Toll-like receptor 2 polymorphisms and their effect on the immune response to ESAT-6, Pam3CSK4 TLR2 agonist in pulmonary tuberculosis patients and household contacts

Cytokine 126 (2020) 154897

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Toll-like receptor 2 polymorphisms and their effect on the immune response to ESAT-6, Pam3CSK4 TLR2 agonist in pulmonary tuberculosis patients and household contacts

T

Jyothi Priya Mandalaa,b, Shazia Ahmada,b, Ashwini Pullagurlaa,b, Shruthi Thadaa,c, Lavanya Joshia, Mohd. Soheb Sadat Ansaria, Vijaya Lakshmi Valluria, Suman Latha Gaddam ⁎ (Assistant professor)a,b, a

Bhagwan Mahavir Medical Research Centre, Hyderabad, India Department of Genetics, Osmania University, Hyderabad, India Institute of Microbiology and Hygiene, Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany b c

A R T I C LE I N FO

A B S T R A C T

Keywords: Tuberculosis Immunogenetics Toll-like receptor polymorphisms Pam3CSK4 and ESAT-6 stimulation Immune response South India

Toll-like receptors (TLRs) play a pivotal role in organizing the effective immune response through inducing the pro-inflammatory cytokines for control of tuberculosis infection and TLR polymorphisms are associated with altered cytokine levels have been described. Therefore, the main aim of the present study was to confirm whether TLR2 (C2029T, G2258A) polymorphisms effects the cytokine production in PTB patients and Household contacts (HHC), healthy controls (HC). The polymorphisms were performed by amplification refractory mutation system-polymerase chain reaction (ARMS) & Restriction Fragment Length Polymorphism (RFLP) in 336 subjects. Cytokine levels were estimated in Pam3CSK4, antigen ESAT-6 stimulated culture supernatants by EnzymeLinked Immunosorbent Assay. Under the over-dominant model GA genotype of G2258A SNP and CT genotype of the co-dominant model in C2029T SNP showed a susceptible effect in patients, whereas in HHC, CT genotype showed a protective effect. A significant decreased TNF-α, IL-12 and increased IL-1β levels were observed after Pam3CSK4, antigen ESAT-6stimulation; our results showed the following associations: TLR2 G2258A SNP of GA with decreased TNF-α; TLR2 C2029T SNP of CT, TT with decreased IL-12 and increased IL-1β levels. Regression analysis demonstrated that age, BCG, gender and T allele were significantly associated with TB. Pre-mRNA secondary structure of the A, T alleles are more stable than G, C alleles. Altogether, we suggest that cytokine levels, 2029T allele, TLR2 polymorphisms were considered as predictive markers for identification of high-risk individuals in TB.

1. Introduction Tuberculosis (TB) is a major cause of death in human beings and caused by an intracellular pathogen called Mycobacterium tuberculosis (M. tb). WHO reported that 1.7 billion people infected with M. tb will develop TB disease during their lifetime and 1.8 million TB - related deaths occurred in 2016 and TB is the ninth leading cause of death worldwide [1]. Generally, either pulmonary TB infects the lungs, which can progress to active, or chronic latent infection, sometimes it can affect other sites called extra pulmonary TB. Aerosol transmission is the major route of infection, when a person with active pulmonary tuberculosis coughs, sneezes or spits [2]. Most of the latent TB infected

⁎

people do not develop the active disease; only 5–10% of infected individuals who do not take treatment will get the active disease at different stages of the immune response [1]. In addition, presentation of the disease itself is a diverse process, which illustrates that many risk factors like a person with immunocompromised systems such as HIV infected people, under-nutrition, diabetes, smoking, and alcohol consumption, close contacts and household contacts of a person with active TB play a significant role in TB diversity and susceptibility towards the disease. Many studies were reported that household contacts comprise a high-risk group in developing active TB; this fact together with other substantial evidence indicates that the pathogen virulence and host genetic polymorphisms have been supposed to play a vital role in TB

Corresponding author at: Bhagwan Mahavir Medical Research Centre, Hyderabad, India. Department of Genetics, Osmania University, Hyderabad, India. E-mail addresses: [email protected] (J.P. Mandala), [email protected] (S.L. Gaddam).

https://doi.org/10.1016/j.cyto.2019.154897 Received 30 December 2018; Received in revised form 29 April 2019; Accepted 22 October 2019 1043-4666/ © 2019 Elsevier Ltd. All rights reserved.

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Linked Immunosorbent Assay (ELISA) of TNF-α, IL-12, IL-1β (before the start of the treatment) performed in Pulmonary Tuberculosis patients (PTB) = 33 Household contacts of PTB (HHC) = 60 and HC = 31.

susceptibility [3–5]. This can affect either from insufficient or excessive acute inflammatory response, which is controlled by single nucleotide polymorphisms (SNPs) in genes [6,7]. The innate immune system contains different phagocytic cells, which presents and process the antigens for T-cells and involves in T-cell-mediated immunity, phagocytic cells with its own receptors helps in pathogen recognition, which triggers the cell-mediated immune response in the host and induces the secretion of different kind of cytokines by macrophages and dendritic cells. This immediate response helps in preventing bacterial growth and suppresses the infection. But, pathogens have evolved many ways to avoid killing by immune response mechanisms to protect themselves and survive within the host [8,9]. Host immune resistance mechanisms involve innate and adaptive immune systems. The innate immune response depends on the recognition of several receptors appears on phagocytic cells in which TLR are an important component of innate immunity [10]. In a total of 11 TLR’s were found in human and mouse and each TLR is recognized by specific ligand. TLR2 detects its tri- or diacylated lipoproteins by forming hetero dimmers with TLR1 or TLR6, respectively [11]. Immune recognition of M.tb ligand and antigen during phagocytosis by TLR2 triggers MyD88 (adapter protein) dependent signaling pathway leads to the secretion of pro-inflammatory cytokines. TLR2 gene has located on chromosome 4q32 and has two exons, but all coding sequences are contained within exon 2. Several studies were reported that TLR2 polymorphisms (G2258A, T597C, T1350C) and in some TLR pathways control the immune response to bacterial components which could affect the susceptibility to TB [12–15]. But contrast results were also found in some studies [16,17]. To the best of our knowledge, this is the first study observed the influence of TLR2 gene polymorphisms on pro-inflammatory cytokine levels along with pre-mRNA secondary structures for susceptibility to TB in patients and household contacts. We found a wide variation in the human whole-blood cytokines response to TLR2 ligand and antigen stimulation and there were no reports were found in this population. Therefore, we aimed to study the effect of single-nucleotide polymorphisms in the exonic region of TLR2 (G2258A; rs5743708), (C2029T; rs121917864) genes on cytokine production in patients, HHC and HC in relation to tuberculosis susceptibility.

