Abstract
Genome-wide association studies have identified many lipid-associated loci primarily in European and Asian populations. In view of the differences between ethnic groups in terms of the frequency and impact of these variants, our objective was to evaluate the relationships between eight lipid-associated variants (considered individually and in combination) and fasting serum triglyceride, total cholesterol, HDL- and LDL-cholesterol levels in an Algerian population sample (ISOR study, n = 751). Three SNPs (in SORT1, CETP and GCKR) were individually associated with lipid level variations. Moreover, the risk allele scores for total cholesterol, triglyceride and LDL-C levels (encompassing between three and six SNPs) were associated with their corresponding lipid traits. Our study is the first to show that some of the lipid-associated loci in European populations are associated with lipid traits in Algerians. Although our results will have to be confirmed in other North African populations, this study contributes to a better understanding of genetic susceptibility to lipid traits in Algeria.
Keywords: Algeria, combined risk allele score, ISOR study, lipid, North African population, polymorphism
Introduction
Dyslipidaemia (as defined by elevated fasting and post-prandial plasma triglyceride (TG)-rich lipoproteins, low high-density lipoprotein cholesterol (HDL-C) and elevated low-density lipoprotein cholesterol (LDL-C) levels is associated with atherosclerosis [1] and coronary heart disease (CHD) [2]. The heritability estimates of lipids traits range from 34 to 53% [3]. Teslovich et al. have identified 95 lipid-associated loci in individuals of European descent [4]. When characterizing gene-disease relationships, the replication of association signals in independent populations is mandatory [5]. Replications have been investigated in various populations: Europeans [4,5], East Asians [4], Hispanics [6] and African Blacks [7,8] but never in North African samples. Moreover, the validation in different population groups is required in order to understand their wider potential for application and clinical benefits.
As each individual single nucleotide polymorphism (SNP) exerts a moderate genetic effect and thus explains a small proportion of the total lipid variation [9], combined analyses appear to be necessary and useful in moderate-size population samples.
Therefore, in the present study, we raised the following question: are lipid-associated SNPs discovered in European populations also associated with lipid traits in Algerians. Answering this question will help in determining whether lipids traits have a common pathophysiology process across different population groups.
Materials and methods
Details of the ISOR (InSulino-résistance à ORan) study have been described elsewhere [10]. The 751 subjects not treated with lipid-lowering drugs were included. All subjects gave their free, informed consent to participation. The study’s objectives and procedures were approved by the independent ethics committee. We selected the lipid-associated SNPs from a previous GWAS [4] for which we had a statistical power of more than 0.80 for at least one of the four main lipid parameters (TG, TC, HDL-C and LDL-C) in the ISOR study. The eight selected SNPs were located within or near the following genes: SORT1, GCKR, LPL, APOA1, CETP, LDLR, APOE and MLXIPL. Genotyping was performed using KASPar technology (Kbioscience, UK). The genotyping success rates ranged from 94.5% to 96.6%.
Statistical analyses were performed with SAS software (version 9.1, USA). Hardy-Weinberg equilibrium was tested using a χ2 test.
For each lipid trait we defined a risk-allele-score, an unweighted score corresponding to the sum of allele effects of the SNPs significantly associated with the corresponding trait in Teslovich’s study [4].
We determined whether each lipid variable was normally distributed before statistical analysis and logarithmic transformation was applied on skewed variables (TG). Intergroup comparisons of means were performed with a general linear model and an additive genetic model. A Pearson χ2 test was used to compare groups in terms of genotype and allele distributions. The covariates were age, gender, smoking status, physical activity and BMI. As this is a replication study, P ≤ 0.05 was used for the significance threshold [11].
The statistical power was estimated on the previously reported effect sizes and allele frequencies [4], using QUANTO software (http://hydra.usc.edu/gxe/).
Results
Characteristics of the study subjects are presented in Table S1.
As the genotyping of the MLXIP rs7811265 SNP failed, seven SNPs were considered in the following analyses. All SNPs conformed with the Hardy-Weinberg equilibrium (Table 1).
Table 1.
