Association Between the Interleukin-10-1082G/A,−592C/A,−819C/T Gene Polymorphism and HIV-1 Susceptibility: A Meta-Analysis

Abstract

The Interleukin-10 (IL-10) gene polymorphism influences the pathogenesis and evolution of HIV-1 disease. Many studies in this regard have evaluated the association between this polymorphism and HIV-1 susceptibility, yet, the exact relationship between them remains ambiguous and contradictory. A systematic literature search was conducted and the found case–control studies assessing the association between IL-10-1082G/A, −592C/A, −819C/T gene polymorphism and HIV-1 susceptibility were analyzed. The pooled odds ratios (ORs) and 95% confidence interval (CI) were calculated by a fixed effect model. In general, no significant relationship was found between IL-10-1082G/A gene polymorphism and susceptibility to HIV-1 infection (A vs. G genotype model: OR = 0.97, 95% CI = 0.81–1.23, p = .775; GG vs. AA+AG model: OR = 0.98, 95% CI = 0.76–1.27, p = .867; GG+AG vs. AA model: OR = 0.97, 95% CI = 0.70–1.35, p = .852; GG vs. AA model: OR = 0.88, 95% CI = 0.67–1.15, p = .348; AG vs. AA model: OR = 0.96, 95% CI = 0.67–1.37, p = .811; GG+AA vs. AG model: OR = 1.03, 95% CI = 0.74–1.43, p = .886). IL-10-529C/A gene polymorphism might lead to a decreased risk of HIV-1 infection (A vs. G genotype model: OR = 0.88, 95% CI = 0.73–1.06, p = .166; GG vs. AA+AG model: OR = 0.94, 95% CI = 0.80–1.11, p = .447; GG+AG vs. AA model: OR = 0.75, 95% CI = 0.61–0.92, p = .005; GG vs. AA model: OR = 0.73, 95% CI = 0.57–0.93, p = .012; AG vs. AA model: OR = 0.74, 95% CI = 0.60–0.92, p = .0.007; GG+AA vs. AG model: OR = 1.11, 95% CI = 0.72–1.71, p = .641). IL-10-819C/T gene polymorphism might lead to an increased risk of HIV-1 infection (A vs. G genotype model: OR = 1.25, 95% CI = 1.04–1.50, p = .019; GG vs. AA+AG model: OR = 1.29, 95% CI = 0.81–2.01, p = .278; GG+AG vs. AA model: OR = 1.42, 95% CI = 1.05–1.93, p = .023; GG vs. AA model: OR = 1.63, 95% CI = 1.11–2.38, p = .012; AG vs. AA model: OR = 1.32, 95% CI = 0.95–1.84, p = .094; GG+AA vs. AG model: OR = 0.92, 95% CI = 0.72–1.19, p = .537). In general, the meta-analysis found no marked association between the IL-10-1082G/A gene polymorphism and HIV-1 susceptibility, IL-10-529C/A gene polymorphism might lead to a decreased risk of HIV-1 infection, and IL-10-819C/T gene polymorphism might lead to an increased risk of HIV-1 infection.

Introduction

Interleukin-10 (IL-10) is an immunoregulatory cytokine that can attenuate inflammatory responses.¹ IL-10 is mainly produced by macrophages, natural killer (NK) cells, dendritic cells (DCs), mast cells, eosinophils, neutrophils, CD4 and CD8 T cells, and B cells.² IL-10 gene is located on chromosome 1 (1q31-1q32) that is encoded by five exons.³ In the IL-10 promoter region, at least 23 single nucleotide polymorphisms (SNPs) have been reported.⁴ The most investigated SNPs are −1082G/A, −592C/A, −819C/T upstream from the transcription start site.⁵

Many reports have documented that HIV infection is characterized by generalized immune activation with high levels of circulating cytokines, such as tumor necrosis factor (TNF)-α, interleukin (IL)-6, and IL-10. ^6

–9 Polymorphisms associated with decreased IL-10 production have been associated with increased likelihood of HIV-1 acquisition and accelerated rate of CD4⁺ T cell decline particularly in late stage disease,¹⁰ suggesting that high IL-10 production may reduce susceptibility to HIV-1 infection and protect against disease progression.¹¹ Meanwhile, several reported studies suggest that IL-10 is associated in the pathogenesis of HIV-1 infection.¹² However, although many population studies on the relationship between susceptibility to HIV infection and IL-10-1082G/A, −592C/A, −819C/T gene polymorphism have been conducted, the results are inconsistent and inconclusive due to limited sample sizes and different study populations.^13,14 Hence, for this reason, a meta-analysis was carried out to explore whether there is any relationship between IL-10-1082G/A, −592C/A, −819C/T gene polymorphism and susceptibility to HIV-1 in the population.

