Study characteristics
A number of 60 articles were garnered through a searching from the PubMed database. 31 articles were removed because of unrelated information. Next, 29 articles with full texts were evaluated, and 14 other articles were excluded because meta-analysis (3), review (5), not related to IL-10 polymorphisms (6) (Fig. 1). Finally, 15 different articles about 3 SNPs in IL-10 and HIV-1 susceptibility were included (10 articles for rs1800896, 11 for rs1800872 and 3 for rs1800871 SNP) (Table 1). Overall, 24 case-control studies with 3957 cases of HIV-1 as well as 4845 controls were included[19–33]. The controls were mainly healthy individuals. The average NOS is 7.8, which stands for the credible and representational for including studies. In final, the Minor Allele Frequency reported for the five main worldwide populations in the 1000 Genomes Browser was checked: because the frequency is the same for rs1800871 and rs1800872, so we combined these two sites into a set of bar graph for presentation (Fig. 2)
Table 1
Characteristics of included studies in IL-10 polymorphisms and HIV risk.
Author | Year | Country | Ethnicity | Case | Control | SOC | Case | Control | Cases | | | | Controls | | | HWE | Genotype | NOS |
rs1800896 -1082 | | | | | | | | GG | GA | AA | | GG | GA | AA | | | |
Sunder | 2012 | India | Asian | 121 | 102 | HB | 121 | 102 | 2 | 83 | 36 | | 2 | 43 | 57 | 0.056 | PCR-RFLP | 6 |
Singh | 2016 | India | Asian | 260 | 260 | PB | 260 | 260 | 21 | 119 | 120 | | 21 | 125 | 114 | 0.098 | ARMS-PCR | 8 |
Kallas | 2015 | Estonia | Caucasian | 172 | 496 | PB | 172 | 496 | 32 | 78 | 62 | | 104 | 251 | 141 | 0.692 | TaqMan | 8 |
Erikstrup | 2007 | Denmark | Caucasian | 195 | 175 | PB | 195 | 175 | 22 | 73 | 100 | | 17 | 82 | 76 | 0.448 | real-time PCR | 7 |
Chatterjee | 2009 | India | Asian | 180 | 305 | HB | 180 | 305 | 20 | 60 | 100 | | 27 | 122 | 156 | 0.653 | PCR-RFLP | 7 |
Freitas | 2015 | Brazil | Mixed | 216 | 294 | HB | 216 | 294 | 14 | 79 | 123 | | 24 | 111 | 159 | 0.459 | PCR-RFLP | 7 |
Ramezani | 2015 | Iran | Asian | 70 | 31 | HB | 70 | 31 | 10 | 32 | 28 | | 3 | 15 | 13 | 0.655 | sequence | 6 |
Naicker | 2009 | South Africa | African | 64 | 195 | PB | 64 | 195 | 5 | 22 | 37 | | 27 | 80 | 88 | 0.206 | ARMS-PCR | 8 |
Singh | 2019 | India | Asian | 131 | 155 | PB | 131 | 155 | 5 | 52 | 74 | | 7 | 59 | 89 | 0.476 | PCR-RFLP | 8 |
Wang | 2004 | UK | Caucasian | 94 | 76 | PB | 94 | 76 | 6 | 61 | 27 | | 4 | 33 | 39 | 0.373 | PCR-SSP | 7 |
rs1800872 -592 | | | | | | Case | Control | AA | AC | CC | | AA | AC | CC | | | |
Singh | 2016 | India | Asian | 260 | 260 | PB | 260 | 260 | 39 | 115 | 106 | | 29 | 122 | 109 | 0.555 | ARMS-PCR | 8 |
Kallas | 2015 | Estonia | Caucasian | 172 | 496 | PB | 172 | 496 | 10 | 49 | 113 | | 23 | 167 | 306 | 0.972 | TaqMan | 8 |
Erikstrup | 2007 | Denmark | Caucasian | 194 | 174 | PB | 194 | 174 | 43 | 71 | 80 | | 25 | 81 | 68 | 0.911 | real-time PCR | 7 |
Chatterjee | 2009 | India | Asian | 180 | 305 | HB | 180 | 305 | 39 | 74 | 67 | | 43 | 122 | 140 | 0.054 | PCR-RFLP | 7 |
