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PCR-Based Techniques for Leprosy Diagnosis: From the Laboratory to the Clinic

  • Alejandra Nóbrega Martinez,

    Current address: Divisions of Bacteriology and Parasitology, Tulane National Primate Research Center, Covington, Louisiana, United States of America.

    Affiliation Laboratório de Hanseníase, Instituto Oswaldo Cruz - Fiocruz, Rio de Janeiro, Rio de Janeiro, Brazil

  • Carolina Talhari,

    Affiliation Fundação Alfredo da Matta, Manaus, Amazonas, Brazil

  • Milton Ozório Moraes ,

    Affiliation Laboratório de Hanseníase, Instituto Oswaldo Cruz - Fiocruz, Rio de Janeiro, Rio de Janeiro, Brazil

  • Sinésio Talhari

    Affiliation Universidade Nilton Lins, Manaus, Amazonas, Brazil

PCR-Based Techniques for Leprosy Diagnosis: From the Laboratory to the Clinic

  • Alejandra Nóbrega Martinez, 
  • Carolina Talhari, 
  • Milton Ozório Moraes, 
  • Sinésio Talhari


In leprosy, classic diagnostic tools based on bacillary counts and histopathology have been facing hurdles, especially in distinguishing latent infection from active disease and diagnosing paucibacillary clinical forms. Serological tests and IFN-gamma releasing assays (IGRA) that employ humoral and cellular immune parameters, respectively, are also being used, but recent results indicate that quantitative PCR (qPCR) is a key technique due to its higher sensitivity and specificity. In fact, advances concerning the structure and function of the Mycobacterium leprae genome led to the development of specific PCR-based gene amplification assays for leprosy diagnosis and monitoring of household contacts. Also, based on the validation of point-of-care technologies for M. tuberculosis DNA detection, it is clear that the same advantages of rapid DNA detection could be observed in respect to leprosy. So far, PCR has proven useful in the determination of transmission routes, M. leprae viability, and drug resistance in leprosy. However, PCR has been ascertained to be especially valuable in diagnosing difficult cases like pure neural leprosy (PNL), paucibacillary (PB), and patients with atypical clinical presentation and histopathological features compatible with leprosy. Also, the detection of M. leprae DNA in different samples of the household contacts of leprosy patients is very promising. Although a positive PCR result is not sufficient to establish a causal relationship with disease outcome, quantitation provided by qPCR is clearly capable of indicating increased risk of developing the disease and could alert clinicians to follow these contacts more closely or even define rules for chemoprophylaxis.


Leprosy is a chronic infectious disease caused by M. leprae, a slow-growing intracellular mycobacteria with tropism for Schwann cell in nerves and macrophages in the skin. In some patients, the disease is challenging to diagnose since there is no gold-standard method to differentiate between infection and disease. Leprosy is also a neglected disease, being endemic in developing countries, where detection rates show only a slight trend toward a decrease in disease (or number of cases) in spite of good treatment and the efforts of the World Health Organization (WHO) to improve the quality of leprosy control programs [1]. It is accepted that transmission occurs from human to human through the upper airways, although intermediate hosts like armadillos may play a role in certain places, such as the United States [2]. It is generally held that untreated multibacillary (MB) patients are the most important source of transmission, which occurs when bacilli are spread—usually by airborne droplets from nasal and/or mouth. Hence, leprosy patients, especially those with high bacterial load, release billions of bacilli that can potentially contaminate their close relatives or household contacts. As a result, the contacts of leprosy patients are known to have a higher risk of illness than the general population. Surveillance of these contacts would be an easy control strategy to block transmission, as suggested by the World Health Organization.

However, the steady number of new cases of leprosy in endemic countries is thought to result from the perpetuating reservoir of M. leprae-infected contacts and/or from the difficulties of early clinical diagnosis. It has been shown that good surveillance of patients' contacts has increased the detection rate of less severe clinical presentations with lower bacteriological indices [3], [4].

Immunological tools to detect M. leprae are based on their ability to detect major unique components like phenolic glycolipid-I (PGL-I), specific proteins by means of monoclonal and polyclonal antibodies [5], [6], or T cell immune response as measured by IFNγ production [7], [8]. Notwithstanding, the development of good diagnostic tests for leprosy is halted by the diversity of the strength of the cellular and humoral responses, varying from high to low (non)responders. On one hand, a major difficulty concerns paucibacillary (PB) forms, in which bacilli or antibodies against it are not easily detected in most cases. These PB patients exhibit cell-mediated immunity, secreting high levels of IFNγ after in vitro stimulation with specific M. leprae antigens (or a peptide fraction). On the other hand, MB patients do not produce IFNγ in vitro but have high bacillary loads that are easily identified by PCR or anti-PGL-I detection. Concerning IFNγ release, one problem in early diagnosis is that most of the household contacts show a similar pattern of IFNγ secretion as that of PB patients [9]. Generally, contacts exhibit a sustained high production of IFNγ that is dependent on continuous exposure to an infective source, i.e., a MB or sometimes a PB patient.

Both serological and immunological tests have limitations, and neither one can be considered a reliable diagnostic tool. Nevertheless, it is known that experienced clinicians and well-equipped clinics with histopathological examinations and bacillary counts, along with other clinical tests, available can diagnose most of the cases. However, the lack of a gold standard test for leprosy and the inability to distinguish infected individuals from those exhibiting active disease makes leprosy diagnosis essentially based on clinical features. Given that recognition of the disease is required, late diagnosis is relatively frequent in many patients. In addition, the lack of a specific and sensitive test to determine whether the infection has progressed to active disease makes it difficult to interrupt the transmission chain and impairs leprosy control.

Detection by PCR of M. leprae DNA in difficult-to-diagnose cases favors correct diagnosis and the possibility of early identification. In fact, the development and constant improvement of molecular tests for leprosy diagnosis has revealed that clinical manifestations like pure neural leprosy (PNL) are much more common than originally thought [10][12]. Here, we review several studies that discuss PCR usefulness in the clinical practice, such as in indeterminate leprosy, with patients who have clinical signs of leprosy but no confirmation through routine tests and histopathology, in difficult-to-diagnose cases, and in early detection in household contacts (Box 1).

Box 1. There Is a Future for PCR in Leprosy Diagnosis

  • Surveillance of household contacts of leprosy patients favors early diagnosis of the disease.
  • Semiautomatic, large-scale, cost-affordable quantitative PCR (qPCR) could be used to screen high-risk contacts and indicate chemoprophylaxis;
  • qPCR can be used to diagnose leprosy in difficult-to-diagnose cases such as pure neural or atypical skin clinical presentations;
  • point-of-care molecular-based technologies are available and could be used for diagnosis of leprosy, among other neglected diseases.

