Quantitative polymerase chain reaction in paucibacillary leprosy diagnosis: A follow-up study

Serodiagnosis of paucibacillary and multibacillary leprosy using a recombinant chimeric protein composed of specific B-cell epitopes derived from Mycobacterium leprae proteins

Leprosy diagnosis is difficult due to the clinical similarity with other infectious diseases, and laboratory tests presents problems related to sensitivity and/or specificity. In this study, we used bioinformatics to assess Mycobacterium leprae proteins and formulated a chimeric protein that was tested as a diagnostic marker for the disease. The amino acid sequences from ML0008, ML0126, ML0308, ML1057, ML2028, ML2038, ML2498 proteins were evaluated, and the B-cell epitopes QASVAYPATSYADFRAHNHWWNGP, SLQRSISPNSYNTARVDP and QLLGQTADVAGAAKSGPVQPMGDRGSVSPVGQ were considered M. leprae-specific and used to construct the gene encoding the recombinant antigen. The gene was constructed, the recombinant protein was expressed, purified and tested in ELISA using 252 sera, which contained samples from multibacillary (MB) or paucibacillary (PB) leprosy patients, from their household contacts and healthy individuals, as well as from patients with Chagas disease, visceral and tegumentary leishmaniases (VL/TL), malaria, tuberculosis, and HIV. Sensitivity (Se) and specificity (Sp) for MB and PB samples compared to sera from both healthy subjects and individuals with cross-reactive diseases were 100%. The Se value for MB and PB samples compared to sera from household contacts was 100%, but Sp was 64%. In conclusion, data suggest that this protein could be considered in future studies for leprosy diagnosis.

Artificial Intelligence on Diagnostic Aid of Leprosy: A Systematic Literature Review

Leprosy is a neglected tropical disease that can cause physical injury and mental disability. Diagnosis is primarily clinical, but can be inconclusive due to the absence of initial symptoms and similarity to other dermatological diseases. Artificial intelligence (AI) techniques have been used in dermatology, assisting clinical procedures and diagnostics. In particular, AI-supported solutions have been proposed in the literature to aid in the diagnosis of leprosy, and this Systematic Literature Review (SLR) aims to characterize the state of the art. This SLR followed the preferred reporting items for systematic reviews and meta-analyses (PRISMA) framework and was conducted in the following databases: ACM Digital Library, IEEE Digital Library, ISI Web of Science, Scopus, and PubMed. Potentially relevant research articles were retrieved. The researchers applied criteria to select the studies, assess their quality, and perform the data extraction process. Moreover, 1659 studies were retrieved, of which 21 were included in the review after selection. Most of the studies used images of skin lesions, classical machine learning algorithms, and multi-class classification tasks to develop models to diagnose dermatological diseases. Most of the reviewed articles did not target leprosy as the study's primary objective but rather the classification of different skin diseases (among them, leprosy). Although AI-supported leprosy diagnosis is constantly evolving, research in this area is still in its early stage, then studies are required to make AI solutions mature enough to be transformed into clinical practice. Expanding research efforts on leprosy diagnosis, coupled with the advocacy of open science in leveraging AI for diagnostic support, can yield robust and influential outcomes.

Epidemiology and grade 2 disability of leprosy among migrant and resident patients in Guangdong: an unignorable continued transmission of leprosy

Introduction

Leprosy remains a major public health concern worldwide and one of the leading causes of disability. New cases of leprosy with grade 2 disability (G2D) often reflect delayed detection due to the limited capacity of the health system to recognize leprosy early. This study aimed to describe the epidemiology and G2D of leprosy among migrant and resident patients with leprosy in Guangdong province, China.

Methods

Data on newly diagnosed cases of leprosy were collected from the leprosy management information system in China. Descriptive statistical analysis was used to describe the status of G2D. Joinpoint regression model and logistic regression were performed to analyze the temporal trends and influencing factors for G2D.