Ramezani | 2015 | Iran | Asian | 70 | 31 | HB | 70 | 31 | 4 | 35 | 31 | | 4 | 11 | 16 | 0.357 | sequence | 6 |
Naicker | 2009 | South Africa | African | 64 | 195 | PB | 64 | 195 | 17 | 23 | 24 | | 18 | 80 | 97 | 0.797 | ARMS-PCR | 8 |
Piddubna | 2013 | Ukraine | Caucasian | 78 | 30 | HB | 78 | 30 | 8 | 28 | 42 | | 0 | 5 | 25 | 0.618 | PCR-RFLP | 6 |
Corchado | 2013 | Spain | Caucasian | 88 | 51 | HB | 88 | 51 | 7 | 38 | 43 | | 6 | 21 | 24 | 0.672 | TaqMan | 7 |
Sobti | 2010 | India | Asian | 300 | 300 | HB | 300 | 300 | 36 | 137 | 127 | | 34 | 146 | 120 | 0.295 | PCR-RFLP | 7 |
Harishankar | 2018 | India | Asian | 100 | 122 | PB | 100 | 122 | 22 | 51 | 27 | | 18 | 54 | 50 | 0.585 | PCR-RFLP | 8 |
Shin | 2000 | USA | Mixed | 377 | 72 | PB | 377 | 72 | | | 207 | | | | 50 | | sequence | 7 |
rs1800871 -819 | | | | | | Case | Control | TT | TC | CC | | TT | TC | CC | | | |
Singh | 2016 | India | Asian | 260 | 260 | PB | 260 | 260 | 39 | 115 | 106 | | 29 | 122 | 109 | 0.555 | ARMS PCR | 8 |
Chatterjee | 2009 | India | Asian | 180 | 305 | HB | 180 | 305 | 39 | 74 | 67 | | 43 | 122 | 140 | 0.054 | PCR-RFLP | 7 |
Singh | 2019 | India | Asian | 131 | 155 | PB | 131 | 155 | 21 | 59 | 51 | | 21 | 84 | 50 | 0.125 | PCR-RFLP | 8 |
HB: hospital-based; PB: population-based; SOC; source of control; PCR-RFLP: polymerase chain reaction followed by restriction fragment length polymorphism; ARMS-PCR: amplification refractory mutation system-PCR; HWE: Hardy–Weinberg equilibrium of control group; NOS: quality score assessment. |
Quantitative Synthesis
Results of the 3 SNPs in IL-10 and HIV-1 risk are presented in Table 2 and Fig. 3–7. For rs1800896 polymorphism (1503 cases and 2089 controls), no association was found in the total and each subgroup, such as the allelic contrast (OR: 1.00, 95% CI: 0.84–1.18, P(heterogeneity): 0.009, P: 0.985 (Fig. 3).
Table 2
Results of the meta-analysis on IL-10 polymorphisms and HIV risk in total and types of subgroups.
Variables | N | Case/ | M-allele vs. W-allele | | MW vs. WW | | MM + MW vs. WW | | MM vs. WW | | MM vs. MW + WW |
| | Control | OR(95%CI) Ph P | | OR(95%CI) Ph P | | OR(95%CI) Ph P | | OR(95%CI) Ph P | | OR(95%CI) Ph P |
rs1800896 -1082 | | | | | | | | | | |
Total | 10 | 1503/2089 | 1.00(0.84–1.18)0.009 0.985 | | 1.02(0.76–1.37)0.000 0.880 | | 1.02(0.77–1.35)0.000 0.869 | | 0.88(0.69–1.12)0.717 0.302 | | 0.96(0.76–1.21)0.916 0.701 |
Ethnicity | | | | | | | | | | | |
Asian | 5 | 762/853 | 1.11(0.87–1.41)0.074 0.407 | | 1.16(0.73–1.83)0.002 0.535 | | 1.18(0.77–1.80)0.003 0.448 | | 1.08(0.72–1.60)0.950 0.715 | | 1.12(0.76–1.64)0.930 0.571 |
Caucasian | 3 | 461/747 | 1.02(0.70–1.49)0.018 0.921 | | 1.04(0.50–2.15)0.001 0.920 | | 1.05(0.53–2.09)0.001 0.885 | | 0.85(0.58–1.25)0.275 0.415 | | 0.97(0.68–1.37)0.691 0.844 |
SOC | | | | | | | | | | | |
HB | 4 | 587/737 | 1.13(0.81–1.57)0.026 0.470 | | 1.20(0.65–2.19)0.001 0.558 | | 1.22(0.70–2.14)0.001 0.482 | | 1.02(0.66–1.57)0.113 0.929 | | 1.06(0.70–1.61)0.678 0.784 |
