Current Atherosclerosis Reports最新文献

Purpose of review: To discuss and review the technical considerations, fundamentals, and guideline-based indications for coronary artery calcium scoring, and the use of other non-invasive imaging modalities, such as extra-coronary calcification in cardiovascular risk prediction.

Recent findings: The most robust evidence for the use of CAC scoring is in select individuals, 40-75 years of age, at borderline to intermediate 10-year ASCVD risk. Recent US recommendations support the use of CAC scoring in varying clinical scenarios. First, in adults with very high CAC scores (CAC ≥ 1000), the use of high-intensity statin therapy and, if necessary, guideline-based add-on LDL-C lowering therapies (ezetimibe, PCSK9-inhibitors) to achieve a ≥ 50% reduction in LDL-C and optimally an LDL-C < 70 mg/dL is recommended. In patients with a CAC score ≥ 100 at low risk of bleeding, the benefits of aspirin use may outweigh the risk of bleeding. Other applications of CAC scoring include risk estimation on non-contrast CT scans of the chest, risk prediction in younger patients (< 40 years of age), its value as a gatekeeper for the decision to perform nuclear stress testing, and to aid in risk stratification in patients presenting with low-risk chest pain. There is a correlation between extra-coronary calcification (e.g., breast arterial calcification, aortic calcification, and aortic valve calcification) and incident ASCVD events. However, its role in informing lipid management remains unclear. Identification of coronary calcium in selected patients is the single best non-invasive imaging modality to identify future ASCVD risk and inform lipid-lowering therapy decision-making.

Purpose of review: The UK National Health Service (NHS) has recently announced a Newborn Genomes Programme (NGP) to identify infants with treatable inherited disorders using whole genome sequencing (WGS). Here, we address, for familial hypercholesterolaemia (FH), the four principles that must be met for the inclusion of a disorder in the NGP.

Recent findings: Principle A: There is strong evidence that the genetic variants causing FH can be reliably detected. Principle B: A high proportion of individuals who carry an FH-causing variant are likely to develop early heart disease if left undiagnosed and not offered appropriate treatment. Principle C: Early intervention has been shown to lead to substantially improved outcomes in children with FH. Principle D: The recommended interventions are equitably accessible for all. FH meets all the Wilson and Jungner criteria for inclusion in a screening programme, and it also meets all four principles and therefore should be included in the Newborn Genomes Programme.

Purpose of review: To summarize selected late-breaking science on cardiovascular (CV) disease prevention presented at the 2023 European Society of Cardiology (ESC) congress.

Recent findings: The NATURE-PARADOX was a naturally randomized trial that used genetic data from the UK Biobank registry to create "cumulative exposure to low-density lipoprotein-cholesterol (LDL-C)" biomarker and evaluate its association with major CV events regardless of plasma LDL-C levels or age. Safety and efficacy data of inclisiran, a PCSK9-interfering mRNA (PCSK9i) administered subcutaneously twice annually, were presented. Data on two new PCSK9is were presented, recaticimab, an oral drug, and lerodalcibep, a subcutaneous drug with a slightly different architecture than currently available PSCK9is. A phase 1 trial on muvalaplin, an oral lipoprotein (a) inhibitor, was presented. An atherosclerotic CV disease (ASCVD) risk prediction algorithm for the Asian population using SCORE2 data was presented. Long-term follow-up of patients enrolled in the CLEAR outcomes trial showed sustained and more significant ASCVD risk reduction with bempedoic acid in high-risk patients. The late-breaking clinical science at the 2023 congress of the ESC extends the known safety and efficacy data of a PCSK9i with the introduction of new drugs in this class. Using cumulative exposure to LDL-C rather than a single value will help clinicians tailor the LDL-C reduction strategy to individual risk and is an important step towards personalized medicine.

Purpose of review: Coronary artery disease is a complex disorder and the leading cause of mortality worldwide. As technologies for the generation of high-throughput multiomics data have advanced, gene regulatory network modeling has become an increasingly powerful tool in understanding coronary artery disease. This review summarizes recent and novel gene regulatory network tools for bulk tissue and single cell data, existing databases for network construction, and applications of gene regulatory networks in coronary artery disease.

