Long-Term Follow-Up of Patients With Elevated Aldosterone-to-Renin Ratio but Negative Confirmatory Test: The Progression of Primary Aldosteronism Phenotypes.

BACKGROUND: About 10% of patients with arterial hypertension have a positive screening test for primary aldosteronism (PA) and 50% to 70% of them have a negative confirmatory test: the appropriate follow-up of these patients is currently unknown. We investigated the incidence of PA in patients with previous negative confirmatory testing, after at least a 2-year follow-up. METHODS: One hundred eighty-four patients with a previously elevated aldosterone-to-renin ratio followed by a negative confirmatory test were recruited in 2 hypertension centers (Torino and Munich). We repeated the screening test for PA and, if positive, the confirmatory test (seated saline infusion test or captopril challenge test). Primary end point of the study was the incidence of newly diagnosed overt PA, as defined by a positive confirmatory test. RESULTS: After a mean follow-up of 5 years, 20% of patients developed overt PA. When subtype diagnosis was offered systematically, one-third of patients displayed unilateral PA. Patients who developed PA showed worsening of blood pressure control and a higher rate of cardiac organ damage, despite similar implementation of antihypertensive therapy, compared with patients without PA. A mild progression of autonomous aldosterone secretion was evident even in patients without confirmed PA but with relatively stable control of blood pressure levels over time. CONCLUSIONS: About one-fifth of patients with a negative confirmatory test develop overt PA over time. A clinical follow-up of patients with a negative confirmatory test is advisable, along with the repetition of PA investigation, primarily in patients with worsening of blood pressure control.

Safety and efficacy of bempedoic acid: a systematic review and meta-analysis of randomised controlled trials.

BACKGROUND AND AIMS: Bempedoic Acid (BA) is a novel Lipid-Lowering Therapy (LLT). We performed a systematic review and meta-analysis to assess the efficacy and safety of BA in patients with hypercholesterolemia. METHODS: PubMed, Scopus, and Cochrane library databases were searched for randomised controlled trials evaluating the efficacy and/or safety of BA compared with placebo. Trials investigating dosages other than 180 mg/die were excluded. Major adverse cardiovascular events (MACE) were the primary efficacy endpoint. LDL-cholesterol reduction was the primary laboratory endpoint. Pre-specified safety endpoints included muscle-related adverse events, new-onset diabetes, and gout. The protocol was registered on PROSPERO (temporary ID:399,867). RESULTS: Study search identified 275 deduplicated results. 11 studies, encompassing 18,315 patients (9854 on BA vs 8461 on placebo/no treatment) were included. BA was associated with a reduced risk of MACE (OR 0.86, 95% CI 0.79-0.95), myocardial infarction (OR 0.76, 95% CI 0.64-0.88) and unstable angina (OR 0.69, 95% CI 0.54-0.88) compared to control, over a median follow up of 87 (15-162) weeks. BA was associated with a reduction of LDL-Cholesterol (mean difference [MD]-22.42,95% CI - 24.02% to - 20.82%), total cholesterol (- 16.50%,95% - 19.21% to - 13.79%), Apo-B lipoprotein (- 19.55%, - 22.68% to - 16.42%) and high-sensitivity CRP (- 27.83%, - 31.71% to - 23.96%) at 12 weeks. BA was associated with a higher risk of gout (OR 1.55, 95% CI 1.27-1.90) as compared with placebo. Efficacy on laboratory endpoints was confirmed, with a variable extent, across patients on statin or ezetimibe background therapy. CONCLUSIONS: The improved cholesterol control achieved with BA translates into a reduced risk of MACE, including myocardial infarction and coronary revascularisation. The drug has a satisfactory safety profile except for an increased risk of gout.

Multiomics of Tissue Extracellular Vesicles Identifies Unique Modulators of Atherosclerosis and Calcific Aortic Valve Stenosis.