Historical Aspects of Biochemical and Genetic Studies of M. leprae

Historically, along with the spectrum of clinical forms of leprosy, one of the problems in developing new diagnostic tests has been an inability to grow M. leprae in vitro. Initial studies of biochemical and molecular features of this mycobacteria species could be achieved only after the development of techniques for growing leprosy bacillus in the mouse footpad [13] and armadillos [14]. These models aided leprosy research, the development of new chemotherapeutic agents, and the confirmation of drug resistance and the antigenic and molecular structure of M. leprae.

The first methods to amplify M. leprae DNA, based on polymerase chain reaction (PCR), were developed a little longer than 20 years ago [15], [16]. Later, another wave of significant progress in understanding the molecular biology of M. leprae came about after the completion of the genome sequencing of the leprosy bacillus described by Cole and colleagues [17] came out, along with other mycobacterial genomes allowing comparisons [18]. Since then, bioinformatics and new-generation sequencing approaches have provided information capable of supporting studies aimed at a better understanding of M. leprae genetic diversity [19], [20]. In fact, it is astonishing that M. leprae has presented a very stable genome for a very long time. Samples recovered from skeletons are genetically conserved as compared to modern strains [21]. The information about M. leprae genomes also enabled isolation and characterization of genes and expression profiles. Recently, DNA microarrays shed light on M. leprae gene function and provided further understanding of the pathogenesis of leprosy [22][27]. In addition, these new technologies have proven useful in leprosy diagnosis, drug resistance detection, and for information about transmission and mycobacterial variability in high- and low-endemic areas [28][33]. Furthermore, a detailed review encloses information on pseudogenes, molecular epidemiology, and biology of M. leprae [34]; thus, these issues will not be covered here.

PCR as a Detection Tool

In the past 20 years, definitive identification of M. leprae has been possible through the development of methods for the extraction, amplification, and identification of M. leprae DNA in clinical specimens using PCR. This technique has been applied not only to skin biopsy samples, but also to several different types of specimens such as skin smears, nerves, urine, oral or nasal swabs, blood, and ocular lesions [11], [35][41]. Different sequences were used as targets for PCR, such as genes encoding the 36-kDa antigen [42], 18-kDa antigen [43], 65-kDa antigen [44], complex 85 [37], 16S rDNA [45], and the repetitive sequences [46] among other M. leprae genes. More recently, real-time PCR technology has improved detection, increasing sensitivity and specificity as it appears to be a robust tool for mycobacteria recognition in selected clinical situations, as well as for quantitation in experimental settings [37], [45], [47][50].

One of the first studies based on PCR was carried out in 1990 by Williams and colleagues They established a procedure for detecting M. leprae DNA in infected tissues [51]. The PCR test was specific and detected M. leprae DNA in biopsies from leprosy patients. The evolution of PCR, as evaluated by technical issues (time and handling) but also by molecular and clinical sensitivity, is remarkable. In the early 1990s, radioactive probes were required to increase PCR sensitivity, and, hence, to overcome problems inherent to radioactivity, nonradioactive probes were developed [43]. Also, nested PCR was introduced and employed to increase specificity and sensitivity, to avoid the use of radioactive probes, and to shorten the time required to obtain a result [44]. Both studies demonstrated the emerging potential of PCR technology in the rapid detection and definitive identification of small numbers of M. leprae in clinical specimens.

The quality and the quantity of the isolated nucleic acid as well as the PCR target product size had tremendous effects on the success of amplification methods. Therefore, several protocols have been described for purification and amplification of M. leprae DNA, RNA, or both. Extractions that do not involve any purification step, for example, can inhibit the polymerase reaction due to impurities in the extract, as described by de Wit in 1991 [52]. Nevertheless, methods employing commercial kits have been consistently used and seem to be effective [53], [54], although conditions to evaluate repeatability and other parameters to further explore the potential of the technique are still lacking. In parallel, extraction methods proved to be suitable for formalin-fixed samples and further amplification under certain conditions [55]. Samples can also be easily stored in 70% ethanol and FTA cards for M. leprae DNA detection [56] exhibiting similar recovery rates.

Furthermore, the size of the PCR fragment amplified has to be taken into account as adaptation of conventional [52], [57] to real-time PCR assays [47] requires shorter length amplicons. An overall assessment of the impact of the PCR technology in leprosy diagnosis can be observed in Table 1 using skin biopsy samples as an example. Also, irrespective of whether the detection method used is conventional or real-time PCR, smaller PCR products allow for better amplification efficiency from DNA extracted from either formalin- or ethanol-fixed or fresh tissues. In fact, an important advance has been the real-time PCR technology. This method allows direct quantitation of bacterial DNA content in clinical samples and has improved turnaround time and cost effectiveness (Table 1), permitting more reliable results. The procedure follows the general principle of PCR, and its key feature is that the amplified DNA or cDNA (complementary DNA) is quantitated as it accumulates in the reaction in real time after each amplification cycle. These real-time methods have improved slightly but consistently the analytical and clinical sensitivity when PB patients' samples were assessed in skin samples [37], [48]. In addition, analyses using real-time PCR showed that total DNA content estimated by molecular levels could be correlated to bacterial load, corroborating the clinical data, which can be useful to determine a molecular bacteriological index, helping to define the clinical form of patients [37], [48], [50]. Nevertheless, while PCR diagnosis is not needed for lepromatous patients with high bacillary load and high number of lesions, it is extremely helpful for the diagnosis of the already-mentioned situations such as clinical presentations with scarce number of M. leprae bacilli and difficult-to-diagnose patients.

Table 1. Selected results obtained by PCR assays tested in frozen and fresh skin biopsies from leprosy patients.

PCR for Diagnosis of Difficult Cases

Pure neural cases

PCR can aid in defining leprosy diagnosis in suspected patients with clinically suggestive or atypical lesions presenting with negative baciloscopy and inconclusive histopathology. This is true for primary neuritic or PNL patients, who are easily missed and misdirected since they do not exhibit cutaneous lesions [11]. Timely treatment is imperative in these cases because, once nerve fibrosis occurs, damage is permanent and irreversible. Ridley and Jopling (R&J) postulated that PNL might occur across the spectrum from borderline lepromatous (BL) to tuberculoid (TT) forms [58], but, in our experience, the PNL cases are indeterminate or borderline tuberculoid (BT) [59]. In fact, these patients cannot be classified according to the R&J system because of the absence of skin lesions and clear histopathological features in the nerve. Nevertheless, a general WHO classification (paucibacillary) is used as none of them present bacilli in the slit-skin smears. A careful investigation examining skin biopsies (areas of skin hypoesthesia) described the histopathological features in the cutaneous lesions of PNL cases [59]. The assessment of PNL skin biopsies showed histopathological features consistent with normal skin, although indeterminate or borderline tuberculoid histological alterations were also detected. However, analysis of patients' nerve biopsies often showed detectable bacilli using Wade staining. It is curious that, even in endemic countries, leprosy is assumed to be a dermatologic disorder. Therefore, it is quite challenging to diagnose PNL cases [10]. Neurologists are not expecting leprosy as a probable cause of peripheral neuropathy and, thus, laboratory techniques (i.e., histological evaluation, PCR from biopsy, and/or PGL-I in the serum) may be used along with pertinent clinical and electroneuromyographical data [12]. In clinical practice, PCR is very useful in detecting M. leprae DNA in nerve specimens that have been shown to be bacteriologically negative by other methods of detection. In fact, Jardim and coworkers [12] demonstrated that M. leprae infection in PNL cases is diagnosed most often by PCR, followed by anti-PGL-I antibodies and direct observation of the bacteria (acid-fast bacilli [AFB]). Hence, PCR is helpful and is being used as a confirmatory and diagnostic routine tool in difficult-to-diagnose cases such as PNL [60][62].

