Dietary patterns derived from principal component- and k-means cluster analysis: Long-term association with coronary heart disease and stroke
BACKGROUND AND AIMS: Studies comparing dietary patterns derived from different a posteriori methods in view of predicting disease risk are scarce. We aimed to explore differences between dietary patterns derived from principal component- (PCA) and k-means cluster analysis (KCA) in relation to their food group composition and ability to predict CHD and stroke risk. METHODS AND RESULTS: The study was conducted in the EPIC-NL cohort that consists of 40,011 men and women. Baseline dietary intake was measured using a validated food-frequency questionnaire. Food items were consolidated into 31 food groups. Occurrence of CHD and stroke was assessed through linkage with registries. After 13 years of follow-up, 1,843 CHD and 588 stroke cases were documented. Both PCA and KCA extracted a prudent pattern (high intakes of fish, high-fiber products, raw vegetables, wine) and a western pattern (high consumption of French fries, fast food, low-fiber products, other alcoholic drinks, soft drinks with sugar) with small variation between components and clusters. The prudent component was associated with a reduced risk of CHD (HR for extreme quartiles: 0.87; 95%-CI: 0.75-1.00) and stroke (0.68; 0.53-0.88). The western component was not related to any outcome. The prudent cluster was related with a lower risk of CHD (0.91; 0.82-1.00) and stroke (0.79; 0.67-0.94) compared to the western cluster. CONCLUSION: PCA and KCA found similar underlying patterns with comparable associations with CHD and stroke risk. A prudent pattern reduced the risk of CHD and stroke.
Available from: Thomas Illig
- "Using a targeted metabolomics approach we analysed the correlation between metabolite serum levels using the Biocrates Absolute-IDQ TM Kit p150 and the above five dietary patterns in 892–965 individuals. These patterns essentially cover all relevant dietary intake information available in the FFQs and are broadly comparable to those reported in a number of large-scale populationbased studies of nutrition (Stricker et al. 2012; Schulze et al. 2001; Adebamowo et al. 2005; Ouderaa et al. 2006). "
[Show abstract] [Hide abstract]
ABSTRACT: Nutrition plays an important role in human metabolism and health. Metabolomics is a promising tool for clinical, genetic and nutritional studies. A key question is to what extent metabolomic profiles reflect nutritional patterns in an epidemiological setting. We assessed the relationship between metabolomic profiles and nutritional intake in women from a large cross-sectional community study. Food frequency questionnaires (FFQs) were applied to 1,003 women from the TwinsUK cohort with targeted metabolomic analyses of serum samples using the Biocrates Absolute-IDQ™ Kit p150 (163 metabolites). We analyzed seven nutritional parameters: coffee intake, garlic intake and nutritional scores derived from the FFQs summarizing fruit and vegetable intake, alcohol intake, meat intake, hypo-caloric dieting and a “traditional English” diet. We studied the correlation between metabolite levels and dietary intake patterns in the larger population and identified for each trait between 14 and 20 independent monozygotic twins pairs discordant for nutritional intake and replicated results in this set. Results from both analyses were then meta-analyzed. For the metabolites associated with nutritional patterns, we calculated heritability using structural equation modelling. 42 metabolite nutrient intake associations were statistically significant in the discovery samples (Bonferroni P < 4 × 10−5) and 11 metabolite nutrient intake associations remained significant after validation. We found the strongest associations for fruit and vegetables intake and a glycerophospholipid (Phosphatidylcholine diacyl C38:6, P = 1.39 × 10−9) and a sphingolipid (Sphingomyeline C26:1, P = 6.95 × 10−13). We also found significant associations for coffee (confirming a previous association with C10 reported in an independent study), garlic intake and hypo-caloric dieting. Using the twin study design we find that two thirds the metabolites associated with nutritional patterns have a significant genetic contribution, and the remaining third are solely environmentally determined. Our data confirm the value of metabolomic studies for nutritional epidemiologic research.
Electronic supplementary material
The online version of this article (doi:10.1007/s11306-012-0469-6) contains supplementary material, which is available to authorized users.
Available from: Christian Herder
[Show abstract] [Hide abstract]
ABSTRACT: Type 2 diabetes (T2D) can be prevented in pre-diabetic individuals with impaired glucose tolerance (IGT). Here, we have used a metabolomics approach to identify candidate biomarkers of pre-diabetes. We quantified 140 metabolites for 4297 fasting serum samples in the population-based Cooperative Health Research in the Region of Augsburg (KORA) cohort. Our study revealed significant metabolic variation in pre-diabetic individuals that are distinct from known diabetes risk indicators, such as glycosylated hemoglobin levels, fasting glucose and insulin. We identified three metabolites (glycine, lysophosphatidylcholine (LPC) (18:2) and acetylcarnitine) that had significantly altered levels in IGT individuals as compared to those with normal glucose tolerance, with P-values ranging from 2.4 × 10(-4) to 2.1 × 10(-13). Lower levels of glycine and LPC were found to be predictors not only for IGT but also for T2D, and were independently confirmed in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort. Using metabolite-protein network analysis, we identified seven T2D-related genes that are associated with these three IGT-specific metabolites by multiple interactions with four enzymes. The expression levels of these enzymes correlate with changes in the metabolite concentrations linked to diabetes. Our results may help developing novel strategies to prevent T2D.
Available from: Claire Mc Evoy
[Show abstract] [Hide abstract]
ABSTRACT: Cardiovascular disease (CVD) is a major cause of morbidity and mortality in the Western world in older people. Diet and lifestyle change can reduce CVD risk in older people, and this evidence base is reviewed. For example, diets low in trans fats can reduce CVD risk, while for saturated fats the CVD-lowering effect depends on what is substituted for the saturated fat. Diets rich in fish reduce CVD risk, although n-3 supplements have not been shown to have a consistent effect on CVD end-points. Antioxidant and B-group vitamin supplementation are unlikely to reduce CVD risk, but diets rich in these micronutrients (e.g. rich in fruits and vegetables and the Mediterranean diet) are associated with lower CVD risk, while, for the Mediterranean diet, this has been supported by randomized controlled trials. Maintaining a healthy weight and being physically active reduce CVD risk factors and CVD incidence and mortality.
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.