Prediction of the Occurrence of Leprosy Reactions Based on Bayesian Networks

Background: Leprosy reactions (LR) are severe episodes of intense activation of the host inflammatory response, of uncertain etiology, today the leading cause of permanent nerve damage in leprosy patients. Several genetic and non-genetic risk factors for LR have been described; however, there are limited attempts to combine this information in order to estimate the risk of a leprosy patient to develop LR. Here we present an artificial intelligence (AI)-based system able to estimate risk of LR using clinical, demographic and genetic data.Methods: The study includes four datasets from different regions of Brazil, totalizing 1,450 leprosy patients followed prospectively for at least two years to assess the occurrence of LR. Data mining using WEKA software was performed following a two-step protocol to select the variables included in the AI system, based on Bayesian Networks and developed using the NETICA software.Results: Analysis of the complete database resulted in a system able to estimate LR-risk with 82.7% accuracy, 79.3% sensitivity, and 86.2% specificity. When using only databases for which host genetic information associated with LR was included, the performance increased to up to 87.7% accuracy, 85.7% sensitivity, and 89.4% specificity.Conclusion: We produced an easy-to-use, online, free-access system that allows the identification of leprosy patients at high risk of developing LR. Risk assessment of LR for individual patients may detect candidates close monitoring, with potential positive impact upon the prevention of permanent disabilities, the quality of life of the patients, as well as upon leprosy control programs.

The Demography, Clinical Characteristics, and White Blood Analysis of Leprosy Reactions in Multibacillary Leprosy: A Retrospective Study

Background: Leprosy is a neglected tropical disease caused by chronic granulomatous infection of Mycobacterium leprae. Indonesia ranks third in new case findings, with 84% of the case being multibacillary (MB) leprosy. MB leprosy cases have a higher risk of leprosy reactions and physical disabilities that decrease quality of life. Purpose: To determine the demographic, clinical characteristics, and white blood analysis of newly diagnosed MB leprosy patients, especially concerning leprosy reactions. Methods: This is a descriptive retrospective study with a cross-sectional design that describe the following data: domicile, gender, age, treatment status, disabilities, body mass index (BMI); bacterial index (BI), morphological index (MI), white blood cell (WBC) and differential counts, and thrombocyte count. Result: This study included 176 adult MB cases, predominantly male aged 20–39 years old with average BMI, lived in Surabaya with negative history of multi-drug therapy, disability, BI, nor MI. The grade 2 disability (G2D) percentage in this study setting than in Indonesia (10.7% vs. 6.43%). The WBCs, especially neutrophil count, was higher in T2R group. Monocyte and lymphocyte counts were relatively similar. There was an increase in thrombocyte count in leprosy reaction groups. Conclusion: MB leprosy in the endemic area, which is more commonly found in productive-aged male, displayed higher G2D than global Indonesia population. Thus denotes the importance of active case findings. The difference in blood analysis characteristics between MB leprosy with and without reactions may serve as the foundation for future study.

Host-Related Laboratory Parameters for Leprosy Reactions

Leprosy reactions are acute inflammatory episodes that complicate the course of a Mycobacterium leprae infection and are the major cause of leprosy-associated pathology. Two types of leprosy reactions with relatively distinct pathogenesis and clinical features can occur: type 1 reaction, also known as reversal reaction, and type 2 reaction, also known as erythema nodosum leprosum. These acute nerve-destructive immune exacerbations often cause irreversible disabilities and deformities, especially when diagnosis is delayed. However, there is no diagnostic test to detect or predict leprosy reactions before the onset of clinical symptoms. Identification of biomarkers for leprosy reactions, which impede the development of symptoms or correlate with early-onset, will allow precise diagnosis and timely interventions to greatly improve the patients' quality of life. Here, we review the progress of research aimed at identifying biomarkers for leprosy reactions, including its correlation with not only immunity but also genetics, transcripts, and metabolites, providing an understanding of the immune dysfunction and inflammation that underly the pathogenesis of leprosy reactions. Nevertheless, no biomarkers that can reliably predict the subsequent occurrence of leprosy reactions from non-reactional patients and distinguish type I reaction from type II have yet been found.

Elevated IL-6R on CD4+ T cells promotes IL-6 driven Th17 cell responses in patients with T1R leprosy reactions

Th17 cells play vital role during pathogenesis of leprosy reactions. Previously, we have reported that IL-23 is involved in Th17 cells differentiation. Subsequently, our group also showed that IL-6 induces Th17 cell differentiation along with TGF-β in leprosy reactions. Here, we next asked the question that whether IL-6 or IL-23 induced Th17 cells are different in nature? In this study, Type 1 Reactions (T1R) showed significantly (p < 0.001) higher percentage of IL-17A producing CD4+IL6R+ T cells as compared to non-reaction (NR) patients. Furthermore, recombinant IL-6, IL-23 and TGF-β promoted IL-17A secretion by CD4+IL6R+ T cells. Subsequently, IL-6R and IL-23R blocking experiments showed significantly (p < 0.002) down regulated IL-17A in T1R reaction as compared to NR leprosy patients. The present study for the first time establishes that pathogenic Th17 cells produce IL-17 in an IL-6 dependent manner in leprosy T1R reactions. Thus, present approaches that specifically target Th17 cells and/or the cytokines that promote their development, such as IL-6, TGF-β and IL-23A may provide more focused treatment strategies for the management of Mycobacterium leprae and its reactions.