Carotid Plaque Research Articles

Plasma proteins associate with carotid plaques and predict incident atherosclerotic cardiovascular events

PurposePerforming non-invasive carotid imaging is challenging, owing inter-operator variability and organizational barriers, but plasma proteomics can offer an alternative. We sought plasma proteins that associate with the presence of carotid plaques, their number and predict the incidence of clinically overt atherosclerotic cardiovascular events (ASCVD) above currently recognized risk factors in “apparently healthy” subjects. MethodsWe studied the plasma levels of 368 proteins in 664 subjects from the PLIC study, who underwent an ultrasound imaging screening of the carotids to check for the presence of plaques. We clustered, by artificial intelligence (A.I.), the proteins that associate with the presence, the number of plaques and that predict incident ASCVDs over 22 years (198 events were registered). Findings299/664 subjects had at least 1 carotid plaque (1+) (77 with only one plaque, 101 with 2 plaques, 121 with ≥3 plaques (3+)). The remaining 365 subjects with no plaques acted as controls. 106 proteins were associated with 1+ plaques, but 97 proteins significantly predicted 3+ plaques only (AUC = 0.683 (0.601–0.785), p < 0.001), when considered alone.A.I. underscored 87 proteins that improved the performance of the classical risk factors both in detecting 3+ plaques (AUC = 0.918 (0.887–0.943) versus risk factors alone, AUC = 0.760 (0.716–0.801), p < 0.001) and in predicting the incident ASCVD (AUC = 0.739 (0.704–0.773) vs risk factors alone AUC = 0.559 (0.521–0.598), p < 0.001). The chemotaxis/migration of leukocytes and interleukins/cytokines signaling were biological pathways mostly represented by these proteins. Discussion and conclusionsPlasma proteomics marks the number of carotid plaques and improve the prediction of incidence ASCVDs in apparently healthy subjects.

Domain Discrimination Expert Weighted Network for Multi-Source Carotid Artery Plaque Classification

The rupture of unstable plaques is a major cause of acute cardiovascular events. The early assessment of carotid plaques can significantly reduce the cardiovascular risks, so developing evaluation models suitable for data from different centers is of great clinical importance. This study leverages plaque datasets from multiple centers to develop a Weighted multi-source carotid artery plaque Unsupervised Classification Framework (WUCF). The multi-source domain adaptation module of the WUCF focuses on maintaining feature consistency between each independent source and target center, while also integrating a specialized domain discriminator expert. This ensures that the knowledge from each source center is effectively learned and combined for accurate predictions in the target domain. The experimental evaluation of WUCF, using datasets from three centers, has demonstrated the method’s superiority and robustness.

Serum Uric Acid, Hypertriglyceridemia, and Carotid Plaques: A Sub-Analysis of the URic Acid Right for Heart Health (URRAH) Study.

High levels of serum uric acid (SUA) and triglycerides (TG) might promote high-cardiovascular-risk phenotypes, including subclinical atherosclerosis. An interaction between plaques xanthine oxidase (XO) expression, SUA, and HDL-C has been recently postulated. Subjects from the URic acid Right for heArt Health (URRAH) study with carotid ultrasound and without previous cardiovascular diseases (CVD) (n = 6209), followed over 20 years, were included in the analysis. Hypertriglyceridemia (hTG) was defined as TG ≥ 150 mg/dL. Higher levels of SUA (hSUA) were defined as ≥5.6 mg/dL in men and 5.1 mg/dL in women. A carotid plaque was identified in 1742 subjects (28%). SUA and TG predicted carotid plaque (HR 1.09 [1.04-1.27], p < 0.001 and HR 1.25 [1.09-1.45], p < 0.001) in the whole population, independently of age, sex, diabetes, systolic blood pressure, HDL and LDL cholesterol and treatment. Four different groups were identified (normal SUA and TG, hSUA and normal TG, normal SUA and hTG, hSUA and hTG). The prevalence of plaque was progressively greater in subjects with normal SUA and TG (23%), hSUA and normal TG (31%), normal SUA and hTG (34%), and hSUA and hTG (38%) (Chi-square, 0.0001). Logistic regression analysis showed that hSUA and normal TG [HR 1.159 (1.002 to 1.341); p = 0.001], normal SUA and hTG [HR 1.305 (1.057 to 1.611); p = 0.001], and the combination of hUA and hTG [HR 1.539 (1.274 to 1.859); p = 0.001] were associated with a higher risk of plaque. Our findings demonstrate that SUA is independently associated with the presence of carotid plaque and suggest that the combination of hyperuricemia and hypertriglyceridemia is a stronger determinant of carotid plaque than hSUA or hTG taken as single risk factors. The association between SUA and CVD events may be explained in part by a direct association of UA with carotid plaques.

