Circulating ceramide levels and ratios in Emirati youth under 18 years: associations with cardiometabolic risk factors

BACKGROUND

Circulating ceramide (Cer) drives various pathological processes associated with cardiovascular diseases, liver illness, and diabetes mellitus. Although recognized as predictors of cardiometabolic diseases (CMD) in research and clinical settings, their potential for predicting CMD risk in individuals under 18 remains unexplored.

OBJECTIVES

This study was designed to utilize Liquid Chromatography-Mass Spectrometry (LC-MS/MS) methodology to determine the biological reference ranges for Cer in plasma samples of Emirati children and develop a risk assessment score (CERT-1) based on Cer concentrations.

METHODS

Using LC-MS/MS, we developed a method to measure five Cer species in plasma samples of 582 Emirati participants aged 5-17. We used the circulating concentrations of these Cer to determine their reference intervals in this population. We employed traditional statistical analyses to develop a risk score (CERT-1) and assess the association between Cer levels and conventional biomarkers of CMD.

RESULTS

We validated a high-throughput methodology using LC-MS/MS to quantify five Cer species in human plasma. Reference values for this population (n = 582) were quantified: CerC16:0 (0.12-0.29 µmol/L), CerC18:0 (0.019-0.067 µmol/L), CerC22:0 (0.102-0.525 µmol/L), CerC24:0 (0.65-1.54 µmol/L) and CerC24:1 (0.212-0.945 µmol/L). We devised a risk assessment score (CERT-1) based on plasma Cer content in the study participants, showing that 72.5% have low to moderate risk and 9.3% are at a higher risk of developing CMD. Our analyses also revealed a significant correlation (P < 0.05) between this score and the conventional risk factors linked to CMD, indicating its potential clinical implication.

CONCLUSION

This study presents a clinical-scaled LC-MS/MS methodology for assessing clinically relevant Cer, setting reference ranges, and developing a risk score (CERT-1) for young Emirati individuals. Our findings can enhance primary risk prediction and inform the management and follow-up of CMD from an early age.

Seeing Is Believing: Photon Counting Computed Tomography Clearly Images Directional Deep Brain Stimulation Lead Segments and Markers After Implantation

BACKGROUND AND OBJECTIVES

Directional deep brain stimulation (DBS) electrodes are increasingly used, but conventional computed tomography (CT) is unable to directly image segmented contacts owing to physics-based resolution constraints. Postoperative electrode segment orientation assessment is necessary because of the possibility of significant deviation during or immediately after insertion. Photon-counting detector (PCD) CT is a relatively novel technology that enables high resolution imaging while addressing several limitations intrinsic to CT. We show how PCD CT can enable clear in vivo imaging of DBS electrodes, including segmented contacts and markers for all major lead manufacturers.

MATERIALS AND METHODS

We describe postoperative imaging and reconstruction protocols we have developed to enable optimal lead visualization. PCD CT images were obtained of directional leads from the three major manufacturers and fused with preoperative 3T magnetic resonance imaging (MRI). Radiation dosimetry also was evaluated and compared with conventional imaging controls. Orientation estimates from directly imaged leads were compared with validated software-based reconstructions (derived from standard CT imaging artifact analysis) to quantify congruence in alignment and directional orientation.

RESULTS

High-fidelity images were obtained for 15 patients, clearly indicating the segmented contacts and directional markers both on CT alone and when fused to MRI. Our routine imaging protocol is described. Ionizing radiation doses were significantly lower than with conventional CT. For most leads, the directly imaged lead orientations and depths corresponded closely to those predicted by CT artifact-based reconstructions. However, unlike direct imaging, the software reconstructions were susceptible to 180° error in orientation assessment.

CONCLUSIONS

High-resolution photon-counting CT can very clearly image segmented DBS electrode contacts and directional markers and unambiguously determine lead orientation, with lower radiation than in conventional imaging. This obviates the need for further imaging and may facilitate anatomically tailored directional programming.

Adipose Tissue in Cardiovascular Disease: From Basic Science to Clinical Translation

The perception of adipose tissue as a metabolically quiescent tissue, primarily responsible for lipid storage and energy balance (with some endocrine, thermogenic, and insulation functions), has changed. It is now accepted that adipose tissue is a crucial regulator of metabolic health, maintaining bidirectional communication with other organs including the cardiovascular system. Additionally, adipose tissue depots are functionally and morphologically heterogeneous, acting not only as sources of bioactive molecules that regulate the physiological functioning of the vasculature and myocardium but also as biosensors of the paracrine and endocrine signals arising from these tissues. In this way, adipose tissue undergoes phenotypic switching in response to vascular and/or myocardial signals (proinflammatory, profibrotic, prolipolytic), a process that novel imaging technologies are able to visualize and quantify with implications for clinical prognosis. Furthermore, a range of therapeutic modalities have emerged targeting adipose tissue metabolism and altering its secretome, potentially benefiting those at risk of cardiovascular disease.

High-sensitivity Troponin (hs-Tn) for Cardiovascular Risk Prognostication: A Systematic Review and Meta-analysis

BACKGROUND

Chronic low-grade inflammation is involved in coronary atherosclerosis progression whereas recent research efforts suggest that preventative methods should be tailored to the "residual inflammatory risk". As such, modalities for the early identification of the risk have to be investigated.

METHODS

We performed a systematic review and meta-analysis according to the PRISMA guidelines. Any study that presented the prognostic value of high sensitivity troponin (hs-cTn) of vascular inflammation in stable patients without known cardiac heart disease was considered to be potentially eligible. The Medline (PubMed) database was searched up to April 22, 2021. The main endpoint was the difference in c-index (Δ[c-index]) with the use of hs-cTn for major adverse cardiovascular events (MACEs), cardiovascular and all-cause mortality. We calculated I2 to test heterogeneity.

RESULTS

In total, 44 studies and 112,288 stable patients without known coronary heart disease were included in this meta-analysis. The mean follow-up duration of the whole cohort was 6.8 ± 1.1 years. 77,004 (68.5%) of the patients presented at low cardiovascular risk while 35,284 (31.5%) in high. The overall pooled estimate of Δ[c-index] for MACE was 1.4% (95%CI: 0.7-2.1, I2=0%) and for cardiovascular death 1.3% (95%CI: 0.3-2.3, I2=0%). Finally, the overall pooled estimate of Δ[c-index] for all-cause mortality was 3% (95%CI: 1.9-3.9, I2=86%), while high heterogeneity was observed between the studies.

CONCLUSION

The predictive usefulness of changes in hs-cTn measures in stable individuals with either high or low cardiovascular risk, demonstrates that assessing vascular inflammation in addition to clinical risk factors enhances risk prediction for cardiovascular events and allcause mortality. Further prospective studies are necessary to confirm these findings and assist clinical decision-making regarding the most optimal prevention strategy.

'Super Rehab': can we achieve coronary artery disease regression? A feasibility study protocol

INTRODUCTION

Patients diagnosed with coronary artery disease (CAD) are currently treated with medications and lifestyle advice to reduce the likelihood of disease progression and risk of future major adverse cardiovascular events (MACE). Where obstructive disease is diagnosed, revascularisation may be considered to treat refractory symptoms. However, many patients with coexistent cardiovascular risk factors, particularly those with metabolic syndrome (MetS), remain at heightened risk of future MACE despite current management.Cardiac rehabilitation is offered to patients post-revascularisation, however, there is no definitive evidence demonstrating its benefit in a primary prevention setting. We propose that an intensive lifestyle intervention (Super Rehab, SR) incorporating high-intensity exercise, diet and behavioural change techniques may improve symptoms, outcomes, and enable CAD regression.This study aims to examine the feasibility of delivering a multicentre randomised controlled trial (RCT) testing SR for patients with CAD, in a primary prevention setting.

METHODS AND ANALYSIS

This is a multicentre randomised controlled feasibility study of SR versus usual care in patients with CAD. The study aims to recruit 50 participants aged 18-75 across two centres. Feasibility will be assessed against rates of recruitment, retention and, in the intervention arm, attendance and adherence to SR. Qualitative interviews will explore trial experiences of study participants and practitioners. Variance of change in CAD across both arms of the study (assessed with serial CT coronary angiography) will inform the design and power of a future, multi-centre RCT.

ETHICS AND DISSEMINATION

Ethics approval was granted by South West-Frenchay Research Ethics Committee (reference: 21/SW/0153, 18 January 2022). Study findings will be disseminated via presentations to relevant stakeholders, national and international conferences and open-access peer-reviewed research publications.

TRIAL REGISTRATION NUMBER

ISRCTN14603929.

Radiomics of pericardial fat: a new frontier in heart failure discrimination and prediction

OBJECTIVES

To use pericardial adipose tissue (PAT) radiomics phenotyping to differentiate existing and predict future heart failure (HF) cases in the UK Biobank.

METHODS

PAT segmentations were derived from cardiovascular magnetic resonance (CMR) studies using an automated quality-controlled model to define the region-of-interest for radiomics analysis. Prevalent (present at time of imaging) and incident (first occurrence after imaging) HF were ascertained using health record linkage. We created balanced cohorts of non-HF individuals for comparison. PyRadiomics was utilised to extract 104 radiomics features, of which 28 were chosen after excluding highly correlated ones (0.8). These features, plus sex and age, served as predictors in binary classification models trained separately to detect (1) prevalent and (2) incident HF. We tested seven modeling methods using tenfold nested cross-validation and examined feature importance with explainability methods.

RESULTS

We studied 1204 participants in total, 297 participants with prevalent (60 ± 7 years, 21% female) and 305 with incident (61 ± 6 years, 32% female) HF, and an equal number of non-HF comparators. We achieved good discriminative performance for both prevalent (voting classifier; AUC: 0.76; F1 score: 0.70) and incident (light gradient boosting machine: AUC: 0.74; F1 score: 0.68) HF. Our radiomics models showed marginally better performance compared to PAT area alone. Increased PAT size (maximum 2D diameter in a given column or slice) and texture heterogeneity (sum entropy) were important features for prevalent and incident HF classification models.

