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Background: Plasma lipidomic measures may enable improved prediction of cardiovascular outcomes in secondary prevention. The aim of this study is to determine the association of plasma lipidomic measurements with cardiovascular events and assess their potential to predict such events., Methods: Plasma lipids (n = 342) were measured in a retrospective subcohort (n = 5,991) of the LIPID study. Proportional hazards regression was used to identify lipids associated with future cardiovascular events (nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death) and cardiovascular death. Multivariable models adding lipid species to traditional risk factors were created using lipid ranking established from the Akaike information criterion within a 5-fold cross-validation framework. The results were tested on a diabetic case cohort from the ADVANCE study (n = 3,779)., Results: Specific ceramide species, sphingolipids, phospholipids, and neutral lipids containing omega-6 fatty acids or odd-chain fatty acids were associated with future cardiovascular events (106 species) and cardiovascular death (139 species). The addition of 7 lipid species to a base model (11 conventional risk factors) resulted in an increase in the C-statistics from 0.629 (95% CI, 0.628-0.630) to 0.654 (95% CI, 0.653-0.656) for prediction of cardiovascular events and from 0.673 (95% CI, 0.671-0.675) to 0.727 (95% CI, 0.725-0.728) for prediction of cardiovascular death. Categorical net reclassification improvements for cardiovascular events and cardiovascular death were 0.083 (95% CI, 0.081-0.086) and 0.166 (95% CI, 0.162-0.170), respectively. Evaluation on the ADVANCE case cohort demonstrated significant improvement on the base models., Conclusions: The improvement in the prediction of cardiovascular outcomes, above conventional risk factors, demonstrates the potential of plasma lipidomic profiles as biomarkers for cardiovascular risk stratification in secondary prevention., Funding: Bristol-Myers Squibb, the National Health and Medical Research Council of Australia (grants 211086, 358395, and 1029754), and the Operational Infrastructure Support Program of the Victorian government of Australia.

Introduction: HIV and antiretroviral therapy (ART) have been associated with increased cardiovascular disease and important changes in lipid metabolism. Advances in mass-spectrometry technology allow for the detailed assessment of individual lipid species which may illuminate the mechanisms underlying increased cardiovascular risk. We describe the change in plasma lipidome with initiation of antiretroviral therapy and compare these by regimen., Methods: Plasma lipid profiling (by electrospray isonisation-tandem mass spectrometry) was performed on ARV-naive HIV positive participants randomised to one of three regimens; tenofovir/emtricitabine with efavirenz, ritonavir-boosted atazanavir (atazanavir/r) or zidovudine/abacavir. Participants (n = 115) who remained on their randomised regimen with complete samples available at baseline, week 12 and 48 were included. 306 lipid species from 22 lipid classes were analysed., Results: Initiation of ART led to significant changes in lipidome which were partly dependent on the randomised regimen received. This led to significant differences in 72 lipid species and 7 classes (cholesterol ester, free cholesterol, phosphatidylcholine, GM3 ganglioside, trihexosylceramide, monohexosylceramide, and ceramides) by arm at week 48. Consistently higher lipid concentrations were seen with efavirenz compared with atazanavir/r or zidovudine/abacavir. Twelve of the lipid species and two lipid classes (cholesterol esters and ceramides) that were significantly increased in the efavirenz arm compared with the atazanavir/r or zidovudine/abacavir arms have previously been associated with future cardiovascular events in HIV positive patients. Change in HIV viral load was predictive of change in 3 lipid species., Conclusions: Initiation of ART lead to significant changes in the plasma lipidome that were greatest in those receiving efavirenz., Competing Interests: No authors have a significant conflicts of interest related to this work but we would like to declare that Professor Jennifer Hoy’s institution has received reimbursement for her participation in Advisory Boards for Gilead Science, Merck Sharp & Dohme, ViiV Healthcare and Abbott. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Background: Differential plasma concentrations of circulating lipid species are associated with pathogenesis of type 2 diabetes (T2D). Whether the wide inter-individual variability in the plasma lipidome contributes to the genetic basis of T2D is unknown. Here, we investigated the potential overlap in the genetic basis of the plasma lipidome and T2D-related traits., Results: We used plasma lipidomic data (1202 pedigreed individuals, 319 lipid species representing 23 lipid classes) from San Antonio Family Heart Study in Mexican Americans. Bivariate trait analyses were used to estimate the genetic and environmental correlation of all lipid species with three T2D-related traits: risk of T2D, presence of prediabetes and homeostatic model of assessment - insulin resistance. We found that 44 lipid species were significantly genetically correlated with one or more of the three T2D-related traits. Majority of these lipid species belonged to the diacylglycerol (DAG, 17 species) and triacylglycerol (TAG, 17 species) classes. Six lipid species (all belonging to the triacylglycerol class and containing palmitate at the first position) were significantly genetically correlated with all the T2D-related traits., Conclusions: Our results imply that: a) not all plasma lipid species are genetically informative for T2D pathogenesis; b) the DAG and TAG lipid classes partially share genetic basis of T2D; and c) 1-palmitate containing TAGs may provide additional insights into the genetic basis of T2D.