Results

The G2D rate among migrant, resident, and total patients with leprosy was 17.5%, 18.7%, and 18.4%, respectively. The total G2D rate increased significantly from 18.0% in 2001 to 25.7% in 2021 (average annual per cent change: 2.5%). Multivariate analysis revealed that factors that negatively influence G2D between migrant and resident patients included delayed discovery time (migrants: OR = 2.57; residents: OR = 4.99) and nerve damage when diagnosed (migrants: OR = 9.40; residents: OR = 21.28).

Discussion

Our findings indicate that the targeted intervention measures implemented by our health system are urgently needed to improve the current situation, such as programs to promote early detection, strengthen awareness and skills of healthcare workers, and rehabilitation for disabled patients to improve their quality of life.

Leprosy in an Adopted Woman Diagnosed by Molecular Tools: A Case Report from a Non-Endemic Area

Coupled with its rarity in non-endemic areas, the clinical heterogeneity of leprosy makes diagnosis very challenging. We report a diagnosis of multibacillary leprosy in a 22-year-old Indian woman, adopted at the age of 10 and living in Italy. The patient presented with painful skin lesions on the face, trunk, and lower and upper extremities, associated with dysesthesia and a motor deficit in her left leg following corticosteroid therapy interruption. Histopathology results from the skin lesions suggested leprosy, but no acid-fast bacilli were identified. Molecular biology in a center specializing in tropical diseases confirmed the diagnosis, allowing prompt and adequate treatment. Genotype analysis allowed the identification of a genotype 1D of M. leprae, facilitating the epidemiological investigation of the plausible infection origin. No resistances to rifampicin, dapsone, or ofloxacin were detected. Leprosy will continue to exist in high-income nations, and the incidence may rise over time due to increasing migration and globalization. CARE guidelines were followed.

Bacilloscopy and polymerase chain reaction of slit-skin smears and anti-phenolic glycolipid-I serology for Hansen’s disease diagnosis

The bacilloscopy of the slit-skin smear (SSS) is the exclusive laboratory test associated with dermato-neurological evaluation for Hansen’s disease (HD) diagnosis; however, it is negative in the majority of PB or primary neural forms. Thus, a PCR technique involving different sequences and target genes has been performed with an aim to increase the sensitivity and specificity of M. leprae identification, especially in patients with low bacillary loads. Additionally, serological assays based on antibody response reflect infection levels and indicate that this could be a simpler, less invasive technique for estimating M. leprae exposure. Serological tests and PCR have been shown to be more sensitive and accurate than the SSS. Our study aimed to measure accuracy and performance among the SSS and PCR of dermal scrapings stored on filter paper and APGL-I serology for diagnosis in HD. A cross-sectional study analyzing the medical records (n = 345) of an HD outpatient-dermatology clinic from 2014 to 2021 was conducted. Accuracy performance parameters, correlation, and concordance were used to assess the value among the SSS, PCR, and APGL-I exams in HD. The SSS presented 24.5% sensitivity, 100% specificity, 37.4% accuracy, and the lowest negative predictive value (21.5%). The PCR assay had 41, 100, and 51% sensitivity, specificity, and accuracy, respectively. PCR and APGL-I serology increased the detection of HD cases by 16 and 20.6%, respectively. PCR was positive in 51.3% of patients when the SSS was negative. The SSS obtained moderate concordance with PCR [k-value: 0.43 (CI: 0.33–0.55)] and APGL-I [k-value: 0.41 (CI: 0.31–0.53)]. A moderate positive correlation was found between the APGL-I index and the bacillary index (r = 0.53; P < 0.0001). Thus, the use of the SSS is a low sensitivity and accuracy method due to its low performance in HD detection. The use of PCR and serological tests allows for a more sensitive and accurate diagnosis of patients.

