Pia R. Kamstrup

Genetically elevated lipoprotein(a) and increased risk of myocardial infarction.

CONTEXT High levels of lipoprotein(a) are associated with increased risk of myocardial infarction (MI). OBJECTIVE To assess whether genetic data are consistent with this association being causal. DESIGN, SETTING, AND PARTICIPANTS Three studies of white individuals from Copenhagen, Denmark, were used: the Copenhagen City Heart Study (CCHS), a prospective general population study with 16 years of follow-up (1991-2007, n = 8637, 599 MI events); the Copenhagen General Population Study (CGPS), a cross-sectional general population study (2003-2006, n = 29 388, 994 MI events); and the Copenhagen Ischemic Heart Disease Study (CIHDS), a case-control study (1991-2004, n = 2461, 1231 MI events). MAIN OUTCOME MEASURES Plasma lipoprotein(a) levels, lipoprotein(a) kringle IV type 2 (KIV-2) size polymorphism genotype, and MIs recorded from 1976 through July 2007 for all participants. RESULTS In the CCHS, multivariable-adjusted hazard ratios (HRs) for MI for elevated lipoprotein(a) levels were 1.2 (95% confidence interval [CI], 0.9-1.6; events/10,000 person-years, 59) for levels between the 22nd and 66th percentile, 1.6 (95% CI, 1.1-2.2; events/10,000 person-years, 75) for the 67th to 89th percentile, 1.9 (95% CI, 1.2-3.0; events/10,000 person-years, 84) for the 90th to 95th percentile, and 2.6 (95% CI, 1.6-4.1; events/10,000 person-years, 108) for levels greater than the 95th percentile, respectively, vs levels less than the 22nd percentile (events/10,000 person-years, 55) (trend P < .001). Numbers of KIV-2 repeats (sum of repeats on both alleles) ranged from 6 to 99 and on analysis of variance explained 21% and 27% of all variation in plasma lipoprotein(a) levels in the CCHS and CGPS, respectively. Mean lipoprotein(a) levels were 56, 31, 20, and 15 mg/dL for the first, second, third, and fourth quartiles of KIV-2 repeats in the CCHS, respectively (trend P < .001); corresponding values in the CGPS were 60, 34, 22, and 19 mg/dL (trend P < .001). In the CCHS, multivariable-adjusted HRs for MI were 1.5 (95% CI, 1.2-1.9; events/10,000 person-years, 75), 1.3 (95% CI, 1.0-1.6; events/10,000 person-years, 66), and 1.1 (95% CI, 0.9-1.4; events/10,000 person-years, 57) for individuals in the first, second, and third quartiles, respectively, as compared with individuals in the fourth quartile of KIV-2 repeats (events/10,000 person-years, 51) (trend P < .001). Corresponding odds ratios were 1.3 (95% CI, 1.1-1.5), 1.1 (95% CI, 0.9-1.3), and 0.9 (95% CI, 0.8-1.1) in the CGPS (trend P = .005), and 1.4 (95% CI, 1.1-1.7), 1.2 (95% CI, 1.0-1.6), and 1.3 (95% CI, 1.0-1.6) in the CIHDS (trend P = .01). Genetically elevated lipoprotein(a) was associated with an HR of 1.22 (95% CI, 1.09-1.37) per doubling of lipoprotein(a) level on instrumental variable analysis, while the corresponding value for plasma lipoprotein(a) levels on Cox regression was 1.08 (95% CI, 1.03-1.12). CONCLUSION These data are consistent with a causal association between elevated lipoprotein(a) levels and increased risk of MI.

