Genetic polymorphisms of IL-17A, IL-17F, TLR4 and miR-146a in association with the risk of pulmonary tuberculosis

Abstract

Genetic factors affect host susceptibility to pathogens. In this population-based case control study, we explored the genetic polymorphisms of IL-17, TLR4 and miR-146a in association with pulmonary tuberculosis in a Chinese Han population. We recruited 1601 pulmonary tuberculosis patients matched with 1526 healthy controls and genotyped twelve functional single nucleotide polymorphisms (SNPs). After the correction for multiple comparisons, two SNPs (rs10759932 and rs2737190) in the TLR4 gene remained significant. Individuals carrying the rs2737190-AG genotype (vs. AA) had a significantly increased risk of either clinical tuberculosis (OR: 1.31, 95% CI: 1.11-1.53) or sputum smear-positive tuberculosis (OR: 1.35, 95% CI: 1.13-1.61). Stratification analysis revealed that the effects of genetic variations on tuberculosis were more evident among non-smokers. People with haplotype TLR4 rs10983755G-rs10759932C had a significantly increased risk of tuberculosis (OR: 3.43, 95% CI: 2.34-5.05). Moreover, we found that SNPs of rs3819024 in IL-17A and rs763780 in IL-17F were weakly related to a prognosis of tuberculosis. Our results suggest that genetic polymorphisms of IL-17 and TLR4 may play a role in host susceptibility to tuberculosis in the Chinese Han population. More work is necessary to identify specific causative variants of tuberculosis underlying the observed associations.

A

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Min* Xu* L Xu Chen Bo Burstrom Burstrom

Tuberculosis is a chronic infectious disease caused by the pathogen of Mycobacterium tuberculosis (MTB), and has been a major public health problem worldwide1. An estimated 9 million people developed active tuberculosis, and 1.5 million died from it in 2013, mostly in developing countries2. The outcome of MTB infection ranges from complete pathogen clearance to asymptomatic latent infection to active tuberculosis disease. Most infected individuals are in the latent period, and only 510% will progress to the active phase during their lifetimes35.

Researchers have shown that the innate and adaptive immune responses play an important role in the control of MTB infection6.

CD4(+) T cells play a critical role during MTB infection by regulating the immune response and mediating host protection. Th1 and Th17 cells are the main eector CD4(+) T cells7. Th1 cells contribute to tuberculosis protection by secreting IFN- and activating the antimycobacterial reaction in macrophages7. Th17 cells are inter-leukin (IL)-17-producing CD4+ T cells with implications in inducing neutrophilic inammation and mediate tissue damage7,8. Antimicrobial inammatory response primarily begins through the initial sensing of dierent pathogen-associated molecular patterns by the pattern recognition receptors of the host9. Amongst the innate immune receptors, Toll-like receptors (TLRs) have the unique capacity to sense the initial infection and are the most potent inducers of the immune responses9. Toll-like receptor 4 (TLR4) is the main receptor mediating the

Department of Social Medicine and Health Education, School of Public Health, Nanjing Medical University,

Department of Learning, Informatics, Management and *These authors contributed

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Figure 1. Regulation and interaction between miR-146a, TLR4 and IL-17A/F.

signals responsible for the production of IL-17A induced by MTB10. The deciency of TLR4 inhibits Th17 cell differentiation by suppressing the Signal Transducer and Activator of Transcription 3 (STAT3) pathway and promoting Th1 cell dierentiation by enhancing the STAT1 pathway11. As shown in Fig.1, microRNA-146a (miR-146a) is also involved in the host immune response to MTB infection by acting as a negative feedback regulator of the TLR/NF-kB pathway and potentially participating in regulating IL-17 expression by targeting the 3-untranslated region (UTR) of the TRAF6 and the IRAK-1 genes12,13. The activation of innate immunity receptors via a pathogen induces the up-regulation of miR-146a expression and will in turn exert a negative feedback on TLR4, leading to an inhibition of Th17 pathway molecules and pro-inammatory cytokines (IL-17A, IL-17F, IL-6 and TNF-) and an attenuation of the inammatory eect of Th17 cells12.

Both IL-17A and IL-17F are members of the IL-17 cytokine family. They are located adjacent to one another on the same human chromosome, 6p12, and have similar expression proles14. The TLR4 gene is located on the long arm of chromosome 9 at position 33.115. Although genetic polymorphisms of IL-17 and TLR4 have gained much more interest in the risk of tuberculosis1620, few studies have examined their synergistic eect, and a small number of these studies were performed in China. Considering the roles of TLR4, IL-17 and miR-146a in the pro-inammatory response12, we conducted a population-based case control study in a Chinese Han population, with the goals of exploring whether genetic polymorphisms in IL-17, TLR4, and miR-146a are associated with susceptibility to and the prognosis of pulmonary tuberculosis.

This study has a mixed case control and prospective follow-up design. We recruited 1601 pulmonary tuberculosis patients from Jiangsu province, China since 2011. They were genetically-unrelated Chinese Han individuals. Patients were aged 18 years or older, without HIV infection, cancer or autoimmune diseases. Tuberculosis cases were group-matched (by sex and age) with 1526 controls from a pool of individuals who participated in the community-based health examination programs. Individuals with a history of tuberculosis, diabetes, malignancy, HIV and immunosuppressive conditions were excluded. This study was approved by the ethics committee of Nanjing Medical University (No: 2012-0105, Date: Jan 5, 2012). The methods were carried out in accordance with the approved guidelines. Written informed consent was obtained from all participants. The manuscript was draed according to the STROBE statement (http://www.strobe-statement.org/).

