The benefits of using genetic information to design prevention trials.

Clinical trials for preventative therapies are complex and costly endeavors focused on individuals likely to develop disease in a short time frame, randomizing them to treatment groups, and following them over time. In such trials, statistical power is governed by the rate of disease events in each group and cost is determined by randomization, treatment, and follow-up. Strategies that increase the rate of disease events by enrolling individuals with high risk of disease can significantly reduce study size, duration, and cost. Comprehensive study of common, complex diseases has resulted in a growing list of robustly associated genetic markers. Here, we evaluate the utility--in terms of trial size, duration, and cost--of enriching prevention trial samples by combining clinical information with genetic risk scores to identify individuals at greater risk of disease. We also describe a framework for utilizing genetic risk scores in these trials and evaluating the associated cost and time savings. With type 1 diabetes (T1D), type 2 diabetes (T2D), myocardial infarction (MI), and advanced age-related macular degeneration (AMD) as examples, we illustrate the potential and limitations of using genetic data for prevention trial design. We illustrate settings where incorporating genetic information could reduce trial cost or duration considerably, as well as settings where potential savings are negligible. Results are strongly dependent on the genetic architecture of the disease, but we also show that these benefits should increase as the list of robustly associated markers for each disease grows and as large samples of genotyped individuals become available.

Deciphering the Causal Role of sPLA2s and Lp-PLA2 in Coronary Heart Disease.

Over the last 10 to 15 years, animal and human observational studies have identified elevated levels of both proinflammatory secretory phospholipase A2-IIA and lipoprotein-associated phospholipase A2 as potential risk factors for coronary heart disease. However, Mendelian randomization, a genetic tool to test causality of a biomarker, and phase III randomized controlled trials of inhibitors of theses enzymes (varespladib and darapladib) converged to indicate that elevated levels are unlikely to be themselves causal of coronary heart disease and that inhibition had little or no clinical utility. The concordance of findings from Mendelian randomization and clinical trials suggests that for these 2 drugs, and for other novel biomarkers in future, validation of potential therapeutic targets by genetic studies (such as Mendelian randomization) before embarking on costly phase III randomized controlled trials could increase efficiency and offset the high risk of drug development, thereby facilitating discovery of new therapeutics and mitigating against the exuberant costs of drug development.

Identifying functional noncoding variants from genome-wide association studies for cardiovascular disease and related traits.

PURPOSE OF REVIEW: Genome-wide association studies have identified many novel loci for cardiovascular disease and related traits. Attention is now shifting towards the analysis of these loci for causal variants, with a view to identify the novel mechanisms leading to disease. RECENT FINDINGS: This review focuses on the approaches to identify causal, noncoding variants for coronary artery disease, lipid traits and other cardiovascular risk factors. Fine-mapping studies are discussed, along with the novel statistical approaches to produce 'credible sets'. The use of combining genome-wide association study datasets with experimental methods such as expression quantitative trait loci and allele-specific chromatin accessibility are explored, with recent examples discussed. Mapping long-range chromatin interactions and evolving genome-editing technologies such as clustered regularly interspaced short palindromic repeats combined with clustered regularly interspaced short palindromic repeats-associated (Cas9) nuclease promise to aid considerably the search for causal variants. SUMMARY: Identification of causal variants for cardiovascular disease and related traits is still in the early stages, but with technologies evolving and increasingly relevant tissue samples undergoing analysis, there are favourable prospects that many new mechanisms for disease will be uncovered by the end of this decade.

Refinement of variant selection for the LDL cholesterol genetic risk score in the diagnosis of the polygenic form of clinical familial hypercholesterolemia and replication in samples from 6 countries.