ELISA Test Based on the Phenolic Glycolipid-I (PGL-I) of Mycobacterium leprae: A Reality of a Laboratory from a Non-Endemic Country

Background: Leprosy is a neglected tropical disease caused by Mycobacterium leprae, leading to disabilities if untreated. The ELISA based on phenolic glycolipid I (PGL-I), or its synthetic version ND-O-BSA, is almost universally positive in multibacillary leprosy and thus extensively used in endemic countries. Household contacts with a positive antibody titer have ~6-fold higher probability to develop the disease than those with a negative titer. Thus, the aim of the study was to evaluate the performance of this ELISA in the setting of a non-endemic country. Methods: We calculate the cut-off using optimized O.D. thresholds, generated by receiver operating characteristics (ROC) curve analysis, testing 39 well-characterized sera obtained from lepromatous leprosy patients with strongly positive ND-O-BSAELISA titer and 39 sera from healthy non-endemic patients never exposed to M. leprae or M. tuberculosis. Indeed, we tested a second set of sera from suspected or confirmed leprosy or household contacts (SLALT group, n=50), and patients with tuberculosis (control group, n=40). Results: We detected 56.4% of SLALT and 22.5% of tuberculosis as positive, consistent with the literature. Conclusion: The ELISA based on ND-O-BSA may thus be considered a good option to be used in a non-endemic area as a screening tool in at risk population usually coming to our center.

Advances in the Diagnosis of Leprosy

Leprosy is a public health issue, and early detection is critical to avert disability. Despite the global attempt to eradicate this disease as a public health problem, it remains an important cause of global neurological disability. India, Brazil and Indonesia share more than 70% of the cases. The reduction of new cases is a priority in the WHO global strategy 2021-2030 which aims to reduce disease transmission in the community by diagnosing cases and identifying subclinical infection. The clinical manifestations of leprosy range from a few to several lesions. The identification remains difficult due to the limited sensitivity of traditional approaches based on bacillary counts of skin smears and histology. To aid in the diagnosis of this disease, molecular biology, and biotechnological technologies have been applied, each with its own set of benefits and downsides despite providing an essential tool to validate the clinical diagnosis of leprosy. Because of this, it is strongly recognized that specific, inexpensive point of care technologies should be developed, particularly to identify asymptomatic M. leprae infections or leprosy nearer to the suspected cases seeking medical attention. Thus, this review will provide an overview of the advancements in leprosy diagnosis over the world. The purpose of this review is to improve our understanding of the outcomes of current tests and technologies used in leprosy diagnosis and to emphasize critical aspects concerning the detection of leprosy bacilli.

Development and validation of a multiplex real-time qPCR assay using GMP-grade reagents for leprosy diagnosis

Leprosy is a chronic dermato-neurological disease caused by Mycobacterium leprae, an obligate intracellular bacterium. Timely detection is a challenge in leprosy diagnosis, relying on clinical examination and trained health professionals. Furthermore, adequate care and transmission control depend on early and reliable pathogen detection. Here, we describe a qPCR test for routine diagnosis of leprosy-suspected patients. The reaction simultaneously amplifies two specific Mycobacterium leprae targets (16S rRNA and RLEP), and the human 18S rRNA gene as internal control. The limit of detection was estimated to be 2.29 copies of the M. leprae genome. Analytical specificity was evaluated using a panel of 20 other skin pathogenic microorganisms and Mycobacteria, showing no cross-reactivity. Intra- and inter-operator C_p variation was evaluated using dilution curves of M. leprae DNA or a synthetic gene, and no significant difference was observed between three operators in two different laboratories. The multiplex assay was evaluated using 97 patient samples with clinical and histopathological leprosy confirmation, displaying high diagnostic sensitivity (91%) and specificity (100%). Validation tests in an independent panel of 50 samples confirmed sensitivity and specificity of 97% and 98%, respectively. Importantly, assay performance remained stable for at least five months. Our results show that the newly developed multiplex qPCR effectively and specifically detects M. leprae DNA in skin samples, contributing to an efficient diagnosis that expedites the appropriate treatment.

