Abstract
Adiponectin (ADIPOQ) plays an important role in the pathogenesis of diabetic nephropathy (DN) and previous studies regarding the association between ADIPOQ polymorphisms and DN risk reported conflicting results. To derive a more precise estimation of this association, we performed a meta-analysis to assess the association between four ADIPOQ polymorphisms [−11391G > A (rs17300539), −11377C > G (rs266729), +45T > G (rs2241766), and +276G > T (rs1501299)] and risk for DN. Odds ratios (ORs) with corresponding 95% confidence intervals (95% CIs) were pooled to assess the association between four aforementioned polymorphisms and susceptibility to DN. Based on the included criteria, we selected 13 articles, among which 7 studies (cases/controls: 2749/7585) for −11391G > A, 8 studies for −11377C > G (3074/3842), 9 studies for +45T > G (2654/7710), and 10 studies for +276G > T (2812/7821), respectively. Our meta-analysis indicated no evidence heterogeneity among the included studies; thus, the fixed-effects model was used. Overall, there was an association between ADIPOQ −11391A allele with increased DN risk (OR = 1.186, 95% CI: 1.051–1.338, p = 0.006). Subgroup by ethnicity suggested significant association between +45T > G polymorphism and DN risk among Caucasians (OR = 1.122, 95% CI: 1.007–1.250, p = 0.038). Sensitivity analysis suggested exclusion of any single study did not materially alter the overall pooled ORs above. Future studies are needed to validate these findings.
Introduction
Diabetic nephropathy (DN) is a common microvascular complication of type 1 and type 2 diabetes (T1DM and T2DM), and it is the primary cause of end-stage renal disease (ESRD) worldwide.Citation1–3 DN results from various causes including genetic and environmental factors, and major genes that contribute to the etiology of DN have yet to be identified.Citation4–8 The adiponectin gene (gene ID 9370) is encoded as ADIPOQ (adipocyte C1q and collagen domain containing); and GBP28, ACRP30, APM1, and ACDC are this gene’s alternative names.Citation9 The ADIPOQ gene is located in chromosome 3q27 and consists of three exons and two introns.Citation9–11 ADIPOQ is an adipokine, which not only performs an important role in the regulation of insulin action, glucose, and lipid metabolism but also exerts anti-inflammatory and anti-atherogenic effects, with a low circulating concentration in cases of insulin resistance, T2DM, and coronary heart disease.Citation12–15 In contrast, ADIPOQ levels are high in cases of DN, but it is still unclear whether these high levels are a cause or a consequence of the disease.Citation16 The influence of ADIPOQ genetic polymorphisms in the development of DN is, nonetheless, not fully understood. Therefore, it is urgent to elucidate the association of ADIPOQ genetic polymorphisms and susceptibility to DN. Several polymorphisms in ADIPOQ gene have been identified, with −11391G > A (rs17300539), −11377C > G (rs266729), +45T > G (rs2241766), and +276G > T (rs1501299) and DN risk being extensively evaluated.Citation8–10,Citation16–33 Evidences have suggested that genetic variations of −11391G > A and −11377C > G in the promoter region of this gene can play a vital role in the increased risk of developing nephropathy partly through affecting the plasma levels of ADIPOQ.Citation8,Citation16 In addition, genetic association studies have demonstrated that single nucleotide polymorphisms (SNPs) +45T > G in exon2 and +276G > T in intron 2 of this gene confer the risk susceptibility to the development of DN.Citation8,Citation16,Citation21 However, results are inconsistent and firm association has not yet been established.
Considering the important roles of the ADIPOQ gene to the risk of developing DN and the insufficient power of a single study to provide responsible conclusion, we conducted a meta-analysis of all available studies relating four aforementioned polymorphisms in ADIPOQ gene to shed some light on these controversial issues.