BACKGROUND: Familial hypercholesterolemia (FH) is an autosomal-dominant disorder caused by mutations in 1 of 3 genes. In the 60% of patients who are mutation negative, we have recently shown that the clinical phenotype can be associated with an accumulation of common small-effect LDL cholesterol (LDL-C)-raising alleles by use of a 12-single nucleotide polymorphism (12-SNP) score. The aims of the study were to improve the selection of SNPs and replicate the results in additional samples. METHODS: We used ROC curves to determine the optimum number of LDL-C SNPs. For replication analysis, we genotyped patients with a clinical diagnosis of FH from 6 countries for 6 LDL-C-associated alleles. We compared the weighted SNP score among patients with no confirmed mutation (FH/M-), those with a mutation (FH/M+), and controls from a UK population sample (WHII). RESULTS: Increasing the number of SNPs to 33 did not improve the ability of the score to discriminate between FH/M- and controls, whereas sequential removal of SNPs with smaller effects/lower frequency showed that a weighted score of 6 SNPs performed as well as the 12-SNP score. Metaanalysis of the weighted 6-SNP score, on the basis of polymorphisms in CELSR2 (cadherin, EGF LAG 7-pass G-type receptor 2), APOB (apolipoprotein B), ABCG5/8 [ATP-binding cassette, sub-family G (WHITE), member 5/8], LDLR (low density lipoprotein receptor), and APOE (apolipoprotein E) loci, in the independent FH/M- cohorts showed a consistently higher score in comparison to the WHII population (P < 2.2 × 10(-16)). Modeling in individuals with a 6-SNP score in the top three-fourths of the score distribution indicated a >95% likelihood of a polygenic explanation of their increased LDL-C. CONCLUSIONS: A 6-SNP LDL-C score consistently distinguishes FH/M- patients from healthy individuals. The hypercholesterolemia in 88% of mutation-negative patients is likely to have a polygenic basis.

Use of allele-specific FAIRE to determine functional regulatory polymorphism using large-scale genotyping arrays.

Following the widespread use of genome-wide association studies (GWAS), focus is turning towards identification of causal variants rather than simply genetic markers of diseases and traits. As a step towards a high-throughput method to identify genome-wide, non-coding, functional regulatory variants, we describe the technique of allele-specific FAIRE, utilising large-scale genotyping technology (FAIRE-gen) to determine allelic effects on chromatin accessibility and regulatory potential. FAIRE-gen was explored using lymphoblastoid cells and the 50,000 SNP Illumina CVD BeadChip. The technique identified an allele-specific regulatory polymorphism within NR1H3 (coding for LXR-α), rs7120118, coinciding with a previously GWAS-identified SNP for HDL-C levels. This finding was confirmed using FAIRE-gen with the 200,000 SNP Illumina Metabochip and verified with the established method of TaqMan allelic discrimination. Examination of this SNP in two prospective Caucasian cohorts comprising 15,000 individuals confirmed the association with HDL-C levels (combined beta = 0.016; p = 0.0006), and analysis of gene expression identified an allelic association with LXR-α expression in heart tissue. Using increasingly comprehensive genotyping chips and distinct tissues for examination, FAIRE-gen has the potential to aid the identification of many causal SNPs associated with disease from GWAS.

The genetic architecture of the familial hyperlipidaemia syndromes: rare mutations and common variants in multiple genes.

PURPOSE OF REVIEW: Genome-Wide Association Studies have provided robust identification of approximately 100 genetic loci determining plasma lipid parameters. Using these multiple common genetic lipid-determining variants in a 'gene score' has thrown new light on the mode of inheritance of familial lipid disorders. RECENT FINDINGS: Different hypertriglyceridaemia states have been explained by the polygenic coinheritance of triglyceride-raising alleles. Taking this gene score approach with 12 LDL-cholesterol-raising alleles, we reported that for patients with a clinical diagnosis of familial hypercholesterolaemia, but no identified rare mutation in the familial hypercholesterolaemia-causing genes, LDL receptor, apolipoprotein B and PCSK9, the most likely explanation for their elevated LDL-C levels was a polygenic, not a monogenic, cause of the disease. SUMMARY: These findings have wider implications for understanding complex disorders, and may very well explain the genetic basis of familial combined hyperlipidaemia, another familial lipid disorder in which the genetic cause(s) has remained elusive.

Use of low-density lipoprotein cholesterol gene score to distinguish patients with polygenic and monogenic familial hypercholesterolaemia: a case-control study.