Background: Clinical lipid measurements do not show the full complexity of the altered lipid metabolism associated with diabetes mellitus or cardiovascular disease. Lipidomics enables the assessment of hundreds of lipid species as potential markers for disease risk., Methods: Plasma lipid species (310) were measured by a targeted lipidomic analysis with liquid chromatography electrospray ionization-tandem mass spectrometry on a case-cohort (n=3779) subset from the ADVANCE trial (Action in Diabetes and Vascular Disease: Preterax and Diamicron-MR Controlled Evaluation). The case-cohort was 61% male with a mean age of 67 years. All participants had type 2 diabetes mellitus with ≥1 additional cardiovascular risk factors, and 35% had a history of macrovascular disease. Weighted Cox regression was used to identify lipid species associated with future cardiovascular events (nonfatal myocardial infarction, nonfatal stroke, and cardiovascular death) and cardiovascular death during a 5-year follow-up period. Multivariable models combining traditional risk factors with lipid species were optimized with the Akaike information criteria. C statistics and NRIs were calculated within a 5-fold cross-validation framework., Results: Sphingolipids, phospholipids (including lyso- and ether- species), cholesteryl esters, and glycerolipids were associated with future cardiovascular events and cardiovascular death. The addition of 7 lipid species to a base model (14 traditional risk factors and medications) to predict cardiovascular events increased the C statistic from 0.680 (95% confidence interval [CI], 0.678-0.682) to 0.700 (95% CI, 0.698-0.702; P<0.0001) with a corresponding continuous NRI of 0.227 (95% CI, 0.219-0.235). The prediction of cardiovascular death was improved with the incorporation of 4 lipid species into the base model, showing an increase in the C statistic from 0.740 (95% CI, 0.738-0.742) to 0.760 (95% CI, 0.757-0.762; P<0.0001) and a continuous net reclassification index of 0.328 (95% CI, 0.317-0.339). The results were validated in a subcohort with type 2 diabetes mellitus (n=511) from the LIPID trial (Long-Term Intervention With Pravastatin in Ischemic Disease)., Conclusions: The improvement in the prediction of cardiovascular events, above traditional risk factors, demonstrates the potential of plasma lipid species as biomarkers for cardiovascular risk stratification in diabetes mellitus., Clinical Trial Registration: URL: https://clinicaltrials.gov. Unique identifier: NCT00145925., (© 2016 American Heart Association, Inc.)

