Genome-Wide Association Study Pinpoints a New Functional Apolipoprotein B Variant Influencing Oxidized Low-Density Lipoprotein Levels But Not Cardiovascular EventsClinical Perspective
Background—Oxidized low-density lipoprotein may be a key factor in the development of atherosclerosis. We performed a genome-wide association study on oxidized low-density lipoprotein and tested the impact of associated single-nucleotide polymorphisms (SNPs) on the risk factors of atherosclerosis and cardiovascular events.
Methods and Results—A discovery genome-wide association study was performed on a population of young healthy white individuals (N=2080), and the SNPs associated with a P<5×10–8 were replicated in 2 independent samples (A: N=2912; B: N=1326). Associations with cardiovascular endpoints were also assessed with 2 additional clinical cohorts (C: N=1118; and D: N=808). We found 328 SNPs associated with oxidized low-density lipoprotein. The genetic variant rs676210 (Pro2739Leu) in apolipoprotein B was the proxy SNP behind all associations (P=4.3×10–136, effect size=13.2 U/L per allele). This association was replicated in the 2 independent samples (A and B, P=2.5×10–47 and 1.1×10–11, effect sizes=10.3 U/L and 7.8 U/L, respectively). In the meta-analyses of cohorts A, C, and D (excluding cohort B without angiographic data), the top SNP did not associate significantly with the age of onset of angiographically verified coronary artery disease (hazard ratio=1.00 [0.94–1.06] per allele), 3-vessel coronary artery disease (hazard ratio=1.03 [0.94–1.13]), or myocardial infarction (hazard ratio=1.04 [0.96–1.12]).
Conclusions—This novel genetic marker is an important factor regulating oxidized low-density lipoprotein levels but not a major genetic factor for the studied cardiovascular endpoints.
Atherosclerosis, a major cause of disability and death, is a multifactorial disease with a strong hereditary and environmental background.1
Clinical Perspective on p 81
The conversion of low-density lipoprotein (LDL) to oxidized LDL (oxLDL) increases the atherogenic potential of LDL and is regarded as a key event in the development of fatty streaks, the early atherosclerotic lesions.2 The removal of oxLDL has been shown to prevent atherosclerosis in mice.3
At present, little is known about the genetic factors affecting the susceptibility of LDL to oxidation. As oxLDL plays an important role in the development of atherosclerosis, we wanted to elucidate the possible genetic factors influencing its formation by performing a genome-wide association study (GWAS) on a population of healthy white adults from the Cardiovascular Risk in Young Finns Study (YFS).4 The genome-wide significant associations were replicated in 2 additional samples: the Ludwigshafen Risk and Cardiovascular Health (LURIC) study5 and the Kooperative Gesundheitsforschung in der Region Augsburg (Cooperative Health Research in the Augsburg Region, ie, KORA) study.6,7 The effect of single-nucleotide polymorphisms (SNPs) with a P<5×10–8 on cardiovascular endpoints was further analyzed in 2 additional clinical cohorts, the Finnish Cardiovascular Study (FINCAVAS)8 and the Angiography and Genes Study (ANGES).9 Meta-analyses of the association between the top hits and cardiovascular outcomes were carried out on 3 independent cohorts (FINCAVAS, ANGES, and LURIC; KORA did not have angiographic data).
The current study comprises 8244 subjects with measured early subclinical (YFS) or more advanced atherosclerosis-related clinical phenotypes, that is, cardiovascular disease endpoints (FINCAVAS, ANGES, KORA, and LURIC). The mentioned studies were engaged in cooperation with the ongoing AtheroRemo Consortium and have been widely involved with other international genetic consortia (online-only Data Supplement references).
Materials and Methods
For more details, please see the online-only Data Supplement.
Study Populations and Ethical Statements
All studies were conducted according to the guidelines of the Declaration of Helsinki, and the study protocols were approved by local ethics committees. All participants gave an informed consent.
The YFS cohort is a Finnish longitudinal population study sample on the evolution of cardiovascular risk factors from childhood to adulthood.4 The first cross-sectional study was conducted in 1980 at 5 different centers. These subjects were reexamined in 1983 and 1986 as young individuals and in 2001 and 2007 as adults. In the current study, we used the variables measured in 2001. Genotype, risk factor, and phenotype data were available for 2080 subjects, and they formed the current study population.
