4.6 Article

Exposing the Causal Effect of Body Mass Index on the Risk of Type 2 Diabetes Mellitus: A Mendelian Randomization Study

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FRONTIERS IN GENETICS
卷 10, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fgene.2019.00094

关键词

body mass index; type 2 diabetes mellitus; casual effect; Mendelian randomisation; phenotype

资金

  1. Major State Research Development Program of China [2016YFC1202302]
  2. National Natural Science Foundation of China [61871160, 61502125]
  3. Heilongjiang Postdoctoral Fund [LBH-TZ20, LBH-Z15179]
  4. China Postdoctoral Science Foundation [2018T110315, 2016M590291]

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Introduction: High body mass index (BMI) is a positive associated phenotype of type 2 diabetes mellitus (T2DM). Abundant studies have observed this from a clinical perspective. Since the rapid increase in a large number of genetic variants from the genome-wide association studies (GWAS), common SNPs of BMI and T2DM were identified as the genetic basis for understanding their associations. Currently, their causality is beginning to blur. Materials and Methods: To classify it, a Mendelian randomisation (MR), using genetic instrumental variables (IVs) to explore the causality of intermediate phenotype and disease, was utilized here to test the effect of BMI on the risk of T2DM. In this article, MR was carried out on GWAS data using 52 independent BMI SNPs as IVs. The pooled odds ratio (OR) of these SNPs was calculated using inverse-variance weighted method for the assessment of 5 kg/m(2) higher BMI on the risk of T2DM. The leave-one-out validation was conducted to identify the effect of individual SNPs. MR-Egger regression was utilized to detect potential pleiotropic bias of variants. Results: We obtained the high OR (1.470; 95% CI 1.170 to 1.847; P = 0.001), low intercept (0.004, P = 0.661), and small fluctuation of ORs {from -0.039 [(1.412 - 1.470) / 1.470)] to 0.075 [(1.568- 1.470) / 1.470)] in leave-one-out validation. Conclusion: We validate the causal effect of high BMI on the risk of T2DM. The low intercept shows no pleiotropic bias of IVs. The small alterations of ORs activated by removing individual SNPs showed no single SNP drives our estimate.

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