Background: Detection of type 2 diabetes (T2D) is routinely based on the presence of dysglycemia. Although disturbed lipid metabolism is a hallmark of T2D, the potential of plasma lipidomics as a biomarker of future T2D is unknown. Our objective was to develop and validate a plasma lipidomic risk score (LRS) as a biomarker of future type 2 diabetes and to evaluate its cost-effectiveness for T2D screening., Methods: Plasma LRS, based on significantly associated lipid species from an array of 319 lipid species, was developed in a cohort of initially T2D-free individuals from the San Antonio Family Heart Study (SAFHS). The LRS derived from SAFHS as well as its recalibrated version were validated in an independent cohort from Australia--the AusDiab cohort. The participants were T2D-free at baseline and followed for 9197 person-years in the SAFHS cohort (n = 771) and 5930 person-years in the AusDiab cohort (n = 644). Statistically and clinically improved T2D prediction was evaluated with established statistical parameters in both cohorts. Modeling studies were conducted to determine whether the use of LRS would be cost-effective for T2D screening. The main outcome measures included accuracy and incremental value of the LRS over routinely used clinical predictors of T2D risk; validation of these results in an independent cohort and cost-effectiveness of including LRS in screening/intervention programs for T2D., Results: The LRS was based on plasma concentration of dihydroceramide 18:0, lysoalkylphosphatidylcholine 22:1 and triacyglycerol 16:0/18:0/18:1. The score predicted future T2D independently of prediabetes with an accuracy of 76%. Even in the subset of initially euglycemic individuals, the LRS improved T2D prediction. In the AusDiab cohort, the LRS continued to predict T2D significantly and independently. When combined with risk-stratification methods currently used in clinical practice, the LRS significantly improved the model fit (p < 0.001), information content (p < 0.001), discrimination (p < 0.001) and reclassification (p < 0.001) in both cohorts. Modeling studies demonstrated that LRS-based risk-stratification combined with metformin supplementation for high-risk individuals was the most cost-effective strategy for T2D prevention., Conclusions: Considering the novelty, incremental value and cost-effectiveness of LRS it should be used for risk-stratification of future T2D.

Aims/hypothesis: The risk of developing diabetes is greater for women with previous gestational diabetes mellitus (GDM). In the general population, plasma lipidomic analysis can identify individuals at risk of developing type 2 diabetes. The aim of this study was to determine whether circulating lipid levels 12 weeks following a GDM pregnancy were associated with an increased risk of developing type 2 diabetes., Methods: Plasma lipid profiles containing >300 lipids were measured in 104 normal glucose-tolerant women 12 weeks following an index GDM pregnancy using electrospray-ionisation tandem mass spectrometry. Women were assessed for 10 years for development of overt type 2 diabetes., Results: Among the 104 women with previous GDM, 21 (20%) developed diabetes during the median follow-up period of 8.5 years. Three lipid species, the cholesteryl ester species CE 20:4, the alkenylphosphatidylethanolamine species PE(P-36:2) and the phosphatidylserine species PS 38:4, were independently and positively associated with the development of type 2 diabetes. In a clinical model of prediction of type 2 diabetes that included age, BMI, and levels of pregnancy fasting glucose, postnatal fasting glucose, triacylglycerol and total cholesterol, the addition of these three lipid species resulted in an improvement in the net reclassification index of 22.3%., Conclusions/interpretation: The lipid species CE 20:4, PE(P-36:2) and PS 38:4 were significant risk factors for the development of type 2 diabetes in women with a previous history of GDM. This report is the first to use plasma lipidomic analysis to identify individual lipids as potential biomarkers for the prediction of type 2 diabetes in women with a history of GDM.

Liver disease is the greatest cause of death related to alcohol and a major public health problem. While excessive alcohol intake results in hepatosteatosis in most individuals, this can progress in some to more severe forms of liver disease including fibrosis and cirrhosis. An ongoing challenge in the management of alcoholic liver disease is the identification of liver injury early in the disease process such that intervention strategies can prevent serious long term outcomes. Given that excessive alcohol consumption results in dysregulation of lipid metabolism we applied lipid profiling technology to characterise and compare serum lipid profiles from excessive chronic drinkers with no liver disease to those with advanced alcoholic cirrhosis. In a cohort of 59 excessive drinkers (31 with liver cirrhosis and 28 with no evidence of liver disease) we used electrospray ionisation tandem mass spectrometry to measure over 300 individual lipid species in serum, including species of the major phospholipid, sphingolipid, glycerolipid and sterol classes. Six of the 25 lipid classes and subclasses were significantly associated with alcoholic liver cirrhosis; these included dihexosylceramide, trihexosylceramide, alkylphosphatidylcholine, lysoalkylphosphatidylcholine, phosphatidylinositol and free cholesterol. Multivariate classification models created with only clinical characteristics gave an optimal model with an AUC of 0.847 and an accuracy of 79.7%. The addition of lipid measurements to the clinical characteristics resulted in models of improved performance with an AUC of 0.892 and accuracy of 81.8%. The gain in AUC and accuracy of the combined models highlight the potential of serum lipids as markers of liver injury in alcoholic liver disease.

