In the present study, we applied a candidate-gene approach and tested the association of 14 polymorphisms in genes VDR, MR1, TLR1, TLR2, TLR10, SLC11A1, IL1B, IL10, IFNG, TNF, IRAK1, and FOXP3 with the risk of pulmonary TB in Moldavian population. Although these genes are critical components of human immunity and their polymorphisms have been implicated in susceptibility/resistance to TB, we could not find convincing statistical evidence for their association with the risk of pulmonary TB in this study. A borderline association was revealed for polymorphism rs1800629 in the TNF gene only, but this did not survive corrections for multiple testing by Bonferroni method. Overall, the results presented here do not support a major role of the analyzed common variants in conferring susceptibility/resistance to pulmonary TB in Moldavian population.
The inability to reach significance level after Bonferroni correction may be explained by a fairly small sample size and inadequate statistical power to produce convincing associations for polymorphisms with low and moderate effects (with OR < 1.5). For this reason, we cannot completely rule out the possibility of true functional effects for variants with nominal associations, in particular for TNF rs1800629 polymorphism. The TNF gene encodes a multifunctional proinflammatory cytokine TNF-α which is mainly produced by activated monocytes, macrophages and T-lymphocytes when stimulated by mycobacterial antigens. TNF-α acts synergistically with IFN-γ to induce macrophages killing of M.tb [39]. In addition, TNF-α is involved in the recruitment of leukocytes to the site of infection and contributes to the formation of TB granuloma, preventing the spread of infection [39]. It is reported that treatment with TNF-α inhibitors leads to reactivation of latent TB infection, indicating TNF-α as a key cytokine towards resistance to M.tb [40]. SNP rs1800629 (− 308G > A) is located within regulatory hotspot region and thus influences transcription critically [41, 42]. The minor allele A of rs1800629 has been associated with increased expression of TNF and higher plasma levels of TNF-α [17]. In agreement with published functional studies, our results demonstrated a higher frequency of allele A in controls than in cases, suggesting its protective role against TB (OR = 0.63). Similarly, allele A was protectively associated with TB in Colombian [16] and Mexican [18] populations. However, other genetic epidemiologic studies involving patient cohorts from various population groups, including Malawi [43], Iran [44], Indian [45], Cambodian [46], Chinese Han and Tibetan [47], did not confirm the above findings. The disparity in results across studies may be explained by certain factors such as inadequate sample sizes and differences in environmental, demographic, cultural, host genetic and bacterial characteristics of M.tb strains.
Additionally, a nominal yet suggestive association was demonstrated for haplotype A-T-G-T-A of the block rs11466657-rs11096957-rs5743618-rs4833095-rs5743810 in the gene cluster TLR1-TLR6-TLR10. Genes TLR1, TLR6, and TLR10 are located in a 54-kb genomic region on chromosome 4p14 and encode proteins that share a high degree of homology in their amino acid sequences. All three genes belong to the TLR2 subfamily of TLRs, which plays a critical role in the early recognition of M.tb and subsequent activation of immune responses [48]. Individual polymorphisms and haplotypes within the TLR10-TLR1-TLR6 locus have been associated with altered susceptibility to infectious disease, including mycobacterial infections of leprosy and TB [11, 49, 50, 51, 52]. Unfortunately, different sets of SNPs used in this and in other studies complicate direct comparisons of the results. Even so, the identified haplotype A-T-G-T-A and, more generally, variations in genes TLR10, TLR1 and TLR6 could be a promising replication target for future studies in larger cohorts.
Genetic interactions are thought to underlie susceptibility/resistance to TB [5, 53], so they could explain some of the missing heritability in this study. Therefore, we also analyzed the impact of allele combinations on TB risk. The strongest evidence for interaction in our data was between SNPs rs5743810 and rs11096957 located in genes TLR6 and TLR10, respectively. Interestingly, the two SNPs showed no or only weak effect on TB susceptibility when evaluated alone, indicating a synergetic mechanism of TLR6 rs5743810 and TLR10 rs11096957 in conferring risk for pulmonary TB.
Interaction between these SNPs is biologically plausible. Firstly, TLRs are the key players in the host defense against infections. Specifically, TLR6 functionally interacts with TLR2 to mediate the cellular response to bacterial lipoproteins and activate the NF-κB pathway and inflammatory events through MyD88 dependent signaling [10, 48, 52]. TLR10 has also the ability to form heterodimers with TLR2, but its specific ligands have not yet been identified and its downstream signaling is not fully understood. It is thought to act through both MyD88 dependent and independent signaling pathways with mainly inhibitory effects on inflammation [10]. The genetic interaction between TLR6 and TLR10 observed in this study may reflect their mutual functional contribution to M.tb recognition and subsequent downstream signaling (Fig. 2). Secondly, the investigated SNPs in TLR6 and TLR10 genes had been shown before to be of functional significance. In fact, the two SNPs are non-synonymous variants located in the extracellular (leucine-rich repeat) domains of the encoded proteins. Both ex vivo and in vitro experiments showed that SNPs rs5743810 (Ser249Pro) and rs11096957 (Asn241His) may influence pro-inflammatory cytokine production in humans [10, 54, 55]. In addition, polymorphism rs5743810 was observed to affect NF-κB signaling activity, thereby modulating inflammatory responses [56]. Furthermore, the two polymorphisms have been associated with several immune-related pathologic conditions and infectious diseases, including TB [11, 51, 52, 57]. These data support the relevance of additive interaction between SNPs rs5743810 and rs11096957 and suggest a molecular mechanism by which genetic variations in TLR6 and TLR10 genes might increase susceptibility to TB (Fig. 2).
The present study is the first to identify an interaction between TLR6 rs5743810 and TLR10 rs11096957 gene variants in TB risk. Further larger case–control studies followed by functional tests are warranted to validate this initial finding and eventually translate it into clinical practice. Particularly, given the high spread of the combined TLR6 rs5743810 GA - TLR10 rs11096957 GT genotype in European population (~ 15–20%), it might be used as a novel predictive biomarker for identification of individuals at high risk for active TB disease.
Some limitations of our study deserve consideration. Firstly, it was limited in power to detect the weak association signals, so our negative results should be treated with caution. Secondly, healthy controls were not tested for latent M.tb infection, and therefore it was not possible to discriminate between TB-infected and TB-uninfected individuals. However, as mentioned in the materials and methods, the controls were recruited from TB-communities where they were permanently exposed to TB and therefore are expected to be infected. Third, the number of polymorphisms in the immune system genes analyzed was limited. Given their key role in TB pathogenesis, additional TB risk variants, haplotypes and allele combinations may possibly exist.
A potential limitation of this study is a significant deviation from HWE of the interacting SNP TLR10 rs11096957 (Asn241His) in the controls. Such deviations can result from genotyping errors, recruiting biases, natural selection or be simply a chance. We excluded genotyping errors by random re-genotyping of TLR10 rs11096957 in 21% of samples. Also, our study design prevented the recruitment of any relatives. The natural selection could be the reason for the observed deviation, which may be supported by the evidence of similar heterozygosity deficiency in Toscani in Italy, TSI (HWE p-value = 0.02; 1000 Genomes Project data) and considerable intra-population variation of SNP TLR10 rs11096957 within Europe (the allele G frequency range: 32.4% in British, GBR − 48.6% in Iberian population, IBS; 1000 Genomes Project data). Moreover, the recruitment of healthy controls from TB communities used in this project may have a similar kind of impact for the locus TLR10 like natural selection, contributing to the deficiency of rs11096957 heterozygotes. Taken together, these arguments justify the inclusion of TLR10 rs11096957 in association tests.