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. 2019 Jun 21;55(6):298. doi: 10.3390/medicina55060298

Association between P2X7 Polymorphisms and Susceptibility to Tuberculosis: An Updated Meta-Analysis of Case-Control Studies

Mohsen Taheri 1,2, Hosna Sarani 3, Abdolkarim Moazeni-Roodi 4, Mohammad Naderi 5, Mohammad Hashemi 1,6,*
PMCID: PMC6631194  PMID: 31234470

Abstract

Background and Objectives: Several studies inspected the impact of P2X7 polymorphisms on individual susceptibility to tuberculosis (TB), but the findings are still controversial and inconclusive. To achieve a more precise estimation, we conducted a meta-analysis of all eligible studies on the association between P2X7 polymorphisms and TB risk. Materials and Methods: Relevant studies were identified by searching the PubMed, Web of Science, Scopus and Google scholar databases up to November 2018. Twenty-four full-text articles were included in our meta-analysis. The strength of association between P2X7 polymorphisms and TB risk was evaluated by odds ratios (ORs) and 95% confidence intervals (95% CIs) under five genetic models. Results: The findings of this meta-analysis revealed that the rs3751143 variant significantly increased the risk of TB in heterozygous codominant (OR = 1.44, 95%CI = 1.17–1.78, p = 0.0006, AC vs. AA), homozygous codominant (OR = 1.87, 95% CI = 1.40–2.49, p = 0.0004, CC vs. AA), dominant (OR = 1.50, 95% CI = 1.22–1.85, p = 0.0002, AC + CC vs. AA), recessive (OR = 1.61, 95% CI = 1.25–2.07, p = 0.001, CC vs. AC + AA), and allele (OR = 1.41, 95% CI = 1.19–1.67, p < 0.0001, C vs. A) genetic models. Stratified analysis showed that rs3751143 increased the risk of pulmonary tuberculosis (PTB) and extrapulmonary tuberculosis (EPTB) in all genetic models. Furthermore, the rs3751143 increased risk of TB in the Asian population. The findings did not support an association between the rs2393799, rs1718119, rs208294, rs7958311, and rs2230911 polymorphisms of P2X7 and TB risk. Conclusions: The findings of this meta-analysis suggest that P2X7 rs3751143 polymorphism may play a role in susceptibility to TB in the Asian population. More well-designed studies are required to elucidate the exact role of P2X7 polymorphisms on TB development.

Keywords: P2X7, polymorphism, tuberculosis, meta-analysis

1. Introduction

Tuberculosis (TB) is a chronic infectious disease caused by the bacillus Mycobacterium tuberculosis (MTB). It remains a serious public global health problem. According to the World Health Organization (WHO) report, there were an estimated 10.4 million new cases of TB worldwide and approximately 1.3 million deaths in 2016 [1]. Approximately one-third of the general population is currently infected with Mtb, and nearly 5–10% of these infected individuals will progress to active TB [2,3]. Mounting evidence has proposed that host genetic factors play an important role in determining inter-individual difference in susceptibility to TB [4,5,6].

The human P2X7 gene is mapped to chromosome 12 (12q24.31). It encodes cell-surface nucleotide receptors called P2X7 receptor (P2X7R) [7]. The P2X7R, a ligand-gated cation channel, is highly expressed on macrophages and other immune cells [8]. Activation of P2X7R by extracellular adenosine triphosphate (eATP) causes immediate opening of a cation selective channel, permitting the influx of Ca2+ and Na+ and the efflux of K+ [9]. In M. tuberculosis infection, activation of the P2X7R promotes a range of signaling cascades leading to the apoptosis of MTB-infected macrophages [10,11].

The P2X7R gene is indeed polymorphic. The precise correlation between the P2X7 polymorphisms and susceptibility to TB is not completely documented. Several single nucleotide polymorphisms (SNPs) have been revealed that affect the function of this receptor which cause P2X7R loss-of-function (LOF) or gain-of-function (GOF) [8]. Many studies have inspected the association between P2X7 polymorphisms and risk of tuberculosis in various populations, but the findings were inconsistent [12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35]. So we conducted an updated meta-analysis of all available eligible case-control studies published to date, focusing on the association between P2X7 polymorphisms and tuberculosis risk.

