Lipidomics in diabetes and the metabolic syndrome

Tandem Mass Spectrometry in Untargeted Lipidomics: A Case Study of Peripheral Blood Mononuclear Cells

Peripheral blood mononuclear cells (PBMCs), including lymphocytes, are important components of the human immune system. These cells contain a diverse array of lipids, primarily glycerophospholipids (GPs) and sphingolipids (SPs), which play essential roles in cellular structure, signaling, and programmed cell death. This study presents a detailed analysis of GP and SP profiles in human PBMC samples using tandem mass spectrometry (MS/MS). Hydrophilic interaction liquid chromatography (HILIC) and electrospray ionization (ESI) coupled with linear ion-trap MS/MS were employed to investigate the diagnostic fragmentation patterns that aided in determining regiochemistry in complex lipid extracts. Specifically, the study explored the fragmentation patterns of various lipid species, including phosphatidylcholines (PCs), phosphatidylethanolamines (PEs), their plasmalogen and lyso forms, phosphatidylserines (PSs), phosphatidylinositols (PIs), phosphatidylglycerols (PGs), sphingomyelins (SMs), and dihexosylceramides (Hex2Cer). Our comprehensive analysis led to the characterization of over 200 distinct lipid species, significantly expanding our understanding of PBMC lipidome complexity. A freely available spreadsheet tool for simulating MS/MS spectra of GPs is provided, enhancing the accessibility and reproducibility of this research. This study advances our knowledge of PBMC lipidomes and establishes a robust analytical framework for future investigations in lipidomics.

Ion mobility spectrometry and ion mobility-mass spectrometry in clinical chemistry

Advancements in clinical chemistry have major implications in terms of public health, prompting many clinicians to seek out chemical information to aid in diagnoses and treatments. While mass spectrometry (MS) and hyphenated-MS techniques such as LC-MS or tandem MS/MS have long been the analytical methods of choice for many clinical applications, these methods routinely demonstrate difficulty in differentiating between isomeric forms in complex matrices. Consequently, ion mobility spectrometry (IM), which differentiates molecules on the basis of size, shape, and charge, has demonstrated unique advantages in the broad application of stand-alone IM and hyphenated IM instruments towards clinical challenges. Here, we highlight representative IM applications and approaches and describe contemporary commercial offerings of IM technology and how these can be, or are currently being, applied to the field of clinical chemistry.

Development of a targeted hydrophilic interaction liquid chromatography-tandem mass spectrometry based lipidomics platform applied to a coronavirus disease severity study

The importance of lipids seen in studies of metabolism, cancer, the recent COVID-19 pandemic and other diseases has brought the field of lipidomics to the forefront of clinical research. Quantitative and comprehensive analysis is required to understand biological interactions among lipid species. However, lipidomic analysis is often challenging due to the various compositional structures, diverse physicochemical properties, and wide dynamic range of concentrations of lipids in biological systems. To study the comprehensive lipidome, a hydrophilic interaction liquid chromatography-tandem mass spectrometry (HILIC-MS/MS)-based screening method with 1200 lipid features across 19 (sub)classes, including both nonpolar and polar lipids, has been developed. HILIC-MS/MS was selected due to its class separation property and fatty acyl chain level information. 3D models of class chromatographic retention behavior were established and evaluations of cross-class and within-class interferences were performed to avoid over-reporting these features. This targeted HILIC-MS/MS method was fully validated, with acceptable analytical parameters in terms of linearity, precision, reproducibility, and recovery. The accurate quantitation of 608 lipid species in the SRM 1950 NIST plasma was achieved using multi-internal standards per class and post-hoc correction, extending current databases by providing lipid concentrations resolved at fatty acyl chain level. The overall correlation coefficients (R2) of measured concentrations with values from literature range from 0.64 to 0.84. The applicability of the developed targeted lipidomics method was demonstrated by discovering 520 differential lipid features related to COVID-19 severity. This high coverage and targeted approach will aid in future investigations of the lipidome in various disease contexts.

LC-MS-Based Lipidomic Analysis of Serum Samples from Patients with Type 2 Diabetes Mellitus (T2DM)

Background

With the development of social economy, type 2 diabetes mellitus (T2DM) is becoming a severe health problem globally.

Methods

To systematically understand the lipid metabolism in T2DM, we applied untargeted lipidomics to the serum of T2DM patients and control group using ultrahigh-performance liquid chromatography (UHPLC) coupled with high-resolution mass spectrometry (MS).

Results

Over two thousand molecular features were detected by our approach, of which 222 lipid species in positive ion mode and 145 species in negative were reliably identified based on precise molecular weights and MS/MS patterns. Multivariate analysis was adopted to differentiate T2DM patients and the control group using principal component analysis (PCA) and orthogonal partial least squares discrimination analysis (OPLS-DA). The dysregulated lipid species were found and their significance in pathophysiology was discussed. Correlation analysis of selected lipids and important clinical variables was performed and addressed.

Conclusions

This study unveils several new lipids and pathways considerably involved in T2DM and provides novel insights into understanding the pathogenesis underlying T2DM.