The LURIC study comprises 3316 white patients who were referred to coronary angiography due to chest pain at a tertiary care center in Southwest Germany between 1997 and 2000.5 All the necessary covariate and endpoint data were available for 2912 LURIC patients, who were hence included in the present study.
The Monitoring Trends and Determinants in Cardiovascular Disease/KORA Augsburg study (KORA) is a series of population-based surveys conducted in the region of Augsburg in Southern Germany.7 The data for the current study were drawn from a subcohort randomly selected on the basis of sex and survey from the KORA surveys S1–S3 conducted between 1984 and 1995.6 Of these, 1326 subjects had all the required covariate and end point data available and were included in the current study.
The FINCAVAS population consists of patients who underwent an exercise stress test at Tampere University Hospital, Finland.8 From the overall recruited study population, 1118 individuals had all the necessary angiographic, genetic, and covariate data available and were included in the current study.
The ANGES population consisted of 1000 patients with a symptomatic heart disease referred to as coronary angiography to rule out or confirm coronary artery disease (CAD).9,10 Angiographic, genetic, and covariate data were available for 808 individuals (online-only Data Supplement Table I, and section A1).
Clinical and Biochemical Characteristics of the Participating Study Cohorts
OxLDL, Lipoprotein, and Apolipoprotein B Measurements
In YFS, LURIC, and KORA, the circulating oxLDL levels were measured using the same immunoassay. In brief, circulating serum oxLDL levels were assayed with a competitive ELISA utilizing a specific murine monoclonal antibody, mAB 4E611 (Mercodia, Uppsala, Sweden; detection limit <0.3 U/L).
In YFS, LDL baseline diene conjugation was measured by determining the level of baseline diene conjugation in lipids extracted from LDL.12 In all cohorts, standard methods were used for serum cholesterol and apolipoprotein B (apoB) analyses (online-only Data Supplement section A2).
Cardiovascular Endpoint Definitions in FINCAVAS, ANGES, and LURIC
Angiographically Verified CAD
In FINCAVAS, ANGES, and LURIC, coronary angiography (KORA did not have angiographic data) was performed using the standard Judkins technique. Transluminal narrowing of at least 50% in any major coronary artery (left anterior descending, left circumflex, or right coronary artery) was the criterion for the diagnosis of CAD. The number of arteries with significant >50% stenosis was used to determine the severity of CAD. In this study, subjects with no CAD were compared with those with 3-vessel disease.
In LURIC, myocardial infarction (MI) was defined as evidence of any MI (acute, previous, ST-elevation MI, or non-ST-elevation MI).5 In FINCAVAS, a history of prior MI was based on patient interviews, resting ECG recordings, and hospital records.8 In ANGES, the clinical diagnosis of MI was based on symptoms, electrocardiographic findings, and biochemical marker tests measuring troponin I and creatine kinase (online-only Data Supplement section A3).9
Genotyping and Quality Control in the Different Cohorts
In brief, in YFS, genotyping was carried out by using a custom-built Illumina Human 670k BeadChip at the Welcome Trust Sanger Institute. Genotype imputation was performed using MACH 1.013 and HapMap II CEU (release 22, NCBI build 36, dbSNP 126) samples as a reference. After imputation, 2 543 887 SNPs were available. SNPs with a squared correlation (r2) of <0.30 between imputed and true genotypes were eliminated from the analysis.
In the FINCAVAS, ANGES, and LURIC cohorts, genotyping was performed by using the Metabochip, which is a custom Illumina iSelect genotyping array designed to test ≈200 000 SNPs identified through genome-wide meta-analyses for metabolic and atherosclerotic/cardiovascular diseases and traits. In KORA, genotyping was accomplished by using the IBC 50K array, which is an Illumina iSelect genotyping array designed to test ≈50 000 SNPs identified through genome-wide meta-analyses associated with a range of cardiovascular, metabolic, and inflammatory syndromes.14 The studied top SNP (rs676210) passed quality check (call rate >0.95, minor allele frequency >0.01, Hardy-Weinbert equilibrium P>10–6) in all 3 cohorts (online-only Data Supplement, section A4).