Background: Cardiovascular disease (CVD) is the most common cause of death in the United States and is associated with a high economic burden. Prevention of CVD focuses on controlling or improving the lipid profile of patients at risk. The human lipidome is made up of thousands of ubiquitous lipid species. By studying biologically simple canonical lipid species, we investigated whether the lipidome is genetically redundant and whether its genetic influences can provide clinically relevant clues of CVD risk., Methods and Results: We performed a genetic study of the human lipidome in 1212 individuals from 42 extended Mexican American families. High-throughput mass spectrometry enabled rapid capture of precise lipidomic profiles, providing 319 unique species. Using variance component-based heritability analyses and bivariate trait analyses, we detected significant genetic influences on each lipid assayed. Median heritability of the plasma lipid species was 0.37. Hierarchical clustering based on complex genetic correlation patterns identified 12 genetic clusters that characterized the plasma lipidome. These genetic clusters were differentially but consistently associated with risk factors of CVD, including central obesity, obesity, type 2 diabetes mellitus, raised serum triglycerides, and metabolic syndrome. Also, these clusters consistently predicted occurrence of cardiovascular deaths during follow-up., Conclusions: The human plasma lipidome is heritable. Shared genetic influences reduce the dimensionality of the human lipidome into clusters that are associated with risk factors of CVD., (© 2014 American Heart Association, Inc.)

Motivation: Recent advances in high-throughput lipid profiling by liquid chromatography electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) have made it possible to quantify hundreds of individual molecular lipid species (e.g. fatty acyls, glycerolipids, glycerophospholipids, sphingolipids) in a single experimental run for hundreds of samples. This enables the lipidome of large cohorts of subjects to be profiled to identify lipid biomarkers significantly associated with disease risk, progression and treatment response. Clinically, these lipid biomarkers can be used to construct classification models for the purpose of disease screening or diagnosis. However, the inclusion of a large number of highly correlated biomarkers within a model may reduce classification performance, unnecessarily inflate associated costs of a diagnosis or a screen and reduce the feasibility of clinical translation. An unsupervised feature reduction approach can reduce feature redundancy in lipidomic biomarkers by limiting the number of highly correlated lipids while retaining informative features to achieve good classification performance for various clinical outcomes. Good predictive models based on a reduced number of biomarkers are also more cost effective and feasible from a clinical translation perspective., Results: The application of LICRE to various lipidomic datasets in diabetes and cardiovascular disease demonstrated superior discrimination in terms of the area under the receiver operator characteristic curve while using fewer lipid markers when predicting various clinical outcomes., Availability and Implementation: The MATLAB implementation of LICRE is available from http://ww2.cs.mu.oz.au/∼gwong/LICRE, (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Aims: The optimal management of asymptomatic subjects at intermediate risk of coronary artery disease (CAD) is often uncertain. Re-stratification to a high- or low-risk category may enable optimization of preventative strategies. Coronary computed tomographic angiography (CCTA) enables a minimally invasive assessment of coronary artery plaque quantity and composition. Non-calcified plaque by CCTA is lipid-rich and more vulnerable to rupture and resultant acute coronary syndromes. The purpose of this study was to determine whether novel approaches to CAD risk stratification, such as plasma lipid profiling, may predict non-calcified plaque burden in intermediate risk subjects., Methods and Results: CCTA and several markers of CAD (including plasma lipid profiling, carotid intima-media thickness, aortic pulse wave velocity, and high-sensitivity C-reactive protein) were prospectively performed in 100 asymptomatic patients at intermediate CAD risk according to the Framingham risk score. Segment stenosis scores (SSS) were calculated to evaluate the burden of total, calcified, and non-calcified coronary artery plaque. Non-calcified plaque was observed in 66 subjects and 158 (11%) of 1425 coronary artery segments. Eighteen lipid species demonstrated significant associations with non-calcified plaque burden, but not with total plaque or calcified plaque burden. No other marker of CAD was found to predict coronary artery plaque burden., Conclusions: Plasma lipidomic analysis can predict the burden of non-calcified coronary plaque in asymptomatic subjects at intermediate risk of CAD. Re-stratification of these patients by plasma lipid profiling may enable more appropriate and effective primary prevention management strategies., (Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2014. For permissions please email: journals.permissions@oup.com.)

