Serological testing for Hansen’s disease diagnosis: Clinical significance and performance of IgA, IgM, and IgG antibodies against Mce1A protein

Hansen’s disease (HD) is an infectious, treatable, and chronic disease. It is the main cause of infectious peripheral neuropathy. Due to the current limitations of laboratory tests for the diagnosis of HD, early identification of infected contacts is an important factor that would allow us to control the magnitude of this disease in terms of world public health. Thus, a cross-sectional study was conducted in the Brazilian southeast with the objective of evaluating humoral immunity and describing the accuracy of the immunoassay based on IgA, IgM, and IgG antibodies against surface protein Mce1A of Mycobacterium, the predictive potential of these molecules, the clinical significance of positivity, and the ability to segregate new HD cases (NC; n = 200), contacts (HHC; n = 105), and healthy endemic controls (HEC; n = 100) as compared to α-PGL-I serology. α-Mce1A levels for all tested antibodies were significantly higher in NC and HHC than in HEC (p < 0.0001). The performance of the assay using IgA and IgM antibodies was rated as highly accurate (AUC > 0.85) for screening HD patients. Among HD patients (NC), positivity was 77.5% for IgA α-Mce1A ELISA, 76.5% for IgM, and 61.5% for IgG, while α-PGL-I serology showed only 28.0% positivity. Multivariate PLS-DA showed two defined clusters for the HEC and NC groups [accuracy = 0.95 (SD = 0.008)] and the HEC and HHC groups [accuracy = 0.93 (SD = 0.011)]. IgA was the antibody most responsible for clustering HHC as compared to NC and HEC, evidencing its usefulness for host mucosal immunity and as an immunological marker in laboratory tests. IgM is the key antibody for the clustering of NC patients. Positive results with high antibody levels indicate priority for screening, new clinical and laboratory evaluations, and monitoring of contacts, mainly with antibody indexes ≥2.0. In light of recent developments, the incorporation of new diagnostic technologies permits to eliminate the main gaps in the laboratory diagnosis of HD, with the implementation of tools of greater sensitivity and accuracy while maintaining satisfactory specificity.