Differential diagnosis to other conditions

In an endemic country, leprosy is suspected in patients with anaesthesic lesions, although not necessarily so. PCR could be of immense help for dermatological differential diagnosis in hypochromic or granulomatous lesions, such as pityriasis alba, leishmaniasis, cutaneous tuberculosis (TB), and sarcoidosis, among other skin diseases in which pathological examination is inconclusive. There are few papers evaluating the application of PCR to solve this matter. Our retrospective analysis testing different gene targets (Ag 85B [37], sodA and 16S rRNA [45], and repetitive sequence [RLEP] [50]) using a panel of samples from patients previously diagnosed by pathologists and dermatologists, provided interesting information [63]. When we include a higher proportion of paucibacillary samples (single skin indeterminate and tuberculoid forms), rates of PCR positivity decrease, but we were able to ascertain 50% of sensitivity. Obviously, that is expected since leprosy diagnosis is challenging in exactly these situations. Also, a group of other dermatological diseases were included as a negative control group, and the results suggest [63] that some positive samples for PCR were misdiagnosed. These samples were defined initially as other dermatological diseases, but patients developed leprosy 10 years later, suggesting that PCR for M. leprae DNA could be a very early detection test for leprosy [63].

PCR for treatment monitoring

In 1991, de Wit and coworkers [52] validated a PCR assay based on the selective amplification of a 530-bp fragment of the gene encoding the proline-rich antigen of M. leprae using clinical samples. They were able to detect the presence of M. leprae DNA on frozen biopsy sections from all untreated AFB-positive patients and 56% of the treated AFB-negative patients. The authors believed that PCR positivity reflected the presence of viable bacilli at the time of biopsy since a strong host immune response could result in killing of M. leprae and breakdown or clearance of its DNA in negative PCR samples.

Subsequent studies confirmed that PCR technology could be useful both for diagnosis and for assessment of viable load, as a reduction in signals was found to correlate with loss of viability. A follow-up study using patient's biopsies confirmed that M. leprae is rapidly killed after one month of multidrug therapy (MDT) treatment since MB cases declined by 54.3% and PB cases by 61.8% of initial positivity rate [42]. However, because of the persistence of weak signals, in some cases a long time after effective treatment [64], [65], the authors concluded that DNA-based PCR assays lack the sensitivity to estimate any real impact of treatment on bacterial viability. Similarly, in 2001, Santos and colleagues [66] tested a PCR assay on different samples of leprosy patients that had completed MDT treatment. This PCR assay targeted a RLEP described previously and was able to detect M. leprae from hair bulb, blood, nasal secretion, lymph, and skin biopsy samples. Results demonstrated that 54.5% of the individuals were PCR positive in at least one of the samples 8 years after completion of MDT. However, it was not possible to draw final conclusions on the clinical significance of PCR positivity since assays were based on DNA detection and did not reflect viable bacilli.

To overcome this problem, several studies were conducted using reverse transcriptase-PCR (RT-PCR)-based assays for M. leprae viability estimation. It has been noted that an RNA-based test is likely to reflect only nucleic acids from living organisms, as the turnover rate of RNA is high, particularly in prokaryotes. Hence, methods based on a quantitative estimation of RNA levels in the tissues have been useful for monitoring therapeutic responses [67][69]. A PCR assay for monitoring bacterial clearance in leprosy patients during chemotherapy based on M. leprae 16S rRNA gene expression was described [67]. After 6 months of MDT, they found that 44% of MB patients and 4% of PB patients tested still showed viable bacilli.

However, this assay was based only on the 16S rRNA, a relatively stable RNA species under several conditions, and was unable to detect rapid killing of M. leprae. Also, given that 16S rRNA gene is a housekeeping gene, a major drawback of these previous works is the lack of a gene target to normalize the template as an indicator of bacterial numbers in the specimen. Thus, Martinez and coworkers [45] propose a real-time PCR integrated approach based on RNA/DNA ratios for viability determination, i.e., decrease of M. leprae-specific RNA is evaluated as a function of total M. leprae DNA content. Previous results demonstrated that a significant decrease in viability could be seen in vitro in as little as 48 hours post-treatment with rifampin. Also, analysis of human biopsies confirmed the correlation of MDT treatment and decline of gene expression level [45]. This new approach may be helpful in the follow-up of leprosy patients on treatment and determination of drug resistance [70]. Also, other researchers have been using the same approach to estimate the viability in M. ulcerans (Buruli ulcers) and also in pathogenic fungi [71], [72]. Interestingly, this method has been applied to estimate M. leprae viability in in vitro assays [73], [74].

A recent and similar approach to monitor the effectiveness of chemotherapy using hsp18 as the gene target was developed by Lini and coworkers [75]. The copy number of bacterial DNA and hsp18 mRNA was estimated from 47 leprosy patients during treatment using paraffin-embedded biopsy samples. A reduction in DNA and mRNA during chemotherapy was observed, and hsp18 mRNA could not be detected in patients who underwent 2 years of MDT. Ten years ago, WHO recommended shortening the treatment to 12 months, although no molecular studies compared both regimens. Anyways, since there are no clear epidemiological alterations in relapse rates as examples, it could be suggested that indeed all M. leprae is being killed after 12 months of treatment, although a considerable amount of M. leprae DNA remained in the skin after 2 years of MDT. Also, recent molecular epidemiological evidence indicates that reinfection is more common than relapse in second episodes of the disease emerging [76].