Associations between the seven genotyped SNPs and lipid traits in the ISOR study
| Nearby genes | Chr | SNP | EA/NEA | Genotypes | EAF ISOR study | EAF Teslovich et al. | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
|
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| 0 | 1 | 2 | Trait | β ± (SE) | p | |||||||
|
|
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| n (freq) | n (freq) | n (freq) | p HWE | |||||||||
| SORT1 | 1 | rs629301 | T/G | 41 (0.06) | 241 (0.34) | 426 (0.60) | 0.37 | 0.77 | 0.78 | TC | 0.21 (0.06) | 0.0003 |
| LDL-C | 0.21 (0.05) | 6.8×10-5 | ||||||||||
| GCKR | 2 | rs1260326 | C/T | 235 (0.33) | 346 (0.49) | 129 (0.18) | 0.93 | 0.43 | 0.41 | Ln(TG) | 0.05 (0.02) | 0.0009 |
| TC | 0.16 (0.05) | 0.0008 | ||||||||||
| LPL | 8 | rs328 | C/G | 609 (0.84) | 108 (0.15) | 5 (0.01) | 0.93 | 0.08 | 0.12 | Ln(TG) | 0.06 (0.04) | 0.08 |
| HDL-C | -0.04 (0.03) | 0.21 | ||||||||||
| APOA1 | 11 | rs964184 | C/G | 413 (0.59) | 261 (0.37) | 31 (0.04) | 0.20 | 0.23 | 0.13 | Ln(TG) | 0.03 (0.02) | 0.16 |
| TC | -0.06 (0.06) | 0.28 | ||||||||||
| HDL-C | -0.01 (0.02) | 0.67 | ||||||||||
| LDL-C | -0.09 (0.06) | 0.12 | ||||||||||
| CETP | 16 | rs3764261 | C/A | 437 (0.61) | 243 (0.34) | 42 (0.06) | 0.29 | 0.23 | 0.32 | TC | 0.07 (0.06) | 0.25 |
| HDL-C | 0.05 (0.02) | 0.003 | ||||||||||
| LDLR | 19 | rs6511720 | G/T | 18 (0.02) | 168 (0.23) | 537 (0.74) | 0.27 | 0.86 | 0.89 | TC | 0.09 (0.07) | 0.21 |
| LDL-C | 0.08 (0.06) | 0.24 | ||||||||||
| APOE | 19 | rs4420638 | A/G | 570 (0.79) | 142 (0.2) | 10 (0.01) | 0.73 | 0.11 | 0.17 | TC | 0.02 (0.08) | 0.76 |
| HDL-C | -0.01 (0.02) | 0.82 | ||||||||||
| LDL-C | -0.01 (0.07) | 0.94 | ||||||||||
EA: Effect allele, NEA: Non-effect allele, EAF: Effect allele frequency, HWE: Hardy-Weinberg equilibrium, SE: standard error. Genotypes were coded as 0/1/2, indicating the number of copies of the designated effect allele per subject. The β coefficients correspond to the effect sizes. p values were adjusted for age, gender, physical activity, smoking status and BMI. Significant p values are indicated in bold.
We found significant associations between SORT1 rs629301 and both TC (P = 0.0003) and LDL-C concentrations (P = 6.8×10-5), between GCKR rs1260326 and TG (P = 0.0009) and TC (P = 0.0008) concentrations and between CETP rs3764261 and HDL-C concentrations (P = 0.003) (Table 1).
We investigated the effects of the lipid-risk-allele-scores (stratified into tertiles and rounded to the closest integer allele) on lipid variables (Table 2). The scores included between three and six SNPs. We observed significant associations between all risk-scores and their corresponding lipid levels, except for HDL-C. For TG, TC and LDL-C, subjects in the highest tertile presented higher TG (P = 0.002), higher TC levels (P = 0.0003) and higher LDL-C levels (P = 0.02) than subjects in the lowest tertile.
Table 2.