Tuberculosis cases were diagnosed by specialized doctors following the guidelines recommended by the China Ministry of Health, which were based on clinical symptoms and signs, chest x-ray examination, sputum smear tests or sputum culture (http://www.chinatb.org). Three sputum samples were collected from each subject with labelled plastic bottles. The Ziehl-Neelsen hot staining method was used for sputum smear microscopy. If the equipment and technology allowed, the culture was carried out. In brief, sputum samples were decontaminated with 4% sodium hydroxide (NaOH), centrifuged and then cultured on Lowenstein-Jensen (LJ) culture media21. The LJ culture media were incubated at 37 C. Identication of MTB was done using the p-nitrobenzoic acid (PNB) and thiophene carboxylic acid hydrazine (TCH) resistance test. Growth in LJ medium containing PNB indicates that the bacilli do not belong to the MTB complex. Species other than MTB were excluded from the current analysis.

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Gene SNPs Primer (5-3) Probe

IL-17A rs2275913 F-TGAATTTCTGCCCTTCCCATT A: FAM-CTTCAGAAGAAGAGATT-MGB

G>A R-GGTTCAGGGGTGACACCATTT G: HEX-TTCAGAAGGAGAGATT-MGB rs3819024 F-CCGGAATTGTCTCCACAACAC G: FAM-AATCTGTGAGGGAAAG-MGB

A>G R-TGTACCTTGATTTTCCATTTGATCTT A: HEX-AGGAATCTGTGAGGAAA-MGB rs8193036 F-CTCCTTTCTAGTTCTCATCACTCTCTACTC G: FAM-CTTTTCTCCATCTTCA-MGB

C>T R-TGTTTTGAGGAAGGAATTGAAAATG A: HEX-CTTTTCTCCATCTCCA-MGB rs3748067 F-TGAGTTTTTATTTTACTTGGGCTGAA G: FAM-TTCTCATACTTAAAGTTC-MGB G>A R-CAACCCAGAAAGGAGCTGATG A: HEX-TTCTCATACTTAAAATTC-MGB IL-17F rs763780 F-GAGAAGGTGCTGGTGACTGTTG G: FAM-CCTGTCATCCACCGTG-MGB

T>C R-CTTCTTCAGCTGAGTGGATATGCA A: HEX-CCTGTCATCCACCATG-MGB TLR4 rs1927914 F-GAAGTGCTTGGAGGATATTACAGTAGAA G: FAM-CTAGGACTTAGCATGCATA-MGB

T>C R-GAACTGGCATTTGTAAAGCTTTTAGG A: HEX-ACTTAGCATACATAATATT-MGB rs10759932 F-CCCACAAATGGTGTACAGGAGTT G: FAM-ATCTTCACCAACGCT-MGB

T>C R-TGCAAGCTTCTGCTATGATTAAAAG A: HEX-CATCTTCACCAACACT-MGB rs10983755 F-ACCACAAAATGGTCCCTCACA G: FAM-CTTGGTTTTTGACACGTT-MGB

G>A R-TTCTACTGTAATATCCTCCAAGCACTTC A: HEX-TTGGTTTTTGACACATTG-MGB rs2737190 F-GGAGCATGCCTTATGCACACT T: FAM-ACCCAAGTAGACACTGT-MGB

A>G R-GACCTGTGATGATTAGGGCTGAA C: HEX-ACCCAAGTAGACACCGT-MGB rs7873784 F-AGAACACTTAACATGAGAGGTACCC C: FAM-TTCATTATACGAACTCTGC-MGB

C>G R-GATGAATTAGCTCTAAAGATCAGCTGT G: HEX-TTCATTATAGGAACTCTGC-MGB rs11536889 F-GTTGGGCAATGCTCCTTGA G: FAM-ATTTTGGGAAGAGTGGAT-MGB

G>C R-GAACCCCATTAATTCCAGACACA C: HEX-CACATTTTGGGAACAGT-MGB miR-146a rs2910164 F-GAACTGAATTCCATGGGTTGTGT G: FAM-TCAGACCTGTGAAATT-MGB

C>G R-GCCCACGATGACAGAGATATCC C: HEX-TCAGACCTCTGAAATT-MGB

Table 1. Primers and probes designed for genotyping.

Trained local health facility sta interviewers administered a risk factor questionnaire to all participants. The collected data included demographic characteristics, tobacco smoking, alcohol drinking, medical history and laboratory tests. Patients were followed to obtain information on their therapeutic regimens, treatment adherence and outcomes. Aer informed consent was obtained, a blood sample was collected from each participant for molecular analyses.

We selected SNPs in the IL-17 and TLR4 genes based on the following criteria: (1) minor allele frequency (MAF) 0.05 in the Chinese Han population; (2) Hardy-Weinberg equilibrium test: P 0.05; and (3) SNPs located in the functional areas such as 5-UTR, 5 near the gene, exon or 3-UTR. In addition, a functional polymorphism in the miR-146a gene was also selected for genotyping (http://www. bioguo.org/miRNASNP2/). As a result, twelve SNPs were genotyped, including four SNPs in IL-17A (rs2275913, rs3819024, rs8193036 and rs3748067), one SNP in IL-17F (rs763780), six SNPs in TLR4 (rs1927914, rs10759932, rs2737190, rs10983755, rs7873784, rs11536889) and one SNP in miR-146a (rs2910164). Genomic DNA was extracted from leukocytes in the peripheral blood sample by proteinase K digestion and phenol/chloroform extraction. The primer and probe sequences for each SNP were showed in Table1. According to the manufacturers instructions, we genotyped SNPs using the TaqMan allelic discrimination technology on the 384-well ABI 7900HT Real-Time PCR System (Applied Biosystems, Foster City, CA, USA), ascertained using SDS soware (version 2.3)22. Amplication was performed under the following conditions: 50C for 2 min, 95 C for 10 min followed by 45 cycles of 95C for 15 s and 60C for 1min. The success rate for each SNP was over 96%. To avoid batch bias, we allocated DNA samples of both cases and controls in each plate with no discrepancies between the reaction conditions. Approximately 10% of the samples were randomly selected for repeat genotyping for conrmation, and the results were 100% concordant.