PCR for the study of leprosy transmission and household contact surveillance

It is clear that household contact examination and follow-up is a determinant of leprosy control [3], [4], [77]. The arsenal of laboratory exams to screen this population could increase detection and early diagnosis. Several findings about leprosy indicate that M. leprae transmission mainly occurs by airborne droplet inhalation of M. leprae. Therefore, for purposes of clinical practice, the application of PCR for detection of M. leprae DNA in nasal swab samples from healthy individuals and household contacts has been reported [36], [39], [78], [79]. Results provided evidence that a majority of MB patients carry M. leprae in their nasal mucosa and that carriage of M. leprae occurs among healthy people living in an area where leprosy is endemic [78][80]. In household contacts, detection of M. leprae DNA by PCR in nasal swabs does not infer whether the contact will progress to active disease. DNA detection rates in nasal swabs in contacts vary from 1 to 10% (Table 2), which sometimes depends on the clinical form of the index cases. The data are not conclusive because prospective studies enrolling high numbers of contacts are still lacking. However, the high positivity rates observed among healthy individuals (Table 2) question the feasibility of the use of PCR in this site to predict the risk of developing the disease. Nevertheless, it has been shown that positive PGL-I test among contacts can increase the risk of developing leprosy [81], [82]. More recently, a very interesting study indicates that, indeed, the risk of progressing to active disease increases if a contact tests positive for PCR in the blood [83]. Thus, it is likely that a PGL-I test in combination with PCR could help identify the population at highest risk among household contacts [84].

Table 2. Selected data showing PCR assays tested in nasal swabs or blood from healthy individuals and household contacts.

It is believed that humans are the only significant reservoir of infection in leprosy, but recent investigations reported the presence of M. leprae DNA in wild armadillos and environmental samples. Thus, studies in areas of high prevalence of the disease confirmed the presence of M. leprae in water samples in Indonesia [85] and soil in India [86] as potential sources of continued transmission of the disease. Also, Job and coworkers suggested that skin and nasal epithelia of untreated MB leprosy patients contribute to the shedding of M. leprae into the environment, which in turn increases the risk for household contacts [87]. In addition, Truman and collaborators [2] used whole-genome sequencing to show that wild armadillos and American patients with leprosy in the southern United States are infected with the same strain of M. leprae. They were able to confirm that about a third of the leprosy autochthonous cases that arise each year in the United States almost certainly result from contact with infected armadillos.

Technical Limitations and Future Perspectives of PCR-Mediated Leprosy Diagnosis

Although PCR could be a useful tool for the detection of subclinical infection, only a few investigations have consistently associated the presence of the M. leprae DNA with further development of the disease among household contacts [83]. However, PCR results associated with a serological test could improve the predictive value of PCR technology in leprosy diagnosis. In addition, the PCR-integrated approach based on RNA/DNA ratios for viability determination can be useful for assessment of infection rate with M. leprae within a population in the future. Earlier diagnosis of leprosy will be of great value in preventing more severe disease that may lead to disabilities. Chemotherapy at an early stage could preclude leprosy transmission and the consequences of late diagnosis.

In clinical practice, the detection of M. leprae by PCR in patients with negative baciloscopy or inconclusive histopathology would be of great value to define leprosy diagnosis. Thus, choosing the right target for an improvement in sensitivity is important. The use of a repetitive sequence as a PCR target DNA, for example, provides the advantage of higher sensitivity over other targets in the DNA because it is present at multiple sites in genomic DNA [88]. However, specificity of a repetitive sequence as a PCR target is an issue since we observed that it is lower than other assays. For this reason, although it seems encouraging, highest sensitivity has to be interpreted with great care. The RLEP gene target is highly conserved and, as a result, many homologous sequences may be present in other Mycobacterium species that have not been thoroughly investigated, generating false positive results, as reported for the M. tuberculosis IS6110 marker elsewhere [89]. So far, gene targets such as 16S and Ag85B could be considered a good cost-benefit ratio concerning specificity and sensitivity (Table 1) [63]. This also argues against results detecting “M. leprae” DNA in water or soil [85], [86].

For routine application of PCR, some operational aspects such as the invasive nature of the sample collection should be considered. Therefore, comparative studies of different types of clinical samples for leprosy diagnosis have been carried out. Less invasive samples such as blood, urine, nasal swab, hair bulbs, and, most importantly, slit-skin smears were accessed, and, although results were encouraging, they were less efficient than those obtained with skin biopsies; skin biopsies would be the best sample for household contacts screen if not for the ethical considerations [35], [90]. Nevertheless, amplification of M. leprae in blood samples, for example, gives inferior results in comparison to those using other types of clinical material [35]. Even though biopsy sampling of the lesion is obtained through an invasive method, it is the choice in most studies as it provides the highest PCR positivity rates.

So far, a well-characterized, commercial test for detection of M. leprae DNA in patients' samples is not available. Therefore, many labs continue to report results using their own definitions of sensitivity and specificity, and, in most cases, the results are not comparable across different clinical applications. Currently, several specific M. leprae genes of interest have been identified, and, thus, assays based on existing simple automated machines such as the GeneXpert assay for diagnosis of M. tuberculosis infection [91] could be developed for leprosy. The Xpert MTB/RIF detects DNA sequences specific for M. tuberculosis and rifampicin resistance by PCR and is a major advance for TB diagnostics, especially for multidrug-resistant (MDR) TB and HIV-associated TB. Additional new technologies for miniature “lab on a chip” [92] and lateral flow assays [93][95] are also progressing so quickly that such assays would be feasible at point–of-care to improve clinical management decisions on leprosy diagnosis.

No data exist concerning the relative performance of different laboratories and methods for M. leprae DNA detection. An external quality assurance study on diagnostic proficiency that includes certifying and publishing the results in a comparative and anonymous manner would be highly recommended for leprosy diagnosis. Validation of paramount issues like adequate clinical material, nucleic acid extraction methods, sensitivity, specificity, PCR inhibition, and control of contamination will assure a reliable diagnosis of the disease. Thus, comparative testing of characterized samples would be a direct way to identify weaknesses of individual laboratories or certain methods. Furthermore, the positive predictive value (PPV) is another means of evaluating the usefulness of a diagnostic test as it reveals the probability that a positive result reflects the underlying condition being tested for. Its value does, however, depend on the prevalence of the disease, which may vary. Similarly, the negative predictive value (NPV) determines the proportion of patients with negative results who are correctly diagnosed. Although very useful, these values are difficult to apply to leprosy diagnosis due to the lack of a true gold standard method.


Overall, extensive evaluation of PCR tests in field studies has shown that DNA-based PCR assays can be 100% specific, while the sensitivity ranges from 34 to 80% in patients with PB forms to greater than 90% in patients with MB forms of the disease (Table 1). Also, since finding M. leprae is crucial in the confirmatory diagnosis of early leprosy, the use of PCR technique to enhance the ascertainment of difficult cases such as early PB and PNL is advisable and important in reaching a definitive diagnosis (Box 2). Thus, performing PCR to detect M. leprae DNA in difficult-to-diagnose cases can be executed in thousands of samples, favoring early identification and early treatment and helping to interrupt the transmission chain. Moreover, definitions of M. leprae strains could be very helpful in leprosy transmission. Undoubtedly, there is a future for PCR-based methods in relation to leprosy since these methods provide options for confirmation of diagnosis, treatment follow-up, detection of resistance, and, especially, support for the diagnosis of difficult cases such as PNL and PB.

