Author + information
- Received November 24, 2009
- Revision received April 20, 2010
- Accepted April 20, 2010
- Published online September 14, 2010.
- Sotirios Tsimikas, MD⁎,⁎ (, )
- Ziad Mallat, MD, PhD†,
- Philippa J. Talmud, DSc‡,
- John J.P. Kastelein, MD, PhD¶,
- Nicholas J. Wareham, MBBS, PhD§,
- Manjinder S. Sandhu, PhD∥,
- Elizabeth R. Miller, BS⁎,
- Joelle Benessiano, MD, PhD†,
- Alain Tedgui, PhD†,
- Joseph L. Witztum, MD⁎,
- Kay-Tee Khaw, MBBChir∥ and
- S. Matthijs Boekholdt, MD, PhD¶
- ↵⁎Reprint requests and correspondence
: Dr. Sotirios Tsimikas, Vascular Medicine Program, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92993-0682
Objectives This study sought to assess whether oxidation-specific biomarkers are associated with an increased risk of coronary artery disease (CAD) events.
Background The relationship of a panel of oxidative biomarkers and lipoprotein(a) [Lp(a)] to CAD risk is not fully determined.
Methods A prospective case-control study nested in the EPIC (European Prospective Investigation of Cancer)-Norfolk cohort of 45- to 79-year-old apparently healthy men and women followed for ∼6 years was designed. Cases consisted of participants in whom fatal or nonfatal CAD developed, matched by sex, age, and enrollment time with controls without CAD. Baseline levels of oxidized phospholipids on apolipoprotein B-100 particles and Lp(a) were measured in 763 cases and 1,397 controls. Their relationship to secretory phospholipase A2type IIA mass and activity, myeloperoxidase mass, and lipoprotein-associated phospholipase A2activity and association with CAD events were determined.
Results After adjusting for age, smoking, diabetes, low- and high-density lipoprotein cholesterol, and systolic blood pressure, the highest tertiles of oxidized phospholipids on apolipoprotein B-100 particles and Lp(a) were associated with a significantly higher risk of CAD events (odds ratios: 1.67 and 1.64, respectively; p < 0.001) compared with the lowest tertiles. The odds ratio of CAD events associated with the highest tertiles of oxidized phospholipids on apolipoprotein B-100 particles or Lp(a) was significantly potentiated (approximately doubled) by the highest tertiles of secretory phospholipase A2activity and mass but less so for myeloperoxidase and lipoprotein-associated phospholipase A2activity. The odds ratios for fatal CAD were higher than for the combined end point. After taking into account the Framingham Risk Score, c-index values progressively increased when oxidative biomarkers were added to the model.
Conclusions This EPIC-Norfolk study links pathophysiologically related oxidation-specific biomarkers and Lp(a) with CAD events. Oxidation-specific biomarkers provide cumulative predictive value when added to traditional cardiovascular risk factors.
The clinical application of biomarkers to predict cardiovascular disease (CVD) is increasing rapidly. The ability of biomarkers to define the presence of CVD, predict new CVD events, and reflect the benefit of therapeutic interventions is contingent on their ability to provide easily measured and noninvasive parameters that will generate insights into CVD pathophysiology. Such insights will afford clinicians a refined approach to optimally diagnose, treat, and monitor patients at high risk of atherothrombotic events.
In this regard, several novel oxidative biomarkers have been proposed to be of value in predicting future CVD events. Lipoprotein-associated phospholipase A2(Lp-PLA2) (1) and secretory phospholipase A2(sPLA2) (2,3) are enzymes that react with oxidized phospholipids (OxPLs) and cleave the oxidized fatty acid side chain at the sn2 position of OxPL to generate lysophosphatidylcholine and an oxidized free fatty acid. Myeloperoxidase (4) is an enzyme derived from activated leukocytes that mediates the generation of oxidized low-density lipoprotein (LDL) and high-density lipoprotein by using hydrogen peroxide and other oxidants as substrates. Based on a series of clinical studies showing enhanced predictive value, Lp-PLA2mass (5) and myeloperoxidase mass (4) have been approved for clinical use in assessing CVD risk.