BACKGROUND: Fewer than 50% of patients who develop aortic valve calcification have concomitant atherosclerosis, implying differential pathogenesis. Although circulating extracellular vesicles (EVs) act as biomarkers of cardiovascular diseases, tissue-entrapped EVs are associated with early mineralization, but their cargoes, functions, and contributions to disease remain unknown. METHODS: Disease stage-specific proteomics was performed on human carotid endarterectomy specimens (n=16) and stenotic aortic valves (n=18). Tissue EVs were isolated from human carotid arteries (normal, n=6; diseased, n=4) and aortic valves (normal, n=6; diseased, n=4) by enzymatic digestion, (ultra)centrifugation, and a 15-fraction density gradient validated by proteomics, CD63-immunogold electron microscopy, and nanoparticle tracking analysis. Vesiculomics, comprising vesicular proteomics and small RNA-sequencing, was conducted on tissue EVs. TargetScan identified microRNA targets. Pathway network analyses prioritized genes for validation in primary human carotid artery smooth muscle cells and aortic valvular interstitial cells. RESULTS: Disease progression drove significant convergence (P<0.0001) of carotid artery plaque and calcified aortic valve proteomes (2318 proteins). Each tissue also retained a unique subset of differentially enriched proteins (381 in plaques; 226 in valves; q<0.05). Vesicular gene ontology terms increased 2.9-fold (P<0.0001) among proteins modulated by disease in both tissues. Proteomics identified 22 EV markers in tissue digest fractions. Networks of proteins and microRNA targets changed by disease progression in both artery and valve EVs revealed shared involvement in intracellular signaling and cell cycle regulation. Vesiculomics identified 773 proteins and 80 microRNAs differentially enriched by disease exclusively in artery or valve EVs (q<0.05); multiomics integration found tissue-specific EV cargoes associated with procalcific Notch and Wnt signaling in carotid arteries and aortic valves, respectively. Knockdown of tissue-specific EV-derived molecules FGFR2, PPP2CA, and ADAM17 in human carotid artery smooth muscle cells and WNT5A, APP, and APC in human aortic valvular interstitial cells significantly modulated calcification. CONCLUSIONS: The first comparative proteomics study of human carotid artery plaques and calcified aortic valves identifies unique drivers of atherosclerosis versus aortic valve stenosis and implicates EVs in advanced cardiovascular calcification. We delineate a vesiculomics strategy to isolate, purify, and study protein and RNA cargoes from EVs entrapped in fibrocalcific tissues. Integration of vesicular proteomics and transcriptomics by network approaches revealed novel roles for tissue EVs in modulating cardiovascular disease.

Prevalence of Cortisol Cosecretion in Patients With Primary Aldosteronism: Role of Metanephrine in Adrenal Vein Sampling.

CONTEXT: Adrenal venous sampling (AVS) is the gold standard procedure for subtype diagnosis in patients with primary aldosteronism (PA). Cortisol is usually adopted for the normalization of aldosterone levels in peripheral and adrenal samples. However, asymmetrical cortisol secretion can potentially affect the lateralization index, leading to subtype misdiagnosis. OBJECTIVE: We aimed to assess the prevalence of asymmetrical cortisol secretion in patients undergoing AVS and whether variations in adrenal vein cortisol might influence AVS interpretations. We then evaluated the use of metanephrines for the normalization of aldosterone levels for lateralization index. METHODS: We retrospectively included 101 patients with PA who underwent AVS: 49 patients underwent unstimulated AVS, while 52 patients underwent both unstimulated and cosyntropin-stimulated AVS. Eighty-eight patients had bilateral successful AVS according to metanephrine ratio. We assessed the prevalence of asymmetrical cortisol secretion through the cortisol to metanephrine (C/M) lateralization index (LI). We then evaluated whether the use of aldosterone to metanephrine (A/M) LI can improve the diagnostic accuracy of AVS compared with aldosterone to cortisol (A/C) LI. RESULTS: Asymmetrical cortisol secretion is present in 18% of patients with PA. Diagnosis with A/M LI and A/C LI is discordant in 14% of patients: 9% had a diagnosis of unilateral PA with A/M LI instead of bilateral PA with A/C LI and 5% had a diagnosis of bilateral PA with A/M LI instead of unilateral PA. CONCLUSION: The assessment of metanephrine levels in AVS is useful for the determination of selectivity and lateralization, allowing an accurate diagnosis, especially in patients with asymmetrical cortisol secretion.

Prevalence of Functioning Adrenal Incidentalomas: A Systematic Review and Meta-analysis.

