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

Circ Cardiovasc Genet

From The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics (J.M.J., K.H.A., C.H.S., N.T.K., N.G., T.H., O.P.), Department of Clinical Medicine (A.L.) and Department of Public Health (T.J.), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Research Centre for Prevention and Health (A.B., A.L., T.J.) and Department of Clinical Experimental Research (A.L.), Glostrup University Hospital, Glostrup, Denmark; Department of Clinical Medicine, Faculty of Medicine, University of Aalborg, Aalborg, Denmark (T.J.); and Department of Clinical Research, Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark (T.H.).

Published: June 2015

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=3.3×10(-69) to P=1.1×10(-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)=9.8×10(-5) and 2.0×10(-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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http://dx.doi.org/10.1161/CIRCGENETICS.114.000637DOI Listing

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