Measures of oxidized lipoproteins are also being applied to a wide variety of CVD studies in assessing risk prediction (6–8). OxPL on apolipoprotein B-100 (OxPL/apoB) levels, measured with monoclonal antibody E06, are elevated in patients with multiple manifestations of anatomic and symptomatic CVD (9–13). OxPL/apoB levels are independent of all known demographic and biochemical risk factors, except for lipoprotein(a) [Lp(a)]. Remarkably, E06-detectable OxPLs are preferentially carried by Lp(a) as opposed to other lipoproteins (14,15). Lp(a) is composed of apolipoprotein B-100 and apolipoprotein(a), and Lp(a) plasma levels are primarily mediated by the apolipoprotein(a) gene locus and generally do not correlate with other risk factors. Although OxPLs can be generated by a variety of oxidative pathways, their measurement in the current assay format by antibody E06 most closely represents binding of OxPL by Lp(a), and therefore OxPL/apoB also reflects the genetic predisposition of Lp(a) levels. The ability of Lp(a) to bind and transport OxPLs may represent a key component of the atherothrombotic risk associated with Lp(a).
Although all these biomarkers may confer additional value to clinical risk prediction individually, biomarkers involved in oxidative stress pathways have not been systematically evaluated in the same population for their association with and prediction of CVD events. In addition, the few studies that showed improved risk stratification for coronary artery disease (CAD) by using multiple biomarkers did not generally include biomarkers amenable to modification by existing medications. In the current study using the prospectively followed EPIC (European Prospective Investigation of Cancer)-Norfolk cohort (16), we hypothesized that elevated baseline levels of OxPL/apoB and Lp(a) would be associated with an increased risk of fatal and nonfatal CAD events. Second, we hypothesized that the risk of CAD conferred by OxPL/apoB or Lp(a) would be potentiated by several pathophysiologically related but unique oxidative biomarkers, such as sPLA2mass and activity, Lp-PLA2activity, and myeloperoxidase mass.
A nested case-control study among participants in the EPIC-Norfolk cohort was designed as previously described (16). Briefly, 25,663 healthy men and women between 45 and 79 years of age were recruited from age-sex registers of general practices in Norfolk, United Kingdom. The participants completed a baseline questionnaire survey between 1993 and 1997, attended a clinic visit, and were followed for an average of 6 years. Individuals who reported a history of heart attack or stroke at the baseline visit were excluded. Case ascertainment was described previously. All individuals were flagged for death certification at the United Kingdom Office of National Statistics, with vital status ascertained for the entire cohort. In addition, participants admitted to hospitals were identified using their National Health Service number by data linkage with the East Norfolk Health Authority database, which identifies all hospital contacts throughout England and Wales for Norfolk residents. Participants were identified as having CAD during follow-up if they had a hospital admission and/or died with CAD as the underlying cause. CAD was defined as codes 410 to 414 according to the International Classification of Diseases 9th Revision. These codes encompass the clinical spectrum of CAD such as unstable angina, stable angina, and myocardial infarction. Controls were participants who remained free of CAD events during follow-up. Data on noncardiac events were not collected. Two controls were matched to each case by sex, age (within 5 years), and time of enrollment (within 3 months). The study was approved by the Norwich Health Authority Ethics Committee, and all participants provided written informed consent.
Laboratory and oxidative biomarker measurements
Blood samples were stored at −80°C at the Clinical School, University of Cambridge. OxPL/apoB content was measured by chemiluminescent enzyme-linked immunosorbent assay, as described previously in detail, using the murine monoclonal antibody E06, which binds to the phosphocholine head group of oxidized but not native phospholipids (11,17). By design, the OxPL/apoB measurement is independent of apoB-100 and LDL cholesterol levels, as previously reported (12). We previously showed that these biomarkers are stable with prolonged freezing or transport to processing sites on ice (12,18,19). It should be emphasized that the OxPL/apoB assay does not measure the total OxPL present in plasma or OxPL not detected by E06, and E06 does not cross-react with apolipoprotein(a).
