Whole blood profiling of leprosy type 1(reversal) reactions highlights prominence of innate immune response genes

Xenophagy as a Strategy for Mycobacterium leprae Elimination during Type 1 or Type 2 Leprosy Reactions: A Systematic Review

BACKGROUND

Mycobacterium leprae is an intracellular bacillus that causes leprosy, a neglected disease that affects macrophages and Schwann cells. Leprosy reactions are acute inflammatory responses to mycobacterial antigens, classified as type1 (T1R), a predominant cellular immune response, or type2 (T2R), a humoral phenomenon, leading to a high number of bacilli in infected cells and nerve structures. Xenophagy is a type of selective autophagy that targets intracellular bacteria for lysosomal degradation; however, its immune mechanisms during leprosy reactions are still unclear. This review summarizes the relationship between the autophagic process and M. leprae elimination during leprosy reactions.

METHODS

Three databases, PubMed/Medline (n = 91), Scopus (n = 73), and ScienceDirect (n = 124), were searched. After applying the eligibility criteria, articles were selected for independent peer reviewers in August 2023.

RESULTS

From a total of 288 studies retrieved, eight were included. In multibacillary (MB) patients who progressed to T1R, xenophagy blockade and increased inflammasome activation were observed, with IL-1β secretion before the reactional episode occurrence. On the other hand, recent data actually observed increased IL-15 levels before the reaction began, as well as IFN-γ production and xenophagy induction.

CONCLUSION

Our search results showed a dichotomy in the T1R development and their relationship with xenophagy. No T2R studies were found.

Prediction of the occurrence of leprosy reactions based on Bayesian networks

Introduction

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 to estimate the risk of a leprosy patient developing LR. Here we present an artificial intelligence (AI)-based system that can assess LR risk 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 2 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 87.7% accuracy, 85.7% sensitivity, and 89.4% specificity.

Conclusion

We produced an easy-to-use, online, free-access system that identifies leprosy patients at risk of developing LR. Risk assessment of LR for individual patients may detect candidates for close monitoring, with a potentially positive impact on the prevention of permanent disabilities, the quality of life of the patients, and upon leprosy control programs.

A Study of NLRC4 in Patients with Leprosy

Background

Activation of the NLRC4 inflammasome appears to start many signalling processes inside the host, including caspase-1, the principal protease responsible for converting proIL-1β and IL-18 to active, secreted IL-1β and IL-18, resulting in pyroptosis.

Aims

To evaluate NLRC4 level in patient's blood serum to highlight its role in the pathogenesis of leprosy.

Materials and Methods

This prospective study was conducted on 40 patients with leprosy and 30 healthy individuals of matched ages and sexes. All patients were subjected to complete history taking, general and dermatological examination, laboratory investigations, slit skin smear with bacillary index, and clinical classification of the studied leprosy group patients regarding disability according to disability grading. And finally, measurement of serum NLRC4 level by ELISA.

Results

In the paucibacillary (PB) group, NLRC4 serum level ranged from 0.9 to 1.8 ng/ml with 1.43 ± 0.28 ng/ml, while in the multibacillary (MB) group, it ranged from 1.2 to 5.7 ng/ml with 2.83 ± 1.11 ng/ml. NLRC4 serum level had increased significantly in MB patients compared to PB patients (P < 0.05). There was a significant difference among the three studied groups, regarding the serum level of NLRC4 (P < 0.05). In leprosy patients, significant positive correlations were found between serum levels of NLRC4 and bacillary index and duration of leprosy.

Conclusions

Leprosy patients had considerably greater serum levels of NLRC4 than controls. It was much greater in MB patients than in PB patients.

Low-Cost Microfluidic Systems for Detection of Neglected Tropical Diseases

Neglected tropical diseases (NTDs) affect tropical and subtropical countries and are caused by viruses, bacteria, protozoa, and helminths. These kinds of diseases spread quickly due to the tropical climate and limited access to clean water, sanitation, and health care, which make exposed people more vulnerable. NTDs are reported to be difficult and inefficient to diagnose. As mentioned, most NTDs occur in countries that are socially vulnerable, and the lack of resources and access to modern laboratories and equipment intensify the difficulty of diagnosis and treatment, leading to an increase in the mortality rate. Portable and low-cost microfluidic systems have been widely applied for clinical diagnosis, offering a promising alternative that can meet the needs for fast, affordable, and reliable diagnostic tests in developing countries. This review provides a critical overview of microfluidic devices that have been reported in the literature for the detection of the most common NTDs over the past 5 years.

Whole blood RNA signatures in leprosy patients identify reversal reactions before clinical onset: a prospective, multicenter study

Early diagnosis of leprosy is challenging, particularly its inflammatory reactions, the major cause of irreversible neuropathy in leprosy. Current diagnostics cannot identify which patients are at risk of developing reactions. This study assessed blood RNA expression levels as potential biomarkers for leprosy. Prospective cohorts of newly diagnosed leprosy patients, including reactions, and healthy controls were recruited in Bangladesh, Brazil, Ethiopia and Nepal. RNA expression in 1,090 whole blood samples was determined for 103 target genes for innate and adaptive immune profiling by dual color Reverse-Transcription Multiplex Ligation-dependent Probe Amplification (dcRT-MLPA) followed by cluster analysis. We identified transcriptomic biomarkers associated with leprosy disease, different leprosy phenotypes as well as high exposure to Mycobacterium leprae which respectively allow improved diagnosis and classification of leprosy patients and detection of infection. Importantly, a transcriptomic signature of risk for reversal reactions consisting of five genes (CCL2, CD8A, IL2, IL15 and MARCO) was identified based on cross-sectional comparison of RNA expression. In addition, intra-individual longitudinal analyses of leprosy patients before, during and after treatment of reversal reactions, indicated that several IFN-induced genes increased significantly at onset of reaction whereas IL15 decreased. This multi-site study, situated in four leprosy endemic areas, demonstrates the potential of host transcriptomic biomarkers as correlates of risk for leprosy. Importantly, a prospective five-gene signature for reversal reactions could predict reversal reactions at least 2 weeks before onset. Thus, transcriptomic biomarkers provide promise for early detection of these acute inflammatory episodes and thereby help prevent permanent neuropathy and disability in leprosy patients.