For a long time, high-density lipoprotein cholesterol (HDL-C) has been regarded as a cardiovascular disease (CVD) protective factor. Recently, several epidemiological studies, while confirming low plasma levels of HDL-C as an established predictive biomarker for atherosclerotic CVD, indicated that not only people at the lowest levels but also those with high HDL-C levels are at increased risk of cardiovascular (CV) mortality. This “U-shaped” association has further fueled the discussion on the pathophysiological role of HDL in CVD. In fact, genetic studies, Mendelian randomization approaches, and clinical trials have challenged the notion of HDL-C levels being causally linked to CVD protection, independent of the cholesterol content in low-density lipoproteins (LDL-C). These findings have prompted a reconsideration of the biological functions of HDL that can be summarized with the word “HDL functionality”, a term that embraces the many reported biological activities beyond the so-called reverse cholesterol transport, to explain this lack of correlation between HDL levels and CVD. All these aspects are summarized and critically discussed in this review, in an attempt to provide a background scenario for the “HDL story”, a lipoprotein still in search of a role.

In the era of personalized medicine, it is of utmost importance to be able to identify subjects at the highest cardiovascular (CV) risk. To date, single biomarkers have failed to markedly improve the estimation of CV risk. Using novel technology, simultaneous assessment of large numbers of biomarkers may hold promise to improve prediction. In the present study, we compared a protein-based risk model with a model using traditional risk factors in predicting CV events in the primary prevention setting of the European Prospective Investigation (EPIC)-Norfolk study, followed by validation in the Progressione della Lesione Intimale Carotidea (PLIC) cohort. Using the proximity extension assay, 368 proteins were measured in a nested case–control sample of 822 individuals from the EPIC-Norfolk prospective cohort study and 702 individuals from the PLIC cohort. Using tree-based ensemble and boosting methods, we constructed a protein-based prediction model, an optimized clinical risk model, and a model combining both. In the derivation cohort (EPIC-Norfolk), we defined a panel of 50 proteins, which outperformed the clinical risk model in the prediction of myocardial infarction [area under the curve (AUC) 0.754 vs. 0.730; P < 0.001] during a median follow-up of 20 years. The clinically more relevant prediction of events occurring within 3 years showed an AUC of 0.732 using the clinical risk model and an AUC of 0.803 for the protein model (P < 0.001). The predictive value of the protein panel was confirmed to be superior to the clinical risk model in the validation cohort (AUC 0.705 vs. 0.609; P < 0.001). In a primary prevention setting, a proteome-based model outperforms a model comprising clinical risk factors in predicting the risk of CV events. Validation in a large prospective primary prevention cohort is required to address the value for future clinical implementation in CV prevention.

PCSK9 is secreted into the circulation, mainly by the liver, and interacts with low-density lipoprotein receptor (LDLR) homologous and non-homologous receptors, including CD36, thus favouring their intracellular degradation. As PCSK9 deficiency increases the expression of lipids and lipoprotein receptors, thus contributing to cellular lipid accumulation, we investigated whether this could affect heart metabolism and function. Wild-type (WT), Pcsk9 KO, Liver conditional Pcsk9 KO and Pcsk9/Ldlr double KO male mice were fed for 20 weeks with a standard fat diet and then exercise resistance, muscle strength, and heart characteristics were evaluated. Pcsk9 KO presented reduced running resistance coupled to echocardiographic abnormalities suggestive of heart failure with preserved ejection fraction (HFpEF). Heart mitochondrial activity, following maximal coupled and uncoupled respiration, was reduced in Pcsk9 KO mice compared to WT mice and was coupled to major changes in cardiac metabolism together with increased expression of LDLR and CD36 and with lipid accumulation. A similar phenotype was observed in Pcsk9/Ldlr DKO, thus excluding a contribution for LDLR to cardiac impairment observed in Pcsk9 KO mice. Heart function profiling of the liver selective Pcsk9 KO model further excluded the involvement of circulating PCSK9 in the development of HFpEF, pointing to a possible role locally produced PCSK9. Concordantly, carriers of the R46L loss-of-function variant for PCSK9 presented increased left ventricular mass but similar ejection fraction compared to matched control subjects. PCSK9 deficiency impacts cardiac lipid metabolism in an LDLR independent manner and contributes to the development of HFpEF. Impact of Pcsk9 deficiency on cardiac function and mitochondrial metabolism. Pcsk9 deficiency is associated with increased heart left ventricular thickness and reduced running performance independently of skeletal muscle alterations. Electron microscopy analysis showed increased cardiac accumulation of lipid droplets associated with a reduced density of mitochondrial cristae; this proffunctionally translated into impaired oxidative phosphorylation and mitochondrial metabolism in PCSK9 KO hearts.