Serum sPLA2activity was measured by a selective fluorometric assay by using fluorescent substrate 1-hexadecanoyl-2-(1-pyrenedecanoyl)-sn-glycero-3 phosphomethanol, sodium salt (Interchim, Montlucon, France), as previously described (2,20). The minimum detectable activity was 0.10 nmol/min/ml. sPLA2type IIA mass was measured as previously described (2,20). Lp-PLA2activity was measured in duplicate from ethylenediamine tetraacetic acid plasma stored at −80°C by the trichloroacetic acid precipitation procedure in 96-well plates, as described previously (21).
Baseline characteristics were compared between cases and controls taking into account matching between groups. Variables with a skewed distribution were log-transformed before being used as continuous variables in analyses, but untransformed medians and corresponding interquartile ranges are shown in the tables. To determine relationships of OxPL/apoB and Lp(a) with CVD risk factors, we calculated mean risk factor levels per tertile. In addition, odds ratios (ORs) and corresponding 95% confidence intervals (CIs) as an estimate of the relative risk of incident CAD events were calculated using conditional logistic regression analysis. The lowest OxPL/apoB and Lp(a) tertiles were used as reference category. Analyses took into account the matching for sex, age, and enrollment time and adjusted for diabetes mellitus, smoking (never, previous, current), systolic blood pressure, and LDL and high-density lipoprotein cholesterol. Analyses were also performed that took into account the matching variables and adjusted for the Framingham Risk Score (FRS). Analyses were performed for men and women separately and in addition for sexes pooled, additionally adjusting for sex. Additional analyses were performed according to tertiles of OxPL/apoB, Lp(a), sPLA2mass and activity, Lp-PLA2activity, and myeloperoxidase mass.
Correlations were computed using Spearman's rank-order method to avoid distributional assumptions, and p < 0.001 was considered significant to account for multiple comparisons. We calculated the area under the receiver-operator characteristic curve (and corresponding 95% CI) and derived both conditional and unconditional c-indexes for a set logistic regression models with FRS + each individual biomarker and with FRS + cumulative adding of the biomarkers. Statistical analyses, including the conditional logistic regression analysis, were performed using SPSS software version 12.0.1 (SPSS, Inc., Chicago, Illinois). A value of p < 0.05 was considered significant.
As expected, cases had a higher occurrence of all CVD risk factors measured than controls (Table 1).In particular, cases had significantly higher levels of OxPL/apoB, Lp(a), sPLA2mass and activity, and Lp-PLA2activity than controls, and there was a strong trend toward higher levels of myeloperoxidase mass.
Relationship of OxPL/apoB and Lp(a) levels to fatal and nonfatal CAD events
As an estimate of the relative risk of fatal and nonfatal CAD, ORs and corresponding 95% CIs were calculated by tertiles of OxPL/apoB and Lp(a) (Table 2).Analyses took into account the matching of cases and controls by age, sex, and enrollment time. Model 1 further adjusted for diabetes, smoking, systolic blood pressure, LDL, and high-density lipoprotein cholesterol, and model 2 adjusted for the FRS. There was a strong relationship between OxPL/apoB and Lp(a) with risk of future CAD. For example, in model 1, subjects in the highest tertile of OxPL/apoB had an OR for CAD events of 1.67 (95% CI: 1.32 to 2.12) compared with the lowest tertile (p < 0.001). Similarly, subjects in the highest tertile of Lp(a) had an OR of 1.64 (95% CI: 1.30 to 2.08) compared with the lowest tertile (p < 0.001). The findings using model 2 were comparable to those of model 1, and similar results were also obtained for men and women (Table 2). No significant differences were noted in either model according to age 65 years or younger versus age older than 65 years (data not shown).
