Evaluation of established coronary heart disease on the basis of HDL and non-HDL NMR lipid profiling

Expanding the Molecular Disturbances of Lipoproteins in Cardiometabolic Diseases: Lessons from Lipidomics

The increasing global burden of cardiometabolic diseases highlights the urgent clinical need for better personalized prediction and intervention strategies. Early diagnosis and prevention could greatly reduce the enormous socio-economic burden posed by these states. Plasma lipids including total cholesterol, triglycerides, HDL-C, and LDL-C have been at the center stage of the prediction and prevention strategies for cardiovascular disease; however, the bulk of cardiovascular disease events cannot be explained sufficiently by these lipid parameters. The shift from traditional serum lipid measurements that are poorly descriptive of the total serum lipidomic profile to comprehensive lipid profiling is an urgent need, since a wealth of metabolic information is currently underutilized in the clinical setting. The tremendous advances in the field of lipidomics in the last two decades has facilitated the research efforts to unravel the lipid dysregulation in cardiometabolic diseases, enabling the understanding of the underlying pathophysiological mechanisms and identification of predictive biomarkers beyond traditional lipids. This review presents an overview of the application of lipidomics in the study of serum lipoproteins in cardiometabolic diseases. Integrating the emerging multiomics with lipidomics holds great potential in moving toward this goal.

Circulating Biomarkers for Laboratory Diagnostics of Atherosclerosis-Literature Review

Atherosclerosis is still considered a disease burden with long-term damaging processes towards the cardiovascular system. Evaluation of atherosclerotic stages requires the use of independent markers such as those already considered traditional, that remain the main therapeutic target for patients with atherosclerosis, together with emerging biomarkers. The challenge is finding models of predictive markers that are particularly tailored to detect and evaluate the evolution of incipient vascular lesions. Important advances have been made in this field, resulting in a more comprehensible and stronger linkage between the lipidic profile and the continuous inflammatory process. In this paper, we analysed the most recent data from the literature studying the molecular mechanisms of biomarkers and their involvement in the cascade of events that occur in the pathophysiology of atherosclerosis.

The role of lipids in exosome biology and intercellular communication: Function, analytics and applications

Exosomes are extracellular vesicles that in recent years have received special attention for their regulatory functions in numerous biological processes. Recent evidence suggests a correlation between the composition of exosomes in body fluids and the progression of some disorders, such as cancer, diabetes and neurodegenerative diseases. In consequence, numerous studies have been performed to evaluate the composition of these vesicles, aiming to develop new biomarkers for diagnosis and to find novel therapeutic targets. On their part, lipids represent one of the most important components of exosomes, with important structural and regulatory functions during exosome biogenesis, release, targeting and cellular uptake. Therefore, exosome lipidomics has emerged as an innovative discipline for the discovery of novel lipid species with biomedical applications. This review summarizes the current knowledge about exosome lipids and their roles in exosome biology and intercellular communication. Furthermore, it presents the state-of-the-art analytical procedures used in exosome lipidomics while emphasizing how this emerging discipline is providing new insights for future applications of exosome lipids in biomedicine.

A Review of Lipidomics of Cardiovascular Disease Highlights the Importance of Isolating Lipoproteins

