Molecular Surveillance of Antimicrobial Resistance of Mycobacterium leprae from Leprosy Patients in Zhejiang Province, China.

Purpose: Reports on antimicrobial resistance (AMR) of Mycobacterium leprae (M. leprae) in Zhejiang Province are limited. Thus, this study aimed to investigate the drug resistance of new leprosy cases within several years and analyse the emergence of AMR mutations from Zhejiang Province. Methods: This study enrolled 34 leprosy cases in Zhejiang Province, China, from 2018 to 2021. Gene mutation of WHO-recommended DRDRs (folP1, rpoB and gyrA) and genes of compensatory AMR-associated DRDRs, including nth, rpoA, rpoC, gyrB and 23S rRNA, were detected by amplification. Clinical data analysis was performed to investigate the epidemiological association of leprosy. Results: Of the 34 samples, 2 (5.9%) strains showed drug resistance, which were mutated to dapsone and ofloxacin, separately. Two single mutations in gyrB were detected in different strains (5.9%), whereas one of the rpoC mutation was also detected in one strain each (2.9%), which were proved to be polymorphs. No correlation of drug resistance proportion was identified in male vs female, nerve vs no nerve involvement, deformity vs no deformity and reaction vs non-reaction cases. Conclusion: Results showed well control of leprosy patients in Zhejiang Province. Gene mutations of WHO-recommended DRDRs folP1 and gyrA confirmed the resistance to dapsone and ofloxacin. Compensatory AMR-associated mutations confirmed to be polymorphs still require further study to determine their phenotypic outcomes in M. leprae. The results demonstrated that drug-resistant strains are not epidemic in this area. Given the few cases of leprosy, analysing the AMR of M. leprae in Zhejiang Province more comprehensively is difficult. However, regular MDT treatment and population management in the early stage may contribute to the low prevalence of leprosy.

Utility of Multi-target Nested PCR and ELISPOT Assays for the Detection of Paucibacillary Leprosy: A Possible Conclusion of Clinical Laboratory Misdiagnosis.

The diagnosis of paucibacillary (PB) leprosy often possesses a diagnostic challenge, especially for pure neuritic and lesser skin lesions with the zero bacillary load, requiring a sensitive and accurate diagnostic tool. We have included 300 clinically diagnosed new leprosy cases (comprising 98 PB cases) and analyzed the sensitivity and specificity of PB leprosy cases by nested PCR with folP, gyrA, rpoB, RLEP, and 16SrRNA and Enzyme-linked Immunospot Assay test (ELISPOT) with MMPII, NDO-BSA, and LID-1 antigens by detecting interferon gamma (IFN-γ) release. The overall positivity rates of genes tested in 300 clinical specimens were identified as 55% of 16SrRNA, 59% of RLEP, 59.3% of folP, 57.3% of rpoB, 61% of gyrA while 90% of nested folP, 92.6% of nested rpoB, and 95% of nested gyrA, and 285 (95%) of at least one gene positive cases. For PB specimens, 95% PCR positivity was achieved by three tested genes in nested PCR. The data obtained from ELISPOT for three antigens were analyzed for IFN-γ expression with 600 subjects. Among 98 PB leprosy cases, the sensitivity of MMP II, LID-1, and NDO-BSA was 90%, 87%, and 83%, respectively, and the specificity was 90%, 91%, and 86%, respectively. The total number of cases positive for at least one antigen was 90 (91.8%) in PB, which is significantly higher than that in multibacillary (MB) leprosy (56.7%). The combination of multi-targets nested PCR and ELISPOT assay provides a specific tool to early clinical laboratory diagnosis of PB leprosy cases. The two assays are complementary to each other and beneficial for screening PB patients.

Temporal-spatial distribution characteristics of leprosy: A new challenge for leprosy prevention and control in Zhejiang, China.