For the fatal CAD end point alone, in model 1, subjects in the highest tertile of OxPL/apoB had an OR for CAD events of 1.99 (95% CI: 1.25 to 3.18) compared with the lowest tertile (p = 0.004). Similarly, subjects in the highest tertile of Lp(a) had an OR of 2.22 (95% CI: 1.44 to 3.43) compared with the lowest tertile (p < 0.001). The findings using model 2 were comparable to those of model 1, and similar results were also obtained for men and women.
Relationship of OxPL/apoB and Lp(a) to other oxidative biomarkers with fatal and nonfatal CAD events
A 3 × 3 tertile analysis was generated to assess the relationships between pairs of biomarkers in the association with risk of future CAD (Table 3).Subjects in the highest tertiles for both OxPL/apoB and sPLA2activity had a significantly elevated risk of future CAD, with an OR of 3.46 (95% CI: 2.22 to 5.42) compared with subjects in the lowest tertiles (Fig. 1A,Table 3). A similar but weaker relationship was noted for the highest tertiles of OxPL/apoB and sPLA2mass (OR: 2.39; 95% CI: 1.58 to 3.61). Strong relationships were also noted for Lp(a) and sPLA2mass and activity. For example, the OR subjects in the highest tertiles of Lp(a) and sPLA2activity was 2.97 (95% CI: 1.93 to 4.57) (Fig. 2B,Table 3). The relationship of OxPL/apoB and Lp(a) to fatal and nonfatal CAD was also accentuated in the highest tertiles (OR: 1.77, 95% CI: 1.31 to 2.37) (Fig. 2, Table 3).
For the remaining pairs of biomarkers, the highest ORs for CAD were generally observed for subjects in the highest tertile of either sPLA2activity or sPLA2mass and the highest tertiles of myeloperoxidase (Table 3). Notably, the OR was 2.86 (95% CI: 1.96 to 4.18) for the highest tertiles of sPLA2mass and sPLA2activity appeared additive (Table 3), suggesting that different biological information may be derived from each measurement.
For the fatal CAD end point alone, the ORs for risk of future CAD for subjects in the highest tertiles for both OxPL/apoB and Lp(a), sPLA2activity, sPLA2mass, Lp-PLA2activity, and myeloperoxidase mass were 2.03 (95% CI: 1.12 to 3.67), 4.56 (95% CI: 1.87 to 11.11), 5.42 (95% CI: 2.20 to 13.39), 1.84 (95% CI: 0.82 to 4.11), and 1.86 (95% CI: 0.85 and 4.09), respectively, compared with the lowest tertiles. For subjects in the highest tertiles for both Lp(a) and sPLA2activity, sPLA2mass, Lp-PLA2activity, and myeloperoxidase mass, the ORs were 4.67 (95% CI: 1.96 to 11.10), 7.27 (95% CI: 2.99 to 17.68), 1.95 (95% CI: 0.89 to 4.26), and 2.83 (95% CI: 1.26 to 6.34), respectively, compared with the lowest tertiles.
Receiver-operator characteristic c-index values
To assess the predictive value of the utility of these biomarkers above the FRS, receiver-operator characteristic unconditional c-indexes were generated. Table 4displays the c-index values of the various biomarkers. The c-index for the FRS was 0.584 (95% CI: 0.558 to 0.609), a relatively low value that reflects the fact that age and sex were already accounted for as part of the matching design. Adding individual biomarkers to the FRS shows that the c-index increased from 0.584 (95% CI: 0.558 to 0.609) to 0.618 (95% CI: 0.593 to 0.642), in progressing order of myeloperoxidase mass, Lp-PLA2activity, OxPL/apoB, high-sensitivity C-reactive protein, Lp(a), sPLA2mass, and sPLA2activity. Adding biomarkers to FRS until all biomarkers were present in the model progressively increased the c-index from 0.584 (95% CI: 0.558 to 0.609) to 0.651 (95% CI: 0.627 to 0.675 (Table 4, Online Figure 1). There were no differences in the c-index values if a conditional c-index was calculated (data not shown).
