Background and Objectives Associations between blood lipids and risk of ischemic heart disease (IHD) have been reported in observational studies. However, due to confounding and reverse causation, observational studies are influenced by bias, thus their results show inconsistency in the effects of lipid levels on IHD. In this study, we evaluate whether lipid levels have an effect on the risk of IHD in a Korean population. Methods A 2-sample Mendelian randomization (MR) study, using the genetic variants associated with lipid levels as the instrumental variables was performed. Genetic variants significantly associated with lipid concentrations were obtained from the Korean Genome and Epidemiology Study (n=35,000), and the same variants on IHD were obtained from the Korean Cancer Prevention Study-II (n=13,855). Inverse variance weighting (IVW), weighted median, and MR-Egger approaches were used to assess the causal association between lipid levels and IHD. Radial MR methods were applied to remove outliers subject to pleiotropic bias. Results Causal association between low-density lipoprotein-cholesterol (LDL-C) and IHD was observed in the IVW method (odds ratio, 1.013; 95% confidence interval, 1.007–1.109). However, high-density lipoprotein-cholesterol (HDL-C) and triglyceride (TG) did not show causal association with IHD. In the Radial MR analysis of the relationship between HDL-C, TG and IHD, outliers were detected. Interestingly, after removing the outliers, a causal association between TG and IHD was found. Conclusions High levels LDL-C and TG were causally associated with increased IHD risk in a Korean population, these results are potentially useful as evidence of a significant causal relationship.

Background and ObjectivesWhether using both traditional risk factors and genetic variants for stroke as opposed to using either of the 2 alone improves the prediction of stroke risk remains unclear. The purpose of this study was to compare the predictability of stroke risk between models using traditional risk score (TRS) and genetic risk score (GRS).MethodsWe used a case-cohort study from the Korean Cancer Prevention Study-II (KCPS-II) Biobank (n=156,701). We genotyped 72 single nucleotide polymorphisms (SNPs) identified in genome-wide association study (GWAS) on the KCPS-II sub-cohort members and stroke cases. We calculated GRS by summing the number of risk alleles. Prediction models with or without GRS were evaluated in terms of the area under the receiver operating characteristic curve (AUROC).ResultsSixteen out of 72 SNPs identified in GWAS showed significant associations with stroke, with an odds ratio greater than 2.0. For participants aged <40 years, AUROCs for incident stroke were 0.58, 0.65, and 0.67 in models using modifiable TRS only, GRS only, and TRS plus GRS, respectively, showing that GRS only model had better prediction than TRS only. For participants aged ≥40 years, however, TRS only model had better prediction than GRS only model. Favorable levels of traditional risk were associated with significantly lower stroke risks within each genetic risk category.ConclusionsTRS and GRS were both independently associated with stroke risk. Using genetic variants in addition to traditional risk factors may be the most accurate way of predicting stroke risk, particularly in relatively younger individuals.

Background: Under the increasing socioeconomic burden caused by rapid aging and chronic diseases, this study aimed to determine the priority criteria and evaluation indicators for preventive medical services focusing on obesity and propose a direction for benefits policies. Methods: A two-round Delphi survey was conducted to select the priority criteria for determining benefits and their evaluation index. The survey interviewed 21 experts with research experience in turning preventive medical services into health insurance benefits and expanding coverage. The first survey was conducted from July 28 to August 6, while the second was conducted from August 11 to August 20 by email every seven days. Results: When determining the benefit of preventive medical services as the priority criteria, experts listed the importance of treatment effectiveness, medical significance, and cost-effectiveness. The following people were prioritized as the beneficiaries of obesity preventive medical service: adults 18 years or older with a body mass index of 30 kg/m 2 or more. The survey respondents tended to agree that education counseling on nutrition and physical activity combined with behavioral and pharmacological treatment should prioritize health insurance benefits of obesity preventive medical service. Conclusion: Focusing on the programs mentioned here, the intervention method of a multidisciplinary expert group centered on primary care, such as doctors, nurses, and nutritionists, should prioritize exercise prescriptions.