Skip to main content
Advertisement
  • Loading metrics

Individual and clinical variables associated with the risk of Buruli ulcer acquisition: A systematic review and meta-analysis

  • João Fevereiro,

    Roles Conceptualization, Formal analysis, Investigation, Visualization, Writing – original draft, Writing – review & editing

    Affiliations Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal, ICVS/3B's—PT Government Associate Laboratory, Braga/Guimarães, Portugal

  • Nikta Sajjadi,

    Roles Validation, Writing – review & editing

    Affiliations Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal, ICVS/3B's—PT Government Associate Laboratory, Braga/Guimarães, Portugal

  • Alexandra G. Fraga,

    Roles Validation, Writing – review & editing

    Affiliations Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal, ICVS/3B's—PT Government Associate Laboratory, Braga/Guimarães, Portugal

  • Pedro M. Teixeira,

    Roles Conceptualization, Formal analysis, Writing – review & editing

    Affiliations Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal, ICVS/3B's—PT Government Associate Laboratory, Braga/Guimarães, Portugal

  • Jorge Pedrosa

    Roles Conceptualization, Funding acquisition, Writing – review & editing

    jpedrosa@med.uminho.pt

    Affiliations Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal, ICVS/3B's—PT Government Associate Laboratory, Braga/Guimarães, Portugal

Abstract

Background

Buruli ulcer (BU) is a necrotizing skin disease, caused by Mycobacterium ulcerans, with poorly understood acquisition risk factors. This review aims at evaluating the importance of individual–sex, age, family ties with history of BU, gene variants–and clinical–Bacillus Calmette-Guérin (BCG) immunization, Human Immunodeficiency Virus (HIV) infection–variables in this process.

Methods

A systematic review was performed considering the following databases: ClinicalTrials.gov, Cochrane Controlled Register of Trials (CENTRAL), Current Contents Connect, Embase, MEDLINE, SciELO, Scopus and Web of Science. Eligible studies were critically appraised with The Joanna Briggs Institute checklists and heterogeneity was assessed with Cochran Q-test and I2 statistic. Published demographic data was descriptively analysed and clinical data pooled within random-effects modelling for meta-analysis.

Results

A total of 29 studies were included in the systematic review. Two randomized controlled trials (RCTs) and 21 case-control studies were selected for meta-analysis. Studies show that BU mainly affects age extremes, more preponderately males among children. Data pooled from RCTs do not reveal BCG to be protective against BU (odds ratio (OR) = 0.63; 95% CI = 0.38–1.05; I2 = 56%), a finding case-control studies appear to corroborate. HIV infection (OR = 6.80; 95% CI = 2.33–19.85; I2 = 0%) and SLC11A1 rs17235409 A allele (OR = 1.86; 95% CI = 1.25–2.77; I2 = 0%) are associated with increased prevalence of the disease. No definite conclusions can be drawn regarding the influence of previous family history of BU.

Discussion

While available evidence warrants further robustness, these results have direct implications on current interventions and future research programs, and foster the development of more cost-effective preventive and screening measures.

Registration

The study was registered at PROSPERO with number CRD42019123611.

Author summary

Buruli ulcer (BU) is a devastating neglected tropical disease, whose worldwide notification to the WHO is currently on the rise. However, evidence has been so far conflicting as to the individual and clinical risk factors underlying the acquisition of the disease. Thus, considering the increasing body of literature made available in the last decade, it becomes essential to revisit this subject. To this aim, a temporal-unrestricted systematic review of published literature was undertaken in eight different online databases and meta-analysis conducted with clinical data. The randomized controlled trials and cohort studies reviewed supported the idea that male children or older adults are more susceptible to BU, BCG vaccination is insufficient to prevent BU in the mid-long term, and the prevalence of the disease is higher among HIV-infected individuals or carriers of genetic polymorphisms in SLC11A1. This knowledge, together with recommendations to tackle some drawbacks found within the reviewed studies, not only underlines the importance of searching for better vaccination alternatives, but also provides guidance for current and future screening and prevention programs.

Introduction

Buruli ulcer (BU) is a neglected tropical chronic skin disease caused by Mycobacterium ulcerans. The archetypal BU case begins with a painless small nodule or ulcer, less commonly a plaque or edema [1]. Over a period of weeks to months, these lesions may progress to extensive ulcerative lesions, which in some circumstances can afflict the underlying bone [1]. Due to its multiple presentations and the prospect of confounding superinfections, WHO recommends, without compromising the beginning of antibiotherapy, that the diagnosis of BU should include at least one, ideally two, of the following laboratorial methods: a) direct smear examination of acid-fast bacilli (AFB) with Ziehl-Neelsen from a swab or a biopsy; b) histopathology; c) culture on Löwenstein-Jensen medium at 32ºC; and d) Polymerase Chain Reaction (PCR) targeting the IS2404 insertion sequence [2]. The latter is currently considered the gold standard test, mostly due to its higher sensitivity and specificity (>90%), despite not being available in all laboratories [2].

BU has been reported in 34 countries worldwide [3,4]. As of 2018, there were two major foci of the disease, one mainly involving sub-Saharan African countries Ghana, Nigeria, Ivory Coast and Benin, and the other located in Australia, accounting for a total of 1892 cases, more than half of all recorded cases that year [3]. However, although there is a degree of consensus regarding the role of some environmental and behavioral factors associated to the disease, the literature has been less clear regarding the individual determinants of BU [57]. In fact, the only systematic reviews that have covered the intrinsic and clinical variables are either almost a decade-year old or largely inconclusive, prompting for an update on the state of the art [7,8].

