The association between the PPARγ2 Pro12Ala polymorphism and nephropathy susceptibility in type 2 diabetes: a meta-analysis based on 9,176 subjects

  • Lei Wang3Email author,

    Affiliated with

    • Zan Teng4,

      Affiliated with

      • Shuang Cai3,

        Affiliated with

        • Difei Wang4,

          Affiliated with

          • Xin Zhao3 and

            Affiliated with

            • Kai Yu3

              Affiliated with

              Diagnostic Pathology20138:118

              DOI: 10.1186/1746-1596-8-118

              Received: 29 June 2013

              Accepted: 3 July 2013

              Published: 15 July 2013

              Abstract

              Background

              The polymorphism Pro12Ala in peroxisome proliferator-activated receptor­γ2 gene (PPARγ2) has been reported to be associated with diabetic nephropathy (DN) in some studies, though the results remain inconclusive. To explore this relationship between PPARγ2 Pro12Ala polymorphism and the susceptibility for DN, a cumulative meta-analysis was performed in this study.

              Method

              PubMed, Medline, Embase and Web of Science databases have been systematically searched to identify relevant studies. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated.

              Results

              18 studies were included in this meta-analysis, involving 3,361 cases and 5,815 controls. The PPARγ2 Ala12 allele was significantly associated with decreased risk of DN based on dominant model (OR=0.778; 95%CI=0.618–0.981; Pheterogeneity=0.008; P=0.034). In the stratified analysis by ethnicity, significantly decreased risks were found among Caucasians for dominant model (OR=0.674; 95%CI=0.500–0.909; Pheterogeneity=0.079; P=0.010), while there was no significant association was found in Asians.

              Conclusions

              The results from the present meta-analysis indicated that the Pro12Ala polymorphism in PPARγ2 gene is not a risk factor for DN in type 2 diabetes (T2D). Further large and well-designed studies are needed to confirm this conclusion.

              Virtual slides

              The virtual slides for this article can be found here: http://​www.​diagnosticpathol​ogy.​diagnomx.​eu/​vs/​7491348341027320​.

              Keywords

              PPARγ2 Meta-analysis Diabetic nephropathy Polymorphisms

              Introduction

              Diabetic nephropathy is the leading cause of end-stage renal disease (ESRD) worldwide, and it is estimated that 20% of T2D patients reach ESRD during their lifetime [1]. The pathogenesis of DN has many genetic and environmental factors contributing to its development and progression. The risk of developing DN has been linked to different chromosomes, including chromosome 3, to which the peroxisome proliferators-activated receptor (PPAR) gene has been mapped, particularly to the PPAR gamma (PPARG) nuclear receptor, which is mainly expressed in adipose tissue but is also found in pancreatic beta cells, vascular endothelium, and macrophage [2, 3].

              PPAR-γ2 is a nuclear receptor that serves important roles in intermediate metabolism. The PPARG gene is located on chromosome 3p [2]. The Pro12Ala polymorphism of the PPARG gene, a Pro-to-Ala exchange that results in the substitution of proline with alanine at codon 12, was associated with reductions in both DNA binding and transcriptional activity in vitro, and Ala12 carriers showed significant improvement in insulin sensitivity [4, 5]. The Pro12Ala polymorphism in the PPARG gene is suggested to be associated with DN. As we all kwon, many epidemiologic studies investigated the potential association of PPARG gene polymorphisms with susceptibility to DN. However, these studies have reported inconclusive results.

              One putative genetic determinant of DN is the Pro12Ala polymorphism in the gene encoding PPARg. PPARg, a member of the nuclear hormone receptor superfamily of ligand-activated transcription factors, plays a key role in regulating the expression of numerous genes involved in lipid metabolism, metabolic syndrome, inflammation, and atherosclerosis [6, 7]. The P12A single-nucleotide polymorphism (SNP) located in the adipocyte-specific PPARg2 isoform has been associated with lower nephropathy in T2D [8, 9]. The underlying molecular mechanism of this polymorphism appears to be, in vitro, a moderate reduction in DNA-binding activity and reduced transcriptional activity [4, 10]. In the present study, we examined the relationship between PPAR-γ2 gene polymorphisms and the risk of T2D DN.

