A cross-sectional study comparing the expression of DNA repair molecules in subjects with and without atherosclerotic plaques.

BACKGROUND: Atherosclerosis, serving as the primary pathological mechanism at the core of cardiovascular disease, is now widely acknowledged to be associated with DNA damage and repair, contributing to atherosclerotic plaque formation. Therefore, molecules involved in the DNA repair process may play an important role in the progression of atherosclerosis. Our research endeavors to explore the contributions of specific and interrelated molecules involved in DNA repair (APE1, BRCA1, ERCC2, miR-221-3p, miR-145-5p, and miR-155-5p) to the development of atherosclerotic plaque and their interactions with each other. METHODS & RESULTS: Gene expression study was conducted using the real-time polymerase chain reaction (qRT-PCR) method on samples from carotid artery atherosclerotic plaques and nonatherosclerotic internal mammary arteries obtained from 50 patients diagnosed with coronary artery disease and carotid artery disease. Additionally, 50 healthy controls were included for the determination of 8-hydroxy-2'-deoxyguanosine (8-OHdG). Although no difference was observed in mRNA gene expressions, we noted a decrease in miR-155-5p gene expression (p = 0.003) and an increase in miR-221-3p gene expression (p = 0.015) in plaque samples, while miR-145-5p gene expression remained unchanged (p = 0.57). Regarding serum 8-OHdG levels, patients exhibited significantly higher levels (1111.82 ± 28.64) compared to controls (636.23 ± 24.23) (p < 0.0001). CONCLUSIONS: In our study demonstrating the role of miR-155-5p and miR-221-3p in atherosclerosis, we propose that these molecules are potential biomarkers and therapeutic targets for coronary artery diseases and carotid artery disease.

Identification and experimental validation of KMO as a critical immune-associated mitochondrial gene in unstable atherosclerotic plaque.

BACKGROUND: The heightened risk of cardiovascular and cerebrovascular events is associated with the increased instability of atherosclerotic plaques. However, the lack of effective diagnostic biomarkers has impeded the assessment of plaque instability currently. This study was aimed to investigate and identify hub genes associated with unstable plaques through the integration of various bioinformatics tools, providing novel insights into the detection and treatment of this condition. METHODS: Weighted Gene Co-expression Network Analysis (WGCNA) combined with two machine learning methods were used to identify hub genes strongly associated with plaque instability. The cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) method was utilized to assess immune cell infiltration patterns in atherosclerosis patients. Additionally, Gene Set Variation Analysis (GSVA) was conducted to investigate the potential biological functions, pathways, and mechanisms of hub genes associated with unstable plaques. To further validate the diagnostic efficiency and expression of the hub genes, immunohistochemistry (IHC), quantitative real-time polymerase chain reaction (RT-qPCR), and enzyme-linked immunosorbent assay (ELISA) were performed on collected human carotid plaque and blood samples. Immunofluorescence co-staining was also utilized to confirm the association between hub genes and immune cells, as well as their colocalization with mitochondria. RESULTS: The CIBERSORT analysis demonstrated a significant decrease in the infiltration of CD8 T cells and an obvious increase in the infiltration of M0 macrophages in patients with atherosclerosis. Subsequently, two highly relevant modules (blue and green) strongly associated with atherosclerotic plaque instability were identified. Through intersection with mitochondria-related genes, 50 crucial genes were identified. Further analysis employing least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine recursive feature elimination (SVM-RFE) algorithms revealed six hub genes significantly associated with plaque instability. Among them, NT5DC3, ACADL, SLC25A4, ALDH1B1, and MAOB exhibited positive correlations with CD8 T cells and negative correlations with M0 macrophages, while kynurenine 3-monooxygenas (KMO) demonstrated a positive correlation with M0 macrophages and a negative correlation with CD8 T cells. IHC and RT-qPCR analyses of human carotid plaque samples, as well as ELISA analyses of blood samples, revealed significant upregulation of KMO and MAOB expression, along with decreased ALDH1B1 expression, in both stable and unstable samples compared to the control samples. However, among the three key genes mentioned above, only KMO showed a significant increase in expression in unstable plaque samples compared to stable plaque samples. Furthermore, the expression patterns of KMO in human carotid unstable plaque tissues and cultured mouse macrophage cell lines were assessed using immunofluorescence co-staining techniques. Finally, lentivirus-mediated KMO silencing was successfully transduced into the aortas of high-fat-fed ApoE-/- mice, with results indicating that KMO silencing attenuated plaque formation and promoted plaque stability in ApoE-/- mice. CONCLUSIONS: The results suggest that KMO, a mitochondria-targeted gene associated with macrophage cells, holds promise as a valuable diagnostic biomarker for assessing the instability of atherosclerotic plaques.