Very little is known on the clinical features that predispose to BU. Sociodemographic variables, such as sex or age, have repeatedly failed to be associated to changes in the incidence of the disease, although some studies reported a higher number of cases amongst children and older adults, as well as a varying predominance of sex across the difference age groups [7,911]. Interestingly, while the reasons for such differences are still elusive, some studies have implicated BU as having a genetic component associated to its development. Whilst one group found that previous family history of BU significantly increased the odds for new cases in the family, other authors reported associations of alleles in SLC11A1, IFNG, amongst others, with increased chances of contracting the disease [1215]. However, not only are many of these findings still pending validation, but others authors have also reached opposite conclusions, thus remaining the question of what role does genetics play in BU [13,1618].

Likewise, the impact of immunological determinants, such as Bacillus Calmette-Guérin (BCG) vaccination or Human Immunodeficiency Virus (HIV) co-infection, on the development of BU is also a matter of uncertainty [19]. A recent meta-analysis concluded that although the original randomized controlled trials (RCTs) testing BCG vaccination showed a protective role for the vaccine, later case-control studies did not confirm such effect [8]. HIV co-infection, on the other hand, appears to promote the clinical manifestation of BU, but the low prevalence (<2–3%) of HIV-infected patients in many of the BU-endemic countries undermines the statistical power of the analyses and the reliability of the results [16,20,21].

Hence, considering the ambiguity governing the importance of the above-mentioned individual factors in the acquisition of BU, a systematic review of the available body of literature was herein undertaken. Eight different medical and scientific databases were screened for experimental and observational studies worldwide, from which data was extracted for meta-analysis whenever applicable. Critical analysis of such information is expected to yield valuable information on the understanding of the risk factors for BU development, with potential implications for future studies and intervention measures.

Methods

This study complies with The Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement (PRISMA; S1 Checklist) and its protocol is published and accessible at PROSPERO with the number CRD42019123611.

Eligibility criteria

For the present systematic review and meta-analysis, data derived from human RCTs, case-control and cohort studies were considered, without any temporal or language constraints. Studies were selected if they met all of the following criteria: (1) patients with BU from any part of the world, excluding studies restricted to specific age groups or presentations of the disease to avoid selection biases, as well as RCTs with recurrent cases of BU to avoid immunological memory confounding; (2) analysis of variables age, sex, BCG vaccination, HIV status, family history of BU and gene alleles, with exclusion of methodological studies and studies mainly focusing on outcomes of the disease process, subjective perceptions or behaviors of individuals and environmental risk factors; (3) primary outcome being the acquisition of BU.

Information sources and search

For this purpose, a literature search of the electronic databases ClinicalTrials.gov (1997 –present), Cochrane Controlled Register of Trials (CENTRAL, until present), Current Contents Connect (1998 –present, via Web of Science), Embase (1947 –present), MEDLINE (1946 –present, via PubMed), SciELO (1997 –present), Scopus (1788 –present) and Web of Science (1900 –present) was last performed on February 1, 2019, following the structure presented in the supporting information (S1 Text).

Study selection

Eligibility assessment was performed independently by JF and NS according to the above-mentioned criteria, with disagreement between the two authors being reviewed by PT. Titles and abstracts regarded as inconclusive were considered for full text inspection. Studies were included only when all the eligibility criteria were met.

Data collection process and summary measures

Extraction was performed by JF, NS and AGF and information independently cross-checked among these authors, namely: sample size, frequency and incidence metrics on individual characteristics of participants–age, age group, sex and genetic alleles–, as well as on the number of individuals vaccinated with BCG, infected by HIV or with previous family history of BU. Whenever the frequency of any group could not be calculated from the available data, corresponding authors were asked, via e-mail contact, to provide the necessary information.

Statistics

Meta-analyses were conducted using Review Manager 5.3 and MetaGenyo [22,23]. Heterogeneity was tested with the Cochran Q-test and I2 statistic, calculated as I2 = [(Q–degree of freedom)/Q] × 100, where Q is the Cochran’s statistic. I2 values of 30, 50 and 75 represent low, medium and high heterogeneity, respectively [24]. In the presence of high heterogeneity, subgroup analysis with laboratory-BU confirmed cases and/or low risk bias studies was attempted. Random-effects model (the Restricted Maximum-Likelihood method) was used to calculate the summary of pooled frequency estimates [25].

Risk of bias across studies

Studies were independently classified by JF and NS as to the risk of biases, using the adequate critical assessment tools developed by the Joanna Briggs Institute [26]. Whenever disagreements between authors were found, a third call to PT was solicited. In addition, meta-analyses comprising at least 10 studies were checked for the presence of potential publication bias through the visual inspection of funnel plot asymmetry.

Results

Study selection

The study selection process is illustrated in Fig 1. The initial search yielded a total of 3575 records, of which 2238 were initially removed using the Zotero duplicate detection tool [27], followed by a manual independent screening by JF and NS. During the title and abstract screening, 1240 references were excluded mainly due to: a) being a non-original study or having a non-eligible design; b) not addressing Mycobacterium ulcerans infection; c) focusing on other outcomes than the acquisition of BU; d) restricting to specific age groups or forms of the disease. Ninety-seven references were selected for full-text review, at which stage 68 studies were additionally excluded mainly due to not having a compatible study design or providing relevant information for the goal of this review. Contacting of authors was attempted for the retrieval of seven studies, but at the moment of manuscript submission these were still not available.