BACKGROUND: Familial hypercholesterolaemia is a common autosomal-dominant disorder caused by mutations in three known genes. DNA-based cascade testing is recommended by UK guidelines to identify affected relatives; however, about 60% of patients are mutation-negative. We assessed the hypothesis that familial hypercholesterolaemia can also be caused by an accumulation of common small-effect LDL-C-raising alleles. METHODS: In November, 2011, we assembled a sample of patients with familial hypercholesterolaemia from three UK-based sources and compared them with a healthy control sample from the UK Whitehall II (WHII) study. We also studied patients from a Belgian lipid clinic (Hôpital de Jolimont, Haine St-Paul, Belgium) for validation analyses. We genotyped participants for 12 common LDL-C-raising alleles identified by the Global Lipid Genetics Consortium and constructed a weighted LDL-C-raising gene score. We compared the gene score distribution among patients with familial hypercholesterolaemia with no confirmed mutation, those with an identified mutation, and controls from WHII. FINDINGS: We recruited 321 mutation-negative UK patients (451 Belgian), 319 mutation-positive UK patients (273 Belgian), and 3020 controls from WHII. The mean weighted LDL-C gene score of the WHII participants (0.90 [SD 0.23]) was strongly associated with LDL-C concentration (p=1.4 x 10(-77); R(2)=0.11). Mutation-negative UK patients had a significantly higher mean weighted LDL-C score (1.0 [SD 0.21]) than did WHII controls (p=4.5 x 10(-16)), as did the mutation-negative Belgian patients (0.99 [0.19]; p=5.2 x 10(-20)). The score was also higher in UK (0.95 [0.20]; p=1.6 x 10(-5)) and Belgian (0.92 [0.20]; p=0.04) mutation-positive patients than in WHII controls. 167 (52%) of 321 mutation-negative UK patients had a score within the top three deciles of the WHII weighted LDL-C gene score distribution, and only 35 (11%) fell within the lowest three deciles. INTERPRETATION: In a substantial proportion of patients with familial hypercholesterolaemia without a known mutation, their raised LDL-C concentrations might have a polygenic cause, which could compromise the efficiency of cascade testing. In patients with a detected mutation, a substantial polygenic contribution might add to the variable penetrance of the disease. FUNDING: British Heart Foundation, Pfizer, AstraZeneca, Schering-Plough, National Institute for Health Research, Medical Research Council, Health and Safety Executive, Department of Health, National Heart Lung and Blood Institute, National Institute on Aging, Agency for Health Care Policy Research, John D and Catherine T MacArthur Foundation Research Networks on Successful Midlife Development and Socio-economic Status and Health, Unilever, and Departments of Health and Trade and Industry.

Influence of common genetic variation on blood lipid levels, cardiovascular risk, and coronary events in two British prospective cohort studies.

AIMS: The aim of this study was to quantify the collective effect of common lipid-associated single nucleotide polymorphisms (SNPs) on blood lipid levels, cardiovascular risk, use of lipid-lowering medication, and risk of coronary heart disease (CHD) events. METHODS AND RESULTS: Analysis was performed in two prospective cohorts: Whitehall II (WHII; N = 5059) and the British Women's Heart and Health Study (BWHHS; N = 3414). For each participant, scores were calculated based on the cumulative effect of multiple genetic variants influencing total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG). Compared with the bottom quintile, individuals in the top quintile of the LDL-C genetic score distribution had higher LDL-C {mean difference of 0.85 [95% confidence interval, (CI) = 0.76-0.94] and 0.63 [95% CI = 0.50-0.76] mmol/l in WHII and BWHHS, respectively}. They also tended to have greater odds of having 'high-risk' status (Framingham 10-year cardiovascular disease risk >20%) [WHII: odds ratio (OR) = 1.36 (0.93-1.98), BWHHS: OR = 1.49 (1.14-1.94)]; receiving lipid-lowering treatment [WHII: OR = 2.38 (1.57-3.59), BWHHS: OR = 2.24 (1.52-3.29)]; and CHD events [WHII: OR = 1.43 (1.02-2.00), BWHHS: OR = 1.31 (0.99-1.72)]. Similar associations were observed for the TC score in both studies. The TG score was associated with high-risk status and medication use in both studies. Neither HDL nor TG scores were associated with the risk of coronary events. The genetic scores did not improve discrimination over the Framingham risk score. CONCLUSION: At the population level, common SNPs associated with LDL-C and TC contribute to blood lipid variation, cardiovascular risk, use of lipid-lowering medications and coronary events. However, their effects are too small to discriminate future lipid-lowering medication requirements or coronary events.

Comparative analysis of genome-wide association studies signals for lipids, diabetes, and coronary heart disease: Cardiovascular Biomarker Genetics Collaboration.