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

OBJECTIVE: Carotid 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. METHODS: We 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. RESULTS: WSS 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%. CONCLUSIONS: V-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.

Automated detection and classification of coronary atherosclerotic plaques on coronary CT angiography using deep learning algorithm.

Background: Coronary artery disease (CAD) is the leading cause of mortality worldwide. Recent advances in deep learning technology promise better diagnosis of CAD and improve assessment of CAD plaque buildup. The purpose of this study is to assess the performance of a deep learning algorithm in detecting and classifying coronary atherosclerotic plaques in coronary computed tomographic angiography (CCTA) images. Methods: Between January 2019 and September 2020, CCTA images of 669 consecutive patients with suspected CAD from Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine were included in this study. There were 106 patients included in the retrospective plaque detection analysis, which was evaluated by a deep learning algorithm and four independent physicians with varying clinical experience. Additionally, 563 patients were included in the analysis for plaque classification using the deep learning algorithm, and their results were compared with those of expert radiologists. Plaques were categorized as absent, calcified, non-calcified, or mixed. Results: The deep learning algorithm exhibited higher sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy {92% [95% confidence interval (CI): 89.5-94.1%], 87% (95% CI: 84.2-88.5%), 79% (95% CI: 76.1-82.4%), 95% (95% CI: 93.4-96.3%), and 89% (95% CI: 86.9-90.0%)} compared to physicians with ≤5 years of clinical experience in CAD diagnosis for the detection of coronary plaques. The algorithm's overall sensitivity, specificity, PPV, NPV, accuracy, and Cohen's kappa for plaque classification were 94% (95% CI: 92.3-94.7%), 90% (95% CI: 88.8-90.3%), 70% (95% CI: 68.3-72.1%), 98% (95% CI: 97.8-98.5%), 90% (95% CI: 89.8-91.1%) and 0.74 (95% CI: 0.70-0.78), indicating strong performance. Conclusions: The deep learning algorithm has demonstrated reliable and accurate detection and classification of coronary atherosclerotic plaques in CCTA images. It holds the potential to enhance the diagnostic capabilities of junior radiologists and junior intervention cardiologists in the CAD diagnosis, as well as to streamline the triage of patients with acute coronary symptoms.

Plasma lipidome differences in patients with and without significant carotid plaque.

BACKGROUND: Atherosclerosis is a major cause of ischemic stroke, and early detection of advanced atherosclerosis in the carotid artery is important for reducing morbidity and mortality. What is even more important is not only detection of atherosclerosis but early determination whether the patients are at high risk of an event with adverse effects as the size of the plaque does not necessarily reflect its potential to trigger such events. AIM: We studied whether plasma lipidomics profile can be used as a diagnostic tool for stratification of stable or unstable plaques without the need of removing the carotid plaque. METHODS: This study used liquid chromatography high-resolution tandem mass spectrometry lipidomics to characterize lipid profiles in patients' plasma and found that patients with significant and complicated (vulnerable) atherosclerotic plaque had distinct lipid profiles compared to those with insignificant plaques. RESULTS: The lipid classes that were most predictive of vulnerable plaque were lysophosphoethanolamines, fatty acyl esters of hydroxy fatty acids, free fatty acids, plasmalogens, and triacylglycerols. Most of these compounds were found decreased in plasma of patients with unstable plaques which enabled sufficient performance of a statistical model used for patient stratification. CONCLUSIONS: Plasma lipidomes measured by liquid chromatography-mass spectrometry show differences in patients with stable and unstable carotid plaques, therefore these compounds could potentially be used as biomarkers for unstable plaque in future clinical diagnosis.

Integrating machine learning algorithms and single-cell analysis to identify gut microbiota-related macrophage biomarkers in atherosclerotic plaques.