Methods
Search strategy
A comprehensive search strategy was conducted towards the electronic databases including PubMed, Embase, Medline and CNKI databases. The following search terms were used: (1) adiponectin, ADIPOQ, APM1, and ACDC; (2) diabetic nephropathy and diabetes nephropathy; and (3) polymorphism, variation, variant, and mutation. An upper date limit of August 2013 was applied and we used no lower date limit. The language was restricted to English and Chinese. In addition, we reviewed the reference lists of retrieved papers and recent reviews.
Study selection
We first performed an initial screening of titles or abstracts. A second screening was based on full-text review. The inclusion criteria were: (1) case--control or cohort studies which evaluated the association between ADIPOQ −11391G > A (rs17300539), −11377C > G (rs266729), +45T > G (rs2241766), and +276G > T (rs1501299) polymorphisms and DN risk in type 1 or type 2 diabetic patients; (2) the controls were diabetic individuals without DN; (3) used an unrelated case–control or cohort design and had available genotype/allele counts for estimating an OR with its 95% CI. If two or more studies described outcomes among the same or overlapping groups of cases or controls, only the one with the largest available data was included in the meta analysis.
Data extraction
All data were reviewed and extracted independently by two investigators. From each study the following information was extracted: ADIPOQ polymorphisms, first author, publication year, ethnicity of study populations, study design, types of diabetes, genotyping methods, the number of cases and controls, minor allele frequency (MAF) in cases and controls. Any discrepancies in the extracted data were settled by discussion and, when necessary, adjudicated by a third reviewer.
Statistical analysis
In view of articles providing data only on allele counts accounted for the majority of the included ones, and to enhance study power to detect an association, we exclusively took account of allelic model in this meta-analysis. To test the population stratification in the controls, the departure of frequencies of ADIPOQ polymorphisms using the chi-square test from expectation under Hardy–Weinberg equilibrium (HWE) was assessed in controls. Pooled ORs (95% CI) for DN risk associated with ADIPOQ gene −11391A, −11377G, +45G, and +276T alleles compared with the alternative alleles were calculated, respectively. In this analysis, both the chi-square based Q statistic test (Cochran's Q statistic) and the I2 statistic were applied to assess the between-study heterogeneity more precisely.Citation35,Citation36 Heterogeneity was considered significant for P Cochran's Q statistic <0.10. With evidence heterogeneity among studies, the random-effects model (the DerSimonian and Laird method) was used to assess the summary ORs of each study;Citation37 Otherwise, the fixed-effects model (the Mantel–Haenszel method) was used to pool the results.Citation38 For exploring between-study heterogeneity or indicating that our results were statistically robust, subgroup analysis was also performed by ethnicity for ADIPOQ −11391G > A, −11377C > G, +45T > G, and +276G > T polymorphisms. Furthermore, we conducted a sensitivity analysis to examine the influence of a single study on the overall risk estimate by omitting one study in each turn.Citation39 Eventually, potential publication bias was tested by Begg’s funnel plot and Egger’s test. Possible publication bias was assessed by visual inspection of the funnel plots in which the log ORs were plotted against their SEs.Citation40 Significance was judged at the p < 0.1 level of Egger’s test.Citation41 All analyses were performed using STATA version 12.0 (StataCorp LP, College Station, TX). p < 0.05 should be considered statistical significance, except where otherwise specified.
Results
Characteristics of included studies
A flow diagram schematizing the study selection process was shown in . Following our search strategy 397 individual abstracts were retrieved originally, and 23 full-text articles were preliminarily identified for further detailed evaluation.Citation8–10,Citation16–34,Citation42 On the basis of the exclusion criteria, 10 articles were excluded including one study containing overlapping data,Citation31 one review article,Citation34 one article with non-diabetic controls,Citation27 one article with cross-sectional in design,Citation28 one article with no included polymorphisms,Citation32 and five articles with missing relevant data.Citation10,Citation29,Citation30,Citation33,Citation42 Since the article by Vionnet et al.Citation8 categorized data in Denmark, Finland, and France populations, we extracted them as three individual case–control studies. Finally, we included 13 articles, among which 7 studies (cases/controls: 2749/7585) for −11391G > A, 8 studies for −11377C > G (3074/3842), 9 studies for +45T > G (2654/7710), and 10 studies for +276G > T (2812/7821), respectively.