CONTEXT: Adrenal hyperfunction is associated with an increased risk of cardiometabolic complications in subjects with adrenal incidentaloma (AI). Reliable prevalence estimates of functioning AIs are important to direct resources allocations. OBJECTIVE: To assess the prevalence of autonomous/possible autonomous cortisol secretion (ACS), primary aldosteronism (PA), pheochromocytoma (PHEO), and Cushing syndrome (CS) in patients with AI. METHODS: We performed a comprehensive search of multiple databases (PubMed, Ovid MEDLINE, Web of Science) for potentially relevant studies without language restriction, up to February 2022. Of the 1661 publications evaluated at title and abstract levels, 161 were examined as full text and 36 were included. Study level clinical data were extracted by 3 independent reviewers. RESULTS: The overall prevalence of functioning AIs was 27.5% (95% CI 23.0, 32.5). ACS/possible ACS, with a prevalence of 11.7% (95% CI 8.6, 15.7), was the most frequent hormonal alteration, while PA occurred in 4.4% of the patients (95% CI 3.1, 6.2). Subgroup analysis showed that PA was more prevalent in patients from Asia than in patients from Europe/America; in contrast, ACS/possible ACS had a lower prevalence in Asian countries. At meta-regression analysis, the prevalence of ACS/possible ACS was influenced by the proportion of female patients, while the prevalence of PA was positively associated with the proportion of patients with hypertension and the publication year. Finally, PHEO and CS prevalence were 3.8% (95% CI 2.8, 5.0) and 3.1% (95% CI 2.3, 4.3) respectively. CONCLUSION: This meta-analysis provides extensive data on the prevalence of functioning AIs and the factors affecting heterogeneity in prevalence estimates.

Primary aldosteronism in pregnancy.

Primary aldosteronism (PA) is the most common form of secondary hypertension. Although hypertensive disorders seem to affect around 5-10% of pregnancies worldwide, literature counts less than 80 cases of PA diagnosed during the peri-partum period. In this review we discuss about current knowledge on pathophysiology, natural history, diagnosis and treatment of PA in pregnancy. Because of the physiologic changes in the renin-angiotensin-aldosterone system (RAAS) and the contraindication to both confirmatory test and subtype differentiation, diagnosis of PA during pregnancy is challenging and relies mostly on detection of low/suppressed renin and high aldosterone levels. The course of pregnancy in patients with PA is highly variable, ranging from progesterone-induced amelioration of blood pressure (BP) control to severe and resistant hypertension with potential maternal and fetal complications. Mineralcorticoid receptor antagonists (MRA) are the recommended and most effective drugs for treatment of PA. As the anti-androgenic effect of spironolactone can potentially interfere with sexual development, their prescription is not recommended during pregnancy. On the other side, eplerenone, has proven to be safe and effective in 6 pregnant women and may be added to conventional first line drug regimen in presence of resistant hypertension or persistent hypokalemia. Ideally, patients with unilateral forms of PA should undergo adrenalectomy prior to conception, however, when PA is diagnosed during pregnancy and medical therapy fails to adequately control hypertension or its complications, adrenalectomy can be considered during the second trimester in case of unilateral adrenal mass at MRI-scan.

Identification of a serum and urine extracellular vesicle signature predicting renal outcome after kidney transplant.

BACKGROUND: A long-standing effort is dedicated towards the identification of biomarkers allowing the prediction of graft outcome after kidney transplant. Extracellular vesicles (EVs) circulating in body fluids represent an attractive candidate, as their cargo mirrors the originating cell and its pathophysiological status. The aim of the study was to investigate EV surface antigens as potential predictors of renal outcome after kidney transplant. METHODS: We characterized 37 surface antigens by flow cytometry, in serum and urine EVs from 58 patients who were evaluated before, and at 10-14 days, 3 months and 1 year after transplant, for a total of 426 analyzed samples. The outcome was defined according to estimated glomerular filtration rate (eGFR) at 1 year. RESULTS: Endothelial cells and platelets markers (CD31, CD41b, CD42a and CD62P) in serum EVs were higher at baseline in patients with persistent kidney dysfunction at 1 year, and progressively decreased after kidney transplant. Conversely, mesenchymal progenitor cell marker (CD1c, CD105, CD133, SSEEA-4) in urine EVs progressively increased after transplant in patients displaying renal recovery at follow-up. These markers correlated with eGFR, creatinine and proteinuria, associated with patient outcome at univariate analysis and were able to predict patient outcome at receiver operating characteristics curves analysis. A specific EV molecular signature obtained by supervised learning correctly classified patients according to 1-year renal outcome. CONCLUSIONS: An EV-based signature, reflecting the cardiovascular profile of the recipient, and the repairing/regenerative features of the graft, could be introduced as a non-invasive tool for a tailored management of follow-up of patients undergoing kidney transplant.