Genetic Associations with Valvular Calcification and Aortic Stenosis

BACKGROUND Limited information is available regarding genetic contributions to valvular calcification, which is an important precursor of clinical valve disease. METHODS We determined genomewide associations with the presence of aortic-valve calcification (among 6942 participants) and mitral annular calcification (among 3795 participants), as detected by computed tomographic (CT) scanning; the study population for this analysis included persons of white European ancestry from three cohorts participating in the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (discovery population). Findings were replicated in independent cohorts of persons with either CT-detected valvular calcification or clinical aortic stenosis. RESULTS One SNP in the lipoprotein(a) (LPA) locus (rs10455872) reached genomewide significance for the presence of aortic-valve calcification (odds ratio per allele, 2.05; P=9.0×10(-10)), a finding that was replicated in additional white European, African-American, and Hispanic-American cohorts (P<0.05 for all comparisons). Genetically determined Lp(a) levels, as predicted by LPA genotype, were also associated with aortic-valve calcification, supporting a causal role for Lp(a). In prospective analyses, LPA genotype was associated with incident aortic stenosis (hazard ratio per allele, 1.68; 95% confidence interval [CI], 1.32 to 2.15) and aortic-valve replacement (hazard ratio, 1.54; 95% CI, 1.05 to 2.27) in a large Swedish cohort; the association with incident aortic stenosis was also replicated in an independent Danish cohort. Two SNPs (rs17659543 and rs13415097) near the proinflammatory gene IL1F9 achieved genomewide significance for mitral annular calcification (P=1.5×10(-8) and P=1.8×10(-8), respectively), but the findings were not replicated consistently. CONCLUSIONS Genetic variation in the LPA locus, mediated by Lp(a) levels, is associated with aortic-valve calcification across multiple ethnic groups and with incident clinical aortic stenosis. (Funded by the National Heart, Lung, and Blood Institute and others.).

Extreme Lipoprotein(a) Levels and Risk of Myocardial Infarction in the General Population The Copenhagen City Heart Study

Background— Elevated lipoprotein(a) levels are associated with myocardial infarction (MI) in some but not all studies. Limitations of previous studies include lack of risk estimates for extreme lipoprotein(a) levels, measurements in long-term frozen samples, no correction for regression dilution bias, and lack of absolute risk estimates in the general population. We tested the hypothesis that extreme lipoprotein(a) levels predict MI in the general population, measuring levels shortly after sampling, correcting for regression dilution bias, and calculating hazard ratios and absolute risk estimates. Methods and Results— We examined 9330 men and women from the general population in the Copenhagen City Heart Study. During 10 years of follow-up, 498 participants developed MI. In women, multifactorially adjusted hazard ratios for MI for elevated lipoprotein(a) levels were 1.1 (95% CI, 0.6 to 1.9) for 5 to 29 mg/dL (22nd to 66th percentile), 1.7 (1.0 to 3.1) for 30 to 84 mg/dL (67th to 89th percentile), 2.6 (1.2 to 5.9) for 85 to 119 mg/dL (90th to 95th percentile), and 3.6 (1.7 to 7.7) for ≥120 mg/dL (>95th percentile) versus levels <5 mg/dL (<22nd percentile). Equivalent values in men were 1.5 (0.9 to 2.3), 1.6 (1.0 to 2.6), 2.6 (1.2 to 5.5), and 3.7 (1.7 to 8.0). Absolute 10-year risks of MI were 10% and 20% in smoking, hypertensive women aged >60 years with lipoprotein(a) levels of <5 and ≥120 mg/dL, respectively. Equivalent values in men were 19% and 35%. Conclusions— We observed a stepwise increase in risk of MI with increasing levels of lipoprotein(a), with no evidence of a threshold effect. Extreme lipoprotein(a) levels predict a 3- to 4-fold increase in risk of MI in the general population and absolute 10-year risks of 20% and 35% in high-risk women and men.

Fasting is not routinely required for determination of a lipid profile: clinical and laboratory implications including flagging at desirable concentration cut-points—a joint consensus statement from the European Atherosclerosis Society and European Federation of Clinical Chemistry and Laboratory Medicine