              Materials and methods

              Search strategy

              A comprehensive literature search was performed using the PubMed, Medline, Embase, and Web of Science database for relevant articles published (last search updated in May. 2013) with the following key words “PPARγ2”, “polymorphism” and “diabetic nephropathy”. Additional studies were identified by hand searching references in original articles and review articles. Authors were contacted directly regarding crucial data not reported in original articles. The search was limited to human studies. All eligible studies were retrieved, and their bibliographies were checked for other relevant publications. When the same sample was used in several publications, only the most complete study was included following careful examination.

              Inclusion criteria

              The included studies have to meet the following criteria: (1) only the case–control studies were considered; (2) evaluated the PPARγ2 Pro12Ala polymorphism and DN risk; (3) the genotype distribution of the polymorphism in cases and controls were described in details, and the results were expressed as odds ratio (OR) and corresponding 95% confidence interval (95% CI).

              Exclusion criteria

              Major reasons for exclusion of studies were as follows: (1) not for DN research; (2) only case population; (3) duplicate of previous publication; and (4) the distribution of genotypes among controls are not in Hardy–Weinberg equilibrium (P <0.01).

              Data extraction

              Information was carefully extracted from all eligible studies independently by two investigators according to the inclusion criteria listed above. The following data were collected from each study: first author’s name, year of publication, country of origin, ethnicity, source of controls, genotyping method, match, sample size, and numbers of cases and controls in the PPARγ2 Pro12Ala genotypes whenever possible. Ethnicity was categorized as “Caucasian” and “Asian”. When a study did not state which ethnic groups were included or if it was impossible to separate participants according to phenotype, the sample was termed as “mixed population”. We did not define any minimum number of patients to include in this meta-analysis. Articles that reported different ethnic groups and different countries or locations, we considered them different study samples for each category cited above.

              Statistical analysis

              Crude odds ratios (ORs) together with their corresponding 95% CIs were used to assess the strength of association between the PPARγ2 Pro12Ala polymorphism and DN risk. The pooled ORs were performed for dominant comparison model (Ala-carrier vs Pro/Pro). Between-study heterogeneity was assessed by calculating Q-statistic (Heterogeneity was considered statistically significant if P < 0.10) [11] and quantified using the I 2 value, Venice criteria [12] for the I 2 test included: “I 2 < 25% represents no heterogeneity, I 2 = 25–50% represents moderate heterogeneity, I 2 = 50–75% represents large heterogeneity, and I 2 >75% represents extreme heterogeneity”. If results were not heterogeneous, the pooled ORs were calculated by the fixed-effect model (we used the Q-statistic, which represents the magnitude of heterogeneity between-studies) [13]. Otherwise, a random-effect model was used (when the heterogeneity between-studies were significant) [14]. We also performed subgroup analysis by ethnicity (Caucasian and Asian). Moreover, sensitivity analysis was performed by excluding a single study each time. In addition, we also ranked studies according to sample size, and then repeated this meta-analysis. Begg’s funnel plots [15] and Egger’s linear regression test [16] were used to assess publication bias. All of the calculations were performed using STATA version 12.0 (STATA Corporation, College Station, TX).

              Results

              Study characteristics

              Studies relevant to the searching words were retrieved originally. 18 publications addressing the association between PPARγ2 Pro12Ala polymorphism and DN risk were preliminarily eligible [8, 9, 1730]. Table 1 presents the main characteristics of these studies. There were a total of 18 studies including 8 groups of Caucasians and 10 groups of Asians. Given the low frequency of Ala allele, even in some studies, Ala homozygous individuals are absent, and only the dominant model was investigated, comparing Ala carriers to Pro/Pro. We also assessed the deviation of Hardy-Weinberg equilibrium in control subjects, and the results demonstrated that all the distribution of genotypes in the controls of all studies was in agreement with Hardy–Weinberg equilibrium.
              Table 1

              Main characteristics of these studies included in this meta-analysis

              First author

              Year

              Country

              Ethnicity

              Genotype method

              Cases

              Controls

              HWE

              Pro/ Pro

              Ala-carrier

              Pro/ Pro

              Ala-carrier

              Mori et al.

              2001

              Japanese

              Asian

              PCR-RFLP

              580

              28

              982

              42

              Yes

              Herrmann et al.

              2002

              German

              Caucasian

              PCR-RFLP

              154

              43

              144

              59

              Yes

              Caramori et al.

              2003

              Brazilian

              Caucasian

              PCR-RFLP

              93

              11

              169

              43

              Yes

              Wu et al.

              2004

              Chinese

              Asian

              PCR-RFLP

              194

              26

              102

              6

              Yes

              Maeda et al.