2.3. Preparation and stimulation of peripheral blood mononuclear cells Heparinized blood was drawn from subjects into sodium heparin tubes, and PBMC were isolated by density sedimentation over Histopaque-1077 (Sigma, St. Louis, MO, USA). PBMC were suspended at a density of 2 × 106 viable cells/ml in complete medium [RPMI 1640 (Rosewell park memorial institute) (Sigma, St Louis, MO, USA) with 10% fatal bovine serum (GIBCOBRL), sodium pyruvate, non-essential amino acids, penicillinG (100 IU/ml) and streptomycin (100 mg/ml)]. In addition, the viability of the cells was checked using trypan blue. Cells were then stimulated with ligand Pam3CSK4 (PAM) (Catalog no. tlrl-pms, InvivoGen, San Diego, CA, 100 ng/mL), antigen ESAT6 (cat# NR-14868) (5 µg/mL) were obtained from BEI resources. Ligand and the antigen selected for specificity to the cell surface pattern recognition receptor of TLR2. The plate was incubated at 37°C in a 5% CO2 humidified air atmosphere until used for supernatant collection. Cytokine measurements TNF-α, IL-12, IL-1β concentrations were measured in culture supernatants collected from the PBMCs stimulated with Pam3CSK4, ESAT-6 by a commercial ELISA kit for cytokine detection (BD opt EIA for human TNF-α, IL-12, IL-1β). The preparation of all reagents, the working standards and the protocol followed according to the manufacturer's instructions (BD Biosciences Bangalore). Moreover, the absorbance was read using an ELISA reader (BIO-RAD) at 450 nm and 570 nm dual filters 2.4. Single nucleotide polymorphism genotyping Genomic DNA from peripheral blood (1–2 ml) was extracted using Flexi gene kit according to the manufacturer’s protocol. The genotyping performed as described in our previous work [18]. NanoDrop confirmed the DNA quantification and DNA was stored at −20 °C until use. 2.5. TLR2(2029C/T) genotyping

2. Materials and methods RFLP-PCR (Restriction Fragment Length Polymorphism) was performed for TLR2 (2029C/T) genotyping using forward primer 5′TACT GGGTGGAGAACCTTAT3′ & reverse primer 5′AGTTCATACTTGCACCA CTC3′ with cycling conditions of 94 °C for 2 min followed by 35 cycles at 95 °C for 30 s, 55 °C for 30 s, 72 °C for 60 s and finally for 60 s extension at 72 °C. 194 bp fragments after digestion with the AciI enzyme at 65 °C for 30 min produced three fragments (194, 121 and 73 bp) in TLR2 (2029C/T) heterozygote in homozygote TLR2 (2029C/C) gives two fragments with 121 bp, 73 bp and in homozygote (T/T) undigested product of 194 bp was observed.

2.1. Subjects A total of 336 participants each of 102 patients, their HHC = 102 who attended Free Chest TB Clinic at Mahavir Hospital & Research Centre, Hyderabad, India. HC = 132 who had no history of tuberculosis were studied. Patients were categorized based upon Sputum, smear examination for Acid Fast Bacilli, Sputum culture and Chest X-ray. Body mass index has been calculated. Informed consents were obtained from all the patients and their HHC. Tuberculin skin test (TST) positivity was assessed by administering five tuberculin units sub-cutaneous on the left arm. An induration of > 10 mm in between 48 and 72 h was considered positive (TST+). Tuberculin Skin Test (TST) was not performed in HC. An Institutional ethical committee has approved the study. Patients of either sex, their contacts & healthy controls, patients who are sputum positive for pulmonary tuberculosis as per the RNTCP/WHO guidelines and patients who are willing to give the consent were involved in the study. The exclusion criteria include the presence of causes of secondary immunodeficiency such as HIV, transplant patients, malignancy, cardiac patients who were unwilling or unable to comply with the study.

2.6. TLR2 (2258G/A) genotyping ARMS-PCR (Amplification refractory mutation system-polymerase chain reaction) was carried out for TLR2 (2258G/A) genotyping using common primer 5′TGACATAAAGATCCCAACTAGACAA3′, G allele primer 5′GGTCTTGGTGTTCATTATCTTCC3′ and A allele primer 5′ GGTCTTGGTGTTCATTATCTTCT3′, with cycling conditions of 95 °C for 8 min followed by 30 cycles at 95 °C for 90 s, 60 °C for 90 s, 72 °C for 60 s and finally for 10 min extension at 72 °C. Product size of 328 bps was detected. The primers were designed using primer-BLAST (NCBI) and were purchased from Eurofins. PCR mix (buffer, dNTPs, Taq polymerase) was obtained from Genie Bangalore and amplification step was performed using Bio-Rad thermal cycler. Electrophoresis of PCR reaction was carried out on 2% agarose gel stained with ethidium bromide and gel image was visualized by UV transilluminator.