Data were entered with EpiData 3.1 soware (Denmark) and analyzed using STATA 10.0 (StataCorp, College Station, TX, USA). Students t-test (for continuous variables) and the 2 test (for categorical variables) were used to analyze the dierences in demographic variables and potential risk factors between cases and controls. Hardy-Weinberg equilibrium (HWE) was tested using a goodness-of-t 2 test by comparing the observed genotype frequencies with the expected frequencies among the controls to make sure that the alleles were independently segregated. An unconditional logistic regression model was carried out to analyze the associations between genotypes and the risk of tuberculosis by calculating the odds ratio (OR) and 95% condence interval (CI). The relative risk (RR) and 95% CI were calculated to evaluate the eect of genetic polymorphisms on the patient prognoses. To control for potential confounding, we adjusted for age, sex, tobacco smoking and alcohol drinking. To comprehensively analyze the eect of SNPs, we applied three dierent genetic models: additive model, dominant model and recessive model. IL-17A and TLR4 haplotypes were performed using phase 2.1 soware. Bonferroni corrections were applied for multiple comparisons.

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Case

(n=1601)

n(%)

Control

(n=1526)

n(%)

Variables

t/2

P

Age(years)

MeanSD 52.117.7 52.417.0 0.564 0.573 Sex 0.321 0.571

Male 1181(73.8) 1112(72.9)

Female 420(26.2) 414(27.1)

Smoking 84.730 <0.001

Never 762(47.6) 976(64.0)

Ever 839(52.4) 550(36.0)

Drink 9.065 0.003

Never 1246(77.8) 1117(73.2)

Ever 355(22.2) 409(26.8)

Sputum smear test

Positive 1080(67.5)

Negative 521(32.5)

Table 2. General characteristics of the cases and controls.

Demographic characteristics of the cases and controls are shown in Table2. In total, 1601 tuberculosis cases (73.8% males and 26.2% females) and 1526 controls (72.9% males and 27.1% females) were recruited. The average (standard deviation, SD) age was 52.1(17.7) years in cases and 52.4(17.0) years in controls. Due to the frequency matching, there was no signicant dierence in the distribution of age and sex between the two groups. The proportion of ever smokers was 52.4% among cases, which was signicantly higher than that in controls (36.0%) (2=84.73, P< 0.001). Alcohol drinking was inversely related to tuberculosis, and 22.2% of the cases vs. 26.8% of the controls had a history of alcohol consumption (2=9.06, P=0.003).

Except for rs1927914 (P = 0.012), the genotype distributions of the eleven SNPs were all in HWE in the controls (P = 0.43 for rs2275913, P = 0.41 for rs3819024, P = 0.84 for rs8193036, P = 0.12 for rs3748067, P = 0.06 for rs763780, P = 0.10 for rs10759932, P = 0.07 for rs2737190, P = 0.34 for rs10983755, P= 0.60 for rs7873784, P= 0.98 for rs11536889 and P= 0.33 for rs2910164). As shown in Table3, if we set the test level at 0.002 (0.05/11*2) to consider both the multiple comparisons of 11 SNPs and genotypes of each SNP, two

SNPs (rs10759932 and rs2737190) were found to be signicantly associated with the risk of tuberculosis. For SNP rs2737190, individuals carrying the AG genotype had a signicantly increased risk of either clinical tuberculosis (OR: 1.31, 95% CI: 1.111.53) or sputum smear-positive tuberculosis (OR: 1.35, 95% CI: 1.131.61). For SNP rs10759932, the association was only signicant for clinical tuberculosis, where the TC/CC carrier had a 27% increased risk (OR: 1.27, 95% CI: 1.091.46).

Stratication analysis revealed that the eects of genetic variations on tuberculosis were more evident among non-smokers. Two SNPs of rs10759932 and rs2737190 remained signicant aer correcting for multiple comparisons among non-smokers (Table4).

We followed the treatment outcomes of all tuberculosis cases. Among the cases, 874(54.6%) were cured, 480(30.0%) completed treatment, 57(3.6%) failed to be treated, and 190(11.9%) defaulted. We categorized the outcomes as successful (cured or completed treatment) and unsuccessful. Single SNP analysis showed that rs3819024 in IL-17A and rs763780 in IL-17F were signicantly associated with the treatment outcomes of tuberculosis. For the SNP rs3819024, individuals carrying the AG genotype were likely to have a decreased risk of treatment failure when compared with the AA genotype, with an adjusted RR of 0.56 (95% CI: 0.311.00) (Table5). The dominant model showed a 41% decreased risk among individuals carrying variant genotypes (AG/GG), with the adjusted RR of 0.59 (95% CI: 0.340.99, P= 0.045). For the SNP rs763780, individuals carrying the TC genotype were likely to have a signicantly increased risk of treatment failure when compared with the TT genotype (adjusted RR: 1.84, 95% CI: 1.053.14) (Table5). The dominant model showed a 77% increased risk among individuals carrying variant genotypes (TC/CC), with an adjusted RR of 1.77(95% CI: 1.022.99). However, these dierences were not signicant aer Bonferroni correction.