AIMS: To evaluate the associations of emergent genome-wide-association study-derived coronary heart disease (CHD)-associated single nucleotide polymorphisms (SNPs) with established and emerging risk factors, and the association of genome-wide-association study-derived lipid-associated SNPs with other risk factors and CHD events. METHODS AND RESULTS: Using two case-control studies, three cross-sectional, and seven prospective studies with up to 25 000 individuals and 5794 CHD events we evaluated associations of 34 genome-wide-association study-identified SNPs with CHD risk and 16 CHD-associated risk factors or biomarkers. The Ch9p21 SNPs rs1333049 (OR 1.17; 95% confidence limits 1.11-1.24) and rs10757274 (OR 1.17; 1.09-1.26), MIA3 rs17465637 (OR 1.10; 1.04-1.15), Ch2q36 rs2943634 (OR 1.08; 1.03-1.14), APC rs383830 (OR 1.10; 1.02, 1.18), MTHFD1L rs6922269 (OR 1.10; 1.03, 1.16), CXCL12 rs501120 (OR 1.12; 1.04, 1.20), and SMAD3 rs17228212 (OR 1.11; 1.05, 1.17) were all associated with CHD risk, but not with the CHD biomarkers and risk factors measured. Among the 20 blood lipid-related SNPs, LPL rs17411031 was associated with a lower risk of CHD (OR 0.91; 0.84-0.97), an increase in Apolipoprotein AI and HDL-cholesterol, and reduced triglycerides. SORT1 rs599839 was associated with CHD risk (OR 1.20; 1.15-1.26) as well as total- and LDL-cholesterol, and apolipoprotein B. ANGPTL3 rs12042319 was associated with CHD risk (OR 1.11; 1.03, 1.19), total- and LDL-cholesterol, triglycerides, and interleukin-6. CONCLUSION: Several SNPs predicting CHD events appear to involve pathways not currently indexed by the established or emerging risk factors; others involved changes in blood lipids including triglycerides or HDL-cholesterol as well as LDL-cholesterol. The overlapping association of SNPs with multiple risk factors and biomarkers supports the existence of shared points of regulation for these phenotypes.

The representation of heart development in the gene ontology.

An understanding of heart development is critical in any systems biology approach to cardiovascular disease. The interpretation of data generated from high-throughput technologies (such as microarray and proteomics) is also essential to this approach. However, characterizing the role of genes in the processes underlying heart development and cardiovascular disease involves the non-trivial task of data analysis and integration of previous knowledge. The Gene Ontology (GO) Consortium provides structured controlled biological vocabularies that are used to summarize previous functional knowledge for gene products across all species. One aspect of GO describes biological processes, such as development and signaling. In order to support high-throughput cardiovascular research, we have initiated an effort to fully describe heart development in GO; expanding the number of GO terms describing heart development from 12 to over 280. This new ontology describes heart morphogenesis, the differentiation of specific cardiac cell types, and the involvement of signaling pathways in heart development. This work also aligns GO with the current views of the heart development research community and its representation in the literature. This extension of GO allows gene product annotators to comprehensively capture the genetic program leading to the developmental progression of the heart. This will enable users to integrate heart development data across species, resulting in the comprehensive retrieval of information about this subject. The revised GO structure, combined with gene product annotations, should improve the interpretation of data from high-throughput methods in a variety of cardiovascular research areas, including heart development, congenital cardiac disease, and cardiac stem cell research. Additionally, we invite the heart development community to contribute to the expansion of this important dataset for the benefit of future research in this area.

Application of statistical and functional methodologies for the investigation of genetic determinants of coronary heart disease biomarkers: lipoprotein lipase genotype and plasma triglycerides as an exemplar.

Genome-wide association studies have proved very successful in identifying novel single-nucleotide polymorphisms (SNPs) associated with disease or traits, but the related, functional SNP is usually unknown. In this paper, we describe a methodology to locate and validate candidate functional SNPs using lipoprotein lipase (LPL), a gene previously associated with triglyceride levels, as an exemplar. Two thousand seven hundred and eighty-six healthy middle-aged men from the NPHSII UK prospective study (with up to six measures of plasma lipid levels) were genotyped for 20 LPL tagging (t)SNPs using Illumina Bead technology. Using model-selection procedures and haplotypes, we identified eight SNPs that consistently maximized the fit of the model to the phenotype. Fifteen SNPs in high linkage disequilibrium with these were identified, and functional assays were carried out on all 23 SNPs. Electrophoretic mobility shift assay (EMSA) was used to identify SNPs that had the potential to alter DNA-protein interactions, reducing the number to eight possible candidate SNPs. These were examined for ability to alter expression using a luciferase reporter assay, and two regulatory SNPs, showing genotype differences, rs327 and rs3289, were identified. Finally, multiplexed-competitor-EMSA (MC-EMSA) and supershift EMSA identified FOXA2 to rs327T, and CREB-binding protein (CBP) and CCAAT displacement protein (CDP) to rs3289C as the factors responsible for transcription binding. We have identified two novel candidate functional SNPs in LPL and presented a procedure aimed to efficiently detect SNPs potentially causal to genetic association. We believe that this methodology could be successfully applied to future re-sequencing data.

