Abstract
Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is an enduring public health problem globally, particularly in sub-Saharan Africa. Several studies have suggested a role for host genetic susceptibility in increased risk for TB but results across studies have been equivocal. As part of a household contact study of Mtb infection and disease in Kampala, Uganda, we have taken a unique approach to the study of genetic susceptibility to TB, by studying three phenotypes. First, we analyzed culture confirmed TB disease compared to latent Mtb infection (LTBI) or lack of Mtb infection. Second, we analyzed resistance to Mtb infection in the face of continuous exposure, defined by a persistently negative tuberculin skin test (PTST-); this outcome was contrasted to LTBI. Third, we analyzed an intermediate phenotype, tumor necrosis factor-alpha (TNFα) expression in response to soluble Mtb ligands enriched with molecules secreted from Mtb (culture filtrate). We conducted a full microsatellite genome scan, using genotypes generated by the Center for Medical Genetics at Marshfield. Multipoint model-free linkage analysis was conducted using an extension of the Haseman-Elston regression model that includes half sibling pairs, and HIV status was included as a covariate in the model. The analysis included 803 individuals from 193 pedigrees, comprising 258 full sibling pairs and 175 half sibling pairs. Suggestive linkage (p<10−3) was observed on chromosomes 2q21-2q24 and 5p13-5q22 for PTST-, and on chromosome 7p22-7p21 for TB; these findings for PTST- are novel and the chromosome 7 region contains the IL6 gene. In addition, we replicated recent linkage findings on chromosome 20q13 for TB (p = 0.002). We also observed linkage at the nominal α = 0.05 threshold to a number of promising candidate genes, SLC11A1 (PTST- p = 0.02), IL-1 complex (TB p = 0.01), IL12BR2 (TNFα p = 0.006), IL12A (TB p = 0.02) and IFNGR2 (TNFα p = 0.002). These results confirm not only that genetic factors influence the interaction between humans and Mtb but more importantly that they differ according to the outcome of that interaction: exposure but no infection, infection without progression to disease, or progression of infection to disease. Many of the genetic factors for each of these stages are part of the innate immune system.
Highlights
Tuberculosis (TB), caused by the bacterium Mycobacterium tuberculosis (Mtb), is a significant, global public health problem, in sub-Saharan Africa, where the prevalence of TB is increasing dramatically with the rise of the HIV pandemic
Another study showed differences in FOXP3 gene expression between TST2 and TST+ individuals [13]; it was unknown if those TST2 individuals ever converted their TST, which is possible since they were contacts of TB cases, so they cannot be definitively classified as resistant to Mtb infection. These findings have suggested a role for human genetics in resistance to Mtb infection [14], but this has not been examined in a formal genetic epidemiological study
We have focused on tumor necrosis factor-alpha (TNFa) because it is a central cytokine in TB pathogenesis that is involved in granuloma formation, induces symptoms including fever and weight loss [20,21], and is important in the containment of latent Mtb infection [22]
Summary
Tuberculosis (TB), caused by the bacterium Mycobacterium tuberculosis (Mtb), is a significant, global public health problem, in sub-Saharan Africa, where the prevalence of TB is increasing dramatically with the rise of the HIV pandemic. Since only 10% of individuals infected with Mtb go on to develop active disease (TB), it has been suggested that host genetics may influence the risk for TB. Numerous candidate gene studies have been conducted for TB; though there is consistent support for a role of human genetics in disease risk, the results for specific genes have been equivocal (reviewed in [4]). Four genome-wide linkage scans have been conducted [5,6,7,8], but their results did not replicate each other. This may be due to differences in TB diagnostic criteria, population genetic differences (Brazilian, Gambian, Malawian and South African), small sample size, or analytic approach
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