To better understand the genetic associations, the linkage disequilibrium (LD) and haplotype blocks were further assessed. LD analysis was carried out on four SNPs of IL-17A and ve SNPs of TLR4. Figure2 displays the LD plot of SNPs on the same chromosome. With a D 0.95, two SNPs (rs2275913 and rs3748067) of IL-17A on chromosome 6, as well as two SNPs (rs10983755 and rs10759932) of TLR4 on chromosome 9, were in relatively strong linkage disequilibrium with one another. Thus, we performed a haplotype analysis based on these four SNPs. As shown in Table6, compared with the common haplotype rs10983755Grs10759932T, rs10983755Grs10759932C had a signicantly increased risk of tuberculosis (OR: 3.43, 95% CI: 2.345.05). This increased risk remained signicant aer Bonferroni correction

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Total cases(n=1601) Smear-positive cases (n=1080) n(%) OR(95%Cl)a P n(%) OR(95%Cl)a P

Gene SNPs Control (n=1526) n(%)

IL-17A rs2275913

GG 450(29.6) 477(31.7) 1 309(30.7) 1GA 741(48.7) 729(48.4) 0.89(0.751.06) 0.192 494(49.2) 0.94(0.771.13) 0.500 AA 331(21.7) 301(20.0) 0.79(0.640.97) 0.028 202(20.1) 0.82(0.651.04) 0.098 Add 0.89(0.800.99) 0.027 0.91(0.811.02) 0.106 Dom 0.86(0.731.01) 0.066 0.90(0.751.08) 0.249 Rec 0.85(0.711.02) 0.074 0.85(0.701.05) 0.129 G 1641(53.9) 1683(55.8) 1 1112(55.3) 1A 1403(46.1) 1331(44.2) 0.93(0.841.02) 0.131 898(44.7) 0.95(0.841.06) 0.323 rs3819024

AA 422(27.7) 442(28.2) 1 284(26.8) 1AG 745(48.9) 784(50.0) 0.98(0.831.16) 0.816 544(51.4) 1.06(0.881.29) 0.547 GG 358(23.5) 341(21.8) 0.85(0.691.04) 0.110 230(21.7) 0.90(0.711.13) 0.355 Add 0.92(0.831.02) 0.124 0.95(0.851.07) 0.401 Dom 0.94(0.801.10) 0.421 1.01(0.841.21) 0.942 Rec 0.86(0.721.02) 0.081 0.86(0.711.05) 0.137 A 1589(52.1) 1668(53.2) 1 1112(52.6) 1G 1461(47.9) 1466(46.8) 0.96(0.871.06) 0.376 1004(47.4) 0.98(0.881.10) 0.748 rs8193036

CC 783(51.4) 789(51.1) 1 515(49.7) 1CT 621(40.7) 618(40.0) 1.00(0.861.17) 0.966 429(41.4) 1.07(0.901.27) 0.433 TT 120(7.9) 137(8.9) 1.22(0.931.60) 0.156 92(8.9) 1.26(0.931.71) 0.128 Add 1.06(0.951.19) 0.312 1.10(0.971.25) 0.135 Dom 1.04(0.901.20) 0.623 1.10(0.941.30) 0.246 Rec 1.22(0.931.58) 0.146 1.23(0.921.64) 0.172 C 2187(71.8) 2196(71.1) 1 1459(70.4) 1T 861(28.2) 892(28.9) 1.03(0.921.15) 0.580 613(29.6) 1.07(0.941.21) 0.300 rs3748067

GG 1094(71.8) 1135(71.2) 1 757(70.5) 1GA 385(25.3) 415(26.1) 1.06(0.891.25) 0.528 286(26.6) 1.09(0.901.31) 0.369 AA 45(3.0) 43(2.7) 1.02(0.661.58) 0.935 31(2.9) 1.13(0.701.83) 0.607 Add 1.04(0.901.19) 0.592 1.08(0.931.26) 0.325 Dom 1.05(0.901.23) 0.540 1.09(0.921.31) 0.327 Rec 1.00(0.651.55) 0.984 1.11(0.691.79) 0.670 G 2573(84.4) 2685(84.3) 1 1800(83.8) 1A 475(15.6) 501(15.7) 1.01(0.881.16) 0.878 348(16.2) 1.05(0.901.22) 0.549 IL-17F rs763780

TT 1175(77.0) 1225(77.6) 1 840(79.0) 1TC 318(20.9) 323(20.5) 1.00(0.841.20) 0.974 207(19.5) 0.95(0.771.16) 0.586 CC 32(2.1) 31(2.0) 0.91(0.541.52) 0.713 16(1.5) 0.67(0.361.25) 0.207 Add 0.99(0.851.15) 0.866 0.91(0.761.08) 0.269 Dom 0.99(0.841.18) 0.947 0.92(0.761.12) 0.397 Rec 0.91(0.541.51) 0.710 0.68(0.361.26) 0.219 T 2668(87.5) 2773(87.8) 1 1887(88.8) 1C 382(12.5) 385(12.2) 0.97(0.831.13) 0.690 239(11.2) 0.89(0.751.05) 0.162 TLR4 rs10759932

TT 779(51.4) 722(45.7) 1 505(47.2) 1TC 597(39.4) 697(44.1) 1.27(1.091.48) 0.002b 458(42.8) 1.18(1.001.40) 0.054 CC 140(9.2) 161(10.2) 1.25(0.971.61) 0.090 107(10.0) 1.20(0.911.60) 0.199 Add 1.17(1.051.31) 0.005 1.13(1.001.28) 0.053 Dom 1.27(1.091.46) 0.001b 1.19(1.011.39) 0.037 Rec 1.12(0.871.43) 0.378 1.12(0.851.47) 0.430 T 2155(71.1) 2141(67.8) 1 1468(68.6) 1C 877(28.9) 1019(32.2) 1.17(1.051.30) 0.005 672(31.4) 1.13(1.001.27) 0.055 rs2737190

