Study population
This study evaluated participants included in a rural-based, cardiovascular disease association study (CAVAS) among individuals of the Korean Genome Epidemiology Study (KoGES) conducted by the Korea Centers for Disease Control and Prevention. The CAVAS study covered the years 2005–2011 and recruited men and women aged 40–69 years living in 11 rural areas. A total of 28,338 people were recruited. Among them, 20,701 were surveyed for both epidemiological and genomic data. In this study, individuals who lacked information on systolic blood pressure (SBP), diastolic blood pressure (DBP), or LDL-C (n = 49) and those with triglycerides levels greater than 400 mg/dL were excluded (n = 472) [18]. Except for 644 subjects currently undergoing treatment for hyperlipidemia, a total of 19,536 subjects were analyzed in this study (Fig. 1). The study protocol was approved by the Institutional Review Board of Wonju Severance Christian Hospital (CR317334).
Data collection
Study participants were asked to complete self-reported questionnaires in order to assess their personal and family medical histories, smoking habits, alcohol consumption, exercise status, and use of medication. Smoking status and drinking status were categorized as never, past, or current. Height, body weight, and waist circumference were measured using standard methods. Waist circumference was measured at the narrowest point between the upper iliac crest and the lowest rib after normal expiration. Blood pressure was measured by averaging three recordings taken in the morning after at least 10 min of rest in a sitting position. Laboratory samples were obtained after a 12-h fast. Plasma total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-C), creatinine, and alanine and aspartate aminotransferase levels were measured using a Hitachi 747 chemistry analyzer (Hitachi Ltd., Tokyo, Japan). LDL-C was assessed using the Friedewald equation. Nutrition was examined using data extracted from the Korea Health and Nutrition Examination Survey on multi-frequency foods in 1988 considering the contributions of each of the 17 major nutrients.
Gene data source
Genetic data were gleaned from next-generation sequencing and SNP information contained in K-CHIP (Center for Genetic Studies, Genome Center, Korea National Institute for Disease Control and Prevention). The K-CHIP comprises 830,000 representative SNPs in the Korean genome extracted from next-generation sequencing of more than 2000 Asian genomes and 1000 Korean genomes. Currently, K-CHIP covers about 95% of SNPs, with a genome representation of 5% or more [19].
Hypertension and LDL-C
Hypertension was defined in accordance with the Korean Society of Hypertension 2018 treatment guidelines [20]: 1) SBP ≥ 140 mmHg, 2) DBP ≥ 90 mmHg, or 3) currently undergoing treatment for hypertension. LDL-C was categorized as optimal (< 100 mmHg), near optimal (100–219 mmHg), borderline high (130–159 mmHg), high (160–189 mmHg), and very high (≥ 190 mmHg) as indicated by the National Cholesterol Education Program Adult Treatment Panel III. In the present study, LDL-C was analyzed as optimal (< 100 mmHg), near optimal (100–219 mmHg), and high (≥ 130 mmHg).
Gene selection (genotype)
Genes related to LDL-C was selected with reference to the Global Lipids Genetics Consortium (GLGC). Based on genome-wide association study results, we selected genes with p-values < 5 × 10− 8 for association between SNPs and LDL-C and with low linkage disequilibrium. Of these, haplotypes were excluded. In total, 24 SNPs were selected for analysis.
Statistical analysis
To analyze differences in the general characteristics of the study subjects according to the presence of hypertension, t-test was used for continuous variables, and chi-square test was used for categorical variables.
Three analytical methods were used to confirm the relationship between LDL cholesterol and hypertension. In the first method, logistic regression analysis was performed to confirm relationships noted in observational study analysis. The second and third methods implemented Mendelian randomization for two-stage least square regression using counted genetic risk scores and weighted genetic risk scores, respectively. In total, three models were developed: model 1 was unadjusted; model 2 was adjusted for age, family history of hypertension, and body mass index; and model 3 was adjusted for the same covariates in model 2 in addition to smoking status, drinking status, and salt intake.
Before implementing MRA, three basic assumptions were proposed: Assumption 1 assumed that the instrumental variable would be associated with the exposure of interest. Assumption 2 assumed that the instrumental variable is dependent on factors confounding the association between exposure and the outcome. Assumption 3 assumed that the instrumental variable is only associated with the outcome through the exposure.
Assumption 1 was confirmed through F-statistics and indicated that SNPs identified by consortium were associated with LDL-C. Only SNPs with p-values < 5 × 10− 8 were considered for analysis and confirmed LDL-C according to genotype through Cuzick’s test. In addition, genetic risk scores (GRSs) were calculated for the SNPs satisfying the assumption, and linear relationships for counted GRSs and weighted GRSs with LDL-C were confirmed. Assumption 2 indirectly confirmed that the two relationships were independent by identifying differences from confounding factors according to genotypes of each SNP because direct proof was impossible. Finally, assumption 3 was confirmed using the Durbin-Wu-Hausman test and Sargan test.
All analyses were conducted using SAS version 9.4 (SAS Institute Inc., Cary, NC, USA), R version 3.3.1. and STATA. p-values < 0.05 were considered indicative of statistical significance.