Gene-centric association signals for lipids and apolipoproteins identified via the HumanCVD BeadChip.

Blood lipids are important cardiovascular disease (CVD) risk factors with both genetic and environmental determinants. The Whitehall II study (n=5592) was genotyped with the gene-centric HumanCVD BeadChip (Illumina). We identified 195 SNPs in 16 genes/regions associated with 3 major lipid fractions and 2 apolipoprotein components at p<10(-5), with the associations being broadly concordant with prior genome-wide analysis. SNPs associated with LDL cholesterol and apolipoprotein B were located in LDLR, PCSK9, APOB, CELSR2, HMGCR, CETP, the TOMM40-APOE-C1-C2-C4 cluster, and the APOA5-A4-C3-A1 cluster; SNPs associated with HDL cholesterol and apolipoprotein AI were in CETP, LPL, LIPC, APOA5-A4-C3-A1, and ABCA1; and SNPs associated with triglycerides in GCKR, BAZ1B, MLXIPL, LPL, and APOA5-A4-C3-A1. For 48 SNPs in previously unreported loci that were significant at p<10(-4) in Whitehall II, in silico analysis including the British Women's Heart and Health Study, BRIGHT, ASCOT, and NORDIL studies (total n>12,500) revealed previously unreported associations of SH2B3 (p<2.2x10(-6)), BMPR2 (p<2.3x10(-7)), BCL3/PVRL2 (flanking APOE; p<4.4x10(-8)), and SMARCA4 (flanking LDLR; p<2.5x10(-7)) with LDL cholesterol. Common alleles in these genes explained 6.1%-14.7% of the variance in the five lipid-related traits, and individuals at opposite tails of the additive allele score exhibited substantial differences in trait levels (e.g., >1 mmol/L in LDL cholesterol [approximately 1 SD of the trait distribution]). These data suggest that multiple common alleles of small effect can make important contributions to individual differences in blood lipids potentially relevant to the assessment of CVD risk. These genes provide further insights into lipid metabolism and the likely effects of modifying the encoded targets therapeutically.

Effect modification by population dietary folate on the association between MTHFR genotype, homocysteine, and stroke risk: a meta-analysis of genetic studies and randomised trials.

BACKGROUND: The MTHFR 677C→T polymorphism has been associated with raised homocysteine concentration and increased risk of stroke. A previous overview showed that the effects were greatest in regions with low dietary folate consumption, but differentiation between the effect of folate and small-study bias was difficult. A meta-analysis of randomised trials of homocysteine-lowering interventions showed no reduction in coronary heart disease events or stroke, but the trials were generally set in populations with high folate consumption. We aimed to reduce the effect of small-study bias and investigate whether folate status modifies the association between MTHFR 677C→T and stroke in a genetic analysis and meta-analysis of randomised controlled trials. METHODS: We established a collaboration of genetic studies consisting of 237 datasets including 59,995 individuals with data for homocysteine and 20,885 stroke events. We compared the genetic findings with a meta-analysis of 13 randomised trials of homocysteine-lowering treatments and stroke risk (45,549 individuals, 2314 stroke events, 269 transient ischaemic attacks). FINDINGS: The effect of the MTHFR 677C→T variant on homocysteine concentration was larger in low folate regions (Asia; difference between individuals with TT versus CC genotype, 3·12 µmol/L, 95% CI 2·23 to 4·01) than in areas with folate fortification (America, Australia, and New Zealand, high; 0·13 µmol/L, -0·85 to 1·11). The odds ratio (OR) for stroke was also higher in Asia (1·68, 95% CI 1·44 to 1·97) than in America, Australia, and New Zealand, high (1·03, 0·84 to 1·25). Most randomised trials took place in regions with high or increasing population folate concentrations. The summary relative risk (RR) of stroke in trials of homocysteine-lowering interventions (0·94, 95% CI 0·85 to 1·04) was similar to that predicted for the same extent of homocysteine reduction in large genetic studies in populations with similar folate status (predicted RR 1·00, 95% CI 0·90 to 1·11). Although the predicted effect of homocysteine reduction from large genetic studies in low folate regions (Asia) was larger (RR 0·78, 95% CI 0·68 to 0·90), no trial has evaluated the effect of lowering of homocysteine on stroke risk exclusively in a low folate region. INTERPRETATION: In regions with increasing levels or established policies of population folate supplementation, evidence from genetic studies and randomised trials is concordant in suggesting an absence of benefit from lowering of homocysteine for prevention of stroke. Further large-scale genetic studies of the association between MTHFR 677C→T and stroke in low folate settings are needed to distinguish effect modification by folate from small-study bias. If future randomised trials of homocysteine-lowering interventions for stroke prevention are undertaken, they should take place in regions with low folate consumption. FUNDING: Full funding sources listed at end of paper (see Acknowledgments).