Abstract Aims To critically evaluate the clinical implications of the use of non-fasting rather than fasting lipid profiles and to provide guidance for the laboratory reporting of abnormal non-fasting or fasting lipid profiles. Methods and results Extensive observational data, in which random non-fasting lipid profiles have been compared with those determined under fasting conditions, indicate that the maximal mean changes at 1–6 h after habitual meals are not clinically significant [+0.3 mmol/L (26 mg/dL) for triglycerides; −0.2 mmol/L (8 mg/dL) for total cholesterol; −0.2 mmol/L (8 mg/dL) for LDL cholesterol; +0.2 mmol/L (8 mg/dL) for calculated remnant cholesterol; −0.2 mmol/L (8 mg/dL) for calculated non-HDL cholesterol]; concentrations of HDL cholesterol, apolipoprotein A1, apolipoprotein B, and lipoprotein(a) are not affected by fasting/non-fasting status. In addition, non-fasting and fasting concentrations vary similarly over time and are comparable in the prediction of cardiovascular disease. To improve patient compliance with lipid testing, we therefore recommend the routine use of non-fasting lipid profiles, while fasting sampling may be considered when non-fasting triglycerides >5 mmol/L (440 mg/dL). For non-fasting samples, laboratory reports should flag abnormal concentrations as triglycerides ≥2 mmol/L (175 mg/dL), total cholesterol ≥5 mmol/L (190 mg/dL), LDL cholesterol ≥3 mmol/L (115 mg/dL), calculated remnant cholesterol ≥0.9 mmol/L (35 mg/dL), calculated non-HDL cholesterol ≥3.9 mmol/L (150 mg/dL), HDL cholesterol ≤1 mmol/L (40 mg/dL), apolipoprotein A1 ≤1.25 g/L (125 mg/dL), apolipoprotein B ≥1.0 g/L (100 mg/dL), and lipoprotein(a) ≥50 mg/dL (80th percentile); for fasting samples, abnormal concentrations correspond to triglycerides ≥1.7 mmol/L (150 mg/dL). Life-threatening concentrations require separate referral when triglycerides >10 mmol/L (880 mg/dL) for the risk of pancreatitis, LDL cholesterol >13 mmol/L (500 mg/dL) for homozygous familial hypercholesterolaemia, LDL cholesterol >5 mmol/L (190 mg/dL) for heterozygous familial hypercholesterolaemia, and lipoprotein(a) >150 mg/dL (99th percentile) for very high cardiovascular risk. Conclusion We recommend that non-fasting blood samples be routinely used for the assessment of plasma lipid profiles. Laboratory reports should flag abnormal values on the basis of desirable concentration cut-points. Non-fasting and fasting measurements should be complementary but not mutually exclusive.

Lipoprotein(a) and Risk of Type 2 Diabetes

BACKGROUND Previous studies have demonstrated that cardiovascular risk is higher with increased lipoprotein(a) [Lp(a)]. Whether Lp(a) concentration is related to type 2 diabetes is unclear. METHODS In 26 746 healthy US women (mean age 54.6 years), we prospectively examined baseline Lp(a) concentrations and incident type 2 diabetes (n = 1670) for a follow-up period of 13 years. We confirmed our findings in 9652 Danish men and women with prevalent diabetes (n = 419). Analyses were adjusted for risk factors that included age, race, smoking, hormone use, family history, blood pressure, body mass index, hemoglobin A(1c) (Hb A(1c)), C-reactive protein, and lipids. RESULTS Lp(a) was inversely associated with incident diabetes, with fully adjusted hazard ratios (HRs) and 95% CIs for quintiles 2-5 vs quintile 1 of 0.87 (0.75-1.01), 0.80 (0.68-0.93), 0.88 (0.76-1.02), and 0.78 (0.67-0.91); P for trend 0.002. The association was stronger in nonfasting women, for whom respective HRs were 0.79 (0.58-1.09), 0.78 (0.57-1.08), 0.66 (0.46-0.93), and 0.56 (0.40-0.80); P for trend 0.001; P for interaction with fasting status 0.002. When we used Lp(a) > or =10 mg/L and Hb A(1c) <5% as reference values, the adjusted HRs were 1.62 (0.91-2.89) for Lp(a) <10 mg/L and Hb A(1c) <5%, 3.50 (3.06-4.01) for Lp(a) > or =10 mg/L and Hb A(1c) 5%-<6.5%, and 5.36 (4.00-7.19) for Lp(a) <10 mg/L and Hb A(1c) 5%-<6.5%. Results were similar in nonfasting Danish men and women, for whom adjusted odds ratios were 0.75 (0.55-1.03), 0.64 (0.46-0.88), 0.74 (0.54-1.01), and 0.58 (0.42-0.79) for Lp(a) quintiles 2-5 vs quintile 1; P for trend 0.002. CONCLUSIONS Our results indicated that Lp(a) was associated inversely with risk of type 2 diabetes independently of risk factors, in contrast to prior findings of positive associations of Lp(a) with cardiovascular risk.