Leprosy is a chronic dermato-neurological disease caused by Mycobacterium leprae, an obligate intracellular bacterium. Diagnosis of leprosy often relies on skin examinations for clinical signs, bacilli staining from skin smears and invasive skin biopsies. However, the spectrum of clinical manifestations and, often, low bacilli numbers can hinder accurate diagnosis. Timely detection is a challenge in leprosy diagnosis, relying on clinical examination and requiring trained health professionals. Proper intervention for adequate care and transmission control depends on early and reliable pathogen detection. Quantitative PCR methods for detecting bacterial DNA are more sensitive and could aid in differentially diagnosing leprosy from other dermatological conditions. In this work, we present a new multiplex PCR that was assessed for quality control standards, and the data indicate that the assay is stable and reproducible. The results presented here are the basis of a novel and robust tool with potential to increase the accuracy of leprosy diagnosis in routine or reference laboratories.

Reimagining leprosy elimination with AI analysis of a combination of skin lesion images with demographic and clinical data

Background

Leprosy is an infectious disease that mostly affects underserved populations. Although it has been largely eliminated, still about 200'000 new patients are diagnosed annually. In the absence of a diagnostic test, clinical diagnosis is often delayed, potentially leading to irreversible neurological damage and its resulting stigma, as well as continued transmission. Accelerating diagnosis could significantly contribute to advancing global leprosy elimination. Digital and Artificial Intelligence (AI) driven technology has shown potential to augment health workers abilities in making faster and more accurate diagnosis, especially when using images such as in the fields of dermatology or ophthalmology. That made us start the quest for an AI-driven diagnosis assistant for leprosy, based on skin images.

Methods

Here we describe the accuracy of an AI-enabled image-based diagnosis assistant for leprosy, called AI4Leprosy, based on a combination of skin images and clinical data, collected following a standardized process. In a Brazilian leprosy national referral center, 222 patients with leprosy or other dermatological conditions were included, and the 1229 collected skin images and 585 sets of metadata are stored in an open-source dataset for other researchers to exploit.

Findings

We used this dataset to test whether a CNN-based AI algorithm could contribute to leprosy diagnosis and employed three AI models, testing images and metadata both independently and in combination. AI modeling indicated that the most important clinical signs are thermal sensitivity loss, nodules and papules, feet paresthesia, number of lesions and gender, but also scaling surface and pruritus that were negatively associated with leprosy. Using elastic-net logistic regression provided a high classification accuracy (90%) and an area under curve (AUC) of 96.46% for leprosy diagnosis.

Interpretation

Future validation of these models is underway, gathering larger datasets from populations of different skin types and collecting images with smartphone cameras to mimic real world settings. We hope that the results of our research will lead to clinical solutions that help accelerate global leprosy elimination.

Funding

This study was partially funded by Novartis Foundation and Microsoft (in-kind contribution).

A new paradigm for leprosy diagnosis based on host gene expression

Transcriptional profiling is a powerful tool to investigate and detect human diseases. In this study, we used bulk RNA-sequencing (RNA-Seq) to compare the transcriptomes in skin lesions of leprosy patients or controls affected by other dermal conditions such as granuloma annulare, a confounder for paucibacillary leprosy. We identified five genes capable of accurately distinguishing multibacillary and paucibacillary leprosy from other skin conditions. Indoleamine 2,3-dioxygenase 1 (IDO1) expression alone was highly discriminatory, followed by TLR10, BLK, CD38, and SLAMF7, whereas the HS3ST2 and CD40LG mRNA separated multi- and paucibacillary leprosy. Finally, from the main differentially expressed genes (DEG) and enriched pathways, we conclude that paucibacillary disease is characterized by epithelioid transformation and granuloma formation, with an exacerbated cellular immune response, while multibacillary leprosy features epithelial-mesenchymal transition with phagocytic and lipid biogenesis patterns in the skin. These findings will help catalyze the development of better diagnostic tools and potential host-based therapeutic interventions. Finally, our data may help elucidate host-pathogen interplay driving disease clinical manifestations.

