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Serum anti-phenolic glycolipid-1 IgA correlates to IgM isotype in leprosy patients: a possible candidate for seroepidemiological surveys?
Journal of Clinical Laboratory Analysis 2018 March
OBJECTIVE: The aim of this study was to compare serum anti-phenolic glycolipid-1 IgA, IgG, and IgM levels in leprosy patients and controls.
METHOD: Analysis of anti-PGL-1 IgA, IgG, or IgM in serum samples from multibacillary (MB, n=32) and paucibacillary (PB, n=22) leprosy patients, and in non-endemic controls (n=17), using an indirect enzyme-linked immunosorbent assay.
RESULTS: A strong correlation between serum IgM and IgA isotypes was found (r=.745, P<.0001) in MB patients. A moderate correlation was found in all analyses in PB patients. A moderate agreement was found between anti-PGL1 IgA and IgM tests. Based on the ROC curves, the cut-off values were selected and the parameters of validation were calculated. Considering the clinical forms altogether, the diagnostic sensitivities were 50.0% for IgA, 22.2% for IgG, and 74.1% for IgM. The positive (VPP) and negative (VPN) predictive values were estimated for each isotype. For IgA, the VPP and VPN were, respectively, 100.0% (87.0%-100.0%; 95% confidence interval) and 38.7% (24.4%-54.5%); for IgG, 100% (87.0%-100.0%) and 28.8% (17.8%-42.1%), respectively; and for IgM, 95.2% (83.8%-99.4%) and 51.7% (32.5%-70.6%), respectively.
CONCLUSION: Despite the limiting factors, anti-PGL1 IgA correlates to IgM levels and it could be considered as a possible laboratorial tool to be also used, for instance, in serological follow-up studies.
METHOD: Analysis of anti-PGL-1 IgA, IgG, or IgM in serum samples from multibacillary (MB, n=32) and paucibacillary (PB, n=22) leprosy patients, and in non-endemic controls (n=17), using an indirect enzyme-linked immunosorbent assay.
RESULTS: A strong correlation between serum IgM and IgA isotypes was found (r=.745, P<.0001) in MB patients. A moderate correlation was found in all analyses in PB patients. A moderate agreement was found between anti-PGL1 IgA and IgM tests. Based on the ROC curves, the cut-off values were selected and the parameters of validation were calculated. Considering the clinical forms altogether, the diagnostic sensitivities were 50.0% for IgA, 22.2% for IgG, and 74.1% for IgM. The positive (VPP) and negative (VPN) predictive values were estimated for each isotype. For IgA, the VPP and VPN were, respectively, 100.0% (87.0%-100.0%; 95% confidence interval) and 38.7% (24.4%-54.5%); for IgG, 100% (87.0%-100.0%) and 28.8% (17.8%-42.1%), respectively; and for IgM, 95.2% (83.8%-99.4%) and 51.7% (32.5%-70.6%), respectively.
CONCLUSION: Despite the limiting factors, anti-PGL1 IgA correlates to IgM levels and it could be considered as a possible laboratorial tool to be also used, for instance, in serological follow-up studies.
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