Strategy for literature search

An extensive search of the available literature on the association between susceptibility to HIV-1 and IL-10 gene polymorphism (−1082G/A, −592C/A, −819C/T) was conducted by searching PubMed, Web of Knowledge, Embase, Chinese Web of Knowledge, Wanfang, and Chongqing VIP database. The database was searched up to January 2016 and included English and/or Chinese studies with the keywords “Human Immunodeficiency Virus” or “HIV” or “AIDS” or “Acquired Immune Deficiency Syndrome,” polymorphism or variant or mutation, “interleukin” or “IL” or “cytokine.”

Criteria for inclusion and exclusion

A strict criteria for inclusion and exclusion was used in this meta-analysis and all selected studies met the following inclusion criteria: (1) the aim of the study must be to assess the association between the IL-10-1082G/A, −592C/A, −819C/T gene polymorphism and HIV-1 susceptibility (2) must be a relevant case–control study (3) must have selected published and printed data for estimating the odds ratio (OR) with 95% confidence interval (CI).

On the other hand, the following studies were excluded: (1) animal studies (2) repeated study (3) studies where genotype frequencies were not reported.

Data extraction

Data was extracted by two investigators using a standardized data extraction method form from all elected studies individually, and in case of disagreement between the two researchers, discussion would ensue to reach consensus. The following information was extracted from each study: name of the first author, publication year, country, background, sample size, selection criteria of controls, genotype and allele/number of patients and controls.

Quality assessment

The Newcastle-Ottawa Scale for assessing quality of observational and nonrandomized studies was adopted for quality assessment.

Statistical analysis

The association between IL-10-1082G/A, −592C/A, −819C/T gene polymorphism and the susceptibility of HIV-1 was anticipated by OR with the corresponding 95% confidence interval (CI) under an allele model (G vs. A), a dominant model (GG vs. AA+AG), a recessive model (GG+AG vs. AA), and a co-dominant model (GG vs. AA) and an over-dominant model (GG+AA vs. AG). The implication of the pooled OR was determined by Z test. The fixed-effects model or random-effects model was utilized depending on whether heterogeneity existed among studies or not. Heterogeneity among studies was analyzed with Cochran's Q statistic and the I² statistic. p < .10 in Q-test indicated no heterogeneity among studies. p < .1 rather than 0.05 was considered noteworthy heterogeneity for the χ ²-based Q testing and a value of 0% for I² indicated no heterogeneity and increasing percentage implied increased heterogeneity. That is, I² will be utilized to guess total variation across studies that are due to heterogeneity rather than chance (<25% is considered low heterogeneity, 25%–50% moderate, and >50% as high-level heterogeneity).^15,16 The numerical significance of OR was estimated using Z test, and p < .05 was measured as statistically important. To assess the stability of results sensitivity analysis was done by eliminating one single study each time.¹⁷ Similarly, Hardy–Weinberg equilibrium was estimated by the χ ² test in the controls.¹⁸ To find publication bias Begg's funnel plot and Egger's test were examined.^19,20 Also, Egger's linear regression test was conducted to estimate funnel plot asymmetry (p < .05 was estimated significant publication bias), and other similar study analyses were done by using STATA version 12.0 software (Stata Corporation, College Station, TX). It was analyzed that all tests were two-sided and the significance levels were found to be 0.05.

Results

Search results and characteristics of the included studies

A database was used to shortlist 190 potentially relevant articles, from which a total of 146 articles were identified for further evaluation. Afterward, a more exhaustive reading and analysis helped to remove 97 potentially relevant articles, which were rejected because of their obvious irrelevance to the purpose of this study. Ultimately, six studies including 1147 cases and 1637 controls for IL-10-1082G/A, seven studies including 1279 cases and 1696 controls for IL-10-592C/A, and two studies including 440 cases and 565 controls for IL-10-819C/T gene polymorphism were incorporated in our meta-analysis. The flow chart of the search method is shown in Figure 1, while the individuality and characteristics of these articles are listed in Table 1. All nine studies provide the numbers of alleles in both cases and controls. To test all the polymorphism in the control group, the Hardy–Weinberg equilibrium model was used (Tables 2 –4).

FIG. 1.

Flow diagram of included/excluded studies.

Table 1.