Relationship of OxPL/apoB and Lp(a) levels to the metabolic syndrome
In the overall cohort, the mean number of criteria for the metabolic syndrome was 2.5 ± 1.0, and the FRS estimated 10-year risk was 19 ± 11%. OxPL/apoB and Lp(a) levels were not statistically associated with the number of metabolic syndrome criteria or FRS estimates (Table 5).
Relationship of oxidative biomarkers to FRS
To assess whether oxidative biomarkers provided additional predictive value to the FRS, tertiles of OxPL/apoB, Lp(a), sPLA2mass, sPLA2activity, Lp-PLA2activity, and myeloperoxidase mass were evaluated within each FRS risk estimate (Fig. 3).In the low FRS categories, the OxPL/apoB and Lp(a) measures did not provide additional predictive value, but sPLA2mass and activity showed a near tripling of the OR. However, in the high FRS estimates, OxPL/apoB and Lp(a) more than doubled the OR for predicting new cardiovascular events, sPLA2mass and activity were slightly less predictive, and Lp-PLA2activity and myeloperoxidase mass did not appear to add any additional discriminative value within the FRS risk categories.
The combination of OxPL/apoB and sPLA2activity was particularly useful in reflecting risk adjustment among the FRS categories. For example, in the low FRS category, compared with the lowest tertiles, the highest tertiles of OxPL/apoB and sPLA2activity were associated with an OR of 8.48 (95% CI: 2.98 to 24.16; p < 0.001), 5.01 (95% CI: 2.28 to 11.41, p < 0.001) in the medium FRS category, and 14.35 (95% CI: 6.21 to 33.17; p < 0.001) in the high FRS category.
This case-control study nested within the prospectively followed EPIC-Norfolk cohort demonstrates that elevated baseline levels of OxPL/apoB and Lp(a) are strongly associated with an increased risk of fatal and nonfatal CAD events. Furthermore, increased levels of phospholipases involved in the breakdown of OxPL, particularly sPLA2activity and mass, potentiated the risk mediated by either OxPL/apoB or Lp(a). For the first time, this study links distinct oxidative processes, ranging from oxidative substrates, carriers of OxPL such as Lp(a), and enzymes that either generate or degrade oxidized lipids, in the association of fatal and nonfatal CAD events. Individually these oxidative biomarkers were independent of traditional risk factors and the FRS, and collectively they modestly increased the risk prediction of CAD events, likely because they represent pathophysiologically related but distinct pathways.