2.2. Sample collection A total of 10 ml blood was drawn from each subject (PTB, HHC& HC) which was collected in Heparin tubes for assay, EDTA tubes for DNA isolation and SNP studies. Cell-Mediated Immunity and Enzyme2

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2.7. Statistical analysis The differences in the distributions of clinical characteristics of three study groups (Patients, House Hold Contacts (HHC) and Healthy Controls (HC) were evaluated by using the Student’s t-test (for continuous variables) or x2-test (for categorical variables). Genotypes were tested for deviation from Hardy-Weinberg equilibrium (HWE) with x2test. The cytokine levels were analysed by GraphPad Prism software (version 5.0). Genotypic distribution and the corresponding odds ratios (OR) was assessed under the dominant, recessive and over-dominant genetic models, using the online tool SNPstats and a one-way analysis of variance (ANOVA) with a Tukey posthoc test was used for comparison of 3 groups were calculated using SPSS, p-value of less than 0.05 was considered as statistically significant. Multivariate logistic regression analysis with a stepwise approach was applied in the choice of variables. The analyzed variables were age, sex, BCG, BMI and the presence of the 2029T allele. Variables with a p-value of < 0.05 were considered and the variables p > 0.1 were excluded from the regression analysis. The model with the largest area under the curve (AUC) was considered. Statistical analyses were performed using MedCalc Statistical Software (MedCalc Software, Ostend, Belgium2). Insilico analysis was done for secondary pre-mRNA structure to conclude changes its associated free energy by using online Vienna RNAfold WebServer (http://rna.tbi.univie.ac.at/). 3. Results

Fig. 1. TLR2 (2029C/T), TLR2 (2258G/A) gene polymorphism. (A) Agarose gel image showing the RFLP-PCR products of TLR2 2029C/T polymorphism Lane 1–100 bp ladder; Lane 2,5,7,9-TT genotype; Lane 3,4,6,10-CC genotype; Lane 8-CT genotype (B) Agarose gel image showing the ARMS-PCR products of TLR2 −2258G/A polymorphismLane 1–100 bp ladder; Lane 2–3; GA genotype; 4–5,6–7; -GG genotype; 8-9; -AA genotype.

3.1. Demographic characteristics In a total of 105 active TB patients, 102 household contacts and 139 healthy controls were enrolled in this study. All these categories include age, sex, BCG scar, body mass index (BMI) and tuberculin skin test (TST) was assessed both in patients and HHC for analyzing the data. Among these numbers of males were more in PTB, HC. However, PTB & HHC showed a significant difference when compared to HC. The age of PTB, HHC and HC were (32.04 ± 1.270; 29.53 ± 1.099; 31.01 ± 0.6739), but HHC showed a significant difference when compared to HC. The TST-negative and BCG scar negative individuals were more in PTB and HHC, HC showed more scar positive individuals but patients, HHC showed a significant difference in scar status. A significant difference in BMI was observed between the groups (Table1).

significant difference was observed in PTB vs HC (p < 0.0001), HHC vs. HC (p < 0.0023) and PTB vs. HHC (p < 0.0224) (Fig. 2A). Similarly, low IL-12 levels were produced in PTB, HHC (43.54 ± 4.098, 74.31 ± 8.709 pg/ml) compared to HC (89.11 ± 10.5 pg/ml) and significant difference was observed in PTB vs HC (p < 0.0010), PTB vs HHC (p < 0.0253) (Fig. 2C). But, high IL-1β levels were observed in PTB, HHC (47.46 ± 4.703, 32.71 ± 2.693 pg/ml) compared to HC (34.8 ± 3.447 pg/ml), a significant difference was observed in PTB vs. HHC (p < 0.0166) (Fig. 2B).

3.2. Cytokine profiles in PAM, ESAT-6 stimulated culture supernatants:

3.4. Cytokine profiles with ESAT-6 stimulation in PTB patients, HHC and HC:

TNF-α, IL-12, IL-1β cytokine production were measured in Pulmonary Tuberculosis patients (PTB) = 33, Household contacts of PTB (HHC) = 60 and Healthy Controls (HC) = 31 at (before the start of treatment).

The mean values of TNF-α cytokine were significantly low among PTB (34.25 ± 5.345 pg/ml) and HHC (31.63 ± 2.48 pg/ml) compared to HCs (64.78 ± 9.661 pg/ml) (P < 0.0024) (Fig. 3A). The IL12 levels did not show any significant difference and showed low values in PTB (43.27 ± 4.156 pg/ml), as compared to HHC (52.23 ± 5.339 pg/ml) and HCs (60.46 ± 10.69 pg/ml) (Fig. 3C). IL1β levels also were elevated among PTB (45.94 ± 4.31 pg/ml) compared to HHC (40.94 ± 3.325 pg/ml) and HC (33.47 ± 3.433 pg/ml). A significant difference was observed between P vs HC and HHC vs HC

3.3. Cytokine profiles with PAM stimulation in PTB patients, HHC and HC: Cytokine levels were assessed in the PBMC’s produced significantly low TNF-α levels in PTB, HHC (22.88 ± 3.241, 51.35 ± 7.771 pg/ml) compared to HC (65.24 ± 7.171 pg/ml) when stimulated with PAM. A

Table 1 Clinical characteristic of PTB, HHC and HC. Mean ± SEM, independent samples t-test, *P value by chi-square analysis; ns- not significant, NA–not applicable tests, p/n, positive/negative; TST, tuberculin skin test; BMI, body mass index. Variable

PTB (n = 105)

HHC (n = 102)

HC (n = 139)

PTB vs HC p-value

HHC vs HC p-value

Age (Mean ± SEM) Gender M/F (%) TST P/N (%) BMI(Kg/m2) BCG Scar P/N (%)

32.04 ± 1.270 57 (49.5)/48 (45.71) 52 (49.52)/53 (50.47) 19.0643 ± 0.4084 45 (42.85)/60 (57.14)

29.53 ± 1.099 50 (49)/52 (50.98) 37 (36.27)/65 (63.7) 20.0288 ± 0.4042 28 (27.45)/74 (72.5)

31.01 ± 0.6739 101 (72.66)/38 (27.3) NA 23.96 ± 0.3125 122 (87.7)/17 (12.23)

NS 0.0029* NA 0.0001* 0.0001*

0.027* 0.0002* NA 0.0001* 0.0001*

3

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Fig. 2. Immune responses in PAM stimulated culture supernatants TB cases, HHC and HC. (A) TNF-α levels in PAM stimulated culture supernatants of PTB patients, their HHC, and HC. (B) IL1β levels in PAM stimulated culture supernatants of PTB patients, their HHC, and HC. (C) IL-12 levels in PAM stimulated culture supernatants of PTB patients, their HHC, and HC. Horizontal lines indicate a statistically significant difference between groups. Differences between the groups were analyzed by Mann-Whitney U test. p < 0.05 was considered statistically significant.