CONCLUSIONS

The amount and character of PAT discriminate individuals with prevalent HF and predict incidence of future HF.

CLINICAL RELEVANCE STATEMENT

This study presents an innovative application of pericardial adipose tissue (PAT) radiomics phenotyping as a predictive tool for heart failure (HF), a major public health concern. By leveraging advanced machine learning methods, the research uncovers that the quantity and characteristics of PAT can be used to identify existing cases of HF and predict future occurrences. The enhanced performance of these radiomics models over PAT area alone supports the potential for better personalised care through earlier detection and prevention of HF.

KEY POINTS

•PAT radiomics applied to CMR was used for the first time to derive binary machine learning classifiers to develop models for discrimination of prevalence and prediction of incident heart failure. •Models using PAT area provided acceptable discrimination between cases of prevalent or incident heart failure and comparator groups. •An increased PAT volume (increased diameter using shape features) and greater texture heterogeneity captured by radiomics texture features (increased sum entropy) can be used as an additional classifier marker for heart failure.

Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

INTRODUCTION

The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures.

METHODS

In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025.

FINDINGS

Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2-6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p<0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5-5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p<0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4-10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p<0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32-4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP >5mg/L, OR 3·55 [1·23-11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation.

INTERPRETATION

After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification.

FUNDING

UK Research and Innovation and National Institute for Health Research.

Perivascular adipose tissue as a source of therapeutic targets and clinical biomarkers

Obesity is a modifiable cardiovascular risk factor, but adipose tissue (AT) depots in humans are anatomically, histologically, and functionally heterogeneous. For example, visceral AT is a pro-atherogenic secretory AT depot, while subcutaneous AT represents a more classical energy storage depot. Perivascular adipose tissue (PVAT) regulates vascular biology via paracrine cross-talk signals. In this position paper, the state-of-the-art knowledge of various AT depots is reviewed providing a consensus definition of PVAT around the coronary arteries, as the AT surrounding the artery up to a distance from its outer wall equal to the luminal diameter of the artery. Special focus is given to the interactions between PVAT and the vascular wall that render PVAT a potential therapeutic target in cardiovascular diseases. This Clinical Consensus Statement also discusses the role of PVAT as a clinically relevant source of diagnostic and prognostic biomarkers of vascular function, which may guide precision medicine in atherosclerosis, hypertension, heart failure, and other cardiovascular diseases. In this article, its role as a 'biosensor' of vascular inflammation is highlighted with description of recent imaging technologies that visualize PVAT in clinical practice, allowing non-invasive quantification of coronary inflammation and the related residual cardiovascular inflammatory risk, guiding deployment of therapeutic interventions. Finally, the current and future clinical applicability of artificial intelligence and machine learning technologies is reviewed that integrate PVAT information into prognostic models to provide clinically meaningful information in primary and secondary prevention.

Assessment of Myocardial 18F-FDG Uptake at PET/CT in Asymptomatic SARS-CoV-2-vaccinated and Nonvaccinated Patients

Background Patients who developed myocarditis following SARS-CoV-2 vaccination show abnormalities on cardiac MRI. However, whether myocardial changes occur in asymptomatic individuals following vaccination is not well established. Purpose To assess myocardial 18Fluorine-fluorodeoxyglucose (18F-FDG) uptake on PET/CT in asymptomatic SARS-CoV-2 vaccinated patients compared to nonvaccinated patients. Materials and Methods This retrospective study included patients who underwent 18F-FDG PET/CT for indications unrelated to myocarditis during the period before (11/1/2020 - 2/16/2021) and after (2/17/20121 - 3/31/2022) SARS-CoV-2 vaccines were available. Myocardial and axillary FDG uptake were quantitatively assessed using maximum standardized uptake value (SUVmax). SUVmax values in all patients and in patients stratified by sex (male/female), age (<40, 41-60, >60 years), and time interval between vaccination and PET/CT were compared using Mann-Whitney U test or Kruskal-Wallis test with post ad -hoc Dwass, Steel, Critchlow-Fligner multiple comparison analysis. Results The study included 303 nonvaccinated patients (mean age, 52.9 years ± 14.9 [SD]; 157 females) and 700 vaccinated patients (mean age, 56.8 years ± 13.7 [SD]; 344 females). Vaccinated patients had overall higher myocardial FDG uptake compared to nonvaccinated patients (median SUVmax, 4.8 [IQR: 3.0-8.5] vs median SUVmax, 3.3 [IQR: 2.5-6.2]; P < .0001). Myocardial SUVmax was higher in vaccinated patients regardless of sex (median range, 4.7-4.9 [IQR: 2.9-8.6]) or patient age (median range, 4.7-5.6 [IQR: 2.9-8.6]) compared to corresponding nonvaccinated groups (sex median range, 3.2-3.9 [IQR: 2.4-7.2]; age median range, 3.3-3.3 [IQR: 2.3-6.1]; P range, <.001-.015). Furthermore, increased myocardial FDG uptake was observed in patients imaged 1-30, 31-60, 61-120, and 121-180 days after their second vaccination (median SUVmax range, 4.6-5.1 [IQR: 2.9-8.6]) and increased ipsilateral axillary uptake was observed in patients imaged 1-30, 31-60, 61-120 days after their 2nd vaccination (median SUVmax range, 1.5-2.0 [IQR: 1.2-3.4]) compared to the nonvaccinated patients (P range, <.001-<.001). Conclusion Compared to nonvaccinated patients, asymptomatic patients who received their 2nd vaccination 1-180 days prior to imaging showed increased myocardial FDG uptake on PET/CT. See also the editorial by Bluemke in this issue.

Role of Human Epicardial Adipose Tissue-Derived miR-92a-3p in Myocardial Redox State

BACKGROUND

Visceral obesity is directly linked to increased cardiovascular risk, including heart failure.

OBJECTIVES

This study explored the ability of human epicardial adipose tissue (EAT)-derived microRNAs (miRNAs) to regulate the myocardial redox state and clinical outcomes.

METHODS

This study screened for miRNAs expressed and released from human EAT and tested for correlations with the redox state in the adjacent myocardium in paired EAT/atrial biopsy specimens from patients undergoing cardiac surgery. Three miRNAs were then tested for causality in an in vitro model of cardiomyocytes. At a clinical level, causality/directionality were tested using genome-wide association screening, and the underlying mechanisms were explored using human biopsy specimens, as well as overexpression of the candidate miRNAs and their targets in vitro and in vivo using a transgenic mouse model. The final prognostic value of the discovered targets was tested in patients undergoing cardiac surgery, followed up for a median of 8 years.

RESULTS

EAT miR-92a-3p was related to lower oxidative stress in human myocardium, a finding confirmed by using genetic regulators of miR-92a-3p in the human heart and EAT. miR-92a-3p reduced nicotinamide adenine dinucleotide phosphate (NADPH)-oxidase-derived superoxide (O2.-) by targeting myocardial expression of WNT5A, which regulated Rac1-dependent activation of NADPH oxidases. Finally, high miR-92a-3p levels in EAT were independently related with lower risk of adverse cardiovascular events.

CONCLUSIONS

EAT-derived miRNAs exert paracrine effects on the human heart. Indeed miR-92a-3p suppresses the wingless-type MMTV integration site family, member 5a/Rac1/NADPH oxidase axis and improves the myocardial redox state. EAT-derived miR-92a-3p is related to improved clinical outcomes and is a rational therapeutic target for the prevention and treatment of obesity-related heart disease.

Deep-Learning for Epicardial Adipose Tissue Assessment With Computed Tomography: Implications for Cardiovascular Risk Prediction

BACKGROUND

Epicardial adipose tissue (EAT) volume is a marker of visceral obesity that can be measured in coronary computed tomography angiograms (CCTA). The clinical value of integrating this measurement in routine CCTA interpretation has not been documented.

OBJECTIVES

This study sought to develop a deep-learning network for automated quantification of EAT volume from CCTA, test it in patients who are technically challenging, and validate its prognostic value in routine clinical care.

METHODS

The deep-learning network was trained and validated to autosegment EAT volume in 3,720 CCTA scans from the ORFAN (Oxford Risk Factors and Noninvasive Imaging Study) cohort. The model was tested in patients with challenging anatomy and scan artifacts and applied to a longitudinal cohort of 253 patients post-cardiac surgery and 1,558 patients from the SCOT-HEART (Scottish Computed Tomography of the Heart) Trial, to investigate its prognostic value.

RESULTS

External validation of the deep-learning network yielded a concordance correlation coefficient of 0.970 for machine vs human. EAT volume was associated with coronary artery disease (odds ratio [OR] per SD increase in EAT volume: 1.13 [95% CI: 1.04-1.30]; P = 0.01), and atrial fibrillation (OR: 1.25 [95% CI: 1.08-1.40]; P = 0.03), after correction for risk factors (including body mass index). EAT volume predicted all-cause mortality (HR per SD: 1.28 [95% CI: 1.10-1.37]; P = 0.02), myocardial infarction (HR: 1.26 [95% CI:1.09-1.38]; P = 0.001), and stroke (HR: 1.20 [95% CI: 1.09-1.38]; P = 0.02) independently of risk factors in SCOT-HEART (5-year follow-up). It also predicted in-hospital (HR: 2.67 [95% CI: 1.26-3.73]; P ≤ 0.01) and long-term post-cardiac surgery atrial fibrillation (7-year follow-up; HR: 2.14 [95% CI: 1.19-2.97]; P ≤ 0.01).

