for distinguishing β-thalassemia. The local optimal models for single parameter and the optimal equivalent model sets were proposed, providing more models to match possible constraints in practical applications. The NIR analysis method for the screening indicator of β-thalassemia was successfully established. The proposed method was rapid, simple and promising for thalassemia screening in a large population.