Box 2. Top Five Papers in the Field

  1. Reis EM, Araujo S, Lobato J, Neves AF, Costa AV, et al. (2013) Mycobacterium leprae DNA in peripheral blood may indicate a bacilli migration route and high-risk for leprosy onset. Clin Microbiol Infect. E-pub ahead of print. doi: 10.1111/1469-0691.12349
  2. Ezenduka C, Post E, John S, Suraj A, Namadi A, et al. (2012) Cost-effectiveness analysis of three leprosy case detection methods in Northern Nigeria. PLOS Negl Trop Dis 6: e1818.
  3. Martinez AN, Ribeiro-Alves M, Sarno EN, Moraes MO (2011) Evaluation of qPCR-based assays for leprosy diagnosis directly in clinical specimens. PLOS Negl Trop Dis 5: e1354.
  4. Truman RW, Andrews PK, Robbins NY, Adams LB, Krahenbuhl JL, et al. (2008) Enumeration of Mycobacterium leprae using real-time PCR. PLOS Negl Trop Dis 2: e328.
  5. Jardim MR, Antunes SL, Santos AR, Nascimento OJ, Nery JA, et al. (2003) Criteria for diagnosis of pure neural leprosy. J Neurol 250: 806–809.


  1. 1. Talhari S, Grossi MA, de Oliveira ML, Gontijo B, Talhari C, et al. (2012) Hansen's disease: a vanishing disease? Mem Inst Oswaldo Cruz 107 Suppl 1: 13–16.
  2. 2. Truman RW, Singh P, Sharma R, Busso P, Rougemont J, et al. (2011) Probable zoonotic leprosy in the southern United States. N Engl J Med 364: 1626–1633.
  3. 3. Hacker Mde A, Duppre NC, Nery JA, Sales AM, Sarno EN (2012) Characteristics of leprosy diagnosed through the surveillance of contacts: a comparison with index cases in Rio de Janeiro, 1987–2010. Mem Inst Oswaldo Cruz 107 Suppl 1: 49–54.
  4. 4. Ezenduka C, Post E, John S, Suraj A, Namadi A, et al. (2012) Cost-effectiveness analysis of three leprosy case detection methods in Northern Nigeria. PLOS Negl Trop Dis 6: e1818.
  5. 5. Duthie MS, Truman RW, Goto W, O'Donnell J, Hay MN, et al. (2011) Insight toward early diagnosis of leprosy through analysis of the developing antibody responses of Mycobacterium leprae-infected armadillos. Clin Vaccine Immunol 18: 254–259.
  6. 6. Spencer JS, Kim HJ, Wheat WH, Chatterjee D, Balagon MV, et al. (2011) Analysis of antibody responses to Mycobacterium leprae phenolic glycolipid I, lipoarabinomannan, and recombinant proteins to define disease subtype-specific antigenic profiles in leprosy. Clin Vaccine Immunol 18: 260–267.
  7. 7. Spencer JS, Dockrell HM, Kim HJ, Marques MA, Williams DL, et al. (2005) Identification of specific proteins and peptides in mycobacterium leprae suitable for the selective diagnosis of leprosy. J Immunol 175: 7930–7938.
  8. 8. Geluk A, Klein MR, Franken KL, van Meijgaarden KE, Wieles B, et al. (2005) Postgenomic approach to identify novel Mycobacterium leprae antigens with potential to improve immunodiagnosis of infection. Infect Immun 73: 5636–5644.
  9. 9. Martins MV, Guimaraes MM, Spencer JS, Hacker MA, Costa LS, et al. (2012) Pathogen-specific epitopes as epidemiological tools for defining the magnitude of Mycobacterium leprae transmission in areas endemic for leprosy. PLOS Negl Trop Dis 6: e1616.
  10. 10. Antunes SL, Chimelli L, Jardim MR, Vital RT, Nery JA, et al. (2012) Histopathological examination of nerve samples from pure neural leprosy patients: obtaining maximum information to improve diagnostic efficiency. Mem Inst Oswaldo Cruz 107: 246–253.
  11. 11. Jardim MR, Antunes SL, Santos AR, Nascimento OJ, Nery JA, et al. (2003) Criteria for diagnosis of pure neural leprosy. J Neurol 250: 806–809.
  12. 12. Jardim MR, Antunes SL, Simons B, Wildenbeest JG, Nery JA, et al. (2005) Role of PGL-I antibody detection in the diagnosis of pure neural leprosy. Lepr Rev 76: 232–240.
  13. 13. Shepard CC (1960) The Experimental Disease That Follows the Injection of Human Leprosy Bacilli into Foot-Pads of Mice. J Exp Med 112: 445–454.
  14. 14. Kirchheimer WF, Storrs EE (1971) Attempts to establish the armadillo (Dasypus novemcinctus Linn.) as a model for the study of leprosy. I. Report of lepromatoid leprosy in an experimentally infected armadillo. Int J Lepr Other Mycobact Dis 39: 693–702.
  15. 15. Woods SA, Cole ST (1989) A rapid method for the detection of potentially viable Mycobacterium leprae in human biopsies: a novel application of PCR. FEMS Microbiol Lett 53: 305–309.
  16. 16. Hartskeerl RA, de Wit MY, Klatser PR (1989) Polymerase chain reaction for the detection of Mycobacterium leprae. J Gen Microbiol 135: 2357–2364.
  17. 17. Cole ST, Eiglmeier K, Parkhill J, James KD, Thomson NR, et al. (2001) Massive gene decay in the leprosy bacillus. Nature 409: 1007–1011.
  18. 18. Cole ST, Brosch R, Parkhill J, Garnier T, Churcher C, et al. (1998) Deciphering the biology of Mycobacterium tuberculosis from the complete genome sequence. Nature 393: 537–544.
  19. 19. Monot M, Honore N, Garnier T, Araoz R, Coppee JY, et al. (2005) On the origin of leprosy. Science 308: 1040–1042.
  20. 20. Monot M, Honoré N, Garnier T, Zidane N, Sherafi D, et al. (2009) Comparative genomic and phylogeographic analysis of Mycobacterium leprae. Nat Genet 41: 1282–1289.
  21. 21. Schuenemann VJ, Singh P, Mendum TA, Krause-Kyora B, Jager G, et al. (2013) Genome-wide comparison of medieval and modern Mycobacterium leprae. Science 341: 179–183.
  22. 22. Akama T, Suzuki K, Tanigawa K, Nakamura K, Kawashima A, et al. (2010) Whole-genome expression analysis of Mycobacterium leprae and its clinical application. Jpn J Infect Dis 63: 387–392.
  23. 23. Akama T, Tanigawa K, Kawashima A, Wu H, Ishii N, et al. (2010) Analysis of Mycobacterium leprae gene expression using DNA microarray. Microb Pathog 49: 181–185.