Combined risk allele scores for lipid traits in the ISOR study
| Trait | SNPs included in the risk allele score | Tertile | N | Mean | SD | p trend | β | SE | p |
|---|---|---|---|---|---|---|---|---|---|
| TG | GCKR, LPL, APOA1 | < 3 alleles | 163 | 1.10a | 0.47 | reference | |||
| (mmol/L) | = 3 alleles | 306 | 1.11a | 0.47 | 0.001 | 0.02b | 0.04 | 0.58 | |
| > 3 alleles | 228 | 1.25a | 0.56 | 0.12b | 0.04 | 0.002 | |||
| TC | SORT1, GCKR, APOA1, CETP, LDLR, APOE | < 5 alleles | 207 | 4.29 | 0.84 | reference | |||
| (mmol/L) | = 5 alleles | 186 | 4.41 | 0.92 | 0.0003 | 0.14 | 0.09 | 0.15 | |
| > 5 alleles | 292 | 4.58 | 0.97 | 0.30 | 0.08 | 0.0003 | |||
| HDL-C | LPL, APOA1, CETP, APOE | < 4 alleles | 251 | 1.24 | 0.28 | reference | |||
| (mmol/L) | = 4 alleles | 250 | 1.24 | 0.31 | 0.51 | -0.01 | 0.03 | 0.74 | |
| > 4 alleles | 194 | 1.27 | 0.35 | 0.02 | 0.029 | 0.41 | |||
| LDL-C | SORT1, APOA1, LDLR, APOE | < 4 alleles | 232 | 2.58 | 0.81 | reference | |||
| (mmol/L) | = 4 alleles | 247 | 2.73 | 0.82 | 0.02 | 0.16 | 0.08 | 0.04 | |
| > 4 alleles | 211 | 2.74 | 0.98 | 0.20 | 0.08 | 0.02 | |||
SD: standard deviation, SE: standard error. The b coefficients represent the effect sizes.
Means ± SD are for TG (mmol/L).
β ± SE are for ln (TG).
p values were adjusted for age, gender, physical activity, smoking status and BMI. Significant p values are indicated in bold.
To distinguish between the effects of the combined lipid-risk-allele-scores and the effects of the covariables classically associated with lipid parameters (age, gender, physical activity, smoking status and BMI), we compared models with or without the risk-allele-scores stratified into tertiles (Table 3). The classical covariables alone accounted for 15.5%, 3% and 2.6% for TG, TC and LDL-C variance respectively. Overall, the combined lipid-risk-allele-scores and covariables explained 17.6%, 4.8% and 3.5% of the TG, TC and LDL-C variances, respectively. Then, the lipid-risk-allele-scores alone accounted for 2.1%, 1.8% and 0.9% of the TG, TC and LDL-C variances, respectively.
Table 3.
Effects of combined risk allele scores and covariables on lipid traits in the ISOR study
| Parameters | Models | β | SE | p | Explained variance (%) |
|---|---|---|---|---|---|
| Ln (TG) | Model 1 | 0.03 | 0.00 | < .0001 | 15.5 |
| Model 2 | 0.06 | 0.02 | 0.001 | 17.6 | |
| TC (mmol/L) | Model 1 | 0.03 | 0.01 | 0.0001 | 3.0 |
| Model 2 | 0.15 | 0.04 | 0.0003 | 4.8 | |
| LDL-C (mmol/L) | Model 1 | 0.03 | 0.01 | 0.0001 | 2.6 |
| Model 2 | 0.10 | 0.04 | 0.02 | 3.5 |
The β coefficients represent the effect sizes. SE: standard error. Model 1 included classical covariables: age, gender, physical activity, smoking status and BMI. Model 2 included classical covariables (age, gender, physical activity, smoking status, BMI) and corresponding lipid tertiles of combined risk scores.
Discussion
We attempted to replicate in an Algerian population sample seven European lipid-loci. Three SNPs (in the SORT1, CETP and GCKR genes) were individually significantly associated with lipid level variations, with effects in the same direction as in Europeans [4].
The frequencies of the selected SNPs were similar between Algerians and Europeans, except for the APOA1 and CETP SNPs. The lack of significant individual associations between the LPL, APOA1, LDLR and APOE SNPs and lipid traits probably results from an overestimated power of the ISOR study. Indeed, the statistical power calculated apriori using allele frequencies and effect sizes from Teslovich’s study [4] was in fact overestimated with respect to a posteriori calculations based on the allele frequencies and effect sizes from the ISOR study.
The lack of significant individual associations could also be explained by different haplotype structure between ethnic populations, as previously described for the APOE rs4420638 SNP [10].