              2004

              Japanese

              Asian

              PCR-RFLP

              46

              15

              55

              24

              Yes

              Pollex et al.

              2007

              Canadian

              Caucasian

              PCR-RFLP

              94

              3

              55

              7

              Yes

              Erdogan et al.

              2007

              Turk

              Asian

              PCR-RFLP

              43

              0

              47

              1

              Yes

              Wei et al.

              2008

              Chinese

              Asian

              PCR-RFLP

              68

              14

              89

              10

              Yes

              Li et al.

              2008

              Chinese

              Asian

              PCR

              150

              15

              77

              17

              Yes

              Wu et al.

              2009

              Taiwanese

              Asian

              Taqman

              157

              18

              197

              17

              Yes

              De Cosmo et al.

              2009

              Italian

              Caucasian

              Taqman

              86

              7

              856

              170

              Yes

              Liu et al.

              2010

              Chinese

              Asian

              PCR-RFLP

              499

              33

              199

              29

              Yes

              Lapice et al.

              2010

              Italian

              Caucasian

              PCR-RFLP

              53

              2

              606

              89

              Yes

              Zhu et al.

              2011

              Chinese

              Asian

              PCR-RFLP

              39

              2

              33

              4

              Yes

              De Cosmo et al1

              2011

              Italian

              Caucasian

              SBE

              221

              40

              499

              81

              Yes

              De Cosmo et al2

              2011

              Italian

              Caucasian

              Taqman

              224

              30

              316

              53

              Yes

              De Cosmo et al3

              2011

              Italian

              Caucasian

              ASA

              207

              25

              422

              60

              Yes

              Zhang et al.

              2012

              Indian

              Asian

              PCR-RFLP

              113

              28

              206

              49

              Yes

              PCR-RFLP: Polymerase Chain Reaction-Restriction Fragment Length Polymorphism; PCR: Polymerase Chain Reaction; SBE: Single-Base Extension; ASA: Allele-Specific Amplification; 1,2,3: Different studies in one publication; HWE: Hardy–Weinberg Equilibrium; Yes: P HWE value>0.05.Reaction; SBE: Single-Base Extension; ASA: Allele-Specific Amplification; 1,2,3: Different studies in one publication; HWE: Hardy–Weinberg Equilibrium; Yes: P HWE value>0.05.

              Meta-analysis results

              Overall, the Pro12Ala polymorphism was found to be significantly associated with decreased risk of T2D DN (OR=0.778; 95%CI=0.618–0.981; Pheterogeneity=0.008; P=0.034) (Figure 1). Both the Cochran Q test and estimate of I 2 revealed significant heterogeneity among the constituent studies (Pheterogeneity=0.008; I 2 =50.1%). To avoid the influence of heterogeneity among the included studies, subgroup analyses were distinctively carried out according to the ethnicity. In the stratified analysis by ethnicity, significantly decreased risks were found among Caucasians for dominant model (Ala carrier vs Pro/Pro: OR=0.674; 95%CI=0.500–0.909; Pheterogeneity=0.079; P=0.010), while there was no significant association was found under the same genetic model (OR=0.917; 95%CI=0.639-1.315; Pheterogeneity=0.019; P=0.637) (Figure 2). Significant heterogeneity was found in Asian populations (Pheterogeneity=0.019; I 2 = 54.7%), but not found in Caucasian populations (Pheterogeneity=0.079; I 2 =44.9%).
              http://static-content.springer.com/image/art%3A10.1186%2F1746-1596-8-118/MediaObjects/13000_2013_806_Fig1_HTML.jpg
              Figure 1

              Forest plots of the meta-analysis for the association between PPARγ2 Pro12Ala and nephropathy in type 2 diabetes patients.

              http://static-content.springer.com/image/art%3A10.1186%2F1746-1596-8-118/MediaObjects/13000_2013_806_Fig2_HTML.jpg
              Figure 2

              Subgroup meta-analysis was held by ethnicity for the association between PPARγ2 Pro12Ala and nephropathy in type 2 diabetes patients.

              Sensitivity analysis

              To test the stability of the pooled results, one-way sensitivity analyses were performed. A single study involved in the meta-analysis was deleted each time to reflect the influence of the individual data set to the pooled ORs, no other single study influenced the pooled OR qualitatively, suggesting that the results of this meta-analysis were stable (Figure 3).
              http://static-content.springer.com/image/art%3A10.1186%2F1746-1596-8-118/MediaObjects/13000_2013_806_Fig3_HTML.jpg
              Figure 3

              One-way sensitivity analysis of the pooled ORs and 95% CI for the overall analysis, omitting each dataset in the meta-analysis.

