BACKGROUND/OBJECTIVES Habitual coffee consumption was inversely associated with type 2 diabetes (T2D) and hyperglycemia in observational studies, but the causality of the association remains uncertain. This study tested a causal association of genetically predicted coffee consumption with T2D using the Mendelian randomization (MR) method. SUBJECTS/METHODS We used five single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs) associated with habitual coffee consumption in a previous genome-wide association study among Koreans. We analyzed the associations between IVs and T2D, fasting blood glucose (FBG), 2h-postprandial glucose (2h-PG), and glycated haemoglobin (HbA1C) levels. The MR results were further evaluated by standard sensitivity tests for possible pleiotropism. RESULTS MR analysis revealed that increased genetically predicted coffee consumption was associated with a reduced prevalence of T2D; ORs per one-unit increment of log-transformed cup per day of coffee consumption ranged from 0.75 (0.62–0.90) for the weighted mode-based method to 0.79 (0.62–0.99) for Wald ratio estimator. We also used the inverse-variance-weighted method, weighted median-based method, MR-Egger method, and MR-PRESSO method. Similarly, genetically predicted coffee consumption was inversely associated with FBG and 2h-PG levels but not with HbA1c. Sensitivity measures gave similar results without evidence of pleiotropy. CONCLUSIONS A genetic predisposition to habitual coffee consumption was inversely associated with T2D prevalence and lower levels of FBG and 2h-PG profiles. Our study warrants further exploration.
Background The role of lipid metabolism in obesity and cancer manifestations cannot be underestimated, but whether alterations in lipid metabolism can manipulate the vasculature to promote obesity among breast cancer (BC) survivors is yet to be clearly understood. This study quantified plasma lipid and particle sizes using high-throughput proton (1H) nuclear magnetic resonance (NMR) and tested their associations with obesity among breast cancer (BC) survivors. Methods A total of 348 (225 premenopausal and 123 postmenopausal) BC survivors enrolled from five hospitals in Korea were included. We assessed thirty-four plasma lipid biomarkers using 1H NMR, and obesity status was defined as a body mass index (BMI) of 25 kg/m2 or greater. Generalized linear and logistic regression models were applied to estimate the least-square means of BMI (kg/m2) and odds ratio (OR)s of obesity, respectively, and the corresponding 95% confidence interval (CI)s across plasma lipid levels. Results Mean (SD) values of BMI was 23.3 (3.2) kg/m2 and 90 (25.9%) had BMI of ≥ 25 kg/m2. BMI levels increased with increasing total triglycerides (TG), TG in lipoproteins and very-low-density lipoprotein (VLDL) subfractions. However, BMI levels decreased with increasing tertiles of high-density lipoprotein (HDL)-cholesterol (C) and HDL particle size (HDL-p). Similar associations were observed in the logistic regression models. The increasing and decreasing BMI trends with TG and HDL profiles respectively were predominantly limited to premenopausal BC survivors. Conclusions Increasing levels of plasma total TG and TG in lipoproteins were associated with increasing levels of BMI among premenopausal BC survivors. High HDL-C levels and large HDL-p were inversely associated with obesity among premenopausal BC survivors. Due to the cross-sectional design of this study, longitudinal studies are necessary to examine the association between obesity and lipid profile among BC survivors.
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