PB | 6 | 916/1357 | 0.93(0.76–1.14)0.055 0.488 | | 0.93(0.66–1.30)0.009 0.658 | | 0.92(0.66–1.27)0.007 0.613 | | 0.82(0.60–1.10)0.517 0.187 | | 0.91(0.69–1.21)0.835 0.519 |
Genotyping | | | | | | | | | | | |
PCR-RFLP | 4 | 648/856 | 1.09(0.81–1.47)0.027 0.557 | | 1.20(0.70–2.03)0.001 0.508 | | 1.19(0.73–1.95)0.001 0.483 | | 0.96(0.63–1.47)0.786 0.852 | | 0.99(0.66–1.50)0.733 0.966 |
ARMS PCR | 2 | 324/455 | 0.85(0.68–1.07)0.135 0.170 | | 0.83(0.61–1.31)0.368 0.239 | | 0.81(0.61–1.09)0.220 0.170 | | 0.74(0.43–1.27)0.216 0.277 | | 0.82(0.48–1.38)0.287 0.446 |
rs1800872 -592 | | | | | | | | | | |
Total | 11 | 1883/2036 | 1.22(1.02–1.41)0.007 0.033 | | 1.02(0.88–1.91)0.115 0.775 | | 1.23(0.99–1.53)0.018 0.059 | | 1.51(1.10–2.06)0.084 0.011 | | 1.49(1.21–1.83)0.120 0.000 |
Ethnicity | | | | | | | | | | | |
Asian | 5 | 910/1081 | 1.17(1.02–1.34) 0.141 0.021 | | 1.09(0.90–1.33) 0.245 0.372 | | 1.16(0.97–1.14) 0.162 0.109 | | 1.42(1.07–1.88) 0.203 0.014 | | 1.35(1.04–1.75) 0.334 0.024 |
Caucasian | 4 | 532/751 | 1.16(0.78–1.71) 0.024 0.460 | | 0.98(0.63–1.53) 0.076 0.931 | | 1.09(0.69–1.74) 0.041 0.705 | | 1.36(0.89–2.08) 0.320 0.150 | | 1.48(0.99–2.21) 0.312 0.055 |
SOC | | | | | | | | | | | |
HB | 5 | 716/717 | 1.21(0.86–1.71) 0.041 0.067 | | 1.13(0.90–1.42)0.142 0.303 | | 1.28(0.86–1.91)0.045 0.218 | | 1.32(0.94–1.84)0.107 0.112 | | 1.26(0.92–1.73)0.144 0.153 |
PB | 6 | 1167/1319 | 1.24(0.99–1.55) 0.013 0.269 | | 0.95(0.77–1.16)0.183 0.599 | | 1.22(0.92–1.62)0.039 0.167 | | 1.69(1.25–2.27)0.191 0.001 | | 1.69(1.28–2.23)0.291 0.000 |
Genotyping | | | | | | | | | | | |
ARMS PCR | 2 | 324/455 | 1.42(0.84–2.38)0.031 0.187 | | 1.01(0.74–1.40)0.632 0.934 | | 1.19(0.88–1.60)0.189 0.262 | | 2.20(0.82–5.94)0.040 0.119 | | 2.15(0.87–5.33)0.043 0.098 |
TaqMan | 2 | 260/547 | 0.91(0.70–1.18)0.883 0.470 | | 0.84(0.60–1.17)0.569 0.302 | | 0.86(0.62–1.18)0.800 0.355 | | 0.99(0.51–1.91)0.416 0.972 | | 1.03(0.54–1.96)0.340 0.928 |
PCR-RFLP | 4 | 658/757 | 1.44(0.99–2.10)0.005 0.057 | | 1.36(0.88–2.09)0.045 0.166 | | 1.53(0.94–2.49)0.010 0.084 | | 1.60(1.15–2.22)0.125 0.005 | | 1.46(1.07–1.98)0.367 0.016 |
sequence | 2 | 447/103 | | | | | 1.70(1.08–2.68)0.520 0.022 | | | | |
rs1800871 -819 | | | | | | | | | | |
Total | 3 | 571/720 | 1.16(0.99–1.36)0.131 0.071 | | 0.99(0.77–1.26)0.189 0.910 | | 1.09(0.87–1.37)0.113 0.449 | | 1.46(1.04–2.04)0.337 0.028 | | 1.47(1.08-2.00)0.720 0.015 |
Ph: value of Q-test for heterogeneity test; P: Z-test for the statistical significance of the OR |
For the rs1800872 polymorphism (1883 cases and 2036 controls), individuals carrying the A-allele existed an increased relation with HIV-1 risk in the total sample population (the allelic contrast: OR: 1.22, 95% CI: 1.02–1.41, P(heterogeneity) = 0.007, P: 0.033, Fig. 4A; AA verse CC: OR: 1.51, 95% CI: 1.10–2.06, P = 0.084 for heterogeneity, P: 0.011; AA vs. AC + CC: OR: 1.49, 95% CI: 1.21–1.83, P = 0.120 for heterogeneity, P < 0.01). In the stratified analysis by race subgroup, a similar significant difference was observed for the Asians (allelic contrast: OR: 1.17, 95% CI: 1.02–1.34, P(heterogeneity): 0.141, P: 0.021, Fig. 4B; AA vs. CC: OR: 1.42, 