Innovative screening test for the early detection of sickle cell anemia

In this study, the capability of thermogravimetry in conjuction with a multivariate statistical analysis, was investigated for the screening of Sickle Cell Anemia (SCA), a hereditary disorder of hemoglobin characterized by severe hemolytic anemia with different severe clinical manifestations. SCA results from a mutation in the sixth codon of the beta globin gene, which results in the substitution of glutamic acid for valine and leads to the production of an altered form of hemoglobin, hemoglobin S (HbS). People with this disorder have atypical hemoglobin molecules which tend to aggregate together and form filaments inside the red blood cells. These deformed red blood cells called half-moon or sickle, are rigid and unable to flow inside the small vessels, creating occlusions of the small circulation. Systematic screening for SCA is not a common practice, and diagnosis is usually made when a severe complication occurs. An early and rapid diagnosis is important for patients in order to prevent and treat the painful episodes that can occur when sickled red blood cells, which are stiff and inflexible, get stuck in small blood vessels. A novel test was developed using whole blood samples from patients with congenital defects and analyzed by the TG7 thermobalance (PerkinElmer) without any pretreatment. The resulting TG and DTG curves of blood samples were compared to those typical of healthy individuals and results demonstrated a different thermal behaviour of the anemic patients with respect to healthy individuals as result of the different amounts of water content and corpuscular fraction. The multivariate statistical analysis performed by chemometrics allowed a quick identification of differences between the two population and provided a model of prediction in patients with heterogeneous congenital hematological disorders. The predictive ability of the model was tested by processing patient affected by SCA and with a confirmed diagnosis obtained by the molecular analysis. The model provided for a sensitivity and an accuracy of a 100% and an error of prediction of about 0.1%.