  24. 24. Nakamura K, Akama T, Bang PD, Sekimura S, Tanigawa K, et al. (2009) Detection of RNA expression from pseudogenes and non-coding genomic regions of Mycobacterium leprae. Microb Pathog 47: 183–187.
  25. 25. Akama T, Suzuki K, Tanigawa K, Kawashima A, Wu H, et al. (2009) Whole-genome tiling array analysis of Mycobacterium leprae RNA reveals high expression of pseudogenes and noncoding regions. J Bacteriol 191: 3321–3327.
  26. 26. Williams DL, Slayden RA, Amin A, Martinez AN, Pittman TL, et al. (2009) Implications of high level pseudogene transcription in Mycobacterium leprae. BMC Genomics 10: 397.
  27. 27. Williams DL, Torrero M, Wheeler PR, Truman RW, Yoder M, et al. (2004) Biological implications of Mycobacterium leprae gene expression during infection. J Mol Microbiol Biotechnol 8: 58–72.
  28. 28. Fontes AN, Sakamuri RM, Baptista IM, Ura S, Moraes MO, et al. (2009) Genetic diversity of mycobacterium leprae isolates from Brazilian leprosy patients. Lepr Rev 80: 302–315.
  29. 29. Cardona-Castro N, Beltran-Alzate JC, Romero-Montoya IM, Melendez E, Torres F, et al. (2009) Identification and comparison of Mycobacterium leprae genotypes in two geographical regions of Colombia. Lepr Rev 80: 316–321.
  30. 30. Gillis T, Vissa V, Matsuoka M, Young S, Richardus JH, et al. (2009) Characterisation of short tandem repeats for genotyping Mycobacterium leprae. Lepr Rev 80: 250–260.
  31. 31. Shinde V, Newton H, Sakamuri RM, Reddy V, Jain S, et al. (2009) VNTR typing of Mycobacterium leprae in South Indian leprosy patients. Lepr Rev 80: 290–301.
  32. 32. Srisungnam S, Rudeeaneksin J, Lukebua A, Wattanapokayakit S, Pasadorn S, et al. (2009) Molecular epidemiology of leprosy based on VNTR typing in Thailand. Lepr Rev 80: 280–289.
  33. 33. Xing Y, Liu J, Sakamuri RM, Wang Z, Wen Y, et al. (2009) VNTR typing studies of Mycobacterium leprae in China: assessment of methods and stability of markers during treatment. Lepr Rev 80: 261–271.
  34. 34. Singh P, Cole ST (2011) Mycobacterium leprae: genes, pseudogenes and genetic diversity. Future Microbiol 6: 57–71.
  35. 35. Santos AR, De Miranda AB, Sarno EN, Suffys PN, Degrave WM (1993) Use of PCR-mediated amplification of Mycobacterium leprae DNA in different types of clinical samples for the diagnosis of leprosy. J Med Microbiol 39: 298–304.
  36. 36. Almeida EC, Martinez AN, Maniero VC, Sales AM, Duppre NC, et al. (2004) Detection of Mycobacterium leprae DNA by polymerase chain reaction in the blood and nasal secretion of Brazilian household contacts. Mem Inst Oswaldo Cruz 99: 509–511.
  37. 37. Martinez AN, Britto CF, Nery JA, Sampaio EP, Jardim MR, et al. (2006) Evaluation of real-time and conventional PCR targeting complex 85 genes for detection of Mycobacterium leprae DNA in skin biopsy samples from patients diagnosed with leprosy. J Clin Microbiol 44: 3154–3159.
  38. 38. Shamsi FA, Chaudhry IA, Moraes MO, Martinez AN, Riley FC (2007) Detection of Mycobacterium leprae in ocular tissues by histopathology and real-time polymerase chain reaction. Ophthalmic Res 39: 63–68.
  39. 39. de Wit MY, Douglas JT, McFadden J, Klatser PR (1993) Polymerase chain reaction for detection of Mycobacterium leprae in nasal swab specimens. J Clin Microbiol 31: 502–506.
  40. 40. Caleffi KR, Hirata RD, Hirata MH, Caleffi ER, Siqueira VL, et al. (2012) Use of the polymerase chain reaction to detect Mycobacterium leprae in urine. Braz J Med Biol Res 45: 153–157.
  41. 41. da Rosa FB, de Souza VC, de Almeida TA, do Nascimento VA, Vasquez FG, et al. (2013) Detection of Mycobacterium leprae in saliva and the evaluation of oral sensitivity in patients with leprosy. Mem Inst Oswaldo Cruz 108: 572–577.
  42. 42. Kampirapap K, Singtham N, Klatser PR, Wiriyawipart S (1998) DNA amplification for detection of leprosy and assessment of efficacy of leprosy chemotherapy. Int J Lepr Other Mycobact Dis 66: 16–21.
  43. 43. Scollard DM, Gillis TP, Williams DL (1998) Polymerase chain reaction assay for the detection and identification of Mycobacterium leprae in patients in the United States. Am J Clin Pathol 109: 642–646.
  44. 44. Plikaytis BB, Gelber RH, Shinnick TM (1990) Rapid and sensitive detection of Mycobacterium leprae using a nested-primer gene amplification assay. J Clin Microbiol 28: 1913–1917.
  45. 45. Martinez AN, Lahiri R, Pittman TL, Scollard D, Truman R, et al. (2009) Molecular determination of Mycobacterium leprae viability by use of real-time PCR. J Clin Microbiol 47: 2124–2130.
  46. 46. Adams LB, Pena MT, Sharma R, Hagge DA, Schurr E, et al. (2012) Insights from animal models on the immunogenetics of leprosy: a review. Mem Inst Oswaldo Cruz 107 Suppl 1: 197–208.
  47. 47. Kramme S, Bretzel G, Panning M, Kawuma J, Drosten C (2004) Detection and quantification of Mycobacterium leprae in tissue samples by real-time PCR. Med Microbiol Immunol 193: 189–193.
  48. 48. Rudeeaneksin J, Srisungngam S, Sawanpanyalert P, Sittiwakin T, Likanonsakul S, et al. (2008) LightCycler real-time PCR for rapid detection and quantitation of Mycobacterium leprae in skin specimens. FEMS Immunol Med Microbiol 54: 263–270.
  49. 49. Martinez AN, Ribeiro-Alves M, Sarno EN, Moraes MO (2011) Evaluation of qPCR-Based Assays for Leprosy Diagnosis Directly in Clinical Specimens. PLOS Negl Trop Dis 5: e1354.
