METHODS: We performed a meta-analysis of three GWAS comprising 684 patients with type 2 diabetes and 955 controls of Southern Han Chinese descent. We followed up the top signals in two independent Southern Han Chinese cohorts (totalling 10,383 cases and 6,974 controls), and performed in silico replication in multiple populations.
RESULTS: We identified CDKN2A/B and four novel type 2 diabetes association signals with p
OBJECTIVE: We examined whether adipocytokines might explain the ethnic differences in the relationship between obesity and insulin resistance among the three major ethnic groups in Singapore.
DESIGN AND PARTICIPANTS: This was a cross-sectional study of 101 Chinese, 82 Malays, and 81 South Asian men. Insulin sensitivity index (ISI) was measured using hyperinsulinemic euglycemic clamp. Visceral (VAT) and subcutaneous adipose tissue (SAT) volumes were quantified using magnetic resonance imaging.
MAIN OUTCOME MEASURES: Plasma total and high-molecular-weight adiponectin, leptin, visfatin, apelin, IL-6, fibroblast growth factor 21 (FGF21), retinol binding protein-4 (RBP 4), and resistin were measured using enzyme-linked immunoassays.
RESULTS: Principle component (PC) analysis on the adipocytokines identified three PCs, which explained 49.5% of the total variance. Adiponectin loaded negatively, and leptin and FGF21 loaded positively onto PC1. Visfatin, resistin, and apelin all loaded positively onto PC2. IL-6 loaded positively and RBP-4 negatively onto PC3. Only PC1 was negatively associated with ISI in all ethnic groups. In the path analysis, SAT and VAT were negatively associated with ISI in Chinese and Malays without significant mediatory role of PC1. In South Asians, the relationship between VAT and ISI was mediated partly through PC1, whereas the relationship between SAT and ISI was mediated mainly through PC1.
CONCLUSIONS: The relationships between abdominal obesity, adipocytokines and insulin sensitivity differ between ethnic groups. Adiponectin, leptin, and FGF21 play a mediating role in the relationship between abdominal adiposity and insulin resistance in South Asians, but not in Malays or Chinese.
METHODS AND RESULTS: Blood pressures, fasting lipid profile and fasting glucose were measured, and DASH score was computed based on a 22-item food frequency questionnaire. Older individuals, women, those not consuming alcohol and those undertaking regular physical activity were more likely to have higher DASH scores. In the Malaysian cohort, while total DASH score was not significantly associated with cardio-metabolic risk factors after adjusting for confounders, significant associations were observed for intake of green vegetable [0.011, standard error (SE): 0.004], and red and processed meat (-0.009, SE: 0.004) with total cholesterol. In the Philippines cohort, a 5-unit increase in total DASH score was significantly and inversely associated with systolic blood pressure (-1.41, SE: 0.40), diastolic blood pressure (-1.09, SE: 0.28), total cholesterol (-0.015, SE: 0.005), low-density lipoprotein cholesterol (-0.025, SE: 0.008), and triglyceride (-0.034, SE: 0.012) after adjusting for socio-demographic and lifestyle groups. Intake of milk and dairy products, red and processed meat, and sugared drinks were found to significantly associated with most risk factors.
CONCLUSIONS: Differential associations of DASH diet and dietary components with cardio-metabolic risk factors by country suggest the need for country-specific tailoring of dietary interventions to improve cardio-metabolic risk profiles.