Among the 7 SNPs studied in ISOR, 5 have been previously investigated in African-Americans [7,8]. The SNPs presented similar allele frequencies in Algerians and African-Americans, except for GCKR. Regarding their effect sizes on lipids traits, only information about the GCKR rs1260326 and LDLR rs6511720 SNPs in African-Americans are available. These two SNPs had lower effect sizes in Algerians than in African-Americans [7].
In the ISOR study, the combined risk allele scores for TC, TG and LDL-C (encompassing between three and six SNPs) were associated with their corresponding lipid traits. This finding is in line with the data shown in European [4] and Chinese [12] populations. The lack of an association between the combined risk allele score for HDL-C and the HDL-C concentration may be due to the fact that among the four SNPs used to calculate the score, only CETP rs3764261 was significantly associated with HDL-C in the ISOR study.
Bearing in mind limitations and although only seven established lipid-loci were investigated, our findings contribute to a better understanding of the genetic contribution to lipid traits in Algeria. Moreover, our data are consistent with the existence of a common pathophysiology process of lipids traits across different population groups.
Acknowledgements
The ISOR project was funded through a collaboration agreement between the Direction de la Post-Graduation et de la Recherche-Formation (DPGRF) (Algeria) and the Institut National de la Santé et de la Recherche Médicale (INSERM) in (France). The work in France was also part-funded by INSERM. The work in Algeria was also part-funded by the Agence Thématique de Recherche en Sciences de la Santé (ATRSS, ex-ANDRS) and a grant from the Projets Nationaux de Recherche (PNR) program run by the Algerian Direction Générale de la Recherche Scientifique et du Développement Technologique/Ministère de l’Enseignement Supérieur et de la Recherche Scientifique (DGRSDT/MESRS). We thank the Algerian Caisse Nationale des Assurances Sociales des Travailleurs Salariés for assistance with recruiting subjects into the ISOR study. We are indebted to the study subjects for their participation.
Disclosure of conflict of interest
None.
Supporting Information
References
- 1.European Association for Cardiovascular Prevention & Rehabilitation; Reiner Z, Catapano AL, De Backer G, Graham I, Taskinen MR, Wiklund O, Agewall S, Alegria E, Chapman MJ, Durrington P, Erdine S, Halcox J, Hobbs R, Kjekshus J, Filardi PP, Riccardi G, Storey RF, Wood D ESC Committee for Practice Guidelines (CPG) 2008-2010 and 2010-2012 Committees. The Task Force for the management of dyslipidaemias of the European Society of Cardiology (ESC) and the European Atherosclerosis Society (EAS) Eur Heart J. 2011;32:1769–1818. doi: 10.1093/eurheartj/ehr158. [DOI] [PubMed] [Google Scholar]