Continued

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Total cases(n=1601) Smear-positive cases (n=1080) n(%) OR(95%Cl)a P n(%) OR(95%Cl)a P AA 557(37.0) 518(32.6) 1 343(32.0) 1AG 690(45.8) 840(52.9) 1.31(1.111.53) 0.001b 580(54.1) 1.35(1.131.61) 0.001b GG 259(17.2) 231(14.5) 0.95(0.761.18) 0.628 150(14.0) 0.93(0.731.19) 0.566 Add 1.03(0.931.15) 0.559 1.03(0.921.16) 0.601 Dom 1.21(1.041.41) 0.015 1.23(1.041.46) 0.015 Rec 0.81(0.660.99) 0.038 0.78(0.620.98) 0.030 A 1804(59.9) 1876(59.0) 1 1266(59.0) 1G 1208(40.1) 1302(41.0) 1.04(0.941.15) 0.489 880(41.0) 1.04(0.931.16) 0.516 rs10983755

GG 793(52.1) 806(50.7) 1 551(51.5) 1GA 600(39.4) 644(40.5) 1.06(0.911.23) 0.450 424(39.6) 1.02(0.861.21) 0.829 AA 128(8.4) 139(8.7) 1.06(0.811.38) 0.672 95(8.9) 1.07(0.801.44) 0.636 Add 1.04(0.931.17) 0.472 1.03(0.911.17) 0.650 Dom 1.06(0.921.22) 0.428 1.03(0.881.21) 0.731 Rec 1.03(0.801.34) 0.808 1.07(0.801.42) 0.665 G 2186(71.9) 2256(71.0) 1 1526(71.3) 1A 856(28.1) 922(29.0) 1.04(0.941.17) 0.446 614(28.7) 1.03(0.911.16) 0.664 rs7873784

GG 1271(83.9) 1310(83.1) 1 876(82.2) 1GC 235(15.5) 256(16.2) 1.07(0.881.31) 0.476 181(17.0) 1.13(0.911.41) 0.265 CC 9(0.6) 11(0.7) 1.38(0.563.41) 0.489 9(0.8) 1.76(0.684.54) 0.244 Add 1.09(0.911.31) 0.362 1.16(0.951.42) 0.144 Dom 1.09(0.891.32) 0.411 1.15(0.931.43) 0.192 Rec 1.36(0.553.37) 0.505 1.72(0.674.44) 0.262 G 2777(91.7) 2876(91.2) 1 1933(90.7) 1C 253(8.3) 278(8.8) 1.06(0.891.27) 0.515 199(9.3) 1.13(0.931.37) 0.218 rs11536889

GG 891(58.7) 953(60.2) 1 637(59.5) 1GC 545(35.9) 535(33.8) 0.95(0.811.11) 0.506 372(34.7) 0.99(0.831.18) 0.911 CC 83(5.5) 94(5.9) 1.04(0.761.43) 0.799 62(5.8) 1.03(0.721.47) 0.859 Add 0.98(0.871.11) 0.780 1.00(0.881.15) 0.970 Dom 0.96(0.831.11) 0.602 1.00(0.851.17) 0.962 Rec 1.06(0.781.45) 0.704 1.04(0.731.47) 0.840 G 2327(76.6) 2441(77.1) 1 1646(76.8) 1C 711(23.4) 723(22.9) 0.97(0.861.09) 0.606 496(23.2) 0.99(0.871.12) 0.836 miR-146a rs2910164

CC 537(35.4) 550(34.7) 1 387(36.1) 1CG 715(47.2) 775(48.9) 1.08(0.921.27) 0.360 505(47.2) 1.01(0.841.21) 0.927 GG 264(17.4) 259(16.4) 0.96(0.771.19) 0.691 179(16.7) 0.94(0.741.19) 0.620 Add 1.00(0.901.10) 0.934 0.98(0.871.10) 0.693 Dom 1.05(0.901.22) 0.567 0.99(0.841.17) 0.909 Rec 0.92(0.761.11) 0.378 0.94(0.761.16) 0.554 C 1789(59.0) 1875(59.2) 1 1279(59.7) 1G 1243(41.0) 1293(40.8) 0.99(0.901.10) 0.884 863(40.3) 0.97(0.871.09) 0.610

Table 3. Genotype distributions of the eleven SNPs among the cases and controls. aOR: odds ratio;

CI: condence interval, adjusted for age, sex, smoking and drinking. bSignicant aer the Bonferroni correction for multiple comparisons. Add: additive model; Dom: dominant model; Rec: recessive model.

for multiple comparisons. No signicant haplotypes were found be related to the treatment outcome (data not shown).

Discussion

The magnitude and complexity of the human immune response to mycobacteria have historically been underestimated23. It is vital to determine whether those who remain healthy have a genetically endowed high level of resistance to tuberculosis or whether the resistance is aected by environmental or other exogenous factors24.

The genome-wide association study (GWAS) identied several susceptibility loci for tuberculosis in sub-Saharan African, Russian and Moroccan populations2527. However, the follow-up studies reported conicting results28.