Accuracy of home blood pressure measurement: the ACCURAPRESS study - a proposal of Young Investigator Group of the Italian Hypertension Society (Società Italiana dell'Ipertensione Arteriosa).

PURPOSE: Home blood pressure monitoring (HBPM) might be considered a valid alternative to ambulatory blood pressure monitoring (ABPM) for both the diagnosis and management of hypertension. Correct information on how to perform HBPM are crucial for its reliability. The aim of the present survey was to assess if hypertensive patients followed current recommendation on how to correctly perform HBPM measurements. MATERIALS AND METHODS: The survey included 30 different items on how to perform the HBPM. It was developed by the 'Young Investigators' group of the Italian Society of Arterial Hypertension (SIIA) and it was administered during the office visit between May 2019 and December 2021. RESULTS: A total of 643 hypertensive patients participated in the study. Main results show that, despite the rate of informed patients was relatively high (71% of the whole population), unacceptable number of patients did not follow indications on how to perform a correct HBPM. Patients who were informed on how to measure home BP had a significantly higher rate of correct position during measurement (78 vs. 22%, p < 0.01), avoidance of talking and moving during measurement (68 vs. 32%, p < 0.0001), and correct number and time interval between two measurements (85 vs. 15%, p < 0.001). More accurate measurements of home BP were associated with less prevalence of carotid plaque. CONCLUSIONS: Correct performance for HBPM is low among patients treated in Italian hypertension centers. These findings shed light on the importance of correct HBPM measurements for the detection of accurate BP values for the proper management of hypertensive patients.

Whole blood methylome-derived features to discriminate endocrine hypertension.

BACKGROUND: Arterial hypertension represents a worldwide health burden and a major risk factor for cardiovascular morbidity and mortality. Hypertension can be primary (primary hypertension, PHT), or secondary to endocrine disorders (endocrine hypertension, EHT), such as Cushing's syndrome (CS), primary aldosteronism (PA), and pheochromocytoma/paraganglioma (PPGL). Diagnosis of EHT is currently based on hormone assays. Efficient detection remains challenging, but is crucial to properly orientate patients for diagnostic confirmation and specific treatment. More accurate biomarkers would help in the diagnostic pathway. We hypothesized that each type of endocrine hypertension could be associated with a specific blood DNA methylation signature, which could be used for disease discrimination. To identify such markers, we aimed at exploring the methylome profiles in a cohort of 255 patients with hypertension, either PHT (n = 42) or EHT (n = 213), and at identifying specific discriminating signatures using machine learning approaches. RESULTS: Unsupervised classification of samples showed discrimination of PHT from EHT. CS patients clustered separately from all other patients, whereas PA and PPGL showed an overall overlap. Global methylation was decreased in the CS group compared to PHT. Supervised comparison with PHT identified differentially methylated CpG sites for each type of endocrine hypertension, showing a diffuse genomic location. Among the most differentially methylated genes, FKBP5 was identified in the CS group. Using four different machine learning methods-Lasso (Least Absolute Shrinkage and Selection Operator), Logistic Regression, Random Forest, and Support Vector Machine-predictive models for each type of endocrine hypertension were built on training cohorts (80% of samples for each hypertension type) and estimated on validation cohorts (20% of samples for each hypertension type). Balanced accuracies ranged from 0.55 to 0.74 for predicting EHT, 0.85 to 0.95 for predicting CS, 0.66 to 0.88 for predicting PA, and 0.70 to 0.83 for predicting PPGL. CONCLUSIONS: The blood DNA methylome can discriminate endocrine hypertension, with methylation signatures for each type of endocrine disorder.

Cardiac Phenotypes in Secondary Hypertension: JACC State-of-the-Art Review.

Several forms of secondary hypertension carry a high risk of cardiac morbidity and mortality. Evaluation of cardiac phenotypes in secondary hypertension provides a unique opportunity to study underlying hormonal and biochemical mechanisms affecting the heart. We review the characteristics of cardiac dysfunction in different forms of secondary hypertension and clarify the mechanisms behind the higher prevalence of heart damage in these patients than in those with primary hypertension. Attention to the specific clinical/biochemical phenotypes of these conditions may assist clinicians to screen for and confirm secondary forms of hypertension. Thereby, early signs of heart damage can be recognized and monitored, allowing individualized treatment to delay or prevent evolution toward more advanced disease.

