Research Paper Volume 12, Issue 3 pp 2584—2594
LDL-C plays a causal role on T2DM: a Mendelian randomization analysis
- 1 Department of Radiology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
- 2 Cardiovascular Department, The First Affiliated Hospital of Harbin Medical University, Harbin, China
- 3 College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
- 4 Department of Information Engineering, Heilongjiang Biological Science and Technology Career Academy, Harbin, China
- 5 Department of General Surgery, Heilongjiang Province Land Reclamation Headquarters General Hospital, Harbin, China
- 6 Cardiovascular Department, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China
received: August 26, 2019 ; accepted: January 12, 2020 ; published: February 10, 2020 ;https://doi.org/10.18632/aging.102763
How to Cite
Copyright © 2020 Pan et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Diabetic dyslipidemia is a common condition in patients with Type 2 diabetes mellitus (T2DM). However, with the increasing application of statins which mainly decrease low-density lipoprotein cholesterol (LDL-C) levels, clinical trials and meta-analysis showed a clearly increase of the incidence of new-onset DMs, partly due to genetic factors. To determine whether a causal relationship exists between LDL-C and T2DM, we conducted a two-sample Mendelian Randomization (MR) analysis using genetic variations as instrumental variables (IVs). Initially, 29 SNPs significantly related to LDL-C (P≤ 5.0×10-8) were selected as based on results from the study of Henry et al, which processed loci data influencing lipids identified by the Global Lipids Genetics Consortium (GLGC) from 188,577 individuals of European ancestry. While 6 SNPs related to T2DM (P value < 5×10-2) were deleted, with the remaining 23 SNPs without LD eventually being deemed as IVs. The combined effect of all these 23 SNPs on T2DM, as generated with use of the penalized robust inverse-variance weighted (IVW) method (Beta value 0.24, 95%CI 0.087~0.393, P-value=0.002) demonstrated that elevated LDL-C levels significantly increased the risk of T2DM. The relationship between LDL-C and Type 1 diabetes mellitus (T1DM) with this analysis producing negative pooled results (Beta value -0.202, 95%CI -2.888~2.484, P-value=0.883).