2. Methods

2.1. Literature Search

The PubMed, Web of Science, Scopus, and Google scholar databases for all potentially eligible research articles up to November 2018 on the relationship between P2X7 polymorphisms and TB risk were searched. The search key words used were “P2X7 or P2X7R” and “tuberculosis” and “polymorphism or variant”. Figure 1 shows the process of recognizing eligible studies. The inclusion criteria were as follows: case-control studies focusing on the association between P2X7 polymorphisms and TB risk; the frequencies distribution of alleles and genotypes in patients and controls can be extracted. The exclusion criteria were studies that are not associated with P2X7 polymorphisms and TB risk; overlapping data, conference papers, reviews, meta-analyses; no sufficient data reported.

Figure 1.

Figure 1

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Flow chart illustrates the detailed study selection process of this meta-analysis.

2.2. Data Extraction

Two investigators independently inspected and evaluated the articles for eligibility according to inclusion and exclusion criteria. The following data were recorded from the selected studies such as the first author’s name, publication year, ethnicity, genotyping methods, genotype and allelic profile, as well as the source of controls.

2.3. Statistical Analysis

The chi-square test was used to check whether genotypes within the controls conformed to the Hardy-Weinberg equilibrium (HWE). We calculated the pooled odds ratios (ORs) and corresponding 95% confidence intervals (CIs) to assess the association between the P2X7 polymorphisms and TB susceptibility. The significance of the pooled OR was determined by the Z-test, and a p-value less than 0.05 was considered significant. Heterogeneity between the studies was estimated by Q statistic and the I2 test. p < 0.10 designated significant heterogeneity. If heterogeneity did not exist, a fixed-effects model was used to calculate the pooled ORs; otherwise, a random-effects model was utilized.

Publication bias was inspected with the funnel plot and an asymmetric plot suggests a possible publication bias. Funnel plot asymmetry was further measured using Egger’s linear regression test. p value < 0.05 was considered a significant publication bias. Sensitivity analysis was done by neglecting each study in turn to assess the quality and consistency of the results. All statistical analyses were executed using STATA v14.1 software (College Station, TX, USA).

3. Results

3.1. Study Characteristics

Through a comprehensive literature search and selection based on the inclusion criteria, 59 relevant case-control studies from 24 selected articles [12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35] were included in the pooled analysis. There were 30 studies with 5247 cases and 7614 controls on rs3751143 (1513A > C), 19 studies with 3235 cases and 4685 controls on rs2393799 (−762 C > T), 3 studies with 2185 cases and 2107 controls on rs1718119 (Thr348Ala), 3 studies with 1994 cases and 2037 controls on rs208294 (His155Tyr), 2 studies with 2000 cases and 2006 controls on rs7958311, 2 studies with 1853 cases and 1797 controls on rs2230911 included into meta-analysis. The main characteristics of included studies are shown in Table 1.

Table 1.

Characteristics of all studies included in the meta-analysis.