Fig. 3. Immune responses in ESAT-6stimulated culture supernatants TB cases, HHC and HC. (A) TNF-α levels in ESAT-6 stimulated culture supernatants of PTB patients, their HHC, and HC. (B) IL1β levels in ESAT-6 stimulated culture supernatants of PTB patients, their HHC, and HC. (C) IL-12 levels in ESAT-6 stimulated culture supernatants of PTB patients, their HHC, and HC. Horizontal lines indicate a statistically significant difference between groups. Differences between the groups were analysed by Mann-Whitney U test. p < 0.05 was considered statistically significant.

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Table 2 Comparison of Immune responses in PTB cases, HHC and HC. Mean ± SEM, PTB-pulmonary tuberculosis patients, HHC-household contacts of PTB, HC-healthy controls, NS-not significant, P < 0.05 was considered statistically significant. Cytokine

Stimulation

PTB

TNF-α IL-1β IL-12 TNF-α IL-1β IL-12

PAM PAM PAM ESAT-6 ESAT-6 ESAT-6

(22.88 (47.46 (43.54 (34.25 (45.94 (43.27

HHC ± ± ± ± ± ±

3.241) pg/ml 4.703) pg/ml 4.098) pg/ml 5.345) pg/ml 4.31) pg/ml 4.156) pg/ml

(51.35 (32.71 (74.31 (31.63 (40.94 (52.23

± ± ± ± ± ±

7.77) pg/ml 2.693) pg/ml 8.709) pg/ml 2.48) pg/ml 3.325) pg/ml 5.339) pg/ml

HC

PTB vs HC p-value

PTB vs HHC p-value

HHC vs HC p-value

(65.24 ± 7.171) pg/ml (34.8 ± 3.447) pg/ml (89.11 ± 10.5) pg/ml (64.78 ± 9.661) pg/ml (33.47 ± 3.433) pg/ml (60.46 ± 10.69) pg/ml

0.0001 NS 0.0010 0.0024 0.023 NS

0.0224 0.0166 0.0253 NS NS NS

0.0023 NS NS 0.0003 0.0451 NS

3.6. The genotypes and alleles frequencies comparison inTLR2 (2258G > A, 2029C > T) polymorphisms among PTB patients, HHC and healthy controls

Table 3 One-way ANOVA analysis for TNF-α, IL-1β and IL-12 levels in PTB patients, their HHC and HC. ANOVA Cytokines

Comparisons

Degrees of freedom

F statistic

P-value

TNF-α

Between Groups Within Groups Total Between Groups Within Groups Total Between Groups Within Groups Total

2 118 120 2 116 118 2 118 120

6.249 – – 5.439 – – 6.088 – –

0.003 – – 0.006 – – 0.003 – –

IL-1β

IL-12

The genotypes and alleles frequencies of 2258G > A, 2029C > T are studied (Tables 4 and 5). TLR2 polymorphisms was performed in 336 subjects (102 = TB patients, 102 = household contacts and HCs = 132). The genotype frequencies were all similar when compared between the subjects and were insignificant for (2258G > A) polymorphism. High GG genotype frequency was observed when compared to the GA and AA genotypes in PTB, HHC and HC respectively. The G allele frequency was high when compared to that of A allele in TB, HHC and HCs respectively. There was no significant association with the allele frequency in both TB and HHC when compared to that of the HC. In TLR2 2029C > T polymorphism, the high CC genotype frequency was observed when compared to the CT and TT genotypes in PTB, HHC and HC respectively. C allele frequency was found to be high when compared to that of the T allele in TB, and HCs but in HHC T allele frequency was found to be high compared to C allele.

p < 0.05 was considered statistically significant.

at P < 0.023, P < 0.0451 respectively (Fig. 3B). Comparison of immune responses in PTB cases, HHC and HC were shown in Table 2.

3.7. Association of TLR2 SNPs and PTB 3.5. One-way analysis of variance (ANOVA)

For TLR2 2029C/T polymorphism the product size was 194 bp and 328 bp for TLR2 2258 G/A polymorphism was considered as detected amplification (Fig. 1A, B).

The comparisons between groups were carried out by using analysis of variance (ANOVA). Our results of ANOVA illustrating a significant difference in the TNF-α, IL-12 & IL-1β levels between the subjects at p < 0.05. ANOVA with Post hoc test for comparisons by using the Tukey HSD and Bonferroni test applied for three markers confirmed that there was a significant difference in mean levels between the group's Table 3.

3.8. Genotype distribution of TLR2 (2258 G > A) (2029C > T) gene polymorphisms in PTB, HHC Comparison of genotypes and allele frequencies of TLR2 2258 G > A SNP in PTB, HHC and HC revealed that the G/A genotype (p < 0.032, OR 1.91, 95% CI (1.05–3.47) of the over-dominant model

Table 4 Allele distribution of TLR2 (2258G > A) (2029C > T) gene polymorphisms in PTB patients, HHC and HC. Alleles

HC N = 264(%)

TB N = 204(%)

OR (95%CI) p-value

HHC N = 204 (%)

OR (95% CI) p-value

G

196 (74)

161 (79)

138 (68)

A

68 (26)

43 (21)

1.299 (0.822–2.055) 0.273 0.770 (0.487–1.216) 0.273

0.725 (0.475–1.107) 0.123 1.379 (0.903–2.104) 0.123

C

191 (72)

142 (70)

0.87 (0.574–1.335) 0.538

83 (41)

0.262 (0.174–0.394) 0.0001*

T

73 (28)

62 (30)

1.142 (0.749–1.742) 0.538

121 (59)

3.814 (2.540–5.735) 0.0001*

Tuberculosis patients, HHC-Household Contacts of TB, HC-Healthy Controls, OR-Odds Ratio, CI-Confidence Interval. 5

66 (32)

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Table 5 Genotype distribution of TLR2 (2258G > A) (2029C > T) gene polymorphisms in TB patients, HHC and HC. Model

Co–dominant

Genotype

G/G

C/C

50 (49%) 38 (37.2%) 14 (13.7%) 50 (49%) 52 (51%) 88 (86.3%) 14 (13.7%) 64 (62.8%) 38 (37.2%) 20 (19.6%)

C/T

20 (19.6%)

43 (42.2%)

T/T

21 (20.6%)

39 (38.2%)

C/C

61 (59.8%)

20 (19.6%)

C/T-T/T

41 (40.2%)

82 (80.4%)