OxPL are key components of minimally oxidized LDL, fully oxidized LDL, apoptotic cells, and atherosclerotic lesions and are important contributors to atherogenesis by activating proinflammatory genes, leading to inflammatory cascades in the arterial wall. This study provides insights into the atherogenicity of OxPL/apoB and Lp(a) and related oxidative biomarkers in several novel ways. It demonstrates in a large, prospective nested case-control study that OxPL/apoB levels are strongly and independently associated with future risk of fatal and nonfatal CAD events. These data confirm the findings from the smaller but prospective Bruneck study in which elevated baseline levels of OxPL/apoB levels predicted future risk of all-cause mortality, myocardial infarction, and stroke (13). Importantly, it also demonstrates for the first time that evaluating OxPL/apoB and Lp(a) together in the same model further increases the OR for CAD events. This suggests that although high Lp(a) levels can be associated with high OxPL/apoB levels in many patients, there may be a divergence of levels in other patients, implying that not all Lp(a) particles carry the same amount of E06-detectable OxPL. One potential explanation influencing this observation may be the underlying differences in the genetic makeup and clinical presentation of the individuals or patient cohorts in these studies. For example, in the Mayo Clinic study (11), OxPL/apoB levels were an independent predictor of angiographically determined CAD in patients younger than 60 years of age, even with Lp(a) in the multivariable model. However, in the Bruneck study evaluating carotid and femoral atherosclerosis in healthy subjects, OxPL/apoB and Lp(a) provided similar risk prediction (13). New insights into the OxPL-Lp(a) relationship were recently obtained from the Dallas Heart Study in which it was demonstrated that OxPL/apoB levels vary significantly according to race, with the highest levels found in blacks, followed by whites and then Hispanics (24). Furthermore, OxPL/apoB levels were inversely associated with apolipoprotein(a) isoform size. Despite differences in Lp(a) levels between racial/ethnic groups, a similar relationship was present between OxPL/apoB and small apolipoprotein(a) isoforms, but not large isoforms, suggesting that elevated OxPL/apoB levels in the setting of small apolipoprotein(a) isoforms may be the key determinant of CVD risk in this relationship.
This study demonstrates that the association of OxPL/apoB and Lp(a) with CAD was independent of measures of the metabolic syndrome. Furthermore OxPL/apoB, Lp(a), and sPLA2activity and mass were also independent of other established CVD risk factors and FRS estimates. This was noted despite the fact that age and sex were already adjusted for in both groups, and it is possible that these recalibrations of FRS risk estimates are underestimated. Interestingly, sPLA2activity and mass significantly increased the predictive value of the low-risk FRS category. On a community-wide basis, this is a large group of subjects who are generally not treated for CVD risk. For this group in particular, these measures may be useful to further stratify subjects now categorized by the FRS as low risk into higher risk categories, which might affect treatment decisions.
This study links OxPL/apoB and Lp(a) in the association with CAD with other clinically relevant oxidative biomarkers and particularly with sPLA2type IIA mass and sPLA2activity. The combination of either OxPL/apoB or Lp(a) with sPLA2activity was a particularly strong marker of risk in this study, particularly for fatal CAD. Elevated levels of sPLA2type IIA mass and sPLA2activity, which encompasses sPLA2types IIA, V, and X, were previously shown to be independent predictors of death and new or recurrent myocardial infarction in healthy subjects and in patients with acute coronary syndromes (2,21,25,26). The fact that sPLA2activity levels have additive predictive value for OxPL/apoB and Lp(a) suggests that these factors may mediate risk at different points in the continuum of atherogenesis.
We had previously demonstrated in the Bruneck study (13) a similar relationship between OxPL/apoB or Lp(a) and Lp-PLA2activity, with the nearly doubling of the hazard ratio for congestive heart disease. However, in contrast to the Bruneck study, a weak association was noted in EPIC-Norfolk. Differences in methodology (prospective vs. case control) or the size of the study (82 vs. 763 events) or other factors may explain the disparate findings. Similarly, only a weak potentiation of risk of most of the other oxidative biomarkers measured in this study was noted with myeloperoxidase.
This is the first analysis of receiver-operator characteristic c-index values of a combination of oxidative biomarkers, which were evaluated by adding them to FRS estimates individually and in combination. It must be emphasized that c-index values are an imperfect measure and should not be used in isolation for clinical risk prediction (27). In this study, age and sex, which generally contribute significantly to the c-index, were not part of the c-index due to the nested case-control methodology. In combination, adding individual biomarkers consecutively added to the c-index, ultimately increasing it from 0.584 to 0.651, a change similar to recently reported studies of nonoxidative biomarkers (28).