First Author Year Country Ethnicity TB Source of Control Genotyping Method Case/Control Cases Controls HWE (p)
rs3751143 A > C AA AC CC A C AA AC CC A C
Amiri 2018 Iran Asian PTB PB PCR-RFLP 100/100 76 21 3 173 27 40 58 2 138 62 <0.001
Ben-Selma 2011 Tunisia African PTB HB PCR-RFLP 168/150 130 34 4 294 42 104 40 6 248 52 0.395
Ben-Selma 2011 Tunisia African EPTB HB PCR-RFLP 55/150 19 23 13 61 49 104 40 6 248 52 0.395
Chaudhary 2018 India Asian PTB PB ARMS-PCR 145/247 63 73 9 199 91 141 95 11 377 117 0.315
Chaudhary 2018 India Asian EPTB PB ARMS-PCR 100/247 42 42 16 126 74 141 95 11 377 117 0.315
De 2017 India Asian PTB PB PCR-RFLP 56/60 26 18 12 70 42 36 21 3 93 27 0.978
Fernando 2007 Southeast Asia Asian PTB PB TaqMan 56/167 34 17 5 85 27 105 55 7 265 69 0.952
Fernando 2007 Southeast Asia Asian EPTB PB TaqMan 30/167 9 17 4 35 25 105 55 7 265 69 0.952
Fernando 2007 Australia Caucasian PTB PB TaqMan 49/102 28 21 0 77 21 64 34 4 162 42 0.845
Fernando 2007 Australia Caucasian EPTB PB TaqMan 50/102 18 28 4 64 36 64 34 4 162 42 0.845
Li 2002 Gambia African PTB HB PCR-RFLP 325/297 261 58 6 580 70 256 37 4 549 45 0.057
Mokrousov 2008 Russia Caucasian PTB HB PCR-RFLP 188/126 120 59 9 299 77 96 27 3 219 33 0.511
Nino-Moreno 2007 México Mixed PTB HB PCR-RFLP 94/110 53 33 8 139 49 70 38 2 178 42 0.215
Ozdemir 2014 Turkey Asian PTB PB PCR-RFLP 71/160 44 18 9 106 36 76 63 21 215 105 0.176
Ozdemir 2014 Turkey Asian EPTB PB PCR-RFLP 89/160 47 34 8 128 50 76 63 21 215 105 0.176
Sambasivan 2010 India Asian PTB HB PCR-RFLP 156/100 89 55 12 233 79 71 21 8 163 37 0.002
Shamsi 2016 Iran Asian PTB HB PCR-RFLP 100/100 33 66 1 132 68 83 16 1 182 18 0.817
Sharma 2010 India Asian PTB PB T-ARMS-PCR 181/177 102 75 4 279 83 126 48 3 300 54 0.515
Sharma 2010 India Asian EPTB PB T-ARMS-PCR 23/177 8 13 2 29 17 126 48 3 300 54 0.515
Singla 2012 India Asian PTB PB PCR-RFLP 286/392 162 112 12 436 136 258 123 11 639 145 0.420
Singla 2012 India Asian EPTB PB PCR-RFLP 71/392 45 22 4 112 30 258 123 11 639 145 0.420
Souza de Lima 2016 Brazil South American PTB HB TaqMan 288/287 170 95 23 435 141 184 89 14 457 117 0.450
Taype 2010 Peru Caucasian PTB HB PCR-RFLP 498/513 352 130 16 834 162 347 149 17 843 183 0.838
Taype 2010 Peru Caucasian EPTB HB PCR-RFLP 121/513 82 37 2 201 41 347 149 17 843 183 0.838
Tekin 2010 Turkey Caucasian EPTB HB PCR-RFLP 74/192 39 28 7 106 42 141 46 5 328 56 0.595
Velayati 2013 Iran Asian PTB HB PCR- RFLP 79/50 42 35 2 119 39 37 12 1 86 14 0.981
Wu 2015 China Asian PTB PB PCR-RFLP 103/87 33 49 21 115 91 51 27 9 129 45 0.075
Xiao 2009 China Asian PTB HB PCR-RFLP 41/384 21 18 2 60 22 221 119 44 561 207 <0.001
Xiao 2009 China Asian EPTB HB PCR-RFLP 55/384 30 19 6 79 31 221 119 44 561 207 <0.001
Zheng 2017 China Asian PTB PB TaqMan 1595/1521 972 551 72 2495 695 900 544 77 2344 698 0.655
rs2393799
C > T		 CC CT TT C T CC CT TT C T
Amiri 2018 Iran Asian PTB PB PCR-RFLP 100/100 8 88 4 104 96 4 95 1 103 97 <0.001
Bahari 2013 Iran Asian PTB PB ARMS-PCR 150/150 71 54 25 196 104 104 40 6 248 52 0.395
Ben-Selma 2011 Tunisia African PTB HB ARMS-PCR 168/150 16 57 95 89 247 14 51 85 79 221 0.130
