Notice bibliographique
Résumé
Lipoproteins are major mediators of atherosclerosis, myocardial infarction, and cardiovascular death. While lowering of LDLs has convincingly been shown to reduce cardiovascular events, the role of(HDLs as a therapeutic target is less clear. Indeed, HDL is much more heterogenous in its size and composition than LDL. This may at least in part explain why attempts to reduce cardiovascular events by pharmacologically increasing HDL plasma levels have failed.1–5 Even for LDL, particle size may matter. Furthermore, although statins are able to reduce LDL plasma levels and cardiovascular events successfully, there is considerable remaining risk. Thus, novel approaches to lower LDL levels further are of great interest. The current issue of the European Heart Journal addresses these important issues in four clinical and basic science papers. The first paper ‘HDL cholesterol subclasses, myocardial infarction, and mortality in secondary prevention: the Lipoprotein Investigators Collaborative’ by Seth Shay Martin et al. from Johns Hopkins University School of Medicine in Baltimore,6 commented on in an Editorial by Jean-Claude Tardif from the Montreal Heart Institute,7 concerns the heterogeneity of HDL and the link of its subclasses to prognosis. The authors analysed data from two, complementary prospective cohorts: the TRIUMPH study of 2465 patients with acute myocardial infarction, and the IHCS study involving 2414 patients who underwent coronary angiography. All patients had baseline HDL subclassification by vertical-spin density gradient ultracentrifugation stratified by tertiles of HDL-cholesterol (HDL-C) and its two major subclasses (HDL2-C and HDL3-C). HDL3-C accounted for more than three-quarters of HDL-C. During 2 years of follow-up in TRIUMPH, mortality was 9.2%. In IHCS patients, death and myocardial infarction averaged 16.6% over 5 years. No independent associations with outcomes were observed for HDL-C or HDL2-C. In contrast, the lowest tertile of HDL3-C was independently associated with a >50% higher risk in each cohort. Thus, in secondary prevention, low HDL3-C, but not HDL2-C or HDL-C, is associated with an increased risk of major clinical events, highlighting the potential value of subclassifying HDL-C for risk stratification. The second paper ‘Low-density lipoprotein particle diameter and mortality: the Ludwigshafen Risk and Cardiovascular Health Study’ by Hubert Scharnagl et al. from the Medical University of Graz in Austria8 focuses on a similar issue. The authors investigated whether changes in average diameter of LDL particles are associated with mortality. They studied 1643 subjects referred for coronary angiography, who did not receive lipid-lowering drugs, and calculated the average particle diameter of LDLs. When LDLs with intermediate diameter (16.5–16.8 nm) were used as reference, the hazard ratios (HRs) adjusted for cardiovascular risk factors for death from any cause were 1.71 and 1.24 in patients with large (>16.8 nm) or small LDLs (<16.5 nm), respectively. Adjusted HRs for death from cardiovascular causes were 1.89 and 1.54 in patients with large or small LDLs, respectively. Patients with large LDLs had higher concentrations of inflammatory markers such as interleukin-6 and C-reactive protein. Equilibrium density gradient ultracentrifugation revealed characteristic and distinct profiles of LDL particles in persons with large, intermediate, or small LDL particles. Thus, calculated LDL particle diameters identify patients with different profiles of LDL subfractions. Both large and small LDL diameters are independently associated with an increased risk for all-cause and cardiovascular mortality compared with LDLs of intermediate size. The third paper ‘Anacetrapib reduces progression of atherosclerosis, mainly by reducing non-HDL-cholesterol, improves lesion stability, and adds to the beneficial effects of atorvastatin’ by Susan Kühnast et al. (from the TNO, Metabolic Health Research in Leiden, The Netherlands) is an experimental study that investigated the cholesteryl ester transfer protein (CETP) which transfers cholesteryl esters from atheroprotective HDL to atherogenic (V)LDL.9 The authors used the CETP inhibitor anacetrapib that decreases (V)LDL-C by ∼15–40% and increases HDL-C by 40–140%. They evaluated the effect