2,977 research outputs found

    Insulin resistance and triglyceride/HDLc index are associated with coronary artery disease

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    <p>Abstract</p> <p>Background</p> <p>Insulin-resistance is associated with cardiovascular disease but it is not used as a marker for disease in clinical practice.</p> <p>Aims</p> <p>To study the association between the homeostatic model assessment (HOMA-IR) and triglyceride/HDLc ratio (TG/HDLc) with the presence of coronary artery disease in patients submitted to cardiac catheterization.</p> <p>Methods</p> <p>In a cross-sectional study, 131 patients (57.0 ± 10 years-old, 51.5% men) underwent clinical, laboratory and angiographic evaluation and were classified as No CAD (absence of coronary artery disease) or CAD (stenosis of more than 30% in at least one major coronary artery).</p> <p>Results</p> <p>Prevalence of coronary artery disease was 56.7%. HOMA-IR and TG/HDLc index were higher in the CAD <it>vs </it>No CAD group, respectively: HOMA-IR: 3.19 (1.70-5.62) vs. 2.33 (1.44-4.06), p = 0.015 and TG/HDLc: 3.20 (2.38-5.59) vs. 2.80 (1.98-4.59) p = 0.045) - median (p25-75). After a ROC curve analysis, cut-off values were selected based on the best positive predictive value for each variable: HOMA-IR = 6.0, TG/HDLc = 8.5 and [HOMA-IR×TG/HDLc] = 28. Positive predictive value for coronary artery disease for HOMA-IR>6.0 was 82.6%, for TG/HDLc>8.5 was 85.7% and for [HOMA-IR×TG/HDLc]>28 was 88.0%. Adjusted relative risk (age, gender, diabetes, body mass index, systolic blood pressure) for the presence of coronary artery disease was: for HOMA-IR>6.0, 1.47 (95.CI: 1.06-2.04, p = 0.027), for TG/HDLc>8.5, 1.46 (95% CI:1.07-1.98), p = 0.015) and for [HOMA-IR × TG/HDLc] >28, 1.64 (95%CI: 1.28-2.09), p < 0.001).</p> <p>Conclusions</p> <p>Increased HOMA-IR, TG/HDLc and their product are positively associated with angiographic coronary artery disease, and may be useful for risk stratification as a high-specificity test for coronary artery disease.</p

    The role of lipid metabolism in the immunopathogenesis of juvenile-onset systemic lupus erythematosus

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    Juvenile-onset systemic lupus erythematosus (JSLE) is a complex autoimmune disorder characterised by chronic inflammation, multiple organ damage and increased risk of cardiovascular disease (CVD). Disease onset in JSLE is more common during puberty and the female to male ratio is 4.5:1, suggesting a hormonal importance in disease pathogenesis. Work by the Jury lab in adult-onset SLE links immune cell dysregulation with defects in plasma membrane lipids rafts; signalling platforms that facilitate immune cell activation and effector function. However, in patients with JSLE, the immune system is still developing and very little is known about disease pathogenesis, whether it is the same as adult disease and whether the same treatments available to the adults are relevant for this younger group of patients. My hypothesis is that altered lipid metabolism leads to changes in immune cell function; differences in lipid metabolism exist between males and females and defects in these pathways contribute to JSLE pathogenesis. My aims were to 1) investigate sex differences in immune and metabolic phenotype in healthy individuals and JSLE patients, 2) assess the relationship between immune cells and serum lipids and 3) identify predictive biomarkers for CVD risk in JSLE. Using in depth immunophenotyping by flow cytometry and metabolomic analysis, this study has identified fundamental differences between healthy adolescent males and females. Males had increased regulatory T-cell (Treg) frequencies, altered lipid raft profiles and functional differences including an increased IL-4 production and suppressive capacity compared to females. These Treg phenotypic differences were associated with the very low density lipoprotein (VLDL) signature connected with males. In a chronic inflammatory setting (JSLE), these differences were lost between males and females. I also found that JSLE patients could be stratified according to their serum lipoprotein profile allowing potential identification of patients with increased CVD risk. This work provides evidence that a combination of pubertal development, immune cell defects and dyslipidemia may contribute to JSLE pathogenesis. Patient stratification has identified a unique group of patients that could benefit from lipid modification therapy, reducing both CVD risk and immune cell activity

    A low-cost machine learning-based cardiovascular/stroke risk assessment system: integration of conventional factors with image phenotypes

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    Background: Most cardiovascular (CV)/stroke risk calculators using the integration of carotid ultrasound image-based phenotypes (CUSIP) with conventional risk factors (CRF) have shown improved risk stratification compared with either method. However such approaches have not yet leveraged the potential of machine learning (ML). Most intelligent ML strategies use follow-ups for the endpoints but are costly and time-intensive. We introduce an integrated ML system using stenosis as an endpoint for training and determine whether such a system can lead to superior performance compared with the conventional ML system.Methods: The ML-based algorithm consists of an offline and online system. The offline system extracts 47 features which comprised of 13 CRF and 34 CUSIP. Principal component analysis (PCA) was used to select the most significant features. These offline features were then trained using the event-equivalent gold standard (consisting of percentage stenosis) using a random forest (RF) classifier framework to generate training coefficients. The online system then transforms the PCA-based test features using offline trained coefficients to predict the risk labels on test subjects. The above ML system determines the area under the curve (AUC) using a 10-fold cross-validation paradigm. The above system so-called "AtheroRisk-Integrated" was compared against "AtheroRisk-Conventional", where only 13 CRF were considered in a feature set.Results: Left and right common carotid arteries of 202 Japanese patients (Toho University, Japan) were retrospectively examined to obtain 395 ultrasound scans. AtheroRisk-Integrated system [AUC=0.80, P&lt;0.0001, 95% confidence interval (CI): 0.77 to 0.84] showed an improvement of similar to 18% against AtheroRisk-Conventional ML (AUC=0.68, P&lt;0.0001, 95% CI: 0.64 to 0.72).Conclusions: ML-based integrated model with the event-equivalent gold standard as percentage stenosis is powerful and offers low cost and high performance CV/stroke risk assessment