CONCLUSIONS

Automated assessment of EAT volume is possible in CCTA, including in patients who are technically challenging; it forms a powerful marker of metabolically unhealthy visceral obesity, which could be used for cardiovascular risk stratification.

Assessment of Cardiac Energy Metabolism, Function, and Physiology in Patients With Heart Failure Taking Empagliflozin: The Randomized, Controlled EMPA-VISION Trial

BACKGROUND

Sodium-glucose co-transporter 2 inhibitors (SGLT2i) have emerged as a paramount treatment for patients with heart failure (HF), irrespective of underlying reduced or preserved ejection fraction. However, a definite cardiac mechanism of action remains elusive. Derangements in myocardial energy metabolism are detectable in all HF phenotypes, and it was proposed that SGLT2i may improve energy production. The authors aimed to investigate whether treatment with empagliflozin leads to changes in myocardial energetics, serum metabolomics, and cardiorespiratory fitness.

METHODS

EMPA-VISION (Assessment of Cardiac Energy Metabolism, Function and Physiology in Patients With Heart Failure Taking Empagliflozin) is a prospective, randomized, double-blind, placebo-controlled, mechanistic trial that enrolled 72 symptomatic patients with chronic HF with reduced ejection fraction (HFrEF; n=36; left ventricular ejection fraction ≤40%; New York Heart Association class ≥II; NT-proBNP [N-terminal pro-B-type natriuretic peptide] ≥125 pg/mL) and HF with preserved ejection fraction (HFpEF; n=36; left ventricular ejection fraction ≥50%; New York Heart Association class ≥II; NT-proBNP ≥125 pg/mL). Patients were stratified into respective cohorts (HFrEF versus HFpEF) and randomly assigned to empagliflozin (10 mg; n=35: 17 HFrEF and 18 HFpEF) or placebo (n=37: 19 HFrEF and 18 HFpEF) once daily for 12 weeks. The primary end point was a change in the cardiac phosphocreatine:ATP ratio (PCr/ATP) from baseline to week 12, determined by phosphorus magnetic resonance spectroscopy at rest and during peak dobutamine stress (65% of age-maximum heart rate). Mass spectrometry on a targeted set of 19 metabolites was performed at baseline and after treatment. Other exploratory end points were investigated.

RESULTS

Empagliflozin treatment did not change cardiac energetics (ie, PCr/ATP) at rest in HFrEF (adjusted mean treatment difference [empagliflozin - placebo], -0.25 [95% CI, -0.58 to 0.09]; P=0.14) or HFpEF (adjusted mean treatment difference, -0.16 [95% CI, -0.60 to 0.29]; P=0.47]. Likewise, there were no changes in PCr/ATP during dobutamine stress in HFrEF (adjusted mean treatment difference, -0.13 [95% CI, -0.35 to 0.09]; P=0.23) or HFpEF (adjusted mean treatment difference, -0.22 [95% CI, -0.66 to 0.23]; P=0.32). No changes in serum metabolomics or levels of circulating ketone bodies were observed.

CONCLUSIONS

In patients with either HFrEF or HFpEF, treatment with 10 mg of empagliflozin once daily for 12 weeks did not improve cardiac energetics or change circulating serum metabolites associated with energy metabolism when compared with placebo. Based on our results, it is unlikely that enhancing cardiac energy metabolism mediates the beneficial effects of SGLT2i in HF.

REGISTRATION

URL: https://www.

CLINICALTRIALS

gov; Unique identifier: NCT03332212.

PHACTR1 modulates vascular compliance but not endothelial function: a translational study

AIMS

The non-coding locus at 6p24 located in Intron 3 of PHACTR1 has consistently been implicated as a risk allele in myocardial infarction and multiple other vascular diseases. Recent murine studies have identified a role for Phactr1 in the development of atherosclerosis. However, the role of PHACTR1 in vascular tone and in vivo vascular remodelling has yet to be established. The aim of this study was to investigate the role of PHACTR1 in vascular function.

METHODS AND RESULTS

Prospectively recruited coronary artery disease (CAD) patients undergoing bypass surgery and retrospectively recruited spontaneous coronary artery dissection (SCAD) patients and matched healthy volunteers were genotyped at the PHACTR1 rs9349379 locus. We observed a significant association between the PHACTR1 loci and changes in distensibility in both the ascending aorta (AA = 0.0053 ± 0.0004, AG = 0.0041 ± 0.003, GG = 0.0034 ± 0.0009, P < 0.05, n = 58, 54, and 7, respectively) and carotid artery (AA = 12.83 ± 0.51, AG = 11.14 ± 0.38, GG = 11.69 ± 0.66, P < 0.05, n = 70, 65, and 18, respectively). This association was not observed in the descending aorta or in SCAD patients. In contrast, the PHACTR1 locus was not associated with changes in endothelial cell function with no association between the rs9349379 locus and in vivo or ex vivo vascular function observed in CAD patients. This finding was confirmed in our murine model where the loss of Phactr1 on the pro-atherosclerosis ApoE-/- background did not alter ex vivo vascular function.

CONCLUSION

In conclusion, we have shown a role for PHACTR1 in arterial compliance across multiple vascular beds. Our study suggests that PHACTR1 has a key structural role within the vasculature.

Combination of exercise and GLP-1 receptor agonist treatment reduces severity of metabolic syndrome, abdominal obesity, and inflammation: a randomized controlled trial

BACKGROUND

Identifying and reducing cardiometabolic risks driven by obesity remains a healthcare challenge. The metabolic syndrome is associated with abdominal obesity and inflammation and is predictive of long-term risk of developing type 2 diabetes and cardiovascular disease in otherwise healthy individuals living with obesity. Therefore, we investigated the effects of adherent exercise, a glucagon-like peptide 1 receptor agonist (GLP-1 RA), or the combination on severity of metabolic syndrome, abdominal obesity, and inflammation following weight loss.

METHODS

This was a randomized, double-blinded, placebo-controlled trial. During an 8-week low-calorie diet (800 kcal/day), 195 adults with obesity and without diabetes lost 12% in body weight. Participants were then evenly randomized to four arms of one-year treatment with: placebo, moderate-to-vigorous exercise (minimum of 150 min/week of moderate-intensity or 75 min/week of vigorous-intensity aerobic physical activity or an equivalent combination of both), the GLP-1 RA liraglutide 3.0 mg/day, or a combination (exercise + liraglutide). A total of 166 participants completed the trial. We assessed the prespecified secondary outcome metabolic syndrome severity z-score (MetS-Z), abdominal obesity (estimated as android fat via dual-energy X-ray absorptiometry), and inflammation marker high-sensitivity C-reactive protein (hsCRP). Statistical analysis was performed on 130 participants adherent to the study interventions (per-protocol population) using a mixed linear model.

RESULTS

The diet-induced weight loss decreased the severity of MetS-Z from 0.57 to 0.06, which was maintained in the placebo and exercise groups after one year. MetS-Z was further decreased by liraglutide (- 0.37, 95% CI - 0.58 to - 0.16, P < 0.001) and the combination treatment (- 0.48, 95% CI - 0.70 to - 0.25, P < 0.001) compared to placebo. Abdominal fat percentage decreased by 2.6, 2.8, and 6.1 percentage points in the exercise, liraglutide, and combination groups compared to placebo, respectively, and hsCRP decreased only in the combination group compared with placebo (by 43%, P = 0.03).

CONCLUSION

The combination of adherent exercise and liraglutide treatment reduced metabolic syndrome severity, abdominal obesity, and inflammation and may therefore reduce cardiometabolic risk more than the individual treatments. Trial registration EudraCT number: 2015-005585-32, ClinicalTrials.gov: NCT04122716.

Artificial intelligence in coronary computed tomography angiography: Demands and solutions from a clinical perspective

Coronary computed tomography angiography (CCTA) is increasingly the cornerstone in the management of patients with chronic coronary syndromes. This fact is reflected by current guidelines, which show a fundamental shift towards non-invasive imaging - especially CCTA. The guidelines for acute and stable coronary artery disease (CAD) of the European Society of Cardiology from 2019 and 2020 emphasize this shift. However, to fulfill this new role, a broader availability in adjunct with increased robustness of data acquisition and speed of data reporting of CCTA is needed. Artificial intelligence (AI) has made enormous progress for all imaging methodologies concerning (semi)-automatic tools for data acquisition and data post-processing, with outreach toward decision support systems. Besides onco- and neuroimaging, cardiac imaging is one of the main areas of application. Most current AI developments in the scenario of cardiac imaging are related to data postprocessing. However, AI applications (including radiomics) for CCTA also should enclose data acquisition (especially the fact of dose reduction) and data interpretation (presence and extent of CAD). The main effort will be to integrate these AI-driven processes into the clinical workflow, and to combine imaging data/results with further clinical data, thus - beyond the diagnosis of CAD- enabling prediction and forecast of morbidity and mortality. Furthermore, data fusing for therapy planning (e.g., invasive angiography/TAVI planning) will be warranted. The aim of this review is to present a holistic overview of AI applications in CCTA (including radiomics) under the umbrella of clinical workflows and clinical decision-making. The review first summarizes and analyzes applications for the main role of CCTA, i.e., to non-invasively rule out stable coronary artery disease. In the second step, AI applications for additional diagnostic purposes, i.e., to improve diagnostic power (CAC = coronary artery classifications), improve differential diagnosis (CT-FFR and CT perfusion), and finally improve prognosis (again CAC plus epi- and pericardial fat analysis) are reviewed.