Inflammatory biomarkers, physical activity, waist circumference, and risk of future coronary heart disease in healthy men and women.

AIMS: The aim of this study was to determine the contribution of physical activity and abdominal obesity to the variation in inflammatory biomarkers and incident coronary heart disease (CHD) in a European population. METHODS AND RESULTS: In a prospective case-control study nested in the European Prospective Investigation into Cancer and Nutrition-Norfolk cohort, we examined the associations between circulating levels or activity of C-reactive protein, myeloperoxidase (MPO), secretory phospholipase A2 (sPLA2), lipoprotein-associated phospholipase A2 (Lp-PLA2), fibrinogen, adiponectin, waist circumference, physical activity, and CHD risk over a 10-year period among healthy men and women (45-79 years of age). A total of 1002 cases who developed fatal or non-fatal CHD were matched to 1859 controls on the basis of age, sex, and enrolment period. Circulating levels of C-reactive protein, sPLA2 (women only), fibrinogen, and adiponectin were linearly associated with increasing waist circumference and decreasing physical activity levels. After adjusting for waist circumference, physical activity, smoking, diabetes, systolic blood pressure, low-density lipoprotein and high-density lipoprotein cholesterol levels, and further adjusted for hormone replacement therapy in women, C-reactive protein, MPO (men only), sPLA2, fibrinogen, but not Lp-PLA2 and adiponectin were associated with an increased CHD risk. CONCLUSION: Inactive participants with an elevated waist circumference were characterized by deteriorated levels of inflammatory markers. However, several inflammatory markers were associated with an increased CHD risk, independent of underlying CHD risk factors such as waist circumference and physical activity levels.

Lipoprotein association studies: taking stock and moving forward.

PURPOSE OF REVIEW: Over the last year, huge progress has been made using SNP arrays to identify genes associated with lipid traits. RECENT FINDINGS: The single genome-wide association studies (GWASs) may have reached a limit in identifying novel genes, but there has been tremendous progress from collaborative consortia examining pooled data from GWASs, often employing SNP imputation. For example, the Global Lipid Consortium reported that 56 of the 95 lipid-associated loci were novel to the pooled analysis from over 100 000 individuals. Complementary to this, a gene-centric approach, such as the 50K IBC HumanCVD chip, which provides deep coverage of approximately 2100 genes, has had success in ascertaining independently acting variants and helped us to move a step closer to identify functional variants. Yet irrespective of the platform used, for each trait, the percentage variance explained by these genes remains in the order of approximately 10-12% and it is still unclear to what extent rare mutations, identified by resequencing or exome sequencing approaches, or gene × gene and gene × environment studies, might boost this. SUMMARY: GWAS-identified novel lipid-related loci highlight new pathways in lipid metabolism and may provide innovative drug targets. Furthermore, the use of lipid gene scores, over and above a single lipid measure, may have clinical utility.

Relationship of IgG and IgM autoantibodies and immune complexes to oxidized LDL with markers of oxidation and inflammation and cardiovascular events: results from the EPIC-Norfolk Study.