Background: The increased risk of coronary artery disease in human immunodeficiency virus (HIV) positive patients is collectively contributed to by the human immunodeficiency virus and antiretroviral-associated dyslipidaemia. In this study, we investigate the characterisation of the plasma lipid profiles of treated HIV patients and the relationship of 316 plasma lipid species across multiple lipid classes with the risk of future cardiovascular events in HIV-positive patients., Methods: In a retrospective case-control study, we analysed plasma lipid profiles of 113 subjects. Cases (n = 23) were HIV-positive individuals with a stored blood sample available 12 months prior to their diagnosis of coronary artery disease (CAD). They were age and sex matched to HIV-positive individuals without a diagnosis of CAD (n = 45) and with healthy HIV-negative volunteers (n = 45)., Results: Association of plasma lipid species and classes with HIV infection and cardiovascular risk in HIV were determined. In multiple logistic regression, we identified 83 lipids species and 7 lipid classes significantly associated with HIV infection and a further identified 74 lipid species and 8 lipid classes significantly associated with future cardiovascular events in HIV-positive subjects. Risk prediction models incorporating lipid species attained an area under the receiver operator characteristic curve (AUC) of 0.78 (0.775, 0.785)) and outperformed all other tested markers and risk scores in the identification of HIV-positive subjects with increased risk of cardiovascular events., Conclusions: Our results demonstrate that HIV-positive patients have significant differences in their plasma lipid profiles compared with healthy HIV-negative controls and that numerous lipid species were significantly associated with elevated cardiovascular risk. This suggests a potential novel application for plasma lipids in cardiovascular risk screening of HIV-positive patients.

Background: Currently, the relationship between circulating lipids and abdominal aortic aneurysm (AAA) is unclear. We conducted a lipidomic analysis to identify serum lipids associated with AAA presence. Secondary analyses assessed the ability of models incorporating lipidomic features to improve stratification of patient groups with and without AAA beyond traditional risk factors., Methods and Results: Serum lipids were profiled via liquid chromatography tandem mass spectrometry analysis of serum from 161 patients with AAA and 168 controls with peripheral artery disease. Binary logistic regression was used to identify AAA-associated lipids. Classification models were created based on a combination of (1) traditional risk factors only or (2) lipidomic features and traditional risk factors. Model performance was assessed using receiver operator characteristic curves. Three diacylglycerols and 7 triacylglycerols were associated with AAA. Combining lipidomic features with traditional risk factors significantly improved stratification of AAA and peripheral artery disease groups when compared with traditional risk factors alone (mean area under the receiver operator characteristic curve [95% confidence interval], 0.760 [0.756-0.763] and 0.719 [0.716-0.723], respectively; P<0.05)., Conclusions: A group of linoleic acid containing triacylglycerols and diacylglycerols were significantly associated with AAA presence. Inclusion of lipidomic features in multivariate analyses significantly improved prediction of AAA presence when compared with traditional risk factors alone.