Lectin-Like Oxidized Low-Density Lipoprotein Receptor 1 Inhibition in Type 2 Diabetes: Phase 1 Results

Background Blockade of the lectin-like oxidized low-density lipoprotein receptor-1 (LOX-1) is a potentially attractive mechanism for lowering inflammatory and lipid risk in patients with atherosclerosis. This study aims to assess the safety, tolerability, and target engagement of MEDI6570, a high-affinity monoclonal blocking antibody to LOX-1. Methods and Results This phase 1, first-in-human, placebo-controlled study (NCT03654313) randomized 88 patients with type 2 diabetes to receive single ascending doses (10, 30, 90, 250, or 500 mg) or multiple ascending doses (90, 150, or 250 mg once monthly for 3 months) of MEDI6570 or placebo. Primary end point was safety; secondary and exploratory end points included pharmacokinetics, immunogenicity, free soluble LOX-1 levels, and change in coronary plaque volume. Mean age was 57.6/58.1 years in the single ascending doses/multiple ascending doses groups, 31.3%/62.5% were female, and mean type 2 diabetes duration was 9.7/8.7 years. Incidence of adverse events was similar among cohorts. MEDI6570 exhibited nonlinear pharmacokinetics, with terminal half-life increasing from 4.6 days (30 mg) to 11.2 days (500 mg), consistent with target-mediated drug disposition. Dose-dependent reductions in mean soluble LOX-1 levels from baseline were observed (>66% at 4 weeks and 71.61-82.96% at 10 weeks in the single ascending doses and multiple ascending doses groups, respectively). After 3 doses, MEDI6570 was associated with nonsignificant regression of noncalcified plaque volume versus placebo (-13.45 mm3 versus -8.25 mm3). Conclusions MEDI6570 was well tolerated and demonstrated dose-dependent soluble LOX-1 suppression and a pharmacokinetic profile consistent with once-monthly dosing. Registration URL: https://clinicaltrials.gov/; Unique identifier: NCT03654313.

Mechanisms, therapeutic implications, and methodological challenges of gut microbiota and cardiovascular diseases: a position paper by the ESC Working Group on Coronary Pathophysiology and Microcirculation

The human gut microbiota is the microbial ecosystem in the small and large intestines of humans. It has been naturally preserved and evolved to play an important role in the function of the gastrointestinal tract and the physiology of its host, protecting from pathogen colonization, and participating in vitamin synthesis, the functions of the immune system, as well as glucose homeostasis and lipid metabolism, among others. Mounting evidence from animal and human studies indicates that the composition and metabolic profiles of the gut microbiota are linked to the pathogenesis of cardiovascular disease, particularly arterial hypertension, atherosclerosis, and heart failure. In this review article, we provide an overview of the function of the human gut microbiota, summarize, and critically address the evidence linking compositional and functional alterations of the gut microbiota with atherosclerosis and coronary artery disease and discuss the potential of strategies for therapeutically targeting the gut microbiota through various interventions.

Non-canonical WNT signalling in cardiovascular disease: mechanisms and therapeutic implications

WNT signalling comprises a diverse spectrum of receptor-mediated pathways activated by a large family of WNT ligands and influencing fundamental biological processes. WNT signalling includes the β-catenin canonical pathway and the non-canonical pathways, namely the planar cell polarity and the calcium-dependent pathways. Advances over the past decade have linked non-canonical WNT signalling with key mechanisms of atherosclerosis, including oxidative stress, endothelial dysfunction, macrophage activation and vascular smooth muscle cell phenotype regulation. In addition, non-canonical WNT signalling is involved in crucial aspects of myocardial biology, from fibrosis to hypertrophy and oxidative stress. Importantly, non-canonical WNT signalling activation has complex effects in adipose tissue in the context of obesity, thereby potentially linking metabolic and vascular diseases. Tissue-specific targeting of non-canonical WNT signalling might be associated with substantial risks of off-target tumorigenesis, challenging its therapeutic potential. However, novel technologies, such as monoclonal antibodies, recombinant decoy receptors, tissue-specific gene silencing with small interfering RNAs and gene editing with CRISPR-Cas9, might enable more efficient therapeutic targeting of WNT signalling in the cardiovascular system. In this Review, we summarize the components of non-canonical WNT signalling, their links with the main mechanisms of atherosclerosis, heart failure and arrhythmias, and the rationale for targeting individual components of non-canonical WNT signalling for the treatment of cardiovascular disease.

Noninvasive Plaque Imaging to Accelerate Coronary Artery Disease Drug Development

Coronary artery disease (CAD) remains the leading cause of adult mortality globally. Targeting known modifiable risk factors has had substantial benefit, but there remains a need for new approaches. Improvements in invasive and noninvasive imaging techniques have enabled an increasing recognition of distinct quantitative phenotypes of coronary atherosclerosis that are prognostically relevant. There are marked differences in plaque phenotype, from the high-risk, lipid-rich, thin-capped atheroma to the low-risk, quiescent, eccentric, nonobstructive calcified plaque. Such distinct phenotypes reflect different pathophysiologic pathways and are associated with different risks for acute ischemic events. Noninvasive coronary imaging techniques, such as computed tomography, positron emission tomography, and coronary magnetic resonance imaging, have major potential to accelerate cardiovascular drug development, which has been affected by the high costs and protracted timelines of cardiovascular outcome trials. This may be achieved through enrichment of high-risk phenotypes with higher event rates or as primary end points of drug efficacy, at least in phase 2 trials, in a manner historically performed through intravascular coronary imaging studies. Herein, we provide a comprehensive review of the current technology available and its application in clinical trials, including implications for sample size requirements, as well as potential limitations. In its effort to accelerate drug development, the US Food and Drug Administration has approved surrogate end points for 120 conditions, but not for CAD. There are robust data showing the beneficial effects of drugs, including statins, on CAD progression and plaque stabilization in a manner that correlates with established clinical end points of mortality and major adverse cardiovascular events. This, together with a clear mechanistic rationale for using imaging as a surrogate CAD end point, makes it timely for CAD imaging end points to be considered. We discuss the importance of global consensus on these imaging end points and protocols and partnership with regulatory bodies to build a more informed, sustainable staged pathway for novel therapies.

Pericardial adiposity is independently linked to adverse cardiovascular phenotypes: a CMR study of 42 598 UK Biobank participants

AIMS

We evaluated independent associations of cardiovascular magnetic resonance (CMR)-measured pericardial adipose tissue (PAT) with cardiovascular structure and function and considered underlying mechanism in 42 598 UK Biobank participants.

METHODS AND RESULTS

We extracted PAT and selected CMR metrics using automated pipelines. We estimated associations of PAT with each CMR metric using linear regression adjusting for age, sex, ethnicity, deprivation, smoking, exercise, processed food intake, body mass index, diabetes, hypertension, height cholesterol, waist-to-hip ratio, impedance fat measures, and magnetic resonance imaging abdominal visceral adiposity measures. Higher PAT was independently associated with unhealthy left ventricular (LV) structure (greater wall thickness, higher LV mass, more concentric pattern of LV hypertrophy), poorer LV function (lower LV global function index, lower LV stroke volume), lower left atrial ejection fraction, and lower aortic distensibility. We used multiple mediation analysis to examine the potential mediating effect of cardiometabolic diseases and blood biomarkers (lipid profile, glycaemic control, inflammation) in the PAT-CMR relationships. Higher PAT was associated with cardiometabolic disease (hypertension, diabetes, high cholesterol), adverse serum lipids, poorer glycaemic control, and greater systemic inflammation. We identified potential mediation pathways via hypertension, adverse lipids, and inflammation markers, which overall only partially explained the PAT-CMR relationships.

CONCLUSION

We demonstrate association of PAT with unhealthy cardiovascular structure and function, independent of baseline comorbidities, vascular risk factors, inflammatory markers, and multiple non-invasive and imaging measures of obesity. Our findings support an independent role of PAT in adversely impacting cardiovascular health and highlight CMR-measured PAT as a potential novel imaging biomarker of cardiovascular risk.

Coronary CT angiography derived pericoronary inflammation and bespoke cardiovascular risk prediction in the lipid clinic: beyond the calcium score

Background

Dyslipidaemia promotes atherosclerosis. Genetic dyslipidaemias, Familial Hypercholesterolaemia (FH) being the most common, are associated with heightened risk of coronary artery disease (CAD) and premature major adverse cardiovascular events (MACE). However, this risk is both heterogeneous and modifiable with treatment.

CT coronary imaging can identify subclinical atherosclerosis, enabling personalised risk stratification and treatment targets. Coronary artery calcium scoring (CACS) is current first-line in European guidelines for asymptomatic patients. However, calcification occurs late in CAD pathogenesis and CACS has low specificity in young patients with severe FH. CT coronary angiography (CTCA) assesses non-calcific plaque and high-risk plaque (HRP) features unappreciable with CACS. Additionally, the pericoronary fat attenuation index (FAI) measures inflammation on routine CTCA and is the strongest non-invasive imaging biomarker of risk of fatal MI.

Purpose

To quantify and compare the reclassification of subclinical atherosclerosis burden in Lipid Clinic patients assessed via CACS vs CTCA with FAI analysis.

Methods

Analysis of a prospectively maintained clinical database of asymptomatic Lipid Clinic patients with both CACS and CTCA imaging from May 2019 to December 2020. CACS was reported with the standardised Agastston criteria and compared with (i) the CTCA-derived Coronary Artery Disease – Reporting and Data System (CAD RADS) grading of anatomical stenosis, including a modifier for HRP features, and (ii) FAI analysis. Significance was defined as two-tailed p75th percentile vs age and sex matched controls) was seen in 6/27 (22%) patients with none to mild calcification on CACS and 6/28 (21%) patients with none to mild CAD on CTCA, of whom 3/7 (43%) had HRP. High FAI was seen in all groups of calcification severity and CAD RADS score (Figure 2). The proportion with high FAI was higher in CAD RADS 0 vs CAD RADS 4, and CACS severity was not associated with level of inflammation (p=0.94).