Ben-Selma 2011 Tunisia African EPTB HB ARMS-PCR 55/150 4 15 36 23 87 14 51 85 79 221 0.130
Chaudhary 2018 India Asian PTB PB ARMS-PCR 145/247 62 67 16 191 99 101 111 35 313 181 0.614
Chaudhary 2018 India Asian EPTB PB ARMS-PCR 100/247 44 48 8 136 64 101 111 35 313 181 0.614
Li 2002 Gambia African PTB HB PCR-RFLP 323/347 23 118 182 164 482 44 140 163 228 466 0.111
Mokrousov 2008 Russia Caucasian PTB HB ARMS 190/127 86 87 17 259 121 65 46 16 176 78 0.093
Nino-Moreno 2007 México Mixed PTB HB ARMS 92/110 8 32 52 48 136 15 44 51 74 146 0.275
Sambasivan 2010 India Asian PTB HB PCR-RFLP 156/100 38 88 30 164 148 15 49 36 79 121 0.801
Shamsi 2016 Iran Asian PTB HB PCR-RFLP 100/100 1 99 0 101 99 6 93 1 105 95 <0.001
Singla 2012 India Asian PTB PB ARMS 286/392 143 115 28 401 171 231 143 18 605 179 0.485
Singla 2012 India Asian EPTB PB ARMS 71/392 40 25 6 105 37 231 143 18 605 179 0.485
Songane 2012 Indonesia Asian PTB PB MassARRAY 842/844 181 413 248 775 909 177 412 255 766 922 <0.001
Velayati 2013 Iran Asian PTB HB ARMS 79/50 10 67 2 87 71 3 47 0 53 47 <0.001
Wu 2015 China Asian PTB PB PCR-RFLP 103/87 35 47 21 117 89 9 30 48 48 126 0.202
Xiao 2009 China Asian PTB HB ARMS 38/384 23 11 4 57 19 208 135 41 551 217 0.009
Xiao 2009 China Asian EPTB HB ARMS 58/384 40 12 6 92 24 208 135 41 551 217 0.009
Zhou 2018 China Asain EPTB HB Mass Spectrometry 179/324 81 77 21 239 119 122 143 59 387 261 0.137
rs1718119
G > A		 GG AG AA G A GG AG AA G A
Bahari 2013 Iran Asian PTB PB T-ARMS-PCR 150/150 63 72 15 198 102 66 69 15 201 99 0.622
Zheng 2017 China Asian PTB PB TaqMan 1568/1454 1090 440 38 2620 516 978 417 59 2373 535 0.087
Zhu 2016 China Asian PTB HB MassARRAY 467/503 372 91 4 835 99 412 89 2 913 93 0.222
rs208294
G > A		 GG AG AA G A GG AG AA G A
Chaudhary 2018 India Asian Mixed PB PCR-RFLP 245/246 56 147 42 259 231 49 143 54 241 251 0.011
Zheng 2017 China Asian PTB PB TaqMan 1570/1467 597 732 241 1926 1214 578 679 210 1835 1099 0.642
Zhou 2018 China Asian EPTB HB Mass
Spectrometry		 179/324 22 80 77 124 234 70 145 109 285 363 0.099
rs7958311
G > A		 GG AG AA G A GG AG AA G A
Zheng 2017 China Asian PTB PB TaqMan 1533/1503 402 797 334 1601 1465 396 775 332 1567 1439 0.199
Zhu 2016 China Asian PTB HB MassARRAY 467/503 114 215 138 443 491 137 262 104 536 470 0.300
rs2230911
C > G		 CC CG GG C G CC CG GG C G
Souza de Lima 2016 Brazil South American PTB HB TaqMan 288/288 170 95 23 435 141 193 89 6 475 101 0.245
Zheng 2017 China Asian PTB PB TaqMan 1565/1509 1029 482 54 2540 590 997 467 45 2461 557 0.274
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List of abbreviations: PTB: Pulmonary Tuberculosis; TB: Tuberculosis; EPTB: Extrapulmonary Tuberculosis; PCR-RFLP: PCR-Restriction fragment length polymorphism; ARMS-PCR: Amplification-refractory mutation system-PCR; TaqMan: probes used in quantitative PCR; T-ARMS-PCR: Multiplex Tetra-Primer Amplification Refractory Mutation System-PCR; MassARRAY: Non-fluorescent detection platform utilizing mass spectrometry to accurately measure PCR-derived amplicons.

