Fotios Drenos

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.

Mendelian randomization of blood lipids for coronary heart disease.

Aims To investigate the causal role of high-density lipoprotein cholesterol (HDL-C) and triglycerides in coronary heart disease (CHD) using multiple instrumental variables for Mendelian randomization. Methods and results We developed weighted allele scores based on single nucleotide polymorphisms (SNPs) with established associations with HDL-C, triglycerides, and low-density lipoprotein cholesterol (LDL-C). For each trait, we constructed two scores. The first was unrestricted, including all independent SNPs associated with the lipid trait identified from a prior meta-analysis (threshold P < 2 × 10−6); and the second a restricted score, filtered to remove any SNPs also associated with either of the other two lipid traits at P ≤ 0.01. Mendelian randomization meta-analyses were conducted in 17 studies including 62,199 participants and 12,099 CHD events. Both the unrestricted and restricted allele scores for LDL-C (42 and 19 SNPs, respectively) associated with CHD. For HDL-C, the unrestricted allele score (48 SNPs) was associated with CHD (OR: 0.53; 95% CI: 0.40, 0.70), per 1 mmol/L higher HDL-C, but neither the restricted allele score (19 SNPs; OR: 0.91; 95% CI: 0.42, 1.98) nor the unrestricted HDL-C allele score adjusted for triglycerides, LDL-C, or statin use (OR: 0.81; 95% CI: 0.44, 1.46) showed a robust association. For triglycerides, the unrestricted allele score (67 SNPs) and the restricted allele score (27 SNPs) were both associated with CHD (OR: 1.62; 95% CI: 1.24, 2.11 and 1.61; 95% CI: 1.00, 2.59, respectively) per 1-log unit increment. However, the unrestricted triglyceride score adjusted for HDL-C, LDL-C, and statin use gave an OR for CHD of 1.01 (95% CI: 0.59, 1.75). Conclusion The genetic findings support a causal effect of triglycerides on CHD risk, but a causal role for HDL-C, though possible, remains less certain.

Chromosome 9p21.3 Coronary Heart Disease Locus Genotype and Prospective Risk of CHD in Healthy Middle-Aged Men

BACKGROUND We investigated whether chromosome 9p21.3 single-nucleotide polymorphisms (SNPs), identified in coronary heart disease (CHD) genome-wide association scans, added significantly to the predictive utility for CHD of conventional risk factors (CRF) in the Framingham risk score (FRS) algorithm. METHODS In the Northwick Park Heart Study II of 2742 men (270 CHD events occurring during a 15-year prospective study), rs10757274 A>G [mean frequency G = 0.48 (95% CI 0.47-0.50)] was genotyped. Using the area under the ROC curve (A(ROC)) and the likelihood ratio (LR) statistic, we assessed the discriminatory performance of the FRS based on CRFs with and without genotype. RESULTS rs10757274 A>G was associated with incident CHD, with an effect size as reported previously [hazard ratio in GG vs AA men of 1.60 (95% CI 1.12-2.28)], independent of CRFs and family history of CHD. Although the A(ROC) for CRFs alone [0.62 (95% CI 0.58-0.66)] did not increase significantly (P = 0.14) when rs10757274 A>G genotype was added [0.64 (95% CI 0.60-0.68)], including genotype gave better fit (LR P = 0.01) and including rs10757274 moved 369 men (13.5% of the total) into more accurate risk categories. To model polygenic effects, 10 hypothetical, randomly assigned gene variants, with similar effect size and frequencies were added. Two variants made significant A(ROC) improvements to the FRS prediction (P = 0.01), whereas further variants had smaller incremental effects (final A(ROC) = 0.71, P <0.001 vs CRFs; LR vs CRFs P <0.0001). CONCLUSIONS Although overall, rs10757274 did not add substantially to the usefulness of the FRS for predicting future events, it did improve reclassification of CHD risk, and thus may have clinical utility.

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 Womens 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.

Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk.

Elevated blood pressure is the leading heritable risk factor for cardiovascular disease worldwide. We report genetic association of blood pressure (systolic, diastolic, pulse pressure) among UK Biobank participants of European ancestry with independent replication in other cohorts, and robust validation of 107 independent loci. We also identify new independent variants at 11 previously reported blood pressure loci. In combination with results from a range of in silico functional analyses and wet bench experiments, our findings highlight new biological pathways for blood pressure regulation enriched for genes expressed in vascular tissues and identify potential therapeutic targets for hypertension. Results from genetic risk score models raise the possibility of a precision medicine approach through early lifestyle intervention to offset the impact of blood pressure–raising genetic variants on future cardiovascular disease risk.

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.