Cell and Tissue Imaging by TOF-SIMS and MALDI-TOF: An Overview for Biological and Pharmaceutical Analysis

The potential of mass spectrometry imaging (MSI) has been demonstrated in cell and tissue research since 1970. MSI can reveal the spatial distribution of a wide range of atomic and molecular ions detected from biological sample surfaces, it is a powerful and valuable technique used to monitor and detect diverse chemical and biological compounds, such as drugs, lipids, proteins, and DNA. MSI techniques, notably matrix-assisted laser desorption/ionization time of flight (MALDI-TOF) and time of flight secondary ion mass spectrometry (TOF-SIMS), witnessed a dramatic upsurge in studying and investigating biological samples especially, cells and tissue sections. This advancement is attributed to the submicron lateral resolution, the high sensitivity, the good precision, and the accurate chemical specificity, which make these techniques suitable for decoding and understanding complex mechanisms of certain diseases, as well as monitoring the spatial distribution of specific elements, and compounds. While the application of both techniques for the analysis of cells and tissues is thoroughly discussed, a briefing of MALDI-TOF and TOF-SIMS basis and the adequate sampling before analysis are briefly covered. The importance of MALDI-TOF and TOF-SIMS as diagnostic tools and robust analytical techniques in the medicinal, pharmaceutical, and toxicology fields is highlighted through representative published studies.

Development and Application of Multidimensional Lipid Libraries to Investigate Lipidomic Dysregulation Related to Smoke Inhalation Injury Severity

The implication of lipid dysregulation in diseases, toxic exposure outcomes, and inflammation has brought great interest to lipidomic studies. However, lipids have proven to be analytically challenging due to their highly isomeric nature and vast concentration ranges in biological matrices. Therefore, multidimensional techniques such as those integrating liquid chromatography, ion mobility spectrometry, collision-induced dissociation, and mass spectrometry (LC-IMS-CID-MS) have been implemented to separate lipid isomers as well as provide structural information and increased identification confidence. These data sets are however extremely large and complex, resulting in challenges for data processing and annotation. Here, we have overcome these challenges by developing sample-specific multidimensional lipid libraries using the freely available software Skyline. Specifically, the human plasma library developed for this work contains over 500 unique lipids and is combined with adapted Skyline functions such as indexed retention time (iRT) for retention time prediction and IMS drift time filtering for enhanced selectivity. For comparison with other studies, this database was used to annotate LC-IMS-CID-MS data from a NIST SRM 1950 extract. The same workflow was then utilized to assess plasma and bronchoalveolar lavage fluid (BALF) samples from patients with varying degrees of smoke inhalation injury to identify lipid-based patient prognostic and diagnostic markers.

Coupling Machine Learning and Lipidomics as a Tool to Investigate Metabolic Dysfunction-Associated Fatty Liver Disease. A General Overview

Hepatic biopsy is the gold standard for staging nonalcoholic fatty liver disease (NAFLD). Unfortunately, accessing the liver is invasive, requires a multidisciplinary team and is too expensive to be conducted on large segments of the population. NAFLD starts quietly and can progress until liver damage is irreversible. Given this complex situation, the search for noninvasive alternatives is clinically important. A hallmark of NAFLD progression is the dysregulation in lipid metabolism. In this context, recent advances in the area of machine learning have increased the interest in evaluating whether multi-omics data analysis performed on peripheral blood can enhance human interpretation. In the present review, we show how the use of machine learning can identify sets of lipids as predictive biomarkers of NAFLD progression. This approach could potentially help clinicians to improve the diagnosis accuracy and predict the future risk of the disease. While NAFLD has no effective treatment yet, the key to slowing the progression of the disease may lie in predictive robust biomarkers. Hence, to detect this disease as soon as possible, the use of computational science can help us to make a more accurate and reliable diagnosis. We aimed to provide a general overview for all readers interested in implementing these methods.

Complementing Matrix-Assisted Laser Desorption Ionization-Mass Spectrometry Imaging with Chromatography Data for Improved Assignment of Isobaric and Isomeric Phospholipids Utilizing Trapped Ion Mobility-Mass Spectrometry

Lipids, such for example the multifaceted category of glycerophospholipids (GP), play a major role in many biological processes. High-resolution mass spectrometry is able to identify these highly diverse lipid species in combination with fragmentation experiments (MS/MS) on the basis of the accurate m/z and fragmentation pattern. However, for the differentiation of isomeric lipids or isobaric interferences, more elaborate separation methods are required. Especially for imaging techniques, such as matrix-assisted laser desorption/ionization (MALDI)-MS imaging, the identification is often exclusively based on the accurate m/z. Fragmentation via MS/MS increases the confidence in lipid annotation in imaging approaches. However, this is sometimes not feasible due to insufficient sensitivity and significantly prolonged analysis time. The use of a separation dimension such as trapped ion mobility spectrometry (TIMS) after ionization strengthens the confidence of the identification based on the collision cross section (CCS). Since CCS libraries are limited, a tissue-specific database was initially generated using hydrophilic interaction liquid chromatography-TIMS-MS. Using this database, the identification of isomeric lipid classes as well as isobaric interferences in a lipid class was performed using a mouse spleen sample in a workflow described in this study. Besides a CCS-based identification as an additional identification criterion for GP in general, the focus was on the distinction of the isomeric GP classes phosphatidylglycerol and bis(monoacylglycero)phosphate, as well as the differentiation of possible isobaric interferences based on the formation of adducts by MALDI-TIMS-MS imaging on a molecular level.