- 2.Emerging Risk Factors Collaboration. Di Angelantonio E, Sarwar N, Perry P, Kaptoge S, Ray KK, Thompson A, Wood AM, Lewington S, Sattar N, Packard CJ, Collins R, Thompson SG, Danesh J. Major lipids, apolipoproteins, and risk of vascular disease. JAMA. 2009;302:1993–2000. doi: 10.1001/jama.2009.1619. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Wu J, Province MA, Coon H, Hunt SC, Eckfeldt JH, Arnett DK, Heiss G, Lewis CE, Ellison RC, Rao DC, Rice T, Kraja AT. An investigation of the effects of lipid-lowering medications: genome-wide linkage analysis of lipids in the HyperGEN study. BMC Genet. 2007;8:60. doi: 10.1186/1471-2156-8-60. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Teslovich TM, Musunuru K, Smith AV, Edmondson AC, Stylianou IM, Koseki M, Pirruccello JP, Ripatti S, Chasman DI, Willer CJ, Johansen CT, Fouchier SW, Isaacs A, Peloso GM, Barbalic M, Ricketts SL, Bis JC, Aulchenko YS, Thorleifsson G, Feitosa MF, Chambers J, Orho-Melander M, Melander O, Johnson T, Li X, Guo X, Li M, Shin Cho Y, Jin Go M, Jin Kim Y, Lee JY, Park T, Kim K, Sim X, Twee-Hee Ong R, Croteau-Chonka DC, Lange LA, Smith JD, Song K, Hua Zhao J, Yuan X, Luan J, Lamina C, Ziegler A, Zhang W, Zee RY, Wright AF, Witteman JC, Wilson JF, Willemsen G, Wichmann HE, Whitfield JB, Waterworth DM, Wareham NJ, Waeber G, Vollenweider P, Voight BF, Vitart V, Uitterlinden AG, Uda M, Tuomilehto J, Thompson JR, Tanaka T, Surakka I, Stringham HM, Spector TD, Soranzo N, Smit JH, Sinisalo J, Silander K, Sijbrands EJ, Scuteri A, Scott J, Schlessinger D, Sanna S, Salomaa V, Saharinen J, Sabatti C, Ruokonen A, Rudan I, Rose LM, Roberts R, Rieder M, Psaty BM, Pramstaller PP, Pichler I, Perola M, Penninx BW, Pedersen NL, Pattaro C, Parker AN, Pare G, Oostra BA, O’Donnell CJ, Nieminen MS, Nickerson DA, Montgomery GW, Meitinger T, McPherson R, McCarthy MI, McArdle W, Masson D, Martin NG, Marroni F, Mangino M, Magnusson PK, Lucas G, Luben R, Loos RJ, Lokki ML, Lettre G, Langenberg C, Launer LJ, Lakatta EG, Laaksonen R, Kyvik KO, Kronenberg F, König IR, Khaw KT, Kaprio J, Kaplan LM, Johansson A, Jarvelin MR, Janssens AC, Ingelsson E, Igl W, Kees Hovingh G, Hottenga JJ, Hofman A, Hicks AA, Hengstenberg C, Heid IM, Hayward C, Havulinna AS, Hastie ND, Harris TB, Haritunians T, Hall AS, Gyllensten U, Guiducci C, Groop LC, Gonzalez E, Gieger C, Freimer NB, Ferrucci L, Erdmann J, Elliott P, Ejebe KG, Döring A, Dominiczak AF, Demissie S, Deloukas P, de Geus EJ, de Faire U, Crawford G, Collins FS, Chen YD, Caulfield MJ, Campbell H, Burtt NP, Bonnycastle LL, Boomsma DI, Boekholdt SM, Bergman RN, Barroso I, Bandinelli S, Ballantyne CM, Assimes TL, Quertermous T, Altshuler D, Seielstad M, Wong TY, Tai ES, Feranil AB, Kuzawa CW, Adair LS, Taylor HA Jr, Borecki IB, Gabriel SB, Wilson JG, Holm H, Thorsteinsdottir U, Gudnason V, Krauss RM, Mohlke KL, Ordovas JM, Munroe PB, Kooner JS, Tall AR, Hegele RA, Kastelein JJ, Schadt EE, Rotter JI, Boerwinkle E, Strachan DP, Mooser V, Stefansson K, Reilly MP, Samani NJ, Schunkert H, Cupples LA, Sandhu MS, Ridker PM, Rader DJ, van Duijn CM, Peltonen L, Abecasis GR, Boehnke M, Kathiresan S. Biological, clinical and population relevance of 95 loci for blood lipids. Nature. 2010;466:707–713. doi: 10.1038/nature09270. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.NCI-NHGRI Working Group on Replication in Association Studies. Chanock SJ, Manolio T, Boehnke M, Boerwinkle E, Hunter DJ, Thomas G, Hirschhorn JN, Abecasis G, Altshuler D, Bailey-Wilson JE, Brooks LD, Cardon LR, Daly M, Donnelly P, Fraumeni JF Jr, Freimer NB, Gerhard DS, Gunter C, Guttmacher AE, Guyer MS, Harris EL, Hoh J, Hoover R, Kong CA, Merikangas KR, Morton CC, Palmer LJ, Phimister EG, Rice JP, Roberts J, Rotimi C, Tucker MA, Vogan KJ, Wacholder S, Wijsman EM, Winn DM, Collins FS. Replicating genotype-phenotype associations. Nature. 2007;447:655–660. doi: 10.1038/447655a. [DOI] [PubMed] [Google Scholar]