A strong database exists with assays in detecting OxPL and oxidized LDL in their association with CVD and CVD events (6–8). Additionally, previous studies have evaluated other oxidative biomarkers in subjects with congestive heart disease, such as urinary isoprostanes (29), serum malondialdehyde levels measured as thiobarbituric reactive substances (30), and glutathione redox state (31). In a recent study (32), the relationship of OxPL/apoB, Lp(a), and immunoglobulin G and M autoantibodies to malondialdehyde-LDL, immunoglobulin G and M apoB- immune complexes, Lp-PLA2activity, oxidized LDL by the Mercodia assay, and urinary F2 isoprostanes were evaluated in 160 subjects with hypercholesterolemia treated with various doses of different statins. Remarkably, the baseline levels and the response to various statins on plasma levels of the biomarkers were quite variable, and no strong relationships were noted among these biomarkers. Thus, even though these biomarkers are conceptually related, they did not seem to reflect the same pathophysiology. The overall reported experience of many of these markers in predicting cardiovascular events is limited at this stage, and certain limitations exist. For example, urinary isoprostanes correlate with cardiovascular risk factors but are not widely available and require significant expertise and instrumentation to measure accurately. Malondialdehyde measures can be nonspecific because they are generated by sources other than lipid hydroperoxides such as platelets, glucose, bilirubin, and amino acids. However, they were predictive of new events in the PREVENT (Prospective Randomized Evaluation of the Vascular Effects of Norvasc Trial) study (30). Glutathione redox state is a promising oxidative marker, and elevated levels predict subclinical atherosclerosis in unselected populations, but clinical outcomes data are awaited to assess their clinical predictive value (31).
Previous studies have not generally incorporated modifiable biomarkers in their multiple biomarker approaches to improve risk stratification for CVDs. Even though the present data should not be interpreted as implying a clinical benefit from reduction in these biomarkers, it is interesting to note that most of these oxidative biomarkers can be modified by therapeutic interventions such as statins and other CVD therapies (33). In addition, sPLA2and Lp-PLA2inhibitors are currently undergoing evaluation in clinical trials to assess whether they reduce the incidence of CVD events (34,35). Thus, if confirmed by prospective therapeutic studies, these results may have important implications for patient selection for treatment with approved or emerging CVD therapies.
The c-index values in this study were relatively low due to the fact that controls were matched to cases by sex and age, thus removing a substantial amount of their discriminatory ability. The nested case-control design only allowed us to assess the relative but not absolute risk prediction of oxidative biomarkers.
Oxidation-specific biomarkers are strongly associated with CAD events and can be a useful adjunct to traditional risk factors or FRS in risk prediction of future CAD in initially healthy subjects.
For a supplementary figure, please see the online version of this article.
Oxidation-Specific Biomarkers, Lipoprotein (a) and Risk of Fatal and non-Fatal Coronary Events
EPIC-Norfolk is supported by program grants from the Medical Research Council UKand Cancer Research UK, with additional support from the European Union, Stroke Association, British Heart Foundation, Department of Health, Food Standards Agency, and the Wellcome Trust. This study was funded by the Fondation Leducq. Drs. Mallat and Tedgui have received a Contrat d'Interface from Assistance Publique-Hôpitaux de Paris, Paris, France. Drs. Tsimikas and Witztum are inventors of patents owned by the University of California for the clinical use of oxidation-specific antibodies. Drs. Mallat, Tedgui and Benessiano are listed as co-inventors on 2 patents filed by INSERM relating to cardiovascular prognostic and diagnostic markers. Drs. Mallat and Tedgui are consultants to ATEROVAX. Drs. Tsimikas and Witztum are directors and hold equity in Atherotope, Inc. David Harrison, MD, served as Guest Editor for this paper.
- Abbreviations and Acronyms
- coronary artery disease
- confidence interval
- cardiovascular disease
- Framingham Risk Score
- low-density lipoprotein
- lipoprotein-associated phospholipase A2
- odds ratio
- oxidized phospholipid
- oxidized phospholipids on apolipoprotein B-100
- secretory phospholipase A2
- Received November 24, 2009.
- Revision received April 20, 2010.
- Accepted April 20, 2010.
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