Study characteristics and demographic characterization

Demographic characterization of the 29 eligible studies is presented in Table 1. These account for a total of 9265 BU cases, with a generally well-balanced male:female ratio (average of studies: 0.99). Following this line, five of the included sex-unmatched case-control studies [11,16,2830] (S1 Table), showed comparable sex frequencies between groups (OR = 0.90; 95% CI = 0.71–1.14; I2 = 58%; S1A Fig), independent of restricting analysis to BU laboratory-confirmed cases (OR = 1.01; 95% CI = 0.83–1.24; I2 = 0%; S1B Fig). Regarding age, although data distribution hampers a direct comparison between case-control studies, two of them described children below 15 years of age to be more prevalent amongst cases than controls [10,30] (S2 Table). Remarkably, most cohort studies equally converged on a higher incidence of the disease in this age group, particularly among males, with two additionally reporting another peak of incidence in the elderly [10,31] (Table 1).

Family history of BU

One cohort study found higher rates of BU in family members of BU patients (5.69/1000 person-years) when comparing the estimated rates for the general population of the region (0.85–4.04 cases/year/1000 population; [41] (Table 1). Among the five case-control studies registering this variable, only one adjusted the analyses for non-consanguineous bonds [15], while two included household relationships [33,40] and the other two did not provide any description on the variable [16,18] (S3 Table). Pooling of available data from studies comprising probable (OR = 1.14; 95% CI = 0.70–1.88; I2 = 54%; S2A Fig) or laboratory-confirmed (OR = 1.01; 95% CI = 0.61–1.68; I2 = 54%; S2B Fig) cases revealed no significant impact of family history in BU development, although a moderate heterogeneity is noted.

Genetic variants

Looking at the four genetic association studies captured by this systematic review [1214,39], it is foremost noticeable a discrepancy in the statistical approaches used by the different authors, hampering direct comparison and interpretation of results (S4 Table). As such, allelic frequencies were calculated from the available data, demonstrating minor alleles in iNOS rs9282799 (OR = 2.11; 95% CI = 1.27–3.50), IFNG rs2069705 (OR = 1.55; 95% CI = 1.13–2.14), PARK2 rs1333955 (OR = 1.36; 95% CI = 1.01–1.82) and SLC11A1 rs17235409 (OR = 2.34; 95% CI = 1.21–4.52) to be more likely present in BU patients than in controls, while the opposite was true in the case of IFNG rs3138557 (OR = 0.59; 95% CI = 0.40–0.85; S4 Table). Additionally, two SNPs PARK2 rs1040079 and SLC11A1 rs17235409 were studied in more than one setting and thus had their effects weighed (S4 Table). Overall, PARK2 rs1040079 showed a small to no significant association with BU prevalence (OR = 0.82; 95% CI = 0.67–1.00, I2 = 0%; Fig 2A), apparently more relevant when considering a recessive model of inheritance (OR = 0.68; 95% CI = 0.48–0.98; I2 = 0%; S3 Fig). As for SLC11A1 rs17235409, aggregation of studies resulted in a detrimental role for the minor allele (OR = 1.86; 95% CI = 1.25–2.77; I2 = 0%; Fig 2B), namely when modelled in dominance (OR = 2.10; 95% CI = 1.37–3.21; I2 = 0%) or overdominance (OR = 2.21; 95% CI = 1.45–3.39; I2 = 0%; S4 Fig).

thumbnail
Fig 2. Comparison of the frequency of allelic variants among BU patients and endemic controls.

The number of events indicates the frequency of the minor allele. (A) PARK2 rs1040079. (B) SLC11A1 rs17235409. Bias: + low risk;—high risk; ? unclear risk.

https://doi.org/10.1371/journal.pntd.0008161.g002

BCG vaccination

Only two RCTs attempted to scrutinize the role of BCG in protecting against BU [43,45], both concluding on a short-term positive effect for the vaccine (S5 Table). However, studies were moderately heterogeneous, demonstrating a negligible effect for the vaccine when analyzed under a random-effects model (OR = 0.63; 95% CI = 0.38–1.05; I2 = 56%; Fig 3).

thumbnail
Fig 3. Comparison of the frequency of BU among BCG vaccinated and non-vaccinated individuals in RCTs.

The number of events indicates BCG-vaccinated individuals. Bias: + low risk;—high risk; ? unclear risk.

https://doi.org/10.1371/journal.pntd.0008161.g003

Ten case-control studies determined BCG-vaccination status, mostly through BCG scar, although one did report the vaccine strains under use at the time of evaluation [28] (S5 Table). Results among authors were highly heterogeneous (Tau2 = 0.48; Chi2 = 126.03; p < 0.00001; I2 = 93%), with four studies showing a protective [18,29,37,42] (total n participants = 1953), five a neutral [16,30,31,35,38] (total n participants = 2338), and one a detrimental [10] (total n participants = 2742) role for the vaccine (S5 Fig). Thus, focus was placed exclusively on results derived from laboratory-confirmed cases, which despite still heterogenous (Tau2 = 0.07; Chi2 = 13.85; p = 0.03; I2 = 57%), suggested that the overall OR of BU acquisition is similar between vaccinated and unvaccinated individuals (OR = 0.79; 95% CI = 0.60–1.04; Fig 4).

thumbnail
Fig 4. Comparison of the frequency of BCG vaccination among laboratory-confirmed BU patients and endemic controls in case-control studies.

The number of events indicates BCG-vaccinated individuals. Bias: + low risk;—high risk; ? unclear risk.

https://doi.org/10.1371/journal.pntd.0008161.g004

HIV infection/co-infection

Three studies evaluated HIV serotype 1/2 status of case and control participants [16,20,44] (S6 Table). While the number of HIV patients was small, they were homogeneous in showing HIV infection being associated with higher BU prevalence (OR = 6.80; 95% CI = 2.33–19.85; I2 = 0%; I2 = 0%; Fig 5), regardless of the confirmation of BU diagnosis (OR = 6.40; 95% CI = 2.12–19.29; I2 = 0%; S6 Fig).

thumbnail
Fig 5. Comparison of frequency of HIV infection among BU patients and endemic controls.