Rapid Multiplex Loop-Mediated Isothermal Amplification (m-LAMP) Assay for Differential Diagnosis of Leprosy and Post-Kala-Azar Dermal Leishmaniasis

Leprosy and post-kala-azar dermal leishmaniasis (PKDL) are co-endemic neglected tropical diseases often misdiagnosed because of close resemblance in their clinical manifestations. The test that aids in differential diagnosis of leprosy and PKDL would be useful in endemic areas. Here, we report development of a multiplex loop-mediated isothermal amplification (m-LAMP) assay for differential detection of Mycobacterium leprae and Leishmania donovani using a real-time fluorometer. The m-LAMP assay was rapid with a mean amplification time of 15 minutes, and analytical sensitivity of 1 fg for L. donovani and 100 fg for M. leprae. The distinct mean Tm values for M. leprae and L. donovani allowed differentiation of the two organisms in the m-LAMP assay. Diagnostic sensitivity of the assay was evaluated by using confirmed cases of leprosy (n = 40) and PKDL (n = 40) (tissue and slit aspirate samples). All the leprosy and PKDL samples used in this study were positive by organism-specific QPCR and loop-mediated isothermal amplification assays. The diagnostic sensitivity of the m-LAMP assay was 100% (95% CI: 91.2-100.0%) for detecting PKDL and 95% for leprosy (95% CI: 83.1-99.4%). Our m-LAMP assay was successfully used to detect both M. leprae and L. donovani in a patient coinfected with leprosy and macular PKDL. The m-LAMP assay is rapid, accurate, and applicable for differential diagnosis of leprosy versus PKDL, especially in endemic areas.

Sensitivity and specificity of multibacillary and paucibacillary leprosy laboratory tests: A systematic review and meta-analysis

This systematic review (number register: CRD42018112736) was performed to compare the sensitivity and specificity of leprosy diagnostic methods. The search was conducted in 3 electronic databases in January 2021. Studies evaluating leprosy diagnostic tests were included according the eligibility criteria. Meta-analysis was performed to calculate the sensibility and specificity of the groups. We included 36 studies. The test sensitivity for paucibacillary patients was 0.31 (95%CI: 0.29-0.33) and the specificity was 0.92 (95%CI: 0.92-0.93). In multibacillary patients, the sensitivity was 0.78 (95%CI: 0.77-0.80) and specificity was 0.92 (95%CI: 0.92-0.93). Comparing the sensitivity and specificity of the different techniques included, it should be noted that polymerase chain reaction (PCR) test presented the highest sensitivity for paucibacillary patients, while the western blot technique showed the highest sensitivity for multibacillary patients. However, further studies are needed to optimise the diagnosis of leprosy, requiring research with a larger number of samples and more uniform protocols.

Leprosy incidence and risk estimates in a 33-year contact cohort of leprosy patients

Reduction in incidence has been associated with the introduction of novel approaches, like chemo/immune-prophylaxis. Incidence determined through follow-up cohort studies can evaluate the implementation of these innovative policies towards control and prevention. We have assessed the incidence in our contacts cohort over past 33 years, considering the effect of demographic and clinical variables. Survival analysis was used to estimate the risk of leprosy. A total of 9024 contacts were evaluated, of which 192 developed leprosy, resulting in an overall incidence of 1.4/1000 person-years. The multivariate analysis showed that the major risk factors were (i) contact from MB index cases and (ii) consanguinity (iii) intra household contact. Lower risk was detected for contacts with BCG scar who were revaccinated. There was a significant decrease in accumulated risk between the 2011-2019 period compared with 1987, probably linked to the improvement in laboratory tools to monitor contacts, thereby providing early diagnosis of contacts at intake and reduction of transmission. Our findings suggest that a combination of contact surveillance and tracing, adequate neurodermatological examination, and availability of molecular tools is highly effective in supporting early diagnosis, while a second dose of the BCG vaccination can exert extra protection.

A comprehensive research agenda for zero leprosy

BACKGROUND

Leprosy control achieved dramatic success in the 1980s-1990s with the implementation of short course multidrug therapy, which reduced the global prevalence of leprosy to less than 1 in 10 000 population. However, a period of relative stagnation in leprosy control followed this achievement, and only limited further declines in the global number of new cases reported have been achieved over the past decade.