Objective: The relationship between macrophages and the gut microbiota in patients with atherosclerosis remains poorly defined, and effective biological markers are lacking. This study aims to elucidate the interplay between gut microbial communities and macrophages, and to identify biomarkers associated with the destabilization of atherosclerotic plaques. The goal is to enhance our understanding of the underlying molecular pathways and to pave new avenues for diagnostic approaches and therapeutic strategies in the disease. Methods: This study employed Weighted Gene Co-expression Network Analysis (WGCNA) and differential expression analysis on atherosclerosis datasets to identify macrophage-associated genes and quantify the correlation between these genes and gut microbiota gene sets. The Random Forest algorithm was utilized to pinpoint PLEK, IRF8, BTK, CCR1, and CD68 as gut microbiota-related macrophage genes, and a nomogram was constructed. Based on the top five genes, a Non-negative Matrix Factorization (NMF) algorithm was applied to construct gut microbiota-related macrophage clusters and analyze their potential biological alterations. Subsequent single-cell analyses were conducted to observe the expression patterns of the top five genes and the interactions between immune cells. Finally, the expression profiles of key molecules were validated using clinical samples from atherosclerosis patients. Results: Utilizing the Random Forest algorithm, we ultimately identified PLEK, IRF8, CD68, CCR1, and BTK as gut microbiota-associated macrophage genes that are upregulated in atherosclerotic plaques. A nomogram based on the expression of these five genes was constructed for use as an auxiliary tool in clinical diagnosis. Single-cell analysis confirmed the specific expression of gut microbiota-associated macrophage genes in macrophages. Clinical samples substantiated the high expression of PLEK in unstable atherosclerotic plaques. Conclusion: Gut microbiota-associated macrophage genes (PLEK, IRF8, CD68, CCR1, and BTK) may be implicated in the pathogenesis of atherosclerotic plaques and could serve as diagnostic markers to aid patients with atherosclerosis.

Engineering Nanoplatforms for Theranostics of Atherosclerotic Plaques.

Atherosclerotic plaque formation is considered the primary pathological mechanism underlying atherosclerotic cardiovascular diseases, leading to severe cardiovascular events such as stroke, acute coronary syndromes, and even sudden cardiac death. Early detection and timely intervention of plaques are challenging due to the lack of typical symptoms in the initial stages. Therefore, precise early detection and intervention play a crucial role in risk stratification of atherosclerotic plaques and achieving favorable post-interventional outcomes. The continuously advancing nanoplatforms have demonstrated numerous advantages including high signal-to-noise ratio, enhanced bioavailability, and specific targeting capabilities for imaging agents and therapeutic drugs, enabling effective visualization and management of atherosclerotic plaques. Motivated by these superior properties, various noninvasive imaging modalities for early recognition of plaques in the preliminary stage of atherosclerosis are comprehensively summarized. Additionally, several therapeutic strategies are proposed to enhance the efficacy of treating atherosclerotic plaques. Finally, existing challenges and promising prospects for accelerating clinical translation of nanoplatform-based molecular imaging and therapy for atherosclerotic plaques are discussed. In conclusion, this review provides an insightful perspective on the diagnosis and therapy of atherosclerotic plaques.

Caught in action: how MSCs modulate atherosclerotic plaque.

Atherosclerosis (AS) is a medical condition marked by the stiffening and constriction of the arteries. This is caused by the accumulation of plaque, a substance made up of fat, cholesterol, calcium, and other elements present in the blood. Over time, this plaque solidifies and constricts the arteries, restricting the circulation of oxygen-rich blood to the organs and other body parts. The onset and progression of AS involve a continuous inflammatory response, including the infiltration of inflammatory cells, foam cells derived from monocytes/macrophages, and inflammatory cytokines and chemokines. Mesenchymal stromal cells (MSCs), a type of multipotent stem cells originating from various body tissues, have recently been demonstrated to have a protective and regulatory role in diseases involving inflammation. Consequently, the transplantation of MSCs is being proposed as a novel therapeutic strategy for atherosclerosis treatment. This mini-review intends to provide a summary of the regulatory effects of MSCs at the plaque site to lay the groundwork for therapeutic interventions.

Cardiovascular Disease from Pathophysiology to Risk Estimation: Is Inflammation Estimated through Perivascular Attenuation on Computed Tomography the Key?