The number of events indicates HIV+ individuals. Bias: + low risk;—high risk; ? unclear risk.

https://doi.org/10.1371/journal.pntd.0008161.g005

Risk of bias

The summary of the risk of bias among studies can be found in S7S9 Tables. Unclear effects of selection and detection biases should be considered when analyzing all studies, mainly due to the lack of incorporation of the social history and BCG vaccination and HIV infection statuses of BU patients, or the use of the unreliable BCG scar as a source of vaccination status check [47]. Considering a mean incubation period of M. ulcerans of 4.8 months, it is also impossible to warrant that the studies reviewed only included individuals free-of-outcome ad initium [48]. This timeframe was also considered in the evaluation of exposure periods, which was here established as minimum for the correct sorting of controls. Furthermore, literature supports that BU clinical diagnosis can be correctly achieved in over 90% of cases, although this value is dependent on the experience of the physician documenting the event [49]. This reinforces the assertions made by WHO and other authors to confirm BU cases by any of the specified laboratorial methods [2,49]. Finally, there appeared to be a reporting bias in the BCG analysis, as observed by the asymmetric funnel plot of the studies (S7 Fig).

Discussion

Demographic variables of BU patients have been reviewed by many authors, with no strict consensus having been achieved as to their role as a risk modifier for disease acquisition [7,50]. Results here obtained point to a bipartisan role of age and sex in the susceptibility to BU, as the disease is more frequently observed among children, particularly males, and in the elderly. Interestingly, these patterns can also be observed in other studies not fulfilling the inclusion criteria for this systematic review (S10 Table). In younger generations, it has been previously argued that these differences could be explained based on increased exposure to M. ulcerans, mainly due to the more erratic behavior that makes children more prone to skin lesions, as well as their likelihood to stay near aquatic environments [50]. However, more recent data encompassing worse outcomes of BU among the elderly casted a stronger suspicion on age as a modulator of intrinsic processes, likely immunological, a phenomenon that could be transversal across generations [41,51]. As such, while age and sex have the ability to influence the disease process, it is still uncertain at this point why.

Suspicion on a role for inheritance in susceptibility to BU can be traced to a case series from 1990, fostered by the question: why, in a community of individuals with similar environmental exposure, do some develop the disease while others do not [15,52]? Unfortunately, not all studies have used the same criteria to assess this variable, significantly increasing the chance of incorporating the confounding effects of environmental exposure (S6 Table). In this regard, when considering exclusively non-consanguine relationships, Sopoh et al. found the odds of acquiring BU to increase the susceptibility to the disease (adjusted OR = 5.5; 95% CI = 3.0–10.0), which altogether with previous evidence suggests BU resistance/susceptibility can be inherited [15,17,41].

Genetic association studies performed so far also point to a role for genetics in BU. More importantly, not only does the study of SNPs help define further risk factors for BU development, but it also reinforces findings from cellular and molecular research, as seen, for instance, with interferon-gamma [13,53]. From the SNPs that were addressed in more than one study, data revealed that the minor allele from SLC11A1 rs17235409 was associated with decreased prevalence of the disease. Besides its role as a divalent cation transport, SLC11A1 (solute carrier family 11, member 1) possesses several other immunomodulatory properties, having also been significantly associated with other mycobacterioses in another meta-analysis [54,55]. Likewise, parkin, encoded by PARK2, can mediate an antimycobacterial response through protein ubiquitination, a process critical for autophagic targeting of intracellular pathogens [56]. Despite the absence of effect estimated for PARK2 rs1040079 in BU acquisition, Capela et al. found that the allelic variant in PARK2 rs1333955 conferred susceptibility to the disease, when modelling for dominant model of genetic inheritance [12]. As of now, these SNPs could be considered for population screening and stratification. However, in the future, larger scale genomic studies may point to new variants that open avenues for novel therapeutic targets.

The WHO recently advocated BCG vaccination in BU endemic countries, based on the results of a systematic review and meta-analysis from Zimmermann et al. demonstrating a protective effect for BCG, at least when considering the RCTs included in the study [8,19]. By analyzing data of RCTs and case-control studies within a random-effects modelling, the present study suggests that BCG does not have a meaningful impact in protecting against BU. In fact, and similar to what was already observed in tuberculosis, the protection conferred by the vaccine appears to wane over time, being in BU apparently restricted to the first 6 months post-vaccination [43,57]. Moreover, from the 4-year follow-up made by Smith et al. it is possible to estimate that it is necessary to vaccinate at least 125 individuals in order to prevent one case of BU within this timeframe [43,45]. Still, whether stratification of these results by BCG strains could have exposed different results remains an interrogation, as this is a factor known to influence immune cellular response [58]. Thus, based on current evidence, the usefulness of BCG in BU appears to be essentially restricted to protecting against osteomyelitis forms of the disease [59,60].

Contrary to tuberculosis, in which HIV coinfection is well-known to foster active infection, evidence for such role in BU has been scarcer [7,61]. The studies gathered in this systematic review allow to draw a similar conclusion regarding BU development, further supported by estimates of a generally higher HIV prevalence among BU patients [21,62]. Indeed, not only does HIV favor the acquisition of BU, but Christinet et al. also described increased lesion size and severity, together with more prolonged wound healing periods in BU HIV+ patients with low CD4 T cell counts [62]. Thus, immune compromise by HIV infection hampers control of M. ulcerans, findings that not only have consequences at the populational level but may prove helpful to advance the understanding of the disease mechanisms.

