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

doi:10.1155/2018/4283078

. 2018 Nov 19:2018:4283078.

doi: 10.1155/2018/4283078. eCollection 2018.

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

Omar Ramos-Lopez¹, Jose I Riezu-Boj^{1

2}, Fermin I Milagro^{1

3}, Marta Cuervo^{1

2

3}, Leticia Goni¹, J A Martinez^{1

2

3

4}

Affiliations

¹ Department of Nutrition, Food Science and Physiology, and Center for Nutrition Research, University of Navarra, Pamplona, Spain.
² Navarra Institute for Health Research (IdiSNA), Pamplona, Spain.
³ CIBERobn, Fisiopatología de la Obesidad y la Nutrición, Carlos III Health Institute, Madrid, Spain.
⁴ Madrid Institute of Advanced Studies (IMDEA Food), Madrid, Spain.

PMID: 30581838
PMCID: PMC6276413
DOI: 10.1155/2018/4283078

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

Omar Ramos-Lopez et al. Int J Genomics. 2018.

. 2018 Nov 19:2018:4283078.

doi: 10.1155/2018/4283078. eCollection 2018.

Authors

Omar Ramos-Lopez¹, Jose I Riezu-Boj^{1

2}, Fermin I Milagro^{1

3}, Marta Cuervo^{1

2

3}, Leticia Goni¹, J A Martinez^{1

2

3

4}

Affiliations

¹ Department of Nutrition, Food Science and Physiology, and Center for Nutrition Research, University of Navarra, Pamplona, Spain.
² Navarra Institute for Health Research (IdiSNA), Pamplona, Spain.
³ CIBERobn, Fisiopatología de la Obesidad y la Nutrición, Carlos III Health Institute, Madrid, Spain.
⁴ Madrid Institute of Advanced Studies (IMDEA Food), Madrid, Spain.

PMID: 30581838
PMCID: PMC6276413
DOI: 10.1155/2018/4283078

Abstract

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 (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.

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Figures

**Figure 1**
Venn diagram showing the number of SNPs associated with blood lipid levels. TC: total cholesterol; TG: triglycerides; LDL-c: low-density lipoprotein cholesterol; HDL-c: high-density lipoprotein cholesterol.

**Figure 2**
Comparisons of average blood lipids levels between predictor categories based on the median values. Data are expressed as means ± standard errors and sorted in descending order by the effect sizes. TC: total cholesterol; LDL-c: low-density lipoprotein cholesterol; HDL-c: high-density lipoprotein cholesterol; TG: triglycerides; GRS_TC: genetic risk score for total cholesterol; GRS_LDL-c: genetic risk score for low-density lipoprotein cholesterol; GRS_HDL-c: genetic risk score for high-density lipoprotein cholesterol; GRS_TG: genetic risk score for triglycerides; TFAT: total body fat; VFAT: visceral fat; DR: drinkers; NDR: nondrinkers.

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References

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[1] AbouRjaili G., Shtaynberg N., Wetz R., Costantino T., Abela G. S. Current concepts in triglyceride metabolism, pathophysiology, and treatment. Metabolism. 2010;59(8):1210–1220. doi: 10.1016/j.metabol.2009.11.014. - DOI - PubMed

[2] AbouRjaili G., Shtaynberg N., Wetz R., Costantino T., Abela G. S. Current concepts in triglyceride metabolism, pathophysiology, and treatment. Metabolism. 2010;59(8):1210–1220. doi: 10.1016/j.metabol.2009.11.014. - DOI - PubMed

[3] Errico T. L., Chen X., Martin Campos J. M., Julve J., Escolà-Gil J. C., Blanco-Vaca F. Basic mechanisms: structure, function and metabolism of plasma lipoproteins. Clinic and Research in Arteriosclerosis. 2013;25(2):98–103. doi: 10.1016/j.arteri.2013.05.003. - DOI - PubMed

[4] Errico T. L., Chen X., Martin Campos J. M., Julve J., Escolà-Gil J. C., Blanco-Vaca F. Basic mechanisms: structure, function and metabolism of plasma lipoproteins. Clinic and Research in Arteriosclerosis. 2013;25(2):98–103. doi: 10.1016/j.arteri.2013.05.003. - DOI - PubMed

[5] Colantonio L. D., Bittner V., Reynolds K., et al. Association of serum lipids and coronary heart disease in contemporary observational studies. Circulation. 2016;133(3):256–264. doi: 10.1161/CIRCULATIONAHA.115.011646. - DOI - PMC - PubMed

[6] Colantonio L. D., Bittner V., Reynolds K., et al. Association of serum lipids and coronary heart disease in contemporary observational studies. Circulation. 2016;133(3):256–264. doi: 10.1161/CIRCULATIONAHA.115.011646. - DOI - PMC - PubMed

[7] Piepoli M. F., Hoes A. W., Agewall S., et al. 2016 European guidelines on cardiovascular disease prevention in clinical practice. Revista Española de Cardiología. 2016;69(10):p. 939. doi: 10.1016/j.rec.2016.09.009. - DOI - PubMed

[8] Piepoli M. F., Hoes A. W., Agewall S., et al. 2016 European guidelines on cardiovascular disease prevention in clinical practice. Revista Española de Cardiología. 2016;69(10):p. 939. doi: 10.1016/j.rec.2016.09.009. - DOI - PubMed

[9] Cole C. B., Nikpay M., McPherson R. Gene-environment interaction in dyslipidemia. Current Opinion in Lipidology. 2015;26(2):133–138. doi: 10.1097/MOL.0000000000000160. - DOI - PubMed

[10] Cole C. B., Nikpay M., McPherson R. Gene-environment interaction in dyslipidemia. Current Opinion in Lipidology. 2015;26(2):133–138. doi: 10.1097/MOL.0000000000000160. - DOI - PubMed

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

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

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