Levels of IgG and IgM autoantibodies (AA) to malondialdehyde (MDA)-LDL and apoB-immune complexes (ICs) were measured in 748 cases and 1,723 controls in the EPIC-Norfolk cohort and their association to coronary artery disease (CAD) events determined. We evaluated whether AA and IC modify CAD risk associated with secretory phospholipase A(2) (sPLA(2)) type IIA mass and activity, lipoprotein-associated PLA(2) activity, lipoprotein (a) [Lp(a)], oxidized phospholipids on apoB-100 (OxPL/apoB), myeloperoxidase, and high sensitivity C-reactive protein. IgG ICs were higher in cases versus controls (P = 0.02). Elevated levels of IgM AA and IC were inversely associated with Framingham Risk Score and number of metabolic syndrome criteria (p range 0.02-0.001). In regression analyses adjusted for age, smoking, diabetes, LDL-cholesterol, HDL-cholesterol, and systolic blood pressure, the highest tertiles of IgG and IgM AA and IC were not associated with higher risk of CAD events compared with the lowest tertiles. However, elevated levels of IgM IC reduced the risk of Lp(a) (P = 0.006) and elevated IgG MDA-LDL potentiated the risk of sPLA(2) mass (P = 0.018). This epidemiological cohort of initially healthy subjects shows that IgG and IgM AA and IC are not independent predictors of CAD events but may modify CAD risk associated with elevated levels of oxidative biomarkers.

PLA2G7 genotype, lipoprotein-associated phospholipase A2 activity, and coronary heart disease risk in 10 494 cases and 15 624 controls of European Ancestry.

BACKGROUND: Higher lipoprotein-associated phospholipase A(2)(Lp-PLA2) activity is associated with increased risk of coronary heart disease (CHD), making Lp-PLA2 a potential therapeutic target. PLA2G7 variants associated with Lp-PLA2 activity could evaluate whether this relationship is causal. METHODS AND RESULTS: A meta-analysis including a total of 12 studies (5 prospective, 4 case-control, 1 case-only, and 2 cross-sectional studies; n=26 118) was undertaken to examine the association of the following: (1) Lp-PLA2 activity versus cardiovascular biomarkers and risk factors and CHD events (2 prospective studies; n=4884); (2) PLA2G7 single-nucleotide polymorphisms and Lp-PLA2 activity (3 prospective, 2 case-control, 2 cross-sectional studies; up to n=6094); and (3) PLA2G7 single-nucleotide polymorphisms and angiographic coronary artery disease (2 case-control, 1 case-only study; n=4971 cases) and CHD events (5 prospective, 2 case-control studies; n=5523). Lp-PLA2 activity correlated with several CHD risk markers. Hazard ratios for CHD events for the top versus bottom quartile of Lp-PLA2 activity were 1.61 (95% confidence interval, 1.31 to 1.99) and 1.17 (95% confidence interval, 0.91 to 1.51) after adjustment for baseline traits. Of 7 single-nucleotide polymorphisms, rs1051931 (A379V) showed the strongest association with Lp-PLA2 activity, with VV subjects having 7.2% higher activity than AAs. Genotype was not associated with risk markers, angiographic coronary disease (odds ratio, 1.03; 95% confidence interval, 0.80 to 1.32), or CHD events (odds ratio, 0.98; 95% confidence interval, 0.82 to 1.17). CONCLUSIONS: Unlike Lp-PLA2 activity, PLA2G7 variants associated with modest effects on Lp-PLA2 activity were not associated with cardiovascular risk markers, coronary atheroma, or CHD. Larger association studies, identification of single-nucleotide polymorphisms with larger effects, or randomized trials of specific Lp-PLA2 inhibitors are needed to confirm or refute a contributory role for Lp-PLA2 in CHD.

Separating the mechanism-based and off-target actions of cholesteryl ester transfer protein inhibitors with CETP gene polymorphisms.