  50. 50. Truman RW, Andrews PK, Robbins NY, Adams LB, Krahenbuhl JL, et al. (2008) Enumeration of Mycobacterium leprae using real-time PCR. PLOS Negl Trop Dis 2: e328.
  51. 51. Williams DL, Gillis TP, Booth RJ, Looker D, Watson JD (1990) The use of a specific DNA probe and polymerase chain reaction for the detection of Mycobacterium leprae. J Infect Dis 162: 193–200.
  52. 52. de Wit MY, Faber WR, Krieg SR, Douglas JT, Lucas SB, et al. (1991) Application of a polymerase chain reaction for the detection of Mycobacterium leprae in skin tissues. J Clin Microbiol 29: 906–910.
  53. 53. Wen Y, Xing Y, Yuan LC, Liu J, Zhang Y, et al. (2013) Whole-Blood Nested-PCR Amplification of M. leprae-Specific DNA for Early Diagnosis of Leprosy. Am J Trop Med Hyg 88: 918–922.
  54. 54. da Silva Rocha A, Cunha M, Diniz LM, Salgado C, Aires MA, et al. (2012) Drug and multidrug resistance among Mycobacterium leprae isolates from Brazilian relapsed leprosy patients. J Clin Microbiol 50: 1912–1917.
  55. 55. Morgado de Abreu MA, Roselino AM, Enokihara M, Nonogaki S, Prestes-Carneiro LE, et al. (2013) Mycobacterium leprae is identified in the oral mucosa from paucibacillary and multibacillary leprosy patients. Clin Microbiol Infect E-pub ahead of print. doi: 10.1111/1469-0691.12190.
  56. 56. Aye KS, Matsuoka M, Kai M, Kyaw K, Win AA, et al. (2011) FTA card utility for PCR detection of Mycobacterium leprae. Jpn J Infect Dis 64: 246–248.
  57. 57. Goulart IM, Cardoso AM, Santos MS, Goncalves MA, Pereira JE, et al. (2007) Detection of Mycobacterium leprae DNA in skin lesions of leprosy patients by PCR may be affected by amplicon size. Arch Dermatol Res 299: 267–271.
  58. 58. Ridley DS, Jopling WH (1966) Classification of leprosy according to immunity. A five-group system. Int J Lepr Other Mycobact Dis 34: 255–273.
  59. 59. Menicucci LA, Miranda A, Antunes SL, Jardim MR, da Costa Nery JA, et al. (2005) Microscopic leprosy skin lesions in primary neuritic leprosy. J Am Acad Dermatol 52: 648–652.
  60. 60. Bezerra Da Cunha FM, Werneck MC, Scola RH, Werneck LC (2006) Pure neural leprosy: diagnostic value of the polymerase chain reaction. Muscle Nerve 33: 409–414.
  61. 61. Medeiros MF, Jardim MR, Vital RT, Costa Nery JA, Sales AM, et al. (2013) An Attempt to Improve Pure Neural Leprosy Diagnosis Using Immunohistochemistry Tests in Peripheral Nerve Biopsy Specimens. Appl Immunohistochem Mol Morphol E-pub ahead of print. doi: 10.1097/PAI.0b013e31828dc70c.
  62. 62. Rodriguez G, Pinto R, Gomez Y, Rengifo ML, Estrada OL, et al. (2013) Pure neuritic leprosy in patients from a high endemic region of Colombia. Lepr Rev 84: 41–50.
  63. 63. Martinez AN, Ribeiro-Alves M, Sarno EN, Moraes MO (2011) Evaluation of qPCR-based assays for leprosy diagnosis directly in clinical specimens. PLOS Negl Trop Dis 5: e1354.
  64. 64. Katoch VM (2002) Advances in the diagnosis and treatment of leprosy. Expert Rev Mol Med 4: 1–14.
  65. 65. Singh HB, Katoch K, Natrajan M, Sharma RK, Gupta UD, et al. (1999) Effect of treatment on PCR positivity in multibacillary leprosy patients treated with conventional and newer drugs ofloxacin and minocycline. Acta Leprol 11: 179–182.
  66. 66. Santos AR, Balassiano V, Oliveira ML, Pereira MA, Santos PB, et al. (2001) Detection of Mycobacterium leprae DNA by polymerase chain reaction in the blood of individuals, eight years after completion of anti-leprosy therapy. Mem Inst Oswaldo Cruz 96: 1129–1133.
  67. 67. Phetsuksiri B, Rudeeaneksin J, Supapkul P, Wachapong S, Mahotarn K, et al. (2006) A simplified reverse transcriptase PCR for rapid detection of Mycobacterium leprae in skin specimens. FEMS Immunol Med Microbiol 48: 319–328.
  68. 68. Kurabachew M, Wondimu A, Ryon JJ (1998) Reverse transcription-PCR detection of Mycobacterium leprae in clinical specimens. J Clin Microbiol 36: 1352–1356.
  69. 69. Jadhav RS, Kamble RR, Shinde VS, Edward S, Edward VK (2005) Use of reverse transcription polymerase chain reaction for the detection of Mycobacterium leprae in the slit-skin smears of leprosy patients. Indian J Lepr 77: 116–127.
  70. 70. Davis GL, Ray NA, Lahiri R, Gillis TP, Krahenbuhl JL, et al. (2013) Molecular Assays for Determining Mycobacterium leprae Viability in Tissues of Experimentally Infected Mice. PLOS Negl Trop Dis 7: e2404.
  71. 71. Beissner M, Symank D, Phillips RO, Amoako YA, Awua-Boateng NY, et al. (2012) Detection of viable Mycobacterium ulcerans in clinical samples by a novel combined 16S rRNA reverse transcriptase/IS2404 real-time qPCR assay. PLOS Negl Trop Dis 6: e1756.
  72. 72. Xie Z, Thompson A, Kashleva H, Dongari-Bagtzoglou A (2011) A quantitative real-time RT-PCR assay for mature C. albicans biofilms. BMC Microbiol 11: 93.
  73. 73. Liu PT, Wheelwright M, Teles R, Komisopoulou E, Edfeldt K, et al. (2012) MicroRNA-21 targets the vitamin D-dependent antimicrobial pathway in leprosy. Nat Med 18: 267–273.
  74. 74. Teles RM, Graeber TG, Krutzik SR, Montoya D, Schenk M, et al. (2013) Type I interferon suppresses type II interferon-triggered human anti-mycobacterial responses. Science 339: 1448–1453.
  75. 75. Lini N, Shankernarayan NP, Dharmalingam K (2009) Quantitative real-time PCR analysis of Mycobacterium leprae DNA and mRNA in human biopsy material from leprosy and reactional cases. J Med Microbiol 58: 753–759.
  76. 76. da Silva Rocha A, Cunha Dos Santos AA, Pignataro P, Nery JA, de Miranda AB, et al. (2011) Genotyping of Mycobacterium leprae from Brazilian leprosy patients suggests the occurrence of reinfection or of bacterial population shift during disease relapse. J Med Microbiol 60: 1441–1446.