C/C-C/T

81 (79.4%)

63 (61.8%)

T/T

21 (20.6%)

39 (38.2%)

C/C-T/T

82 (80.4%)

59 (57.8%)

C/T

20 (19.6%)

43 (42.2%)

A/A G/G G/A-A/A Recessive

G/G-G/A A/A

Over -dominant

G/G-A/A G/A

Co–dominant

Dominant

Recessive

Over -dominant

HHC N = 102 (%)

69 (67.7%) 23 (22.6%) 10 (9.8%) 69 (67.7%) 33 (32.4%) 92 (90.2%) 10 (9.8%) 79 (77.5%) 23 (22.6%) 61 (59.8%)

G/A

Dominant

TB N = 102 (%)

HC N = 132(%)

75 (56.8%) 46 (34.9%) 11 (8.3%) 75 (56.8%) 57 (43.2%) 121 (91.7%) 11 (8.3%) 86 (65.2%) 46 (34.9%) 68( 51.5%) 55 (41.7%) 9 (6.8%) 68 (51.5%) 64 (48.5%) 123 (93.2%) 9 (6.8%) 77 (58.3%) 55 (41.7%)

TB vs HC

HHC vs HC

OR (95% CI)

p-value AIC value

OR (95% CI)

p-value AIC value

1.00

0.096 315.2

1.00

0.2 309.5

1.88 (1.02–3.46) 0.88 (0.34–2.24) 1.00 1.56 (0.90–2.70) 1.00 0.72 (0.29–1.81) 1.00 1.91 (1.05–3.47) 1.00 2.37 (1.27–4.44) 0.37 (0.16–0.89) 1.00 1.35 (0.79–2.30) 1.00 0.28 (0.12–0.64) 1.00

0.75 (0.42–1.34) 0.46(0.19–1.13) 0.11 315.3

0.49 317.4

0.032 313.3

2e-04 302.6

0.27 316.7

0.0018 308.2

5e-04 305.9

2.83 (1.54–5.20)

1.00 0.67 (0.39–1.15) 1.00 0.52 (0.22–1.23) 1.00 0.86 (0.49–1.50) 1.00 0.34 (0.18–0.67) 0.06 (0.03–0.16) 1.00 0.21 (0.11–0.39) 1.00 0.12 (0.05–0.26) 1.00

0.15 308.6

0.13 308.5

0.59 310.5

< 0.0001 268.3

< 0.0001 283.8

< 0.0001 276.8

0.76 310.7

0.92 (0.53–1.58)

Tuberculosis patients, HHC-Household Contacts of TB, HC-Healthy Controls, OR-Odds Ratio, CI-Confidence Interval.

3.9. Association ofTLR2 (2258 G > A) (2029C > T) gene polymorphisms of genotypes with cytokine levels:

was found to be susceptible to statistical significance in PTB patients when compared to the HC. HHC has not shown a significant association when compared to the HC. The G/A genotype was found to be 1.191 times at risk in PTB patients when compared to the HCs. Based on the AIC over-dominant model was the best fit model in the PTB. There was no significant association with the allele frequency in PTB, HHC when compared to that of the HC. In TLR2 2029C > T SNP, C/T genotype (p < 2e−04, OR 2.37, 95% CI 1.27–4.44) of co-dominant model, (p < 5e−04, OR 2.83, 95% CI (1.54–5.20) over dominant was found to be susceptible and associated with TB in PTB patients when compared to the HCs. In addition, T/T genotype of co-dominant model (p < 2e−04, OR 0.37, 95% CI (0.16–0.89), recessive model (p < 0.0018, OR 0.28, 95% CI (0.12–0.64)) was found to be protective in PTB when compared to HC. The C/T genotype was found to be 2.37 times at risk in PTB patients when compared to the HCs. Based on the AIC Co-dominant model was considered as the best-fit model in PTB patients. Whereas in HHC C/T, T/T genotypes of co-dominant model (p < 0.0001, OR 0.34, 95% CI (0.18–0.67) (p < 0.0001, OR 0.06, 95% CI (0.03–0.16), C/T-T/T genotype of dominant model (p < 0.0001, OR 0.21, 95% CI (0.11–0.39)) and T/T genotype of recessive model (p < 0.001, OR 0.12 95% CI (0.05–0.26)) was found to be protective in HHC when compared to HCs. The C allele was negatively associated in HHC (p < 0.0001, OR 0.262, 95% CI 0.174–0.394), whereas T allele was, positively associated in HHC (p < 0.0001, OR 3.814, 95% CI 2.540–5.735) when compared to HC. There was no significant association with the allele frequency in PTB when compared to that of the HC (Tables 4 and 5).

The GA genotype of (2258G > A) SNP showed decreased TNF-α levels in culture supernatants between PTB and HHC when compared with HC at P < 0.05 (Fig. 4A). In addition, the TT genotype of (2029C > T) SNP with significantly increased IL-1β levels was observed in PTB & HHC at P < 0.0001& P < 0.034 (Fig. 4B). The CT, TT genotypes of (2029C > T) SNP with significantly decreased IL-12 levels and it was a low producer compare to other genotypes in PTB and HHC when compared with HC at P < 0.008 (Fig. 4C). 3.10. Multivariate logistic regression analysis (MLR) Multivariate logistic regression analysis was applied for all the clinical characters and the TLR2 SNP to know the association with PTB by using a logistic regression model, which includes gender, age, BCG, BMI & TST with TLR2 alleles in PTB, HHC&HC. Gender was not affected in the analysis. Logistic regression with a stepwise approach only showed the variables with age, (OR = 1.0625; CI = 1.0190–1.1079; p = 0.0045), BCG (OR = 10.9205; CI = 4.6867–25.4459; p = 0.0001), BMI (OR = 0.6888; CI = 0.6152–0.7711; p = 0.0001) and allele 2029 T (OR = 2.5451; CI = 1.1002–5.8873; p = 0.0290) significantly associated with the PTB in patients (Table 6). where as in HHC significance association with TB was observed in gender (male) (OR = 2.3958; CI = 1.0688–5.3700; p = 0.0339), BCG (OR = 25.8732; CI = 10.8405–61.7519; p = 0.0001), BMI (OR = 0.7488; 6

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Fig. 4. Comparison of TLR2 gene polymorphisms of TLR2 (2258G/A), TLR2 (2029C/T), with culture supernatant levels (TNF-α, IL-1β, IL-12). (A) Comparison of TLR2 gene polymorphisms of (2258G/A) with culture supernatant of TNF-α levels; (B) Comparison of TLR2 gene polymorphisms of (2029C/T), with culture supernatant of IL-1β levels; (C) Comparison of TLR2 gene polymorphisms of (2029C/T), with culture supernatant of IL-12 levels; Vertical axis- culture supernatant levels showing mean values; Horizontal axis- genotypes of TLR2 (2258G/A); TLR2 (2029C/T), PTB-pulmonary tuberculosis patients; HHC-household contacts; HChealthy controls.

