Evaluation of Immunodiagnostic Tests for Leprosy in Brazil, China and Ethiopia.
Anouk van HooijElisa M Tjon Kon FatMoises Batista da SilvaRaquel Carvalho BouthAna Caroline Cunha MessiasAngélica Rita GobboTsehaynesh LemaKidist BoboshaJinlan LiXiaoman WengClaudio G SalgadoJohn S SpencerPaul Leo Albert Maria CorstjensAnnemieke GelukPublished in: Scientific reports (2018)
Leprosy remains persistently endemic in several low- or middle income countries. Transmission is still ongoing as indicated by the unabated rate of leprosy new case detection, illustrating the insufficiency of current prevention methods. Therefore, low-complexity tools suitable for large scale screening efforts to specifically detect M. leprae infection and diagnose disease are required. Previously, we showed that combined detection of cellular and humoral markers, using field-friendly lateral flow assays (LFAs), increased diagnostic potential for detecting leprosy in Bangladesh compared to antibody serology alone. In the current study we assessed the diagnostic performance of similar LFAs in three other geographical settings in Asia, Africa and South-America with different leprosy endemicity. Levels of anti-PGL-I IgM antibody (humoral immunity), IP-10, CCL4 and CRP (cellular immunity) were measured in blood collected from leprosy patients, household contacts and healthy controls from each area. Combined detection of these biomarkers significantly improved the diagnostic potential, particularly for paucibacillary leprosy in all three regions, in line with data obtained in Bangladesh. These data hold promise for the use of low-complexity, multibiomarker LFAs as universal tools for more accurate detection of M. leprae infection and different phenotypes of clinical leprosy.
Keyphrases
- immune response
- loop mediated isothermal amplification
- real time pcr
- end stage renal disease
- label free
- big data
- chronic kidney disease
- electronic health record
- ejection fraction
- newly diagnosed
- risk assessment
- high throughput
- prognostic factors
- human health
- artificial intelligence
- climate change
- quality improvement
- deep learning
- quantum dots
- single cell
- data analysis