Machine learning methods for adult OSAHS risk prediction

BackgroundObstructive sleep apnea hypopnea syndrome (OSAHS) is a common disease that can cause multiple organ damage in the whole body. Our aim was to use machine learning (ML) to build an independent polysomnography (PSG) model to analyze risk factors and predict OSAHS.Materials and methodsClinical data of 2064 snoring patients who underwent physical examination in the Health Management Center of the First Affiliated Hospital of Shanxi Medical University from July 2018 to July 2023 were retrospectively collected, involving 24 characteristic variables. Then they were randomly divided into training group and verification group according to the ratio of 7:3. By analyzing the importance of these features, it was concluded that LDL-C, Cr, common carotid artery plaque, A1c and BMI made major contributions to OSAHS. Moreover, five kinds of machine learning algorithm models such as logistic regression, support vector machine, Boosting, Random Forest and MLP were further established, and cross validation was used to adjust the model hyperparameters to determine the final prediction model. We compared the accuracy, Precision, Recall rate, F1-score and AUC indexes of the model, and finally obtained that MLP was the optimal model with an accuracy of 85.80%, Precision of 0.89, Recall of 0.75, F1-score of 0.82, and AUC of 0.938.ConclusionWe established the risk prediction model of OSAHS using ML method, and proved that the MLP model performed best among the five ML models. This predictive model helps to identify patients with OSAHS and provide early, personalized diagnosis and treatment options.

The association of carotid plaque burden and composition and the coronary artery calcium score in intermediate cardiovascular risk patients.

Both the carotid ultrasound and coronary artery calcium (CAC) score quantify subclinical atherosclerosis and are associated with cardiovascular disease and events. This study investigated the association between CAC score and carotid plaque quantity and composition. Adult participants (n = 43) without history of cardiovascular disease were recruited to undergo a carotid ultrasound. Maximum plaque height (MPH), total plaque area (TPA), carotid intima-media thickness (CIMT), and plaque score were measured. Grayscale pixel distribution analysis of ultrasound images determined plaque tissue composition. Participants then underwent CT to determine CAC score, which were also categorized as absent (0), mild (1-99), moderate (100-399), and severe (400+). Spearman correlation coefficients between carotid variables and CAC scores were computed. The mean age of participants was 63 ± 11 years. CIMT, TPA, MPH, and plaque score were significantly associated with CAC score (ρ = 0.60, p < 0.0001; ρ = 0.54, p = 0.0002; ρ = 0.38, p = 0.01; and ρ = 0.49, p = 0.001). Echogenic composition features %Calcium and %Fibrous tissue were not correlated to a clinically relevant extent. There was a significant difference in the TPA, MPH, and plaque scores of those with a severe CAC score category compared to lesser categories. While carotid plaque burden was associated with CAC score, plaque composition was not. Though CAC score reliably measures calcification, carotid ultrasound gives information on both plaque burden and composition. Carotid ultrasound with assessment of plaque features used in conjunction with traditional risk factors may be an alternative or additive to CAC scoring and could improve the prediction of cardiovascular events in the intermediate risk population.

Exploring auditory temporal resolution and dichotic listening skills among individuals with type 2 diabetes mellitus

The study aimed to explore the auditory temporal resolution and dichotic listening skills in patients with type 2 diabetes mellitus (T2DM) and identify associated health-related factors. Using a cross-sectional design, 87 adults with T2DM and 48 non-diabetic controls, all with normal hearing, participated. The two central auditory processing (CAP) skills were assessed through the Gaps-In-Noise (GIN) and Dichotic-Digits Listening (DDL) tests. T2DM participants underwent blood tests to measure various health-related factors. In the GIN test, the shortest gap threshold (GapTh) obtained across both ears was significantly higher in the diabetic group (9.1 ± 2.4 ms) compared to the non-diabetic group (7.5 ± 1.5 ms), and the score of correctly identified gaps (GapSc) in the diabetic group (45±11 %) was significantly lower than GapSc in the non-diabetic group (52±9 %), p < 0.001. In the DDL test, the free-recall score (73.8 ± 18.5 %) across both ears and the right-ear advantage (-1.3 ± 20.6 %) in the diabetic group were significantly lower than the free-recall score (85.8 ± 11.9 %) and right-ear advantage (6.9 ± 11.9 %) in the non-diabetic group, p < 0.005. Furthermore, the duration of diabetes, eGFR level, retinopathy, carotid plaque, fasting blood glucose level, and HDL-C (good cholesterol) level were factors significantly associated with performances in the GIN and/or DDL tests for T2DM participants. In conclusion, individuals with T2DM are at risk of reduced auditory processing skills in temporal resolution and dichotic listening, impacting their speech understanding. Six health-related factors were identified as significantly associated with CAP skills in T2DM patients.