Machine learning for classification of hypertension subtypes using multi-omics: A multi-centre, retrospective, data-driven study.

BACKGROUND: Arterial hypertension is a major cardiovascular risk factor. Identification of secondary hypertension in its various forms is key to preventing and targeting treatment of cardiovascular complications. Simplified diagnostic tests are urgently required to distinguish primary and secondary hypertension to address the current underdiagnosis of the latter. METHODS: This study uses Machine Learning (ML) to classify subtypes of endocrine hypertension (EHT) in a large cohort of hypertensive patients using multidimensional omics analysis of plasma and urine samples. We measured 409 multi-omics (MOmics) features including plasma miRNAs (PmiRNA: 173), plasma catechol O-methylated metabolites (PMetas: 4), plasma steroids (PSteroids: 16), urinary steroid metabolites (USteroids: 27), and plasma small metabolites (PSmallMB: 189) in primary hypertension (PHT) patients, EHT patients with either primary aldosteronism (PA), pheochromocytoma/functional paraganglioma (PPGL) or Cushing syndrome (CS) and normotensive volunteers (NV). Biomarker discovery involved selection of disease combination, outlier handling, feature reduction, 8 ML classifiers, class balancing and consideration of different age- and sex-based scenarios. Classifications were evaluated using balanced accuracy, sensitivity, specificity, AUC, F1, and Kappa score. FINDINGS: Complete clinical and biological datasets were generated from 307 subjects (PA=113, PPGL=88, CS=41 and PHT=112). The random forest classifier provided ∼92% balanced accuracy (∼11% improvement on the best mono-omics classifier), with 96% specificity and 0.95 AUC to distinguish one of the four conditions in multi-class ALL-ALL comparisons (PPGL vs PA vs CS vs PHT) on an unseen test set, using 57 MOmics features. For discrimination of EHT (PA + PPGL + CS) vs PHT, the simple logistic classifier achieved 0.96 AUC with 90% sensitivity, and ∼86% specificity, using 37 MOmics features. One PmiRNA (hsa-miR-15a-5p) and two PSmallMB (C9 and PC ae C38:1) features were found to be most discriminating for all disease combinations. Overall, the MOmics-based classifiers were able to provide better classification performance in comparison to mono-omics classifiers. INTERPRETATION: We have developed a ML pipeline to distinguish different EHT subtypes from PHT using multi-omics data. This innovative approach to stratification is an advancement towards the development of a diagnostic tool for EHT patients, significantly increasing testing throughput and accelerating administration of appropriate treatment. FUNDING: European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No. 633983, Clinical Research Priority Program of the University of Zurich for the CRPP HYRENE (to Z.E. and F.B.), and Deutsche Forschungsgemeinschaft (CRC/Transregio 205/1).

Approach to the Patient on Antihypertensive Therapy: Screen for Primary Aldosteronism.

Primary aldosteronism (PA) is a condition that is still largely overlooked, resulting in a considerable burden of mortality and morbidity. This is despite decades of clinical and translational research on the deleterious effects of aldosterone on the cardiovascular system and the publication of several guidelines and consensuses on its diagnosis and treatment. One of the main reasons for the low rate of testing is the difficulty of screening patients on antihypertensive therapy that potentially interferes with aldosterone and renin levels and thus confound the interpretation of the aldosterone to renin ratio, the accepted and conventionally used screening test. To avoid interference, usually the therapies that affect the renin-angiotensin aldosterone system are withdrawn and substituted with noninterfering medications. However, in many cases the screening test can be confidently interpreted even when such therapies are not discontinued. In this review, we will evaluate the effects of antihypertensive therapies on the screening test for PA and suggest a practical approach for its interpretation.

Prediction of All-Cause Mortality Following Percutaneous Coronary Intervention in Bifurcation Lesions Using Machine Learning Algorithms.