3.2. Main Analysis Results

The Forest plots were applied to show meta-analysis results for each genetic model. Overall, the rs3751143 variant significantly increased the risk of TB in heterozygous codominant (OR = 1.44, 95% CI = 1.17–1.78, p = 0.0006, AC vs. AA), homozygous codominant (OR = 1.87, 95% CI = 1.40–2.49, p = 0.0004, CC vs. AA), dominant (OR = 1.50, 95% CI = 1.22–1.85, p = 0.0002, AC + CC vs. AA), recessive (OR = 1.61, 95% CI = 1.25–2.07, p = 0.001, CC vs. AC + AA), and allele (OR = 1.41, 95% CI = 1.19–1.67, p < 0.0001, C vs. A) genetic models (Table 2 and Figure 2).

Table 2.

The pooled ORs and 95% CIs for the association between P2X7 polymorphisms and tuberculosis susceptibility.

Polymorphism No. Genetic Model Association Test Heterogeneity Publication Bias Tests
OR (95%CI) Z P χ2 I2 (%) P Egger’s Test
p-Value		 Begg’s Test
p-Value
rs3751143 30 AC vs. AA 1.44 (1.17–1.78) 3.42 0.0006 158.86 81.7 0.000 0.016 0.016
CC vs. AA 1.87 (1.40–2.49) 4.26 0.0004 61.79 54.7 0.000 0.002 0.047
AC + CC vs. AA 1.50 (1.22–1.85) 3.78 0.0002 178.85 83.8 0.000 0.007 0.018
CC vs. AC + AA 1.61 (1.25–2.07) 3.65 0.001 50.79 44.9 0.005 0.006 0.051
C vs. A 1.41 (1.19–1.67) 3.97 <0.0001 173.41 83.3 0.000 0.006 0.066
rs2393799 19 CT v CC 1.00 (0.83–1.20) 0.01 0.989 32.34 44.3 0.020 0.460 0.753
TT vs. CC 0.99 (0.68–1.44) 0.04 0.965 73.55 75.5 0.000 0.935 0.510
CT + TT vs. CC 0.97 (0.77–1.23) 0.22 0.825 58.41 69.2 0.000 0.557 0.649
TT vs. CT + CC 0.99 (0.74–1.32) 0.08 0.938 71.34 74.8 0.000 0.962 0.680
T vs. C 0.98 (0.83–1.17) 0.20 0.844 95.15 81.1 0.000 0.657 0.763
rs1718119 3 AG vs. GG 0.99 (0.86–1.13) 0.16 0.88 1.13 0 0.57 0.308 0.602
AA vs. GG 0.70 (0.49–0.99) 1.99 0.05 3.56 44 0.17 0.136 0.117
AG + AA vs. GG 0.96 (0.84–1.09) 0.68 0.50 2.22 10 0.33 0.312 0.602
AA vs. AG + GG 0.70 (0.49–1.00) 1.98 0.05 3.24 38 0.20 0.141 0.117
G vs. A 0.93 (0.83–1.04) 1.24 0.21 3.49 43 0.17 0.242 0.602
rs208294 3 AG vs. GG 1.03 (0.93–1.23) 0.89 0.37 3.77 47 0.15 0.694 0.602
AA vs. GG 1.18 (0.69–2.02) 0.61 0.54 8.99 78 0.010 0.900 0.602
AG + AA vs. GG 1.16 (0.80–1.68) 0.76 0.45 6.50 69 0.04 0.751 0.602
AA vs. AG + GG 1.08 (0.78–1.49) 0.47 0.64 5.60 64 0.06 0.904 0.602
A vs. G 1.09 (0.85–1.40) 0.70 0.49 8.82 77 0.01 0.860 0.602
rs7958311 2 AG vs. GG 1.01 (0.87–1.17) 0.09 0.93 0.02 0 0.88
AA vs. GG 1.23 (0.77–1.95) 0.87 0.38 5.15 81 0.02
AG + AA vs. GG 0.81 (0.50–1.31) 0.87 0.38 8.09 88 0.004
AA vs. AG + GG 1.24 (0.76–2.01) 0.87 0.38 8.09 88 0.004
A vs. G 1.11 (0.88–1.40) 0.87 0.38 5.18 81 0.02
rs2230911 2 CG vs. CC 1.03 (0.90–1.19) 0.42 0.67 0.95 0 0.33
GG vs. CC 2.10 (0.58–7.66) 1.13 0.26 6.65 85 0.010
CG + GG vs. CC 1.01 (0.88–1.16) 0.13 0.89 0.28 0 0.60
GG vs. CG + CC 2.03 (0.60–6.94) 1.13 0.26 6.12 84 0.01
G vs. C 1.22 (0.83–1.80) 1.03 0.30 6.09 84 0.01
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List of Abbreviations: OR: Odds Ratio; CI: Confidence interval Z: Z-score; P: Probability; χ2: χ2 test; I2: I2 value.

Figure 2.

Figure 2

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The forest plot for association between P2X7 rs3751143 polymorphism and tuberculosis risk under allelic genetic model (C vs. A).

No significant association was found between P2X7 rs2393799, rs1718119, rs208294, rs7958311, and rs2230911 polymorphisms and TB risk (Table 2).

