Bakker Mirjam I, May Linda, Hatta Mochammad, Kwenang Agnes, Klatser Paul R, Oskam Linda, Houwing-Duistermaat Jeanine J
KIT (Koninklijk Instituut voor de Tropen/Royal Tropical Institute), KIT Biomedical Research, Meibergdreef 39, 1105 AZ Amsterdam, The Netherlands.
BMC Med Genet. 2005 Nov 24;6:40. doi: 10.1186/1471-2350-6-40.
It 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.
The 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.
For 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.
Genetic 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.
人们普遍认为遗传因素在麻风病本身的易感性以及麻风病类型方面发挥作用,但仅有少数研究试图对此进行量化。由于家庭成员通常共享相同环境,因此估计遗传因素对麻风病家庭聚集性的影响较为困难。本研究的首要目的是检验哪种相关结构(遗传、家庭或空间)能对麻风病患者和血清反应阳性者的分布给出最佳解释,其次是量化遗传因素在麻风病发生和血清反应阳性中的作用。
针对在一个麻风病高度流行的地理隔离岛屿上收集的人群数据(n = 560),提出了三种相关结构,以解释麻风病本身、麻风病类型以及携带麻风分枝杆菌特异性抗体者的分布情况。计算了同胞的遗传度估计值和风险比,以量化遗传效应。麻风病通过临床诊断,特异性抗麻风分枝杆菌抗体采用酶联免疫吸附测定法进行检测。
对于总体人群中的麻风病本身,遗传相关结构拟合最佳。在家庭状况相对稳定的人群(21岁以下和39岁以上者)中,所有结构均具有显著性。对于多菌型麻风(MB),遗传因素似乎比少菌型麻风更为重要。血清反应阳性最好由空间模型解释,但遗传模型也具有显著性。麻风病本身的遗传度为57%,血清反应阳性的遗传度为31%。
遗传因素似乎在更晚期麻风病患者的聚集性中发挥重要作用,并且它们可以解释超过一半的总表型变异。