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1.  The association between circulating lipoprotein(a) and type 2 diabetes: is it causal? 
Diabetes  2013;63(1):332-342.
Epidemiological evidence supports a direct and causal association between lipoprotein(a) [Lp(a)] levels and coronary risk, but the nature of the association between Lp(a) levels and risk of type 2 diabetes (T2D) is unclear. In this study, we assessed the association of Lp(a) levels with risk of incident T2D, and tested whether Lp(a) levels are causally linked to T2D. We analysed data on 18,490 participants from the EPIC-Norfolk cohort that included adults aged 40-79 years at baseline 1993-1997. During average 10 years of follow-up, 593 participants developed incident T2D. Cox regression models were used to estimate the association between Lp(a) levels and T2D. In Mendelian randomisation analyses, based on EPIC-Norfolk combined with DIAGRAM data involving a total of 10,088 diabetes cases and 68,346 controls, we used a genetic variant (rs10455872) as an instrument to test whether the association between Lp(a) levels and T2D is causal. In adjusted analyses there was an inverse association between Lp(a) levels and T2D: hazard ratio (HR) was 0.63 (95% confidence interval 0.49-0.81; p-trend=0.003) comparing the top versus bottom quintile of Lp(a). In EPIC-Norfolk, a 1-SD increase in logLp(a) was associated with a lower risk of T2D (OR=0.88, 95%CI: 0.80-0.95). However, in Mendelian randomisation analyses, a 1-SD increase in logLp(a) due to rs10455872, which explained 26.8% of the variability in Lp(a) levels, was not associated with risk of T2D (OR=1.03, 95%CI: 0.96-1.10, p = 0.41). These prospective findings demonstrate a strong inverse association of Lp(a) levels with risk of T2D. However, a genetic variant that elevated Lp(a) levels was not associated with risk of T2D, suggesting that elevated Lp(a) levels are not causally associated with a lower risk of T2D.
PMCID: PMC4246060  PMID: 24089516
lipoprotein(a); type 2 diabetes; causal association; coronary heart disease; hazard ratio; Mendelian randomisation; prospective study
2.  Chemokine Ligand 2 Genetic Variants, serum MCP-1 Levels and the Risk of Coronary Artery Disease 
In humans, evidence about the association between levels of monocyte chemoattractant protein-1 (MCP-1), its coding gene chemokine (C-C motif) ligand 2 (CCL2) and risk of coronary artery disease (CAD) is contradictory.
Methods and Results
We performed a nested case-control study in the prospective EPIC-Norfolk cohort investigating the relation between CCL2 single nucleotide polymorphisms (SNP)’s, MCP-1 concentrations and the risk for future CAD. Cases (n = 1138) were apparently healthy men and women aged 45-79 years who developed fatal or nonfatal CAD during a mean follow-up of 6 years. Controls (n=2237) were matched by age, sex, and enrollment time. Using linear regression analysis no association between CCL2 SNPs and MCP-1 serum concentrations became apparent, nor did we find a significant association between MCP-1 serum levels and risk of future CAD. Finally, Cox regression analysis showed no significant association between CCL2 SNPs and the future CAD risk. In addition we did not find any robust associations between the CCL2 haplotypes and MCP-1 serum concentration or future CAD risk.
Our data do not support previous publications indicating that MCP-1 is involved in the pathogenesis of CAD.
PMCID: PMC4210837  PMID: 20431065
Atherosclerosis; Coronary Artery Disease; CCL2; MCP-1 and Single nucleotide polymorphism
3.  Lipoprotein (a) and risk of coronary, cerebrovascular and peripheral artery disease; the EPIC-Norfolk prospective population study 
While the association between circulating levels of lipoprotein(a) (Lp(a)) and risk of coronary artery disease (CAD) and stroke is well established, its role in risk of peripheral artery disease (PAD) remains unclear. Here, we examine the association between Lp(a) levels and PAD in a large prospective cohort. To contextualise these findings, we also examined the association between Lp(a) levels and risk of stroke and CAD and studied the role of LDL as an effect modifier of Lp(a) associated cardiovascular risk.
Methods and Results
Lp(a) levels were measured in apparently healthy participants in the EPIC-Norfolk cohort. Cox regression was used to quantify the association between Lp(a) levels and risk of PAD, stroke and CAD outcomes. During 212,981 person-years at risk, a total of 2365 CAD, 284 ischemic stroke and 596 PAD events occurred in 18,720 participants. Lp(a) was associated with PAD and CAD outcomes but not with ischemic stroke (HR per 2.7 fold increase in Lp(a) of 1.37, 95% CI 1.25-1.50, 1.13, 95% CI 1.04-1.22 and 0.91, 95%CI 0.79-1.03 respectively). LDL-C levels did not modify these associations.
Lp(a) levels were associated with future PAD and CAD events. The association between Lp(a) and cardiovascular disease was not modified by LDL-C levels.
PMCID: PMC4210842  PMID: 23065826
4.  Levels and changes of HDL cholesterol and apolipoprotein A-I in relation to risk of cardiovascular events among statin-treated patients; a meta-analysis 
Circulation  2013;128(14):10.1161/CIRCULATIONAHA.113.002670.
It is unclear whether levels of high-density lipoprotein cholesterol (HDL-C) or apolipoprotein A-I (apoA-I) remain inversely associated with cardiovascular risk among patients who achieve very low levels of low-density lipoprotein cholesterol (LDL-C) on statin therapy. It is also unknown whether a rise in HDL-C or apoA-I after initiation of statin therapy is associated with a reduced cardiovascular risk.