The association between consumption of full-fat dairy foods and CVD may depend partly on the nature of products and may not apply to low-fat dairy foods. Increased circulating levels of inflammatory biomarkers after consumption of dairy product-rich meals suggest an association with CVD. In the present study, we tested the effects of low-fat and full-fat dairy diets on biomarkers associated with inflammation, oxidative stress or atherogenesis and on plasma lipid classes. Within full-fat dairy diets, we also compared fermented v. non-fermented products. In a randomised cross-over study, twelve overweight/obese subjects consumed during two 3-week periods two full-fat dairy diets containing either yogurt plus cheese (fermented) or butter, cream and ice cream (non-fermented) or a low-fat milk plus yogurt diet, with the latter being consumed between and at the end of the full-fat dairy dietary periods. The concentrations of six inflammatory and two atherogenic biomarkers known to be raised in CVD were measured as well as those of plasma F2-isoprostanes and lipid classes. The concentrations of six of the eight biomarkers tended to be higher on consumption of the low-fat dairy diet than on that of the fermented dairy diet and the concentrations of two plasmalogen lipid classes reported to be associated with increased oxidisability were also higher on consumption of the low-fat dairy diet than on that of the fermented dairy diet (P< 0.001), although plasma F2-isoprostane concentrations did not differ on consumption of any of the diets. On the other hand, the concentrations of plasma sphingomyelin and IL-6 were significantly higher on consumption of the non-fermented dairy diet than on that of the low-fat dairy diet (P< 0.02). In conclusion, short-term diets containing low-fat dairy products did not lead to a more favourable biomarker profile associated with CVD risk compared with the full-fat dairy products, suggesting that full-fat fermented dairy products may be the more favourable.

Background: A significant proportion of individuals with diabetes or impaired glucose tolerance have fasting plasma glucose less than 6.1 mmol/L and so are not identified with fasting plasma glucose measurements. In this study, we sought to evaluate the utility of plasma lipids to improve on fasting plasma glucose and other standard risk factors for the identification of type 2 diabetes or those at increased risk (impaired glucose tolerance)., Methods and Findings: Our diabetes risk classification model was trained and cross-validated on a cohort 76 individuals with undiagnosed diabetes or impaired glucose tolerance and 170 gender and body mass index matched individuals with normal glucose tolerance, all with fasting plasma glucose less than 6.1 mmol/L. The inclusion of 21 individual plasma lipid species to triglycerides and HbA1c as predictors in the diabetes risk classification model resulted in a statistically significant gain in area under the receiver operator characteristic curve of 0.049 (p<0.001) and a net reclassification improvement of 10.5% (p<0.001). The gain in area under the curve and net reclassification improvement were subsequently validated on a separate cohort of 485 subjects., Conclusions: Plasma lipid species can improve the performance of classification models based on standard lipid and non-lipid risk factors.

We have performed plasma lipid profiling using liquid chromatography electrospray ionization tandem mass spectrometry on a population cohort of more than 1,000 individuals. From 10 μl of plasma we were able to acquire comparative measures of 312 lipids across 23 lipid classes and subclasses including sphingolipids, phospholipids, glycerolipids, and cholesterol esters (CEs) in 20 min. Using linear and logistic regression, we identified statistically significant associations of lipid classes, subclasses, and individual lipid species with anthropometric and physiological measures. In addition to the expected associations of CEs and triacylglycerol with age, sex, and body mass index (BMI), ceramide was significantly higher in males and was independently associated with age and BMI. Associations were also observed for sphingomyelin with age but this lipid subclass was lower in males. Lysophospholipids were associated with age and higher in males, but showed a strong negative association with BMI. Many of these lipids have previously been associated with chronic diseases including cardiovascular disease and may mediate the interactions of age, sex, and obesity with disease risk.