Gene SNPs Control (n=1526) n(%)

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Never(n=1738) Ever (n=1389)

Control(%) Case(%) OR(95%Cl)a P Control(%) Case(%) OR(95%Cl)a P IL-17A rs2275913

GG 290(29.7) 257(36.3) 1 160(29.3) 220(27.5) 1GA 487(49.9) 318(44.9) 0.74(0.590.92) 0.007 254(46.4) 411(51.4) 1.12(0.871.46) 0.380 AA 198(20.3) 133(18.8) 0.73(0.550.97) 0.028 133(24.3) 168(21.0) 0.88(0.651.21) 0.439 rs3819024

AA 268(27.5) 234(31.7) 1 154(28.0) 208(25.1) 1AG 492(50.5) 354(47.9) 0.80(0.641.01) 0.057 253(46.0) 430(51.9) 1.25(0.961.63) 0.100 GG 215(22.1) 151(20.4) 0.77(0.581.01) 0.063 143(26.0) 190(22.9) 0.96(0.711.31) 0.796 rs8193036

CC 502(51.5) 347(47.9) 1 281(51.1) 442(54.0) 1CT 401(41.2) 300(41.4) 1.08(0.881.33) 0.458 220(40.0) 318(38.8) 0.91(0.721.15) 0.437 TT 71(7.3) 78(10.8) 1.64(1.152.33) 0.006 49(8.9) 59(7.2) 0.83(0.541.26) 0.372 rs3748067

GG 696(71.4) 529(70.0) 1 398(72.5) 606(72.4) 1GA 256(26.3) 202(26.7) 1.08(0.871.35) 0.484 129(23.5) 213(25.4) 1.02(0.791.32) 0.882 AA 23(2.4) 25(3.3) 1.49(0.832.67) 0.181 22(4.0) 18(2.2) 0.66(0.341.26) 0.206 IL-17F rs763780

TT 747(76.6) 570(76.2) 1 428(77.8) 655(78.8) 1TC 205(21.0) 165(22.1) 1.06(0.841.34) 0.625 113(20.5) 158(19.0) 0.94(0.711.24) 0.651 CC 23(2.4) 13(1.7) 0.70(0.351.41) 0.318 9(1.6) 18(2.2) 1.29(0.572.95) 0.545 TLR4 rs10759932

TT 507(52.3) 323(43.4) 1 272(49.8) 399(47.8) 1TC 372(38.4) 348(46.7) 1.47(1.201.81) <0.001b 225(41.2) 349(41.8) 1.04(0.821.31) 0.751 CC 91(9.4) 74(9.9) 1.24(0.881.75) 0.214 49(9.0) 87(10.4) 1.23(0.831.82) 0.299 rs2737190

AA 363(37.8) 238(31.6) 1 194(35.6) 280(33.5) 1AG 437(45.5) 402(53.3) 1.43(1.151.78) 0.001b 253(46.4) 438(52.5) 1.17(0.911.49) 0.215 GG 161(16.8) 114(15.1) 1.05(0.781.41) 0.757 98(18.0) 117(14.0) 0.80(0.581.12) 0.200 rs10983755

GG 514(52.8) 369(48.9) 1 279(50.9) 437(52.4) 1GA 375(38.5) 322(42.6) 1.20(0.981.47) 0.074 225(41.1) 322(38.6) 0.89(0.711.13) 0.338 AA 84(8.6) 64(8.5) 1.03(0.721.47) 0.867 44(8.0) 75(9.0) 1.09(0.721.64) 0.685 rs7873784

GG 812(83.9) 606(81.7) 1 459(83.9) 704(84.3) 1GC 151(15.6) 129(17.4) 1.14(0.881.48) 0.332 84(15.4) 127(15.2) 0.99(0.731.34) 0.939 CC 5(0.5) 7(0.9) 1.92(0.606.15) 0.270 4(0.7) 4(0.5) 0.89(0.223.67) 0.873 rs11536889

GG 561(57.8) 456(61.0) 1 330(60.2) 497(59.6) 1GC 355(36.6) 254(34.0) 0.89(0.731.10) 0.276 190(34.7) 281(33.7) 1.04(0.821.32) 0.720 CC 55(5.7) 38(5.1) 0.87(0.561.35) 0.538 28(5.1) 56(6.7) 1.32(0.812.14) 0.267 miR-146a rs2910164

CC 327(33.8) 266(35.3) 1 210(38.3) 284(34.2) 1CG 471(48.7) 364(48.3) 0.93(0.751.16) 0.530 244(44.4) 411(49.5) 1.27(0.991.62) 0.057 GG 169(17.5) 123(16.3) 0.87(0.661.16) 0.352 95(17.3) 136(16.4) 1.07(0.771.48) 0.693

Table 4. The association between eleven SNPs and the risk of tuberculosis stratied by smoking. aOR: odds ratio; CI: condence interval, adjusted for age, sex and drinking. bSignicant aer the Bonferroni correction for multiple comparisons.

In the present study, we explored the genetic polymorphisms of IL-17, TLR4 and miR-146a in association with pulmonary tuberculosis in a Chinese Han population. To our knowledge, this is the rst study revealing the eect of genetic variations of rs10759932 and rs2737190 of TLR4 on the risk of tuberculosis. Haplotype analysis found an increased risk for tuberculosis among individuals carrying TLR4 rs10983755Grs10759932C. Moreover, we found that SNPs of rs3819024 in IL-17A and rs763780 in IL-17F might be weakly related to the tuberculosis prognosis.