(1) Background: Systemic inflammation stands as a well-established risk factor for ischemic cardiovascular disease, as well as a contributing factor in the development of cardiac arrhythmias, notably atrial fibrillation. Furthermore, scientific studies have brought to light the pivotal role of localized vascular inflammation in the initiation, progression, and destabilization of coronary atherosclerotic disease. (2) Methods: We comprehensively review recent, yet robust, scientific evidence elucidating the use of perivascular adipose tissue attenuation measurement on computed tomography applied to key anatomical sites. Specifically, the investigation extends to the internal carotid artery, aorta, left atrium, and coronary arteries. (3) Conclusions: The examination of perivascular adipose tissue attenuation emerges as a non-invasive and indirect means of estimating localized perivascular inflammation. This measure is quantified in Hounsfield units, indicative of the inflammatory response elicited by dense adipose tissue near the vessel or the atrium. Particularly noteworthy is its potential utility in assessing inflammatory processes within the coronary arteries, evaluating coronary microvascular dysfunction, appraising conditions within the aorta and carotid arteries, and discerning inflammatory states within the atria, especially in patients with atrial fibrillation. The widespread applicability of perivascular adipose tissue attenuation measurement underscores its significance as a diagnostic tool with considerable potential for enhancing our understanding and management of cardiovascular diseases.

A clinical-radiomics combined model based on carotid atherosclerotic plaque for prediction of ischemic stroke.

Objectives: To accurately predict the risk of ischemic stroke, we established a radiomics model of carotid atherosclerotic plaque-based high-resolution vessel wall magnetic resonance imaging (HR-VWMRI) and combined it with clinical indicators. Materials and methods: In total, 127 patients were finally enrolled and randomly divided into training and test cohorts. HR-VWMRI three-dimensional T1-weighted imaging (T1WI) and contrast-enhanced T1WI (T1CE) were collected. A traditional model was built by recording and calculating radiographic features of the carotid plaques and patients' clinical indicators. After extracting radiomics features from T1WI and T1CE images, the least absolute shrinkage and selection operator (LASSO) algorithm was used to select the optimal features and construct the radiomics_T1WI model and the radiomics_T1CE model. The traditional and radiomics features were used to build combined models. The performance of all the models predicting ischemic stroke was evaluated in the training and test cohorts, respectively. Results: Body mass index (BMI) and intraplaque hemorrhage (IPH) were independently related to ischemic stroke and were used to build the traditional model, which achieved an area under the curve (AUC) of 0.79 versus 0.78 in the training and test cohorts, respectively. The AUC value of the radiomics_T1WI model is the lowest in the training and test cohorts, but the prediction performance is significantly improved when the model combines IPH and BMI. The AUC value of the combined_T1WI model was 0.78 and 0.81 in the training and test cohorts, respectively. In addition, in the training and test cohorts, the radiomics_T1CE model based on HR-VWMRI combined clinical characteristics, which is the combined_T1CE model, had the highest AUC value of 0.84 and 0.82, respectively. Conclusion: Compared with other models, the radiomics_T1CE model based on HR-VWMRI combined clinical characteristics, which is a combined_T1CE model, can accurately predict the risk of ischemic stroke.

The role of computed tomography angiography in assessing the correlation between properties of coronary atherosclerotic plaque and blood lipids.

BACKGROUND: Coronary atherosclerotic heart disease (CAHD) is the leading cause of death in developed countries. OBJECTIVE: This study aimed to explore the correlation between the properties of coronary atherosclerotic plaque and blood lipids using computed tomography angiography (CTA). METHODS: A total of 83 patients with coronary heart disease were included in this study (males: 50; females: 33; average age: [59 ± 8] years old). They were classified into the stable angina group and unstable angina group. Atherosclerotic plaques were classified as fatty plaques (soft plaques), fibrous plaques, and calcified plaques based on the computed tomography (CT) values. SPSS 17.0 statistical software was used to analyze the correlation between the properties of angina and the CT values of atherosclerotic plaques, blood lipids, and plaque properties, and then compared between the stable and unstable angina groups. RESULTS: There were statistically significant differences in plaque properties between the stable and unstable angina groups (P< 0.001). During CTA examination, we found statistically significant differences in the CT density values of atherosclerotic plaques between the stable and unstable angina groups (P< 0.001). There were statistically significant differences between the properties of angina and the level of blood lipids (P< 0.05). CONCLUSION: Anginal properties negatively correlated with calcified plaques and positively correlated with non-calcified plaques. Calcified plaques negatively correlated with total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG), and positively correlated with high-density lipoprotein cholesterol (HDL-C). Non-calcified plaques negatively correlated with HDL-C and positively correlated with TC, LDL-C, and TG.