Characteristics of Included Studies

First author	Country	Year	Case	Control
Erikstrup	Zimbabwe	2007	198	180
Chatterjee	India	2008	180	305
Kallas	Tallinn	2015	172	496
Freitas	Brazil	2014	216	294
Sobti	India	2009	300	300
Sunder	India	2012	121	102
Corchado	Spain	2013	91	55
Singh³⁸	India	2016	260	260
Piddubna³⁹	Ukraine	2013	78	100

Table 2.

Genotype and Allele Distributions in Cases and Controls (−1082G/A)

	Cases					Controls
First author	GG	GA	AA	G	A	GG	GA	AA	G	A	HWE(P)
Erikstrup	22	73	100	117	273	17	82	76	116	234	0.50
Chatterjee	20	60	100	100	260	27	122	156	176	434	0.68
Kallas	32	78	62	142	202	104	251	141	459	533	0.72
Freitas	14	79	123	107	325	24	111	159	159	429	0.46
Sunder	2	83	36	87	155	2	43	57	47	157	0.09
Singh	21	119	120	161	359	21	125	114	167	353	0.12

HWE, Hardy–Weinberg equilibrium.

Table 3.

Genotype and Allele Distributions in Cases and Controls (−592C/A)

	Cases					Controls
First author	CC	CA	AA	C	A	CC	CA	AA	C	A	HWE(P)
Erikstrup	80	71	43	231	157	68	81	25	217	131	1.00
Chatterjee	67	74	39	208	152	140	122	43	402	208	0.06
Kallas	113	49	10	275	69	306	167	23	779	213	1.00
Sobti	36	136	127	208	390	34	146	120	214	386	0.32
Corchado	43	38	7	124	52	24	21	6	69	33	0.75
Singh	106	115	39	327	193	109	122	29	340	180	0.68
Piddubna	42	28	8	112	44	25	5	0	55	5	1.00

Table 4.

Genotype and Allele Distributions in Cases and Controls (−819C/T)

	Cases					Controls
First author	TT	CT	CC	T	C	TT	CT	CC	T	C	HWE(P)
Chatterjee	39	74	67	152	208	43	122	140	208	402	0.06
Singh	29	122	109	180	340	39	115	106	193	327	0.43

Risk of bias assessment

The quality of the studies included in the meta-analysis was assessed with the Newcastle-Ottawa Scale, and higher scores reflect better quality of the study methodology. The average score of all studies was above six (these results are not shown).

Pooled analyses

Association between the IL-10-1082G/A gene polymorphism and HIV-1 susceptibility

Fixed-effects model was used in the recessive model and the co-dominant model, and random-effects model was used in the other models. In general, no significant relationship was found between the IL-10-1082G/A gene polymorphism and susceptibility to HIV-1 infection (A vs. G genotype model: OR = 0.97, 95% CI = 0.81–1.23, p = .775; GG vs. AA+AG model: OR = 0.98, 95% CI = 0.76–1.27, p = .867; GG+AG vs. AA model: OR = 0.97, 95% CI = 0.70–1.35, p = .852; GG vs. AA model: OR = 0.88, 95% CI = 0.67–1.15, p = .348; AG vs. AA model: OR = 0.96, 95% CI = 0.67–1.37, p = .811; GG+AA vs. AG model: OR = 1.03, 95% CI = 0.74–1.43, p = .886) (Table 5 and Fig. 2).

FIG. 2.

Forest plot of the susceptibility of HIV-1 associated with IL-10-1082G/A (AA vs. GG/AG).

Table 5.