Cytokine secretion is initiated by different immune cells interacting with bacteria29. IL-17 acts as a pro-inammatory cytokine by recruiting granulocytes to the sites of infection17. Previous studies have suggested the association between genetic polymorphisms of IL-17A/IL-17F and susceptibility to tuberculosis but with

Gene SNPs

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Gene SNP Success (n%) Failure (n%) RR(95%Cl)a P

IL-17A rs2275913GG 397(30.9) 23(43.4) 1

GA 635(49.4) 21(39.6) 0.60(0.331.08) 0.089 AA 253(19.7) 9(17.0) 0.62(0.291.32) 0.219 Add 0.75(0.501.10) 0.140 Dom 0.61(0.351.04) 0.069 Rec 0.82(0.401.64) 0.576 rs3819024

AA 376(28.1) 23(41.1) 1

AG 680(50.8) 22(39.3) 0.56(0.311.00) 0.049 GG 283(21.1) 11(19.6) 0.64(0.311.30) 0.219 Add 0.75(0.521.10) 0.143 Dom 0.59(0.340.99) 0.045 Rec 0.89(0.461.68) 0.719 rs8193036

CC 675(51.3) 23(42.6) 1

CT 531(40.3) 23(42.6) 1.21(0.692.12) 0.503 TT 111(8.4) 8(14.8) 2.09(0.954.36) 0.067 Add 1.38(0.932.05) 0.107 Dom 1.36(0.802.30) 0.251 Rec 1.91(0.913.86) 0.085 rs3748067

GG 971(71.9) 38(66.7)

AG 343(25.4) 18(31.6) 1.29(0.742.21) 0.373 AA 37(2.7) 1(1.8) 0.75(0.104.75) 0.769 Add 1.15(0.711.85) 0.581 Dom 1.24(0.722.11) 0.440 Rec 0.69(0.104.38) 0.712 IL-17F rs763780

TT 1056(78.6) 37(66.1) 1

TC 260(19.3) 18(32.1) 1.84(1.053.14) 0.032 CC 28(2.1) 1(1.8) 1.06(0.146.50) 0.955 Add 1.52(0.952.43) 0.082 Dom 1.77(1.022.99) 0.041 Rec 0.90(0.125.50) 0.918 TLR4 rs10759932

TT 622(46.2) 23(41.1) 1

TC 594(44.1) 27(48.2) 1.16(0.671.98) 0.601 CC 130(9.7) 6(10.7) 1.29(0.533.02) 0.573 Add 1.14(0.771.70) 0.515 Dom 1.18(0.701.98) 0.537 Rec 1.20(0.512.68) 0.675 rs2737190

AA 452(33.6) 18(32.1) 1

AG 703(52.2) 28(50.0) 0.98(0.551.75) 0.958 GG 191(14.2) 10(17.9) 1.34(0.622.78) 0.449 Add 1.13(0.761.67) 0.552 Dom 1.06(0.611.82) 0.840 Rec 1.35(0.692.60) 0.378 rs10983755

GG 682(50.7) 26(45.6) 1

GA 547(40.6) 27(47.4) 1.24(0.732.08) 0.431 AA 117(8.7) 4(7.0) 0.96(0.342.63) 0.937 Add 1.09(0.731.62) 0.690 Dom 1.19(0.711.97) 0.501 Rec 0.87(0.312.30) 0.778 rs7873784

Continued

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Gene SNP Success (n%) Failure (n%) RR(95%Cl)a P

GG 1120(83.3) 46(82.1) 1

GC 215(16.0) 9(16.1) 1.03(0.512.06) 0.924 CC 9(0.7) 1(1.8) 2.61(0.3512.18) 0.337 Add 1.16(0.622.17) 0.643 Dom 1.10(0.562.13) 0.780 Rec 2.60(0.3512.17) 0.339 rs11536889

GG 811(60.3) 31(55.4) 1

GC 453(33.7) 23(41.1) 1.31(0.772.21) 0.312 CC 81(6.0) 2(3.6) 0.66(0.162.63) 0.568 Add 1.07(0.701.64) 0.753 Dom 1.22(0.722.03) 0.453 Rec 0.60(0.142.32) 0.464 miR-146a rs2910164

CC 468(34.9) 20(35.7) 1

GC 660(49.3) 25(44.6) 0.91(0.511.60) 0.737 GG 212(15.8) 11(19.6) 1.18(0.572.38) 0.645 Add 1.06(0.731.54) 0.766 Dom 0.98(0.571.66) 0.930 Rec 1.25(0.652.36) 0.495

Table 5. The association analysis of genetic polymorphisms and treatment outcomes. aRR: rate ratio; CI: condence interval, adjusted for age and sex.

Figure 2. Graphical representation of the SNP locations and LD structure. The SNP distribution and haplotype block structure across IL-17A and TLR4 genes are shown. The measure of LD (D) among all possible pairs of SNPs is shown graphically according to the shade of color (A/B), where white represents very low D, and dark represents very high D. The numbers in squares are D values (D100).

inconsistent results18,3032. Du et al. observed that the rs763780-CC polymorphisms of the IL-17F gene were more likely to have an increased risk30. Ocejo-Vinyals et al. investigated the IL-17A rs2275913 polymorphisms and suggested that the GG genotype was related to an increased risk of tuberculosis18. Shi et al. genotyped rs2275913 and rs3748067 in IL-17A and rs763780 in IL-17F and found that the CC genotype of rs763780 was associated with an increased risk of tuberculosis32. Peng et al. conducted a study in a Chinese population and found that those carrying the CT/TT genotype of rs763780 were more susceptible to tuberculosis, but no signicant association was found for rs227591331. The discrepancies between these results may be due to the dierent ethnicities, study design and sample sizes32.