IL-12, the sensitivity, specificity was 96.97%, 45.71% respectively. In patients the ROC curve analysis of these three cytokines TNF-α, IL-12 were statistically significant and TNF-α with the highest AUC score compared to IL-12, IL-1β as shown in Table 8. In the HHC group, ROC analysis for three markers, AUC of TNF-α, IL-1β and IL-12 was 0.732 (95% CI: 0.614–0.851), 0.626 (95% CI: 0.505–0.748), 0.501 (95% CI: 0.372–0.631) respectively (Fig. 6). The marker IL-12 is less likely to contribute to the separation of study groups compared to other markers. In HHC when using the best cut-off value of 57.13 for TNF-α, the sensitivity, specificity was 94.12%, 41.94%; a cut-off value of 4.17 for IL-1β, the sensitivity, specificity was 100%, 15.15%; a cut-off value of 24.651 for IL-12, the sensitivity, specificity was 76.47%, 33.33%. ROC curve analysis of these three cytokines TNF-α and IL-1β in HHC group showed statistically difference and TNF-α having highest AUC score compare to IL-12, IL-1β as shown in Table 9. These results demonstrated that the comparison of three markers through ROC analysis in patients and HHC. As regards TNF-α, in patients, with less than 33.73 was considered as high-risk and above that threshold were low-risk individuals. Likewise, in IL-12, the subjects who were having less than 86.59 value considered high risk and above that threshold value measured as low risk. Similarly, TNF-α, in HHC, with less than 57.13 were measured as high risk and above that threshold considered as a low risk, in IL-1β, the subjects with less 4.17 value were measured as high risk and above the threshold value considered as low risk.

Table 6 Multivariate logistic regression for Patients. Variable (Patients)

Odds ratio

95% CI

P-value

AGE BCG BMI 2029T

1.0625 10.9205 0.6888 2.5451

1.0190–1.1079 4.6867–25.4459 0.6152–0.7711 1.1002–5.8873

0.0045 < 0.0001 < 0.0001 0.0290

Table 7 Multivariate logistic regression for HHC. Variable(HHC)

Odds ratio

95% CI

P- value

AGE BCG BMI Male 2029T

1.0525 25.8732 0.7488 2.3958 3.9181

1.0081–1.0989 10.8405–61.7519 0.6704–0.8364 1.0688–5.3700 1.6416–9.3514

0.0199 < 0.0001 < 0.0001 0.0339 0.0021

CI = 0.6704–0.8364; p = 0.0001), age (OR = 1.0525; CI = 1.0081–1.0989; p = 0.0199) and 2029 T allele (OR = 3.9181; CI = 1.6416–9.3514; p = 0.0021) (Table 7). 3.11. ROC curve analysis

3.12. Pre-mRNA secondary structure of TLR2 (2029 C/T, 2258 G/A) polymorphisms

TNF-α, IL-1β and IL-12 were selected for ROC analysis. The ROC curves were found by comparing PTB, HHC and HC for the marker’s TNF-α, IL-1β and IL-12 and the cut-off values were measured based on the maximum Youden’s index. The Area under the ROC curve (AUC) of TNF-α, IL-1β and IL-12 was 0.899 (95% CI: 0.798–0.960), 0.594 (95% CI: 0.467–0.712), 0.738 (95% CI: 0.618–0.857) respectively (Fig. 5). In an additional way, the IL-1β marker is not as much likely to contribute to the separation of study groups compared to other markers. When considering the best cut-off value of 33.738 for TNF-α, the sensitivity, specificity was 87.8%, 77.4%; a cut-off value of 18.764 for IL-1β, the sensitivity, specificity was 100%, 33.33%; a cut-off value of 86.595 for

Using the Vienna RNA fold webserver, we determined the effect of TLR2 variants on mRNA secondary structures. We detected the secondary pre-mRNA structures of the wild-type allele and variant allele. Our results indicated the difference in pre-mRNA secondary structures and minimum free energy of variant T; A alleles are much more stable when compared to wild-type C, G structures as shown in Fig. 7. The T, A alleles showed minimum energy of −140.24 kcal/mol, −26.48 kcal/ mol while C, G alleles showed the energy of −138.86 kcal/mol, 7

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Fig. 5. ROC plots for TNF-α, IL-12 and IL-1β for the comparison between patient and control (HC) groups. (A) ROC plots for TNF-α for the comparison between patient and control (HC) groups. (B) ROC plots for IL-1β the comparison between patient and control (HC) groups. (C) ROC plots for IL-12 for the comparison between patient and control (HC) groups.

−25.79 kcal/mol to get stability.

response for the establishment of chronic infection involved in the immunopathology of tuberculosis and slightly elevated TNF-α level in HHC may include an initial response to M. tuberculosis infection, in HHC, shows strong cell-mediated immune response characterized by elevated TNF-α levels production, which is essential for protection. IL1β is the important proinflammatory cytokine mediating anti-microbial activities in TB and IL-1β directly augments TNF-α signaling and which leads to apoptosis and direct killing of M.tb in macrophages [27,28]. We observed increased IL-1β levels in patients and HHC when stimulated with PAM, ESAT-6. A recent study also reported that the inflammatory response was characterized by elevated IL-1β levels showed in China [29]. LPS-induced PBMC increased IL-1β production observed in invitro model [30]. Brazil study showed an increase in IL-1β production in response to PPD in TB [31] and PAM, ESAT-6 induced high IL-1β levels were observed in some studies [31,32]. The polymorphisms of the IL-1β gene may be one of the risk factors to predict the development of TB in HHC [33]. However, contrast results also observed in some coinfection studies [34]. Thus, the increased IL-1β levels in the present study could result in an inflammatory reaction occurs in TB infection. It was demonstrated in some inflammasome-mediated signaling studies. The main regulatory step of IL-1β secretion occurs at the level of transcription and constitutively active caspase-1 was observed in PBMC