Aims: Here, we aimed to determine the therapeutic effect of longevity-associated variant (LAV)-BPIFB4 gene therapy on atherosclerosis. Methods and results: ApoE knockout mice (ApoE−/−) fed a high-fat diet were randomly allocated to receive LAV-BPIFB4, wild-type (WT)-BPIFB4, or empty vector via adeno-associated viral vector injection. The primary endpoints of the study were to assess (i) vascular reactivity and (ii) atherosclerotic disease severity, by Echo-Doppler imaging, histology and ultrastructural analysis. Moreover, we assessed the capacity of the LAV-BPIFB4 protein to shift monocyte-derived macrophages of atherosclerotic mice and patients towards an anti-inflammatory phenotype. LAV-BPIFB4 gene therapy rescued endothelial function of mesenteric and femoral arteries from ApoE−/− mice; this effect was blunted by AMD3100, a CXC chemokine receptor type 4 (CXCR4) inhibitor. LAV-BPIFB4-treated mice showed a CXCR4-mediated shift in the balance between Ly6Chigh/Ly6Clow monocytes and M2/M1 macrophages, along with decreased T cell proliferation and elevated circulating levels of interleukins IL-23 and IL-27. In vitro conditioning with LAV-BPIFB4 protein of macrophages from atherosclerotic patients resulted in a CXCR4-dependent M2 polarization phenotype. Furthermore, LAV-BPIFB4 treatment of arteries explanted from atherosclerotic patients increased the release of atheroprotective IL-33, while inhibiting the release of pro-inflammatory IL-1β, inducing endothelial nitric oxide synthase phosphorylation and restoring endothelial function. Finally, significantly lower plasma BPIFB4 was detected in patients with pathological carotid stenosis (>25%) and intima media thickness >2 mm. Conclusion: Transfer of the LAV of BPIFB4 reduces the atherogenic process and skews macrophages towards an M2-resolving phenotype through modulation of CXCR4, thus opening up novel therapeutic possibilities in cardiovascular disease.

The Mediterranean diet has emerged as a comprehensive lifestyle, including specific foods and meal composition and a set of behavioural and social features. Adherence to the Mediterranean diet has been shown to promote health and reduce the prevalence of chronic diseases. The actual implementation of the Mediterranean diet is affected by several sociocultural factors as well as geographical components. Indeed, the geographical location, such as a specific country or different areas in a country and specific latitude and climate, appears to be an important factor that may strongly affect the implementation of the Mediterranean diet or some of its principles as well as the adherence to it. Another dynamic component affecting personal nutritional choices, also regarding adherence to the Mediterranean diet and its principles, is the individual life-long trajectory of food preference and nutrition habits and awareness. In this review, we discuss the current evidence on the impact of geographical location on adherence to the Mediterranean diet.

Genetics and environmental and lifestyle factors deeply affect cardiovascular diseases, with atherosclerosis as the etiopathological factor (ACVD) and their early recognition can significantly contribute to an efficient prevention and treatment of the disease. Due to the vast number of these factors, only the novel “omic” approaches are surmised. In addition to genomics, which extended the effective therapeutic potential for complex and rarer diseases, the use of “omics” presents a step-forward that can be harnessed for more accurate ACVD prediction and risk assessment in larger populations. The analysis of these data by artificial intelligence (AI)/machine learning (ML) strategies makes is possible to decipher the large amount of data that derives from such techniques, in order to provide an unbiased assessment of pathophysiological correlations and to develop a better understanding of the molecular background of ACVD. The predictive models implementing data from these “omics”, are based on consolidated AI best practices for classical ML and deep learning paradigms that employ methods (e.g., Integrative Network Fusion method, using an AI/ML supervised strategy and cross-validation) to validate the reproducibility of the results. Here, we highlight the proposed integrated approach for the prediction and diagnosis of ACVD with the presentation of the key elements of a joint scientific project of the University of Milan and the Almazov National Medical Research Centre.