Lipid-based biomarkers for CVD, COPD, and aging - A translational perspective

For many diseases, there is an unmet need for new or better biomarkers for improved disease risk assessment and monitoring, as available markers lack sufficient specificity. Lipids are drawing major interest as potential candidates for filling these gaps. This has recently been demonstrated by the identification of selective ceramides for prediction of cardiovascular mortality, enabling improved risk assessment of cardiovascular disease compared with conventional clinical markers. In this review, we discuss current lipid biomarker findings and the possible connection between cardiovascular disease, chronic obstructive pulmonary disease, and aging. Moreover, we discuss how to overcome the current roadblocks facing lipid biomarker research. We stress the need for improved quantification, standardization of methodologies, and establishment of initial reference values to allow for an efficient transfer path of research findings into the clinical landscape, and, ultimately, to put newly identified biomarkers into practical use.

Lipid Annotator: Towards Accurate Annotation in Non-Targeted Liquid Chromatography High-Resolution Tandem Mass Spectrometry (LC-HRMS/MS) Lipidomics Using A Rapid and User-Friendly Software

Lipidomics has great promise in various applications; however, a major bottleneck in lipidomics is the accurate and comprehensive annotation of high-resolution tandem mass spectral data. While the number of available lipidomics software has drastically increased over the past five years, the reduction of false positives and the realization of obtaining structurally accurate annotations remains a significant challenge. We introduce Lipid Annotator, which is a user-friendly software for lipidomic analysis of data collected by liquid chromatography high-resolution tandem mass spectrometry (LC-HRMS/MS). We validate annotation accuracy against lipid standards and other lipidomics software. Lipid Annotator was integrated into a workflow applying an iterative exclusion MS/MS acquisition strategy to National Institute of Standards and Technology (NIST) SRM 1950 Metabolites in Frozen Human Plasma using reverse phase LC-HRMS/MS. Lipid Annotator, LipidMatch, and MS-DIAL produced consensus annotations at the level of lipid class for 98% and 96% of features detected in positive and negative mode, respectively. Lipid Annotator provides percentages of fatty acyl constituent species and employs scoring algorithms based on probability theory, which is less subjective than the tolerance and weighted match scores commonly used by available software. Lipid Annotator enables analysis of large sample cohorts and improves data-processing throughput as compared to previous lipidomics software.

Advances in Research on Diabetes by Human Nutriomics

The incidence and prevalence of diabetes mellitus (DM) have increased rapidly worldwide over the last two decades. Because the pathogenic factors of DM are heterogeneous, determining clinically effective treatments for DM patients is difficult. Applying various nutrient analyses has yielded new insight and potential treatments for DM patients. In this review, we summarized the omics analysis methods, including nutrigenomics, nutritional-metabolomics, and foodomics. The list of the new targets of SNPs, genes, proteins, and gut microbiota associated with DM has been obtained by the analysis of nutrigenomics and microbiomics within last few years, which provides a reference for the diagnosis of DM. The use of nutrient metabolomics analysis can obtain new targets of amino acids, lipids, and metal elements, which provides a reference for the treatment of DM. Foodomics analysis can provide targeted dietary strategies for DM patients. This review summarizes the DM-associated molecular biomarkers in current applied omics analyses and may provide guidance for diagnosing and treating DM.

Lipidomic analysis of urinary exosomes from hereditary α-tryptasemia patients and healthy volunteers

Exosomes are nano‐sized vesicles that are involved in various biological processes including cell differentiation, proliferation, signaling, and intercellular communication. Urinary exosomes were isolated from a cohort of hereditary α‐tryptasemia (HαT) patients and from healthy volunteers. There was a greater number of exosomes isolated from the urine in the HαT group compared to the control volunteers. Here, we investigated the differences in both lipid classes and lipid species within urinary exosomes of the two groups. Lipids were extracted from urinary exosomes and subjected to liquid chromatography mass spectrometry using a targeted approach. Various molecular species of glycerophospholipids, glycerolipids, and sterols were significantly reduced in HαT patients. Out of a possible 1127 lipids, 521 lipid species were detected, and relative quantities were calculated. Sixty‐four lipids were significantly reduced in urinary exosomes of HαT patients compared to controls. All significantly reduced sphingolipids and most of the phospholipids were saturated or mono‐unsaturated lipids. These results suggest exosome secretion is augmented in HαT patients and the lipids within these exosomes may be involved in various biological processes. The unique lipid composition of urinary exosomes from HαT patients will contribute to our understanding of the biochemistry of this disease.

