Journal Article

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

Cuervo, Marta, Martínez, J. Alfredo, Riezu-Boj, Jose I., Goni, Leticia, Milagro, Fermín I., Ramos-Lopez, Omar

2018

Overview

Background and Aim. Individual lipid phenotypes including circulating total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDL-c), and triglycerides (TG) determinations are influenced by gene-environment interactions. The aim of this study was to predict blood lipid level (TC, LDL-c, HDL-c, and TG) variability using genetic and lifestyle data in subjects with excessive body weight-for-height. Methods. This cross-sectional study enrolled 304 unrelated overweight/obese adults of self-reported European ancestry. A total of 95 single nucleotide polymorphisms (SNPs) related to obesity and weight loss were analyzed by a targeted next-generation sequencing system. Relevant genotypes of each SNP were coded as 0 (nonrisk) and 1 (risk). Four genetic risk scores (GRS) for each lipid phenotype were calculated by adding the risk genotypes. Information concerning lifestyle (diet, physical activity, alcohol drinking, and smoking) was obtained using validated questionnaires. Total body fat (TFAT) and visceral fat (VFAT) were determined by dual-energy X-ray absorptiometry. Results. Overall, 45 obesity-related genetic variants were associated with some of the studied blood lipids. In addition to conventional factors (age, sex, dietary intakes, and alcohol consumption), the calculated GRS significantly contributed to explain their corresponding plasma lipid trait. Thus, HDL-c, TG, TC, and LDL-c serum concentrations were predicted by approximately 28% (optimism-corrected adj. R2=0.28), 25% (optimism-corrected adj. R2=0.25), 24% (optimism-corrected adj. R2=0.24), and 21% (optimism-corrected adj. R2=0.21), respectively. Interestingly, GRS were the greatest contributors to TC (squared partial correlation (PC2) = 0.18) and LDL-c (PC2 = 0.18) features. Likewise, VFAT and GRS had a higher impact on HDL-c (PC2 = 0.09 and PC2 = 0.06, respectively) and TG levels (PC2 = 0.20 and PC2 = 0.07, respectively) than the rest of variables. Conclusions. Besides known lifestyle influences, some obesity-related genetic variants could help to predict blood lipid phenotypes.

• Publisher: Hindawi Publishing Corporation,Hindawi,John Wiley & Sons, Inc,Wiley
• Subject: adults / Alcohol / alcohol drinking / Alcohol use / ancestry / Blood / blood lipids / Blood pressure / blood serum / Body fat / Body height / Body weight / Body weight loss / Cardiovascular disease / Cholesterol / cross-sectional studies / Deoxyribonucleic acid / Diabetes / Dietary intake / DNA / Drinking behavior / Dual energy X-ray absorptiometry / eating habits / food intake / Genetic diversity / genetic variation / Genomes / genotype / genotype-environment interaction / Health risk assessment / High density lipoprotein / high density lipoprotein cholesterol / high-throughput nucleotide sequencing / Hypertension / lifestyle / Lifestyles / Lipids / Lipoproteins / Low density lipoprotein / low density lipoprotein cholesterol / Metabolism / Next-generation sequencing / Nutrition research / Obesity / Overweight / phenotype / Phenotypes / Physical activity / prediction / Questionnaires / risk / Single-nucleotide polymorphism / Smoking / smoking (habit) / Studies / Systematic review / triacylglycerols / Triglycerides / visceral fat / Weight control / weight loss / Womens health