This study represents the first meta-analysis on clinical risk factors for BU beyond BCG vaccination. Its major strengths rely on the broad search criteria employed, inclusion and ponderation of results from a large number of variables from both RCTs and observational studies, as well as the consideration of the BU-confirmation status of cases in the analyses. In contrast, it is limited by the level of evidence provided by the studies, the actual number of studies that addressed some of the risk factors here reviewed, as well by a lack of uniformity among definitions and study designs seen across the literature. Thus, some recommendations for more robust epidemiological studies are here proposed: consideration of the confirmation-status of BU patients throughout analyses; reporting and/or more thorough evaluation of the exposure variables here addressed; and the use of consistent cut-off values, namely for age groups, to allow data comparison.

Overall, this work contributes with the notion that there is a bimodal peak of incidence in BU, namely among children and older adults, although the underlying causes are yet to be unraveled. Furthermore, evidence suggests BCG vaccination is not suitable to prevent BU in the mid-long term, prompting even further for the investigation of better vaccination alternatives. Additionally, this review found a higher prevalence of the disease in HIV-infected individuals and also carriers of genetic polymorphisms in SLC11A1, both of which can be easily detected by low-cost methods and thus be used for BU risk stratification. Altogether, these findings contribute to the understanding of BU and should be regarded when advocating for new global health policies against this neglected tropical disease.

Supporting information

S1 Table. Sex-related comparisons in sex unmatched case-control studies.

https://doi.org/10.1371/journal.pntd.0008161.s003

(PDF)

S2 Table. Age-related comparisons in age unmatched case-control studies.

https://doi.org/10.1371/journal.pntd.0008161.s004

(PDF)

S3 Table. Family history of BU-related comparisons in case-control studies.

https://doi.org/10.1371/journal.pntd.0008161.s005

(PDF)

S4 Table. Allelic frequency-related comparisons in genetic association studies.

https://doi.org/10.1371/journal.pntd.0008161.s006

(PDF)

S5 Table. BCG vaccination-related comparisons in randomized clinical trials (RCT) and case-control studies.

https://doi.org/10.1371/journal.pntd.0008161.s007

(PDF)

S6 Table. Human Immunodeficiency Virus (HIV) infection-related comparisons in case-control studies.

https://doi.org/10.1371/journal.pntd.0008161.s008

(PDF)

S7 Table. Risk of bias among the cohort studies included in the systematic review.

https://doi.org/10.1371/journal.pntd.0008161.s009

(PDF)

S8 Table. Risk of bias among the case-control studies included in meta-analysis.

https://doi.org/10.1371/journal.pntd.0008161.s010

(PDF)

S9 Table. Risk of bias among the RCTs included in meta-analysis.

https://doi.org/10.1371/journal.pntd.0008161.s011

(PDF)

S10 Table. Demographic information from relevant observational and case series studies not eligible for systematic review.

Overall male:female ratio = 1.06.

https://doi.org/10.1371/journal.pntd.0008161.s012

(PDF)

S1 Fig. Comparison of the frequency of sexes among BU patients and endemic controls in sex unmatched case-control studies.

The number of events indicates female individuals. (A) All BU cases included. (B) BU laboratory-confirmed cases only. Bias: + low risk;—high risk; ? unclear risk.

https://doi.org/10.1371/journal.pntd.0008161.s013

(TIF)

S2 Fig. Comparison of the frequency of family history of BU among BU patients and endemic controls.

The number of events indicates patients with BU history in family members. (A) All BU cases included. (B) BU laboratory-confirmed cases only. Bias: + low risk;—high risk; ? unclear risk.

https://doi.org/10.1371/journal.pntd.0008161.s014

(TIF)

S3 Fig. Comparison of the frequency of PARK2 rs1040079 polymorphism among BU patients and endemic controls according to different genetic models of inheritance.

(A) Dominant. (B) Overdominant. (C) Recessive.

https://doi.org/10.1371/journal.pntd.0008161.s015

(TIF)

S4 Fig. Comparison of the frequency of SLC11A1 rs17235409 polymorphism among BU patients and endemic controls according to different genetic models of inheritance.

(A) Dominant. (B) Overdominant.

https://doi.org/10.1371/journal.pntd.0008161.s016

(TIF)

S5 Fig. Comparison of the frequency of BCG vaccination among BU patients and endemic controls in all of the included case-control studies.

The number of events indicates BCG-vaccinated individuals. Bias: + low risk;—high risk; ? unclear risk.

https://doi.org/10.1371/journal.pntd.0008161.s017

(TIF)

S6 Fig. Comparison of the frequency of HIV infection among BU laboratory-confirmed patients and endemic controls.

Bias: + low risk;—high risk; ? unclear risk.

https://doi.org/10.1371/journal.pntd.0008161.s018

(TIF)

S7 Fig. Funnel plot of BCG vaccination studies.

Each symbol is representative of a reference. SE–standard error.

https://doi.org/10.1371/journal.pntd.0008161.s019

(TIF)

Acknowledgments

The authors acknowledge Carlos Capela (University of Minho) for sharing his vast clinical knowledge, as well as Tiago Monteiro Brás (Thomas Jefferson University) and Torcato Meira (Columbia University) for their assistance during the search process.