Methods and results
We performed a meta-analysis of 8 statin trials in which lipids and apolipoproteins were determined in all study participants at baseline and at 1-year follow-up. Individual patient data were obtained for 38,153 trial participants allocated to statin therapy, of whom 5387 suffered a major cardiovascular event. HDL-C levels were associated with a reduced risk of major cardiovascular events (adjusted hazard ratio 0.83, 95%CI 0.81–0.86 per 1 standard deviation increment), as were apoA-I levels (HR 0.79, 95%CI 0.72–0.82). This association was also observed among patients achieving on-statin LDL-C levels < 50 mg/dL. An increase of HDL-C was not associated with reduced cardiovascular risk (HR 0.98, 95%CI 0.94–1.01 per 1 standard deviation increment), whereas a rise in apoA-I was (HR 0.93, 95%CI 0.90–0.97).
Among patients treated with statin therapy, HDL-C and apoA-I levels were strongly associated with a reduced cardiovascular risk, even among those achieving very low LDL-C. An apoA-I increase was associated with a reduced risk of major cardiovascular events, whereas for HDL-C this was not the case. These findings suggest that therapies that increase apoA-I concentration require further exploration with regard to cardiovascular risk reduction.
PMCID: PMC3807966  PMID: 23965489
high-density lipoprotein cholesterol; apolipoprotein; meta-analysis; cardiovascular outcomes
5.  Distribution of lipid parameters according to different socio-economic indicators- the EPIC-Norfolk prospective population study 
BMC Public Health  2014;14(1):782.
Data on the relationship between plasma levels of cholesterol and triglycerides and social class have been inconsistent. Most previous studies have used one classification of social class.
This was a cross-sectional population based study with data on occupational social class, educational level obtained using a detailed health and lifestyle questionnaire. A total of 10,147 men and 12,304 women aged 45–80 years living in Norfolk, United Kingdom, were recruited using general practice age-sex registers as part of the European Prospective Investigation into Cancer (EPIC-Norfolk). Plasma levels of cholesterol and triglycerides were measured in baseline samples. Social class was classified according to three classifications: occupation, educational level, and area deprivation score according to Townsend deprivation index. Differences in lipid levels by socio-economic status indices were quantified by analysis of variance (ANOVA) and multiple linear regression after adjusting for body mass index and alcohol consumption.
Total cholesterol levels were associated with occupational level among men, and with educational level among women. Triglyceride levels were associated with educational level and occupational level among women, but the latter association was lost after adjustment for age and body mass index. HDL-cholesterol levels were associated with both educational level and educational level among men and women. The relationships with educational level were substantially attenuated by adjustment for age, body mass index and alcohol use, whereas the association with educational class was retained upon adjustment. LDL-cholesterol levels were not associated with social class indices among men, but a positive association was observed with educational class among women. This association was not affected by adjustment for age, body mass index and alcohol use.
The findings of this study suggest that there are sex differences in the association between socio-economic status and serum lipid levels. The variations in lipid profile with socio-economic status may be largely attributed to potentially modifiable factors such as obesity, physical activity and dietary intake.
PMCID: PMC4155077  PMID: 25179437
6.  Genetic variants influencing circulating lipid levels and risk of coronary artery disease 
Genetic studies might provide new insights into the biological mechanisms underlying lipid metabolism and risk of CAD. We therefore conducted a genome-wide association study to identify novel genetic determinants of LDL-c, HDL-c and triglycerides.
Methods and results
We combined genome-wide association data from eight studies, comprising up to 17,723 participants with information on circulating lipid concentrations. We did independent replication studies in up to 37,774 participants from eight populations and also in a population of Indian Asian descent. We also assessed the association between SNPs at lipid loci and risk of CAD in up to 9,633 cases and 38,684 controls.
We identified four novel genetic loci that showed reproducible associations with lipids (P values 1.6 × 10−8 to 3.1 × 10−10). These include a potentially functional SNP in the SLC39A8 gene for HDL-c, a SNP near the MYLIP/GMPR and PPP1R3B genes for LDL-c and at the AFF1 gene for triglycerides. SNPs showing strong statistical association with one or more lipid traits at the CELSR2, APOB, APOE-C1-C4-C2 cluster, LPL, ZNF259-APOA5-A4-C3-A1 cluster and TRIB1 loci were also associated with CAD risk (P values 1.1 × 10−3 to 1.2 × 10−9).
We have identified four novel loci associated with circulating lipids. We also show that in addition to those that are largely associated with LDL-c, genetic loci mainly associated with circulating triglycerides and HDL-c are also associated with risk of CAD. These findings potentially provide new insights into the biological mechanisms underlying lipid metabolism and CAD risk.