High FAI was observed in 16% of patients on treatment, suggesting treatment failure. This included patients with CACS ranging from 0 to severe (&gt;400), and CAD RADS of minimal (1) to severe (4).

Conclusion

CTCA re-stratifies CAD presence and severity vs CACS in a high-risk, asymptomatic patient group and identified a high proportion of patients with HRP features. FAI provides incremental value in identification of patients at risk of future MACE regardless of CACS grade, including patients without evidence of overt CAD. Identifying high FAI on treatment may imply treatment failure.

Funding Acknowledgement

Type of funding sources: None.

Constructing custom-made radiotranscriptomic signatures from CT angiograms: an application in COVID-19 vascular inflammation

Background

Advances in computational methodologies have enabled processing of large datasets originating from imaging studies. However, most imaging biomarkers suffer from a lack of direct links with underlying biology, as they are only observationally correlated with pathophysiology.

Purpose

To develop and validate a novel AI-assisted image analysis platform, by applying quantitative radiotranscriptomics that quantifies cytokine-driven vascular inflammation from routine CT angiograms (CTA) performed as part of clinical care in COVID-19.

Methods

We used this platform to train the radiotranscriptomic signature C19-RS, derived from the perivascular space around the aorta and the internal mammary artery in routine chest CTAs, to best describe cytokine-driven vascular inflammation, defined using transcriptomic profiles from RNA sequencing data from human arterial biopsies (A). This signature was validated externally in 358 clinically indicated CT pulmonary angiograms from patients with or without COVID-19 from 3 different geographical regions.

Results

First, 22 patients who had a CTA before the pandemic underwent repeat CTA <6 months post COVID-19 infection (B). Compared with 22 controls (matched for age, gender, and BMI) C19-RS was increased only in the COVID-19 group (C). Next, C19-RS was calculated in a cohort of 331 patients hospitalised during the pandemic, and was higher in COVID-19 positives (adjusted OR=2.97 [95% CI: 1.43–6.27], p=0.004, D). C19-RS had prognostic value for in-hospital mortality in COVID-19, with HR=3.31 ([95% CI: 1.49–7.33], p=0.003) and 2.58 ([95% CI: 1.10–6.05], p=0.028) in two testing cohorts respectively (E, F), adjusted for clinical factors and biochemical biomarkers of inflammation and myocardial injury. The corrected HR for in-hospital mortality was 8.24 [95% CI: 2.16–31.36], p=0.002 for those who received no treatment with dexamethasone, but only 2.27 [95% CI: 0.69–7.55], p=0.18 in those who received dexamethasone subsequently to the C19-RS based image analysis, suggesting that vascular inflammation may have been a therapeutic target of dexamethasone in COVID-19. Finally, C19-RS was strongly associated (r=0.61, p=0.0003) with a whole blood transcriptional module representing dysregulation of coagulation and platelet aggregation pathways.

Conclusion

We present the first proof of concept study that combines transcriptomics with radiomics to provide a platform for the development of machine learning derived radiotranscriptomics analysis of routine clinical CT scans for the development of non-invasive imaging biomarkers. Application in COVID-19 produced C19-RS, a marker of cytokine-driven inflammation driving systemic activation of coagulation, that predicts in-hospital mortality and identifies people who will have better response to anti-inflammatory treatments, allowing targeted therapy. This AI-assisted image analysis platform may have applications across a wide range of vascular diseases, from infections to autoimmune diseases.

Funding Acknowledgement

Type of funding sources: Foundation. Main funding source(s): EPSRC, British Heart Foundation, NIHR

Automated deep learning quantification of epicardial adiposity on cardiac CT predicts atrial fibrillation risk immediately following cardiac surgery and long-term

Introduction

Epicardial adipose tissue (EAT) is a visceral fat deposit within the pericardial sac which surrounds the heart myocardium and coronary arteries. The automated quantification of EAT volume is possible from routine CCTA scans via a deep-learning approach. The use of automated EAT quantification for the assessment of atrial fibrillation (AF) risk in the post-operative period, and longer-term, has not been previously investigated.

Purpose

To apply a deep-learning approach for automated segmentation of EAT from routine CCTA scans to assess the immediate post-operative and long-term risk of AF conveyed by EAT.

Methods

A deep-learning automated EAT segmentation tool using a 3D Residual-U-Net neural network architecture for 3D volumetric segmentation of CCTA data was created and trained on over 2800 consecutive CCTA performed as part of clinical care in patients with stable chest pain from 2015 onwards within the European arm of the Oxford Risk Factors And Non Invasive Imaging (ORFAN) Study. External validation in 817patients demonstrated excellent correlation between machine and human expert (CCC = 0.972). The prognostic value of deep-learning derived EAT volume was assessed in the AdipoRedOx Study (n=253; UK patients undergoing cardiac surgery) against both immediate in-hospital outcomes and longer-term outcomes from UK-wide NHS data, with adjustment for AF risk factors.

Results

There were 97 cases of new-onset AF in the immediate post-operative period (38.3%). EAT volume was found to be an independent predictor of post-operative AF regardless of body mass index. Utilising the median EAT volume as the cut point, the adjusted hazard ratio (HR [95% CI]) for risk of new-onset post-operative AF in-hospital was 1.56 [1.09–3.85], p&lt;0.01 (Figure 1A). In receiver-operator characteristic analysis EAT volume added significant incremental prognostic power for the discrimination of in-hospital post-operative AF over a traditional risk factor model ΔAUC=0.101, p&lt;0.01 (Figure 1B).

Over a median follow-up period of 89 months there were 48 unique cases (19%) of confirmed AF found in nation-wide NHS hospital episode statistics data for the AdipoRedOx cohort. EAT volume was found to be a significant independent predictor of long-term AF. Utilising the median EAT volume as the cut point, the adjusted HR for risk of new-onset long-term AF following cardiac surgery was 1.25 [1.08–3.17], p&lt;0.01 (Figure 1C).

Conclusions

Automatically segmented EAT volume measured using a deep learning network predicts risk of both short-term new onset AF following cardiac surgery, and long-term risk of AF in the 7 years following the surgery independently of BMI and AF risk factors. This suggests that EAT is a potent mediator of AF risk in the post cardiac surgery setting.

Funding Acknowledgement

Type of funding sources: Foundation. Main funding source(s): British Heart Foundation - TG/19/2/34831EU Commission - 965286

Adipose tissue derived ceramides regulate myocardial redox state and predict cardiovascular outcomes

Background

Obesity is linked to both dysfunctional adipose tissue (AT) and heart failure, but the exact mechanisms mediating these associations are unknown. Although ceramides biosynthesis is dysregulated in obesity, their role as mediators of obesity-induced myocardial dysfunction is unclear.

Purpose

We investigate the causal role of AT-derived ceramides in the regulation of myocardial redox state and explore their role in predicting cardiovascular outcomes.

Methods

The study population included a total of 880 patients undergoing cardiac surgery. A panel of 20 sphingolipids was measured in plasma as well as in biopsies of subcutaneous AT (ScAT), thoracic AT (ThAT) and epicardial AT (EpAT) and their secretome, obtained from a subgroup of n=48. Myocardial redox state was measured using lucigenin chemiluminescence and the contribution of NOXs, uncoupled nitric oxide synthases and mitochondrial oxidases in O2•– production was quantified. The cohort was followed up for a median of 8.3 years. Genome-wide genetic analysis was done using the UK Biobank array. A total of 99,524 SNPs within 50kb of 110 genes involved in sphingolipid biosynthesis were analysed to identify genetic variants that could predict CVD outcomes using cis-Mendelian Randomisation. The underlying mechanisms were then explored further, using differentiated H9c2 cardiomyocytes in vitro and human right atrial tissue ex vivo.

Results

The production and secretion of C16:0-ceramide (CerC16) was higher in visceral AT (EpAT and ThAT) compared to ScAT (p&lt;0.0001). Patients with high plasma levels of CerC16 and its derivative C16:0-glucosylceramide (GlcC16) had higher myocardial O2•– production vs those with low/int. levels (p&lt;0.05 for both) (A). To test the causality of this association, we performed a targeted single-SNP analysis for the genetic prediction of GlcC16 levels demonstrating that rs112572487, an intronic variant in UGCG (an enzyme that catalyses glucosylceramide formation from ceramides), was the top hit (B). Indeed, those with the rs112572487 minor allele (G) displayed significantly increased myocardial NOX-derived O2•– (C) and plasma GlcC16 levels (D) vs those without. Exogenous CerC16 (20nM) induced NOX-derived O2•– production in H9c2 cardiomyocytes, an effect prevented by the UGCG inhibitor D-PDMP (E), suggesting that GlcC16 is a modifiable regulator of myocardial NOX-O2•–. Importantly, high plasma GlcC16 levels were associated with a higher risk of cardiac death and/or heart failure (adj. HR=2.128 [95% CI: 1.101, 4.115], p=0.025, for high vs low/int. levels), a relationship also seen with rs112572487 (F).

Conclusions

We demonstrate for the first time, that AT-derived ceramides are causally related with dysregulated myocardial redox signalling and adverse cardiovascular disease outcomes in patients with advanced atherosclerosis. As such, GlcC16 may be an important therapeutic target for the prevention and treatment of cardiovascular complications in obesity and diabetes.

Funding Acknowledgement

Type of funding sources: Foundation. Main funding source(s): The British Heart FoundationBritish Heart Foundation Chair Award

Constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine CT angiograms: a prospective outcomes validation study in COVID-19

BACKGROUND

Direct evaluation of vascular inflammation in patients with COVID-19 would facilitate more efficient trials of new treatments and identify patients at risk of long-term complications who might respond to treatment. We aimed to develop a novel artificial intelligence (AI)-assisted image analysis platform that quantifies cytokine-driven vascular inflammation from routine CT angiograms, and sought to validate its prognostic value in COVID-19.

