Literature DB >> 25714099

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

Johanne M Justesen1, Kristine H Allin2, Camilla H Sandholt1, Anders Borglykke1, Nikolaj T Krarup1, Niels Grarup1, Allan Linneberg1, Torben Jørgensen1, Torben Hansen1, Oluf Pedersen1.   

Abstract

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.
© 2015 American Heart Association, Inc.

Entities:  

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

Mesh:

Substances:

Year:  2015        PMID: 25714099     DOI: 10.1161/CIRCGENETICS.114.000637

Source DB:  PubMed          Journal:  Circ Cardiovasc Genet        ISSN: 1942-3268


  13 in total

1.  Increasing insulin resistance accentuates the effect of triglyceride-associated loci on serum triglycerides during 5 years.

Authors:  Johanne M Justesen; Ehm A Andersson; Kristine H Allin; Camilla H Sandholt; Torben Jørgensen; Allan Linneberg; Marit E Jørgensen; Torben Hansen; Oluf Pedersen; Niels Grarup
Journal:  J Lipid Res       Date:  2016-10-24       Impact factor: 5.922

2.  Interaction of Insulin Resistance and Related Genetic Variants With Triglyceride-Associated Genetic Variants.

Authors:  Yann C Klimentidis; Amit Arora
Journal:  Circ Cardiovasc Genet       Date:  2016-02-05

3.  Adiposity and Genetic Factors in Relation to Triglycerides and Triglyceride-Rich Lipoproteins in the Women's Genome Health Study.

Authors:  Shafqat Ahmad; Samia Mora; Paul W Franks; Marju Orho-Melander; Paul M Ridker; Frank B Hu; Daniel I Chasman
Journal:  Clin Chem       Date:  2017-11-02       Impact factor: 8.327

4.  Genetic Risk and Altering Lipids With Lifestyle Changes and Metformin: Is Fate Modifiable?

Authors:  Naveen L Pereira
Journal:  Circ Cardiovasc Genet       Date:  2016-12

5.  A genome-wide search for gene-by-obesity interaction loci of dyslipidemia in Koreans shows diverse genetic risk alleles.

Authors:  Moonil Kang; Joohon Sung
Journal:  J Lipid Res       Date:  2019-10-29       Impact factor: 5.922

6.  The Contribution of Lipids to the Interindividual Response of Vitamin K Biomarkers to Vitamin K Supplementation.

Authors:  Jennifer M Kelly; Jose M Ordovas; Gregory Matuszek; Caren E Smith; Gordon S Huggins; Hassan S Dashti; Reiko Ichikawa; Sarah L Booth
Journal:  Mol Nutr Food Res       Date:  2019-10-03       Impact factor: 5.914

7.  Prediction of Blood Lipid Phenotypes Using Obesity-Related Genetic Polymorphisms and Lifestyle Data in Subjects with Excessive Body Weight.

Authors:  Omar Ramos-Lopez; Jose I Riezu-Boj; Fermin I Milagro; Marta Cuervo; Leticia Goni; J A Martinez
Journal:  Int J Genomics       Date:  2018-11-19       Impact factor: 2.326

8.  Hypertension genetic risk score is associated with burden of coronary heart disease among patients referred for coronary angiography.

Authors:  Maria Lukács Krogager; Regitze Kuhr Skals; Emil Vincent R Appel; Theresia M Schnurr; Line Engelbrechtsen; Christian Theil Have; Oluf Pedersen; Thomas Engstrøm; Dan M Roden; Gunnar Gislason; Henrik Enghusen Poulsen; Lars Køber; Steen Stender; Torben Hansen; Niels Grarup; Charlotte Andersson; Christian Torp-Pedersen; Peter E Weeke
Journal:  PLoS One       Date:  2018-12-19       Impact factor: 3.240

9.  Common variants in the hERG (KCNH2) voltage-gated potassium channel are associated with altered fasting and glucose-stimulated plasma incretin and glucagon responses.

Authors:  Line Engelbrechtsen; Yuvaraj Mahendran; Anna Jonsson; Anette Prior Gjesing; Peter E Weeke; Marit E Jørgensen; Kristine Færch; Daniel R Witte; Jens J Holst; Torben Jørgensen; Niels Grarup; Oluf Pedersen; Henrik Vestergaard; Signe Torekov; Jørgen K Kanters; Torben Hansen
Journal:  BMC Genet       Date:  2018-03-16       Impact factor: 2.797

Review 10.  Genetics of Hypertriglyceridemia.

Authors:  Jacqueline S Dron; Robert A Hegele
Journal:  Front Endocrinol (Lausanne)       Date:  2020-07-24       Impact factor: 5.555

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