- 6.Weissglas-Volkov D, Aguilar-Salinas CA, Nikkola E, Deere KA, Cruz-Bautista I, Arellano-Campos O, Muñoz-Hernandez LL, Gomez-Munguia L, Ordoñez-Sánchez ML, Reddy PM, Lusis AJ, Matikainen N, Taskinen MR, Riba L, Cantor RM, Sinsheimer JS, Tusie-Luna T, Pajukanta P. Genomic study in Mexicans identifies a new locus for triglycerides and refines European lipid loci. J Med Genet. 2013;50:298–308. doi: 10.1136/jmedgenet-2012-101461. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Musunuru K, Romaine SP, Lettre G, Wilson JG, Volcik KA, Tsai MY, Taylor HA Jr, Schreiner PJ, Rotter JI, Rich SS, Redline S, Psaty BM, Papanicolaou GJ, Ordovas JM, Liu K, Krauss RM, Glazer NL, Gabriel SB, Fornage M, Cupples LA, Buxbaum SG, Boerwinkle E, Ballantyne CM, Kathiresan S, Rader DJ. Multi-ethnic analysis of lipid-associated loci: the NHLBI CARe project. PLoS One. 2012;7:e36473. doi: 10.1371/journal.pone.0036473. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Global Lipids Genetics Consortium. Willer CJ, Schmidt EM, Sengupta S, Peloso GM, Gustafsson S, Kanoni S, Ganna A, Chen J, Buchkovich ML, Mora S, Beckmann JS, Bragg-Gresham JL, Chang HY, Demirkan A, Den Hertog HM, Do R, Donnelly LA, Ehret GB, Esko T, Feitosa MF, Ferreira T, Fischer K, Fontanillas P, Fraser RM, Freitag DF, Gurdasani D, Heikkilä K, Hyppönen E, Isaacs A, Jackson AU, Johansson A, Johnson T, Kaakinen M, Kettunen J, Kleber ME, Li X, Luan J, Lyytikäinen LP, Magnusson PK, Mangino M, Mihailov E, Montasser ME, Müller-Nurasyid M, Nolte IM, O’Connell JR, Palmer CD, Perola M, Petersen AK, Sanna S, Saxena R, Service SK, Shah S, Shungin D, Sidore C, Song C, Strawbridge RJ, Surakka I, Tanaka T, Teslovich TM, Thorleifsson G, Van den Herik EG, Voight BF, Volcik KA, Waite LL, Wong A, Wu Y, Zhang W, Absher D, Asiki G, Barroso I, Been LF, Bolton JL, Bonnycastle LL, Brambilla P, Burnett MS, Cesana G, Dimitriou M, Doney AS, Döring A, Elliott P, Epstein SE, Eyjolfsson GI, Gigante B, Goodarzi MO, Grallert H, Gravito ML, Groves CJ, Hallmans G, Hartikainen AL, Hayward C, Hernandez D, Hicks AA, Holm H, Hung YJ, Illig T, Jones MR, Kaleebu P, Kastelein JJ, Khaw KT, Kim E, Klopp N, Komulainen P, Kumari M, Langenberg C, Lehtimäki T, Lin SY, Lindström J, Loos RJ, Mach F, McArdle WL, Meisinger C, Mitchell BD, Müller G, Nagaraja R, Narisu N, Nieminen TV, Nsubuga RN, Olafsson I, Ong KK, Palotie A, Papamarkou T, Pomilla C, Pouta A, Rader DJ, Reilly MP, Ridker PM, Rivadeneira F, Rudan I, Ruokonen A, Samani N, Scharnagl H, Seeley J, Silander K, Stancáková A, Stirrups K, Swift AJ, Tiret L, Uitterlinden AG, van Pelt LJ, Vedantam S, Wainwright N, Wijmenga C, Wild SH, Willemsen G, Wilsgaard T, Wilson JF, Young EH, Zhao JH, Adair LS, Arveiler D, Assimes TL, Bandinelli S, Bennett F, Bochud M, Boehm BO, Boomsma DI, Borecki IB, Bornstein SR, Bovet P, Burnier M, Campbell H, Chakravarti A, Chambers JC, Chen YD, Collins FS, Cooper RS, Danesh