95% CI: 1.07–1.88, P(heterogeneity) = 0.203, P: 0.014; AA vs. AC + CC: OR: 1.35, 95% CI: 1.04–1.75, P(heterogeneity) = 0.334, P: 0.024). In addition, in source of control group, a significant risk effect was observed in PB (AA vs. CC: OR: 1.69, 95% CI: 1.25–2.27, P(heterogeneity) = 0.191, P < 0.01, Fig. 5; AA vs. AC + CC: OR: 1.69, 95% CI: 1.28–2.23, P(heterogeneity) = 0.291, P < 0.01). Finally, in group for genotype method, increased trends were found in both PCR-RFLP (AA vs. CC: OR: 1.60, 95% CI: 1.15–2.22, P(heterogeneity) = 0.125, P: 0.005; OR: 1.46, 95% CI: 1.07–1.98, P(heterogeneity) = 0.367, P: 0.016, Fig. 6A for AA vs. AC + CC) and sequence methods (OR: 1.70, 95% CI: 1.08–2.68, P(heterogeneity) = 0.520, P: 0.022, Fig. 6B for AA + AC vs. CC).
For the rs1800871 polymorphism (571 cases and 720 controls), increased associations were observed in total in two models (TT vs. CC: OR: 1.46, 95% CI: 1.04–2.04, P(heterogeneity) = 0.337, P: 0.028; TT vs. TC + CC: OR: 1.47, 95% CI: 1.08-2.00, P(heterogeneity) = 0.720, P: 0.015, Fig. 7).
Bias Diagnosis And Sensitivity Analysis For Rs1800896 And Rs1800872
We used the Begg’s funnel diagram and Egger’s test to evaluate the publication bias (such as the allelic contrast, t = 1.5, P = 0.172 for Egger’s test; z = 1.43, P = 0.152 for Begg’s test for rs1800896, Fig. 8A,B, and the allelic contrast, t = 1.43, P = 0.189 for Egger’s test; z = 1.43, P = 0.152 for Begg’s test for rs1800872, Fig. 8C,D, Table 3). We use sensitivity analysis to determine whether changes in a single study will affect final outcomes., We applied the sensitive analysis to delete the power and stability of each study and whole study, no significant influence was found (rs1800896, Fig. 8E; rs1800872, Fig. 8F).
Table 3
Publication bias tests (Begg’s funnel plot and Egger’s test for publication bias test) for IL-10 polymorphisms.
Egger's test | | | | | | | Begg's test | |
Genetic type | Coefficient | Standard error | t | P value | 95%CI of intercept | | z | P value |
rs1800896 -1082 | | | | | | | | |
G-allele vs. A-allele | 2.683 | 1.787 | 1.5 | 0.172 | (-1.439- 6.805) | | 1.43 | 0.152 |
GA vs. AA | 1.846 | 1.412 | 1.31 | 0.227 | (-1.411- 5.105) | | 1.07 | 0.283 |
GG + GA vs. AA | 2.019 | 1.384 | 1.46 | 0.183 | (-1.173- 5.213) | | 1.07 | 0.283 |
GG vs. AA | 0.792 | 0.348 | 2.27 | 0.053 | (-0.011-1.597) | | 1.79 | 0.074 |
GG vs. GA + AA | 0.79 | 0.343 | 2.3 | 0.05 | (-0.001-1.581) | | 1.79 | 0.074 |
rs1800872 -592 | | | | | | | | |
A-allele vs. C-allele | 1.991 | 1.387 | 1.43 | 0.189 | (-1.208- 5.19) | | 1.43 | 0.152 |
AC vs. CC | 1.976 | 1.011 | 1.95 | 0.087 | (-0.356- 4.309) | | 1.43 | 0.152 |
AA + AC vs. CC | 2.906 | 1.093 | 2.66 | 0.026 | (-0.432- 5.379) | | 1.71 | 0.087 |
AA vs. CC | 0.201 | 1.175 | 0.17 | 0.868 | (-2.509-2.913) | | 0.36 | 0.721 |
AA vs. AC + CC | 0.084 | 1.225 | 0.07 | 0.947 | (-2.741-2.909) | | 0.18 | 0.858 |
Gene-gene Network Diagram And Interaction Of Online Website
IL-10 gene may interact with several genes from String online server. The network of gene-gene interaction has been shown in Fig. 9.