BACKGROUND: After the elimination of leprosy in 1995, there were 10-30 newly detected leprosy cases every year in Zhejiang Province, and the epidemiological characteristics of the newly detected leprosy cases have changed. While most of the newly detected cases came from other provinces in China, not Zhejiang, it brought a new challenge for leprosy prevention and control in post- elimination era in Zhejiang, China. This study was aimed to understand the temporal-spatial distribution characteristics of newly detected leprosy cases, and provide the scientific rationales for the development of leprosy control strategy. METHODS: Data on the demographic of Zhejiang Province from 2011 to 2019 were obtained from the China Information System for Disease Control and Prevention, and the epidemiological data on leprosy cases newly detected in Zhejiang Province from 2011 to 2019 were obtained from the LEPROSY MANAGEMANT INFORMATION SYSTEM IN CHINA (LEPMIS), and temporal-spatial distributions were described. The geographic information system software-ArcGIS 10.4 was used to draw the statistical maps, and Geoda 1.14.0 was used for local spatial autocorrelation analysis (local Getis coefficient method). Ridley-Jopling classification was used to classify the clinical types into I, TT, BT, BB, BL or LL. Two-group classification system developed by the World Health Organization (WHO) was used and cases were classified into multibacillary (MB) type or paucibacillary (PB) type. RESULTS: A total of 167 leprosy cases were reported in Zhejiang Province during 2011-2019, including 107 cases in males and 60 in females. The mean age at diagnosis was 37.99±14.81 years, and 94.01% of the cases were detected through the examination at skin-clinics. The number of workers, MB cases, G2D cases were 81 (48.50%), 159 (94.01%), 24 (14.37%) respectively, and the rate of early detection increased from 45.16% in 2011 to 90.91% in 2019. Leprosy cases were reported in all the prefectures of Zhejiang except Zhoushan City. The cases in local population accounted for 23.35% (39 cases), and the cases in floating population (especially coming from high epidemic provinces in China) accounted for 76.65% (128 cases). The annual number of newly detected cases showed a decreasing trend, from 31 cases in 2011 to 11 in 2019. Time of the floating population living in Zhejiang Province ranged from several months to more than 10 years. The annual proportion of new cases with G2D declined from 22.58% in 2011 to 9.09% in 2019. The results of local indicators of autocorrelation (LISA) analysis showed that the high-high areas were mainly concentrated in the middle and northeast of Zhejiang Province, while the low-low areas were in the east and southwest. CONCLUSION: A few scattered cases still can be seen in post-elimination era, and there was a spatial clustering of the newly detected leprosy cases in Zhejiang Province. Most of the cases in Zhejiang Province were from other high epidemic provinces in China, which brought a new challenge for leprosy control and prevention in post- elimination era in Zhejiang, and it is also necessary to strengthen the early detection and standard management of the leprosy cases in floating population in Zhejiang.

Single-Nucleotide Polymorphisms in Genes Predisposing to Leprosy in Leprosy Household Contacts in Zhejiang Province, China.

PURPOSE: Genome-wide association studies (GWAS) have identified multiple genetic variants associated with leprosy. To investigate the single and combined associations between single-nucleotide polymorphisms (SNPs) and the development of leprosy, we therefore performed generalized multi-analytical (GMDR) analysis in Chinese leprosy household contacts and constructed a risk prediction model. PATIENTS AND METHODS: This case-control study included 229 leprosy cases and 233 healthy household contacts in Zhejiang province, China. Participants were genotyped for 17 polymorphisms selected from GWAS. The Pearson χ2 test, logistic regression and GMDR analysis were performed to investigate gene-gene interactions and construct a risk prediction model for leprosy. RESULTS: The genotype and the allele distributions of rs142179458, rs2275606, rs663743 and rs73058713 were significantly different between patients and controls. rs2275606, rs6478108, rs663743 and rs73058713 showed an association after adjusting for sex and age in the logistic regression. A five-way interaction model consisting of rs2058660, rs2275606, rs4720118, rs6478108 and rs780668 was chosen as the optimal model for determining leprosy susceptibility. The model classified 237 (51.3%) into the low-risk group and 225 (48.7%) individuals into the high-risk group. The area under the curve (AUC) of this model was 0.757 (95% CI: 0.712-0.803), and the odds ratio for leprosy between the high- and low-risk groups was 9.733 (95% CI: 6.384-14.960; P<0.001). The sensitivity and specificity of the model were observed to be 74.7% and 76.8%, respectively. CONCLUSION: Our results suggest that rs2058660, rs2275606, rs4720118, rs6478108 and rs780668, five SNPs with a significant sole effect on leprosy, interact to confer a higher risk for the disease in leprosy household contacts (HHCs).