3.3. Subgroup Analysis Results

Stratified analysis was achieved (Table 3). The findings proposed that rs3751143 polymorphism increased the risk of pulmonary tuberculosis (PTB) and extrapulmonary tuberculosis (EPTB) in all genetic models. Besides, this polymorphism only contributes to the risk of TB in the Asian population, but not in the Caucasian population (Table 3). The rs2393799 polymorphism was not associated with the risk of TB in the Asian population (Table 3).

Table 3.

Stratified analysis of P2X7 polymorphisms and tuberculosis risk.

Parameters No. AC vs. AA CC vs. AA AC + CC vs. AA CC vs. AC + AA C vs. A
OR (95% CI) P OR (95%CI) P OR (95%CI) P OR (95%CI) P OR (95%CI) P
rs3751143
Tuberculosis
PTB 21 1.35 (1.05–1.74) 0.020 1.50 (1.10–2.04) 0.010 1.39 (1.09–1.78) 0.009 1.34 (1.04–1.73) 0.020 1.31 (1.09–1.58) 0.004
EPTB 9 1.68 (1.17–2.42) 0.005 2.62 (1.19–5.78) 0.020 1.84 (1.21–2.79) 0.004 2.05 (1.07–3.93) 0.030 1.67 (1.16–2.42) 0.006
Ethnicities
Asian 19 1.48 (1.09–2.00) 0.010 1.70 (1.17–2.48) 0.006 1.53 (1.13–2.06) 0.006 1.47 (1.07–2.00) 0.020 1.57 (1.22–2.02) 0.0005
Caucasian 6 1.47 (0.99–2.17) 0.05 1.56 (0.70 − 3.51) 0.28 1.49 (0.98–2.26) 0.06 1.36 (0.70–2.66) 0.37 1.37 (0.96–1.97) 0.09
African 3 1.45 (0.66–3.19) 0.36 2.16 (0.33–13.95) 0.42 1.60 (0.62–4.13) 0.33 1.89 (0.41–8.81) 0.42 1.56 (0.62–3.94) 0.35
rs2393799 CT vs. CC TT vs. CC CT + TT vs. CC TT vs. CT + CC C vs. T
Asian 14 0.92 (0.74–1.14) 0.44 0.87 (0.54–1.41) 0.58 0.86 (0.66–1.14) 0.30 0.92 (0.61–1.40) 0.70 0.98 (0.83–1.17) 0.84
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3.4. Heterogeneity and Publication Bias

In our study, relatively obvious heterogeneities existed under all five genetic models for rs3751143 and rs2393799 (Table 2). For rs1718119, heterogeneities were not observed under all genetic models. For rs208294, heterogeneities were not observed under heterozygous codominant and recessive genetic models. For rs7958311, heterogeneities were not observed under heterozygous codominant and for rs2230911 variant, heterogeneities were not observed under heterozygous codominant and dominant models.

Begg’s tests were done with funnel plot to assess publication bias. Publication bias was found for rs3751143 under five genetic models (Table 2 and Figure 3).

Figure 3.

Figure 3

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The funnel plot for the test of publication bias. The funnel plot for rs3751143 polymorphism under allele genetic model (C vs. A).

The Begg’s tests indicated no evidence of publication bias for rs2393799, rs1718119, and rs208294 (Table 2) under all genetic models.

3.5. Sensitivity Analysis

To better inspect the impact of individual study on the pooled OR, we performed sensitivity analysis through deleting each study one by one. Outcomes indicated that ORs were not statistically influenced in all genetic models for rs3751143 (Figure 4), as well as for rs2393799, showing that our results are stable and reliable.

Figure 4.

Figure 4

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Sensitivity analyses for studies on P2X7 rs3751143 polymorphism and the risk of tuberculosis for C vs. A.

4. Discussion

Mounting evidence proposed that host genetic factors are implicated in tuberculosis susceptibility [4,6]. The P2X7R is highly expressed on macrophages and other immune cells [8]. It is a key molecule in the clearance of MTB in macrophages by adenosine triphosphate (ATP)-induced apoptosis of macrophage [8,10]. P2X7 is polymorphic and several studies investigated the impact of P2X7 polymorphisms on predisposition to TB [12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35]. But these studies failed to reach a consistent conclusion. Therefore, to provide a comprehensive and reliable conclusion, we conducted the present meta- analysis to increase the statistical power of the association. Our findings suggest the P2X7 rs3751143 (Glu498Ala) polymorphism significantly increased the risk of overall TB. Stratified analysis of this polymorphism significantly increased the risk of PTB and EPTB. Also, the rs3751143 polymorphism increased the risk of TB in the Asian population. Findings did not support an association between rs2393799 (−762 C > T), rs1718119 (Thr348Ala), rs208294 (His155Tyr), rs7958311 (Arg270His), and rs2230911(Thr357Ser) polymorphisms and TB risk.