7-year follow-up atherosclerotic plaque progression in patients with antiphospholipid syndrome versus diabetes mellitus and healthy controls.

OBJECTIVES: Patients with antiphospholipid syndrome (APS) carry a substantial burden of cardiovascular disease and subclinical atherosclerosis. We aimed to assess a 7-year follow-up atherosclerotic plaque progression in APS patients vs diabetes mellitus (DM) and healthy controls (HC). METHODS: Eighty-six patients with thrombotic APS, 86 with DM and 86 HC (all age- and sex-matched) who underwent a baseline ultrasound of carotid and femoral arteries were invited for a 7-year follow-up ultrasonography examination. We compared atherosclerosis progression among the three groups and examined determinants of plaque progression in APS patients. RESULTS: Sixty-four APS patients (75% females, 43.8% with primary APS), 58 patients with DM and 66 HC were included in the 7-year ultrasound re-evaluation. New plaque was detected in 51.6%, 36.2% and 25.8% of APS, DM and HC subjects, respectively. After adjusting for traditional cardiovascular risk factors (CVRFs) and baseline plaque presence, APS patients showed a 3-fold (OR = 3.07, p= 0.007) higher risk for atherosclerosis progression vs HC and 2-fold (OR = 2.25, p= 0.047) higher risk than DM patients. In multivariate analysis in the APS group, plaque progression was independently associated with systemic lupus erythematosus (SLE) co-existence (OR = 7.78, p= 0.005) and number of CVRFs (OR = 3.02, p= 0.002), after adjusting for disease-related parameters and CVRF-related medications. Sustained low-density lipoprotein target attainment reduced plaque progression risk (OR = 0.34, p= 0.021). CONCLUSION: Half of APS patients develop new atherosclerotic plaques over a 7-year follow-up, having a three-times higher risk vs HC. Concomitant SLE and number of traditional CVRFs are associated with plaque progression, supporting the need for thorough CVRF assessment and control.

Near-Infrared Persistent Luminescence Nanoprobe for Early Detection of Atherosclerotic Plaque.

Atherosclerosis (AS) is a crucial contributor to various cardiovascular diseases (CVDs), which seriously threaten human life and health. Early and accurate recognition of AS plaques is essential for the prevention and treatment of CVD. Herein, we introduce an AS-targeting nanoprobe based on near-infrared (NIR) persistent luminescence nanoparticles (PLNPs), developing a highly sensitive NIR persistent luminescence (PersL) AS plaque imaging technique and successfully realizing early AS plaque detection. The nanoprobe exhibits good monodispersity and regular spherical morphology and also owns exceptional NIR PersL performance upon repetitive irradiation by biological window light. The surface-conjugated antibody (anti-osteopontin) endowed nanoprobe excellent targeting ability to foam cells within plaques. After intravenously injected nanoprobe into AS model mice, the highly sensitive PersL imaging technique can accurately detect AS plaques prior to ultrasonography (US) and magnetic resonance imaging (MRI). Specifically, the NIR PersL imaging reveals AS plaques at the earliest within 2 weeks, with higher signal-to-background ratio (SBR) up to 5.72. Based on this technique, the nanoprobe has great potential for applications in the prevention and treatment of CVD, the study of AS pathogenesis, and the screening of anti-AS drugs.

Comprehensive biomechanical and anatomical atherosclerotic plaque metrics predict major adverse cardiovascular events: A new tool for clinical decision making.

BACKGROUND AND AIMS: Anatomical imaging alone of coronary atherosclerotic plaques is insufficient to identify risk of future adverse events and guide management of non-culprit lesions. Low endothelial shear stress (ESS) and high plaque structural stress (PSS) are associated with events, but individually their predictive value is insufficient for risk prediction. We determined whether combining multiple complementary, biomechanical and anatomical plaque characteristics improves outcome prediction sufficiently to inform clinical decision-making. METHODS: We examined baseline ESS, ESS gradient (ESSG), PSS, and PSS heterogeneity index (HI), and plaque burden in 22 lesions that developed subsequent events and 64 control lesions that remained quiescent from the PROSPECT study. RESULTS: 86 fibroatheromas were analysed from 67 patients. Lesions with events showed higher PSS HI (0.32 vs. 0.24, p<0.001), lower local ESS (0.56Pa vs. 0.91Pa, p = 0.007), and higher ESSG (3.82 Pa/mm vs. 1.96 Pa/mm, p = 0.007), while high PSS HI (hazard ratio [HR] 3.9, p = 0.006), high ESSG (HR 3.4, p = 0.007) and plaque burden>70 % (HR 2.6, p = 0.02) were independent outcome predictors in multivariate analysis. Combining low ESS, high ESSG, and high PSS HI gave both high positive predictive value (80 %), which increased further combined with plaque burden>70 %, and negative predictive value (81.6 %). Low ESS, high ESSG, and high PSS HI co-localised spatially within 1 mm in lesions with events, and importantly, this cluster was distant from the minimum lumen area site. CONCLUSIONS: Combining complementary biomechanical and anatomical metrics significantly improves risk-stratification of individual coronary lesions. If confirmed from larger prospective studies, our results may inform targeted revascularisation vs. conservative management strategies.