TLR4 is expressed on the plasma membrane and bind lipoprotein or lipid components of bacteria, and it may sense and simultaneously recognize various MTB-encoded factors. TLR4 signaling may have a critical function in

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Haplotype Control, n(%) Case, n(%) OR(95%Cl)a P

rs2275913-rs3748067

AG 1401(45.90) 1416(44.22) 1

GG 1176(38.53) 1285(40.13) 1.12(1.001..25) 0.046 GA 469(15.37) 493(15.4) 1.09(0.941.27) 0.265 AA 6(0.20) 8(0.25) 1.28(0.423.87) 0.667 rs10983755-rs10759932

GT 2159(70.74) 2156(67.33) 1

AC 846(27.72) 909(28.39) 1.08(0.961.21) 0.198 GC 36(1.18) 120(3.75) 3.43(2.345.05) <0.001b AT 11(0.36) 17(0.53) 1.42(0.653.09) 0.375

Table 6. The haplotype analysis on the risk of tuberculosis. aOR: odds ratio; CI: condence interval, adjusted for age, sex, smoking and drinking. bSignicant aer the Bonferroni correction for multiple comparisons.

ne tuning inammation during chronic mycobacterial infection33. The SNP rs10759932 is located in the 5 anking region of the TLR4 gene34. It has been reported to be associated with the risk of precancerous lesions in the stomach35, gastric carcinogenesis34 or prostate cancer36. In contrast to the ndings of a study in a Sudanese population37, we found that variations of this SNP were related to an increased risk of tuberculosis. The SNP rs2737190 is located in the 5-UTR of TLR4 gene. As 5-UTR inuences the translation of regulatory proteins, modulation of 5-UTR activity plays a role in the development or progress of specic forms of disease38. Zhou et al. have observed that the G allele was more frequent among preterm gram-negative bacterial infection neonates with a 32% increased risk39. We rst explored the eect of the polymorphism at this locus on susceptibility to pulmonary tuberculosis. Our ndings support the hypothesis that genetic polymorphisms of the TLR4 gene aect the hosts susceptibility to infectious diseases.

MiR-146a has been previously described as a negative regulator of the immune response and its systemic down-regulation may be associated with the exacerbated inammatory response in tuberculosis patients40.

Pre-miR-146a C/G polymorphism, designated rs2910164, is encoded on chromosome 5q33 and located in the precursor stem region, +60 relative to the rst nucleotide of pre-miR-146a, opposite the mature miR-146a sequence41. The change from the G:U pair to the C:U mismatch in the stem structure of the miR-146a precursor might reduce the stability of the pri-miR, the efficiency of processing pri-miR into pre-miR, or processing pre-miR into mature miR42. Previous studies indicated that miR-146a rs2910164 was related to an altered risk of colorectal cancer43, breast cancer or ovarian cancer44. To date, two studies have described the association between this SNP and tuberculosis45,46. One was performed in a Kazak population45, and another was conducted in a Tibetan/Han population46. However, our study did not replicate the previous signicant ndings in the Chinese Han population. This dierence might be attributed to the variations in allelic frequencies of genetic polymorphisms, and therefore, it is not surprising that the genetic association analyses yielded conicting results in different populations47.

Haplotype-based methods oer a powerful approach to disease gene mapping, based on the association between causal mutations and the ancestral haplotypes from which they arose48. In this study, we constructed an LD analysis and identied SNPs of IL-17A and TLR4 in a Chinese Han population. Our data showed a combined eect of rs2275913 together with rs3748067 on the risk of tuberculosis. Additionally, a LD was found between rs10983755 and rs10759932, contributing to the susceptibility of tuberculosis. LD is a concept of statistical correlation between alleles segregated at two or more loci. Population genetic factors can produce LD through a variety of processes such as natural selection, strong genetic dri, admixture and new mutations49. The association between each mutant allele and its ancestral haplotype is disrupted only by mutation and recombination in subsequent generations48. Further approaches should be carried out to identify the responsible functional SNPs in the LD areas where we identied risk haplotype alleles.

There are several limitations in this study. First, we purposely selected functional SNPs in the IL-17A, IL-17F and TLR4 gene. Although the analysis of the Encyclopedia of DNA Elements (ENCODE) as implemented in Regulome DB indicated that some SNPs might inuence the binding of specied transcription factors, their real functions were not proven with experimental evidence. Further work with both knockout and overexpression models is likely to be the most fruitful approach for understanding the mechanisms through which these variants inuence the risk of tuberculosis. Second, due to the weak eect of a single genetic polymorphism, other genes in the immunity pathway, together with environmental factors, should also be considered.

Conclusions

Taken together, our results suggest that genetic polymorphisms of rs10759932 and rs2737190 in TLR4 gene may play a role in susceptibility to tuberculosis in the Chinese population.

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The National Natural Science Foundation of China (81473027), Jiangsu Science Supported Planning/Social Development Foundation (BE2011841), Qing Lan Project (2014), Six Talent Peaks Project in Jiangsu Province (2014-YY-023), Zhenjiang Key Lab for Drug Resistant Tuberculosis (SS2013018), Jiangsu Provincial Clinical Medical Science and Technology Project (BL2014067) and Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD) supported this study. The funders had no role in the study design, data collection and analysis, decision to publish, or in the preparation of the manuscript.

M.W., G.X. and J.W. conceived the study. Y.C., H.P. and J.W. collected data. M.W., G.X., L.L. and K.X. performed the experiment. M.W. and G.X. performed the analysis. M.W., G.X. and J.W. draed the manuscript. B.B. and K.B. rened the manuscript. All authors reviewed the manuscript.

Competing nancial interests: The authors declare no competing nancial interests.

How to cite this article: Wang, M. et al. Genetic polymorphisms of IL-17A, IL-17F, TLR4 and miR-146a in association with the risk of pulmonary tuberculosis. Sci. Rep. 6, 28586; doi: 10.1038/srep28586 (2016).

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