Atherosclerotic carotid artery disease Radiomics: A systematic review with meta-analysis and radiomic quality score assessment

BackgroundStroke, a leading global cause of mortality and neurological disability, is often associated with atherosclerotic carotid artery disease. Distinguishing between symptomatic and asymptomatic carotid artery disease is crucial for appropriate treatment decisions. Radiomics, a quantitative image analysis technique, and ML have emerged as promising tools in medical imaging, including neuroradiology. This systematic review and meta-analysis aimed to evaluate the methodological quality of studies employing radiomics for atherosclerotic carotid artery disease analysis and ML algorithms for culprit plaque identification using CT or MRI. Materials and methodsPubmed, WoS and Scopus databases were searched for relevant studies published from January 2005 to May 2023. RQS assessed methodological quality of studies included in the review. QUADAS-2 assessed the risk of bias. A meta-analysis and three meta regressions were conducted on study performance based on model type, imaging modality and segmentation method. ResultsRQS assessed methodological quality, revealing an overall low score and consistent findings with other radiology domains. QUADAS-2 indicated an overall low risk, except for a single study with high bias. The meta-analysis demonstrated that radiomics-based ML models for predicting culprit plaques had a satisfactory performance, with an AUC of 0.85, surpassing clinical models. However, combining radiomics with clinical features yielded the highest AUC of 0.89. Meta-regression analyses confirmed these findings. MRI-based models slightly outperformed CT-based ones, but the difference was not significant. ConclusionIn conclusion, radiomics and ML hold promise for assessing carotid plaque vulnerability, aiding in early cerebrovascular event prediction. Combining radiomics with clinical data enhances predictive performance.

Association of the High-Sensitivity C-Reactive Protein-to-Albumin Ratio with Carotid Atherosclerotic Plaque: A Community-Based Cohort Study.

The inflammatory response is a pivotal factor in accelerating the progression of atherosclerosis. The high-sensitivity C-reactive protein-to-albumin ratio (CAR) has emerged as a novel marker of systemic inflammation. However, few studies have shown the CAR to be a promising prognostic marker for carotid atherosclerotic disease. This study aimed to analyse the predictive role of the CAR in carotid atherosclerotic disease. This community-based cohort study recruited 2003 participants from the Rose asymptomatic IntraCranial Artery Stenosis (RICAS) study who were free of stroke or transient ischemic attack. Carotid atherosclerotic plaques and their stability were identified via carotid ultrasound. Logistic regression models were utilized to investigate the association between CAR and the presence of carotid atherosclerotic plaques. The prevalence of carotid atherosclerotic plaques was 38.79% in this study. After adjusting for clinical risk factors, including sex, age, dyslipidemia, hypertension, diabetes mellitus (DM), and smoking and drinking habits, a high CAR-level was independently associated with carotid plaque (odds ratio [OR] of upper: 1.46, 95% confidence interval [CI]: 1.13-1.90, P = 0.004; P for trend = 0.011). The highest CAR tertile was still significantly associated with carotid plaques among middle-aged (40-64 years) or female participants. Notably, an elevated CAR may be an independent risk factor for vulnerable carotid plaques (OR of upper: 2.06, 95% CI: 1.42-2.98, P < 0.001; P for trend <0.001). A high CAR may be correlated with a high risk of carotid plaques, particularly among mildly aged adults (40-64 years) or females. Importantly, the CAR may be associated with vulnerable carotid plaques, suggesting that the CAR may be a new indicator for stroke prevention.

Effect of evolocumab on carotid plaque composition in asymptomatic carotid artery stenosis (EVOCAR-1) using magnetic resonance imaging

Background and AimsTo determine the effect of evolocumab treatment in patients with asymptomatic carotid artery stenosis ≥50 % on carotid plaque morphology and composition, as determined by magnetic resonance imaging. MethodsWe conducted a double-blind randomized controlled trial in patients with asymptomatic carotid artery plaque with ≥50 % stenosis and low-density lipoprotein-associated cholesterol (LDL-C) ≥1.8 mmol/L, despite standard lipid-lowering therapy, with 12 months of evolocumab or placebo injection every two weeks. The primary endpoint was the between group difference in the absolute change from baseline in carotid plaque lipid-rich necrotic core (LRNC), assessed by carotid magnetic resonance. ResultsDue to interrupted recruitment during the COVID-19 pandemic, 33 patients (36 % female) were randomised, which was less than the target of 52. Mean age was 68.7 years (SD, 8.5) and baseline LDL-C 2.4 mmol/L(SD, 0.7). LDL-C was reduced with evolocumab to 0.8 mmol/L (SD, 0.5) vs 2.2 mmol/L (SD, 0.7) with placebo at 3 months (between group absolute difference -1.3 mmol/L [95 % CI, -1.7 to -0.9], p < 0.001). Evolocumab treatment was associated with a favourable change in LRNC at 12 months of -16 mm3 (SD, 54) whereas the placebo group showed -4 mm3 (SD, 44). Between group differences did not show statistically significance with a placebo-adjusted LRNC change of -17 mm3 ([95 % CI, -45 to 12], p = 0.25). Percentage carotid plaque LRNC also numerically reduced at 12 months, however this did not reach statistical significance (-2.4 % vessel wall volume [95 % CI, -5.7 to 0.9], p = 0.16). ConclusionIntensive LDL-C lowering with the addition of evolocumab to maximally tolerated lipid-lowering therapy did not lead to a statistically significant change in vulnerable plaque phenotype characteristics in patients with asymptomatic carotid artery stenosis, but the study was underpowered due to under-recruitment in the context of the COVID-19 pandemic.