References

  1. 1. Sizaire V, Nackers F, Comte E, Portaels F. Mycobacterium ulcerans infection: control, diagnosis, and treatment. Lancet Infect Dis. 2006;6: 288–296. pmid:16631549
  2. 2. Portaels F, World Health Organization. Laboratory diagnosis of buruli ulcer: a manual for health care providers. World Health Organization; 2014. Available: http://apps.who.int/iris/handle/10665/111738
  3. 3. World Health Organization. GHO | By category | Number of new reported cases—Data by country. [cited 20 Aug 2018]. Available: http://apps.who.int/gho/data/node.main.A1631
  4. 4. Douine M, Gozlan R, Nacher M, Dufour J, Reynaud Y, Elguero E, et al. Mycobacterium ulcerans infection (Buruli ulcer) in French Guiana, South America, 1969–2013: an epidemiological study. Lancet Planet Health. 2017;1: e65–e73. pmid:29851583
  5. 5. Merritt RW, Walker ED, Small PLC, Wallace JR, Johnson PDR, Benbow ME, et al. Ecology and transmission of Buruli ulcer disease: a systematic review. PLoS Negl Trop Dis. 2010;4: e911. pmid:21179505
  6. 6. Tomczyk S, Deribe K, Brooker SJ, Clark H, Rafique K, Knopp S, et al. Association between footwear use and neglected tropical diseases: a systematic review and meta-analysis. PLoS Negl Trop Dis. 2014;8: e3285. pmid:25393620
  7. 7. Jacobsen KH, Padgett JJ. Risk factors for Mycobacterium ulcerans infection. Int J Infect Dis IJID Off Publ Int Soc Infect Dis. 2010;14: e677–681. pmid:20185351
  8. 8. Zimmermann P, Finn A, Curtis N. Does BCG Vaccination Protect Against Nontuberculous Mycobacterial Infection? A Systematic Review and Meta-Analysis. J Infect Dis. 2018;218: 679–687. pmid:29635431
  9. 9. Vincent QB, Ardant M-F, Adeye A, Goundote A, Saint-André J-P, Cottin J, et al. Clinical epidemiology of laboratory-confirmed Buruli ulcer in Benin: a cohort study. Lancet Glob Health. 2014;2: e422–430. pmid:25103396
  10. 10. Debacker M, Aguiar J, Steunou C, Zinsou C, Meyers WM, Scott JT, et al. Mycobacterium ulcerans disease: role of age and gender in incidence and morbidity. Trop Med Int Health TM IH. 2004;9: 1297–1304. pmid:15598261
  11. 11. Marston BJ, Diallo MO, Horsburgh CR, Diomande I, Saki MZ, Kanga JM, et al. Emergence of Buruli ulcer disease in the Daloa region of Cote d’Ivoire. Am J Trop Med Hyg. 1995;52: 219–224. pmid:7694962
  12. 12. Capela C, Dossou AD, Silva-Gomes R, Sopoh GE, Makoutode M, Menino JF, et al. Genetic Variation in Autophagy-Related Genes Influences the Risk and Phenotype of Buruli Ulcer. PLoS Negl Trop Dis. 2016;10: e0004671. pmid:27128681
  13. 13. Bibert S, Bratschi MW, Aboagye SY, Collinet E, Scherr N, Yeboah-Manu D, et al. Susceptibility to Mycobacterium ulcerans Disease (Buruli ulcer) Is Associated with IFNG and iNOS Gene Polymorphisms. Front Microbiol. 2017;8: 1903. pmid:29046669
  14. 14. Stienstra Y, van der Werf TS, Oosterom E, Nolte IM, van der Graaf WTA, Etuaful S, et al. Susceptibility to Buruli ulcer is associated with the SLC11A1 (NRAMP1) D543N polymorphism. Genes Immun. 2006;7: 185–189. pmid:16395392
  15. 15. Sopoh GE, Barogui YT, Johnson RC, Dossou AD, Makoutodé M, Anagonou SY, et al. Family relationship, water contact and occurrence of Buruli ulcer in Benin. PLoS Negl Trop Dis. 2010;4: e746. pmid:20644620
  16. 16. Raghunathan PL, Whitney EAS, Asamoa K, Stienstra Y, Taylor TH, Amofah GK, et al. Risk factors for Buruli ulcer disease (Mycobacterium ulcerans Infection): results from a case-control study in Ghana. Clin Infect Dis Off Publ Infect Dis Soc Am. 2005;40: 1445–1453. pmid:15844067
  17. 17. Vincent QB, Belkadi A, Fayard C, Marion E, Adeye A, Ardant M-F, et al. Microdeletion on chromosome 8p23.1 in a familial form of severe Buruli ulcer. PLoS Negl Trop Dis. 2018;12: e0006429. pmid:29708969
  18. 18. Ahoua L, Guetta AN, Ekaza E, Bouzid S, N’Guessan R, Dosso M. Risk factors for Buruli ulcer in Côte d’Ivoire: Results of a case-control study, August 2001. Afr J Biotechnol. 2009;8. Available: https://www.ajol.info/index.php/ajb/article/view/59860
  19. 19. World Health Organization. BCG vaccines: WHO position paper–February 2018. Releve Epidemiol Hebd. 2018;93: 73–96.
  20. 20. Johnson RC, Nackers F, Glynn JR, de Biurrun Bakedano E, Zinsou C, Aguiar J, et al. Association of HIV infection and Mycobacterium ulcerans disease in Benin. AIDS Lond Engl. 2008;22: 901–903. pmid:18427211
  21. 21. Vincent QB, Ardant M-F, Marsollier L, Chauty A, Alcaïs A, Franco-Beninese Buruli Research Group (listed in appendix). HIV infection and Buruli ulcer in Africa. Lancet Infect Dis. 2014;14: 796–797. pmid:25164193
