Genetic, household and spatial clustering of leprosy on an island in Indonesia: a population-based study

Abstract

BackgroundIt is generally accepted that genetic factors play a role in susceptibility to both leprosy per se and leprosy type, but only few studies have tempted to quantify this. Estimating the contribution of genetic factors to clustering of leprosy within families is difficult since these persons often share the same environment. The first aim of this study was to test which correlation structure (genetic, household or spatial) gives the best explanation for the distribution of leprosy patients and seropositive persons and second to quantify the role of genetic factors in the occurrence of leprosy and seropositivity.MethodsThe three correlation structures were proposed for population data (n = 560), collected on a geographically isolated island highly endemic for leprosy, to explain the distribution of leprosy per se, leprosy type and persons harbouring Mycobacterium leprae-specific antibodies. Heritability estimates and risk ratios for siblings were calculated to quantify the genetic effect. Leprosy was clinically diagnosed and specific anti-M. leprae antibodies were measured using ELISA.ResultsFor leprosy per se in the total population the genetic correlation structure fitted best. In the population with relative stable household status (persons under 21 years and above 39 years) all structures were significant. For multibacillary leprosy (MB) genetic factors seemed more important than for paucibacillary leprosy. Seropositivity could be explained best by the spatial model, but the genetic model was also significant. Heritability was 57% for leprosy per se and 31% for seropositivity.ConclusionGenetic factors seem to play an important role in the clustering of patients with a more advanced form of leprosy, and they could explain more than half of the total phenotypic variance.

Selection of Antigens and Development of Prototype Tests for Point-of-Care Leprosy Diagnosis

“…larly troubling because the earlier a patient is identified and treated, the better the disease outcome (9). Additionally, it is well documented that close contact with leprosy patients, particularly MB leprosy patients, increases the risk of developing the disease (2,16,17,21). Early detection and treatment will make it more likely that a patient's bacterial load will be limited and the potential to transmit viable M. leprae will be reduced.…”

Análise da situação epidemiológica da hanseníase em uma área endêmica no Brasil: distribuição espacial dos períodos 2001 - 2003 e 2010 - 2012

“…Of these, 2,341 (7.5%) new cases corresponded to people aged less than 15 years, and 2,034 (6.5%) patients presented grade 2 disabilities 3 . To intensify the strategies of intervention and control of leprosy in specific geographic zones, the spatial analysis has been used by identifying the distribution of the condition in a national, regional and local level [4][5][6][7][8] . In Brazil, the spatial distribution of leprosy is heterogeneous: the States that are more socioeconomically developed in the South Region reached the goal of eliminating leprosy as a public health issue -prevalence of less than 1 case per 10,000 inhabitants.…”

The rare allele of DGKZ SNP rs10838599 is associated with variability in HDL-cholesterol levels among severely obese patients

“…These SNPs were genotyped using the QuantStudio™ 12K Flex OpenArray® AccuFill™ system (Applied Biosystems), and analyzed with TaqMan Genotyper v1.3 (Life Technologies). The inclusion of the rs34470543 SNP in the current study is attributable to its close localization to the cg12856521 CpG site, previously found to be differentially methylated between MetS+ and MetS-subjects [17]. The tagger selection algorithm of the Haploview software (pairwise tagging, R 2 ≥ 0.80) was used for analysis of selected SNPs spanning promoter (2 kb), coding and intronic regions of the DGKZ gene in addition to the 3' gene region (2 kb) [17].…”