METHODS

For this prospective outcomes validation study, we developed a radiotranscriptomic platform that uses RNA sequencing data from human internal mammary artery biopsies to develop novel radiomic signatures of vascular inflammation from CT angiography images. We then used this platform to train a radiotranscriptomic signature (C19-RS), derived from the perivascular space around the aorta and the internal mammary artery, to best describe cytokine-driven vascular inflammation. The prognostic value of C19-RS was validated externally in 435 patients (331 from study arm 3 and 104 from study arm 4) admitted to hospital with or without COVID-19, undergoing clinically indicated pulmonary CT angiography, in three UK National Health Service (NHS) trusts (Oxford, Leicester, and Bath). We evaluated the diagnostic and prognostic value of C19-RS for death in hospital due to COVID-19, did sensitivity analyses based on dexamethasone treatment, and investigated the correlation of C19-RS with systemic transcriptomic changes.

FINDINGS

Patients with COVID-19 had higher C19-RS than those without (adjusted odds ratio [OR] 2·97 [95% CI 1·43-6·27], p=0·0038), and those infected with the B.1.1.7 (alpha) SARS-CoV-2 variant had higher C19-RS values than those infected with the wild-type SARS-CoV-2 variant (adjusted OR 1·89 [95% CI 1·17-3·20] per SD, p=0·012). C19-RS had prognostic value for in-hospital mortality in COVID-19 in two testing cohorts (high [≥6·99] vs low [<6·99] C19-RS; hazard ratio [HR] 3·31 [95% CI 1·49-7·33], p=0·0033; and 2·58 [1·10-6·05], p=0·028), adjusted for clinical factors, biochemical biomarkers of inflammation and myocardial injury, and technical parameters. The adjusted HR for in-hospital mortality was 8·24 (95% CI 2·16-31·36, p=0·0019) in patients who received no dexamethasone treatment, but 2·27 (0·69-7·55, p=0·18) in those who received dexamethasone after the scan, suggesting that vascular inflammation might have been a therapeutic target of dexamethasone in COVID-19. Finally, C19-RS was strongly associated (r=0·61, p=0·00031) with a whole blood transcriptional module representing dysregulation of coagulation and platelet aggregation pathways.

INTERPRETATION

Radiotranscriptomic analysis of CT angiography scans introduces a potentially powerful new platform for the development of non-invasive imaging biomarkers. Application of this platform in routine CT pulmonary angiography scans done in patients with COVID-19 produced the radiotranscriptomic signature C19-RS, a marker of cytokine-driven inflammation driving systemic activation of coagulation and responsible for adverse clinical outcomes, which predicts in-hospital mortality and might allow targeted therapy.

FUNDING

Engineering and Physical Sciences Research Council, British Heart Foundation, Oxford BHF Centre of Research Excellence, Innovate UK, NIHR Oxford Biomedical Research Centre, Wellcome Trust, Onassis Foundation.

Clinical characteristics with inflammation profiling of long COVID and association with 1-year recovery following hospitalisation in the UK: a prospective observational study

BACKGROUND

No effective pharmacological or non-pharmacological interventions exist for patients with long COVID. We aimed to describe recovery 1 year after hospital discharge for COVID-19, identify factors associated with patient-perceived recovery, and identify potential therapeutic targets by describing the underlying inflammatory profiles of the previously described recovery clusters at 5 months after hospital discharge.

METHODS

The Post-hospitalisation COVID-19 study (PHOSP-COVID) is a prospective, longitudinal cohort study recruiting adults (aged ≥18 years) discharged from hospital with COVID-19 across the UK. Recovery was assessed using patient-reported outcome measures, physical performance, and organ function at 5 months and 1 year after hospital discharge, and stratified by both patient-perceived recovery and recovery cluster. Hierarchical logistic regression modelling was performed for patient-perceived recovery at 1 year. Cluster analysis was done using the clustering large applications k-medoids approach using clinical outcomes at 5 months. Inflammatory protein profiling was analysed from plasma at the 5-month visit. This study is registered on the ISRCTN Registry, ISRCTN10980107, and recruitment is ongoing.

FINDINGS

2320 participants discharged from hospital between March 7, 2020, and April 18, 2021, were assessed at 5 months after discharge and 807 (32·7%) participants completed both the 5-month and 1-year visits. 279 (35·6%) of these 807 patients were women and 505 (64·4%) were men, with a mean age of 58·7 (SD 12·5) years, and 224 (27·8%) had received invasive mechanical ventilation (WHO class 7-9). The proportion of patients reporting full recovery was unchanged between 5 months (501 [25·5%] of 1965) and 1 year (232 [28·9%] of 804). Factors associated with being less likely to report full recovery at 1 year were female sex (odds ratio 0·68 [95% CI 0·46-0·99]), obesity (0·50 [0·34-0·74]) and invasive mechanical ventilation (0·42 [0·23-0·76]). Cluster analysis (n=1636) corroborated the previously reported four clusters: very severe, severe, moderate with cognitive impairment, and mild, relating to the severity of physical health, mental health, and cognitive impairment at 5 months. We found increased inflammatory mediators of tissue damage and repair in both the very severe and the moderate with cognitive impairment clusters compared with the mild cluster, including IL-6 concentration, which was increased in both comparisons (n=626 participants). We found a substantial deficit in median EQ-5D-5L utility index from before COVID-19 (retrospective assessment; 0·88 [IQR 0·74-1·00]), at 5 months (0·74 [0·64-0·88]) to 1 year (0·75 [0·62-0·88]), with minimal improvements across all outcome measures at 1 year after discharge in the whole cohort and within each of the four clusters.

INTERPRETATION

The sequelae of a hospital admission with COVID-19 were substantial 1 year after discharge across a range of health domains, with the minority in our cohort feeling fully recovered. Patient-perceived health-related quality of life was reduced at 1 year compared with before hospital admission. Systematic inflammation and obesity are potential treatable traits that warrant further investigation in clinical trials.

FUNDING

UK Research and Innovation and National Institute for Health Research.

Risk factors profile of young and older patients with myocardial infarction

Myocardial infarction (MI) among young adults (<45 years) represents a considerable proportion of the total heart attack incidents. The underlying pathophysiologic characteristics, atherosclerotic plaque features, and risk factors profile differ between young and older patients with MI. This review article discusses the main differences between the younger and elderly MI patients as well as the different pathogenic mechanisms underlying the development of MI in the younger. Young patients with MI often have eccentric atherosclerotic plaques with inflammatory features but fewer lesions, and are more likely to be smokers, obese, and have poor lifestyle, such as inactivity and alcohol intake. Compared to older MI patients, younger are more likely to be men, have familial-combined hyperlipidaemia and increased levels of lipoprotein-a. In addition, MI in younger patients may be related to use of cannabis, cocaine use, and androgenic anabolic steroids. Genomic differences especially in the pathways of coagulation and lipid metabolism have also been identified between young and older patients with MI. Better understanding of the risk factors and the anatomic and pathophysiologic processes in young adults can improve MI prevention and treatment strategies in this patient group. Awareness could help identify young subjects at increased risk and guide primary prevention strategies. Additional studies focusing on gene pathways related to lipid metabolism, inflammation, and coagulation are needed.

MPST sulfurtransferase maintains mitochondrial protein import and cellular bioenergetics to attenuate obesity

Given the clinical, economic, and societal impact of obesity, unraveling the mechanisms of adipose tissue expansion remains of fundamental significance. We previously showed that white adipose tissue (WAT) levels of 3-mercaptopyruvate sulfurtransferase (MPST), a mitochondrial cysteine-catabolizing enzyme that yields pyruvate and sulfide species, are downregulated in obesity. Here, we report that Mpst deletion results in fat accumulation in mice fed a high-fat diet (HFD) through transcriptional and metabolic maladaptation. Mpst-deficient mice on HFD exhibit increased body weight and inguinal WAT mass, reduced metabolic rate, and impaired glucose/insulin tolerance. At the molecular level, Mpst ablation activates HIF1α, downregulates subunits of the translocase of outer/inner membrane (TIM/TOM) complex, and impairs mitochondrial protein import. MPST deficiency suppresses the TCA cycle, oxidative phosphorylation, and fatty acid oxidation, enhancing lipid accumulation. Sulfide donor administration to obese mice reverses the HFD-induced changes. These findings reveal the significance of MPST for white adipose tissue biology and metabolic health and identify a potential new therapeutic target for obesity.

Visceral adipose tissue phenotype and hypoadiponectinemia are associated with aortic Fluorine-18 fluorodeoxyglucose uptake in patients with familial dyslipidemias

BACKGROUND

The role of adipose tissue (AT) in arterial inflammation in familial dyslipidaemias is poorly studied. We investigated the relationship between AT and arterial inflammation in patients with heterozygous familial hypercholesterolemia (heFH) and familial combined hyperlipidemia (FCH).

METHODS AND RESULTS

A total of 40 patients (20 heFH/20 FCH) and a subgroup of 20 of non-heFH/FCH patients were enrolled. Participants underwent blood sampling for serum adipokine measurements and Fluorine-18 fluorodeoxyglucose (18F-FDG) PET/CT imaging. Abdominal visceral (VAT) and subcutaneous (SAT) AT volumes and AT and abdominal aorta 18F-FDG uptake were quantified. FCH patients had increased VAT (pANOVA = 0.004) and SAT volumes (pANOVA = 0.003), lower VAT metabolic activity (pANOVA = 0.0047), and lower adiponectin levels (pANOVA = 0.007) compared to heFH or the control group. Log(Serum adiponectin) levels were correlated with aortic TBR (b = - 0.118, P = 0.038). In mediation analysis, VAT volume was the major determinant of circulating adiponectin, an effect partly mediated via VAT TBR. Clustering of the population of heFH/FCH by VAT volume/TBR and serum adiponectin identified two distinct patient clusters with significant differences in aortic TBR levels (2.11 ± 0.06 vs 1.89 ± 0.05, P= 0.012).