Main Results of the Pooled Odds Ratios in the Meta-Analysis

Polymorphisms	Genetic model	OR(95%CI)	Z	p value	I²%	P_het^*	Effect model
−1082G/A	G vs. A	0.97 (0.81–1.23)	0.29	.775	58.8	0.033	Random
	GG vs. AA+AG	0.98 (0.76–1.27)	0.17	.867	0.0	0.869	Fixed
	GG+AG vs. AA	0.97 (0.70–1.35)	0.19	.852	76.2	0.001	Random
	GG vs. AA	0.88 (0.67–1.15)	0.94	.348	0.0	0.820	Fixed
	AG vs. AA	0.96 (0.67–1.37)	0.24	.811	77.6	0.000	Random
	GG+AA vs. AG	1.03 (0.74–1.43)	0.14	.886	76.7	0.001	Random
−592C/A	C vs. A	0.88 (0.73–1.06)	1.38	.166	54.0	0.042	Random
	CC vs. AA+AC	0.94 (0.80–1.11)	0.76	.447	48.2	0.072	Fixed
	CC+AC vs. AA	0.75 (0.61–0.92)	2.79	.005	0.0	0.441	Fixed
	CC vs. AA	0.73 (0.57–0.93)	2.50	.012	5.7	0.384	Fixed
	AC vs. AA	0.74 (0.60–0.92)	2.68	.007	0.0	0.604	Fixed
	CC+AA vs. AC	1.11 (0.72–1.71)	0.47	.641	85.8	0.000	Random
−819C/T	C vs. T	1.25 (1.04–1.50)	2.34	.019	36.7	0.209	Fixed
	CC vs. TT+TC	1.29 (0.81–2.01)	1.08	.278	59.3	0.117	Random
	CC+TC vs. TT	1.42 (1.05–1.93)	2.27	.023	0.0	0.956	Fixed
	CC vs. TT	1.63 (1.11–2.38)	2.52	.012	0.0	0.415	Fixed
	TC vs. TT	1.32 (0.95–1.84)	1.68	.094	0.0	0.733	Fixed
	CC+TT vs. TC	0.92 (0.72–1.19)	0.62	.537	0.0	0.810	Fixed

^*P_{he t} = p value for heterogeneity.

Association between IL-10-592C/A gene polymorphism and HIV-1 susceptibility

Random-effects model was used in the allele contrast model and over-dominant model, and fixed-effects model was used in the other models. In general, IL-10-592C/A gene polymorphism might lead to a decreased risk of HIV-1 infection (A vs. C genotype model: OR = 0.88, 95% CI = 0.73–1.06, p = .166; CC vs. AA+AC model: OR = 0.94, 95% CI = 0.80–1.11, p = .447; CC+AC vs. AA model: OR = 0.75, 95% CI = 0.61–0.92, p = .005; CC vs. AA model: OR = 0.73, 95% CI = 0.57–0.93, p = .012; AC vs. AA model: OR = 0.74, 95% CI = 0.60–0.92, p = .007; CC+AA vs. AC model: OR = 1.11, 95% CI = 0.72–1.71, p = .641) (Table 5 and Fig. 3).

FIG. 3.

Forest plot of the susceptibility of HIV-1 associated with IL-10-592C/A (CC vs. AA).

Association between the IL-10-819C/T gene polymorphism and HIV-1 susceptibility

Random-effects model was used in the recessive model, and random-effects model was used in the other models. In general, IL-10-819C/T gene polymorphism might lead to an increased risk of HIV-1 infection (C vs. T genotype model: OR = 1.25, 95% CI = 1.04–1.50, p = .019; TT vs. CC+CT model: OR = 1.29, 95% CI = 0.81–2.01, p = .278; TT+CT vs. CC model: OR = 1.42, 95% CI = 1.05–1.93, p = .023; TT vs. CC model: OR = 1.63, 95% CI = 1.11–2.38, p = .012; CT vs. CC model: OR = 1.32, 95% CI = 0.95–1.84, p = .094; TT+CC vs. CT model: OR = 0.92, 95% CI = 0.72–1.19, p = .537) (Table 5 and Fig. 4).

FIG. 4.

Forest plot of the susceptibility of HIV-1 associated with IL-10-819C/T (C vs. T).

Discussion

The present meta-analysis is evocative of the absence of a relationship between the IL-10-1082G/A gene polymorphism and susceptibility to HIV-1. Thus, the results of this meta-analysis indicate that the IL-10-1082G/A gene polymorphism are not involved in susceptibility to HIV-1. As for association between IL-10-592C/A, −819C/T and HIV-1 susceptibility, IL-10-592C/A gene polymorphism might lead to a decreased risk of HIV-1 infection, and IL-10-819C/T gene polymorphism might lead to an increased risk of HIV-1 infection.

HIV/AIDS has been increasing with the passage of time since it was found by the U.S. Center for Disease Control and Prevention (CDC) in 1981.²¹ HIV-infections remain the deadliest epidemic in human history. Despite the reasonable progress made in the HIV/AIDS diagnosis, prevention and treatment of HIV/AIDS are still among the most important public health issues globally.²² Cytokines play a vital role in regulating the homoeostasis of the immune system and alterations in their relative levels play critical roles in the immune response against HIV-1 infection and the progression of HIV-1 infection to clinical AIDS.²³ Many reports have documented that HIV infection is characterized by generalized immune activation with high levels of circulating cytokines, such as TNF-α, IL-6, and IL-10. ^6

–9,24 Numerous population based studies have been conducted to authenticate the hypothesis that IL-10 gene polymorphisms may boost the susceptibility to HIV-1.^2,9,10 Nevertheless, at present, the available published data on the relationship between the IL-10-1082G/A, −592C/A, −819C/T gene polymorphism and HIV-1 susceptibility have only provided conflicting results.^13,14 Accordingly, to address this issue this study was undertaken.