Genetic Predisposition of Atherosclerotic Cardiovascular Disease in Ancient Human Remains.

Background: Several computed tomographic studies have shown the presence of atherosclerosis in ancient human remains. However, while it is important to understand the development of atherosclerotic cardiovascular disease (ASCVD), genetic data concerning the prevalence of the disease-associated single nucleotide polymorphisms (SNPs) in our ancestors are scarce. Objective: For a better understanding of the role of genetics in the evolution of ASCVD, we applied an enrichment capture sequencing approach to mummified human remains from different geographic regions and time periods. Methods: Twenty-two mummified individuals were analyzed for their genetic predisposition of ASCVD. Next-generation sequencing methods were applied to ancient DNA (aDNA) samples, including a novel enrichment approach specifically designed to capture SNPs associated with ASCVD in genome-wide association studies of modern humans. Findings: Five out of 22 ancient individuals passed all filter steps for calculating a weighted polygenic risk score (PRS) based on 87 SNPs in 56 genes. PRSs were correlated to scores obtained from contemporary people from around the world and cover their complete range. The genetic results of the ancient individuals reflect their phenotypic results, given that the only two mummies showing calcified atherosclerotic arterial plaques on computed tomography scans are the ones exhibiting the highest calculated PRSs. Conclusions: These data show that alleles associated with ASCVD have been widespread for at least 5,000 years. Despite some limitations due to the nature of aDNA, our approach has the potential to lead to a better understanding of the interaction between environmental and genetic influences on the development of ASCVD.

The impact of traditional cardiovascular risk factor control on 7-year follow-up atherosclerosis progression in systemic lupus erythematosus.

OBJECTIVES: The 2022 EULAR recommendations for cardiovascular risk management in patients with rheumatic disorders, including SLE, call for rigorous management of cardiovascular risk factors (CVRF). The impact of CVRF target attainment on atherosclerotic plaque progression hasn't been previously evaluated in prospective ultrasound studies. METHODS: A total of 115 patients with SLE and 1:1 age and sex-matched healthy controls who had a baseline carotid and femoral ultrasound examination in our cardiovascular research unit were invited for a 7-year follow-up assessment of new plaque development. We aimed to compare the incidence of plaque progression between SLE patients and controls and reveal the extent to which it is affected by the attainment of European Society of Cardiology (ESC) targets for modifiable CVRFs (blood pressure, smoking status, body weight, lipids and physical activity), and disease-related features (disease duration, disease activity, autoantibodies, treatments). RESULTS: Eighty-six SLE patients and 42 controls had a 7-year follow-up carotid and femoral plaque examination. New plaque development was observed in 32/86 patients vs 8/42 controls (P = 0.037). Patients with SLE had a 4-fold higher risk for plaque progression than controls (OR: 4.16, CI: 1.22, 14.19, P = 0.023), adjusting for potential confounders. Multivariate regression analyses showed a 50% decrease in plaque progression for every modifiable CVRF fulfilling ESC targets (OR: 0.56, CI: 0.34, 0.93, P = 0.026). CONCLUSION: Patients with SLE develop a rapid progression of atherosclerotic plaques which may be drastically reduced by CVRF target attainment according to ESC guidelines.

Distinguishing Intracranial Diabetes-Related Atherosclerotic Plaques: A High-Resolution Magnetic Resonance Imaging-Based Radiomics Study.