Figure 1. Search flow diagram for studies included in the meta analysis.
The characteristics of included studies are summarized in . In the included studies, the distribution of genotypes in the controls was all in agreement with HWE, except for the +45T > G polymorphism in one studyCitation17 and the +276G > T polymorphism in one study.Citation26
Table 1. Characteristics of studies included in the meta-analysis.
Meta-analysis results
In , our meta-analysis indicated no obvious heterogeneity among the included studies of the ADIPOQ −11391G > A polymorphism (Pheterogeneity = 0.218, I2 = 27.6%), −11377C > G polymorphism (Pheterogeneity = 0.304, I2 = 16.1%), +45T > G polymorphism (Pheterogeneity = 0.482, I2 = 0.0%), and +276G > T polymorphism (Pheterogeneity = 0.430, I2 = 0.9%), thus the fixed-effects model was used. ADIPOQ −11391A allele was associated with increased DN risk (OR = 1.186, 95% CI: 1.051–1.338, p = 0.006). However, no significant association between the −11377C > G, +45T > G or +276G > T polymorphism and DN risk was found in our present study (OR = 0.966, 95% CI: 0.894–1.044, p = 0.387; OR = 1.100, 95% CI: 0.997–1.213, p = 0.057; OR = 1.051, 95% CI: 0.976–1.133, p = 0.189; respectively, ).
Figure 2. Forest plot for meta-analysis association between the ADIPOQ polymorphisms with DN risk (allele model). (a) −11391G > A, (b) −11377C > G, (c) +45T > G, (d) +276G > T.
MAF of the three ADIPOQ polymorphisms among the controls across the different ethnicities (Asians and Caucasians) was also assessed (), except for −11391G > A polymorphism because all ethnicities of the included studies of this polymorphism were Caucasians. For the −11377C > G and +276G > T polymorphisms, there were similar results in the MAF among the controls across Asians and Caucasians. However, we found that the +45G allele frequency in Asian populations was 29.5% (95% CI = 23.1–35.9%), which was significantly higher than that in Caucasian populations (11.9%, 95% CI = 7.0–16.7%, p = 0.003; ).
Table 2. MAF among controls stratified by ethnicity.
Subgroup analyses
The subgroup analysis was undertaken according to ethnicity. we found that +45T > G polymorphism was significantly associated with DN in Caucasian populations (G versus T: Pheterogeneity = 0.442, I2 = 0.0%, OR = 1.122, 95% CI: 1.007–1.250, p = 0.038); for Asian populations, we did not find the similar result. However, no significant association between the −11377C > G or +276G > T polymorphism and risk of DN was found among Caucasian populations and Asian populations ().
Table 3. Stratified analyses of the ADIPOQ polymorphisms on DN risk.
Sensitivity analysis
In this meta-analysis, we also performed sensitivity analyses to test the stability of the overall results. By exclusion of the study violating HWE or altering the statistic models, no material alternation was detected ().
Figure 3. Sensitivity analyses. Horizontal line mean effect size (a) −11391G > A, (b) −11377C > G, (c) +45T > G, (d) +276G > T.
Publication bias
Funnel plot and Egger's test were conducted to evaluate the publication bias in this meta-analysis. In , the shape of the funnel plot did not reveal obvious asymmetry. Then, Egger’s linear regression test was used to provide statistical evidence of funnel plots asymmetry. For the ADIPOQ polymorphisms −11391G > A, −11377C > G, +45T > G, and +276G > T, the p values of Egger’s linear regression test were 0.197, 0.182, 0.171, and 0.599, respectively. Hence, the above results indicated that publication bias was not evident in this meta-analysis.
Figure 4. Funnel plot for assessing publication bias in this meta-analysis. (a) −11391G > A, (b) −11377C > G, (c) +45T > G, (d) +276G > T.