For the GWAS analysis, oxLDL was Box-Cox transformed. Residuals were obtained using a linear regression model in which the variables were adjusted for sex, age, and body mass index, as well as principal components (to control population stratification)15 and apoB. Tests for additive genetic effects were carried out on a linear scale by means of linear regression. Genotypes were coded as 0, 1, or 2 when the SNP was genotyped and by dosage (scale 0–2) when imputed. In true genotyped SNPs, the minor allele was the effect allele. The imputation software (MACH 1.0) used HapMap II as reference to assign the alleles for imputed SNPs. Tests were performed to assess the association of SNPs with the standardized residuals using PLINK16 for the genotyped data. ProbABEL17 was employed to fit the linear regression model, taking into account the genotype uncertainty in imputed SNPs. P values were combined from the analysis by favoring genotyped SNPs over imputed ones. Quartile-quartile and Manhattan plots were drawn for the analysis of the results. The P value for genome-wide significance was set at P<5×10−8, corresponding to a target α of 0.05 with a Bonferroni correction for 1 million independent tests.
The severity (functionality) of mutations was assessed by PolyPhen-2 version 2.1.0 software.18 Further statistical analyses were performed using the R Statistical package v. 2.11.1 (http://www.r-project.org). To define associations nonredundantly associated with oxLDL, we applied a forward-selection algorithm.19 We associated the SNPs with genome-wide significance (top SNPs) with cardiovascular-disease–related endpoints (angioraphically verified CAD, severity of CAD, and MI) in FINCAVAS, ANGES, and LURIC. The associations were assessed using the appropriate statistical models (χ2 test, ANOVA, linear regression, or Cox Proportional-Hazards regression) in R. Meta-analyses were performed using a fixed effects model when the P for cohort heterogeneity was >0.05. KORA did not have angiographic data and was only used for the replication of the oxLDL association. The YFS participants were young (<39 years of age, average age 31.7 years in 2001), still without major clinical endpoints, and it was therefore not possible to include them in these analyses. P<0.05 were considered significant (online-only Data Supplement, section A5).
General Characteristics of the Study Populations
There was a predominance of women in the YFS population and a predominance of men in the FINCAVAS, LURIC, and KORA populations (online-only Data Supplement Table I). Furthermore, age differences existed between the cohorts, with YFS as the youngest and LURIC as the oldest population. The mean oxLDL levels also varied, being highest in KORA and lowest in LURIC (online-only Data Supplement Tables I and II).
GWAS Analysis of Oxidized LDL Pinpoints a Novel Variant Affecting LDL Oxidation
In the YFS discovery GWAS, 328 SNPs were associated with oxLDL with genome-wide statistical significance (P<5×10–8). All statistical adjustments applied produced identical top SNP associations. All of these SNPs were within 210 kb from the apoB-100 precursor coding region (OMIM 107730) on chromosome 2 (see the quartile-quartile plot [online-only Data Supplement Figure I], Manhattan plot [online-only Data Supplement Figure II], and regional plot [Figure 1]).
Using a forward-selection algorithm with a P value cut-off of 5×10–8, only 1 SNP (rs676210) was independently associated with oxLDL, implicating a role as the proxy for all of the associations. Eleven SNPs had r2>0.5 with rs676210 (rs1042034, rs6728178, rs6754295, rs673548, rs6711016, rs11902417, rs10184054, rs6544366, rs4564803, rs7557067, and rs2678379), and forward-selection algorithm cannot separate, which is the true proxy. We chose to include rs676210 in the subsequent analyses because it is biologically most plausible from its linkage disequilibrium-block and also because it causes a missense mutation. We also ran the GWAS by adjusting for rs676210, in addition to other covariates. No other independent associations were found (online-only Data Supplement Figure III). Moreover, in a haplotype analysis of all associated missense mutations, only rs676210 (or rs1042034, which is in perfect linkage disequilibrium with rs676210) showed an independent effect on oxLDL.