4. Discussion Phagocytic cells recognize pathogen by its receptors present on it, which triggers host adaptive response by the induction of pro-inflammatory cytokines (TNF-α, IL-1β & IL-12) by macrophages and dendritic cells. TNF-α, a pleiotropic cytokine protects against M. tuberculosis which plays a protective role in the immunopathology of TB and also induces apoptosis [19]. In our study, we stimulated PBMC’s of PTB patients, HHC and HC with TLR2 specific ligand (PAM), antigen (ESAT-6) and we found significantly low TNF-α level was observed in PTB patients and HHC when compared to HC. A Korean study reported decreased TNF-α level was observed in PBMCs stimulated with M.tb antigen [20]. Another study in Italy showed reduced TNF-α level in LPS stimulated human monocytes [21]. South African studies showed that ESAT-6 binds to TLR2 and induce cytokines in macrophages [22]. Several studies showed contrast results to our study and reported increased levels in TNF-α in culture supernatants of PTB patients stimulated with mycobacterial antigens [23–26]. Our results agree with most of the reports that showed low TNF-αlevels in TB patients than in controls. We suggest that TNF-α in patients may involve in protective

Table 8 Comparison of TNF-α, IL-1β and IL-12 between patient (PTB) and Control (HC) groups. Values

AUC

95% Confidence interval

P*

Youden

Cut-off

Sensitivity

Specificity

TNF-α IL-1β IL-12

0.89 0.59 0.73

0.798–0.960 467–0.712 0.618–0.857

< 0.001 0.18 < 0.001

0.66 0.33 0.42

33.73 18.76 86.59

87% 100% 96%

77% 33% 45%

* Significant p < 0.05, AUC- area under the curve. 8

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Fig. 6. ROC plots for TNF-α, IL-12 and IL-1β for the comparison between HHC and control (HC) groups. (A) ROC plots for TNF-α for the comparison between HHC and control (HC) groups. (B) ROC plots for IL-1β the comparison between patient and control (HC) groups. (C) ROC plots for IL-12 for the comparison between HHC and control (HC) groups.

present study, we found CT genotype of the co-dominant model; the over-dominant model was found to be susceptible and associated with TB in PTB patients. Whereas in HHC protective response was observed when compared to the HCs. Similar results were observed in Tunisian, Korean and Roma population [43,44]. In which a small number of individuals were heterozygous for this polymorphism and was absent in the European population [45]. The association of this SNP with the disease confirmed by logistic regression analysis adjusting for gender, age, BCG, BMI, TST with alleles. Among the demographic characters investigated, only Age, BCG, BMI and T allele were associated towards the disease in patients whereas, in HHC male, age, BCG, BMI, T allele showed a significant association. TLR2 (2258G > A) is the most investigated polymorphism observed in the European population [46]. Our study showed G/A genotype of the over-dominant model was found to be susceptible to statistical significance in PTB patients when compared to the HC. However, HHC has not shown a significant association. The G/A genotype was 1.191 times at risk in PTB patients when compared to the HCs. Based on the AIC, over-dominant model was the best fit model in PTB patients. Many studies reported that an increased incidence of tuberculosis in several cohorts of patients [43,47–49]. This polymorphism was absent in some Asian population and showing less

[31]. IL-12 plays a vital role in the maintenance and differentiation of IFN-γ-secreting antigen-specific Th1 cells and in control of mice and men mycobacterial infections [33]. In the present study, we observed decreased levels of IL-12 in response to both PAM, ESAT-6 in patients and HHC when compared to healthy controls. A recombinant 32-kilodalton antigen of Mycobacterium bovis BCG stimulated PBMC showed elevated IL-12 levels in India [35]. PAM stimulated bone marrow cells produces decreased IL-12 cytokines observed in mice study [36]. ESAT6 stimulated in-vitro results in giving decreased IL-12 production in TB cases and HHC compared with PPD, TB10.4 stimulations [37]. Several human and animal studies also reported similar to that of the present study and suggesting that the active PTB in the early stage maybe related with decreased IL-12 level expression and the tendency of lineage 2 strains may decrease levels of protective Th1 cytokines may be in part responsible for higher virulence [38–40]. Many studies were confirmed that genetic factors were associated with TB susceptibility. The TLRs may cause an impairment of the immune response against TB [41,42]. However, TLR2 polymorphisms in the current study provide evidence those TLR2 gene variants were associated with pulmonary TB susceptibility in South Indian population. TLR2 gene has located on chromosome 4q32 and has two exons. In the

Table 9 Comparison of TNF-α, IL-1β and IL-12 between household contacts (HHC) and Control (HC) groups. Values

AUC

95% Confidence interval

P*

Youden

Cut-off

Sensitivity

Specificity

TNF-α IL-β IL-12

0.73 0.62 0.50

0.614–0.851 0.505–0.748 0.372–0.631

< 0.001 0.04 0.98

0.38 0.23 0.13

57.13 4.17 24.65

94% 100% 76%

42% 15% 33%

* Significant p < 0.05, AUC- area under the curve. 9

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Fig. 7. Pre-mRNA secondary structure of TLR2 (2029C/T), (2258 G/A) polymorphisms. (A) mRNA secondary structure for C allele, (B) mRNA secondary structure for T allele, (C) mRNA secondary structure for G allele, (D) mRNA secondary structure for A allele.