MAIN TEXT

In 2016, major stakeholders called for the development of an innovative and comprehensive leprosy strategy aimed at reducing the incidence of leprosy, lowering the burden of disability and discrimination, and interrupting transmission. This led to the establishment of the Global Partnership for Zero Leprosy (GPZL) in 2018, with partners aligned around a shared Action Framework committed to achieving the WHO targets by 2030 through national leprosy program capacity-building, resource mobilisation and an enabling research agenda. GPZL convened over 140 experts from more than 20 countries to develop a research agenda to achieve zero leprosy. The result is a detailed research agenda focusing on diagnostics, mapping, digital technology and innovation, disability, epidemiological modelling and investment case, implementation research, stigma, post exposure prophylaxis and transmission, and vaccines. This research agenda is aligned with the research priorities identified by other stakeholders.

CONCLUSIONS

Developing and achieving consensus on the research agenda for zero leprosy is a significant step forward for the leprosy community. In a next step, research programmes must be developed, with individual components of the research agenda requiring distinct expertise, varying in resource needs, and operating over different timescales. Moving toward zero leprosy now requires partner alignment and new investments at all stages of the research process, from discovery to implementation.

Molecular epidemiology of leprosy: An update

Molecular epidemiology investigations are notoriously challenging in the leprosy field mainly because the inherent characteristics of the disease as well as its yet uncultivated causative agents, Mycobacterium leprae and M. lepromatosis. Despite significant developments in understanding the biology of leprosy bacilli through genomic approaches, the exact mechanisms of transmission is still unclear and the factors underlying pathological variation of the disease in different patients remain as major gaps in our knowledge about leprosy. Despite these difficulties, the last two decades have seen the development of genotyping procedures based on PCR-sequencing of target loci as well as by the genome-wide analysis of an increasing number of geographically diverse isolates of leprosy bacilli. This has provided a foundation for molecular epidemiology studies that are bringing a better understanding of strain evolution associated with ancient human migrations, and phylogeographical insights about the spread of disease globally. This review discusses the advantages and drawbacks of the main tools available for molecular epidemiological investigations of leprosy and summarizes various methods ranging from PCR-based genotyping to genome-typing techniques. We also describe their main applications in analyzing the short-range and long-range transmission of the disease. Finally, we summarise the current gaps and challenges that remain in the field of molecular epidemiology of leprosy.

Reanalysis and integration of public microarray datasets reveals novel host genes modulated in leprosy

Due to multiple hypothesis testing with often limited sample size, microarrays and other-omics technologies can sometimes produce irreproducible findings. Complementary to better experimental design, reanalysis and integration of gene expression datasets may help overcome reproducibility issues by identifying consistent differentially expressed genes from independent studies. In this work, after a systematic search, nine microarray datasets evaluating host gene expression in leprosy were reanalyzed and the information was integrated to strengthen evidence of differential expression for several genes. Our results are relevant in prioritizing genes and pathways for further investigation, whether in functional studies or in biomarker discovery. Reanalysis of individual datasets revealed several differentially expressed genes (DEGs) in accordance with original reports. Then, five integration methods (P value and effect size based) were tested. In the end, random-effects model and ratio association were selected as the main methods to pinpoint DEGs. Overall, classic pathways were found corroborating previous findings and validating this approach. Also, we identified some novel DEG involved especially with skin development processes (AQP3, AKR1C3, CYP27B1, LTB, VDR) and keratinocyte biology (CSTA, DSG1, KRT14, KRT5, PKP1, IVL), both still poorly understood in leprosy context. In addition, here we provide aggregated evidence towards some gene candidates that should be prioritized in further leprosy research, as they are likely important in immunopathogenesis. Altogether, these data are useful in better understanding host responses to the disease and, at the same time, provide a list of potential host biomarkers that could be useful in complementing leprosy diagnosis based on transcriptional levels.