IL10 is a TH-2 cell cytokine that inhibits macrophage growth and T cell cytokine secretion.²⁵ Interleukin 10 is a major regulator of innate immunity and prevents the development of immunopathological lesions that result from exacerbated protective immune response to acute and chronic infections.²⁶ HIV-1-infected individuals with a particular IL-10 promoter haplotype have recently been reported to progress to AIDS more rapidly, but with a late effect manifested primarily about 5 years post-HIV-1 seroconversion.²⁷ Indeed, IL-10 may promote viral persistence by inactivation of effect or immune mechanisms.^28,29 In addition, increasing evidence has suggested that IL-10 acts as a general inhibitor of proliferative and cytokine responses of both T-helper-Th1 and Th2 cells in vitro and in vivo. ³⁰ IL-10 limits viral replication in vivo by inducing secretion of inflammatory cytokines and limiting replication of T cells. Polymorphisms in IL-10 were also shown to influence susceptibility to HIV infection and rate of progression to AIDS.³¹

This study presents a detailed analysis of the association between the IL-10-1082G/A, −592C/A, −819C/T gene polymorphism and HIV-1 susceptibility. The results revealed no statistically significant relationship between the overall effects of the IL-10-1082G/A gene polymorphisms and HIV-1 susceptibility in any of the genetic models. The validity of the failure to detect any significant effect of this polymorphism on HIV-1 infection was endorsed by many critical factors. First, other IL gene polymorphisms such as IL-10-592C/A, −597C/A, −819T/C can affect the ability of produce IL-10 and afterward affect the susceptibility to HIV-1.^32

–35 In the meantime the low AA genotype frequency can be an important element.³⁶ Additionally, it could be due to the antagonistic relation of the opposite effect that can be seen between IL and other genes.³⁷ Consequently, the effect must be analyzed with vigilance, and further investigations with additional extensive number of case–control studies are necessary to authenticate these result. As for association between IL-10-592C/A, −819C/T and HIV-1 susceptibility, IL-10-529C/A gene polymorphism might lead to a decreased risk of HIV-1 infection, and IL-10-819C/T gene polymorphism might lead to an increased risk of HIV-1 infection.

Several limitations need to be addressed, and they could influence the result. First, this meta-analysis was based on a relatively small number of studies. Second, we confined our studies to published studies in English and Chinese, and thus did not include the unpublished researches, as a result related articles published in other language or unpublished studies were left out and this method could lead to the oversight of some related studies concerning the relationship between the IL-10-1082G/A gene polymorphism and HIV-1 susceptibility. Third, we could not test for the gene and environment interactions due to the lack of sufficient studies. Fourth, the detailed genetic data in different age and gender were insufficient in the studies of this meta-analysis, so there is no analysis about different age and gender. In the future, we will continue to collect the detailed genetic data in different age and gender for further analysis. Additionally, we should all be aware of the heterogeneity that was revealed by our analyses. The heterogeneity is a potential problem.

To the best of our knowledge, this is the first meta-analysis that has been performed to examine the relationship between the IL-10-1082G/A, −592C/A, −819C/T gene polymorphism with HIV-1. Additionally, the relationship between the IL-10-1082G/A, −592C/A, −819C/T gene polymorphism and HIV-1 susceptibility is statistically more persuasive than any single study. But this issue must be further investigated to ascertain the relationship between other related variables with the susceptibility to HIV-1.

Conclusion

This study evaluated the association between IL-10-1082G/A, −592C/A, −819C/T gene polymorphism and HIV-1 susceptibility. IL-10-1082G/A gene polymorphism are not involved in susceptibility to HIV-1, IL-10-592C/A gene polymorphism might lead to a decreased risk of HIV-1 infection, and IL-10-819C/T gene polymorphism might lead to an increased risk of HIV-1 infection.

Footnotes

Acknowledgment

We thank all our colleagues working in the Department of Epidemiology and Health Statistics, School of Public Health of Central South University.

Author Contributions

Designed the experiments: L.C. and C.J. Performed the experiments: C.J., Z.L., and S.J.L. Analyzed the data: C.J., S.X.L., and P.C. Contributed reagents/materials/analysis tools: L.C., C.J., and Z.L. Wrote the article: C.J. and L.C.

Author Disclosure Statement

No competing financial interests exist.

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