  22. 22. Review Manager (RevMan). Copenhagen: The Nordic Cochrane Centre: The Cochrane Collaboration; 2014.
  23. 23. Martorell-Marugan J, Toro-Dominguez D, Alarcon-Riquelme ME, Carmona-Saez P. MetaGenyo: a web tool for meta-analysis of genetic association studies. BMC Bioinformatics. 2017;18: 563. pmid:29246109
  24. 24. Huedo-Medina TB, Sánchez-Meca J, Marín-Martínez F, Botella J. Assessing heterogeneity in meta-analysis: Q statistic or I2 index? Psychol Methods. 2006;11: 193–206. pmid:16784338
  25. 25. Hedges LV, Vevea JL. Fixed- and Random-Effects Models in Meta-Analysis. Psychol Methods. 1998;3: 486–504.
  26. 26. Aromataris E, Munn Z. Joanna Briggs Institute Reviewer’s Manual. The Joanna Briggs Institute; 2017. Available: https://reviewersmanual.joannabriggs.org/
  27. 27. Roy Rosenzweig Center for History and New Media. Zotero. 2019. Available: www.zotero.org/
  28. 28. Debacker M, Portaels F, Aguiar J, Steunou C, Zinsou C, Meyers W, et al. Risk factors for Buruli ulcer, Benin. Emerg Infect Dis. 2006;12: 1325–1331. pmid:17073079
  29. 29. Phillips RO, Phanzu DM, Beissner M, Badziklou K, Luzolo EK, Sarfo FS, et al. Effectiveness of routine BCG vaccination on buruli ulcer disease: a case-control study in the Democratic Republic of Congo, Ghana and Togo. PLoS Negl Trop Dis. 2015;9: e3457. pmid:25569674
  30. 30. Quek TYJ, Athan E, Henry MJ, Pasco JA, Redden-Hoare J, Hughes A, et al. Risk factors for Mycobacterium ulcerans infection, southeastern Australia. Emerg Infect Dis. 2007;13: 1661–1666. pmid:18217548
  31. 31. Maman I, Tchacondo T, Kere AB, Piten E, Beissner M, Kobara Y, et al. Risk factors for Mycobacterium ulcerans infection (Buruli Ulcer) in Togo ─ a case-control study in Zio and Yoto districts of the maritime region. BMC Infect Dis. 2018;18: 48. pmid:29351741
  32. 32. Bratschi MW, Bolz M, Minyem JC, Grize L, Wantong FG, Kerber S, et al. Geographic distribution, age pattern and sites of lesions in a cohort of Buruli ulcer patients from the Mapé Basin of Cameroon. PLoS Negl Trop Dis. 2013;7: e2252. pmid:23785529
  33. 33. Aiga H, Amano T, Cairncross S, Adomako J, Domako JA, Nanas O-K, et al. Assessing water-related risk factors for Buruli ulcer: a case-control study in Ghana. Am J Trop Med Hyg. 2004;71: 387–392. pmid:15516631
  34. 34. Johnson PDR, Azuolas J, Lavender CJ, Wishart E, Stinear TP, Hayman JA, et al. Mycobacterium ulcerans in mosquitoes captured during outbreak of Buruli ulcer, southeastern Australia. Emerg Infect Dis. 2007;13: 1653–1660. pmid:18217547
  35. 35. Kenu E, Nyarko KM, Seefeld L, Ganu V, Käser M, Lartey M, et al. Risk factors for buruli ulcer in Ghana-a case control study in the Suhum-Kraboa-Coaltar and Akuapem South Districts of the eastern region. PLoS Negl Trop Dis. 2014;8: e3279. pmid:25411974
  36. 36. Landier J, Fontanet A, Texier G. Defining and targeting high-risk populations in Buruli ulcer. Lancet Glob Health. 2014;2: e629. pmid:25442683
  37. 37. N’krumah RTAS, Koné B, Tiembre I, Cissé G, Pluschke G, Tanner M, et al. Socio-Environmental Factors Associated with the Risk of Contracting Buruli Ulcer in Tiassalé, South Côte d’Ivoire: A Case-Control Study. PLoS Negl Trop Dis. 2016;10: e0004327. pmid:26745723
  38. 38. Nackers F, Dramaix M, Johnson RC, Zinsou C, Robert A, DE Biurrun Bakedano E, et al. BCG vaccine effectiveness against Buruli ulcer: a case-control study in Benin. Am J Trop Med Hyg. 2006;75: 768–774. pmid:17038709
  39. 39. Nackers F, Tonglet R, Slachmuylder V, Johnson RC, Robert A, Zinsou C, et al. Association between haemoglobin variants S and C and Mycobacterium ulcerans disease (Buruli ulcer): a case-control study in Benin. Trop Med Int Health TM IH. 2007;12: 511–518. pmid:17445142
  40. 40. Nackers F, Johnson RC, Glynn JR, Zinsou C, Tonglet R, Portaels F. Environmental and health-related risk factors for Mycobacterium ulcerans disease (Buruli ulcer) in Benin. Am J Trop Med Hyg. 2007;77: 834–836. pmid:17984337
  41. 41. O’Brien DP, Wynne JW, Buultjens AH, Michalski WP, Stinear TP, Friedman ND, et al. Exposure Risk for Infection and Lack of Human-to-Human Transmission of Mycobacterium ulcerans Disease, Australia. Emerg Infect Dis. 2017;23: 837–840. pmid:28418294
  42. 42. Pouillot R, Matias G, Wondje CM, Portaels F, Valin N, Ngos F, et al. Risk factors for buruli ulcer: a case control study in Cameroon. PLoS Negl Trop Dis. 2007;1: e101. pmid:18160977
  43. 43. Smith PG, Revill WD, Lukwago E, Rykushin YP. The protective effect of BCG against Mycobacterium ulcerans disease: a controlled trial in an endemic area of Uganda. Trans R Soc Trop Med Hyg. 1976;70: 449–457. pmid:841647