The relationship between lipid metabolism with prediabetes (impaired fasting glucose and impaired glucose tolerance) and type 2 diabetes mellitus is poorly defined. We hypothesized that a lipidomic analysis of plasma lipids might improve the understanding of this relationship. We performed lipidomic analysis measuring 259 individual lipid species, including sphingolipids, phospholipids, glycerolipids and cholesterol esters, on fasting plasma from 117 type 2 diabetes, 64 prediabetes and 170 normal glucose tolerant participants in the Australian Diabetes, Obesity and Lifestyle Study (AusDiab) then validated our findings on 1076 individuals from the San Antonio Family Heart Study (SAFHS). Logistic regression analysis of identified associations with type 2 diabetes (135 lipids) and prediabetes (134 lipids), after adjusting for multiple covariates. In addition to the expected associations with diacylglycerol, triacylglycerol and cholesterol esters, type 2 diabetes and prediabetes were positively associated with ceramide, and its precursor dihydroceramide, along with phosphatidylethanolamine, phosphatidylglycerol and phosphatidylinositol. Significant negative associations were observed with the ether-linked phospholipids alkylphosphatidylcholine and alkenylphosphatidylcholine. Most of the significant associations in the AusDiab cohort (90%) were subsequently validated in the SAFHS cohort. The aberration of the plasma lipidome associated with type 2 diabetes is clearly present in prediabetes, prior to the onset of type 2 diabetes. Lipid classes and species associated with type 2 diabetes provide support for a number of existing paradigms of dyslipidemia and suggest new avenues of investigation.

Objective: Traditional risk factors for coronary artery disease (CAD) fail to adequately distinguish patients who have atherosclerotic plaques susceptible to instability from those who have more benign forms. Using plasma lipid profiling, this study aimed to provide insight into disease pathogenesis and evaluate the potential of lipid profiles to assess risk of future plaque instability., Methods and Results: Plasma lipid profiles containing 305 lipids were measured on 220 individuals (matched healthy controls, n=80; stable angina, n=60; unstable coronary syndrome, n=80) using electrospray-ionisation tandem mass spectrometry. ReliefF feature selection coupled with an L2-regularized logistic regression based classifier was used to create multivariate classification models which were verified via 3-fold cross-validation (1000 repeats). Models incorporating both lipids and traditional risk factors provided improved classification of unstable CAD from stable CAD (C-statistic=0.875, 95% CI 0.874-0.877) compared with models containing only traditional risk factors (C-statistic=0.796, 95% CI 0.795-0.798). Many of the lipids identified as discriminatory for unstable CAD displayed an association with disease acuity (severity), suggesting that they are antecedents to the onset of acute coronary syndrome., Conclusion: Plasma lipid profiling may contribute to a new approach to risk stratification for unstable CAD.

In the presence of specialized proteins or peptides, a biological membrane can spontaneously restructure itself to allow communication between the intracellular and the extracellular sides. Examples of these proteins include cell-penetrating peptides and antimicrobial peptides (AMPs), which interact with cell membranes in complex ways. We briefly review cell-penetrating peptides and AMPs, and describe in detail how recombinant AMPs are made and their activity evaluated, using α-defensins as a specific example. We also review X-ray scattering methods used in studying peptide-membrane interactions, focusing on the procedures for small-angle X-ray scattering experiments on peptide-membrane interactions at realistic solution conditions, using both laboratory and synchrotron sources., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Complexes of anionic DNA and cationic liposomes self-assemble into a multilamellar structure where two-dimensional lipid sheets confine a periodic one-dimensional lattice of parallel DNA chains, between which Cd(2+) ions can condense, and be subsequently reacted with H(2)S to form CdS nanorods. In this work, we identify the synergistic roles of the anionic and cationic components within the DNA-membrane template; DNA is highly anionic and condenses the Cd(2+) ions, while the cationic membrane modulates the concentration of condensed Cd(2+) ions to control the final CdS nanorod dimensions. Due to the strong electrostatic interactions between the DNA sugar-phosphate backbone and the Cd(2+) ions, crystallographic control of CdS nanostructures is possible using these simple DNA-membrane templates, which we demonstrate using nanobeam electron diffraction experiments on individual templated CdS nanorods.

