Objective: To assess the casual effect of childhood obesity on adulthood coronary artery disease (CAD) using Mendelian randomization (MR) method. Methods: Data on BMI of children aged 2-10 years in 2015 were downloaded from Early Growth Genetics Consortium and Genetic Investigation of Anthropometric Traits Consortium. Twenty-seven genetic variants related to children’s BMI were selected as instrumental variables (IVs), and the associations between IVs and CAD were extracted from a Meta-analysis of the genome-wide association study of CAD cases published in UK Biobank 2015. We used MR-Egger regression to test whether there was the pleiotropy of the selected SNPs. In the present MR methods, we conducted MR analyses by using mode-based estimate method as primary method for summary-level of associations to estimate the causal association between childhood obesity and CAD. Results: The intercept term estimated for CAD from MR-Egger method suggested that the selected SNPs don’t exert pleiotropy with a 95%CI including the null (-0.008-0.018). In addition, we found evidence that support the effect of childhood obesity on CAD risk: a 1 s increase in children BMI (kg/m²), and the risk of suffering from CAD in adulthood increased by an average of 37% (OR=1.37, 95%CI: 1.09-1.72). Conclusion This study provides a causal association between childhood obesity and CAD risk.

Objective:To understand the causal relationship between sleep and coronary artery disease (CAD).Methods:This study included six genome-wide association parts; five for sleep related traits[sleep duration (continuous variable), long sleep duration (binary variable), short sleep duration (binary variable), early-to-bed/up habit (known as 'morningness’) and frequently insomnia] and one for CAD. Heterogeneity in dependent instrument approach was used to assess and to remove the pleiotropic instruments. Generalized summary data-based Mendelian randomization was performed to estimate the causal relationships between sleep related traits and CAD. And a conservative Bonferroni was used for statistical tests.Results:Sleep duration was putatively causal for CAD ( OR=0.755, 95 %CI: 0.658-0.867, P=6.68E-05). Our results also indicated significant causal effects between both short sleep duration and frequently insomnia on CAD, with ORs as 4.251 (95 %CI: 2.396-7.541, P=7.51E-07) and 1.814 (95 %CI: 1.346-2.446, P=9.25E-05), respectively. There was no convincing evidence of causality between long sleep duration or morningness with CAD. Conclusions:Our findings suggested that both sleep duration and frequently insomnia played causal roles on CAD, indicating that disease models should include sleep duration and insomnia as potential factors for CAD to develop effective interventions.