PMCID: PMC3891568  PMID: 20864672
lipids; lipoproteins; genetics; epidemiology
7.  Secretory Phospholipase A2-IIA and Cardiovascular Disease 
Holmes, Michael V. | Simon, Tabassome | Exeter, Holly J. | Folkersen, Lasse | Asselbergs, Folkert W. | Guardiola, Montse | Cooper, Jackie A. | Palmen, Jutta | Hubacek, Jaroslav A. | Carruthers, Kathryn F. | Horne, Benjamin D. | Brunisholz, Kimberly D. | Mega, Jessica L. | van Iperen, Erik P.A. | Li, Mingyao | Leusink, Maarten | Trompet, Stella | Verschuren, Jeffrey J.W. | Hovingh, G. Kees | Dehghan, Abbas | Nelson, Christopher P. | Kotti, Salma | Danchin, Nicolas | Scholz, Markus | Haase, Christiane L. | Rothenbacher, Dietrich | Swerdlow, Daniel I. | Kuchenbaecker, Karoline B. | Staines-Urias, Eleonora | Goel, Anuj | van 't Hooft, Ferdinand | Gertow, Karl | de Faire, Ulf | Panayiotou, Andrie G. | Tremoli, Elena | Baldassarre, Damiano | Veglia, Fabrizio | Holdt, Lesca M. | Beutner, Frank | Gansevoort, Ron T. | Navis, Gerjan J. | Mateo Leach, Irene | Breitling, Lutz P. | Brenner, Hermann | Thiery, Joachim | Dallmeier, Dhayana | Franco-Cereceda, Anders | Boer, Jolanda M.A. | Stephens, Jeffrey W. | Hofker, Marten H. | Tedgui, Alain | Hofman, Albert | Uitterlinden, André G. | Adamkova, Vera | Pitha, Jan | Onland-Moret, N. Charlotte | Cramer, Maarten J. | Nathoe, Hendrik M. | Spiering, Wilko | Klungel, Olaf H. | Kumari, Meena | Whincup, Peter H. | Morrow, David A. | Braund, Peter S. | Hall, Alistair S. | Olsson, Anders G. | Doevendans, Pieter A. | Trip, Mieke D. | Tobin, Martin D. | Hamsten, Anders | Watkins, Hugh | Koenig, Wolfgang | Nicolaides, Andrew N. | Teupser, Daniel | Day, Ian N.M. | Carlquist, John F. | Gaunt, Tom R. | Ford, Ian | Sattar, Naveed | Tsimikas, Sotirios | Schwartz, Gregory G. | Lawlor, Debbie A. | Morris, Richard W. | Sandhu, Manjinder S. | Poledne, Rudolf | Maitland-van der Zee, Anke H. | Khaw, Kay-Tee | Keating, Brendan J. | van der Harst, Pim | Price, Jackie F. | Mehta, Shamir R. | Yusuf, Salim | Witteman, Jaqueline C.M. | Franco, Oscar H. | Jukema, J. Wouter | de Knijff, Peter | Tybjaerg-Hansen, Anne | Rader, Daniel J. | Farrall, Martin | Samani, Nilesh J. | Kivimaki, Mika | Fox, Keith A.A. | Humphries, Steve E. | Anderson, Jeffrey L. | Boekholdt, S. Matthijs | Palmer, Tom M. | Eriksson, Per | Paré, Guillaume | Hingorani, Aroon D. | Sabatine, Marc S. | Mallat, Ziad | Casas, Juan P. | Talmud, Philippa J.
This study sought to investigate the role of secretory phospholipase A2 (sPLA2)-IIA in cardiovascular disease.
Higher circulating levels of sPLA2-IIA mass or sPLA2 enzyme activity have been associated with increased risk of cardiovascular events. However, it is not clear if this association is causal. A recent phase III clinical trial of an sPLA2 inhibitor (varespladib) was stopped prematurely for lack of efficacy.
We conducted a Mendelian randomization meta-analysis of 19 general population studies (8,021 incident, 7,513 prevalent major vascular events [MVE] in 74,683 individuals) and 10 acute coronary syndrome (ACS) cohorts (2,520 recurrent MVE in 18,355 individuals) using rs11573156, a variant in PLA2G2A encoding the sPLA2-IIA isoenzyme, as an instrumental variable.
PLA2G2A rs11573156 C allele associated with lower circulating sPLA2-IIA mass (38% to 44%) and sPLA2 enzyme activity (3% to 23%) per C allele. The odds ratio (OR) for MVE per rs11573156 C allele was 1.02 (95% confidence interval [CI]: 0.98 to 1.06) in general populations and 0.96 (95% CI: 0.90 to 1.03) in ACS cohorts. In the general population studies, the OR derived from the genetic instrumental variable analysis for MVE for a 1-log unit lower sPLA2-IIA mass was 1.04 (95% CI: 0.96 to 1.13), and differed from the non-genetic observational estimate (OR: 0.69; 95% CI: 0.61 to 0.79). In the ACS cohorts, both the genetic instrumental variable and observational ORs showed a null association with MVE. Instrumental variable analysis failed to show associations between sPLA2 enzyme activity and MVE.
Reducing sPLA2-IIA mass is unlikely to be a useful therapeutic goal for preventing cardiovascular events.
PMCID: PMC3826105  PMID: 23916927
cardiovascular diseases; drug development; epidemiology; genetics; Mendelian randomization; ACS, acute coronary syndrome(s); CI, confidence interval; LDL-C, low-density lipoprotein cholesterol; MI, myocardial infarction; MVE, major vascular events; OR, odds ratio; RCT, randomized clinical trial; SNP, single-nucleotide polymorphism; sPLA2, secretory phospholipase A2
8.  Determinants of Residual Risk in Secondary Prevention Patients Treated with High-Versus Low-Dose Statin Therapy: The Treating to New Targets (TNT) Study 
Circulation  2012;125(16):1979-1987.
Cardiovascular events occur among statin-treated patients, albeit at lower rates. Risk factors for this “residual risk” have not been studied comprehensively. We aimed to identify determinants of this risk above and beyond lipid-related risk factors.
