Abstract
Some genetic association studies have tried to investigate potential associations between TLR polymorphisms and tuberculosis. However, the results of these studies have not been consistent. Thus, we performed the present meta-analysis to explore associations between TLR polymorphisms and tuberculosis in a larger combined population. A systematic literature research of PubMed, Web of Science and Embase was performed to identify eligible studies for combined analyses. I2 statistics were employed to assess between-study heterogeneities. If I2 was >50%, random-effects models were used to combine the data. Otherwise, fixed-effects models were applied for synthetic analyses. A total of 39 genetic association studies were included in the analyses. The combined analyses showed that TLR1 rs4833095, TLR1 rs5743557, TLR1 rs5743596, TLR2 rs3804099, TLR2 rs5743704, TLR2 rs5743708, TLR6 rs5743810 and TLR8 rs3764879 polymorphisms were significantly associated with susceptibility to TB in the overall population. Further subgroup analyses revealed similar significant findings for TLR1 rs4833095, TLR1 rs5743557, TLR1 rs5743596, TLR1 rs5743618, TLR2 rs3804099, TLR2 rs5743704, TLR2 rs5743708, TLR4 rs4986790 and TLR4 rs4986791 polymorphisms in certain ethnicities. In conclusion, our findings support that these TLR polymorphisms may be used to identify individuals at high risk of developing tuberculosis.
Introduction
Tuberculosis (TB) is a common chronic infectious disorder caused by Mycobacterium tuberculosis (MTB), and it could manifest as pulmonary tuberculosis and/or extrapulmonary tuberculosis. 1 Despite rapid advancements achieved in early diagnosis and pharmacological therapy over the past few decades, TB remains a serious public-health threat. According to a recent epidemiological study, about 30% of the general population is currently infected with MTB, and around 5–10% of these infected individuals will eventually develop active TB. 2 The course of MTB infection depends on a complex interaction of pathogen, host and environmental factors, and the fact that only a small portion of infected individuals eventually develop active TB suggests that host genetic background is crucial for its development.3,4
TLRs are a group of type 1 transmembrane proteins expressed on a variety of immune cells that recognise stimuli from exogenous pathogens.5,6 The binding of TLRs with their corresponding ligands leads to recruitment of adaptor proteins, activation of downstream signal transduction pathways, up-regulation of cytokine and chemokine production, and ultimately the development of immune responses against exogenous pathogens.7,8 Consequently, it is possible that TLR gene polymorphisms, which may impact biological activities of TLRs, might also be involved in the development of multiple infectious diseases, including TB. 9
To date, numerous studies have already investigated potential associations between TLR gene polymorphisms and TB. However, the results of these studies were not consistent, especially when they were conducted in different populations. Previous studies failed to reach a consensus regarding associations between TLR gene polymorphisms and TB, in part because of their relatively small sample sizes. Thus, we performed the present meta-analysis to explore the relationship between TLR gene polymorphisms and TB in a larger combined population. In addition, we also aimed to elucidate the potential effects of ethnic background on associations between TLR gene polymorphisms and TB.
Materials and methods
The current meta-analysis was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. 10
Literature search and inclusion criteria
Potentially relevant articles were searched in PubMed, Medline and Web of Science using the following keywords: ‘Toll like receptor’, ‘TLR’, ‘polymorphism’, ‘variant’, ‘mutation’, ‘SNP’, ‘variation’, ‘genotype’, ‘allele’, ‘tuberculosis’ and ‘TB’. The initial literature search was performed in January 2019, and the latest update was finished in May 2019. Moreover, we also screened the references of all retrieved articles to identify other potential relevant studies.
Inclusion criteria were (a) genetic association studies on associations between TLR gene polymorphisms and TB in human beings, (b) genotypic frequency of investigated TLR gene polymorphisms provided in cases and controls and (c) full text available in English. For duplicate reports, only the most complete one was included. Excluded criteria were (a) not about TLR gene polymorphisms and TB, (b) not performed on human beings, (c) case reports or case series and (d) reviews, comments and conference presentations.
Data extraction and quality assessment
The following data were extracted from the included studies: (a) last name of first author, (b) year of publication, (c) country where the study was conducted and ethnicity of study participants, (d) type of disease, (e) the number of cases and controls and (f) genotypic distributions of TLR gene polymorphisms in cases and controls. The P-value for Hardy–Weinberg equilibrium (HWE) was also calculated. When necessary, we wrote to the corresponding authors for extra information. We used the Newcastle–Ottawa scale (NOS) to assess the quality of eligible studies. 11 This scale has a score range of zero to nine, and studies with a score of more than seven were thought to be of high quality. Data extraction and quality assessment were performed by two independent reviewers. Any disagreement between two reviewers was solved by discussion until a consensus was reached.