Multiple reaction monitoring (MRM)-profiling with biomarker identification by LC-QTOF to characterize coronary artery disease

Metabolite profiling by mass spectrometry (MS) is an area of interest for disease diagnostics, biomarker discovery, and therapeutic evaluation. A recently developed approach, multiple reaction monitoring (MRM)-profiling, searches for metabolites with precursor (Prec) and neutral loss (NL) scans in a representative sample and creates a list of ion transitions. These are then used in an MRM method for fast screening of individual samples and discrimination between healthy and diseased. A large variety of functional groups are considered and all signals discovered are recorded in the individual samples, making this a largely unsupervised method. MRM-profiling is described here and then demonstrated with data for over 900 human plasma coronary artery disease (CAD) samples. Representative pooled samples for each condition were interrogated using a library of over a hundred Prec and NL scans on a triple quadrupole MS. The data from the Prec and NL experiments were converted into ion transitions, initially some 1266 transitions. Each ion transition was examined in the individual samples on a time scale of milliseconds per transition, which allows for rapid screening of large sample sets (<5 days for 1000 samples). Use of univariate and multivariate statistics allowed classification of the sample set with high accuracy. The metabolite profiles classified the CAD female, CAD male, and peripheral artery disease (PAD) samples relative to controls with an accuracy of 90%, 78%, and 85%, respectively. The compounds responsible for informative ion transitions were identified by chromatography and high resolution MS; some have been previously reported and found to be associated with coronary artery disease metabolism, indicating that the methodology generates a meaningful metabolite profile while being faster than traditional methodologies.

Challenges in Mass Spectrometry-based Lipidomics of Neutral Lipids

Mass spectrometry has played a critical role in the identification and quantitation of neutral lipids such as cholesteryl esters and triacylglycerols present in biological extracts. Various strategies have emerged in order to carry out such lipidomics studies since a large number of neutral lipid molecular species exist in tissues. These include both shotgun approaches as well as those engaging liquid chromatographic separation of species prior to mass spectrometric analysis. Nonetheless challenges remain at every level of the lipidomics experiment, including extraction of lipids, identification of specific species, and quantitation of the vast array of lipids present in the sample extract. Unambiguous identification of molecular species present (qualitative analysis) as well as precise quantitation remains as significant challenges. The relative quantitation enables quite accurate assessment of fold changes of complex lipid species without exact quantitation. The availability of reference standard material as well as relevant internal standards continue to be limited.

Pathophysiology of mitochondrial lipid oxidation: Role of 4-hydroxynonenal (4-HNE) and other bioactive lipids in mitochondria

Mitochondrial lipids are essential for maintaining the integrity of mitochondrial membranes and the proper functions of mitochondria. As the "powerhouse" of a cell, mitochondria are also the major cellular source of reactive oxygen species (ROS). Oxidative stress occurs when the antioxidant system is overwhelmed by overproduction of ROS. Polyunsaturated fatty acids in mitochondrial membranes are primary targets for ROS attack, which may lead to lipid peroxidation (LPO) and generation of reactive lipids, such as 4-hydroxynonenal. When mitochondrial lipids are oxidized, the integrity and function of mitochondria may be compromised and this may eventually lead to mitochondrial dysfunction, which has been associated with many human diseases including cancer, cardiovascular diseases, diabetes, and neurodegenerative diseases. How mitochondrial lipids are oxidized and the underlying molecular mechanisms and pathophysiological consequences associated with mitochondrial LPO remain poorly defined. Oxidation of the mitochondria-specific phospholipid cardiolipin and generation of bioactive lipids through mitochondrial LPO has been increasingly recognized as an important event orchestrating apoptosis, metabolic reprogramming of energy production, mitophagy, and immune responses. In this review, we focus on the current understanding of how mitochondrial LPO and generation of bioactive lipid mediators in mitochondria are involved in the modulation of mitochondrial functions in the context of relevant human diseases associated with oxidative stress.

Assessment of altered lipid homeostasis by HILIC-ion mobility-mass spectrometry-based lipidomics

Ion mobility-mass spectrometry (IM-MS) has proven to be a highly informative technique for the characterization of lipids from cells and tissues. We report the combination of hydrophilic-interaction liquid chromatography (HILIC) with traveling-wave IM-MS (TWIM-MS) for comprehensive lipidomics analysis. Main lipid categories such as glycerolipids, sphingolipids, and glycerophospholipids are separated on the basis of their lipid backbones in the IM dimension, whereas subclasses of each category are mostly separated on the basis of their headgroups in the HILIC dimension, demonstrating the orthogonality of HILIC and IM separations. Using our previously established lipid calibrants for collision cross-section (CCS) measurements in TWIM, we measured over 250 CCS values covering 12 lipid classes in positive and negative modes. The coverage of the HILIC-IM-MS method is demonstrated in the analysis of Neuro2a neuroblastoma cells exposed to benzalkonium chlorides (BACs) with C10 or C16 alkyl chains, which we have previously shown to affect gene expression related to cholesterol and lipid homeostasis. We found that BAC exposure resulted in significant changes to several lipid classes, including glycerides, sphingomyelins, phosphatidylcholines, and phosphatidylethanolamines. Our results indicate that BAC exposure modifies lipid homeostasis in a manner that is dependent upon the length of the BAC alkyl chain.

