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Causal graph between serum lipids and glycemic traits: a Mendelian randomization study

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posted on 27.05.2022, 14:35 authored by Ziwei Zhu, Kai Wang, Xingjie Hao, Liangkai Chen, Zhonghua Liu, Chaolong Wang


We systematically investigated the bidirectional causality between high-density-lipoprotein cholesterol (HDL-C), low-density-lipoprotein cholesterol (LDL-C), triglycerides (TG), fasting insulin (FI), and glycated hemoglobin A1c (HbA1c) based on genome-wide association summary statistics of Europeans (sample size n = 1,320,016 for lipids, 151,013 for FI, and 344,182 for HbA1c). We applied multivariable Mendelian randomization (MR) to account for the correlation between different traits, and constructed a causal graph with 13 significant causal effects after adjusting for multiple testing (P < 0.05/20). Remarkably, we found the effects of lipids on glycemic traits were through FI from TG (β = 0.06 [95% CI: 0.03, 0.08] in unit of 1-SD for each trait) and HDL-C (β = -0.02 [-0.03, -0.01]). On the other hand, FI had strong a negative effect on HDL-C (β = -0.15 [-0.21, -0.09]) and positive effects on TG (β = 0.22 [0.14, 0.31]) and HbA1c (β = 0.15 [0.12, 0.19]), while HbA1c could raise LDL-C (β = 0.06 [0.03, 0.08]) and TG (β = 0.08 [0.06, 0.10]). These estimates derived from the inverse-variance weighting method were robust when using different MR methods. Our results suggested that elevated FI was a strong causal factor of high TG and low HDL-C, which in turn would further increase FI. Therefore, early control of insulin resistance is critical to reduce the risk of type 2 diabetes, dyslipidemia, and cardiovascular complications. 


This work was funded by the Natural Science Foundation of China (82021005, 81973148 and 82003561).