Predicting vulnerable carotid plaques by detecting wall shear stress based on ultrasonic vector flow imaging

ObjectiveCarotid plaque vulnerability is a significant factor in the risk of cardiocerebrovascular events, with intraplaque neovascularization (IPN) being a crucial characteristic of plaque vulnerability. This study investigates the value of ultrasound vector flow imaging (V-flow) for measuring carotid plaque wall shear stress (WSS) in predicting the extent of IPN. MethodsWe enrolled 140 patients into three groups: 53 in the plaque group (72 plaques), 23 in the stenosis group (27 plaques), and 64 in the control group. V-flow was used to measure WSS parameters, including the average WSS (WSS mean) and the maximum WSS (WSS max), across three plaque locations: mid-upstream, maximum thickness, and mid-downstream. Contrast-enhanced ultrasound examination was used in 76 patients to analyze IPN and its correlation with WSS parameters. ResultsWSS max in the stenosis group was significantly higher than that in the control and plaque groups at the maximum thickness part (P < .05) and WSS mean in the stenosis group was significantly lower than that in the control group at the mid-upstream and mid-downstream segments (P < .05). WSS mean in the plaque group was significantly lower than that of the control group at all three locations (P < .05). Contrast-enhanced ultrasound examination revealed that plaques with neovascularization enhancement exhibited significantly higher WSS values (P < .05), with a positive correlation between WSS parameters and IPN enhancement grades, particularly WSS max at the thickest part (r = 0.508). Receiver operating characteristic curve analysis of WSS parameters for evaluating IPN showed that the efficacy of WSS max in evaluating IPN was better than that of WSS mean (P < .05), with an area under the curve of 0.7762 and 0.6973 (95% confidence intervals, 0.725-0.822 and 0.642-0.749, respectively). The cut-offs were 4.57 Pa and 1.12 Pa, sensitivities were 74.03% and 63.64%, and specificities were 75.00% and 68.18%. ConclusionsV-flow effectively measures WSS in carotid plaques. WSS max provides a promising metric for assessing IPN, offering potential insights into plaque characteristics and showing some potential in predicting plaque vulnerability.

Carotid intima-media thickness progression and plaque formation in recreational male endurance athletes - a 10-year follow-up study

Carotid intima-media thickness progression and plaque formation in recreational male endurance athletes - a 10-year follow-up study

A Multi-Dimensional Aggregation Network Guided by Key Features for Plaque Echo Classification Based on Carotid Ultrasound Video

ObjectiveUnstable plaques can cause acute cardiovascular and cerebrovascular diseases. The stability and instability of plaque are related to the plaque echo status in ultrasound. Carotid videos provide detailed plaque information compared to static images. Ultrasound-based plaque echo classification is challenging due to noise, interference frames, small targets (plaques), and complex shape changes. MethodsThis study proposes a Multi-dimensional Aggregation Network (MA-Net) guided by key features for plaque diagnosis based on carotid ultrasound video, which uses only video-level labels. MA-Net consists of Key-Feature (KF) and Temporal-Channel-Spatial (TCS) modules. The KF module learns the contribution of each frame to the classification at the feature level, adaptively infers the importance score of each frame, thereby reducing the influence of interference frames. The TCS module includes the Temporal-Channel (TC) and Temporal-Spatial (TS) sub-modules. In addition to studying the temporal dimension, it delves into the relationship between the channel and spatial dimensions. TC analyses the temporal dependencies among the channels and filters noise. Moreover, TS extracts features more accurately through the spatio-temporal information contained in the surrounding environment of the plaque. ResultsThe performance of MA-Net on the SHU-Ultrasound-Video-2020 dataset is better than that of the state-of-the-art models of video classification, showing at least a 5% increase in accuracy, with an accuracy rate of 87.36%. ConclusionThe outstanding diagnostic capability of the proposed model will help provide a more robust and reproducible diagnostic process with a lower labour cost for clinical carotid plaque diagnosis.