INTRODUCTION: Diabetes markedly affects the formation and development of intracranial atherosclerosis. The study was aimed at evaluating whether radiomics features can help distinguish plaques primarily associated with diabetes. MATERIALS AND METHODS: We retrospectively analyzed patients who were admitted to our center because of acute ischemic stroke due to intracranial atherosclerosis between 2016 and 2022. Clinical data, blood biomarkers, conventional plaque features, and plaque radiomics features were collected for all patients. Odds ratios (ORs) with 95% confidence intervals (CIs) were determined from logistic regression models. The receiver operating characteristic (ROC) curve and area under the ROC curve (AUC) were used to describe diagnostic performance. The DeLong test was used to compare differences between models. RESULTS: Overall, 157 patients (115 men; mean age, 58.7 ± 10.7 years) were enrolled. Multivariate logistic regression analysis showed that plaque length (OR: 1.17; 95% CI: 1.07-1.28) and area (OR: 1.13; 95% CI: 1.02-1.24) were independently associated with diabetes. On combining plaque length and area as a conventional model, the AUCs of the training and validation cohorts for identifying diabetes patients were 0.789 and 0.720, respectively. On combining radiomics features on T1WI and contrast-enhanced T1WI sequences, a better diagnostic value was obtained in the training and validation cohorts (AUC: 0.889 and 0.861). The DeLong test showed the model combining radiomics and conventional plaque features performed better than the conventional model in both cohorts (p < 0.05). CONCLUSIONS: The use of radiomics features of intracranial plaques on high-resolution magnetic resonance imaging can effectively distinguish culprit plaques with diabetes as the primary pathological cause, which will provide new avenues of research into plaque formation and precise treatment.

The FCGR2A Is Associated with the Presence of Atherosclerotic Plaques in the Carotid Arteries-A Case-Control Study.

BACKGROUND: Atherosclerotic plaques in carotid arteries (APCA) are a prevalent condition with severe potential complications. Studies continuously search for innovative biomarkers for APCA, including those participating in cellular metabolic processes, cell adhesion, immune response, and complement activation. This study aimed to assess the relationship between APCA presence and a broad range of cardiometabolic biomarkers in the general population. METHODS: The study group consisted of consecutive participants of the population study Bialystok PLUS. The proximity extension assay (PEA) technique from the Olink Laboratory (Uppsala, Sweden) was used to measure the levels of 92 cardiometabolic biomarkers. RESULTS: The study comprised 693 participants (mean age 48.78 ± 15.27 years, 43.4% males, N = 301). APCA was identified in 46.2% of the participants (N = 320). Of the 92 biomarkers that were investigated, 54 were found to be significantly linked to the diagnosis of APCA. After adjusting for the traditional risk factors for atherosclerosis in multivariate analysis, the only biomarker that remained significantly associated with APCA was FCGR2A. CONCLUSION: In the general population, the prevalence of APCA is very high. A range of biomarkers are linked with APCA. Nonetheless, the majority of these associations are explained by traditional risk factors for atherosclerosis. The only biomarker that was independently associated with APCA was the FCGR2A.

Over-Expression of p190RhoGEF Regulates the Formation of Atherosclerotic Plaques in the Aorta of ApoE-/- Mice via Macrophage Polarization.

The RhoA-specific guanine nucleotide exchange factor p190RhoGEF has been implicated in the control of cell morphology, focal adhesion formation, and cell motility. Previously, we reported that p190RhoGEF is also active in various immune cells. In this study, we examined whether over-expression of p190RhoGEF could affect atherosclerotic plaque formation in mouse aortae. For that purpose, transgenic (TG) mice over-expressing p190RhoGEF were cross-bred with atherosclerosis-prone apolipoprotein E (ApoE)-/- mice to obtain p190RhoGEF-TG mice with ApoE-/- backgrounds (TG/ApoE-/-). Aortic plaque formation was significantly increased in TG/ApoE mice-/- at 30 to 40 weeks of age compared to that in ApoE-/- mice. Serum concentrations of inflammatory cytokines (IL-6 and TNF-α) were greater in TG/ApoE-/- mice than in ApoE-/- mice at ~40 weeks of age. Furthermore, TG/ApoE-/- mice had a greater proportion of peritoneal macrophages within the M1 subset at 30 to 40 weeks of age, together with higher production of inflammatory cytokines and stronger responses to bacterial lipopolysaccharide than ApoE-/- mice. Collectively, these results highlight a crucial role of enhanced p190RhoGEF expression in atherosclerosis progression, including the activation of pro-inflammatory M1 macrophages.