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Prediction of Blood Lipid Phenotypes Using Obesity-Related Genetic Polymorphisms and Lifestyle Data in Subjects with Excessive Body Weight
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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6276413/ https://www.ncbi.nlm.nih.gov/pubmed/30581838 http://dx.doi.org/10.1155/2018/4283078 |
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author | Ramos-Lopez, Omar Riezu-Boj, Jose I. Milagro, Fermin I. Cuervo, Marta Goni, Leticia Martinez, J. A. |
author_facet | Ramos-Lopez, Omar Riezu-Boj, Jose I. Milagro, Fermin I. Cuervo, Marta Goni, Leticia Martinez, J. A. |
author_sort | Ramos-Lopez, Omar |
collection | PubMed |
description | 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. R (2) = 0.28), 25% (optimism-corrected adj. R (2) = 0.25), 24% (optimism-corrected adj. R (2) = 0.24), and 21% (optimism-corrected adj. R (2)=0.21), respectively. Interestingly, GRS were the greatest contributors to TC (squared partial correlation (PC(2)) = 0.18) and LDL-c (PC(2) = 0.18) features. Likewise, VFAT and GRS had a higher impact on HDL-c (PC(2) = 0.09 and PC(2) = 0.06, respectively) and TG levels (PC(2) = 0.20 and PC(2) = 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. |
format | Online Article Text |
id | pubmed-6276413 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-62764132018-12-23 Prediction of Blood Lipid Phenotypes Using Obesity-Related Genetic Polymorphisms and Lifestyle Data in Subjects with Excessive Body Weight Ramos-Lopez, Omar Riezu-Boj, Jose I. Milagro, Fermin I. Cuervo, Marta Goni, Leticia Martinez, J. A. Int J Genomics Research Article 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. R (2) = 0.28), 25% (optimism-corrected adj. R (2) = 0.25), 24% (optimism-corrected adj. R (2) = 0.24), and 21% (optimism-corrected adj. R (2)=0.21), respectively. Interestingly, GRS were the greatest contributors to TC (squared partial correlation (PC(2)) = 0.18) and LDL-c (PC(2) = 0.18) features. Likewise, VFAT and GRS had a higher impact on HDL-c (PC(2) = 0.09 and PC(2) = 0.06, respectively) and TG levels (PC(2) = 0.20 and PC(2) = 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. Hindawi 2018-11-19 /pmc/articles/PMC6276413/ /pubmed/30581838 http://dx.doi.org/10.1155/2018/4283078 Text en Copyright © 2018 Omar Ramos-Lopez et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Ramos-Lopez, Omar Riezu-Boj, Jose I. Milagro, Fermin I. Cuervo, Marta Goni, Leticia Martinez, J. A. Prediction of Blood Lipid Phenotypes Using Obesity-Related Genetic Polymorphisms and Lifestyle Data in Subjects with Excessive Body Weight |
title | Prediction of Blood Lipid Phenotypes Using Obesity-Related Genetic Polymorphisms and Lifestyle Data in Subjects with Excessive Body Weight |
title_full | Prediction of Blood Lipid Phenotypes Using Obesity-Related Genetic Polymorphisms and Lifestyle Data in Subjects with Excessive Body Weight |
title_fullStr | Prediction of Blood Lipid Phenotypes Using Obesity-Related Genetic Polymorphisms and Lifestyle Data in Subjects with Excessive Body Weight |
title_full_unstemmed | Prediction of Blood Lipid Phenotypes Using Obesity-Related Genetic Polymorphisms and Lifestyle Data in Subjects with Excessive Body Weight |
title_short | Prediction of Blood Lipid Phenotypes Using Obesity-Related Genetic Polymorphisms and Lifestyle Data in Subjects with Excessive Body Weight |
title_sort | prediction of blood lipid phenotypes using obesity-related genetic polymorphisms and lifestyle data in subjects with excessive body weight |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6276413/ https://www.ncbi.nlm.nih.gov/pubmed/30581838 http://dx.doi.org/10.1155/2018/4283078 |
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