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Association between insulin-like growth factor-binding protein-3 polymorphism-202 A/C and the risk of prostate cancer: a meta-analysis.

ABSTRACT: BACKGROUND:Some previous studies have investigated the relationship between insulin-like growth factor-binding protein-3 polymorphism and prostate cancer (PCa) susceptibility; however, the findings from those studies remain inconsistent. Hence, the aim of this meta-analysis was to provide a more reliable conclusion about such associations. METHODS:A meta-analysis based on twelve studies was conducted, and 8,341 PCa cases and 7,734 controls were included in this analysis. All relevant studies published till February 1, 2016, were identified by searching the databases such as PubMed, EMBASE, and Web of Science. Data were pooled by odds ratios (ORs) with 95% confidence intervals (CIs) in order to assess the strength of such associations. Publication bias was evaluated using Begg's funnel plots and Egger's regression test. RESULTS:Several articles provided data only for particular genotypes; therefore, only dominant model analyses were carried out for all of these studies. Initially, the results from this analysis indicated that rs2854744 was not associated with PCa susceptibility (OR=1.12, 95% CI=0.996-1.2). However, after excluding one study due to its heterogeneity and publication bias, a significant relationship was detected between rs2854744 and PCa risk (OR=1.10, 95% CI=1.03-1.17). When stratified by genotyping method, significant results were detected only in the Sequenom method group (OR=1.13, 95% CI=1.04-1.22). Moreover, the results from a subgroup analysis that was conducted by using source of controls were significant only in the population-based control group. CONCLUSION:This meta-analysis suggested that the insulin-like growth factor-binding protein-3 polymorphism-202 A/C was associated with PCa susceptibility.

SUBMITTER: Qin Z

PROVIDER: S-EPMC5021063 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Association between insulin-like growth factor-binding protein-3 polymorphism-202 A/C and the risk of prostate cancer: a meta-analysis.

Qin Zhiqiang Z Li Xiao X Tang Jingyuan J Jiang Xuping X Yu Yajie Y Wang Chengming C Xu Weizhang W Hua Yibo Y Yu Bin B Zhang Wei W

OncoTargets and therapy 20160906

<h4>Background</h4>Some previous studies have investigated the relationship between insulin-like growth factor-binding protein-3 polymorphism and prostate cancer (PCa) susceptibility; however, the findings from those studies remain inconsistent. Hence, the aim of this meta-analysis was to provide a more reliable conclusion about such associations.<h4>Methods</h4>A meta-analysis based on twelve studies was conducted, and 8,341 PCa cases and 7,734 controls were included in this analysis. All relev ...[more]

PMID: 27660462

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Project description:Background: Insulin-like growth factor-1 (IGF-1) has been demonstrated to increase fatty acid β oxidation during fasting, and play an important role in regulating lipid metabolism and type 2 diabetes mellitus (T2DM). The rs35767 (T > C) polymorphism, a functional SNP was found in IGF-1 promoter, which may directly affect IGF-1 expression. However, the inconsistent findings showed on the IGF-1 rs35767 polymorphism and T2DM risk. Methods: We performed a comprehensive meta-analysis to estimate the association between the IGF-1 rs35767 and T2DM risk among four genetic models (the allele, additive, recessive and dominant models). Results: A total 49,587 T2DM cases and 97,906 NDM controls were included in the allele model, a total 2256 T2DM cases and 2228 NDM controls were included in the other three genetic models (the additive; recessive and dominant models). In overall analysis, the IGF-1 rs35767 was shown to be significantly associated with increased T2DM risk for the allele model (T vs. C: OR = 1.251, 95% CI: 1.082-1.447, p = 0.002), additive model (homozygote comparisons: TT vs. CC: OR = 2.433, 95% CI: 1.095-5.405, p = 0.029; heterozygote comparisons: TC vs. CC: OR = 1.623, 95% CI: 1.055-2.495, p = 0.027) and dominant model (TT + CT vs. CC: OR = 1.934, 95% CI: 1.148-3.257, p = 0.013) with random effects model. After omitting Gouda's study could reduce the heterogeneity, especially in the recessive model (TT vs. CC + CT: I2 = 38.7%, p = 0.163), the fixed effects model for recessive effect of the T allele (TT vs. CC + CT) produce results that were of borderline statistical significance (OR = 1.206, 95% CI: 1.004-1.448, p = 0.045). And increasing the risk of T2DM in Uyghur population of subgroup for the allele model. Conclusion: The initial analyses that included all studies showed statistically significant associations between the rs35767 SNP and type 2 diabetes, but after removing the Gouda et al. study produced results that were mostly not statistically significant. Therefore, there is not enough evidence from the results of the meta-analysis to indicate that the rs35767 SNP has a statistically significant association with type 2 diabetes.

Project description:ObjectiveTo explore the association between transforming growth factor-beta1 (TGF-?1) T869C polymorphism and risk of ischemic stroke (IS) by performing a meta-analysis based on published articles.MethodsSystematic electronic searches of PubMed, Science Direct, BIOSIS Previews, Chinese Biomedical Database, Chinese National Knowledge Infrastructure, and WANFANG Database were performed. The strength of the association was calculated by pooled odds ratios (ORs) with 95% confidence intervals (95%CIs). Subgroup analysis was conducted to explore potential sources of heterogeneity. Sensitivity analysis was performed to elucidate the stability of the outcomes. Publication bias was evaluated by Begg's funnel plot and Egger's test.ResultsA total of 6 studies involving 1701 cases were included. The overall estimates did not show any significant association between TGF-?1 T869C polymorphism and risk of IS under all genetic models (C vs. T: OR?=?1.08,95%CI?=?0.88-1.32; CC vs. TT:OR?=?1.17,95%CI?=?0.79-1.72; CT vs. TT: OR?=?0.91, 95%CI?=?0.68-1.22; CC+CT vs. TT: OR?=?0.99, 95%CI?=?0.73-1.35; CC vs. CT+TT: OR?=?1.23, 95%CI?=?0.95-1.59). Similar lacking associations were observed in subgroup analysis based on ethnicity and source of controls. When stratified by study design, significant increased association of IS risk was found in cohort studies under genetic models except recessive model(C vs. T: OR?=?1.18, 95%CI?=?1.05-1.32; CC vs. TT: OR?=?1.40, 95%CI?=?1.10-1.77; CT vs. TT: OR?=?1.23, 95%CI?=?1.02-1.49; CC+CT vs. TT: OR?=?1.27, 95%CI?=?1.03-1.57; CC vs. CT+TT, OR?=?1.21, 95%CI?=?0.99-1.47), whereas in case-control studies a significant decreased risk was detected under heterozygote comparison(CT vs. CC: OR?=?0.72, 95%CI?=?0.57-0.92). However, after correction for multiple testing, the associations were observed to be null significant in both cohort and case-control subgroups among all genetic models.ConclusionThis meta-analysis suggested that current epidemiological studies of TGF-?1 T869C polymorphism are too inconsistent to draw a conclusion on the association with IS susceptibility. Given the small sample size and remarkable between-study heterogeneity, further well-designed prospective large-scale studies are warranted.

Dataset Information

Association between insulin-like growth factor-binding protein-3 polymorphism-202 A/C and the risk of prostate cancer: a meta-analysis.

Publications

Association between insulin-like growth factor-binding protein-3 polymorphism-202 A/C and the risk of prostate cancer: a meta-analysis.

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