OBJECTIVE: We aimed to identify a posteriori dietary patterns for Chinese, Malay, and Indian ethnic groups in an urban Asian setting, compare these with a priori dietary patterns, and ascertain associations with cardiovascular disease risk factors including hypertension, obesity, and abnormal blood lipid concentrations.
METHODS: We used cross-sectional data from 8433 Singapore residents (aged 21-94 y) from the Multi-Ethnic Cohort study of Chinese, Malay, and Indian ethnicity. Food consumption was assessed using a validated 169-item food-frequency questionnaire. With the use of 28 food groups, dietary patterns were derived by principal component analysis, and their association with cardiovascular disease risk factors was assessed using multiple linear regression. Associations between derived patterns and a priori patterns (aHEI-2010-Alternative Healthy Eating Index-2010, aMED-alternate Mediterranean Diet, and DASH-Dietary Approaches to Stop Hypertension) were assessed, and the magnitude of associations with risk factors compared.
RESULTS: We identified a "healthy" dietary pattern, similar across ethnic groups, and characterized by high intakes of whole grains, fruit, dairy, vegetables, and unsaturated cooking oil and low intakes of Western fast foods, sugar-sweetened beverages, poultry, processed meat, and flavored rice. This "healthy" pattern was inversely associated with body mass index (BMI; in kg/m2) (-0.26 per 1 SD of the pattern score; 95% CI: -0.36, -0.16), waist circumference (-0.57 cm; 95% CI: -0.82, -0.32), total cholesterol (-0.070 mmol/L; 95% CI: -0.091, -0.048), LDL cholesterol (-0.054 mmol/L; 95% CI: -0.074, -0.035), and fasting triglycerides (-0.22 mmol/L; 95% CI: -0.04, -0.004) and directly associated with HDL cholesterol (0.013 mmol/L; 95% CI: 0.006, 0.021). Generally, "healthy" pattern associations were at least as strong as a priori pattern associations with cardiovascular disease risk factors.
CONCLUSION: A healthful dietary pattern that correlated well with a priori patterns and was associated with lower BMI, serum LDL cholesterol, total cholesterol, and fasting triglyceride concentrations was identified across 3 major Asian ethnic groups.
SUBJECTS/METHODS: Thirty metabolic syndrome subjects (15 men and 15 women) were recruited to a randomized, double-blinded and crossover study. The subjects were administered a single dose of 200 mg or 400 mg γδ-T3 emulsions or placebo incorporated into a glass of strawberry-flavored milkshake, consumed together with a high-fat muffin. Blood samples were collected at 0, 5, 15, 30, 60, 90, 120, 180, 240, 300 and 360 min after meal intake.
RESULTS: Plasma vitamin E levels reflected the absorption of γδ-T3 after treatments. Postprandial changes in serum C-peptide, serum insulin, plasma glucose, triacylglycerol, non-esterified fatty acid and adiponectin did not differ between treatments, with women displaying delayed increase in the aforementioned markers. No significant difference between treatments was observed for plasma cytokines (interleukin-1 beta, interleukin-6 and tumor necrosis factor alpha) and thrombogenic markers (plasminogen activator inhibitor type 1 and D-dimer).
CONCLUSIONS: Supplementation of a single dose of γδ-T3 did not change the insulinemic, anti-inflammatory and anti-thrombogenic responses in metabolic syndrome subjects.
METHODS: In this study, anti-diabetic effect of ML extract is investigated in vivo to evaluate the biochemical changes, potential serum biomarkers and alterations in metabolic pathways pertaining to the treatment of HFD/STZ induced diabetic rats with ML extract using 1H NMR based metabolomics approach. Type 2 diabetic rats were treated with different doses (200 and 400 mg/kg BW) of Melicope lunu-ankenda leaf extract for 8 weeks, and serum samples were examined for clinical biochemistry. The metabolomics study of serum was also carried out using 1H NMR spectroscopy in combination with multivariate data analysis to explore differentiating serum metabolites and altered metabolic pathways.
RESULTS: The ML leaf extract (400 mg/kg BW) treatment significantly increased insulin level and insulin sensitivity of obese diabetic rats, with concomitant decrease in glucose level and insulin resistance. Significant reduction in total triglyceride, cholesterol and low density lipoprotein was also observed after treatment. Interestingly, there was a significant increase in high density lipoprotein of the treated rats. A decrease in renal injury markers and activities of liver enzymes was also observed. Moreover, metabolomics studies clearly demonstrated that, ML extract significantly ameliorated the disturbance in glucose metabolism, tricarboxylic acid cycle, lipid metabolism, and amino acid metabolism.
CONCLUSION: ML leaf extract exhibits potent antidiabetic properties, hence could be a useful and affordable alternative option for the management of T2DM.
METHODS: The case-control portion of the study was conducted in nine UK centers with men ages 50-69 years who underwent prostate-specific antigen screening for prostate cancer within the Prostate Testing for Cancer and Treatment (ProtecT) trial. Two data sources were used to appraise causality: a genome-wide association study (GWAS) of metabolites in 24,925 participants and a GWAS of prostate cancer in 44,825 cases and 27,904 controls within the Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.
RESULTS: Thirty-five metabolites were strongly associated with prostate cancer (P < 0.0014, multiple-testing threshold). These fell into four classes: (i) lipids and lipoprotein subclass characteristics (total cholesterol and ratios, cholesterol esters and ratios, free cholesterol and ratios, phospholipids and ratios, and triglyceride ratios); (ii) fatty acids and ratios; (iii) amino acids; (iv) and fluid balance. Fourteen top metabolites were proxied by genetic variables, but MR indicated these were not causal.
CONCLUSIONS: We identified 35 circulating metabolites associated with prostate cancer presence, but found no evidence of causality for those 14 testable with MR. Thus, the 14 MR-tested metabolites are unlikely to be mechanistically important in prostate cancer risk.
IMPACT: The metabolome provides a promising set of biomarkers that may aid prostate cancer classification.
PATIENTS & METHODS: DPP4, WFS1 and KCNJ11 gene polymorphisms were genotyped in a cohort study of 662 T2DM patients treated with DPP-4 inhibitors sitagliptin, vildagliptin or linagliptin. Genotyping was performed by Applied Biosystems TaqMan SNP genotyping assay.
RESULTS: Patients with triglyceride levels less than 1.7 mmol/l (odds ratio [OR]: 2.2.; 95% CI: 1.031-4.723), diastolic blood pressure (DBP) less than 90 mmHg (OR: 1.7; 95% CI: 1.009-2.892) and KCNJ11 rs2285676 (genotype CC) (OR: 2.0; 95% CI: 1.025-3.767) were more likely to response to DPP-4 inhibitor treatment compared with other patients, as measured by HbA1c levels.
CONCLUSION: Triglycerides, DBP and KCNJ11 rs2285676 are predictors of the DPP-4 inhibitor treatment response in T2DM patients.