J, Dedoussis G, de Faire U, Feranil AB, Ferrières J, Ferrucci L, Freimer NB, Gieger C, Groop LC, Gudnason V, Gyllensten U, Hamsten A, Harris TB, Hingorani A, Hirschhorn JN, Hofman A, Hovingh GK, Hsiung CA, Humphries SE, Hunt SC, Hveem K, Iribarren C, Järvelin MR, Jula A, Kähönen M, Kaprio J, Kesäniemi A, Kivimaki M, Kooner JS, Koudstaal PJ, Krauss RM, Kuh D, Kuusisto J, Kyvik KO, Laakso M, Lakka TA, Lind L, Lindgren CM, Martin NG, März W, McCarthy MI, McKenzie CA, Meneton P, Metspalu A, Moilanen L, Morris AD, Munroe PB, Njølstad I, Pedersen NL, Power C, Pramstaller PP, Price JF, Psaty BM, Quertermous T, Rauramaa R, Saleheen D, Salomaa V, Sanghera DK, Saramies J, Schwarz PE, Sheu WH, Shuldiner AR, Siegbahn A, Spector TD, Stefansson K, Strachan DP, Tayo BO, Tremoli E, Tuomilehto J, Uusitupa M, van Duijn CM, Vollenweider P, Wallentin L, Wareham NJ, Whitfield JB, Wolffenbuttel BH, Ordovas JM, Boerwinkle E, Palmer CN, Thorsteinsdottir U, Chasman DI, Rotter JI, Franks PW, Ripatti S, Cupples LA, Sandhu MS, Rich SS, Boehnke M, Deloukas P, Kathiresan S, Mohlke KL, Ingelsson E, Abecasis GR. Discovery and refinement of loci associated with lipid levels. Nat Genet. 2013;45:1274–1283. doi: 10.1038/ng.2797. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Qi Q, Chu AY, Kang JH, Jensen MK, Curhan GC, Pasquale LR, Ridker PM, Hunter DJ, Willett WC, Rimm EB, Chasman DI, Hu FB, Qi L. Sugar-sweetened beverages and genetic risk of obesity. N Engl J Med. 2012;367:1387–1396. doi: 10.1056/NEJMoa1203039. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Boulenouar H, Mediene Benchekor S, Meroufel DN, Lardjam Hetraf SA, Ouhaibi Djellouli H, Hermant X, Grenier-Boley B, Hamani Medjaoui I, Saidi Mehtar N, Amouyel P, Houti L, Meirhaeghe A, Goumidi L. Impact of APOE gene polymorphisms on the lipid profile in an Algerian population. Lipids Health Dis. 2013;12:155. doi: 10.1186/1476-511X-12-155. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Dumitrescu L, Carty CL, Taylor K, Schumacher FR, Hindorff LA, Ambite JL, Anderson G, Best LG, Brown-Gentry K, Bůžková P, Carlson CS, Cochran B, Cole SA, Devereux RB, Duggan D, Eaton CB, Fornage M, Franceschini N, Haessler J, Howard BV, Johnson KC, Laston S, Kolonel LN, Lee ET, MacCluer JW, Manolio TA, Pendergrass SA, Quibrera M, Shohet RV, Wilkens LR, Haiman CA, Le Marchand L, Buyske S, Kooperberg C, North KE, Crawford DC. Genetic determinants of lipid traits in diverse populations from the population architecture using genomics and epidemiology (PAGE) study. PLoS Genet. 2011;7:e1002138. doi: 10.1371/journal.pgen.1002138. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Zhou L, He M, Mo Z, Wu C, Yang H, Yu D, Yang X, Zhang X, Wang Y, Sun J, Gao Y, Tan A, He Y, Zhang H, Qin X, Zhu J, Li H, Lin X, Zhu J, Min X, Lang M, Li D, Zhai K, Chang J, Tan W, Yuan J, Chen W, Wang Y, Wei S, Miao X, Wang F, Fang W, Liang Y, Deng Q, Dai X, Lin D, Huang S, Guo H, Lilly Zheng S, Xu J, Lin D, Hu FB, Wu T. A genome wide association study identifies common variants associated with lipid levels in the Chinese population. PLoS One. 2013;8:e82420. doi: 10.1371/journal.pone.0082420. [DOI] [PMC free article] [PubMed] [Google Scholar]
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