Lipidomics-Reshaping the Analysis and Perception of Type 2 Diabetes

As a consequence of a sedentary lifestyle as well as changed nutritional behavior, today's societies are challenged by the rapid propagation of metabolic disorders. A common feature of diseases, such as obesity and type 2 diabetes (T2D), is the dysregulation of lipid metabolism. Our understanding of the mechanisms underlying these diseases is hampered by the complexity of lipid metabolic pathways on a cellular level. Furthermore, overall lipid homeostasis in higher eukaryotic organisms needs to be maintained by a highly regulated interplay between tissues, such as adipose tissue, liver and muscle. Unraveling pathological mechanisms underlying metabolic disorders therefore requires a diversified approach, integrating basic cellular research with clinical research, ultimately relying on the analytical power of mass spectrometry-based techniques. Here, we discuss recent progress in the development of lipidomics approaches to resolve the pathological mechanisms of metabolic diseases and to identify suitable biomarkers for clinical application. Due to its growing impact worldwide, we focus on T2D to highlight the key role of lipidomics in our current understanding of this disease, discuss remaining questions and suggest future strategies to address them.

Lipidomics for studying metabolism

Many thousands of lipid species exist and their metabolism is interwoven via numerous pathways and networks. These networks can also change in response to cellular environment alterations, such as exercise or development of a disease. Measuring such alterations and understanding the pathways involved is crucial to fully understand cellular metabolism. Such demands have catalysed the emergence of lipidomics, which enables the large-scale study of lipids using the principles of analytical chemistry. Mass spectrometry, largely due to its analytical power and rapid development of new instruments and techniques, has been widely used in lipidomics and greatly accelerated advances in the field. This Review provides an introduction to lipidomics and describes some common, but important, cellular metabolic networks that can aid our understanding of metabolic pathways. Some representative applications of lipidomics for studying lipid metabolism and metabolic diseases are highlighted, as well as future applications for the use of lipidomics in studying metabolic pathways.

Evaluation of Collision Cross Section Calibrants for Structural Analysis of Lipids by Traveling Wave Ion Mobility-Mass Spectrometry

Collision cross section (CCS) measurement of lipids using traveling wave ion mobility-mass spectrometry (TWIM-MS) is of high interest to the lipidomics field. However, currently available calibrants for CCS measurement using TWIM are predominantly peptides that display quite different physical properties and gas-phase conformations from lipids, which could lead to large CCS calibration errors for lipids. Here we report the direct CCS measurement of a series of phosphatidylcholines (PCs) and phosphatidylethanolamines (PEs) in nitrogen using a drift tube ion mobility (DTIM) instrument and an evaluation of the accuracy and reproducibility of PCs and PEs as CCS calibrants for phospholipids against different classes of calibrants, including polyalanine (PolyAla), tetraalkylammonium salts (TAA), and hexakis(fluoroalkoxy)phosphazines (HFAP), in both positive and negative modes in TWIM-MS analysis. We demonstrate that structurally mismatched calibrants lead to larger errors in calibrated CCS values while the structurally matched calibrants, PCs and PEs, gave highly accurate and reproducible CCS values at different traveling wave parameters. Using the lipid calibrants, the majority of the CCS values of several classes of phospholipids measured by TWIM are within 2% error of the CCS values measured by DTIM. The development of phospholipid CCS calibrants will enable high-accuracy structural studies of lipids and add an additional level of validation in the assignment of identifications in untargeted lipidomics experiments.

Aliphatic chain length by isotropic mixing (ALCHIM): determining composition of complex lipid samples by ¹H NMR spectroscopy

Quantifying the amounts and types of lipids present in mixtures is important in fields as diverse as medicine, food science, and biochemistry. Nuclear magnetic resonance (NMR) spectroscopy can quantify the total amounts of saturated and unsaturated fatty acids in mixtures, but identifying the length of saturated fatty acid or the position of unsaturation by NMR is a daunting challenge. We have developed an NMR technique, aliphatic chain length by isotropic mixing, to address this problem. Using a selective total correlation spectroscopy technique to excite and transfer magnetization from a resolved resonance, we demonstrate that the time dependence of this transfer to another resolved site depends linearly on the number of aliphatic carbons separating the two sites. This technique is applied to complex natural mixtures allowing the identification and quantification of the constituent fatty acids. The method has been applied to whole adipocytes demonstrating that it will be of great use in studies of whole tissues.

Lipidomics Profiling and Risk of Cardiovascular Disease in the Prospective Population-Based Bruneck Study

Background—

The bulk of cardiovascular disease risk is not explained by traditional risk factors. Recent advances in mass spectrometry allow the identification and quantification of hundreds of lipid species. Molecular lipid profiling by mass spectrometry may improve cardiovascular risk prediction.