Aims The optimal management of asymptomatic subjects at intermediate risk of coronary artery disease (CAD) is often uncertain. Re-stratification to a high- or low-risk category may enable optimization of preventative strategies. Coronary computed tomographic angiography (CCTA) enables a minimally invasive assessment of coronary artery plaque quantity and composition. Non-calcified plaque by CCTA is lipid-rich and more vulnerable to rupture and resultant acute coronary syndromes. The purpose of this study was to determine whether novel approaches to CAD risk stratification, such as plasma lipid profiling, may predict non-calcified plaque burden in intermediate risk subjects. Methods and results CCTA and several markers of CAD (including plasma lipid profiling, carotid intima-media thickness, aortic pulse wave velocity, and high-sensitivity C-reactive protein) were prospectively performed in 100 asymptomatic patients at intermediate CAD risk according to the Framingham risk score. Segment stenosis scores (SSS) were calculated to evaluate the burden of total, calcified, and non-calcified coronary artery plaque. Non-calcified plaque was observed in 66 subjects and 158 (11%) of 1425 coronary artery segments. Eighteen lipid species demonstrated significant associations with non-calcified plaque burden, but not with total plaque or calcified plaque burden. No other marker of CAD was found to predict coronary artery plaque burden. Conclusions Plasma lipidomic analysis can predict the burden of non-calcified coronary plaque in asymptomatic subjects at intermediate risk of CAD. Re-stratification of these patients by plasma lipid profiling may enable more appropriate and effective primary prevention management strategies. [ABSTRACT FROM PUBLISHER]

Controlling intestinal lipid absorption is an important strategy for maintaining lipid homeostasis. Accumulation of lipids in the liver is a major risk factor for metabolic syndrome and nonalcoholic fatty liver disease. It is well-known that sphingomyelin (SM) can inhibit intestinal cholesterol absorption. It is, however, unclear if dietary SM also lowers liver lipid levels. In the present study (i) the effect of pure dietary egg SM on hepatic lipid metabolism and intestinal cholesterol absorption was measured with [14C]cholesterol and [3H]sitostanol in male C57BL/6 mice fed a high-fat (HF) diet with or without 0.6% wt/wt SM for 18 days; and (ii) hepatic lipid levels and gene expression were determined in mice given a HF diet with or without egg SM (0.3, 0.6 or 1.2% wt/wt) for 4 weeks. Mice supplemented with SM (0.6% wt/wt) had significantly increased fecal lipid and cholesterol output and reduced hepatic [14C]cholesterol levels after 18 days. Relative to HF-fed mice, SM-supplemented HF-fed mice had significantly lower intestinal cholesterol absorption (−30%). Liver weight was significantly lower in the 1.2% wt/wt SM-supplemented mice (−18%). Total liver lipid (mg/organ) was significantly reduced in the SM-supplemented mice (−33% and −40% in 0.6% wt/wt and 1.2% wt/wt SM, respectively), as were triglyceride and cholesterol levels. The reduction in liver triglycerides was due to inactivation of the LXR-SREBP-1c pathway. In conclusion, dietary egg SM has pronounced hepatic lipid-lowering properties in mice maintained on an obesogenic diet. [ABSTRACT FROM AUTHOR]

Oxidation is associated with conditions related to chronic inflammations and aging. Cubic structures have been observed in the smooth endoplasmic reticulum and mitochondrial membranes of cells under oxidative stress (e.g., tumor cells and virus-infected cells). It has been previously suspected that oxidation can result in the rearrangement of lipids from a fluid lamellar phase to a cubic structure in organelles containing membranes enriched with amphiphiles that have nonzero intrinsic curvature, such as phosphatidylethanolamine (PE) and cardiolipin. This study focuses on the oxidation of 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE), a lipid that natively forms an inverted hexagonal phase at physiological conditions. The oxidized samples contain an approximately 3:2 molar ratio of nonoxidized to oxidized DOPE. Optical microscopy images collected during the hydration of this mixture from a dried film suggest that the system evolves into a coexistence of a stable fluid lamellar phase and transient square lattice structures with unit cell sizes of 500-600 nm. Small-angle X-ray scattering of the same lipid mixture yielded a body-centered Im3m cubic phase with the lattice parameter of 14.04 nm. On average, the effective packing parameter of the oxidized DOPE species was estimated to be 0.657 ' 0.069 (standard deviation). This suggests that the oxidation of PE leads to a group of species with inverted molecular intrinsic curvature. Oxidation can create amphiphilic subpopulations that potently impact the integrity of the membrane, since negative Gaussian curvature intrinsic to cubic phases can enable membrane destabilization processes. [ABSTRACT FROM AUTHOR]