Recent findings: New gene regulatory network tools can integrate multiomics data to elucidate complex disease mechanisms at unprecedented cellular and spatial resolutions. At the same time, updates to coronary artery disease expression data in existing databases have enabled researchers to build gene regulatory networks to study novel disease mechanisms. Gene regulatory networks have proven extremely useful in understanding CAD heritability beyond what is explained by GWAS loci and in identifying mechanisms and key driver genes underlying disease onset and progression. Gene regulatory networks can holistically and comprehensively address the complex nature of coronary artery disease. In this review, we discuss key algorithmic approaches to construct gene regulatory networks and highlight state-of-the-art methods that model specific modes of gene regulation. We also explore recent applications of these tools in coronary artery disease patient data repositories to understand disease heritability and shared and distinct disease mechanisms and key driver genes across tissues, between sexes, and between species.

Purpose of review: In this review, we sought to provide an overview of ML and focus on the contemporary applications of ML in cardiovascular risk prediction and precision preventive approaches. We end the review by highlighting the limitations of ML while projecting on the potential of ML in assimilating these multifaceted aspects of CAD in order to improve patient-level outcomes and further population health.

Recent findings: Coronary artery disease (CAD) is estimated to affect 20.5 million adults across the USA, while also impacting a significant burden at the socio-economic level. While the knowledge of the mechanistic pathways that govern the onset and progression of clinical CAD has improved over the past decade, contemporary patient-level risk models lag in accuracy and utility. Recently, there has been renewed interest in combining advanced analytic techniques that utilize artificial intelligence (AI) with a big data approach in order to improve risk prediction within the realm of CAD. By virtue of being able to combine diverse amounts of multidimensional horizontal data, machine learning has been employed to build models for improved risk prediction and personalized patient care approaches. The use of ML-based algorithms has been used to leverage individualized patient-specific data and the associated metabolic/genomic profile to improve CAD risk assessment. While the tool can be visualized to shift the paradigm toward a patient-specific care, it is crucial to acknowledge and address several challenges inherent to ML and its integration into healthcare before it can be significantly incorporated in the daily clinical practice.

Purpose of review: The purpose of this review is to critically discuss whether more aggressive lipid-lowering strategies are needed in patients with acute coronary syndromes (ACS).

Recent findings: Currently, available data on early (in-hospital/discharge) administration of potent lipid-lowering drugs, such as proprotein convertase subtilisin/kexin 9 (PCSK9) inhibitors in patients during the vulnerable post-ACS phase, have clearly demonstrated clinical efficacy of the "strike early and strike strong" approach not only for rapid reduction of low-density lipoprotein cholesterol (LDL-C) to unprecedentedly low levels, but also for associated favorable composition of coronary plaque. Intensive lipid-lowering therapy with rapid achievement of the LDL-C treatment goal in ACS patients seems reasonable. However, whether such profound LDL-C reduction would result in additional benefit on the reduction of future CV events still has to be established. Thus, data addressing CV outcomes in such vulnerable patients at extreme CV risk are urgently needed.

Purpose of review: Hypertriglyceridaemia (HTG) is a common condition characterised by elevated levels of plasma triglycerides (TG), which are transported in the blood mainly by TG-rich lipoproteins (TRL). Elevated TG levels (150-400 mg/dL) are associated with increased cardiovascular risk. Severe HTG (>880 mg/dL) is associated with a risk of acute pancreatitis only. Randomised clinical trials investigating the clinical benefit of TG-lowering drugs in patients with elevated TG levels have provided conflicting results.