CONCLUSIONS

VAT phenotype (increased VAT volume and/or high VAT TBR) and hypoadiponectinemia may account for the observed differences in arterial inflammation levels between heFH and FCH patients.

Graft flow assessment and early coronary artery bypass graft failure: a computed tomography analysis

OBJECTIVES

We evaluated graft patency by computed tomography and explored the determinants of intraoperative mean graft flow (MGF) and its contribution to predict early graft occlusion.

METHODS

One hundred and forty-eight patients under a single surgeon were prospectively enrolled. Arterial and endoscopically harvested venous conduits were used. Intraoperative graft characteristics and flows were collected. Graft patency was blindly evaluated by a follow-up computed tomography at 11.4 weeks (median).

RESULTS

Graft occlusion rate was 5.2% (n = 22 of 422; 8% venous and 3% arterial). Thirteen were performed on non-significant proximal stenosis while 9 on occluded or >70% stenosed arteries. Arterial and venous graft MGF were lower in females (Parterial = 0.010, Pvenous = 0.009), with median differences of 10 and 13.5 ml/min, respectively. Arterial and venous MGF were associated positively with target vessel diameter ≥1.75 mm (Parterial = 0.025; Pvenous = 0.002) and negatively with pulsatility index (Parterial < 0.001; Pvenous < 0.001). MGF was an independent predictor of graft occlusion, adjusting for EuroSCORE-II, pulsatility index, graft size and graft type (arterial/venous). An MGF cut-off of 26.5 ml/min for arterial (sensitivity 83.3%, specificity 80%) and 36.5 ml/min for venous grafts (sensitivity 75%, specificity 62%) performed well in predicting early graft occlusion.

CONCLUSIONS

We demonstrate that MGF absolute values are influenced by coronary size, gender and graft type. Intraoperative MGF of >26.5 ml/min for arterial and >36.5 ml/min for venous grafts is the most reliable independent predictor of early graft patency. Modern-era coronary artery bypass graft is associated with low early graft failure rates when transit time flow measurement is used to provide effective intraoperative quality assurance.

Cardiovascular risk stratification by coronary computed tomography angiography imaging: current state-of-the-art

Current cardiovascular risk stratification by use of clinical risk score systems or plasma biomarkers is good but less than satisfactory in identifying patients at residual risk for coronary events. Recent clinical evidence puts now further emphasis on the role of coronary anatomy assessment by coronary computed tomography angiography (CCTA) for the management of patients with stable ischaemic heart disease. Available computed tomography (CT) technology allows the quantification of plaque burden, identification of high-risk plaques, or the functional assessment of coronary lesions for ischaemia detection and revascularization for refractory angina symptoms. The current CT armamentum is also further enhanced by perivascular Fat Attenuation Index (FAI), a non-invasive metric of coronary inflammation, which allows for the first time the direct quantification of the residual vascular inflammatory burden. Machine learning and radiomic features' extraction and spectral CT for tissue characterization are also expected to maximize the diagnostic and prognostic yield of CCTA. The combination of anatomical, functional, and biological information on coronary circulation by CCTA offers a unique toolkit for the risk stratification of patients, and patient selection for targeted aggressive prevention strategies. We hereby provide a review of the current state-of-the art in the field and discuss how integrating the full capacities of CCTA into clinical care pathways opens new opportunities for the tailored management of coronary artery disease.

Biomarkers of Vascular Inflammation for Cardiovascular Risk Prognostication: A Meta-Analysis

OBJECTIVES

The purpose of this study was to systematically explore the added value of biomarkers of vascular inflammation for cardiovascular prognostication on top of clinical risk factors.

BACKGROUND

Measurement of biomarkers of vascular inflammation is advocated for the risk stratification for coronary heart disease (CHD).

METHODS

We systematically explored published reports in MEDLINE for cohort studies on the prognostic value of common biomarkers of vascular inflammation in stable patients without known CHD. These included common circulating inflammatory biomarkers (ie, C-reactive protein, interleukin-6 and tumor necrosis factor-a, arterial positron emission tomography/computed tomography and coronary computed tomography angiography-derived biomarkers of vascular inflammation, including anatomical high-risk plaque features and perivascular fat imaging. The main endpoint was the difference in c-index (Δ[c-index]) with the use of inflammatory biomarkers for major adverse cardiovascular events (MACEs) and mortality. We calculated I2 to test heterogeneity. This study is registered with PROSPERO (CRD42020181158).

RESULTS

A total of 104,826 relevant studies were screened and a final of 39 independent studies (175,778 individuals) were included in the quantitative synthesis. Biomarkers of vascular inflammation provided added prognostic value for the composite endpoint and for MACEs only (pooled estimate for Δ[c-index]% 2.9, 95% CI: 1.7-4.1 and 3.1, 95% CI: 1.8-4.5, respectively). Coronary computed tomography angiography-related biomarkers were associated with the highest added prognostic value for MACEs: high-risk plaques 5.8%, 95% CI: 0.6 to 11.0, and perivascular adipose tissue (on top of coronary atherosclerosis extent and high-risk plaques): 8.2%, 95% CI: 4.0 to 12.5). In meta-regression analysis, the prognostic value of inflammatory biomarkers was independent of other confounders including study size, length of follow-up, population event incidence, the performance of the baseline model, and the level of statistical adjustment. Limitations in the published literature include the lack of reporting of other metrics of improvement of risk stratification, the net clinical benefit, or the cost-effectiveness of such biomarkers in clinical practice.

CONCLUSIONS

The use of biomarkers of vascular inflammation enhances risk discrimination for cardiovascular events.

Effects of canagliflozin on human myocardial redox signalling: clinical implications

AIMS

Recent clinical trials indicate that sodium-glucose cotransporter 2 (SGLT2) inhibitors improve cardiovascular outcomes in heart failure patients, but the underlying mechanisms remain unknown. We explored the direct effects of canagliflozin, an SGLT2 inhibitor with mild SGLT1 inhibitory effects, on myocardial redox signalling in humans.

METHODS AND RESULTS

Study 1 included 364 patients undergoing cardiac surgery. Right atrial appendage biopsies were harvested to quantify superoxide (O2.-) sources and the expression of inflammation, fibrosis, and myocardial stretch genes. In Study 2, atrial tissue from 51 patients was used ex vivo to study the direct effects of canagliflozin on NADPH oxidase activity and nitric oxide synthase (NOS) uncoupling. Differentiated H9C2 and primary human cardiomyocytes (hCM) were used to further characterize the underlying mechanisms (Study 3). SGLT1 was abundantly expressed in human atrial tissue and hCM, contrary to SGLT2. Myocardial SGLT1 expression was positively associated with O2.- production and pro-fibrotic, pro-inflammatory, and wall stretch gene expression. Canagliflozin reduced NADPH oxidase activity via AMP kinase (AMPK)/Rac1signalling and improved NOS coupling via increased tetrahydrobiopterin bioavailability ex vivo and in vitro. These were attenuated by knocking down SGLT1 in hCM. Canagliflozin had striking ex vivo transcriptomic effects on myocardial redox signalling, suppressing apoptotic and inflammatory pathways in hCM.

CONCLUSIONS

We demonstrate for the first time that canagliflozin suppresses myocardial NADPH oxidase activity and improves NOS coupling via SGLT1/AMPK/Rac1 signalling, leading to global anti-inflammatory and anti-apoptotic effects in the human myocardium. These findings reveal a novel mechanism contributing to the beneficial cardiac effects of canagliflozin.

Standardized measurement of coronary inflammation using cardiovascular computed tomography: integration in clinical care as a prognostic medical device

AIMS

Coronary computed tomography angiography (CCTA) is a first-line modality in the investigation of suspected coronary artery disease (CAD). Mapping of perivascular fat attenuation index (FAI) on routine CCTA enables the non-invasive detection of coronary artery inflammation by quantifying spatial changes in perivascular fat composition. We now report the performance of a new medical device, CaRi-Heart®, which integrates standardized FAI mapping together with clinical risk factors and plaque metrics to provide individualized cardiovascular risk prediction.

METHODS AND RESULTS

The study included 3912 consecutive patients undergoing CCTA as part of clinical care in the USA (n = 2040) and Europe (n = 1872). These cohorts were used to generate age-specific nomograms and percentile curves as reference maps for the standardized interpretation of FAI. The first output of CaRi-Heart® is the FAI-Score of each coronary artery, which provides a measure of coronary inflammation adjusted for technical, biological, and anatomical characteristics. FAI-Score is then incorporated into a risk prediction algorithm together with clinical risk factors and CCTA-derived coronary plaque metrics to generate the CaRi-Heart® Risk that predicts the likelihood of a fatal cardiac event at 8 years. CaRi-Heart® Risk was trained in the US population and its performance was validated externally in the European population. It improved risk discrimination over a clinical risk factor-based model [Δ(C-statistic) of 0.085, P = 0.01 in the US Cohort and 0.149, P < 0.001 in the European cohort] and had a consistent net clinical benefit on decision curve analysis above a baseline traditional risk factor-based model across the spectrum of cardiac risk.

CONCLUSION

Mapping of perivascular FAI on CCTA enables the non-invasive detection of coronary artery inflammation by quantifying spatial changes in perivascular fat composition. We now report the performance of a new medical device, CaRi-Heart®, which allows standardized measurement of coronary inflammation by calculating the FAI-Score of each coronary artery. The CaRi-Heart® device provides a reliable prediction of the patient's absolute risk for a fatal cardiac event by incorporating traditional cardiovascular risk factors along with comprehensive CCTA coronary plaque and perivascular adipose tissue phenotyping. This integration advances the prognostic utility of CCTA for individual patients and paves the way for its use as a dual diagnostic and prognostic tool among patients referred for CCTA.

