4.0 Article

Interactions of Lipid Genetic Risk Scores With Estimates of Metabolic Health in a Danish Population

Journal

CIRCULATION-CARDIOVASCULAR GENETICS
Volume 8, Issue 3, Pages 465-472

Publisher

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1161/CIRCGENETICS.114.000637

Keywords

genetics; lipids; obesity; meta-analysis; life style

Funding

  1. Novo Nordisk Foundation Center for Basic Metabolic Research, an independent Research Center at the University of Copenhagen from the Novo Nordisk Foundation
  2. Danish Agency for Science, Technology and Innovation
  3. PhD School of Molecular Metabolism University of Southern Denmark
  4. Copenhagen Graduate School of Health and Medical Sciences
  5. Lundbeck Foundation
  6. NNF Center for Basic Metabolic Research [Grarup Group] Funding Source: researchfish

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Background There are several well-established lifestyle factors influencing dyslipidemia and currently; 157 genetic susceptibility loci have been reported to be associated with serum lipid levels at genome-wide statistical significance. However, the interplay between lifestyle risk factors and these susceptibility loci has not been fully elucidated. We tested whether genetic risk scores (GRS) of lipid-associated single nucleotide polymorphisms associate with fasting serum lipid traits and whether the effects are modulated by lifestyle factors or estimates of metabolic health. Methods and Results The single nucleotide polymorphisms were genotyped in 2 Danish cohorts: inter99 (n=5961) for discovery analyses and Health2006 (n=2565) for replication. On the basis of published effect sizes of single nucleotide polymorphisms associated with circulating fasting levels of total cholesterol, low-density lipoprotein-cholesterol, high-density lipoprotein-cholesterol, or triglyceride, 4 weighted GRS were constructed. In a cross-sectional design, we investigated whether the effect of these weighted GRSs on lipid levels were modulated by diet, alcohol consumption, physical activity, and smoking or the individual metabolic health status as estimated from body mass index, waist circumference, and insulin resistance assessed using homeostasis model assessment of insulin resistance. All 4 lipid weighted GRSs associated strongly with their respective trait (from P=3.3x10(-69) to P=1.1x10(-123)). We found interactions between the triglyceride weighted GRS and body mass index and waist circumference on fasting triglyceride levels in Inter99 and replicated these findings in Health2006 (P-interaction=9.8x10(-5) and 2.0x10(-5), respectively, in combined analysis). Conclusions Our findings suggest that individuals who are obese may be more susceptible to the cumulative genetic burden of triglyceride single nucleotide polymorphisms. Therefore, it is suggested that especially these genetically at-risk individuals may benefit more from targeted interventions aiming at obesity prevention.

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