Recent findings: Elevated TG levels are only one marker of altered lipid/lipoprotein metabolism and indeed reflect altered concentrations of one or more classes or subfractions of TRL, which in turn may have a different association with CV risk. Fibrates, the drugs most commonly used to treat HTG, provide cardiovascular benefits to only a specific subgroup of patients. The lack of clinical benefit from pemafibrate has emphasised the concept that lowering TG levels is not sufficient to reduce the CV risk unless it is accompanied by a reduction in the number of circulating atherogenic lipoproteins, which can be assessed by determining apolipoprotein B levels. Treatment with omega-3 fatty acids was also ineffective in reducing CV risk, with the exception of icosapent ethyl, which, however, appears to have beneficial effects beyond lipids. New drugs are currently being developed that aim to lower TG levels by targeting apolipoprotein C-III or angiopoietin-like-3, both of which are involved in the metabolism of TGs. TG reduction can be achieved by various drugs, but most of them are ineffective in reducing CV risk. The results of outcome studies on new TG-lowering drugs will clarify whether lowering apoB levels is critical to achieve clinical benefit.

Purpose of review: An evidence for lipid lowering therapy in heart failure is briefly summarized in this review.

Recent findings: Heart failure therapy is based on recent guidelines for diagnosis and treatment of acute and chronic heart failure. The question of the importance of hypolipidemic treatment in heart failure remains insufficiently answered. We still rely only on results of two randomized controlled trials that did not show significant benefit of statins on mortality in these patients. In contrast, some meta-analysis, prospective or retrospective cohorts, found some positive effects of this therapy. Recently, the role of inflammation and the possibility of its influence by hypolipidemics have been discussed. PCSK9 inhibitors, new lipid lowering drugs, are very effective in LDL-cholesterol lowering and atherosclerotic cardiovascular diseases prevention. The role of PCSK9 inhibitors in heart failure treatment is investigated. Based on current knowledge, hypolipidemics are not generally recommended in heart failure therapy, unless there is another indication for their use.

Purpose of review: This article sumarizes pathopysiological consequencies between obesity and dyslipidemia and aims to bring some practical approach.

Recent findings: Dyslipidemia is often present in individuals with obesity and simultaneusly, many obese individuals have lipid metabolism disorders. Especially the abdominal obesity increases the cardiometabolic risk because of the presence of atherogenic dyslipidemia while the total low density lipoprotein cholesterol (LDL-C) may be normal. LDL-C is the primary goal in dyslipidemia treatment. Apoliprotein B (Apo B) and non - high density lipoprotein cholesterol (non-HDL-C) should be estimated to precise the cardiovascular risk and represents the secondary goal in treatment. Weight loss either with diet or antiobestic medication induces the decrease in triglycerides (TG) and LDL-C and the increase in HDL-C. Composition of nutrients, esp. fatty acids, influences lipid levels. Bariatric surgery is efficient in weight loss and has a significant effect on serum lipids. Dyslipidemia and obesity present common diseases that must be managed to decrease the cardiovascular risk and the risk of obesity-related complications.

Purpose of review: Chronic kidney disease (CKD) is increasingly prevalent worldwide and is associated with increased cardiovascular risk. New therapeutic options to slow CKD progression and reduce cardiovascular morbidity and mortality have recently emerged. This review highlights recent evidence and gaps in knowledge in emerging CKD preventive strategies.

Recent findings: EMPA-Kidney trial found that empagliflozin, a sodium-glucose co-transporter 2 inhibitor (SGLT2i) led to 28% lower risk of progression of kidney disease or death from cardiovascular causes, compared to placebo. This reinforced the previous findings from DAPA-CKD and CREDENCE trials and led to inclusion of SGLT2i as the cornerstone of CKD preventive therapy in both diabetic and non-diabetic CKD. Finerenone, a selective nonsteroidal mineralocorticoid receptor antagonist, slowed diabetic kidney disease progression by 23% compared to placebo in a pool analysis of FIDELIO-DKD and FIGARO-DKD trials. Non-pharmacological interventions, including low protein diet, and early CKD detection and risk stratification strategies based on novel biomarkers have also gained momentum. Ongoing efforts to explore the wealth of molecular mechanisms in CKD, added to integrative omics modeling are well posed to lead to novel therapeutic targets in kidney care. While breakthrough pharmacological interventions continue to improve outcomes in CKD, the heterogeneity of kidney diseases warrants additional investigation. Further research into specific kidney disease mechanisms will facilitate the identification of patient populations most likely to benefit from targeted interventions.