Methods and Results
9,251 coronary patients with LDL cholesterol<130 mg/dL randomized to double-blind atorvastatin 10 or 80 mg/day in the Treating to New Targets (TNT) study had complete on-treatment 1-year lipid data. Median follow-up was 4.9 years. The primary endpoint was major cardiovascular events (n=729): coronary death, non-fatal myocardial infarction, resuscitation after cardiac arrest, or fatal or non-fatal stroke. Multivariable determinants of increased risk were older age (adjusted hazard ratio 1.13 per 1-SD [8.8 years], 95% CI 1.04–1.23), increased body-mass index (BMI) (1.09, 1.02–1.17 per 4.5 kg/m2), male gender (1.33, 1.07–1.65), hypertension (1.38, 1.17–1.63), diabetes (1.33, 1.11–1.60), baseline apolipoprotein B (1.19, 1.11–1.28 per 19 mg/dL) and blood urea nitrogen (1.10, 1.03–1.17 per 4.9 mg/dL), in addition to current smoking, prior cardiovascular disease, and calcium channel blocker use. Determinants of decreased risk were high-dose statin (0.82, 0.70–0.94), aspirin use (0.67, 0.56–0.81), and baseline apolipoprotein A-I (0.91, 0.84–0.99 per 25 mg/dL). On-treatment 1-year lipids or apolipoproteins were not additionally associated with risk in multivariable models. Known baseline variables performed moderately well in discriminating future cases from non-cases (Harrell’s c-index=0.679).
Determinants of residual risk in statin-treated secondary prevention patients included lipid-related and non-lipid factors such as baseline apolipoproteins, increased BMI, smoking, hypertension, and diabetes. A multi-faceted prevention approach should be underscored to address this risk.
Clinical Trial Registration Information; Unique identifier: NCT00327691
PMCID: PMC3338158  PMID: 22461416
apolipoproteins; risk factors; risk prediction; secondary prevention
9.  On-Treatment Non-HDL Cholesterol, Apolipoprotein B, Triglycerides, and Lipid Ratios in Relation to Residual Vascular Risk after Treatment with Potent Statin Therapy: The JUPITER Trial 
To determine whether residual risk after high-dose statin therapy for primary prevention individuals with low LDL cholesterol (LDL-C) is related to on-treatment apolipoprotein B, non-HDL cholesterol (non-HDL-C), or lipid ratios, and how they compare with on-treatment LDL cholesterol (LDL-C).
Guidelines focus on LDL-C as the primary target of therapy, yet residual risk for cardiovascular disease (CVD) among statin-treated individuals remains high and not fully explained.
Participants in the randomized placebo-controlled JUPITER trial were adults without diabetes or CVD, with baseline LDL-C<130 mg/dL, high-sensitivity C-reactive protein ≥2 mg/L, and triglycerides <500 mg/dL. Individuals allocated to rosuvastatin 20 mg daily with baseline and on-treatment lipids and lipoproteins were examined in relation to the primary endpoint of incident CVD (non-fatal myocardial infarction or stroke, hospitalization for unstable angina, arterial revascularization, or cardiovascular death).
Using separate multivariate Cox models, statistically significant associations of a similar magnitude with residual risk of CVD were found for on-treatment LDL-C, non-HDL-C, apolipoprotein B, total/HDL-C, LDL-C/HDL-C, and apolipoprotein B/A-1. The respective adjusted standardized hazard ratios (95% confidence intervals) for each of these measures were 1.31 (1.09–1.56), 1.25 (1.04–1.50), 1.27 (1.06–1.53), 1.22 (1.03–1.44), 1.29 (1.09–1.52), and 1.27 (1.09–1.49). The overall residual risk and the risk associated with these measures decreased among participants achieving on-treatment LDL-C ≤70 mg/dL, on-treatment non-HDL-C ≤100 mg/dL, or on-treatment apolipoprotein B ≤80 mg/dL. By contrast, on-treatment triglycerides showed no association with CVD.
In this primary prevention trial of non-diabetic individuals with low LDL-C, on-treatment LDL-C was as valuable as non-HDL-C, apolipoprotein B, or ratios in predicting residual risk.
PMCID: PMC3338194  PMID: 22516441
apolipoproteins; lipids; lipoproteins; primary prevention; trials
10.  Validation of a model to investigate the effects of modifying cardiovascular disease (CVD) risk factors on the burden of CVD: the rotterdam ischemic heart disease and stroke computer simulation (RISC) model 
BMC Medicine  2012;10:158.
We developed a Monte Carlo Markov model designed to investigate the effects of modifying cardiovascular disease (CVD) risk factors on the burden of CVD. Internal, predictive, and external validity of the model have not yet been established.
The Rotterdam Ischemic Heart Disease and Stroke Computer Simulation (RISC) model was developed using data covering 5 years of follow-up from the Rotterdam Study. To prove 1) internal and 2) predictive validity, the incidences of coronary heart disease (CHD), stroke, CVD death, and non-CVD death simulated by the model over a 13-year period were compared with those recorded for 3,478 participants in the Rotterdam Study with at least 13 years of follow-up. 3) External validity was verified using 10 years of follow-up data from the European Prospective Investigation of Cancer (EPIC)-Norfolk study of 25,492 participants, for whom CVD and non-CVD mortality was compared.
At year 5, the observed incidences (with simulated incidences in brackets) of CHD, stroke, and CVD and non-CVD mortality for the 3,478 Rotterdam Study participants were 5.30% (4.68%), 3.60% (3.23%), 4.70% (4.80%), and 7.50% (7.96%), respectively. At year 13, these percentages were 10.60% (10.91%), 9.90% (9.13%), 14.20% (15.12%), and 24.30% (23.42%). After recalibrating the model for the EPIC-Norfolk population, the 10-year observed (simulated) incidences of CVD and non-CVD mortality were 3.70% (4.95%) and 6.50% (6.29%). All observed incidences fell well within the 95% credibility intervals of the simulated incidences.
