A New Method for Screening Thalassemia Patients Using Mid Infrared Spectroscopy

: Thalassemia is an inherited hematologic disorder characterized by abnormal or reduced synthesis of hemoglobin chains, leading to ineffective erythropoiesis and anemia. It can be classified into two main genetic types—α-thalassemia and β-thalassemia—depending on whether the α- or β-globin gene is affected. Infrared (IR) Microspectroscopy has emerged as a powerful, label-free analytical tool for biomedical and clinical applications, providing molecular fingerprints that reflect biochemical alterations associated with various disease states. In this study, IR Microspectroscopy was combined with multivariate statistical techniques, including Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA), to characterize and classify thalassemia blood samples into normal, carrier, and disease groups. Blood samples were obtained from patients diagnosed with various types of thalassemia. This technique offers several advantages: it is non-destructive, reagent-free, and highly sensitive, enabling comprehensive analysis of the biochemical composition of biological samples. The classification models developed in this study demonstrated specificity and sensitivity values ranging from 80–90%, indicating strong diagnostic performance. In the future, the integration of advanced machine learning algorithms with IR Microspectroscopy is expected to enhance early diagnosis of thalassemia, facilitate accurate risk stratification, and support more effective strategies for disease prevention and management.