Structural Testing of the Pro2739Leu (rs676210) and Other Related Missense Variants
The variant rs676210 causes a missense mutation (change of proline to leucine at position 2739) in apoB. This mutation was predicted to be damaging in the analysis performed with the PolyPhen-2 software. This supports the notion of the biological functionality of the amino acid change caused by the SNP. The SNP in perfect linkage disequilibrium with rs676210 (rs1042034 [Ser4338Asn]) was predicted to be benign, which further supports the role of rs676210 as the functional variant. Two other nearby missense mutations (rs533617 [His1923Arg] and rs679899 [Ala618Val]) were also predicted to be probably damaging to apoB but showed no independent effect on oxLDL in the haplotype analyses and were, therefore, not studied further. The other significantly associated missense mutations (rs1801695 [Ala4481Thr], rs1367117 [Thr98Ile], and rs1042031 [Glu4181Lys]) were predicted to be benign and did not show independent effect on oxLDL in the haplotype analyses. As rs676210 was the most probable SNP behind all the found associations, further analyses were conducted with this SNP only.
Replication of the Association of rs676210 With oxLDL in 2 Independent cohorts
In YFS, rs676210 was associated with oxLDL with a P value of 4.3×10–136 and an effect size of 13.2 U/L oxLDL per allele. The major (risk) allele carriers had significantly higher levels of oxLDL (Table 1). In addition to conventional risk factors, rs676210 explained 11% of the variation in oxLDL (r2=0.11). The association was replicated in 2 independent cohorts, in LURIC with a P value of 2.5×10–47 and an effect size of 10.5 U/L, and in KORA with a P value of 1.1×10–11 and an effect size of 7.8 U/L. The association was also strong with the oxLDL/LDL, oxLDL/apoB, and oxLDL/LDL-apoB ratios (Table 1).
In a linear regression model adjusted for age, sex, and body mass index in the YFS, rs676210 also associated significantly with the apoB-epitope-structure-independent measurement of oxLDL, LDL diene conjugation, with a P value of 0.028 and an effect size of 0.73 µmol/L, confirming the effect of the studied SNP on LDL oxidation.
Furthermore, rs676210 was significantly associated with apoB in YFS: with triglyceride concentrations in YFS and LURIC; with very-low-density lipoprotein (VLDL) cholesterol concentration in LURIC; with high-density lipoprotein (HDL) cholesterol concentrations in YFS, LURIC, and KORA; and with total cholesterol/HDL cholesterol concentrations in YFS and LURIC (Tables 1).
Meta-Analyses of the Association Between the apoB Pro2739Leu (rs676210) Mutation and Cardiovascular Outcomes
We found statistically significant differences in traits between genotypes in the angiographic cohorts (FINCAVAS, ANGES, and LURIC; see Tables 1 and 2). Therefore, and because of the pleiotropic effect of rs676210 with lipids, the meta-analyses were performed adjusting for age, sex, body mass index, LDL, HDL, and triglycerides (Figure 2). We also performed the analyses without adjusting for LDL, HDL, and triglycerides to see what proportion of the effects is caused by the pleiotropic effects of rs676210 (online-only Data Supplement Figure IV).
The apoB Pro2739Leu (rs676210 allele G, also the allele causing high oxLDL levels) was not associated with CAD, 3-vessel CAD, or MI after adjustment for age, sex, body mass index, statin use, LDL, HDL, and triglycerides (Figure 2). Results without adjustment for LDL, HDL, and triglycerides were also not significant in the meta-analysis (online-only Data Supplement Figure IV).
Of the 328 SNPs associated with circulating oxLDL levels in a healthy white adult population (YFS), only 1 missense mutation leading to a proline-to-leucine interchange in apoB (SNP rs676210, Pro2739Leu) on chromosome 2 remained significant in further analysis. The association of apoB rs676210 with oxLDL was convincingly replicated in the LURIC and KORA cohorts. We also tested the association of rs676210 with cardiovascular endpoints in a meta-analysis of 3 independent clinical cohorts but did not find significant associations.
The YFS subjects had higher mean oxLDL levels than the LURIC subjects, although the LURIC subjects were older and had more comorbidities. This could simply be due to different storage conditions or differences in the use of statin medication21 or the levels of oxidants or antioxidants. In LURIC, there was a higher proportion of statin users in comparison with the healthier YFS population (mean oxLDL levels were lower among statin users than among nonusers; data not shown).