              Publication bias

              Begg’s funnel plot and Egger’s test were performed to assess the publication bias of the literature. The shapes of the funnel plots did not reveal any evidence of obvious asymmetry (PBegg=0.472) (Figure 4). Furthermore, Egger’s test was used to provide statistical evidence for funnel plot symmetry. The results still did not suggest any evidence of publication bias (PEegger=0.234) (Figure 5).
              http://static-content.springer.com/image/art%3A10.1186%2F1746-1596-8-118/MediaObjects/13000_2013_806_Fig4_HTML.jpg
              Figure 4

              Begg funnel plot analysis to detect potential publication bias.

              http://static-content.springer.com/image/art%3A10.1186%2F1746-1596-8-118/MediaObjects/13000_2013_806_Fig5_HTML.jpg
              Figure 5

              Egger’s test was held to detect potential publication bias.

              Discussion

              It is well recognized that there is individual susceptibility to the DN even with the same environmental exposure. Host factors, including polymorphisms of genes involved in this formation of DN may have accounted for this difference. Therefore, genetic susceptibility to DN has been a research focus in scientific community. Recently, genetic polymorphisms of the PPARγ2 Pro12Ala gene in the etiology of DN have drawn increasing attention. Previous results of the studies on the relationship between PPARγ2 Pro12Ala polymorphisms and DN risk were contradictory. These inconsistent results are possibly because of a small effect of the polymorphism on DN risk or the relatively low statistical power of the published studies. A meta-analysis is a powerful strategy because it potentially investigates a large number of individuals and can estimate the effect of a genetic factor on the risk of the disease [3135]. To better understanding of this association, a pooled analysis with a large sample, subgroup analysis performed, and heterogeneity explored is necessary to provide a quantitative approach for combining the results of various studies with the same topic, and for estimating the real association in this meta-analysis.

              The present study including 3,361 cases and 5,815 controls from 18 published case–control studies, explored the association between a potentially functional polymorphism, PPARγ2 Pro12Ala and T2D DN risk. We found that there was evidence that the variant genotypes of the PPARγ2 were associated with a significant decreased overall risk of DN. When stratified by ethnicity, Caucasians with the Ala carrier showed a decreased risk of DN compared with those with the Pro/Pro genotype. However, Asians did not show the same results.

              Some limitations of this meta-analysis should be mentioned. Firstly, bladder cancer is a multifactorial disease that results from complex interactions between many environmental and genetic factors. This means that there will not be single gene or single environmental factor that has large effects on DN susceptibility. Our results were based on unadjusted estimates, while a more precise analysis should be conducted if individual data were available, which would allow for the adjustment by other covariates including age, sex, family history, environmental factors and lifestyle. Secondly, the number of subjects was relatively small, not having enough statistical power to explore the real association. Thirdly, the controls were not uniformly defined. Finally, there were only two ethnic decent populations. So, further large and well-designed studies are needed to confirm this conclusion.

              Conclusion

              This meta-analysis suggests that the PPARγ2 Pro12Ala polymorphism is not a risk factor for developing T2D DN. Moreover, gene–gene and gene–environment interactions should also be considered in future analysis. Such studies taking these factors into account may eventually lead to our better, comprehensive understanding of the association between the PPARγ2 Pro12Ala polymorphism and T2D DN risk.

              Abbreviations

              DN: 

              Diabetic nephropathy

              HWE: 

              Hardy–Weinberg equilibrium

              OR: 

              Odds ratio

              CI: 

              Confidence interval

              PPARγ2: 

              Peroxisome proliferator-activated receptor­γ2 gene.

              Declarations

              Acknowledgements

              This work was not supported by any kind of fund.

              Authors’ Affiliations

              (1)
              Department of Gerontology and Geriatrics, the First Hospital of China Medical University
              (2)
              Department of Medical Oncology, the First Hospital of China Medical University
              (3)
              Department of Pharmacy, the First Hospital of China Medical University
              (4)
              Department of Endocrinology and Metabolism, the First Hospital of China Medical University

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              Copyright

              © Wang et al.; licensee BioMed Central Ltd. 2013

              This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://​creativecommons.​org/​licenses/​by/​2.​0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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