We have confirmed the internal, predictive, and external validity of the RISC model. These findings provide a basis for analyzing the effects of modifying cardiovascular disease risk factors on the burden of CVD with the RISC model.
PMCID: PMC3566939  PMID: 23217019
Cardiovascular disease prevention; Simulation modeling; Model validation
11.  R1: The relationship between plasma Angiopoietin-like protein 4 (Angptl4) levels, ANGPTL4 genotype and coronary heart disease risk 
To investigate the relationship between Angiopoietin-like protein 4 (Angptl4) levels, CHD biomarkers and ANGPTL4 variants.
Methods and Results
Plasma Angptl4 was quantified in 666 subjects of the Northwick Park Heart Study II using a validated ELISA. Seven ANGPTL4 SNPs were genotyped and CHD biomarkers assessed in the whole cohort (n=2775). Weighted mean (±SD) plasma Angptl4 levels were 10.0(±11.0) ng/ml. Plasma Angptl4 concentration correlated positively with age (r=0.15, P<0.001), body fat mass (r=0.19, P=0.003) but negatively with plasma HDL-cholesterol (r=−0.13, P=0.01). No correlation with triglycerides was observed. T266M was independently associated with plasma Angptl4 levels (P<0.001), but not associated with triglycerides or with CHD risk in the meta-analysis of five studies (4,061 cases/15,395 controls). E40K showed no independent association with plasma Angptl4 levels. In HEK293 and Huh7 cells compared to wild-type, E40K and T266M showed significantly altered synthesis and secretion, respectively.
These data suggest that circulating Angptl4 levels do not influence triglyceride levels or CHD risk since (1) Angptl4 levels were not correlated with triglycerides, (2) T266M, although associated with Angptl4 levels, showed no association with plasma triglycerides (3) Triglyceride-lowering E40K did not influence Angptl4 levels. These results provide new insights into the role of Angptl4 in triglyceride metabolism.
PMCID: PMC3319296  PMID: 20829508
Angplt4; E40K; T266M; cardiovascular disease; LPL
12.  Large-scale association analyses identifies 13 new susceptibility loci for coronary artery disease 
Schunkert, Heribert | König, Inke R. | Kathiresan, Sekar | Reilly, Muredach P. | Assimes, Themistocles L. | Holm, Hilma | Preuss, Michael | Stewart, Alexandre F. R. | Barbalic, Maja | Gieger, Christian | Absher, Devin | Aherrahrou, Zouhair | Allayee, Hooman | Altshuler, David | Anand, Sonia S. | Andersen, Karl | Anderson, Jeffrey L. | Ardissino, Diego | Ball, Stephen G. | Balmforth, Anthony J. | Barnes, Timothy A. | Becker, Diane M. | Becker, Lewis C. | Berger, Klaus | Bis, Joshua C. | Boekholdt, S. Matthijs | Boerwinkle, Eric | Braund, Peter S. | Brown, Morris J. | Burnett, Mary Susan | Buysschaert, Ian | Carlquist, Cardiogenics, John F. | Chen, Li | Cichon, Sven | Codd, Veryan | Davies, Robert W. | Dedoussis, George | Dehghan, Abbas | Demissie, Serkalem | Devaney, Joseph M. | Do, Ron | Doering, Angela | Eifert, Sandra | El Mokhtari, Nour Eddine | Ellis, Stephen G. | Elosua, Roberto | Engert, James C. | Epstein, Stephen E. | Faire, Ulf de | Fischer, Marcus | Folsom, Aaron R. | Freyer, Jennifer | Gigante, Bruna | Girelli, Domenico | Gretarsdottir, Solveig | Gudnason, Vilmundur | Gulcher, Jeffrey R. | Halperin, Eran | Hammond, Naomi | Hazen, Stanley L. | Hofman, Albert | Horne, Benjamin D. | Illig, Thomas | Iribarren, Carlos | Jones, Gregory T. | Jukema, J.Wouter | Kaiser, Michael A. | Kaplan, Lee M. | Kastelein, John J.P. | Khaw, Kay-Tee | Knowles, Joshua W. | Kolovou, Genovefa | Kong, Augustine | Laaksonen, Reijo | Lambrechts, Diether | Leander, Karin | Lettre, Guillaume | Li, Mingyao | Lieb, Wolfgang | Linsel-Nitschke, Patrick | Loley, Christina | Lotery, Andrew J. | Mannucci, Pier M. | Maouche, Seraya | Martinelli, Nicola | McKeown, Pascal P. | Meisinger, Christa | Meitinger, Thomas | Melander, Olle | Merlini, Pier Angelica | Mooser, Vincent | Morgan, Thomas | Mühleisen, Thomas W. | Muhlestein, Joseph B. | Münzel, Thomas | Musunuru, Kiran | Nahrstaedt, Janja | Nelson, Christopher P. | Nöthen, Markus M. | Olivieri, Oliviero | Patel, Riyaz S. | Patterson, Chris C. | Peters, Annette | Peyvandi, Flora | Qu, Liming | Quyyumi, Arshed A. | Rader, Daniel J. | Rallidis, Loukianos S. | Rice, Catherine | Rosendaal, Frits R. | Rubin, Diana | Salomaa, Veikko | Sampietro, M. Lourdes | Sandhu, Manj S. | Schadt, Eric | Schäfer, Arne | Schillert, Arne | Schreiber, Stefan | Schrezenmeir, Jürgen | Schwartz, Stephen M. | Siscovick, David S. | Sivananthan, Mohan | Sivapalaratnam, Suthesh | Smith, Albert | Smith, Tamara B. | Snoep, Jaapjan D. | Soranzo, Nicole | Spertus, John A. | Stark, Klaus | Stirrups, Kathy | Stoll, Monika | Tang, W. H. Wilson | Tennstedt, Stephanie | Thorgeirsson, Gudmundur | Thorleifsson, Gudmar | Tomaszewski, Maciej | Uitterlinden, Andre G. | van Rij, Andre M. | Voight, Benjamin F. | Wareham, Nick J. | Wells, George A. | Wichmann, H.-Erich | Wild, Philipp S. | Willenborg, Christina | Witteman, Jaqueline C. M. | Wright, Benjamin J. | Ye, Shu | Zeller, Tanja | Ziegler, Andreas | Cambien, Francois | Goodall, Alison H. | Cupples, L. Adrienne | Quertermous, Thomas | März, Winfried | Hengstenberg, Christian | Blankenberg, Stefan | Ouwehand, Willem H. | Hall, Alistair S. | Deloukas, Panos | Thompson, John R. | Stefansson, Kari | Roberts, Robert | Thorsteinsdottir, Unnur | O’Donnell, Christopher J. | McPherson, Ruth | Erdmann, Jeanette | Samani, Nilesh J.