Methods and Results—

Lipids were extracted from 685 plasma samples of the prospective population-based Bruneck Study (baseline evaluation in 2000). One hundred thirty-five lipid species from 8 different lipid classes were profiled by shotgun lipidomics with the use of a triple-quadrupole mass spectrometer. Levels of individual species of cholesterol esters (CEs), lysophosphatidylcholines, phosphatidylcholines, phosphatidylethanolamines (PEs), sphingomyelins, and triacylglycerols (TAGs) were associated with cardiovascular disease over a 10-year observation period (2000–2010, 90 incident events). Among the lipid species with the strongest predictive value were TAGs and CEs with a low carbon number and double-bond content, including TAG(54:2) and CE(16:1), as well as PE(36:5) ( P =5.1×10 −7 , 2.2×10 −4 , and 2.5×10 −3 , respectively). Consideration of these 3 lipid species on top of traditional risk factors resulted in improved risk discrimination and classification for cardiovascular disease (cross-validated ΔC index, 0.0210 [95% confidence interval, 0.0010-0.0422]; integrated discrimination improvement, 0.0212 [95% confidence interval, 0.0031-0.0406]; and continuous net reclassification index, 0.398 [95% confidence interval, 0.175-0.619]). A similar shift in the plasma fatty acid composition was associated with cardiovascular disease in the UK Twin Registry (n=1453, 45 cases).

Conclusions—

This study applied mass spectrometry-based lipidomics profiling to population-based cohorts and identified molecular lipid signatures for cardiovascular disease. Molecular lipid species constitute promising new biomarkers that outperform the conventional biochemical measurements of lipid classes currently used in clinics.

Development of an automated multi-injection shotgun lipidomics approach using a triple quadrupole mass spectrometer

Shotgun lipidomics is a well-suited approach to monitor lipid alterations due to its ability to scan for varying lipid types on a global, class and individual species level. However, the ability to perform high-throughput shotgun lipidomics has remained challenging due to time-consuming data processing and hardware limitations. To increase the throughput nature of shotgun lipidomics, an automated shotgun lipidomics approach is described utilizing conventional low flow gradient liquid chromatography (LC) analysis (post-injection) coupled with multiple sample injections per sample (on a lipid scan per injection basis). The proposed automated multi-injection approach resulted in a reproducible lipid scanning period of 2.5 min (in a 4.5 min total data acquisition period), thereby providing a sufficient scanning period for performing either mass spectrometric or tandem mass spectrometric analyses. In addition to being simple, robust and reproducible, this approach was also constructed to be cost-effective by using common LC instrumentation and customizable as the data acquisition period can be tailored to perform different scan types, period lengths and scan numbers. Combined with a strategy to create multiple lipid-specific aliquots per sample, the overall approach provides a simple and efficient platform to perform high-throughput lipid profiling.

First-in-class cardiolipin-protective compound as a therapeutic agent to restore mitochondrial bioenergetics

A decline in energy is common in aging, and the restoration of mitochondrial bioenergetics may offer a common approach for the treatment of numerous age-associated diseases. Cardiolipin is a unique phospholipid that is exclusively expressed on the inner mitochondrial membrane where it plays an important structural role in cristae formation and the organization of the respiratory complexes into supercomplexes for optimal oxidative phosphorylation. The interaction between cardiolipin and cytochrome c determines whether cytochrome c acts as an electron carrier or peroxidase. Cardiolipin peroxidation and depletion have been reported in a variety of pathological conditions associated with energy deficiency, and cardiolipin has been identified as a target for drug development. This review focuses on the discovery and development of the first cardiolipin-protective compound as a therapeutic agent. SS-31 is a member of the Szeto-Schiller (SS) peptides known to selectively target the inner mitochondrial membrane. SS-31 binds selectively to cardiolipin via electrostatic and hydrophobic interactions. By interacting with cardiolipin, SS-31 prevents cardiolipin from converting cytochrome c into a peroxidase while protecting its electron carrying function. As a result, SS-31 protects the structure of mitochondrial cristae and promotes oxidative phosphorylation. SS-31 represents a new class of compounds that can recharge the cellular powerhouse and restore bioenergetics. Extensive animal studies have shown that targeting such a fundamental mechanism can benefit highly complex diseases that share a common pathogenesis of bioenergetics failure. This review summarizes the mechanisms of action and therapeutic potential of SS-31 and provides an update of its clinical development programme.

Plasma lipidome is independently associated with variability in metabolic syndrome in Mexican American families

Plasma lipidome is now increasingly recognized as a potentially important marker of chronic diseases, but the exact extent of its contribution to the interindividual phenotypic variability in family studies is unknown. Here, we used the rich data from the ongoing San Antonio Family Heart Study (SAFHS) and developed a novel statistical approach to quantify the independent and additive value of the plasma lipidome in explaining metabolic syndrome (MS) variability in Mexican American families recruited in the SAFHS. Our analytical approach included two preprocessing steps: principal components analysis of the high-resolution plasma lipidomics data and construction of a subject-subject lipidomic similarity matrix. We then used the Sequential Oligogenic Linkage Analysis Routines software to model the complex family relationships, lipidomic similarities, and other important covariates in a variance components framework. Our results suggested that even after accounting for the shared genetic influences, indicators of lipemic status (total serum cholesterol, TGs, and HDL cholesterol), and obesity, the plasma lipidome independently explained 22% of variability in the homeostatic model of assessment-insulin resistance trait and 16% to 22% variability in glucose, insulin, and waist circumference. Our results demonstrate that plasma lipidomic studies can additively contribute to an understanding of the interindividual variability in MS.