Lipoprotein(a) and ischemic heart disease—A causal association? A review

The aim of this review is to summarize present evidence of a causal association of lipoprotein(a) with risk of ischemic heart disease (IHD). Evidence for causality includes reproducible associations of a proposed risk factor with risk of disease in epidemiological studies, evidence from in vitro and animal studies in support of pathophysiological effects of the risk factor, and preferably evidence from randomized clinical trials documenting reduced morbidity in response to interventions targeting the risk factor. Elevated and in particular extreme lipoprotein(a) levels have in prospective studies repeatedly been associated with increased risk of IHD, although results from early studies are inconsistent. Data from in vitro and animal studies implicate lipoprotein(a), consisting of a low density lipoprotein particle covalently bound to the plasminogen-like glycoprotein apolipoprotein(a), in both atherosclerosis and thrombosis, including accumulation of lipoprotein(a) in atherosclerotic plaques and attenuation of t-PA mediated plasminogen activation. No randomized clinical trial of the effect of lowering lipoprotein(a) levels on IHD prevention has ever been conducted. Lacking evidence from randomized clinical trials, genetic studies, such as Mendelian randomization studies, can also support claims of causality. Levels of lipoprotein(a) are primarily determined by variation in the LPA gene coding for the apolipoprotein(a) moiety of lipoprotein(a), and genetic epidemiologic studies have documented association of LPA copy number variants, influencing levels of lipoprotein(a), with risk of IHD. In conclusion, results from epidemiologic, in vitro, animal, and genetic epidemiologic studies support a causal association of lipoprotein(a) with risk of IHD, while results from randomized clinical trials are presently lacking.

Extreme Lipoprotein(a) Levels and Improved Cardiovascular Risk Prediction

OBJECTIVES The study tested whether extreme lipoprotein(a) levels and/or corresponding LPA risk genotypes improve myocardial infarction (MI) and coronary heart disease (CHD) risk prediction beyond conventional risk factors. BACKGROUND Elevated lipoprotein(a) levels cause MI and CHD. Levels are primarily determined by variation in the LPA gene. METHODS We followed 8,720 Danish participants in a general population study from 1991 to 1994 through 2011 without losses to follow-up. During this period, 730 and 1,683 first-time MI and CHD events occurred. Using predefined cutpoints for extreme lipoprotein(a) levels and/or corresponding LPA risk genotypes (kringle IV type 2 [KIV-2]) repeat polymorphism, rs3798220, and rs10455872 single nucleotide polymorphisms), we calculated net reclassification indices from <10% to 10% to 19.9% to ≥20% absolute 10-year MI and CHD risk. RESULTS For individuals with lipoprotein(a) levels ≥80th percentile (≥47 mg/dl), 23% (p < 0.001) of MI events and 12% (p < 0.001) of CHD events were reclassified correctly, while no events were reclassified incorrectly for either endpoint. As some incorrect reclassification of individuals with no events occurred, addition of lipoprotein(a) levels ≥80th percentile overall yielded net reclassification indices of +16% (95% confidence interval: 8% to 24%) and +3% (-1% to 8%) for MI and CHD, respectively. Corresponding net reclassification indices for number of KIV-2 repeats ≤21st percentile were +12% (5% to 19%) and +4% (0% to 8%), for rs3798220 carrier status +15% (-14% to 44%) and +10% (-10% to 30%), and for rs10455872 carrier status +16% (6% to 26%) and +2% (-1% to 6%). Considering only individuals at 10% to 19.9% absolute 10-year MI and CHD risk, addition of extreme lipoprotein(a) levels or corresponding LPA risk genotypes improved risk prediction even further. CONCLUSIONS Extreme lipoprotein(a) levels or corresponding LPA KIV-2/rs10455872 risk genotypes substantially improved MI and CHD risk prediction.