Stratifying prognosis following coronary bifurcation percutaneous coronary intervention (PCI) is an unmet clinical need that may be fulfilled through the adoption of machine learning (ML) algorithms to refine outcome predictions. We sought to develop an ML-based risk stratification model built on clinical, anatomical, and procedural features to predict all-cause mortality following contemporary bifurcation PCI. Multiple ML models to predict all-cause mortality were tested on a cohort of 2393 patients (training, n = 1795; internal validation, n = 598) undergoing bifurcation PCI with contemporary stents from the real-world RAIN registry. Twenty-five commonly available patient-/lesion-related features were selected to train ML models. The best model was validated in an external cohort of 1701 patients undergoing bifurcation PCI from the DUTCH PEERS and BIO-RESORT trial cohorts. At ROC curves, the AUC for the prediction of 2-year mortality was 0.79 (0.74-0.83) in the overall population, 0.74 (0.62-0.85) at internal validation and 0.71 (0.62-0.79) at external validation. Performance at risk ranking analysis, k-center cross-validation, and continual learning confirmed the generalizability of the models, also available as an online interface. The RAIN-ML prediction model represents the first tool combining clinical, anatomical, and procedural features to predict all-cause mortality among patients undergoing contemporary bifurcation PCI with reliable performance.

Aldosterone as a Mediator of Cardiovascular Damage.

Besides the physiological regulation of water, sodium, and potassium homeostasis, aldosterone modulates several physiological and pathological processes in the cardiovascular system. At the vascular level, aldosterone excess stimulates endothelial dysfunction and infiltration of inflammatory cells, enhances the development of the atherosclerotic plaque, and favors plaque instability, arterial stiffness, and calcification. At the cardiac level, aldosterone increases cardiac inflammation, fibrosis, and myocardial hypertrophy. As a clinical consequence, high aldosterone levels are associated with enhanced risk of cardiovascular events and mortality, especially when aldosterone secretion is inappropriate for renin levels and sodium intake, as in primary aldosteronism. Several clinical trials showed that mineralocorticoid receptor antagonists reduce cardiovascular mortality in patients with heart failure and reduced ejection fraction, but inconclusive results were reported for other cardiovascular conditions, such as heart failure with preserved ejection fraction, myocardial infarction, and atrial fibrillation. In patients with primary aldosteronism, adrenalectomy or treatment with mineralocorticoid receptor antagonists significantly mitigate adverse aldosterone effects, reducing the risk of cardiovascular events, mortality, and incident atrial fibrillation. In this review, we will summarize the major preclinical and clinical studies investigating the cardiovascular damage mediated by aldosterone and the protective effect of mineralocorticoid receptor antagonists for the reduction of cardiovascular risk in patients with cardiovascular diseases and primary aldosteronism.

Risk stratification of patients with SARS-CoV-2 by tissue factor expression in circulating extracellular vesicles.

Inflammatory response following SARS-CoV-2 infection results in substantial increase of amounts of intravascular pro-coagulant extracellular vesicles (EVs) expressing tissue factor (CD142) on their surface. CD142-EV turned out to be useful as diagnostic biomarker in COVID-19 patients. Here we aimed at studying the prognostic capacity of CD142-EV in SARS-CoV-2 infection. Expression of CD142-EV was evaluated in 261 subjects admitted to hospital for pneumonia and with a positive molecular test for SARS-CoV-2. The study population consisted of a discovery cohort of selected patients (n = 60) and an independent validation cohort including unselected consecutive enrolled patients (n = 201). CD142-EV levels were correlated with post-hospitalization course of the disease and compared to the clinically available 4C Mortality Score as referral. CD142-EV showed a reliable performance to predict patient prognosis in the discovery cohort (AUC = 0.906) with an accuracy of 81.7%, that was confirmed in the validation cohort (AUC = 0.736). Kaplan-Meier curves highlighted a high discrimination power in unselected subjects with CD142-EV being able to stratify the majority of patients according to their prognosis. We obtained a comparable accuracy, being not inferior in terms of prediction of patients' prognosis and risk of mortality, with 4C Mortality Score. The expression of surface vesicular CD142 and its reliability as prognostic marker was technically validated using different immunocapture strategies and assays. The detection of CD142 on EV surface gains considerable interest as risk stratification tool to support clinical decision making in COVID-19.

Role of Extracellular Vesicles in the Pathogenesis of Vascular Damage.