There are few previous reports about the genetics of LDL oxidation. To our knowledge, ours is the first GWAS on circulating oxLDL. Employing a forward-selection algorithm, performing haplotype analyses, assessing the damage-producing probability of the SNPs, and running the GWAS with top-SNP adjustment strongly suggest that apoB rs676210 is the most probable functional variant and the proxy for all of the found 328 associations.
Each LDL particle contains 1 apoB moiety. In the current study, the missense mutation of proline to leucine (rs676210, Pro2739Leu) in apoB increased plasma oxLDL levels in a step-wise manner in the genotype order of AA (Leu/Leu, the minor allele), GA (Pro/Leu), and GG (Pro/Pro). Our results are supported by the fact that the variation in apoB probably changes the 3-dimensional structure of apoB22 in a way that makes LDL less prone to oxidation in homozygous apoB (Leu/Leu) minor allele carriers.
There seem to be some pleiotropic effects for this variation as rs676210 was also associated with HDL cholesterol in all 3 cohorts and with triglyceride levels in YFS and LURIC. The oxLDL association, however, was adjusted for these, so the main effect seems to be on the oxLDL levels.
There are a few studies related to the genetic variation rs676210. In a previous study, the rs676210 minor allele (A) was associated with lower triglyceride, total cholesterol, and LDL cholesterol levels and with higher HDL cholesterol levels, with a P<5×10−8, in comparison with major allele (G) carriers.23 These results are in accordance with our study. In another earlier report, rs676210 was found to associate with VLDL-related fractions, triglycerides, and mean VLDL/LDL size.24 In that study, minor allele carriers had larger VLDL/LDL particles and lower VLDL cholesterol and triglyceride concentrations. These findings are also in accordance with our results, showing a linear trend for the minor allele carriers in LURIC to have lower VLDL cholesterol levels (P=0.0034). VLDL cholesterol was not measured in YFS with this method.
Interestingly, the minor allele of rs676210 (A) has been linked to an improved response to fenofibrate treatment,25 the treatment was reported to lower triglyceride levels by 24.7%, 28.3%, and 34.5% according to the rs676210 genotypes GG, GA, and AA, respectively. The allele found to decrease LDL oxidation also seems to improve the response to fenofibrate. Furthermore, minor allele carriers had lower triglyceride levels in YFS and LURIC when compared with major risk allele carriers. We do not have data on fenofibrate use in our cohorts.
It seems that the oxLDL levels associated apoB Pro2739Leu mutation is not associated with cardiovascular endpoints. This was observed across the cohorts studied in the combined meta-analysis. The association of serum oxLDL levels measured with Mercodia ELISA assay with CAD is controversial. Many smaller studies report oxLDL as a predictor of CAD; however, larger studies have been negative after adjusting for standard lipid variables.26 Our results are in line with these larger nongenetic studies by showing that serum oxLDL levels associated gene variant is not associated with the cardiovascular endpoints.
Limitations and Strengths of the Study
A strength of the study is the replication of the major results in multiple independent cohorts. The association of rs676210 with LDL oxidation is convincing. The oxidation of LDL was, however, measured by structural changes in the apoB protein and does not fully account for the lipid component of these apoB-containing particles. To confirm that our results are not due to the possibility of the Pro2739Leu substitution altering the binding of the used monoclonal antibody to apoB, we also applied a second, apoB-epitope-structure-independent assay to assess the effect of the SNP on the LDL oxidation, with parallel results. In this independent assay, the SNP rs676210 was significantly associated with LDL diene conjugation. These results put together show that our findings are not due to the oxLDL assay employed and imply a true biological function for rs676210 in LDL oxidation.