Nature genetics  2011;43(4):333-338.
We performed a meta-analysis of 14 genome-wide association studies of coronary artery disease (CAD) comprising 22,233 cases and 64,762 controls of European descent, followed by genotyping of top association signals in 60,738 additional individuals. This genomic analysis identified 13 novel loci harboring one or more SNPs that were associated with CAD at P<5×10−8 and confirmed the association of 10 of 12 previously reported CAD loci. The 13 novel loci displayed risk allele frequencies ranging from 0.13 to 0.91 and were associated with a 6 to 17 percent increase in the risk of CAD per allele. Notably, only three of the novel loci displayed significant association with traditional CAD risk factors, while the majority lie in gene regions not previously implicated in the pathogenesis of CAD. Finally, five of the novel CAD risk loci appear to have pleiotropic effects, showing strong association with various other human diseases or traits.
PMCID: PMC3119261  PMID: 21378990
13.  Prospective study of insulin-like growth factor-I, insulin-like growth factor-binding protein 3, genetic variants in the IGF1 and IGFBP3 genes and risk of coronary artery disease 
Although experimental studies have suggested that insulin-like growth factor I (IGF-I) and its binding protein IGFBP-3 might have a role in the aetiology of coronary artery disease (CAD), the relevance of circulating IGFs and their binding proteins in the development of CAD in human populations is unclear. We conducted a nested case-control study, with a mean follow-up of six years, within the EPIC-Norfolk cohort to assess the association between circulating levels of IGF-I and IGFBP-3 and risk of CAD in up to 1,013 cases and 2,055 controls matched for age, sex and study enrolment date. After adjustment for cardiovascular risk factors, we found no association between circulating levels of IGF-I or IGFBP-3 and risk of CAD (odds ratio: 0.98 (95% Cl 0.90-1.06) per 1 SD increase in circulating IGF-I; odds ratio: 1.02 (95% Cl 0.94-1.12) for IGFBP-3). We examined associations between tagging single nucleotide polymorphisms (tSNPs) at the IGF1 and IGFBP3 loci and circulating IGF-I and IGFBP-3 levels in up to 1,133 cases and 2,223 controls and identified three tSNPs (rs1520220, rs3730204, rs2132571) that showed independent association with either circulating IGF-I or IGFBP-3 levels. In an assessment of 31 SNPs spanning the IGF1 or IGFBP3 loci, none were associated with risk of CAD in a meta-analysis that included EPIC-Norfolk and eight additional studies comprising up to 9,319 cases and 19,964 controls. Our results indicate that IGF-I and IGFBP-3 are unlikely to be importantly involved in the aetiology of CAD in human populations.
PMCID: PMC3166154  PMID: 21915365
Epidemiology; Genetics of cardiovascular disease; Risk factors; IGF1; IGFBP3
14.  Biological, Clinical, and Population Relevance of 95 Loci for Blood Lipids 
Teslovich, Tanya M. | Musunuru, Kiran | Smith, Albert V. | Edmondson, Andrew C. | Stylianou, Ioannis M. | Koseki, Masahiro | Pirruccello, James P. | Ripatti, Samuli | Chasman, Daniel I. | Willer, Cristen J. | Johansen, Christopher T. | Fouchier, Sigrid W. | Isaacs, Aaron | Peloso, Gina M. | Barbalic, Maja | Ricketts, Sally L. | Bis, Joshua C. | Aulchenko, Yurii S. | Thorleifsson, Gudmar | Feitosa, Mary F. | Chambers, John | Orho-Melander, Marju | Melander, Olle | Johnson, Toby | Li, Xiaohui | Guo, Xiuqing | Li, Mingyao | Cho, Yoon Shin | Go, Min Jin | Kim, Young Jin | Lee, Jong-Young | Park, Taesung | Kim, Kyunga | Sim, Xueling | Ong, Rick Twee-Hee | Croteau-Chonka, Damien C. | Lange, Leslie A. | Smith, Joshua D. | Song, Kijoung | Zhao, Jing Hua | Yuan, Xin | Luan, Jian'an | Lamina, Claudia | Ziegler, Andreas | Zhang, Weihua | Zee, Robert Y.L. | Wright, Alan F. | Witteman, Jacqueline C.M. | Wilson, James F. | Willemsen, Gonneke | Wichmann, H-Erich | Whitfield, John B. | Waterworth, Dawn M. | Wareham, Nicholas J. | Waeber, Gérard | Vollenweider, Peter | Voight, Benjamin F. | Vitart, Veronique | Uitterlinden, Andre G. | Uda, Manuela | Tuomilehto, Jaakko | Thompson, John R. | Tanaka, Toshiko | Surakka, Ida | Stringham, Heather M. | Spector, Tim D. | Soranzo, Nicole | Smit, Johannes H. | Sinisalo, Juha | Silander, Kaisa | Sijbrands, Eric J.G. | Scuteri, Angelo | Scott, James | Schlessinger, David | Sanna, Serena | Salomaa, Veikko | Saharinen, Juha | Sabatti, Chiara | Ruokonen, Aimo | Rudan, Igor | Rose, Lynda M. | Roberts, Robert | Rieder, Mark | Psaty, Bruce M. | Pramstaller, Peter P. | Pichler, Irene | Perola, Markus | Penninx, Brenda W.J.H. | Pedersen, Nancy L. | Pattaro, Cristian | Parker, Alex N. | Pare, Guillaume | Oostra, Ben A. | O'Donnell, Christopher J. | Nieminen, Markku S. | Nickerson, Deborah A. | Montgomery, Grant W. | Meitinger, Thomas | McPherson, Ruth | McCarthy, Mark I. | McArdle, Wendy | Masson, David | Martin, Nicholas G. | Marroni, Fabio | Mangino, Massimo | Magnusson, Patrik K.E. | Lucas, Gavin | Luben, Robert | Loos, Ruth J. F. | Lokki, Maisa | Lettre, Guillaume | Langenberg, Claudia | Launer, Lenore J. | Lakatta, Edward G. | Laaksonen, Reijo | Kyvik, Kirsten O. | Kronenberg, Florian | König, Inke R. | Khaw, Kay-Tee | Kaprio, Jaakko | Kaplan, Lee M. | Johansson, Åsa | Jarvelin, Marjo-Riitta | Janssens, A. Cecile J.W. | Ingelsson, Erik | Igl, Wilmar | Hovingh, G. Kees | Hottenga, Jouke-Jan | Hofman, Albert | Hicks, Andrew A. | Hengstenberg, Christian | Heid, Iris M. | Hayward, Caroline | Havulinna, Aki S. | Hastie, Nicholas D. | Harris, Tamara B. | Haritunians, Talin | Hall, Alistair S. | Gyllensten, Ulf | Guiducci, Candace | Groop, Leif C. | Gonzalez, Elena | Gieger, Christian | Freimer, Nelson B. | Ferrucci, Luigi | Erdmann, Jeanette | Elliott, Paul | Ejebe, Kenechi G. | Döring, Angela | Dominiczak, Anna F. | Demissie, Serkalem | Deloukas, Panagiotis | de Geus, Eco J.C. | de Faire, Ulf | Crawford, Gabriel | Collins, Francis S. | Chen, Yii-der I. | Caulfield, Mark J. | Campbell, Harry | Burtt, Noel P. | Bonnycastle, Lori L. | Boomsma, Dorret I. | Boekholdt, S. Matthijs | Bergman, Richard N. | Barroso, Inês | Bandinelli, Stefania | Ballantyne, Christie M. | Assimes, Themistocles L. | Quertermous, Thomas | Altshuler, David | Seielstad, Mark | Wong, Tien Y. | Tai, E-Shyong | Feranil, Alan B. | Kuzawa, Christopher W. | Adair, Linda S. | Taylor, Herman A. | Borecki, Ingrid B. | Gabriel, Stacey B. | Wilson, James G. | Stefansson, Kari | Thorsteinsdottir, Unnur | Gudnason, Vilmundur | Krauss, Ronald M. | Mohlke, Karen L. | Ordovas, Jose M. | Munroe, Patricia B. | Kooner, Jaspal S. | Tall, Alan R. | Hegele, Robert A. | Kastelein, John J.P. | Schadt, Eric E. | Rotter, Jerome I. | Boerwinkle, Eric | Strachan, David P. | Mooser, Vincent | Holm, Hilma | Reilly, Muredach P. | Samani, Nilesh J | Schunkert, Heribert | Cupples, L. Adrienne | Sandhu, Manjinder S. | Ridker, Paul M | Rader, Daniel J. | van Duijn, Cornelia M. | Peltonen, Leena | Abecasis, Gonçalo R. | Boehnke, Michael | Kathiresan, Sekar
Nature  2010;466(7307):707-713.
Serum concentrations of total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG) are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with serum lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 × 10-8), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (e.g., CYP7A1, NPC1L1, and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and impact lipid traits in three non-European populations (East Asians, South Asians, and African Americans). Our results identify several novel loci associated with serum lipids that are also associated with CAD. Finally, we validated three of the novel genes—GALNT2, PPP1R3B, and TTC39B—with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.
PMCID: PMC3039276  PMID: 20686565
15.  The hypertriglyceridemic-waist phenotype and the risk of coronary artery disease: results from the EPIC-Norfolk Prospective Population Study 
Screening for increased waist circumference and hypertriglyceridemia (the hypertriglyceridemic-waist phenotype) has been proposed as an inexpensive approach to identify patients with excess intra-abdominal adiposity and associated metabolic abnormalities. We examined the relationship between the hypertriglyceridemic-waist phenotype to the risk of coronary artery disease in apparently healthy individuals.