  77. 77. Sarno EN, Duppre NC, Sales AM, Hacker MA, Nery JA, et al. (2012) Leprosy exposure, infection and disease: a 25-year surveillance study of leprosy patient contacts. Mem Inst Oswaldo Cruz 107: 1054–1059.
  78. 78. Lavania M, Turankar RP, Karri S, Chaitanya VS, Sengupta U, et al. (2012) Cohort study of the seasonal effect on nasal carriage and the presence of Mycobacterium leprae in an endemic area in the general population. Clin Microbiol Infect 19: 970–974.
  79. 79. Beyene D, Aseffa A, Harboe M, Kidane D, Macdonald M, et al. (2003) Nasal carriage of Mycobacterium leprae DNA in healthy individuals in Lega Robi village, Ethiopia. Epidemiol Infect 131: 841–848.
  80. 80. Klatser PR, van Beers S, Madjid B, Day R, de Wit MY (1993) Detection of Mycobacterium leprae nasal carriers in populations for which leprosy is endemic. J Clin Microbiol 31: 2947–2951.
  81. 81. Duppre NC, Camacho LA, Sales AM, Illarramendi X, Nery JA, et al. (2012) Impact of PGL-I seropositivity on the protective effect of BCG vaccination among leprosy contacts: a cohort study. PLOS Negl Trop Dis 6: e1711.
  82. 82. Hacker MA, Sales AM, Illarramendi X, Nery JA, Duppre NC, et al. (2012) A profile of patients treated at a national leprosy outpatient referral clinic in Rio de Janeiro, Brazil, 1986–2007. Rev Panam Salud Publica 31: 485–491.
  83. 83. Reis EM, Araujo S, Lobato J, Neves AF, Costa AV, et al. (2013) Mycobacterium leprae DNA in peripheral blood may indicate a bacilli migration route and high-risk for leprosy onset. Clin Microbiol Infect E-pub ahead of print. doi: 10.1111/1469-0691.12349.
  84. 84. Araujo S, Lobato J, Reis Ede M, Souza DO, Goncalves MA, et al. (2012) Unveiling healthy carriers and subclinical infections among household contacts of leprosy patients who play potential roles in the disease chain of transmission. Mem Inst Oswaldo Cruz 107 Suppl 1: 55–59.
  85. 85. Lavania M, Katoch K, Katoch VM, Gupta AK, Chauhan DS, et al. (2008) Detection of viable Mycobacterium leprae in soil samples: insights into possible sources of transmission of leprosy. Infect Genet Evol 8: 627–631.
  86. 86. Matsuoka M, Izumi S, Budiawan T, Nakata N, Saeki K (1999) Mycobacterium leprae DNA in daily using water as a possible source of leprosy infection. Indian J Lepr 71: 61–67.
  87. 87. Job CK, Jayakumar J, Kearney M, Gillis TP (2008) Transmission of leprosy: a study of skin and nasal secretions of household contacts of leprosy patients using PCR. Am J Trop Med Hyg 78: 518–521.
  88. 88. Kang TJ, Kim SK, Lee SB, Chae GT, Kim JP (2003) Comparison of two different PCR amplification products (the 18-kDa protein gene vs. RLEP repetitive sequence) in the diagnosis of Mycobacterium leprae. Clin Exp Dermatol 28: 420–424.
  89. 89. Kent L, McHugh TD, Billington O, Dale JW, Gillespie SH (1995) Demonstration of homology between IS6110 of Mycobacterium tuberculosis and DNAs of other Mycobacterium spp.? J Clin Microbiol 33: 2290–2293.
  90. 90. Santos AR, Goes Filho JT, Nery JA, Duppre NC, Gallo ME, et al. (1995) Evaluation of PCR mediated DNA amplification in non-invasive biological specimens for subclinical detection of Mycobacterium leprae. FEMS Immunol Med Microbiol 11: 113–120.
  91. 91. Boehme CC, Nabeta P, Hillemann D, Nicol MP, Shenai S, et al. (2010) Rapid molecular detection of tuberculosis and rifampin resistance. N Engl J Med 363: 1005–1015.
  92. 92. Dockrell HM (2011) Keep the faith–leprosy still needs new diagnostic tools and laboratory research. Lepr Rev 82: 340–343.
  93. 93. Hungria EM, de Oliveira RM, de Souza AL, Costa MB, de Souza VN, et al. (2012) Seroreactivity to new Mycobacterium leprae protein antigens in different leprosy-endemic regions in Brazil. Mem Inst Oswaldo Cruz 107 Suppl 1: 104–111.
  94. 94. Duthie MS, Hay MN, Rada EM, Convit J, Ito L, et al. (2011) Specific IgG antibody responses may be used to monitor leprosy treatment efficacy and as recurrence prognostic markers. Eur J Clin Microbiol Infect Dis 30: 1257–1265.
  95. 95. Lobato J, Costa MP, Reis Ede M, Goncalves MA, Spencer JS, et al. (2011) Comparison of three immunological tests for leprosy diagnosis and detection of subclinical infection. Lepr Rev 82: 389–401.
  96. 96. Wichitwechkarn J, Karnjan S, Shuntawuttisettee S, Sornprasit C, Kampirapap K, et al. (1995) Detection of Mycobacterium leprae infection by PCR. J Clin Microbiol 33: 45–49.
  97. 97. Williams DL, Gillis TP, Fiallo P, Job CK, Gelber RH, et al. (1992) Detection of Mycobacterium leprae and the potential for monitoring antileprosy drug therapy directly from skin biopsies by PCR. Mol Cell Probes 6: 401–410.
  98. 98. Yoon KH, Cho SN, Lee MK, Abalos RM, Cellona RV, et al. (1993) Evaluation of polymerase chain reaction amplification of Mycobacterium leprae-specific repetitive sequence in biopsy specimens from leprosy patients. J Clin Microbiol 31: 895–899.
  99. 99. Banerjee S, Sarkar K, Gupta S, Mahapatra PS, Guha S, et al. (2010) Multiplex PCR technique could be an alternative approach for early detection of leprosy among close contacts–a pilot study from India. BMC Infect Dis 10: 252.
  100. 100. Cabral PB, Junior JE, Macedo AC, Alves AR, Goncalves TB, et al. (2013) Anti-PGL1 salivary IgA/IgM, serum IgG/IgM, and nasal Mycobacterium leprae DNA in individuals with household contact with leprosy. Int J Infect Dis 17: e1005–1010.