The step-wise algorithm and top-SNP–adjusted GWAS strongly suggest that rs676210 is the proxy SNP. We also carried out manual haplotype analyses, arriving at the same conclusion of rs676210 as the implied proxy. This information, together with the predicted damaging change caused in apoB (proline-to-leucine interchange), indicates that out of the available SNPs, this is the most likely functional top-SNP candidate. The SNP in perfect linkage disequilibrium with rs676210 was predicted to be benign. Two other nearby missense mutations were also predicted to be damaging but showed no independent effect in the haplotype analysis nor with the forward-selection algorithm; other associated missense mutations were predicted not to be damaging. These results strongly suggest that rs676210 is the true functional variant. However, it is important to note that the true proxy cannot be found with 100% certainty by means of bioinformatic methods, and, therefore, we performed the analyses with the most probable one.
The effect was studied only in whites and might not be generalizable to other populations. There were significant differences in sex distributions and mean ages between the cohorts. However, the association of rs676210 with oxLDL concentration remained significant despite these and other differences in the background populations.
In comparison, the cohorts used for the clinical endpoint association assessments were quite similar. The current analyses related to oxLDL did not include the FINCAVAS or ANGES study populations because oxLDL was not measured in them.
The clinical implications of rs676210 leading to Pro2739Leu missense mutation require further investigation. However, we did not find significant associations in a meta-analysis of 3 independent studies.
We found an SNP that is important in regulating oxLDL levels but not a major genetic factor for studied cardiovascular endpoints.
From the Department of Clinical Chemistry, Fimlab Laboratories, Tampere University Hospital and School of Medicine, University of Tampere, Tampere, Finland (K.-M.M., I.S., J.A.H., L.-P.L., N.O., R.L., T. Lehtimäki); Department of Internal Medicine, North Karelia Central Hospital, Joensuu, Finland (J.A.H.); Division of Vascular Surgery, Department of Surgery, Tampere University Hospital, Tampere, Finland (N.O.); LURIC nonprofit LLC, Freiburg im Breisgau and Mannheim Institute of Public Health, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany (M.E.K.); Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria (H.S.); Mannheim Institute of Public Health, Social and Preventive Medicine, Medical Faculty Mannheim, Rupprecht Karls University, Heidelberg, Germany (T.B.G.); Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany (J.B., B.T.); Population Studies Unit, National Institute of Health and Welfare, Turku, Finland (A.J.); Department of Pediatrics, University of Tampere and Tampere University Hospital, Tampere, Finland (N.H.-K.); Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Department of Internal Medicine, Turku University Hospital, Turku, Finland (M.J.); Department of Clinical Physiology, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland (T. Laitinen); Department of Forensic Medicine, School of Medicine at the University of Tampere and Centre for Laboratory Medicine, Tampere University Hospital, Tampere, Finland (P.J.K.); Department of Cardiology, Heart Center, Tampere University Hospital and University of Tampere, Tampere, Finland (K.C.N.); Division of Cardiology, Helsinki University Central Hospital, Helsinki, Finland (T.N.); Department of Internal Medicine, Päijät-Häme Central Hospital, Lahti, Finland (T.N.); Department of Cardio-Thoracic Surgery, Heart Center, Tampere University Hospital and University of Tampere, Tampere, Finland (J.L., P.K., M.T.); Department of Biomedical Engineering, Tampere University of Technology and BioMediTech, Tampere, Finland (J.V.); Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Munich, Germany (N.K., T.I.); Hannover Unified Biobank, Hannover Medical School, Hannover, Germany (N.K., T.I.); Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland (J.K.); Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland (J.K.); MCA Research Laboratory, Department of Physiology (M.A.) and Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland (O.T.R.); Department of Medicine, University of Turku and Turku University Hospital, Turku, Finland (J.S.A.V.); Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland (O.T.R.); Department of Clinical Physiology, Tampere University Hospital and University of Tampere, Tampere, Finland (M. Kähönen); Department of Internal Medicine II–Cardiology, University of Ulm Medical Center, Ulm, Germany (M. Karakas, W.K.); Division of Endocrinology, Diabetes and Metabolism, Graduate School of Molecular Diabetology and Endocrinology, Ulm University, Ulm, Baden-Württemberg, Germany (B.O.B.); ClinPhenomics Study Center and University of Frankfurt, Frankfurt, Germany (B.R.W.); Synlab Services GmbH, Mannheim and Mannheim Institute of Public Health, Medical Faculty Mannheim, University of Heidelberg, Germany and Clinical Institute of Medical and Chemical Laboratory Diagnostics Medical University of Graz, Graz, Austria (W.M.).