Long-term performance and stability of molecular shotgun lipidomic analysis of human plasma samples

The stability of the lipid concentration levels in shotgun lipidomics analysis was tracked over a period of 3.5 years. Concentration levels in several lipid classes, such as phospholipids, were determined in human plasma lipid extracts. Impact of the following factors on the analysis was investigated: sample amount, internal standard amount, and sample dilution factor. Moreover, the reproducibility of lipid profiles obtained in both polarity modes was evaluated. Total number of samples analyzed was approximately 6800 and 7300 samples in negative and positive ion modes, respectively, out of which 610 and 639 instrument control samples were used in stability calculations. The assessed shotgun lipidomics approach showed to be remarkably robust and reproducible, requiring no batch corrections. Coefficients of variation (CVs) of lipid mean concentration measured with optimized analytical parameters were typically less than 15%. The high reproducibility indicated that no lipid degradation occurred during the monitored time period.

A hyphenated microLC-Q-TOF-MS platform for exosomal lipidomics investigations: application to RCC urinary exosomes

Urinary exosomes are released from every renal epithelial cell type facing the urinary space and therefore, they may carry molecular markers of renal dysfunction and structural injury. Here, we present a hyphenated microLC-Q-TOF-MS platform for lipidomics studies applied to investigate the urinary exosome lipid repertoire. Lipids were separated by reversed-phase chromatography using a linear gradient of formic acid 0.2% and tetrahydrofuran, in 40 min of analysis. Features (m/z with associated own retention time) were extracted by MarkerLynx(TM) (Waters) and processed, demonstrating good analytical performance in terms of repeatability and mass accuracy of the microLC Q-TOF MS platform. In particular, a stable retention time (RSD less than 4%) and relative intensity (RSD from 2.9% to 11%) were observed. Moreover, the method takes advantages by the use of a lock spray interface (Waters) that allows readjusting the m/z data after acquisition, obtaining inaccuracy below 6 ppm in measuring the m/z value of the reference compound during chromatographic run. The method was employed in a preliminary application to perform comparative analysis from healthy control subjects and renal cell carcinoma (RCC) patients, in order to possibly highlight differences in lipid composition to be exploited as potential tumor biomarker. Differential lipid composition in RCC urinary exosomes was achieved and tentatively identified by accurate mass, providing a preliminary indication of a relationship between lipid composition of urinary exosomes and RCC disease. Among the total features significantly different in RCC exosomes, the ion at m/z 502.3 was taken as an example for molecular confirmation by MS/MS fragmentation analysis.

A reversed-phase capillary ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) method for comprehensive top-down/bottom-up lipid profiling

Lipidomics is a critical part of metabolomics and aims to study all the lipids within a living system. We present here the development and evaluation of a sensitive capillary UPLC-MS method for comprehensive top-down/bottom-up lipid profiling. Three different stationary phases were evaluated in terms of peak capacity, linearity, reproducibility, and limit of quantification (LOQ) using a mixture of lipid standards representative of the lipidome. The relative standard deviations of the retention times and peak abundances of the lipid standards were 0.29% and 7.7%, respectively, when using the optimized method. The linearity was acceptable at >0.99 over 3 orders of magnitude, and the LOQs were sub-fmol. To demonstrate the performance of the method in the analysis of complex samples, we analyzed lipids extracted from a human cell line, rat plasma, and a model human skin tissue, identifying 446, 444, and 370 unique lipids, respectively. Overall, the method provided either higher coverage of the lipidome, greater measurement sensitivity, or both, when compared to other approaches of global, untargeted lipid profiling based on chromatography coupled with MS.

Localization of fatty acyl and double bond positions in phosphatidylcholines using a dual stage CID fragmentation coupled with ion mobility mass spectrometry

A high content molecular fragmentation for the analysis of phosphatidylcholines (PC) was achieved utilizing a two-stage [trap (first generation fragmentation) and transfer (second generation fragmentation)] collision-induced dissociation (CID) in combination with travelling-wave ion mobility spectrometry (TWIMS). The novel aspects of this work reside in the fact that a TWIMS arrangement was used to obtain a high level structural information including location of fatty acyl substituents and double bonds for PCs in plasma, and the presence of alkali metal adduct ions such as [M + Li](+) was not required to obtain double bond positions. Elemental compositions for fragment ions were confirmed by accurate mass measurements. A very specific first generation fragment ion m/z 577 (M-phosphoryl choline) from the PC [16:0/18:1 (9Z)] was produced, which by further CID generated acylium ions containing either the fatty acyl 16:0 (C(15)H(31)CO(+), m/z 239) or 18:1 (9Z) (C(17)H(33)CO(+), m/z 265) substituent. Subsequent water loss from these acylium ions was key in producing hydrocarbon fragment ions mainly from the α-proximal position of the carbonyl group such as the hydrocarbon ion m/z 67 (+H(2)C-HC = CH-CH = CH(2)). Formation of these ions was of important significance for determining double bonds in the fatty acyl chains. In addition to this, and with the aid of (13)C labeled lyso-phosphatidylcholine (LPC) 18:1 (9Z) in the ω-position (methyl) TAP fragmentation produced the ion at m/z 57. And was proven to be derived from the α-proximal (carboxylate) or distant ω-position (methyl) in the LPC.