Machine Learning Detects Symptomatic Plaques in Patients With Carotid Atherosclerosis on CT Angiography.

This study aimed to develop and validate a computed tomography angiography based machine learning model that uses plaque composition data and degree of carotid stenosis to detect symptomatic carotid plaques in patients with carotid atherosclerosis. The machine learning based model was trained using degree of stenosis and the volumes of 13 computed tomography angiography derived intracarotid plaque subcomponents (eg, lipid, intraplaque hemorrhage, calcium) to identify plaques associated with cerebrovascular events. The model was internally validated through repeated 10-fold cross-validation and tested on a dedicated testing cohort according to discrimination and calibration. This retrospective, single-center study evaluated computed tomography angiography scans of 268 patients with both symptomatic and asymptomatic carotid atherosclerosis (163 for the derivation set and 106 for the testing set) performed between March 2013 and October 2019. The area-under-receiver-operating characteristics curve by machine learning on the testing cohort (0.89) was significantly higher than the areas under the curve of traditional logit analysis based on the degree of stenosis (0.51, P<0.001), presence of intraplaque hemorrhage (0.69, P<0.001), and plaque composition (0.78, P<0.001), respectively. Comparable performance was obtained on internal validation. The identified plaque components and associated cutoff values that were significantly associated with a higher likelihood of symptomatic status after adjustment were the ratio of intraplaque hemorrhage to lipid volume (≥50%, 38.5 [10.1-205.1]; odds ratio, 95% CI) and percentage of intraplaque hemorrhage volume (≥10%, 18.5 [5.7-69.4]; odds ratio, 95% CI). This study presented an interpretable machine learning model that accurately identifies symptomatic carotid plaques using computed tomography angiography derived plaque composition features, aiding clinical decision-making.

MPSA: Multi-Position Supervised Soft Attention-based convolutional neural network for histopathological image classification

In recent years, significant achievements have been made in the field of histopathological image analysis using convolutional neural networks (CNNs). However, existing CNNs fail to fully capture the important local structures and regional information in histopathological images due to the complex tissue structures and variable pathological features present in these images. They often treat all regions equally, which further exacerbates the challenge of accurately analyzing such images. Current network model can’t extract deep layer features efficiently without guiding. To alleviate this problem, we propose a novel network model called Multi-Position Supervised Soft Attention (MPSA). MPSA adds regions of interest (RoI) labels at multiple feature layers for deep supervision, and then uses the supervised layers as soft attention to guide the learning of the classification network, enabling the network to accurately extract features of the lesion target. Additionally, we design a Multi-level Attention Feature Enhancement Module (MAFEM), which combines multiple levels of attention mechanisms to enhance the performance of the convolutional neural network in histopathological image classification. MAFEM includes spatial attention, soft attention of the main branch, and our proposed soft attention for multi-branch feature fusion. The proposed soft attention for multi-branch feature fusion aims to enhance the predictive performance of the classification model by activating relevant neurons in the diagnostic area in a highly activated state, while effectively avoiding noise activation. This innovative approach ensures that the model can focus on the most pertinent information, leading to improved classification accuracy. We conducted classification experiments on the liver cancer histopathological images dataset and the results showed that our method achieved a classification accuracy of 95.79%, indicating that it is very effective in the analysis of liver histopathological images. Our proposed network architecture has also demonstrated good generalization ability in other medical datasets, achieving a classification accuracy of 84.41% on the ultrasound carotid plaque dataset.

Associations of psychological factors with atherosclerosis and cardiovascular health in middle-age: the population-based Swedish CArdioPulmonary bioImage study (SCAPIS)

BackgroundCardiovascular disease (CVD) is a major global health issue, primarily caused by atherosclerosis. Psychological factors may play a role in the development and progression of CVD. However, the relationship between psychological factors and atherosclerosis is complex and poorly understood. This study, therefore, aimed to examine the association of psychological factors with (i) coronary and carotid atherosclerosis and (ii) cardiovascular health according to Life’s Essential 8, in a large Swedish cohort.MethodsThis study utilized data from the Swedish CArdioPulmonary bioImage Study (SCAPIS), a large population-based project including individuals aged 50 to 65 years. Several psychological factors were analysed: general stress, stress at work, financial stress, major adverse life events, locus of control, feeling depressed, and depression. Coronary atherosclerosis was assessed as the degree of stenosis by coronary computed tomography angiography (CCTA) and coronary artery calcification (CAC) scores. Carotid atherosclerosis was examined using ultrasound. In addition, cardiovascular health was examined using the Life’s Essential 8 concept created by the American Heart Association, which includes four health behaviors and four health factors. Associations were examined through binomial logistic regression (atherosclerosis variables) and linear regression (Life’s Essential 8).ResultsA total of 25,658 participants were included in the study. The presence of financial stress, higher locus of control, and depression was weakly associated with increased odds of CCTA stenosis, CAC ≥ 1 and the presence of carotid plaques (all odds ratios: 1.10–1.21, 95% CI: 1.02–1.32) after adjusting for sex, age, and study site. However, these associations were attenuated and not statistically significant after additional adjustments for socioeconomic factors and health behaviors. Conversely, we observed inverse associations between the worst category for all psychological factors and cardiovascular health according to Life’s Essential 8 score (all standardized β-Coefficient ≤-0.033, p < 0.001).ConclusionWhile there were no strong and consistent associations between psychological factors and atherosclerosis, the consistent associations of psychological factors with cardiovascular health by Life’s Essential 8 may have relevance for future CVD risk. However, further studies are needed to elucidate the long-term effects of psychological factors on atherosclerosis development and cardiovascular health.

