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

Manta, Fernanda S. N.; Barbieri, Raquel Rodrigues; Moreira, Suelen Justo Maria; Santos, P.; Nery, José A. C.; Duppré, Nádia Cristina; Sales, Anna Maria; Pacheco, Antônio Guilherme; Hacker, Mariana A.; Machado, Adriana Rodrigues; Sarno, Euzenir Nunes; Moraes, Milton Ozório

doi:10.1038/s41598-019-52640-5

Cited by 28 publications

(38 citation statements)

References 32 publications

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“…A longitudinal study conducted in Brazil (Manta et al, 2019), investigated SSS from 995 HHC by qPCR including follow-up for at least 3 years with occurrence of five new cases. The authors reported 20% qPCR positivity in HHC representing future new cases compared to 9% in HHC without disease.…”

Section: Discussionmentioning

confidence: 99%

Detection of new Mycobacterium leprae subtype in Bangladesh by genomic characterization to explore transmission patterns

Tió-Coma

Avanzi

Verhard

et al. 2020

Preprint

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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. M. leprae transmission is suggested to occur through aerosols but the exact mechanisms of infection remains unclear. 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. 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, we explored bacterial 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.

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Section: Discussionmentioning

confidence: 99%

Detection of new Mycobacterium leprae subtype in Bangladesh by genomic characterization to explore transmission patterns

Tió-Coma

Avanzi

Verhard

et al. 2020

Preprint

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“…Our clinic routinely performs diagnosis of difficult cases aided by the use of qPCR 28 . The availability of this method provides the clinicians the possibility to interrogate leprosy when histopathological analysis of prevalent contacts with smaller lesions examined at intake are assumed equivocal or inconclusive 13 , 28 . In Manta et al 13 we followed up 980 contacts for at least 3 years after diagnosis of the index cases.…”

Section: Discussionmentioning

confidence: 99%

“…In Brazil, few studies have measured incidence in contacts from a follow-up cohort [12][13][14][15] . The factors associated with disease outcome among contacts include consanguinity, proximity, bacterial index/ clinical form of the index case, age, and sex 2,[12][13][14][15][16][17][18] .Contact tracing and geographic information systems studies reveal a concentration of new patients among household and social contacts, either children or adults, of previous patients highlighting the importance of developing differentiated actions for surveillance of this group [19][20][21] . Simulation studies 22 and systematic reviews 23 suggest that the control of leprosy could be achieved faster through household contact tracing associated with new interventions such as chemo or immunoprophylactic approaches 17,18,24 .…”

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confidence: 99%

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

Hacker

Sales

Duppré

et al. 2021

Sci Rep

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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.

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“…In the past years, several studies have searched for biomarkers to (early) detect leprosy either based on the host immune response [26] , [27] , [28] , [29] , [30] , [31] , the pathogen [32] , [33] , [34] , [35] , [36] , [37] , or a combination of both [38] , [39] , [40] , [41] , [42] , [43] , [44] , [45] . Molecular detection by identification of the repetitive element RLEP by (quantitative) PCR [ 33 , 46 , 47 ] as well as detection of anti- M. leprae phenolic glycolipid I (PGL-I) IgM in blood [ 28 , 29 ] are methods employed to assist leprosy diagnosis.…”

Section: Introductionmentioning

confidence: 99%

Blood RNA signature RISK4LEP predicts leprosy years before clinical onset

et al. 2021

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Background Leprosy, a chronic infectious disease caused by Mycobacterium leprae , is often late- or misdiagnosed leading to irreversible disabilities. Blood transcriptomic biomarkers that prospectively predict those who progress to leprosy (progressors) would allow early diagnosis, better treatment outcomes and facilitate interventions aimed at stopping bacterial transmission. To identify potential risk signatures of leprosy, we collected whole blood of household contacts (HC, n=5,352) of leprosy patients, including individuals who were diagnosed with leprosy 4-61 months after sample collection. Methods We investigated differential gene expression (DGE) by RNA-Seq between progressors before presence of symptoms (n=40) and HC (n=40), as well as longitudinal DGE within each progressor. A prospective leprosy signature was identified using a machine learning approach (Random Forest) and validated using reverse transcription quantitative PCR (RT-qPCR). Findings Although no significant intra-individual longitudinal variation within leprosy progressors was identified, 1,613 genes were differentially expressed in progressors before diagnosis compared to HC. We identified a 13-gene prospective risk signature with an Area Under the Curve (AUC) of 95.2%. Validation of this RNA-Seq signature in an additional set of progressors (n=43) and HC (n=43) by RT-qPCR, resulted in a final 4-gene signature, designated RISK4LEP ( MT-ND2, REX1BD, TPGS1, UBC ) (AUC=86.4%). Interpretation This study identifies for the first time a prospective transcriptional risk signature in blood predicting development of leprosy 4 to 61 months before clinical diagnosis. Assessment of this signature in contacts of leprosy patients can function as an adjunct diagnostic tool to target implementation of interventions to restrain leprosy development. Funding This study was supported by R2STOP Research grant, the Order of Malta-Grants-for-Leprosy-Research, the Q.M. Gastmann-Wichers Foundation and the Leprosy Research Initiative (LRI) together with the Turing Foundation (ILEP# 702.02.73 and # 703.15.07).

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

Cited by 28 publications

References 32 publications

Detection of new Mycobacterium leprae subtype in Bangladesh by genomic characterization to explore transmission patterns

Detection of new Mycobacterium leprae subtype in Bangladesh by genomic characterization to explore transmission patterns

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

Blood RNA signature RISK4LEP predicts leprosy years before clinical onset

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