Statistical analyses
We used Review Manager v5.3.3 (The Cochrane Collaboration, London, UK) to conduct statistical analyses. We calculated odds ratios (ORs) and 95% confidence intervals (CIs) to estimate the strength of associations between TLR gene polymorphisms and TB in dominant, recessive, over-dominant and allele models. Statistical significances of combined analyses were determined by the Z-test, with a P-value of ≤ 0.05 defined as statistically significant. I2 statistics were employed to assess between-study heterogeneities. If I2 was >50%, random-effects models (REMs; DerSimonian–Laird method) was used to combine the data because of significant heterogeneities. Otherwise, fixed-effects models (Mantel–Haenszel method) were used for synthetic analyses. Subgroup analyses by ethnicity of participants were subsequently performed to evaluate effects of ethnic background on investigated genetic associations. Sensitivity analyses were carried out to test the stability of combined results by omitting one study at a time and performing the analyses again based on the results of the remaining studies. Publication biases were evaluated with funnel plots.
Results
Characteristics of included studies
The initial literature search identified 573 potential relevant articles. After exclusion of irrelevant and duplicate articles by reading titles and abstracts, 78 potentially relevant articles were retrieved for eligibility assessment. Another 39 articles were subsequently excluded after reading the full text. Finally, 39 studies that met the inclusion criteria were included (see online supplemental Figure S1). Baseline characteristics of included studies are shown in Table 1. The full manuscripts of the included studies can be found at Open Science Framework (https://osf.io). Data sets are also available to readers upon request.
The characteristics of 39 included studies for this meta-analysis.
TB: tuberculosis; PTB: pulmonary tuberculosis; EPTB: extrapulmonary tuberculosis; HWE: Hardy–Weinberg equilibrium; NOS: Newcastle–Ottawa scale; NA: not available.
TLR gene polymorphisms and TB
The results of overall and subgroup analyses are summarised in Table 2. The combined analyses showed that TLR1 rs4833095 (recessive model: P = 0.02, OR = 1.17, 95% CI 1.03–1.33), TLR1 rs5743557 (dominant model: P < 0.0001, OR = 1.34, 95% CI 1.17–1.54; over-dominant model: P = 0.02, OR = 0.85, 95% CI 0.75–0.97; allele model: P = 0.04, OR = 1.19, 95% CI 1.01–1.41), TLR1 rs5743596 (dominant model: P = 0.01, OR = 1.18, 95% CI 1.04–1.35; over-dominant model: P = 0.02, OR = 0.86, 95% CI 0.75–0.98), TLR2 rs3804099 (dominant model: P = 0.002, OR = 1.16, 95% CI 1.06–1.28; over-dominant model: P = 0.0002, OR = 0.83, 95% CI 0.76–0.92), TLR2 rs5743704 (dominant model: P = 0.01, OR = 0.49, 95% CI 0.29–0.84; over-dominant model: P = 0.01, OR = 2.02, 95% CI 1.19–3.45; allele model: P = 0.01, OR = 0.50, 95% CI 0.29–0.85), TLR2 rs5743708 (dominant model: P < 0.0001, OR = 0.37, 95% CI 0.24–0.55; over-dominant model: P < 0.0001, OR = 2.74, 95% CI 1.81–4.13; allele model: P < 0.0001, OR = 0.38, 95% CI 0.25–0.57), TLR6 rs5743810 (dominant model: P = 0.0005, OR = 1.52, 95% CI 1.20–1.91; over-dominant model: P = 0.002, OR = 0.68, 95% CI 0.53–0.87) and TLR8 rs3764879 (recessive model: P = 0.02, OR = 1.51, 95% CI 1.06–2.16) polymorphisms were significantly associated with susceptibility to TB in overall population. Further subgroup analyses revealed similar significant findings for TLR1 rs4833095, TLR1 rs5743557, TLR1 rs5743596, TLR1 rs5743618, TLR2 rs3804099, TLR2 rs5743704, TLR2 rs5743708, TLR4 rs4986790 and TLR4 rs4986791 polymorphisms in certain ethnicities (see Table 2).
Meta-analysis results on associations between TLR gene polymorphisms and TB in different genetic models.
Values in bold indicate a statistically significant difference between cases and controls.
OR: odds ratio; CI: confidence interval.
Sensitivity analyses
We performed sensitivity analyses by deleting one study at a time to test the effects of individual studies on combined results. No altered results were observed in overall and subgroup comparisons, which indicated that our findings were statistically robust.
Publication biases
We used funnel plots to assess publication biases. We did not find obvious asymmetry of funnel plots in any comparisons, which suggested that our findings were unlikely to be impacted by severe publication biases.
Discussion
TLRs, a group of PRRs for structural conserved exogenous protospacer adjacent motifs, play vital roles in evoking immune reactions in response to infectious stimuli.5,6 The interaction of TLRs with their corresponding ligands activates the TLR signalling pathway, which leads to pro-inflammatory cytokine production and leucocyte infiltration.7,8 Given the crucial roles of TLRs in regulating immune responses against exogenous pathogens, the potential associations of certain TLR gene polymorphisms with susceptibility to infectious diseases such as TB were extensively studied, but the results of these studies were contradictory. Therefore, we performed the present meta-analysis of all published genetic association studies on the relationship between TLR gene polymorphisms and TB in order to obtain a more conclusive result.