  44. 44. Stienstra Y, van der Werf TS, van der Graaf WTA, Secor WE, Kihlstrom SL, Dobos KM, et al. Buruli ulcer and schistosomiasis: no association found. Am J Trop Med Hyg. 2004;71: 318–321. pmid:15381813
  45. 45. Uganda Buruli Group. BCG vaccination against mycobacterium ulcerans infection (Buruli ulcer). First results of a trial in Uganda. Lancet Lond Engl. 1969;1: 111–115.
  46. 46. Uganda Buruli Group. Epidemiology of Mycobacterium ulcerans infection (Buruli ulcer) at Kinyara, Uganda. Trans R Soc Trop Med Hyg. 1971;65: 763–775. pmid:5157438
  47. 47. Dansereau E, Brown D, Stashko L, Danovaro-Holliday MC. A systematic review of the agreement of recall, home-based records, facility records, BCG scar, and serology for ascertaining vaccination status in low and middle-income countries. Gates Open Res. 2019;3: 923.
  48. 48. Loftus MJ, Trubiano JA, Tay EL, Lavender CJ, Globan M, Fyfe JAM, et al. The incubation period of Buruli ulcer (Mycobacterium ulcerans infection) in Victoria, Australia—Remains similar despite changing geographic distribution of disease. PLoS Negl Trop Dis. 2018;12: e0006323. pmid:29554096
  49. 49. Eddyani M, Sopoh GE, Ayelo G, Brun LVC, Roux J-J, Barogui Y, et al. Diagnostic Accuracy of Clinical and Microbiological Signs in Patients With Skin Lesions Resembling Buruli Ulcer in an Endemic Region. Clin Infect Dis Off Publ Infect Dis Soc Am. 2018;67: 827–834. pmid:29538642
  50. 50. Röltgen K, Pluschke G. Buruli Ulcer: History and Disease Burden. In: Pluschke G, Röltgen K, editors. Buruli Ulcer: Mycobacterium Ulcerans Disease. Cham: Springer International Publishing; 2019. pp. 1–41. https://doi.org/10.1007/978-3-030-11114-4_1 pmid:32091710
  51. 51. Fevereiro J, Fraga AG, Pedrosa J. The Immunology of Buruli Ulcer. In: Pluschke G, Röltgen K, editors. Buruli Ulcer: Mycobacterium Ulcerans Disease. Cham: Springer International Publishing; 2019. pp. 135–158. https://doi.org/10.1007/978-3-030-11114-4_8 pmid:32091712
  52. 52. Muelder K, Nourou A. Buruli ulcer in Benin. Lancet Lond Engl. 1990;336: 1109–1111.
  53. 53. Torrado E, Fraga AG, Logarinho E, Martins TG, Carmona JA, Gama JB, et al. IFN-gamma-dependent activation of macrophages during experimental infections by Mycobacterium ulcerans is impaired by the toxin mycolactone. J Immunol Baltim Md 1950. 2010;184: 947–955. pmid:20008288
  54. 54. Archer NS, Nassif NT, O’Brien BA. Genetic variants of SLC11A1 are associated with both autoimmune and infectious diseases: systematic review and meta-analysis. Genes Immun. 2015;16: 275–283. pmid:25856512
  55. 55. Wessling-Resnick M. Nramp1 and Other Transporters Involved in Metal Withholding during Infection. J Biol Chem. 2015;290: 18984–18990. pmid:26055722
  56. 56. Manzanillo PS, Ayres JS, Watson RO, Collins AC, Souza G, Rae CS, et al. The ubiquitin ligase parkin mediates resistance to intracellular pathogens. Nature. 2013;501: 512–516. pmid:24005326
  57. 57. Nguipdop-Djomo P, Heldal E, Rodrigues LC, Abubakar I, Mangtani P. Duration of BCG protection against tuberculosis and change in effectiveness with time since vaccination in Norway: a retrospective population-based cohort study. Lancet Infect Dis. 2016;16: 219–226. pmid:26603173
  58. 58. Ritz N, Dutta B, Donath S, Casalaz D, Connell TG, Tebruegge M, et al. The influence of bacille Calmette-Guerin vaccine strain on the immune response against tuberculosis: a randomized trial. Am J Respir Crit Care Med. 2012;185: 213–222. pmid:22071384
  59. 59. Portaels F, Aguiar J, Debacker M, Guédénon A, Steunou C, Zinsou C, et al. Mycobacterium bovis BCG vaccination as prophylaxis against Mycobacterium ulcerans osteomyelitis in Buruli ulcer disease. Infect Immun. 2004;72: 62–65. pmid:14688081
  60. 60. Pommelet V, Vincent QB, Ardant M-F, Adeye A, Tanase A, Tondeur L, et al. Findings in patients from Benin with osteomyelitis and polymerase chain reaction-confirmed Mycobacterium ulcerans infection. Clin Infect Dis Off Publ Infect Dis Soc Am. 2014;59: 1256–1264. pmid:25048846
  61. 61. Diedrich CR, O’Hern J, Wilkinson RJ. HIV-1 and the Mycobacterium tuberculosis granuloma: A systematic review and meta-analysis. Tuberc Edinb Scotl. 2016;98: 62–76. pmid:27156620
  62. 62. Christinet V, Comte E, Ciaffi L, Odermatt P, Serafini M, Antierens A, et al. Impact of human immunodeficiency virus on the severity of buruli ulcer disease: results of a retrospective study in cameroon. Open Forum Infect Dis. 2014;1: ofu021. pmid:25734094