Genomic Characterization of Mycobacterium leprae to Explore Transmission Patterns Identifies New Subtype in Bangladesh

Mycobacterium leprae, the causative agent of leprosy, is an unculturable bacterium with a considerably reduced genome (3.27 Mb) compared to homologues mycobacteria from the same ancestry. In 2001, the genome of M. leprae was first described and subsequently four genotypes (1-4) and 16 subtypes (A-P) were identified providing means to study global transmission patterns for leprosy. In order to understand the role of asymptomatic carriers we investigated M. leprae carriage as well as infection in leprosy patients (n = 60) and healthy household contacts (HHC; n = 250) from Bangladesh using molecular detection of the bacterial element RLEP in nasal swabs (NS) and slit skin smears (SSS). In parallel, to study M. leprae genotype distribution in Bangladesh we explored strain diversity by whole genome sequencing (WGS) and Sanger sequencing. In the studied cohort in Bangladesh, M. leprae DNA was detected in 33.3% of NS and 22.2% of SSS of patients with bacillary index of 0 whilst in HHC 18.0% of NS and 12.3% of SSS were positive. The majority of the M. leprae strains detected in this study belonged to genotype 1D (55%), followed by 1A (31%). Importantly, WGS allowed the identification of a new M. leprae genotype, designated 1B-Bangladesh (14%), which clustered separately between the 1A and 1B strains. Moreover, we established that the genotype previously designated 1C, is not an independent subtype but clusters within the 1D genotype. Intraindividual differences were present between the M. leprae strains obtained including mutations in hypermutated genes, suggesting mixed colonization/infection or in-host evolution. In summary, we observed that M. leprae is present in asymptomatic contacts of leprosy patients fueling the concept that these individuals contribute to the current intensity of transmission. Our data therefore emphasize the importance of sensitive and specific tools allowing post-exposure prophylaxis targeted at M. leprae-infected or -colonized individuals.

The immunology of other mycobacteria: M. ulcerans, M. leprae

Mycobacterial pathogens can be categorized into three broad groups: Mycobacterium tuberculosis complex causing tuberculosis, M. leprae and M. lepromatosis causing leprosy, and atypical mycobacteria, or non-tuberculous mycobacteria (NTM), responsible for a wide range of diseases. Among the NTMs, M. ulcerans is responsible for the neglected tropical skin disease Buruli ulcer (BU). Most pathogenic mycobacteria, including M. leprae, evade effector mechanisms of the humoral immune system by hiding and replicating inside host cells and are furthermore excellent modulators of host immune responses. In contrast, M. ulcerans replicates predominantly extracellularly, sheltered from host immune responses through the cytotoxic and immunosuppressive effects of mycolactone, a macrolide produced by the bacteria. In the year 2018, 208,613 new cases of leprosy and 2713 new cases of BU were reported to WHO, figures which are notoriously skewed by vast underreporting of these diseases.

Ultra-sensitive detection of Mycobacterium leprae: DNA extraction and PCR assays

Leprosy urgently needs a precise and early diagnostic tool. The sensitivity of the direct (bacilli staining, Mycobacterium leprae DNA) and indirect (antibody levels, T cell assays) diagnostics methods vary based on the clinical form. Recently, PCR-based M. leprae DNA detection has been shown to differentially diagnose leprosy from other dermatological conditions. However, accuracy can still be improved, especially for use with less invasive clinical samples. We tested different commercial DNA extraction kits: DNeasy Blood & Tissue, QIAamp DNA Microbiome, Maxwell 16 DNA Purification, PowerSoil DNA Isolation; as well as in-house phenol-chloroform and Trizol/FastPrep methods. Extraction was performed on M. leprae-infected mouse footpads and different clinical samples of leprosy patients (skin biopsies and scrapings, lesion, oral and nasal swabs, body hair, blood on FTA cards, peripheral whole blood). We observed that the Microbiome kit was able to enrich for mycobacterial DNA, most likely due the enzymatic digestion cocktail along with mechanical disruption involved in this method. Consequently, we had a significant increase in sensitivity in skin biopsies from paucibacillary leprosy patients using a duplex qPCR targeting 16S rRNA (M. leprae) and 18S rRNA (mammal) in the StepOnePlus system. Our data showed that the presence of M. leprae DNA was best detected in skin biopsies and skin scrapings, independent of the extraction method or the clinical form. For multibacillary patients, detection of M. leprae DNA in nasal swabs indicates the possibility of having a much less invasive sample that can be used for the purposes of DNA sequencing for relapse analysis and drug resistance monitoring. Overall, DNA extracted with the Microbiome kit presented the best bacilli detection rate for paucibacillary cases, indicating that investments in extraction methods with mechanical and DNA digestion should be made.