To our knowledge, this is the most comprehensive meta-analysis to date on associations between TLR gene polymorphisms and TB, and our combined analyses suggested that TLR1 rs4833095, TLR1 rs5743557, TLR1 rs5743596, TLR1 rs5743618, TLR2 rs3804099, TLR2 rs5743704, TLR2 rs5743708, TLR4 rs4986790, TLR4 rs4986791, TLR6 rs5743810 and TLR8 rs3764879 polymorphisms were all significantly associated with TB in certain ethnicities. The stabilities of synthetic results were evaluated by sensitivity analyses, and no alterations of results were observed in any comparisons, which suggested that our findings were statistically robust.
As for evaluation of heterogeneities, we found that for TLR1 rs4506565, TLR4 rs4986790, TLR4 rs4986791 and TLR9 rs5743836 polymorphisms, significant heterogeneities existed among the included studies. Thus, most of the combined analyses for these polymorphisms were performed with REMs. However, in further subgroup analyses, an obvious reduction tendency of heterogeneity was found in both Asians and Caucasians, which suggested that differences in ethnic background could largely explain observed heterogeneities between studies. The obvious heterogeneities that existed between included studies for TLR1 rs4506565, TLR4 rs4986790, TLR4 rs4986791 and TLR9 rs5743836 polymorphisms in the overall analyses also indicated that the distributions of these TLR polymorphisms vary greatly from population to population. Therefore, the genetic associations between these TLR polymorphisms and TB may be ethnicity specific, and we should not generalise these results to a broader population.
Several factors need to be pointed out about the current study. First, the exact underlying molecular mechanisms of our positive findings remains to be explored by experimental studies, but we speculate that investigated polymorphisms of the TLR gene may lead to alterations in gene expression or changes in protein structure, which may subsequently affect the biological functions of the TLR signalling pathway and, ultimately, individual susceptibility to TB. Second, the pathogenic mechanism of TB is extremely complex, and hence despite our positive findings, it is unlikely that a single gene polymorphism could significantly contribute to its development. Thus, we strongly recommend further studies to perform haplotype analyses and explore potential gene–gene interactions.12,13 Third, to measure the effects of certain genetic factors on disease occurrence and development more precisely, gene–environment interactions should also be considered. However, since the included studies only focused on the effects of TLR gene polymorphisms on individual susceptibility to TB, such analyses were not applicable in the current meta-analysis. 14 Fourth, the present meta-analysis aimed to explore associations between all TLR gene polymorphisms and TB. However, only 17 polymorphisms could be analysed in the current study because no other TLR polymorphisms were investigated by at least two different genetic association studies. Fifth, it should be noted that a recent meta-analyses conducted by Schurz et al. 15 also tried to explore potential associations between TLR1, TLR 2, TLR4, TLR6 and TLR9 variants and TB. However, many related studies have been published in the last three yr. Therefore, an updated meta-analysis is warranted. The sample sizes of our analyses were also significantly larger than that of the previous meta-analysis, which could significantly reduce the risk of obtaining false-positive or false-negative results. So, our work should be considered as a valuable supplementary work to the existing literature.
This meta-analysis also has some limitations. First, although the methodology qualities of the included studies were generally good, it should be noted that we did not have direct access to genotypic distributions of investigated polymorphisms according to the base characteristics of the study subjects. Therefore, our results were derived from unadjusted estimations, and failure to conduct further adjusted analyses for baseline characteristics of participants such as age, sex and co-morbidity conditions may influence the reliability of our findings.16,17 Second, significant heterogeneities were detected in certain subgroup comparisons, which indicated that the inconsistent results of the included studies could not be fully explained by differences in ethnic background, and other unmeasured characteristics of participants may also partially attribute to between-study heterogeneities. 18 Third, since only published articles were eligible for analyses, although funnel plots revealed no obvious publication biases, we still could not rule out the possibility of potential publication biases. 19 Taken these limitations into consideration, the results of the current study should be interpreted with caution.
In conclusion, the present meta-analysis indicated that TLR1 rs4833095, TLR1 rs5743557, TLR1 rs5743596, TLR1 rs5743618, TLR2 rs3804099, TLR2 rs5743704, TLR2 rs5743708, TLR4 rs4986790, TLR4 rs4986791, TLR6 rs5743810 and TLR8 rs3764879 polymorphisms were all significantly associated with TB in certain ethnicities. These results suggest that these polymorphisms may be used to identify individuals at high risk of developing TB. The exact underlying molecular mechanisms of our positive findings remain to be explored by future experimental studies, but we speculate that these TLR polymorphisms may lead to alterations in gene expression or changes in TLR protein structure, which may subsequently affect biological activities of TLR, impact immune responses against exogenous pathogens and ultimately alter individual susceptibility to TB. Moreover, it is worth noting that many genetic comparisons in the current study were only based on a limited number of studies. So, further well-designed studies are still warranted to confirm our findings.
Supplemental Material
Supplemental material for Associations between genetic polymorphisms of TLRs and susceptibility to tuberculosis: A meta-analysis
Supplemental Material for Associations between genetic polymorphisms of TLRs and susceptibility to tuberculosis: A meta-analysis by Yong Zhou and Mengtao Zhang in Innate Immunity
Footnotes
Declaration of conflicting interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship and/or publication of this article.
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References
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