A total of 21 787 participants aged 45–79 years were followed for a mean of 9.8 (standard deviation 1.7) years. Coronary artery disease developed in 2109 of them during follow-up. The hypertriglyceridemic-waist phenotype was defined as a waist circumference of 90 cm or more and a triglyceride level of 2.0 mmol/L or more in men, and a waist circumference of 85 cm or more and a triglyceride level of 1.5 mmol/L or more in women.
Compared with participants who had a waist circumference and triglyceride level below the threshold, those with the hypertriglyceridemic-waist phenotype had higher blood pressure indices, higher levels of apolipoprotein B and C-reactive protein, lower levels of high-density lipoprotein cholesterol and apolipoprotein A-I, and smaller low-density lipoprotein particles. Among men, those with the hypertriglyceridemic-waist phenotype had an unadjusted hazard ratio for future coronary artery disease of 2.40 (95% confidence interval [CI] 2.02–2.87) compared with men who did not have the phenotype. Women with the phenotype had an unadjusted hazard ratio of 3.84 (95% CI 3.20–4.62) compared with women who did not have the phenotype.
Among participants from a European cohort representative of a contemporary Western population, the hypertriglyceridemic-waist phenotype was associated with a deteriorated cardiometabolic risk profile and an increased risk for coronary artery disease.
PMCID: PMC2942915  PMID: 20643837
16.  Separating the mechanism-based and off-target actions of CETP-inhibitors using CETP gene polymorphisms 
Circulation  2009;121(1):52-62.
Cholesteryl ester transfer protein (CETP) inhibitors raise HDL-cholesterol but torcetrapib, the first-in-class inhibitor tested in a large outcome trial caused unexpected blood pressure elevation and increased cardiovascular events. Whether the hypertensive effect resulted from CETP-inhibition or an off-target action of torcetrapib has been debated. We hypothesised that common single nucleotide polymorphisms (SNPs) in the CETP-gene could help distinguish mechanism-based from off-target actions of CETP-inhibitors to inform on the validity of CETP as a therapeutic target.
Methods and Results
We compared the effect of CETP SNPs and torcetrapib treatment on lipid fractions, blood pressure and electrolytes in up to 67,687 individuals from genetic studies and 17,911 from randomised trials. CETP SNPs and torcetrapib treatment reduced CETP activity and had directionally concordant effect on eight lipid and lipoprotein traits (total-, LDL- and HDL-cholesterol, HDL2, HDL3, apolipoproteins A-I, -B, and triglycerides), with the genetic effect on HDL-cholesterol (0.13 mmol/L; 95% CI: 0.11, 0.14) being consistent with that expected of a 10 mg dose of torcetrapib (0.13 mmol/L; 0.10, 0.15). In trials, 60mg torcetrapib elevated systolic and diastolic blood pressure by 4.47mmHg (4.10, 4.84) and 2.08mmHg (1.84, 2.31) respectively. However, the effect of CETP SNPs on systolic 0.16mmHg (−0.28, 0.60) and diastolic blood pressure −0.04mmHg (−0.36, 0.28) was null and significantly different from that expected of 10 mg torcetrapib.
Discordance in the effects of CETP SNPs and torcetrapib treatment on blood pressure despite the concordant effects on lipids indicates the hypertensive action of torcetrapib is unlikely to be due to CETP-inhibition, or shared by chemically dissimilar CETP inhibitors. Genetic studies could find use in drug development programmes as a new source of randomised evidence for drug target validation in man.
PMCID: PMC2811869  PMID: 20026784
genetics; pharmacology; epidemiology
17.  Both Paraoxonase-1 Genotype and Activity Do Not Predict the Risk of Future Coronary Artery Disease; the EPIC-Norfolk Prospective Population Study 
PLoS ONE  2009;4(8):e6809.
Paraoxonase-1 (PON1) is an antioxidant enzyme, that resides on high-density lipoprotein (HDL). PON1-activity, is heavily influenced by the PON1-Q192R polymorphism. PON1 is considered to protect against atherosclerosis, but it is unclear whether this relation is independent of its carrier, HDL. In order to evaluate the atheroprotective potential of PON1, we assessed the relationships among PON1-genotype, PON1-activity and risk of future coronary artery disease (CAD), in a large prospective case-control study.
Methodology/Principal Findings
Cases (n = 1138) were apparently healthy men and women aged 45–79 years who developed fatal or nonfatal CAD during a mean follow-up of 6 years. Controls (n = 2237) were matched by age, sex and enrollment time. PON1-activity was similar in cases and controls (60.7±45.3 versus 62.6±45.8 U/L, p = 0.3) and correlated with HDL-cholesterol levels (r = 0.16, p<0.0001). The PON1-Q192R polymorphism had a profound impact on PON1-activity, but did not predict CAD risk (Odds Ratio [OR] per R allele 0.98[0.84–1.15], p = 0.8). Using conditional logistic regression, quartiles of PON1-activity showed a modest inverse relation with CAD risk (OR for the highest versus the lowest quartile 0.77[0.63–0.95], p = 0.01; p-trend = 0.06). PON1-activity adjusted for Q192R polymorphism correlated better with HDL-cholesterol (r = 0.26, p<0.0001) and more linearly predicted CAD risk (0.79[0.64–0.98], p = 0.03; p-trend = 0.008). However, these relationships were abolished after adjustment for HDL (particles-cholesterol-size) and apolipoproteinA-I (0.94[0.74–1.18], p-trend = 0.3).
This study, shows that PON1-activity inversely relates to CAD risk, but not independent of HDL, due to its close association with the HDL-particle. These data strongly suggest that a low PON1-activity is not a causal factor in atherogenesis.
PMCID: PMC2728540  PMID: 19710913

Results 1-17 (17)