Ge et al. [36] performed a meta-analysis (n = 10) on the association between P2X7 rs3751143 polymorphism and PTB risk and found that this variant significantly increased the risk of PTB. Another meta-analysis (n = 11) performed by Alshammari et al. [37] showed no significant association between rs3751143 polymorphism and risk of TB. Stratified analysis revealed an association between this variant and the risk of TB in the Asian population. The results of a meta-analysis of 8 studies indicated that rs3751143 polymorphism significantly increased the risk of EPTB [38]. Another meta-analysis of 9 studies conducted by Wu et al. [39] revealed that rs3751143 significantly increased the risk of TB. A meta-analysis published by Yi et al. [40] on the association between rs2393799 (−762 C > T) polymorphism and TB susceptibility indicated that this variant is associated with TB risk. Our meta-analysis has more advantages than previous meta-analyses. We included a higher number of relevant published studies. Besides, we evaluated 6 polymorphisms in this meta-analysis.

Several polymorphisms have been described that cause P2X7R loss-of-function (LOF) or gain-of-function (GOF) [8]. The common polymorphism of P2X7 is rs3751143 (A1513C; Glu498Ala) polymorphism located in exon 13, accountable for LOF. This polymorphism affects the sensitivity of P2X7R to ATP and may contribute to increased susceptibility to MTB infection in humans [13,14,41]. The findings of the present meta-analysis support an association between rs3751143 polymorphism and the risk of TB. Another LOF polymorphism is rs2393799 (−762 C > T), which is located in the promoter of P2X7 and decrease the expression of P2X7R. The relationship between the rs2393799 polymorphism and susceptibility to TB is still debated [12,13,14,17,18,19,21,23,27,28,29,31,32,33,34], and pooled analysis of all available data did not support an association between this variant and susceptibility to TB. The rs208294 (489 C > T; His155Tyr) is GOF polymorphism. This polymorphism increases the affinity of P2X7R to ATP [42]. Limited studies investigated the impact of this polymorphism on TB susceptibility [14,30,34]. Pooled analysis revealed no evidence of association between this variant and TB risk.

Up until now, only 3 studies investigated the association between rs1718119 (1068 G > A; Thr348Ala) polymorphism and TB risk [30,31,34]. Our findings did not support an association between this polymorphism and TB risk.

Porphyromonas gingivalis, a bacterial carcinogen, plays a key role in cancer development by inhibiting apoptosis through several mechanisms. It has been shown that this bacterium secretes an anti-apoptotic enzyme nucleoside diphosphate kinase (NDK) which cleaves ATP and prevents proapoptotic P2X7 receptor activation, consequently modulating ATP/P2X7-signaling pathway [43]. It has been proposed that MTB secrete NDK, which act as a Rho-GTPase-activating protein (Rho-GAP), and covert Guanosine triphosphate (GTP)-bound active form to guanosine diphosphate (GDP)-bound inactive form, eventually facilitating its pathogenesis [44].

Some limitations of our meta-analysis should be acknowledged. Firstly, heterogeneity between studies was evident, which might distort the conclusion of this meta-analysis. Heterogeneity may be partly arising in the differences of ethnicities. Secondly, the sample sizes for some polymorphisms were small. Therefore, the results of this meta-analysis should be interpreted with caution.

Despite these limitations, however, there are still some advantages to having done this meta-analysis. First, this meta-analysis involved more studies than the previous meta-analyses, so the statistical power of our study is higher than the published meta-analysis. Second, we evaluated six polymorphisms of P2X7.

5. Conclusions

Overall, our meta-analysis proposed that P2X7 rs3751143 polymorphism may serve as a risk factor for TB in the Asian population. However, further well-designed studies with large sample sizes are necessary to confirm our findings.

Author Contributions

M.T., designed the study. H.S. and A.M.-R. searched the literatures and extracted the data. M.H. performed the statistical analyses. M.T. and M.H. wrote the manuscript. All authors read and approved the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest, financial or otherwise.

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