compared to wild type genotype. Further the expression results (data not shown) also confirm that TT + CT individuals showed lower expression than wild type CC genotype suggesting that there is no regulatory effect of the pseudogene on the present polymorphism. Secondary pre-mRNA structures of wild and variant alleles were determined by Vienna RNA to fold webserver. We found the effect of variants on secondary pre-mRNA structures of TLR2 polymorphisms. The difference in free energy levels of variant, T, A alleles were more stable when compared to wild-type C, G. Due to the release of low minimum free energy in the process of stabilizing secondary structure C allele showed extra stem-loop as shown in the Fig. 7. It was confirmed by pre-mRNA secondary structure predictions. This is in agreement with altered cytokine levels in subjects with T, A allele conferring an increased risk of tuberculosis. The altered pro-inflammatory response could result from variant TLR2 may change in the dimerization with other TLRs and impairs the ability to recruit further mediators in the signaling pathway. We observed the differences in three cytokine levels patterns evaluated by stimulating with TLR2 ligand and antigen. This fact will be explained by the production of mediators involved in TLRs signaling. More studies are required to evaluate the mutual effect of genetic factors along with other risk factors in TB, and to know the functional effect of TLR2 gene variant, its signaling pathways involved in regulating immune response mechanisms and disease outcome. To the best of our knowledge, this is the first study examined the influence

frequency [50–52]. Our results also supported by many studies given above. Studies with PBMCs isolated from patients having R753Q SNP showed attenuated NF-κB activation and cytokine release upon stimulation with Borrelia burgdorferi lysates and R677W TLR2-expressing monocytes responded to Mycobacterium leprae produced low TNF-αand IL-12 p40, compared with WT TLR2 [53,54]. However, our study showed the correlation between TLR2 polymorphisms and their cytokine production. The GA genotype of 2258G > A SNP showed low levels of TNF-α in culture supernatants and TT genotype of 2029C > TSNP produced high IL-1β levels. The CT, TT genotype of 2029C > T SNP showed IL-12 was a low producer than other genotypes in PTB and HHC compared to HC. TLR2 2029C > T SNP performed in our study is present in the exonic region of the true gene (NC_000004.12.). In addition, other studies have discussed TLR2 SNP was subsequently identified in a pseudogene and found not to encode a TLR2 transcript, the substitution of C with T in TLR2 (Arg677Trp) polymorphism present in pseudogene region had more than 95% sequence similarity with original gene [55]. Several investigators have examined the altered cytokine profiles of PBMC’ with TLR2 SNP wild genotypes compared to mutant genotypes and showed its association with susceptibility to leprosy, TB and other diseases [56–60]. The present study also reveals that PBMCs with TLR2 (Arg677Trp) mutant genotypes produced low TNF-α, IL-12, and high IL-1β levels 10

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of TLR2 gene polymorphisms on pro-inflammatory cytokine levels along with pre-mRNA secondary structures for susceptibility to PTB in patients and household contacts.

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5. Conclusion In the present study, we demonstrated that TLR2 SNPs are important genetic factors and associated with the disease, which can alter the proinflammatory cytokine levels in PTB patients and HHC. The GA genotype of 2258 G > A SNP with decreased TNF-α. The CT, TT genotype of 2029C > T SNP with decreased IL-12, the TT genotype with increased IL-1β respectively. Effect of TLR2 genotype association with inflammatory cytokines (TNF-α, IL-12, IL-1β) was found to be significantly associated with the disease. Which specifies the role of pro-inflammatory cytokines in TLR2 expression and its maintenance of acquired cellular immunity. ROC results suggest that TNF-α, IL-12 in PTB, TNF-α, IL-1β in HHC used as a predictive biomarker to differentiate between PTB and HHC. In vitro stimulation with TLR2 ligands PAM, ESAT-6 stimulation with decreased TNF-α, IL-12 and increased IL-1β indicates high inflammatory reaction and protection against TB in patients and HHC. Our conclusion would support that TLR2 polymorphisms effects the cytokine production and this polymorphism were associated with tuberculosis in South Indian population. Additional functional studies in a large sample size of PTB patients is required and allow further investigation of TLRs variants for new therapies of PTB infection. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgement Financial support was provided by the Department of Biotechnology, Government of India. Sanction order no: 102/IFD/SAN/ 3209/2012‐2013, dated 28/09/12. We thank Late Dr. K.J.R Murthy and staff of the free chest clinic Mahavir PPM DOTS, Tuberculosis Unit (T.U) and Bhagwan Mahavir Trust, Hyderabad, India. Appendix A. Supplementary material Supplementary data to this article can be found online at https:// doi.org/10.1016/j.cyto.2019.154897. References [1] Who, WHO Global tuberculosis report 2017, 2017 (Report No.: 978 92 4 156539 4). [2] K. Styblo, J. Meijer, I. Sutherland, Tuberculosis Surveillance Research Unit Report No. 1: the transmission of tubercle bacilli; its trend in a human population, Bull. Int. Union Again. Tubercul. 42 (1969) 1–104. [3] M.N. Bates, A. Khalakdina, M. Pai, L. Chang, F. Lessa, K.R. Smith, Risk of tuberculosis from exposure to tobacco smoke: a systematic review and meta-analysis, Arch. Intern. Med. 167 (4) (2007) 335–342. [4] V. Dhingra, S. Rajpal, N. Aggarwal, D. Taneja, Tuberculosis trend among household contacts of TB patients, Ind. J. Commun. Med. 29 (1) (2004) 44. [5] M. Murray, O. Oxlade, H.H. Lin, Modeling social, environmental and biological determinants of tuberculosis, Int. J. Tubercul. Lung Disease Off. J. Int. Union Again. Tubercul. Lung Dis. 15 (Suppl 2) (2011) 64–70. [6] D.M. Tobin, F.J. Roca, S.F. Oh, R. McFarland, T.W. Vickery, J.P. Ray, et al., Host genotype-specific therapies can optimize the inflammatory response to mycobacterial infections, Cell 148 (3) (2012) 434–446. [7] D.M. Tobin, J.C. Vary Jr., J.P. Ray, G.S. Walsh, S.J. Dunstan, N.D. Bang, et al., The lta4h locus modulates susceptibility to mycobacterial infection in zebrafish and humans, Cell 140 (5) (2010) 717–730. [8] K. Bhatt, P. Salgame, Host innate immune response to Mycobacterium tuberculosis, J. Clin. Immunol. 27 (4) (2007) 347–362. [9] T.K. Means, S. Wang, E. Lien, A. Yoshimura, D.T. Golenbock, M.J. Fenton, Human toll-like receptors mediate cellular activation by Mycobacterium tuberculosis, J. Immunol. (Baltimore, Md : 1950) 163 (7) (1999) 3920–3927.

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[37]

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