Discussion
Diabetes mellitus affects the kidney in stages, and 30–40% of the patients with T1DM and T2DM suffer from DN.Citation1,Citation2,Citation43 It is well recognized that DN has genetic components and individual susceptibility, while the pathophysiology of DN remains unclear and needs to be fully investigated.Citation6,Citation44–47 Recently, more attention has been paid to the identification of the genetic variations of nephropathy in T1DM and T2DM. Thus, identification of susceptibility or resistance genes in DN will provide better knowledge of pathomechanism, genetic biomarkers and future therapies.Citation48–50
Considerable studies have indicated that the levels of ADIPOQ are influenced by genetic polymorphisms in the ADIPOQ geneCitation51–54 and these polymorphisms have been implicated in DN.Citation8–10,Citation16–32 Nephropathy has been associated with high ADIPOQ levels in T1DM and T2DM.Citation16,Citation31 Thus, the genetic studies of DN and ADIPOQ gene will give new insight into the underlying etiology and lead to new therapies for treatment and prevention in this disease. Previous studies regarding the association between SNPs within ADIPOQ and DN risk reported conflicting results. Studies proposed that these SNPs were determinants of the DN risk.Citation9,Citation16,Citation21 However, several studies also showed that these SNPs were not associated with susceptibility to DN.Citation17,Citation22,Citation23 Among these SNPs, −11391G/A and −11377C/G are located in the ADIPOQ gene promoter region, whereas +45T > G and +276G > T are located in the exon2 and intron 2 region.Citation9–11 Evidences suggested that genetic variation in the promoter region of this gene could play an important role in the risk of DN partly through affecting the plasma levels of ADIPOQ.Citation8,Citation16 Moreover, studies demonstrated that −11377C > G polymorphism could alter the sequence in one of four SP1 binding sites in this promoter region and reduce ADIPOQ promoter transcription activity.Citation9,Citation55 Jaziri et al.Citation16 reported high ADIPOQ concentrations associated with the −11391A, +45G alleles might be the cause, rather than a consequence of DN. Several studies indicated that SNP +276G > T was associated with lower plasma ADIPOQ levels, while no significant association between +276G > T and the prevalence of DN was found in other studies.Citation17,Citation20,Citation23 In view of inconsistent results, we performed a meta-analysis of these SNPs to derive a more precise estimation of the relationship between these SNPs and susceptibility to DN.
In this meta-analysis, 14 articles (7 studies for −11391G > A, 8 studies for −11377C > G, 9 studies for +45T > G, and 10 studies for +276G > T) were performed to provide the assessment of the relationship between ADIPOQ polymorphisms and DN. No obvious heterogeneity was found among the included studies. For ADIPOQ −11391G > A polymorphism, studies observed significant association with DN risk in the allele genetic comparison model. For the −11377C > G, +45T > G, or +276G > T polymorphism, no significant association with DN was found. However, in the subgroup analysis of +45T > G by ethnicity, the results demonstrated significant association was found among Caucasian populations, partly because there was evidence difference in the MAF of +45T > G among the controls across Asians and Caucasians. Sensitivity analysis indicated that our results were statistically robust.
Some possible limitations of this meta-analysis should be acknowledged in explaining the results. First, most included studies were retrospective in design. Second, publication bias might have occurred because only published studies were included and unpublished studies which had null results were missed, which might bias the results. Therefore, these biases could lead to an overestimation of the effects in this meta-analysis. Third, the studies involved were relatively less and small study samples. More and larger studies should be warranted in future to elucidate the role of the variant in DN susceptibility. Finally, DN is a multifactorial disease that results from complex interactions between many environmental and genetic factors. We only focused on ADIPOQ gene polymorphisms, and did not cover other DN susceptibility genes or polymorphisms.
In conclusion, for the −11391G > A and +45T > G polymorphisms, significant association with DN was found by the allele genetic comparison model in overall or subgroup analysis. However, our meta-analysis provided evidence that −11377C > G and +276G > T polymorphisms were unlikely to be associated with genetic susceptibility of DN based on the current published studies. To get a more exact conclusion on the effects of ADIPOQ polymorphisms on DN risk, future large and well-designed studies are necessary.
Declaration of interest
The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.
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