Quantitative PCR for leprosy diagnosis and monitoring in household contacts: A follow-up study, 2011-2018

Household contacts (HHC) of leprosy patients exhibit high-risk of developing leprosy and contact tracing is helpful for early diagnosis. From 2011 to 2018,2,437 HHC were examined in a clinic in Rio de Janeiro, Brazil and 16S qPCR was used for diagnosis and monitoring of contacts. Fifty-four HHCs were clinically diagnosed with leprosy at intake. Another 25 exhibited leprosy-like skin lesions at intake, 8 of which were confirmed as having leprosy (50% of which were qPCR positive) and 17 of which were diagnosed with other skin diseases (6% qPCR positive). In skin biopsies, qPCR presented a sensitivity of 0.50 and specificity of 0.94. Furthermore, 955 healthy HHCs were followed-up for at least 3 years and skin scrapings were collected from earlobes for qPCR detection. Positive qPCR indicated a non-significant relative risk of 2.52 of developing the disease. During follow-up, those who progressed towards leprosy exhibited 20% qPCR positivity, compared to 9% of those who remained healthy. Disease-free survival rates indicated that age had a significant impact on disease progression, where patients over 60 had a greater chance of developing leprosy [HR = 32.4 (3.6-290.3)]. Contact tracing combined with qPCR may assist in early diagnosis and age is a risk factor for leprosy progression.

Secondary syphilis mimicking tuberculoid leprosy in an HIV-positive individual: a case report

Secondary syphilis is a polymorphic condition resulting from the hematogenous and lymphatic dissemination of Treponema pallidum. Human immunodeficiency virus-positive patients are in greater risk of atypical and severe forms of the disease. The most common manifestation is a generalized papulosquamous eruption with variable mucosal involvement. However, annular plaques, split commissural papules, crusted necrotic or ulcerated lesions are also frequent. Granulomatous lesions, both clinically and histologically, are less common and present a diagnostic challenge. We describe a case of secondary syphilis presenting as a granulomatous rash with both clinical and histological features of tuberculoid leprosy. Complementary tests and clinical suspicion are essential to ensure a correct diagnosis and avoid subsequent complications.

Diagnostic accuracy of tests for leprosy: a systematic review and meta-analysis

OBJECTIVES

Owing to difficulties in the clinical diagnosis of leprosy, several complementary tests have been developed and used. The aim was to systematically summarize the accuracy of diagnostic tests for leprosy.

METHODS

We searched for relevant articles in Embase, Medline, and Global Health databases, until June 2017. Studies evaluating the accuracy of any diagnostic techniques for differentiating between people with and without leprosy were included. Studies solely focusing on differentiating between the separate forms of leprosy were excluded. Our protocol was registered on PROSPERO (CRD42017071803). We assessed study quality using the QUADAS-2 checklist. A bivariate random effects regression model was used for the meta-analyses.

RESULTS

We included 78 studies, most of those evaluating the detection of IgM antibodies against phenolic glycolipid I using ELISA. Sensitivity of the 39 studies evaluating ELISA was 63.8% (95% CI 55.0-71.8); specificity 91.0% (95% CI 86.9-93.9). The lateral flow test (nine studies) and the agglutination test (five studies) had a slightly higher sensitivity and a slightly lower specificity. Sensitivity of qPCR was (five studies) 78.5% (95% CI 61.9-89.2) and specificity 89.3% (95% CI 61.4-97.8). Sensitivity of conventional PCR was (17 studies) 75.3% (95% CI 67.9-81.5) and specificity 94.5% (95% CI 91.4-96.5).

CONCLUSIONS

Although the test accuracy looks reasonable, the studies suffered from heterogeneity and low methodological quality.