Role of β adrenergic receptor polymorphisms in heart failure: Systematic review and meta-analysis

Heart Failure (HF) is a common disorder associated with substantial morbidity and mortality. β adrenergic receptors (βAR) are the primary pathway through which cardiac function is influenced. Chronic β1AR activation is implicated in the pathogenesis of HF and βAR blockade improves survival in left ventricular systolic dysfunction. Common functional polymorphisms in β adrenergic receptor genes (ADRB) have been associated with HF phenotypes, and with pharmacogenetic interaction with β adrenergic receptor blockers (β blockers). However, these associations have not been consistently replicated. The evidence for ADRB variant involvement in pathogenesis, progression and response to β blockers in HF is reviewed. In addition, a meta‐analysis of three studies analysing the effect of ADRB1 Arg389Gly polymorphism on left ventricular remodelling with the use of β blockers, demonstrating a 5% improvement in left ventricular ejection fraction in Arg389 homozygotes, is presented. There is now accumulating molecular evidence for a different functional response to β blockers associated with this polymorphism. In the future, confirmed genotypic associations may enable patients to be identified who are either at greater risk of developing HF, whose HF may rapidly progress, or who are unlikely to benefit from β blockers, and such patients may benefit from targeted aggressive therapy.

ANGPTL4 E40K and T266M. Effects on Plasma Triglyceride and HDL Levels, Postprandial Responses, and CHD Risk

Background—Angiopoietin-like 4 is a dual-function protein: an inhibitor of LPL, influencing plasma triglycerides (TGs), with angiogenic properties. We examined the association of common ANGPTL4 variants with CHD traits and risk in 5 studies (13 527 individuals). Methods and Results—The effects on plasma lipids of 6 tagging SNPs and the recently identified E40K were examined in a study of 2772 men. Only T266M (rs1044250, MAF=30%) and E40K (MAF=2%) were significantly associated with TG-lowering (−10.4%, P<0.004 and −20.4%, P<0.0001), respectively. T266M no longer showed significant associations when K40 carriers (K40+) were excluded (P=0.2). Combining data from 5 studies confirmed the TG-lowering effect of K40+ (weighted mean difference: −0.12 [95% CI −0.18, −0.05] mmol/L TG P=0.0001). Surprisingly, in the 3 prospective studies, the combined OR for CHD was 1.48 (1.11 to 1.96, P=0.007), independent of TG. In individuals with a paternal history of MI (n=332) T266M, but not E40K, showed effects on postprandial AUC TG and glucose (P=0.009 and P=0.017, respectively) compared to controls (n=370). Conclusion—Although associated with an atheroprotective lipid profile, E40K was associated with increased CHD risk, suggesting Angptl4 influences parameters beyond lipid levels. T266M showed effects only under conditions of postprandial stress. The functionality of these potential “loss-of-function” variants needs validation.

Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci

Meta-analyses of association results for blood pressure using exome-centric single-variant and gene-based tests identified 31 new loci in a discovery stage among 146,562 individuals, with follow-up and meta-analysis in 180,726 additional individuals (total n = 327,288). These blood pressure–associated loci are enriched for known variants for cardiometabolic traits. Associations were also observed for the aggregation of rare and low-frequency missense variants in three genes, NPR1, DBH, and PTPMT1. In addition, blood pressure associations at 39 previously reported loci were confirmed. The identified variants implicate biological pathways related to cardiometabolic traits, vascular function, and development. Several new variants are inferred to have roles in transcription or as hubs in protein–protein interaction networks. Genetic risk scores constructed from the identified variants were strongly associated with coronary disease and myocardial infarction. This large collection of blood pressure–associated loci suggests new therapeutic strategies for hypertension, emphasizing a link with cardiometabolic risk.

Coronary Heart Disease Risk Prediction in the Era of Genome-Wide Association Studies Current Status and What the Future Holds

For DNA-based tests that assess genetic predisposition to coronary heart disease (CHD) to be of clinical value, they need to provide information over and above conventional risk factors (CRFs) currently used in risk algorithms, such as the Framingham Risk Score,1 which incorporates CRFs such as age, gender, blood lipid concentrations, blood pressure, body mass index, family history, and smoking habit. To achieve this, several hurdles must be passed. The first challenge is to identify a set of common single-nucleotide polymorphisms (SNPs) at loci associated with CHD risk. Over the last 10 to 15 years, this has been done by use of a “candidate gene” approach through association studies in prospective analysis or case-control studies, ie, comparing SNP genotype or allele frequency between groups of individuals with CHD and healthy subjects. Several of the genes, chosen because of their key role in processes that predispose to atherosclerosis, have meta-analysis–confirmed effects on risk of CHD,2 the best example of which is the APOE gene, which encodes apolipoprotein E, with 3 common isoforms that are associated with strong effects on plasma lipids and more modest effects on risk of CHD.3 This “hypothesis-driven” search for useful genetic variants provides the foundation for the development of genetic CHD risk profiles, and in the last 2 years, it has been enhanced by technical advances that have allowed “hypothesis-free” genome-wide association studies (GWASs), primarily in a case-control setting. Although the list of identified CHD-risk loci and SNPs will clearly grow, we have at least the basis to start the examination of their potential clinical utility. The second set of challenges is to obtain a robust estimate of the size of the risk effects associated with these SNPs. This requires population-based prospective studies to avoid bias, because estimates in the case-control setting, although efficient for …