4.6 Review

Association Between Insulin-like Growth Factor-1 rs35767 Polymorphism and Type 2 Diabetes Mellitus Susceptibility: A Meta-Analysis

Journal

FRONTIERS IN GENETICS
Volume 12, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fgene.2021.774489

Keywords

type 2 diabete mellitus; insulin-like growth factor-1; rs35767; susceptibility; meta-analysis

Funding

  1. National Natural Science Foundation of China [81873649]
  2. Doctoral scientific research Initiate funding project of Shunde Women and Children's Hospital of Guangdong Medical University (Maternity and Child Healthcare Hospital of Shunde Foshan) [2020BSQD007]
  3. Guangdong Medical University Research Foundation [GDMUM2020008, GDMUM2020012]
  4. Medical Research Project of Foshan Health Bureau [20210188, 20210289]

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The meta-analysis revealed a significant association between IGF-1 rs35767 and an increased risk of type 2 diabetes (T2DM) in various genetic models, especially in homozygote comparisons and after excluding the study by Gouda et al. Additionally, the gene also increased the risk of T2DM in the Uyghur population subgroup. However, overall, there was not enough evidence to suggest a statistically significant association between the rs35767 SNP and type 2 diabetes.
Background: Insulin-like growth factor-1 (IGF-1) has been demonstrated to increase fatty acid beta 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: I-2 = 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.

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