Insights on P2X7 in patients with abdominal aortic aneurysm and carotid atherosclerosis

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Ministero della Salute, Italia, Rete Cardiologica Nazionale Background Carotid atherosclerosis and abdominal aortic aneurysm (AAA) are co-morbidities [1]. P2X-purinoceptor-7 (P2X7) is expressed both in human AAA and atherosclerotic carotid plaque (CPL) and is instability-associated in CPL [2-4]. P2X7 is functionally related to miR-150 and miR-186 (two microRNA which modulate vascular cell proliferation) [5,6], and may be shed into the bloodstream in correlation with C-reactive protein increase [7]. Little is known about the possible association between AAA risk and circulating P2X7, miR-150 and miR-186 in patients with/without hemodinamically significant CPL. Purpose Our aim is exploring the possible relationship between circulating P2X7, target miRs clinical status and lesion dimensions in patients with CPL and/or AAA. Methods Male patients with AAA and/or CPL were characterized.CPL stenosis was assessed by Ecocolordoppler-TSA. Eligible cohort included 20 patients with AAA undergoing aneurysmectomy [10 with CPL stenosis ≤40% (group A), 10with CPL stenosis &amp;gt;40% (group B)], 10 patients with hemodinamically significant CPL and small or no AAA undergoing endarterectomy (group C) donating blood and vascular samples at surgery. Twelve healthy blood donors (group D) were enrolled as controls. P2X7 protein was evaluated by ELISA. P2X7 gene, miR-150 and miR-186 were determined by RT-qPCR. Results In group A, CPL appeared mainly localized at carotid bulb, in group B extended along branches. P2X7 gene was undetermined into serum and expressed without differences among groups in patient tissues. P2X7 protein was measurable in all serum samples and was lower in group B than in the others (p=0,0117, p=0,0009, p=0,0003 vs. group A, C, D, respectively) and in group C vs. D (p=0,0006). These data differentiated patients with hemodinamically significant CPLs with severe AAA from the other patients and all those with hemodinamically significant CPLs (irrespectively from AAA severity) from healthy individuals. In group B but not in the others, serum P2X7 was linearly associated to platelet concentration. In group C the amounts of P2X7 in CPL tissue and serum were negatively associated, whereas in group A and B the P2X7 levels in AAA tissue and serum were unrelated. The miRs were detected into both serum and tissue and not correlated among them nor with circulating P2X7 protein. The serum miR-186, but not miR-150, was differentially expressed in group A vs. B (p=0,0266) and linearly related to AAA diameter in group B (p=0.0351). P2X7 content and expressed gene (p=0,015, p= 0,023, respectively) and miR expressions (p=0,0418 for miR-186, p=0,0012 for miR-150) were more elevated in AAA vs. CPL tissues, highlighting the vascular heterogenicity. Conclusions Preliminary data suggest a role for P2X7 and miR-186 in profiling patients with hemodinamically significant CPL with/without high risk AAA, deserving further investigations.