CT coronary angiography-guided cardiovascular risk screening in asymptomatic patients: is it time?

Cardiovascular disease (CVD) is the leading cause of death in the UK, whilst millions live with various forms of the disease. Coronary artery disease constitutes a significant portion of this morbidity and mortality, and is the leading cause of premature death. Increasing focus is thus being placed on the optimisation of CVD prevention, where risk screening plays a key role. Indeed, the decline in age-adjusted cardiovascular mortality achieved up to now has been largely attributed to primary preventative therapies (e.g., statins) introduced earlier in the disease process. National initiatives exist to improve cardiovascular health at a population level, but in its current form, CVD screening at the individual level is predominantly undertaken using multivariate risk scores based on population-based data. These have multiple innate flaws, highlighted in this review. Non-invasive imaging plays a key role in the screening of other disease processes, helping to personalise the screening process. Although the coronary artery calcium score as a screening tool has a role in national and international guidance, whether a shift to screening with computed tomography coronary angiography (CTCA) is now appropriate is open for discussion. Image acquisition techniques continue to improve with reducing radiation exposure and an ever-expanding evidence-base for additional prognostic data offered by CTCA. This enables the potential identification of sub-clinical atherosclerosis, including with novel artificial intelligence techniques. This review aims to report current guidelines regarding cardiac CT imaging in the asymptomatic primary prevention setting, advances in various CT technologies and future opportunities for progress in this field.

Perivascular fat imaging by computed tomography (CT): a virtual guide

Imaging in medicine has been revolutionised by technological, computational and research advances over the past decades. Computed tomography (CT), in particular, has seen rapid evolution especially in the field of cardiovascular non-invasive imaging. It is being recognised as the first-line tool for the assessment of stable and unstable disease with diagnostic, prognostic and re-stratification potential. Vascular inflammation is a key component of the atherosclerotic process and has been shown to induce molecular, transcriptional and structural changes to perivascular adipose tissue (PVAT). Being a diverse structure itself, PVAT surrounds the human vessels and is characterised by a highly rich secretome, including, amongst others, adipokines, cytokines, gaseous messengers and miRNAs It is implicated in a bidirectional interplay with the adjacent vascular wall, affecting and being affected by aspects of its biology, mainly inflammation. In this review, we discuss the current status of cardiac CT in imaging vascular inflammation through PVAT phenotyping. LINKED ARTICLES: This article is part of a themed issue on Molecular imaging - visual themed issue. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v178.21/issuetoc.

Automated quantification of epicardial adipose tissue on CCTA via deep-learning detection of the pericardium: clinical implications

Background

Epicardial adipose tissue (EAT) is a visceral fat deposit within the pericardial sac which surrounds the heart myocardium and coronary arteries. EAT volume has been demonstrated to be strongly associated with the development and prognosis of cardiovascular diseases, but its measurement is subjective and challenging in practice.

Purpose

To develop a deep-learning approach for automated segmentation of EAT from routine CCTA scans, that could assist clinical interpretation of CCTA.

Methods

A deep-learning method using a 3D Residual-U-Net neural network architecture for 3D volumetric segmentation of CCTA data was created. The network was trained on a diverse sample of 1900 CCTAs, each manually segmented by a single expert, drawn from the UK sites of the Oxford Risk Factors And Non-invasive imaging (ORFAN) Study. Three iterations of feedback learning were used to fine tune the algorithm for the segmentation of the whole heart within the bounds of the pericardium. In each iteration, the machine analysed sets of 100–250 unannotated CCTAs unseen by the machine which were then corrected by experts. EAT volumes were calculated by automated thresholding of adipose tissue (−190HU through −30HU) from within the bound of the pericardial segment (Figure 1). The network was then applied to 817 unseen CCTAs from US sites of the ORFAN Study. These scans were also segmented for ground truth by two experts blind to all other data. Comparisons between machine vs expert total pericardial volume and EAT volume were made using Lin's concordance correlation coefficient (CCC). The algorithm was then applied externally in 1588 CCTAs from the SCOTHEART trial (UK), and the EAT volume was automatically calculated for each case. Cross-sectional associations between standardised EAT volumes and prevalent AF and CAD were performed.

Results

Within both the internal (UK ORFAN sites) and external (USA ORFAN sites) validation cohorts correlation between human and machine segmented total pericardium and EAT was excellent, with CCC of 0.97 for both volumes (external validation cohort shown in Figure 2A). Utilising SCOTHEART CCTAs with automatically segmented EAT volumes, a multivariable-adjusted logistic regression model accounting for risk factors of age, sex, BMI, hypertension, diabetes mellitus, valvular disease, and previous heart surgery found that EAT volumes were significantly associated with prevalent AF, with odds ratio (OR) per 1 SD increase of EAT volume of 1.20 (95% CI, 1.06 to 1.44; P=0.03). A similar model for prevalent CAD, adjusted for age, sex, BMI, hypertension, non-HDL cholesterol, diabetes mellitus, and coronary artery calcium score resulted in an OR per 1 SD increase of EAT volume of 1.26 (95% CI, 1.10 to 1.45; P=0.001) (Figure 2B).

Conclusion

Highly accurate, reproducible, and instantaneous EAT volume quantification is possible utilising deep-learning detection of the whole human heart within the pericardial sac.

Funding Acknowledgement

Type of funding sources: Public Institution(s). Main funding source(s): British Heart FoundationNational Institute for Health Research - Oxford University Hospitals Biomedical Research Centre Figure 1Figure 2

A human arterial transcriptomic signature predicts major adverse cardiac events and identifies novel, redox-related therapeutic targets within the vascular wall

Background

The transcriptomic profile of the human vascular wall is implicated in a range of pathologies. RNA sequencing technologies allow for interrogation of gene expression patterns that are associated with clinical outcomes and can guide future research and drug development.

Purpose

To apply discovery network transcriptomics to internal mammary arteries (IMAs) obtained from patients undergoing cardiac surgery, in order to identify redox-related molecular pathways within the vascular wall that can be treated therapeutically.

Methods

Arm 1 included 377 patients in whom segments of IMA were used for ex-vivo quantification of NADPH-stimulated superoxide production by lucigenin-enhanced chemiluminescence. Arm 2 included 205 patients in whom bulk RNA sequencing was performed in RNA isolated from IMA, and the WGCNA package used for the analyses. The association with future incidence of major adverse cardiac events (MACE: cardiovascular death, non-fatal myocardial infarction, and stroke) was assessed using Cox regression models (adjusted for age, sex, hypertension, dyslipidaemia, diabetes mellitus, body mass index, smoking, and plasma TNFa).

Results

Over a median follow-up of 4.84 years [IQR: 2.03–7.14], 38 (11.2%) MACE occurred in Arm 1. High arterial NADPH-stimulated superoxide was independently associated with MACE risk (Adj. HR [95% CI]: 2.62 [1.13–6.07] high group, p=0.02). Unsupervised transcriptomic analysis in Arm 2 allowed identification of 10 coexpressed gene “modules”. Eigengenes summarising modular coexpression signatures were then correlated with NADPH-stimulated superoxide revealing the red module (a) as the most significant (rho=0.19, p=0.01). In survival analysis the red module showed significant correlation with MACE (Adj. HR [95% CI]: 1.40 [1.00–1.95] per SD, p=0.04). For an optimal cut-off, patients with high eigengene values for the red module showed a 4-fold higher risk of MACE (b), and significantly higher arterial oxidative stress (c). Enrichment analysis (performed with Enrichr) of genes in the red module revealed “Electron Transport Chain”, “Oxidative phosphorylation”, “Striated Muscle Contraction Pathway”, and “Glycolysis and Gluconeogenesis” amongst the top enriched pathways (d).

Conclusion

We present for the first time a novel human arterial transcriptomic signature reflecting changes in redox state, which identifies long-term cardiovascular risk. Targeting pathways in the vasculature related with the mitochondrial electron transport chain, the contractile mechanism, or glucose metabolism may lead to the development of novel therapeutics in cardiovascular disease.

Funding Acknowledgement

Type of funding sources: Foundation. Main funding source(s): EPSRC-EP/N509711/1-2119518British Heart Foundation Figure 1

Artificial intelligence in medical imaging: A radiomic guide to precision phenotyping of cardiovascular disease

ABSTRACT

Rapid technological advances in non-invasive imaging, coupled with the availability of large data sets and the expansion of computational models and power, have revolutionized the role of imaging in medicine. Non-invasive imaging is the pillar of modern cardiovascular diagnostics, with modalities such as cardiac computed tomography (CT) now recognized as first-line options for cardiovascular risk stratification and the assessment of stable or even unstable patients. To date, cardiovascular imaging has lagged behind other fields, such as oncology, in the clinical translational of artificial intelligence (AI)-based approaches. We hereby review the current status of AI in non-invasive cardiovascular imaging, using cardiac CT as a running example of how novel machine learning (ML)-based radiomic approaches can improve clinical care. The integration of ML, deep learning, and radiomic methods has revealed direct links between tissue imaging phenotyping and tissue biology, with important clinical implications. More specifically, we discuss the current evidence, strengths, limitations, and future directions for AI in cardiac imaging and CT, as well as lessons that can be learned from other areas. Finally, we propose a scientific framework in order to ensure the clinical and scientific validity of future studies in this novel, yet highly promising field. Still in its infancy, AI-based cardiovascular imaging has a lot to offer to both the patients and their doctors as it catalyzes the transition towards a more precise phenotyping of cardiovascular disease.