Cutting-edge lipidomic profiling measures hundreds or even thousands of lipids in plasma and is increasingly used to investigate mechanisms of cardiovascular disease (CVD). In this review, we introduce lipidomic techniques, describe distributions of lipids across lipoproteins, and summarize findings on the association of lipids with CVD based on lipidomics. The main findings of 16 cohort studies were that, independent of total and high-density lipoprotein cholesterol (HDL-c), ceramides (d18:1/16:0, d18:1/18:0, and d18:1/24:1) and phosphatidylcholines (PCs) containing saturated and monounsaturated fatty acyl chains are positively associated with risks of CVD outcomes, while PCs containing polyunsaturated fatty acyl chains (PUFA) are inversely associated with risks of CVD outcomes. Lysophosphatidylcholines (LPCs) may be positively associated with risks of CVD outcomes. Interestingly, the distributions of the identified lipids vary across lipoproteins: LPCs are primarily contained in HDLs, ceramides are mainly contained in low-density lipoproteins (LDLs), and PCs are distributed in both HDLs and LDLs. Thus, the potential mechanism behind previous findings may be related to the effect of the identified lipids on the biological functions of HDLs and LDLs. Only eight studies on the lipidomics of HDL and non-HDL particles and CVD outcomes have been conducted, which showed that higher triglycerides (TAGs), lower PUFA, lower phospholipids, and lower sphingomyelin content in HDLs might be associated with a higher risk of coronary heart disease (CHD). However, the generalizability of these studies is a major concern, given that they used case-control or cross-sectional designs in hospital settings, included a very small number of participants, and did not correct for multiple testing or adjust for blood lipids such as HDL-c, low-density lipoprotein cholesterol (LDL-c), or TAGs. Overall, findings from the literature highlight the importance of research on lipidomics of lipoproteins to enhance our understanding of the mechanism of the association between the identified lipids and the risk of CVD and allow the identification of novel lipid biomarkers in HDLs and LDLs, independent of HDL-c and LDL-c. Lipidomic techniques show the feasibility of this exciting research direction, and the lack of high-quality epidemiological studies warrants well-designed prospective cohort studies.

Analytical Evaluation of Low-Field 31P NMR Spectroscopy for Lipid Analysis

We investigate the potential of ³¹P NMR with simple, maintenance-free benchtop spectrometers to probe phospholipids in complex mixtures. ³¹P NMR-based lipidomics has become an important topic in a wide range of applications in food- and health-sciences, and the continuous improvements of compact, maintenance- and cryogen-free instruments opens new opportunities for NMR routine analyses. A prior milestone is the evaluation of the analytical performance provided by ³¹P NMR at low magnetic field. To address this, we assess the ability of state-of-the-art benchtop NMR spectrometers to detect, identify, and quantify several types of phospholipids in mixtures. Relying on heteronuclear cross-polarization experiments, phospholipids can be detected in 2 h with a limit of detection of 0.5 mM at 1 T and 0.2 mM at 2 T, while the headgroups of phosphatidylcholine (PC), phosphatidyl-ethanolamine (PE), phosphatidylinositol (PI), phosphatidylserine (PS), and phosphatidyl-glycerol (PG) can be unambiguously assigned based on 2D ¹H-³¹P total correlated spectroscopy (TOCSY) spectra. Furthermore, two quantitative methods to obtain absolute concentrations are proposed and discussed, and the performance is evaluated regarding precision and accuracy.

Lipidome of plasma lipoproteins and liver is zinc- modulated in High fat diet treated mice

Zinc (Zn) and Zn-transcription Factors regulate the metabolic pathways of lipids and glucose, consequently nutritional zinc deficiency or excess, activates stress pathways and deranges the hepatic metabolism of lipids. High fat diet (HFD) also leads to lipids' profile disorders as well as to intracellular free radicals (FR) accumulation and finally to metabolic stress-syndrome. Study of nutritional Zn effects on the lipidome of plasma lipoproteins and liver, in HFD-mice, was the aim of the present research. Three Zn enriched HF-Diets as follows, 3 mg/kg feed (Zn deficient diet), 30 mg/kg feed (Zn sufficient diet), 300mgZn /kg feed (Zn excess diet) (Mucedola s.r.l Italy-55% cal) were applied respectively to three groups of male wild type (wt) mice (Hybrid F1/F1),C57Bl/6xCBA, one month old, for 10 weeks. Accordingly, mice body weight rate and ¹H-NMR spectrum analysis of liver extracts and plasma HDL and non-HDL lipoproteins were evaluated at the end of the experimental period. It is concluded that Zn sufficient diet (30 mg/Kg Feed) creates a highly protective lipidomic profile on plasma and liver lipoproteins of HFD-mice, related to significantly increased antiatherogenic indicators in lipids' composition, compared to mice in nutritional Zn deficiency or excess.