Asporin expression is associated with human atherosclerotic plaque integrity

Abstract Funding Acknowledgements Type of funding sources: Other. Main funding source(s): This work was supported by the Swedish Research Council, the Swedish Heart and Lung Foundation, Skåne University Hospital funds Background Calcification serves as a clinical marker of atherosclerotic plaque burden. Recent studies have also shed light on its intricate association with plaque vulnerability, likely depend on calcification structures and the surrounding environment. Asporin (ASPN) is a member of the small-leucine-rich proteoglycans that contains a unique and well-conserved stretch of aspartate (D) residues, which mimic the role of glycosaminoglycans. Via its D-repeat, ASPN can interact with calcium and several other extracellular matrix molecules, thus influencing collagen mineralization and TGF-β signaling. ASPN expression has been shown to be higher in asymptomatic compared to symptomatic atherosclerotic plaques, suggesting a potential protective role. However, the role of ASPN in maintaining plaque integrity remains unknown. Purpose Here we aimed to explore the role of ASPN in atherosclerosis, by investigating if ASPN was expressed in human carotid plaques and by determining if ASPN is associated with risk for postoperative cardiovascular events and death. Methods ASPN and TGF-β protein levels were measured by ELISA and Milliplex in 176 human plaque tissue homogenates obtained from the Carotid Plaque Imaging Project (CPIP) biobank. Plaque tissue sections were stained for ASPN, destabilizing (CD68, oil red O, glycophorin A) and stabilizing plaque components (Movat, α-actin). Plaque tissue RNA expression levels were assessed in 82 plaques using bulk RNA sequencing. Plaque levels of phosphate, elastin and collagen were measured using ELISA. Results ASPN protein levels were higher in plaques from asymptomatic patients compared to symptomatic patients (p=0.011). ASPN RNA levels correlated positively to RNA levels of the smooth muscle cell markers ACTA2, MYH11 and TAGLN. Moreover, protein levels correlated with plaque levels of phosphate (r=0.258, p=0.001), elastin (r=0.423, p&amp;lt;0.001), collagen (r=0.248, p=0.002) and stability factors like the TGF-β family members, TGF-β1 (r=0.176, p=0.035), TGF-β2 (r=0.581, p&amp;lt;0.001) and TGF-β3 (r=0.396, p&amp;lt;0.001). Furthermore, plaque ASPN protein concentration, correlated inversely with a histological plaque vulnerability index (r=-0.265, p=0.0029), which is ratio between the plaque area of destabilizing (macrophages, lipids, intra-plaque hemorrhage) and stabilizing plaque components (collagen and smooth muscle cells). Additionally, above median ASPN levels were associated with lower risk for postoperative cardiovascular events (p=0.008) and death (p=0.009). Conclusion Our findings suggest that elevated levels of ASPN might have a crucial role in maintaining plaque stability, affecting plaque calcification.

Au/FeNiPO4‐Based Multiple Spectra Optoacoustic Tomography/CT Dual‐Mode Nanoprobe for Systemic Screening of Atherosclerotic Vulnerable Plaque

AbstractCurrent diagnostic technique in direct identification of multi‐site plaques and simultaneous assessment of plaque vulnerability remains a challenge, which is crucial for indicating the risk of atherosclerotic cardiovascular diseases (ASCVD). Herein, an osteopontin (OPN)‐specific nanoprobe (OPN Ab‐Au/FeNiPO4@ICG) with both multiple spectra optoacoustic tomography (MSOT) and computed tomography (CT) imaging, is constructed successfully realizing systemic screening of vulnerable plaque. OPN Ab‐Au/FeNiPO4@ICG nanoprobe specifically targeted OPN‐overexpressed foam cells and recognized the vulnerable plaque at the molecular level. In AS mice, CT imaging exhibits that OPN Ab‐Au/FeNiPO4@ICG nanoprobe effectively avoid interference from calcification and accurately visualized AS plaque. MSOT functional imaging results reveals that after the injection of OPN Ab‐Au/FeNiPO4@ICG nanoprobe, the carotid plaque exhibited a much higher MSOT signal than the aortic arch plaque (P = 0.0291). Further pathological analysis displays that the carotid plaque possessed a much higher vulnerability score (P = 0.0247), in agreement with the MSOT signals. More importantly, the linear regression analysis confirms the high correlation between the MSOT signals and plaque vulnerability with R = 0.7095 (P = 0.0216), demonstrating the potential of the proposed nanoprobe in systematic evaluation of plaque vulnerability. This work employs the dual‐model nanoprobe strategy for both plaque localization and vulnerability assessment, greatly advancing the accurate diagnosis of ASCVD.

The extracellular matrix proteoglycan serglycin is associated with human atherosclerotic plaque inflammation