of a broad dose range of anacetrapib on atherosclerosis and HDL function, and possible additive or synergistic effects on top of atorvastatin in APOE*3Leiden mice. Mice were fed a diet without or with ascending dosages of anacetrapib, and atorvastatin alone or in combination with anacetrapib for 21 weeks. Anacetrapib dose-dependently reduced CETP activity by 59–100%, thereby decreasing non-HDL-C by 24–45% and increasing HDL-C by 30–86%. Anacetrapib dose-dependently reduced atherosclerotic lesion area by 41–2% and increased the plaque stability index. It further added to the effects of atorvastatin by further decreasing lesion size by 95%. Of note, both anacetrapib and non-HDL-C, but not HDL-C, independently determined lesion size. The authors conclude that anacetrapib dose-dependently reduces atherosclerosis, and adds to the antiatherogenic effects of atorvastatin, which is mainly ascribed to a reduction in non-HDL-C. These findings are of utmost importance for the interpretation of the upcoming Reveal-TIMI55 trial10 with anacetrapib scheduled to be presented in 2015 or 2016. The fourth paper ‘The Sirt1 activator SRT3025 provides atheroprotection in Apoe–/– mice by reducing hepatic Pcsk9 secretion and enhancing Ldlr expression’ by Christian M. Matter et al. from the Center for Molecular Cardiology of the University of Zurich investigated the effects of the novel deacetylase sirtuin 1 (SIRT1) activator SRT3025 on atherosclerosis in genetically modified mice.11 Sirt1 exerts beneficial effects on lipid metabolism, but its roles in the regulation of plasma LDL-C and atherosclerosis are unclear. Apolipoprotein E-deficient (Apoe–/–) mice were fed a high-cholesterol diet with or without SRT3025 (3.18 g/kg diet) for 12 weeks. In vitro, the drug activated Sirt1 protein, but not the activation-resistant Sirt1 mutant. SRT3025 treatment decreased plasma levels of LDL-cholesterol and total cholesterol and reduced atherosclerosis. Drug treatment did not change mRNA expression of hepatic LDL receptor (Ldlr) and proprotein convertase subtilisin/kexin type 9 (Pcsk9), but increased their protein expression, indicating post-translational effects. Consistent with hepatocyte Ldlr and Pcsk9 accumulation, the authors found reduced plasma levels of Pcsk9 after Sirt1 activation. In vitro administration of SRT3025 to cultured hepatocytes attenuated Pcsk9 secretion and its binding to Ldlr, thereby reducing Pcsk9-mediated Ldlr degradation and increasing expression and LDL uptake. Co-administration of exogenous Pcsk9 with SRT3025 blunted these effects. Sirt1 activation with SRT3025 in Ldlr–/– mice did not affect either plasma cholesterol levels or atherosclerosis. The authors thus identified reduction in Pcsk9 secretion as a novel effect of Sirt1 activity and the Ldlr was identified as a prerequisite for Sirt1-mediated atheroprotection in mice. Pharmacological activation of Sirt1 may provide a novel strategy to reduce atherosclerosis and its clinical sequelae such as myocardial infarction and stroke. The current issue is complemtented by a review on ‘Carotid artery stenting carotid endarterectomy randomized controlled trials neuro-protection systems carotid stents’ by Alberto Cremonesi et al. from the GVM Hospitals of Care and Research in Cotignola, Italy.12 In patients with carotid disease, the purpose of carotid artery revascularization is stroke prevention. For >50 years, carotid endarterectomy (CEA) has been considered the standard treatment for severe asymptomatic and symptomatic carotid stenoses. Carotid artery stenting (CAS) has emerged in the last 15 years as a minimally invasive alternative to surgery. However, the value of the endovascular approach in the management of carotid disease patients remains highly controversial. The aims of this review are to add information on the current role of CAS, to describe the major technological advancements in the field, and to speculate on the future of this therapy. We hope you enjoy this first issue of the new year.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,011 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,004 |
| Communication savante | 0,008 | 0,007 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,007 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,068 | 0,031 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».