BACKGROUND: Cholesteryl ester transfer protein (CETP) inhibitors raise high-density lipoprotein (HDL) cholesterol, but torcetrapib, the first-in-class inhibitor tested in a large outcome trial, caused an 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 hypothesized that common single-nucleotide polymorphisms 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 single-nucleotide polymorphisms and torcetrapib treatment on lipid fractions, blood pressure, and electrolytes in up to 67 687 individuals from genetic studies and 17 911 from randomized trials. CETP single-nucleotide polymorphisms and torcetrapib treatment reduced CETP activity and had a directionally concordant effect on 8 lipid and lipoprotein traits (total, low-density lipoprotein, and HDL cholesterol; HDL2; HDL3; apolipoproteins A-I and B; and triglycerides), with the genetic effect on HDL cholesterol (0.13 mmol/L, 95% confidence interval [CI] 0.11 to 0.14 mmol/L) being consistent with that expected of a 10-mg dose of torcetrapib (0.13 mmol/L, 95% CI 0.10 to 0.15). In trials, 60 mg of torcetrapib elevated systolic and diastolic blood pressure by 4.47 mm Hg (95% CI 4.10 to 4.84 mm Hg) and 2.08 mm Hg (95% CI 1.84 to 2.31 mm Hg), respectively. However, the effect of CETP single-nucleotide polymorphisms on systolic blood pressure (0.16 mm Hg, 95% CI -0.28 to 0.60 mm Hg) and diastolic blood pressure (-0.04 mm Hg, 95% CI -0.36 to 0.28 mm Hg) was null and significantly different from that expected of 10 mg of torcetrapib. CONCLUSIONS: Discordance in the effects of CETP single-nucleotide polymorphisms 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 a place in drug-development programs as a new source of randomized evidence for drug-target validation in humans.

Integrated associations of genotypes with multiple blood biomarkers linked to coronary heart disease risk.

Individuals at risk of coronary heart disease (CHD) show multiple correlations across blood biomarkers. Single nucleotide polymorphisms (SNPs) indexing biomarker differences could help distinguish causal from confounded associations because of their random allocation prior to disease. We examined the association of 948 SNPs in 122 candidate genes with 12 CHD-associated phenotypes in 2775 middle aged men (a genic scan). Of these, 140 SNPs indexed differences in HDL- and LDL-cholesterol, triglycerides, C-reactive protein, fibrinogen, factor VII, apolipoproteins AI and B, lipoprotein-associated phospholipase A2, homocysteine or folate, some with large effect sizes and highly significant P-values (e.g. 2.15 standard deviations at P = 9.2 x 10(-140) for F7 rs6046 and FVII levels). Top ranking SNPs were then tested for association with additional biomarkers correlated with the index phenotype (phenome scan). Several SNPs (e.g. in APOE, CETP, LPL, APOB and LDLR) influenced multiple phenotypes, while others (e.g. in F7, CRP and FBB) showed restricted association to the index marker. SNPs influencing six blood proteins were used to evaluate the nature of the associations between correlated blood proteins utilizing Mendelian randomization. Multiple SNPs were associated with CHD-related quantitative traits, with some associations restricted to a single marker and others exerting a wider genetic 'footprint'. SNPs indexing biomarkers provide new tools for investigating biological relationships and causal links with disease. Broader and deeper integrated analyses, linking genomic with transcriptomic, proteomic and metabolomic analysis, as well as clinical events could, in principle, better delineate CHD causing pathways amenable to treatment.

Genetic variants associated with Von Willebrand factor levels in healthy men and women identified using the HumanCVD BeadChip.

We have used the gene-centric Illumina HumanCVD BeadChip to identify common genetic determinants of Von Willebrand factor (vWF) levels in healthy men and women. The Whitehall II (WHII) study (n= 5592) and the British Women's Heart and Health Study (BWHHS) (n= 3445) were genotyped using the HumanCVD BeadChip. Replication was conducted in the British Regional Heart Study (n= 3897) and 1958 Birth Cohort (n= 5048). We identified 48 single nucleotide polymorphisms (SNPs) in four genes/regions associated with vWF at P < 10(-4) . These included 19 SNPs at the ABO blood group locus with the lead variant being rs657152 (P= 9.7 × 10(-233) ). The lead variant in the 24 VWF SNPs was rs1063856 (P= 2.3 × 10(-20) ). SNPs at ESR1 (rs6909023) and NRG1(rs1685103) showed modest associations with vWF, but these were not confirmed in a meta-analysis. Using variable selection, five SNPs at the locus for ABO and two for VWF were found to have independent associations with vWF levels. After adjustment for age and gender, the selected ABO SNPs explained 15% and the VWF SNPs an additional 2% of the variance in vWF levels. Individuals at opposite tails of the additive seven SNP allele score exhibited substantial differences in vWF levels. These data demonstrate that multiple common alleles with small effects make, in combination, important contributions to individual differences in vWF levels.