For the YFS, the expert technical assistance in data management and statistical analyses done by Irina Lisinen and Ville Aalto are gratefully acknowledged. For the LURIC study, we extend our appreciation to the participants of the LURIC study; without their collaboration, this article would not have been written. We thank the LURIC study team that was either temporarily or permanently involved in patient recruitment as well as sample and data handling, in addition to the laboratory staff at the Ludwigshafen General Hospital and the Universities of Freiburg, Ulm, and Graz, Germany. For the KORA study, we would like to thank Gerlinde Trischler (University of Ulm) for her expert technical assistance.
Sources of Funding
This work was supported by the European Union 7th Framework Program funding for the AtheroRemo project (201668). The Cardiovascular Risk in Young Finns Study has been financially supported by the Academy of Finland (grants 126925, 121584, 124282, 129378 [Salve], 117787 [Gendi], and 41071 [Skidi]); the Social Insurance Institution of Finland; the Kuopio, Tampere, and Turku University Hospital Medical Funds (grant 9M048 and 9N035 for TeLeht); the Juho Vainio Foundation; the Paavo Nurmi Foundation; the Finnish Foundation of Cardiovascular Research; the Finnish Cultural Foundation; as well as the Tampere Tuberculosis Foundation and the Emil Aaltonen Foundation (Dr Lehtimäki). The Monitoring Trends and Determinants in Cardiovascular Disease/KORA Augsburg studies were financed by the Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany, and supported by grants from the German Federal Ministry of Education and Research. A part of the work was financed by the German National Genome Research Network (NGFNPlus, project number 01GS0834), the German Research Foundation (TH-784/2–2), and additional funds from the University of Ulm. Furthermore, the research was supported within the Munich Center of Health Sciences (MC Health) as part of the Ludwig-Maximilians University innovative. The LURIC study received funding through the 6th Framework Program (integrated project Bloodomics, grant LSHM-CT-2004–503485) and the 7th of Framework Program (integrated project AtheroRemo, Grant Agreement number 201668) of the European Union. Mercodia AB, Uppsala, provided the reagents for the determination of oxLDL free of charge but did not assume any other role in the conducting of this study. FINCAVAS and ANGES have been financially supported by the Tampere University Hospital Medical Fund (grants 9M048 and 9N035 for TeLeht), the Tampere Tuberculosis Foundation, and the Emil Aaltonen Foundation (Dr Lehtimäki). This work has been financially supported by a grant awarded to Dr Mäkelä by the Urho Känkänen foundation.
The online-only Data Supplement is available at http://circgenetics.ahajournals.org/lookup/suppl/doi:10.1161/CIRCGENETICS.111.964965/-/DC1.
- Received July 25, 2012.
- Accepted November 16, 2012.
- © 2013 American Heart Association, Inc.
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Atherogenic oxidized low-density lipoprotein (LDL) is regarded as a key element in atherosclerosis. By performing a genome-wide association analysis, we identified the most important single-nucleotide polymorphism associating with circulating levels of oxidized LDL. The discovered single-nucleotide polymorphism (rs676210) leads to a Pro2739Leu missense mutation in the apolipoprotein B gene, likely rendering LDL less prone to oxidation and resulting in significantly lower levels of circulating oxidized LDL. Oxidized LDL levels have previously been reported to predict coronary artery disease but often not independently after adjusting for standard lipid variables. Correspondingly, we did not observe statistically significant associations between rs676210 and the age of onset of cardiovascular endpoints in a meta-analysis of 3 independent patient populations undergoing angiography (N=4801). However, population stratification by genetic and environmental factors regulating the oxidation of LDL could potentially lead to improved accuracy in patient selection for interventions such as statin therapy, novel antioxidant-molecule-based therapies, or diet-based prevention strategies. Supporting this, the discovered single-nucleotide polymorphism has previously been found to associate with an improved response to fenofibrate treatment, with the minor (protective) allele associating with greater reductions in triglyceride levels. Our study provides a useful framework for future investigations to elucidate the oxidative processes underlying coronary artery disease and to investigate how genes and environmental exposures (such as smoking) interact in causing the condition.