Abstract Funding Acknowledgements Type of funding sources: Other. Main funding source(s): This work was supported by grants from the Swedish Research Council, the Swedish Heart and Lung Foundation, Skåne University Hospital funds, Royal Physiographic Society in Lund and O.E. and Edla Johanssons Foundation. Background Atherosclerotic cardiovascular disease is caused by the formation of plaques in the arterial wall which contain lipids, cells, cell debris and a unique extracellular matrix (ECM) signature. These plaques may ultimately rupture or erode away causing thrombosis, thereby leading to myocardial infarction or stroke. Rupture-prone plaques generally bear a greater inflammatory activity, with ECM proteins suggested to influence the inflammatory activity. Among many ECM proteins, serglycin (SRGN) is highly expressed by inflammatory cells, and SRGN has been linked to modulation of the inflammatory response in disease such as cancer. Yet, if SRGN contributes to the inflammatory circuitry in human atherosclerotic plaques remains to be explored. Purpose We aimed to investigate if SRGN was associated with inflammation in atherosclerotic plaques. Methods Plaque protein levels of SRGN were measured by ELISA in human carotid plaques obtained from the Carotid Plaque Imaging Project (CPIP) biobank. Plaque RNA expression levels of SRGN and cell markers were assessed by plaque bulk RNA sequencing. SRGN expression and distribution were further examined in tissue plaque sections through histology and multispectral imaging. In vitro models were used to investigate the functional consequences of SRGN expression changes, using SRGN CRISPR knockout THP1 monocytic cells. Immunoprecipitation of SRGN and immunoblotting against SRGN, heparan and chondroitin sulfate chains were employed to structurally characterize plaque protein SRGN. Results SRGN protein levels were significantly higher in plaques from asymptomatic patients compared to symptomatic. Multispectral imaging showed that SRGN protein was observed in plaque areas rich in macrophages and lipids. Using immunoprecipitation and immunoblotting, we identified a unique low glycosylated plaque SRGN, with both heparan sulfate and chondroitin sulfate glycosaminoglycans decorating its protein core. This exclusive configuration suggests that the plaque cell origin of SRGN may be macrophages or mast cells. In support of this, plaque SRGN RNA expression correlated with RNA levels of pro-inflammatory macrophage cells markers like CD68, CD163, MRC1, ITGAX. Plaque SRGN protein levels correlated with plaque levels of oxidised lipoproteins, proatherogenic (CCL1, IL7, MCP-4 and TNFα) and antiatherogenic cytokines (IL33, IL16 and CXCL13), as well as with growth factors, such as TGF-β. On the one hand, in vitro suppression of SRGN expression in monocytes led to a reduction in the anti-inflammatory M2-polarized phenotype, while M1 pro-inflammatory macrophages were unskewed. Furthermore, our in vitro studies showed that upon SRGN knockdown M2 macrophages retained more oxidized lipoproteins. Conclusions Our results suggest that SRGN may be a crucial modulator of inflammation in human atherosclerotic plaques, potentially by affecting the bioavailability of effector molecules such as growth factors and cytokines.

Leukemia inhibitory factor receptor inhibition reduces stenosis grade and total serum cholesterol levels in a mouse model for atherosclerosis

Abstract Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): Dutch Heart Foundation Atherosclerosis is characterized by the accumulation of lipids and immune cells in the arterial wall and it is the main underlying pathology causing cardiovascular diseases (CVD). Cytokines are involved in all stages of atherosclerosis and most cytokines contribute to disease progression. For instance, IL-6 cytokine family members, such as IL-6, oncostatin-M and cardiotrophin-1, are closely related to CVDs. However, the role of leukemia inhibitory factor (LIF), a member of the IL-6 cytokine family, and its receptor (LIFR) in atherosclerosis remains unknown. Therefore, the aim of this study is to assess the contribution of LIFR signaling to atherosclerosis development by systemically inhibiting LIFR in an atherosclerotic mouse model. First, the expression of LIF and LIFR was examined using single-cell RNA sequencing data of human carotid artery plaques. Mast cells highly and exclusively express LIF, whereas LIFR was specifically expressed by activated endothelial cells. To validate LIFR signaling in vivo, female western-type diet fed Ldlr-/- mice were treated with LIFR inhibitor EC359 (5 mg/kg s.c., n=15) or control solvent (n=15) three times per week for eight weeks. During the experiment, weights of the mice did not differ between groups, whereas total serum cholesterol levels were significantly reduced in EC359 treated mice (p=0.03). In particular, EC359 treatment reduced VLDL levels. Additionally, EC359 treatment significantly reduced Sr1, Abca1 and Lrp1 expression in the liver, suggesting an altered lipid metabolism in EC359 treated mice. Furthermore, LIFR inhibition affected innate immunity, both systemically and locally in the plaque. Neutrophil numbers were significantly increased in the circulation (ctrl 18.7±1.7%; EC359 28.0±2.0%; p=0.002) and aortic plaques (ctrl 3.9±0.8%; EC359 9.9±1.9%; p=0.003) of mice treated with EC359 compared to control mice. Moreover, LIFR inhibition affected circulating monocytes resulting in less inflammatory monocytes. The adaptive immune cells, such as T and B cells, remained largely unaffected. Collectively, the reduction of serum total cholesterol and increase in neutrophil numbers in EC359 treated mice resulted in a trend towards reduced atherosclerotic stenosis grade compared to control mice (39.8±1.4% versus 34.9±1.9%; p=0.054), but it did not affect plaque collagen and monocyte/macrophage content in the aortic root. Conclusively, LIFR signaling inhibition reduces atherosclerotic stenosis grade, lowers plasma total cholesterol levels and affects innate immunity.