Extracellular vesicles (EVs) are nanosized membrane-bound structures released by cells that are able to transfer nucleic acids, protein cargos, and metabolites to specific recipient cells, allowing cell-to-cell communications in an endocrine and paracrine manner. Endothelial, leukocyte, and platelet-derived EVs have emerged both as biomarkers and key effectors in the development and progression of different stages of vascular damage, from earliest alteration of endothelial function, to advanced atherosclerotic lesions and cardiovascular calcification. Under pathological conditions, circulating EVs promote endothelial dysfunction by impairing vasorelaxation and instigate vascular inflammation by increasing levels of adhesion molecules, reactive oxygen species, and proinflammatory cytokines. Platelets, endothelial cells, macrophages, and foam cells secrete EVs that regulate macrophage polarization and contribute to atherosclerotic plaque progression. Finally, under pathological stimuli, smooth muscle cells and macrophages secrete EVs that aggregate between collagen fibers and serve as nucleation sites for ectopic mineralization in the vessel wall, leading to formation of micro- and macrocalcification. In this review, we summarize the emerging evidence of the pathological role of EVs in vascular damage, highlighting the major findings from the most recent studies and discussing future perspectives in this research field.

Supervised and unsupervised learning to define the cardiovascular risk of patients according to an extracellular vesicle molecular signature.

Cardiovascular (CV) disease represents the most common cause of death in developed countries. Risk assessment is highly relevant to intervene at individual level and implement prevention strategies. Circulating extracellular vesicles (EVs) are involved in the development and progression of CV diseases and are considered promising biomarkers. We aimed at identifying an EV signature to improve the stratification of patients according to CV risk and likelihood to develop fatal CV events. EVs were characterized by nanoparticle tracking analysis and flow cytometry for a standardized panel of 37 surface antigens in a cross-sectional multicenter cohort (n = 486). CV profile was defined by presence of different indicators (age, sex, body mass index, hypertension, hyperlipidemia, diabetes, coronary artery disease, cardiac heart failure, chronic kidney disease, smoking habit, organ damage) and according to the 10-year risk of fatal CV events estimated using SCORE charts of European Society of Cardiology. By combining expression levels of EV antigens using unsupervised learning, patients were classified into 3 clusters: Cluster-I (n = 288), Cluster-II (n = 83), Cluster-III (n = 30). A separate analysis was conducted on patients displaying acute CV events (n = 82). Prevalence of hypertension, diabetes, chronic heart failure, and organ damage (defined as left ventricular hypertrophy and/or microalbuminuria) increased progressively from Cluster-I to Cluster-III. Several EV antigens, including markers for platelets (CD41b-CD42a-CD62P), leukocytes (CD1c-CD2-CD3-CD4-CD8-CD14-CD19-CD20-CD25-CD40-CD45-CD69-CD86), and endothelium (CD31-CD105) were independently associated with CV risk indicators and correlated to age, blood pressure, glucometabolic profile, renal function, and SCORE risk. EV profiling, obtained from minimally invasive blood sampling, allows accurate patient stratification according to CV risk profile.

Usefulness of Combined Renin-Angiotensin System Inhibitors and Diuretic Treatment In Patients Hospitalized with COVID-19.

Antecedent use of renin-angiotensin system inhibitors (RASi) prevents clinical deterioration and protects against cardiovascular/thrombotic complications of COVID-19, for indicated patients. Uncertainty exists regarding treatment continuation throughout infection and doing so with concomitant medications. Hence, the purpose of this study is to evaluate the differential effect of RASi continuation in patients hospitalized with COVID-19 according to diuretic use. We used the Coracle registry, which contains data of hospitalized patients with COVID-19 from 4 regions of Italy. We used Firth logistic regression for adult (>50 years) cases with admission on/after February 22, 2020, with a known discharge status as of April 1, 2020. There were 286 patients in this analysis; 100 patients (35.0%) continued RASi and 186 (65%) discontinued. There were 98 patients treated with a diuretic; 51 (52%) of those continued RASi. The in-hospital mortality rates in patients treated with a diuretic and continued versus discontinued RASi were 8% versus 26% (p = 0.0179). There were 188 patients not treated with a diuretic; 49 (26%) of those continued RASi. The in-hospital mortality rates in patients not treated with a diuretic and continued versus discontinued RASi were 16% versus 9% (p = 0.1827). After accounting for age, cardiovascular disease, and laboratory values, continuing RASi decreased the risk of mortality by approximately 77% (odds ratio 0.23, 95% confidence interval 0.06 to 0.95, p = 0.0419) for patients treated with diuretics, but did not alter the risk in patients treated with RASi alone. Continuing RASi in patients concomitantly treated with diuretics was associated with reduced in-hospital mortality.

Clinical Score and Machine Learning-Based Model to Predict Diagnosis of Primary Aldosteronism in Arterial Hypertension.

[Figure: see text].