LipSpin: A New Bioinformatics Tool for Quantitative 1H NMR Lipid Profiling

The structural similarity among lipid species and the low sensitivity and spectral resolution of nuclear magnetic resonance (NMR) have traditionally hampered the routine use of ¹H NMR lipid profiling of complex biological samples in metabolomics, which remains mostly manual and lacks freely available bioinformatics tools. However, ¹H NMR lipid profiling provides fast quantitative screening of major lipid classes (fatty acids, glycerolipids, phospholipids, and sterols) and some individual species and has been used in several clinical and nutritional studies, leading to improved risk prediction models. In this Article, we present LipSpin, a free and open-source bioinformatics tool for quantitative ¹H NMR lipid profiling. LipSpin implements a constrained line shape fitting algorithm based on voigt profiles and spectral templates from spectra of lipid standards, which automates the analysis of severely overlapped spectral regions and lipid signals with complex coupling patterns. LipSpin provides the most detailed quantification of fatty acid families and choline phospholipids in serum lipid samples by ¹H NMR to date. Moreover, analytical and clinical results using LipSpin quantifications conform with other techniques commonly used for lipid analysis.

Applications of nuclear magnetic resonance in lipid analyses: An emerging powerful tool for lipidomics studies

The role of lipids in cell, tissue, and organ physiology is crucial; as many diseases, including cancer, diabetes, neurodegenerative, and infectious diseases, are closely related to absorption and metabolism of lipids. Mass spectrometry (MS) based methods are the most developed powerful tools to study the synthetic pathways and metabolic networks of cellular lipids in biological systems; leading to the birth of an emerging subject lipidomics, which has been extensively reviewed. Nuclear magnetic resonance (NMR), another powerful analytical tool, which allows the visualization of single atoms and molecules, is receiving increasing attention in lipidomics analyses. However, very little work focusing on lipidomic studies using NMR has been critically reviewed. This paper presents a first comprehensive summary of application of ¹H, ¹³C &³¹P NMR in lipids and lipidomics analyses. The scientific basis, principles and characteristic diagnostic peaks assigned to specific atoms/molecular structures of lipids are presented. Applications of 2D NMR in mapping and monitoring of the components and their changes in complex lipids systems, as well as alteration of lipid profiling over disease development are also reviewed. The applications of NMR lipidomics in diseases diagnosis and food adulteration are exemplified.

Detection of Lipid and Amphiphilic Biomarkers for Disease Diagnostics

Rapid diagnosis is crucial to effectively treating any disease. Biological markers, or biomarkers, have been widely used to diagnose a variety of infectious and non-infectious diseases. The detection of biomarkers in patient samples can also provide valuable information regarding progression and prognosis. Interestingly, many such biomarkers are composed of lipids, and are amphiphilic in biochemistry, which leads them to be often sequestered by host carriers. Such sequestration enhances the difficulty of developing sensitive and accurate sensors for these targets. Many of the physiologically relevant molecules involved in pathogenesis and disease are indeed amphiphilic. This chemical property is likely essential for their biological function, but also makes them challenging to detect and quantify in vitro. In order to understand pathogenesis and disease progression while developing effective diagnostics, it is important to account for the biochemistry of lipid and amphiphilic biomarkers when creating novel techniques for the quantitative measurement of these targets. Here, we review techniques and methods used to detect lipid and amphiphilic biomarkers associated with disease, as well as their feasibility for use as diagnostic targets, highlighting the significance of their biochemical properties in the design and execution of laboratory and diagnostic strategies. The biochemistry of biological molecules is clearly relevant to their physiological function, and calling out the need for consideration of this feature in their study, and use as vaccine, diagnostic and therapeutic targets is the overarching motivation for this review.

Lipoprotein subfractions by nuclear magnetic resonance are associated with tumor characteristics in breast cancer

Background

High-Density Lipoprotein (HDL)-cholesterol, has been associated with breast cancer development, but the association is under debate, and whether lipoprotein subfractions is associated with breast tumor characteristics remains unclear.

Methods

Among 56 women with newly diagnosed invasive breast cancer stage I/II, aged 35–75 years, pre-surgery overnight fasting serum concentrations of lipids were assessed, and body mass index (BMI) was measured. All breast tumors were immunohistochemically examined in the surgical specimen. Serum metabolomics of lipoprotein subfractions and their contents of cholesterol, free cholesterol, phospholipids, apolipoprotein-A1 and apolipoprotein-A2, were assessed using nuclear magnetic resonance. Principal component analysis, partial least square analysis, and uni- and multivariable linear regression models were used to study whether lipoprotein subfractions were associated with breast cancer tumor characteristics.

Results

The breast cancer patients had following means: age at diagnosis: 55.1 years; BMI: 25.1 kg/m²; total-Cholesterol: 5.74 mmol/L; HDL-Cholesterol: 1.78 mmol/L; Low-Density Lipoprotein (LDL)-Cholesterol: 3.45 mmol/L; triglycerides: 1.18 mmol/L. The mean tumor size was 16.4 mm, and the mean Ki67 hotspot index was 26.5 %. Most (93 %) of the patients had estrogen receptor (ER) positive tumors (≥1 % ER+), and 82 % had progesterone receptor (PgR) positive tumors (≥10 % PgR+). Several HDL subfraction contents were strongly associated with PgR expression: Apolipoprotein-A1 (β 0.46, CI 0.22–0.69, p < 0.001), HDL cholesterol (β 0.95, CI 0.51–1.39, p < 0.001), HDL free cholesterol (β 2.88, CI 1.28–4.48, p = 0.001), HDL phospholipids (β 0.70, CI 0.36–1.04, p < 0.001). Similar results were observed for the subfractions of HDL1-3. We observed inverse associations between HDL phospholipids and Ki67 (β -0.25, p = 0.008), and in particular between HDL1’s contents of cholesterol, phospholipids, apolipoprotein-A1, apolipoprotein-A2 and Ki67. No association was observed between lipoproteins and ER expression.

Conclusion

Our findings hypothesize associations between different lipoprotein subfractions, and PgR expression, and Ki 67 % in breast tumors. These findings may have clinical implications, but require confirmation in larger studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12944-016-0225-4) contains supplementary material, which is available to authorized users.

Dysfunctional High-Density Lipoprotein: An Innovative Target for Proteomics and Lipidomics

High-Density Lipoprotein-Cholesterol (HDL-C) is regarded as an important protective factor against cardiovascular disease, with abundant evidence of an inverse relationship between its serum levels and risk of cardiovascular disease, as well as various antiatherogenic, antioxidant, and anti-inflammatory properties. Nevertheless, observations of hereditary syndromes featuring scant HDL-C concentration in absence of premature atherosclerotic disease suggest HDL-C levels may not be the best predictor of cardiovascular disease. Indeed, the beneficial effects of HDL may not depend solely on their concentration, but also on their quality. Distinct subfractions of this lipoprotein appear to be constituted by specific protein-lipid conglomerates necessary for different physiologic and pathophysiologic functions. However, in a chronic inflammatory microenvironment, diverse components of the HDL proteome and lipid core suffer alterations, which propel a shift towards a dysfunctional state, where HDL-C becomes proatherogenic, prooxidant, and proinflammatory. This heterogeneity highlights the need for further specialized molecular studies in this aspect, in order to achieve a better understanding of this dysfunctional state; with an emphasis on the potential role for proteomics and lipidomics as valuable methods in the search of novel therapeutic approaches for cardiovascular disease.