Hepatic Lipase, Genetically Elevated High-Density Lipoprotein, and Risk of Ischemic Cardiovascular Disease

CONTEXT Hepatic lipase influences metabolism of high-density lipoprotein (HDL), a risk factor for ischemic cardiovascular disease (ICD: ischemic heart disease and ischemic cerebrovascular disease). OBJECTIVE We tested the hypothesis that genetic variation in the hepatic lipase genetic variants V73M, N193S, S267F, L334F, T383M, and -480c>t influence levels of lipids, lipoproteins, and apolipoproteins and risk of ICD. DESIGN For the cross-sectional study, we genotyped 9003 individuals from the Copenhagen City Heart Study; hereof were 8971 individuals included in the prospective study, 1747 of whom had incident ICD during 28 yr of follow-up. For the case-control studies, 2110 ischemic heart disease patients vs. 4899 controls and 769 ischemic cerebrovascular disease patients vs. 2836 controls, respectively, were genotyped. Follow-up was 100% complete. RESULTS HDL cholesterol was higher by 0.21 mmol/liter in S267F heterozygotes, by 0.06 mmol/liter in -480c>t heterozygotes, and by 0.13 mmol/liter in -480c>t homozygotes, as compared with noncarriers. These HDL increases theoretically predicted hazard ratios for ICD of 0.87 [95% confidence interval (CI) 0.84-0.90], 0.96 (95% CI 0.95-0.97), and 0.91 (95% CI 0.89-0.94), respectively; this calculation assumes that genetically elevated HDL levels confer decreased risk similar to common HDL elevations. In contrast, when all cases and controls were combined, the observed odds ratios for ICD for these three genetic variants vs. noncarriers were 1.19 (0.76-1.88), 1.04 (0.96-1.13), and 1.08 (0.89-1.30), respectively. Hazard/odds ratios for ICD in carriers vs. noncarriers of the four remaining hepatic lipase genetic variants did not differ consistently from 1.0. CONCLUSION Hepatic lipase genetic variants with elevated levels of HDL cholesterol did not associate with risk of ICD.

Genetic Evidence That Lipoprotein(a) Associates With Atherosclerotic Stenosis Rather Than Venous Thrombosis

Objective—The aim of the present study was to determine whether lipoprotein(a) [Lp(a)], considered a causal risk factor for cardiovascular disease, primarily promotes thrombosis or atherosclerosis. Methods and Results—Using a Mendelian randomization study design, we measured plasma Lp(a) and genetically elevated Lp(a) levels through the LPA kringle IV type 2 repeat genotype in 41231 individuals. We included 2 general population studies of both venous thrombosis and combined thrombosis and atherosclerosis in coronary arteries (=myocardial infarction), and 3 case–control studies of atherosclerotic stenosis. Neither Lp(a) tertiles nor LPA kringle IV type 2 tertiles associated with the risk of venous thrombosis in general population studies (trend: P=0.12–0.76), but did each associate with risk of coronary, carotid, and femoral atherosclerotic stenosis in case–control studies (trend: P<0.001 to 0.04). Lp(a) and LPA kringle IV type 2 tertiles also associated with the risk of myocardial infarction in general population studies (trend: P<0.001 to 0.003). For doubling of Lp(a) levels, instrumental variable estimates of hazard/odds ratios were 1.02 (95% CI 0.90–1.15) and 1.04 (0.93–1.16) for venous thrombosis in the 2 general population studies, 1.12 (1.01–1.25), 1.17 (1.05–1.32), and 1.16 (1.01–1.35), respectively, for coronary, carotid, and femoral atherosclerotic stenosis in case–control studies, and 1.21 (1.10–1.33) and 1.17 (1.05–1.29) for myocardial infarction in general population studies. Conclusion—This supports that Lp(a) primarily promotes atherosclerotic stenosis rather than venous thrombosis.

Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms

Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP–CAD associations (P < 5 × 10−8, in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms.