87 research outputs found

    Metabolic effects of PCSK9 inhibition with Evolocumab in subjects with elevated Lp(a)

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    Background: Epidemiological studies substantiated that subjects with elevated lipoprotein(a) [Lp(a)] have a markedly increased cardiovascular risk. Inhibition of proprotein convertase subtilisin/kexin type 9 (PCSK9) lowers both LDL cholesterol (LDL-C) as well as Lp(a), albeit modestly. Effects of PCSK9 inhibition on circulating metabolites such as lipoprotein subclasses, amino acids and fatty acids remain to be characterized. Methods: We performed nuclear magnetic resonance (NMR) metabolomics on plasma samples derived from 30 individuals with elevated Lp(a) (> 150 mg/dL). The 30 participants were randomly assigned into two groups, placebo (N = 14) and evolocumab (N = 16). We assessed the effect of 16 weeks of evolocumab 420 mg Q4W treatment on circulating metabolites by running lognormal regression analyses, and compared this to placebo. Subsequently, we assessed the interrelationship between Lp(a) and 14 lipoprotein subclasses in response to treatment with evolocumab, by running multilevel multivariate regression analyses. Results: On average, evolocumab treatment for 16 weeks resulted in a 17% (95% credible interval: 8 to 26%, P < 0.001) reduction of circulating Lp(a), coupled with substantial reduction of VLDL, IDL and LDL particles as well as their lipid contents. Interestingly, increasing concentrations of baseline Lp(a) were associated with larger reduction in triglyceride-rich VLDL particles after evolocumab treatment. Conclusions: Inhibition of PCSK9 with evolocumab markedly reduced VLDL particle concentrations in addition to lowering LDL-C. The extent of reduction in VLDL particles depended on the baseline level of Lp(a). Our findings suggest a marked effect of evolocumab on VLDL metabolism in subjects with elevated Lp(a). Trial registration: Clinical trial registration information is registered at ClinicalTrials.gov on April 14, 2016 with the registration number NCT02729025.</p

    Endothelin in renal pathophysiology: From experimental to therapeutic application

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    Systematic review and network meta-analysis on the efficacy of evolocumab and other therapies for the management of lipid levels in hyperlipidemia

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    Background: The proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors evolocumab and alirocumab substantially reduce low‐density lipoprotein cholesterol (LDL‐C) when added to statin therapy in patients who need additional LDL‐C reduction. Methods and Results: We conducted a systematic review and network meta‐analysis of randomized trials of lipid‐lowering therapies from database inception through August 2016 (45 058 records retrieved). We found 69 trials of lipid‐lowering therapies that enrolled patients requiring further LDL‐C reduction while on maximally tolerated medium‐ or high‐intensity statin, of which 15 could be relevant for inclusion in LDL‐C reduction networks with evolocumab, alirocumab, ezetimibe, and placebo as treatment arms. PCSK9 inhibitors significantly reduced LDL‐C by 54% to 74% versus placebo and 26% to 46% versus ezetimibe. There were significant treatment differences for evolocumab 140 mg every 2 weeks at the mean of weeks 10 and 12 versus placebo (−74.1%; 95% credible interval −79.81% to −68.58%), alirocumab 75 mg (−20.03%; 95% credible interval −27.32% to −12.96%), and alirocumab 150 mg (−13.63%; 95% credible interval −22.43% to −5.33%) at ≄12 weeks. Treatment differences were similar in direction and magnitude for PCSK9 inhibitor monthly dosing. Adverse events were similar between PCSK9 inhibitors and control. Rates of adverse events were similar between PCSK9 inhibitors versus placebo or ezetimibe. Conclusions: PCSK9 inhibitors added to medium‐ to high‐intensity statin therapy significantly reduce LDL‐C in patients requiring further LDL‐C reduction. The network meta‐analysis showed a significant treatment difference in LDL‐C reduction for evolocumab versus alirocumab

    A six question screen to facilitate primary cardiovascular disease prevention

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    Background: European guidelines on primary prevention of cardiovascular disease (CVD) recommend the SCORE risk charts for determining CVD risk, which include blood pressure and serum cholesterol as risk parameters. To facilitate cost-effective large-scale screening, we aimed to construct a risk score with 'non-invasive' parameters as a first screening step to identify persons at increased CVD risk requiring further risk assessment. Methods: We used data of Dutch employees from 25 organisations participating in a health risk assessment between August 2007 and January 2013. Backward multivariate logistic regression analysis was employed to select non-invasive, independent predictors of high CVD risk, defined as the 10-year risk of fatal CVD of ≄5 % based on the SCORE formula. The total CVD risk score was calculated as the summed coefficients of the retained variables. Results: Data of 6189 male participants was used for the development and validation of the risk score. Age, tobacco use, history of hypertension, alcohol consumption, BMI, and waist circumference were independent predictors of high CVD risk. Ten-fold cross-validation resulted in an area under the curve of 0.95 (SE 0.01, 95 % confidence interval 0.94-0.96). A cut-off score ≄45 on the CVD risk score yielded a sensitivity of 0.93, and a specificity of 0.85. Conclusions: We developed a simple, non-invasive risk score that accurately identifies persons at increased CVD risk according to the SCORE formula in a population of working men. The risk score enables a stepwise approach in large screening programmes, strongly reducing the number of persons that require full risk estimation including blood pressure and cholesterol measures

    Thresholds for Arterial Wall Inflammation Quantified by 18F-FDG PET Imaging Implications for Vascular Interventional Studies

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    AbstractObjectivesThis study assessed 5 frequently applied arterial 18fluorodeoxyglucose (18F-FDG) uptake metrics in healthy control subjects, those with risk factors and patients with cardiovascular disease (CVD), to derive uptake thresholds in each subject group. Additionally, we tested the reproducibility of these measures and produced recommended sample sizes for interventional drug studies.Background18F-FDG positron emission tomography (PET) can identify plaque inflammation as a surrogate endpoint for vascular interventional drug trials. However, an overview of 18F-FDG uptake metrics, threshold values, and reproducibility in healthy compared with diseased subjects is not available.Methods18F-FDG PET/CT of the carotid arteries and ascending aorta was performed in 83 subjects (61 ± 8 years) comprising 3 groups: 25 healthy controls, 23 patients at increased CVD risk, and 35 patients with known CVD. We quantified 18F-FDG uptake across the whole artery, the most-diseased segment, and within all active segments over several pre-defined cutoffs. We report these data with and without background corrections. Finally, we determined measurement reproducibility and recommended sample sizes for future drug studies based on these results.ResultsAll 18F-FDG uptake metrics were significantly different between healthy and diseased subjects for both the carotids and aorta. Thresholds of physiological 18F-FDG uptake were derived from healthy controls using the 90th percentile of their target to background ratio (TBR) value (TBRmax); whole artery TBRmax is 1.84 for the carotids and 2.68 in the aorta. These were exceeded by >52% of risk factor patients and >67% of CVD patients. Reproducibility was excellent in all study groups (intraclass correlation coefficient >0.95). Using carotid TBRmax as a primary endpoint resulted in sample size estimates approximately 20% lower than aorta.ConclusionsWe report thresholds for physiological 18F-FDG uptake in the arterial wall in healthy subjects, which are exceeded by the majority of CVD patients. This remains true, independent of readout vessel, signal quantification method, or the use of background correction. We also confirm the high reproducibility of 18F-FDG PET measures of inflammation. Nevertheless, because of overlap between subject categories and the relatively small population studied, these data have limited generalizability until substantiated in larger, prospective event-driven studies. (Vascular Inflammation in Patients at Risk for Atherosclerotic Disease; NTR5006

    Low-Cost High-Throughput Genotyping for Diagnosing Familial Hypercholesterolemia

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    BACKGROUND: Familial hypercholesterolemia (FH) is a common but underdiagnosed genetic disorder characterized by high low-density lipoprotein cholesterol levels and premature cardiovascular disease. Current sequencing methods to diagnose FH are expensive and time-consuming. In this study, we evaluated the accuracy of a low-cost, high-throughput genotyping array for diagnosing FH. METHODS: An Illumina Global Screening Array was customized to include probes for 636 variants, previously classified as FH-causing variants. First, its theoretical coverage was assessed in all FH variant carriers diagnosed through next-generation sequencing between 2016 and 2022 in the Netherlands (n=1772). Next, the performance of the array was validated in another sample of FH variant carriers previously identified in the Dutch FH cascade screening program (n=1268). RESULTS: The theoretical coverage of the array for FH-causing variants was 91.3%. Validation of the array was assessed in a sample of 1268 carriers of whom 1015 carried a variant in LDLR, 250 in APOB, and 3 in PCSK9. The overall sensitivity was 94.7% and increased to 98.2% after excluding participants with variants not included in the array design. Copy number variation analysis yielded a 89.4% sensitivity. In 18 carriers, the array identified a total of 19 additional FH-causing variants. Subsequent DNA analysis confirmed 5 of the additionally identified variants, yielding a false-positive result in 16 subjects (1.3%).CONCLUSIONS: The FH genotyping array is a promising tool for genetically diagnosing FH at low costs and has the potential to greatly increase accessibility to genetic testing for FH. Continuous customization of the array will further improve its performance.</p

    Association of Lipoprotein(a) With Atherosclerotic Plaque Progression

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    BACKGROUND: Lipoprotein(a) [Lp(a)] is associated with increased risk of myocardial infarction, although the mechanism for this observation remains uncertain. OBJECTIVES: This study aims to investigate whether Lp(a) is associated with adverse plaque progression. METHODS: Lp(a) was measured in patients with advanced stable coronary artery disease undergoing coronary computed tomography angiography at baseline and 12 months to assess progression of total, calcific, noncalcific, and low-attenuation plaque (necrotic core) in particular. High Lp(a) was defined as Lp(a) ≄ 70 mg/dL. The relationship of Lp(a) with plaque progression was assessed using linear regression analysis, adjusting for body mass index, segment involvement score, and ASSIGN score (a Scottish cardiovascular risk score comprised of age, sex, smoking, blood pressure, total and high-density lipoprotein [HDL]–cholesterol, diabetes, rheumatoid arthritis, and deprivation index). RESULTS: A total of 191 patients (65.9 ± 8.3 years of age; 152 [80%] male) were included in the analysis, with median Lp(a) values of 100 (range: 82 to 115) mg/dL and 10 (range: 5 to 24) mg/dL in the high and low Lp(a) groups, respectively. At baseline, there was no difference in coronary artery disease severity or plaque burden. Patients with high Lp(a) showed accelerated progression of low-attenuation plaque compared with low Lp(a) patients (26.2 ± 88.4 mm(3) vs −0.7 ± 50.1 mm(3); P = 0.020). Multivariable linear regression analysis confirmed the relation between Lp(a) and low-attenuation plaque volume progression (ÎČ = 10.5% increase for each 50 mg/dL Lp(a), 95% CI: 0.7%-20.3%). There was no difference in total, calcific, and noncalcific plaque volume progression. CONCLUSIONS: Among patients with advanced stable coronary artery disease, Lp(a) is associated with accelerated progression of coronary low-attenuation plaque (necrotic core). This may explain the association between Lp(a) and the high residual risk of myocardial infarction, providing support for Lp(a) as a treatment target in atherosclerosis

    Serum Lipoprotein(a) and Bioprosthetic Aortic Valve Degeneration

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    AIMS: Bioprosthetic aortic valve degeneration demonstrates pathological similarities to aortic stenosis. Lipoprotein(a) [Lp(a)] is a well-recognized risk factor for incident aortic stenosis and disease progression. The aim of this study is to investigate whether serum Lp(a) concentrations are associated with bioprosthetic aortic valve degeneration. METHODS AND RESULTS: In a post hoc analysis of a prospective multimodality imaging study (NCT02304276), serum Lp(a) concentrations, echocardiography, contrast-enhanced computed tomography (CT) angiography, and 18F-sodium fluoride (18F-NaF) positron emission tomography (PET) were assessed in patients with bioprosthetic aortic valves. Patients were also followed up for 2 years with serial echocardiography. Serum Lp(a) concentrations [median 19.9 (8.4-76.4) mg/dL] were available in 97 participants (mean age 75 ± 7 years, 54% men). There were no baseline differences across the tertiles of serum Lp(a) concentrations for disease severity assessed by echocardiography [median peak aortic valve velocity: highest tertile 2.5 (2.3-2.9) m/s vs. lower tertiles 2.7 (2.4-3.0) m/s, P = 0.204], or valve degeneration on CT angiography (highest tertile n = 8 vs. lower tertiles n = 12, P = 0.552) and 18F-NaF PET (median tissue-to-background ratio: highest tertile 1.13 (1.05-1.41) vs. lower tertiles 1.17 (1.06-1.53), P = 0.889]. After 2 years of follow-up, there were no differences in annualized change in bioprosthetic hemodynamic progression [change in peak aortic valve velocity: highest tertile [0.0 (-0.1-0.2) m/s/year vs. lower tertiles 0.1 (0.0-0.2) m/s/year, P = 0.528] or the development of structural valve degeneration. CONCLUSION: Serum lipoprotein(a) concentrations do not appear to be a major determinant or mediator of bioprosthetic aortic valve degeneration
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