    Lipoprotein Sub-Fractions by Ion-Mobility Analysis and Its Association with Subclinical Coronary Atherosclerosis in High-Risk Individuals

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    AIMS: There is limited knowledge about the association of lipoprotein particles and markers of coronary atherosclerosis such as coronary artery calcification (CAC) in relatively young high-risk persons. This study examines the association of lipoprotein subfractions and CAC in high cardiometabolic risk individuals. METHODS: The study presents analysis from baseline data of a randomized trial targeted at high-risk workers. Employees of Baptist Health South Florida with metabolic syndrome or diabetes were recruited. At baseline, all 182 participants had lipoprotein subfraction analysis using the ion mobility technique and participants above 35 years (N=170) had CAC test done. Principal components (PC) were computed for the combination of lipoprotein subclasses. Multiple bootstrapped regression analyses (BSA) were conducted to assess the relationship between lipoprotein subfractions and CAC. RESULTS: The study population (N=170) was largely female (84%) with a mean age of 58 years. Three PCs accounted for 88% variation in the sample. PC2, with main contributions from VLDL particles in the positive direction and large LDL particles in the negative direction was associated with a 22% increase in CAC odds (P value <0.05 in 100% of BSA). PC3, with main contributions from HDL lipoprotein particles in the positive direction and small/medium LDL and large IDL particles in the negative direction, was associated with a 9% reduction in CAC odds (P<0.05 in 88% of BSA). PC1, which had approximately even contributions from HDL, LDL, IDL and VLDL lipoprotein subfractions in the positive direction, was not associated with CAC. CONCLUSION: In a relatively young but high-risk population, a lipoprotein profile predominated by triglyceride-rich lipoproteins was associated with increased risk of CAC, while one predominated by HDL lipoproteins offered modest protection. Lipoprotein sub-fraction analysis may help to further discriminate patients who require more intensive cardiovascular work-up and treatment

    Animal models of atherosclerosis.

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    Atherosclerosis is a significant cause of morbidity and mortality globally. Many animal models have been developed to study atherosclerosis, and permit experimental conditions, diet and environmental risk factors to be carefully controlled. Pathophysiological changes can be produced using genetic or pharmacological means to study the harmful consequences of different interventions. Experiments using such models have elucidated its molecular and pathophysiological mechanisms, and provided platforms for pharmacological development. Different models have their own advantages and disadvantages, and can be used to answer different research questions. In the present review article, different species of atherosclerosis models are outlined, with discussions on the practicality of their use for experimentation.GT was supported by a BBSRC Doctoral Training Award and thanks the Croucher Foundation of Hong Kong for the generous support of his clinical assistant professorship. YC is supported by the ESRC

    The Clinical Value of HDL Function Measurements

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    Imaging of atherosclerosis: magnetic resonance imaging

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    Atherosclerosis and its thrombotic complications are the major cause of morbidity and mortality in the industrialized countries. Despite advances in our understanding of the pathophysiology, pathogenesis, and new treatment modalities, the absence of an adequate non-invasive imaging tool for early detection limits both the prevention and treatment of patients with various degrees and anatomical localizations of atherothrombotic disease. An ideal clinical imaging modality for atherosclerotic vascular disease should be safe, inexpensive, non-invasive or minimally invasive, accurate, and reproducible, and the results should correlate with the extent of atherosclerotic disease and have high predictive values for future clinical events. High-resolution magnetic resonance imaging (MRI) has emerged as the most promising technique for studying atherothrombotic disease in humans in vivo. Most importantly, MRI allows for the characterization of plaque composition, i.e. the discrimination of lipid core, fibrosis, calcification, and intraplaque haemorrhage deposits. Magnetic resonance imaging also allows for the detection of arterial thrombi and in defining thrombus age. Magnetic resonance imaging has been used to monitor plaque progression and regression in several animal models of atherosclerosis and in humans. Emerging MRI techniques capable of imaging biological processes, including inflammation, neovascularization, and mechanical forces, may aid in advancing our understanding of the atherothrombotic disease. Advances in diagnosis do prosper provided they march hand-in-hand with advances in treatment. We stand at the threshold of accurate non-invasive assessment of atherosclerosis. Thus, MRI opens new strategies ranging from screening of high-risk patients for early detection and treatment as well as monitoring of the target lesions for pharmacological intervention. Identification of subclinical atherosclerosis and early treatment initiation has the potential to surpass conventional risk factor assessment and management in terms of overall impact on cardiovascular morbidity and mortality. Such strategy is currently under clinical investigatio
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