The -308 bp TNF gene polymorphism influences tumor necrosis factor expression in leprosy patients in Bahia State, Brazil.

Leprosy or Hansen's disease is a debilitating chronic granulomatous disease caused by Mycobacterium leprae, with high incidence and prevalence in Brazil. The -308 bp G/A single nucleotide polymorphism (SNP rs1800629) in the tumor necrosis factor (TNF) gene promoter is a proposed risk factor for leprosy. In Brazil, Northern India, Egypt and Nepal, the common G allele was associated with leprosy. In Eastern India, Thailand and Malawi the minor A allele was the risk factor. Allele A was previously associated with high TNF. We genotyped rs1800629 in 326 leprosy cases from Bahia State, Brazil, including 72 paucibacillary (PB) and 47 multibacillary (MB) without reactions, and 69 reversal reaction (RR) and 78 erythema nodosum leprosum (ENL) with reactions. Logistic regression was used to compare patient groups with 331 healthy controls. Relative TNF mRNA was determined in peripheral blood leukocytes by QRTPCR, and serum TNF levels measured by ELISA. We found that TNF mRNA expression was higher (P=0.03) in leprosy patients compared to endemic controls, but did not differ significantly between clinical subgroups. Carriage of the minor A allele was associated (P=0.003) with low TNF mRNA across leprosy patients. Nevertheless, we found no evidence for either allele at this SNP as a risk factor for leprosy per se (OR=1.12, 95% CI 0.79-1.60, P=0.52), PB (OR=0.99, 95% CI 0.54-1.81, P=0.97), MB (OR=0.86, 95% CI 0.40-1.83, P=0.70), RR (OR=1.37, 95% CI 0.79-2.38, P=0.27) or ENL (OR=0.76, 95% CI 0.40-1.45, P=0.42) when compared to endemic controls. Further studies are required to determine whether the influence of the minor A allele on TNF mRNA levels determines response to treatment, particularly in the context of ENL reaction treatment with anti-TNF therapies and RR reactions where treatment with prednisolone is known to reduce TNF levels. Our findings contribute to understanding TNF as an important determinant of leprosy immunopathology in Brazil.

No evidence for association between SLC11A1 and visceral leishmaniasis in India.

BACKGROUND: SLC11A1 has pleiotropic effects on macrophage function and remains a strong candidate for infectious disease susceptibility. 5' and/or 3' polymorphisms have been associated with tuberculosis, leprosy, and visceral leishmaniasis (VL). Most studies undertaken to date were under-powered, and none has been replicated within a population. Association with tuberculosis has replicated variably across populations. Here we investigate SLC11A1 and VL in India. METHODS: Nine polymorphisms (rs34448891, rs7573065, rs2276631, rs3731865, rs17221959, rs2279015, rs17235409, rs17235416, rs17229009) that tag linkage disequilibrium blocks across SLC11A1 were genotyped in primary family-based (313 cases; 176 families) and replication (941 cases; 992 controls) samples. Family- and population-based analyses were performed to look for association between SLC11A1 variants and VL. Quantitative RT/PCR was used to compare SLC11A1 expression in mRNA from paired splenic aspirates taken before and after treatment from 24 VL patients carrying different genotypes at the functional promoter GTn polymorphism (rs34448891). RESULTS: No associations were observed between VL and polymorphisms at SLC11A1 that were either robust to correction for multiple testing or replicated across primary and replication samples. No differences in expression of SLC11A1 were observed when comparing pre- and post-treatment samples, or between individuals carrying different genotypes at the GTn repeat. CONCLUSIONS: This is the first well-powered study of SLC11A1 as a candidate for VL, which we conclude does not have a major role in regulating VL susceptibility in India.

Geographic information systems and applied spatial statistics are efficient tools to study Hansen's disease (leprosy) and to determine areas of greater risk of disease.

Applied Spatial Statistics used in conjunction with geographic information systems (GIS) provide an efficient tool for the surveillance of diseases. Here, using these tools we analyzed the spatial distribution of Hansen's disease in an endemic area in Brazil. A sample of 808 selected from a universe of 1,293 cases was geocoded in Mossoró, Rio Grande do Norte, Brazil. Hansen's disease cases were not distributed randomly within the neighborhoods, with higher detection rates found in more populated districts. Cluster analysis identified two areas of high risk, one with a relative risk of 5.9 (P = 0.001) and the other 6.5 (P = 0.001). A significant relationship between the geographic distribution of disease and the social economic variables indicative of poverty was observed. Our study shows that the combination of GIS and spatial analysis can identify clustering of transmissible disease, such as Hansen's disease, pointing to areas where intervention efforts can be targeted to control disease.