Genome-wide interaction study of single-nucleotide polymorphisms and alcohol consumption on blood pressure: The Ansan and Ansung study of the Korean Genome and Epidemiology Study (KoGES)

The association between dietary sodium intake and osteoporosis

The association of inadequate dietary sodium intake with bone mineral density (BMD) and the risk of osteoporosis is controversial. To find the association between low sodium diet and the risk of incipient osteoporosis, we performed a population-based cross-sectional analysis using Tanaka method for estimation 24-h urinary sodium excretion (e24hUNaETanaka) as a candidate indicator of sodium intake. We identified 3869 participants without osteoporosis and classified them into quartiles according to their value of e24hUNaETanaka. BMD was measured to find participants at risk of osteoporosis. Lower e24hUNaETanaka was related to decreasing BMD of the distal radius. Multiple Cox-proportional hazard models demonstrated that e24hUNaETanaka had an inverse association with the risk of osteoporosis (adjusted HR = 0.859, 95% CI = 0.751-0.982) and survival analysis revealed that the lowest quartile group had poor osteoporosis-free survival (PLog-rank < 0.0001). Furthermore, our restricted cubic spline analysis revealed that the relationship between e24hUNaETanaka and HR of osteoporosis was negative curvilinear in males and postmenopausal females and positive linear in premenopausal females. Our findings suggest that lower sodium intake was a significant predictor of incipient osteoporosis and there was wide variation in this relationship according to sex and female hormone status.

Variation in Genotype and DNA Methylation Patterns Based on Alcohol Use and CVD in the Korean Genome and Epidemiology Study (KoGES)

Alcohol consumption can increase the risk of chronic diseases, such as myocardial infarction, coronary artery disease, hyperlipidemia, and hypertension. We aimed to assess the association between genotype, DNA methylation patterns, alcohol consumption, and chronic diseases in Korean population. We analyzed 8840 subjects for genotypes and 446 for DNA methylation among the 9351 subjects from the Korean Genome and Epidemiology Study (KoGES). We further divided both groups into two sub-groups according to the presence/absence of chronic diseases. We selected genes whose methylation varied significantly with alcohol consumption, and visualized genotype and DNA methylation patterns specific to each group. Genome-wide association study (GWAS) revealed single nucleotide polymorphisms (SNPs) rs2074356 and rs11066280 in HECT domain E3 ubiquitin protein ligase 4 (HECTD4) to be significantly associated with alcohol consumption in both the presence. The rs12229654 genotype also displayed significantly different patterns with alcohol consumption. Furthermore, we retrieved differentially methylated regions (DMRs) from four groups based on sex and chronic diseases and compared them by drinking status. In genotype analysis, cardiovascular diseases (CVDs) showed a higher proportion in drinker than in non-drinker, but not in DMR analysis. Additionally, we analyzed the enriched Gene Ontology terms and Kyoto Gene and Genome Encyclopedia (KEGG) pathways and visualized the network, heatmap, and upset plot. We show that the pattern of DNA methylation associated with CVD is strongly influenced by alcoholism. Overall, this study identified genetic and epigenetic variants influenced by alcohol consumption and chronic diseases.

The Relationship of Dietary Pattern and Genetic Risk Score with the Incidence Dyslipidemia: 14-Year Follow-Up Cohort Study

This study was conducted to investigate the relationship between dietary pattern and genetic risk score (GRS) for dyslipidemia risk among Korean adults. Hypercholesterolemia and hypertriglyceridemia defined as total cholesterol ≥240 mg/dL and triglyceride ≥200 mg/dL or use dyslipidemia medication. The GRS was calculated by summing the risk alleles of the selected seven single-nucleotide polymorphisms related to dyslipidemia. Dietary patterns were identified by principal component analysis based on the frequency of 36 food groups, "whole grain and soybean products" pattern, "meat, fish and vegetables" pattern, and "bread and noodle" pattern were identified. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using the multivariate Cox proportional hazards regression model. High intake of a "whole grain and soybean products" pattern decreased risks of hypercholesterolemia (HR: 0.82, 95% CI: 0.72-0.93, p for trend = 0.0006) and hypertriglyceridemia (HR: 0.85, 95% CI: 0.75-0.97, p for trend = 0.0344). In the highest tertile of GRS, the "whole grain and soybean products" pattern was inversely related to hypercholesterolemia risk. Therefore, for people with genotypes that can cause hypercholesterolemia, eating whole grains and soybean products may have a meaningful response, these results could be utilized for genome-based nutrition management.