Shotgun lipidomics on high resolution mass spectrometers

Despite their compositional complexity, lipidomes comprise a large number of isobaric species that cannot be distinguished by conventional low resolution mass spectrometry and therefore in-depth MS/MS analysis was required for their accurate quantification. Here we argue that the progress in high resolution mass spectrometry is changing the concept of lipidome characterization. Because exact masses of isobaric species belonging to different lipid classes are not necessarily identical, they can now be distinguished and directly quantified in total lipid extracts. By streamlining and simplifying the molecular characterization of lipidomes, high resolution mass spectrometry has developed into a generic tool for cell biology and molecular medicine.

High throughput quantitative molecular lipidomics

Applications in biomedical research increasingly demand detailed lipid molecule information acquired at high throughput. Although the recent advances in lipidomics offer to delineate the lipidomes in detail, the challenge remains in performing such analyses at the requested quality and to maintain the quality also in a high throughput setting. In this review we describe a high throughput molecular lipidomic solution based on robotic assisted sample preparation and lipid extraction and multiple lipidomic platforms integrated with a sophisticated bioinformatics system. As demonstrated, the virtue of this lipidomic toolkit lies in its high throughput delivery of comprehensive quantitative lipidomic outputs at the molecular lipid level, its ease of scalability and its capability to serve in a regulatory setting. We anticipate that this toolkit will contribute to basic research, nutritional research and promote the discovery of new disease biomarkers, disease related mechanisms of actions and drug targets.

Lipidomic investigations for the characterization of circulating serum lipids in multiple sclerosis

Multiple Sclerosis (MS) is a neurodegenerative autoimmune demyelinating disease affecting young adults. The aetiology still remains a mystery and diagnosis is impaired by the lack of defined molecular markers. Autoimmune response remains the main topic under investigation and recent studies suggest additional non-proteic mediators of brain inflammation such as lipids. We carried out an LC-MS based lipidomics approach to highlight serum lipids profiling in MS. Method was optimised and applied in a preliminary clinical cross-sectional investigation of MS patients vs Healthy Controls (HC) and patients with Other Neurological Diseases (OND). Ten significant metabolites were highlighted and tentatively identified by accurate mass and MS/MS experiments. Our most relevant data show altered level of lyso-glycerophosphatidylcholine (lysoPC) and glycerophosphatidylcholine (PC) species. Total lysoPC/PC ratio showed significant decrease in pathological groups (MS, OND) and, in addition, MS subjects had a relevant decrease of this ratio also in respect to OND. These findings suggest that there may be an altered phospholipid metabolism in MS that can be evaluated in serum. Some of these features are distinctive and may be considered specific for MS. Our lipidomics data show, for the first time, evidence in serum of a relationship between LysoPC/PC ratio and MS.

Comparative plasma lipidome between human and cynomolgus monkey: are plasma polar lipids good biomarkers for diabetic monkeys?

Background

Non-human primates (NHP) are now being considered as models for investigating human metabolic diseases including diabetes. Analyses of cholesterol and triglycerides in plasma derived from NHPs can easily be achieved using methods employed in humans. Information pertaining to other lipid species in monkey plasma, however, is lacking and requires comprehensive experimental analysis.

Methodologies/Principal Findings

We examined the plasma lipidome from 16 cynomolgus monkey, Macaca fascicularis, using liquid chromatography coupled with mass spectrometry (LC/MS). We established novel analytical approaches, which are based on a simple gradient elution, to quantify polar lipids in plasma including (i) glycerophospholipids (phosphatidylcholine, PC; phosphatidylethanolamine, PE; phosphatidylinositol, PI; phosphatidylglycerol, PG; phosphatidylserine, PS; phosphatidic acid, PA); (ii) sphingolipids (sphingomyelin, SM; ceramide, Cer; Glucocyl-ceramide, GluCer; ganglioside mannoside 3, GM3). Lipidomic analysis had revealed that the plasma of human and cynomolgus monkey were of similar compositions, with PC, SM, PE, LPC and PI constituting the major polar lipid species present. Human plasma contained significantly higher levels of plasmalogen PE species (p<0.005) and plasmalogen PC species (p<0.0005), while cynomolgus monkey had higher levels of polyunsaturated fatty acyls (PUFA) in PC, PE, PS and PI. Notably, cynomolgus monkey had significantly lower levels of glycosphingolipids, including GluCer (p<0.0005) and GM₃ (p<0.0005), but higher level of Cer (p<0.0005) in plasma than human. We next investigated the biochemical alterations in blood lipids of 8 naturally occurring diabetic cynomolgus monkeys when compared with 8 healthy controls.

Conclusions

For the first time, we demonstrated that the plasma of human and cynomolgus monkey were of similar compositions, but contained different mol distribution of individual molecular species. Diabetic monkeys exhibited decreased levels of sphingolipids, which are microdomain-associated lipids and are thought to be associated with insulin sensitivity. Significant increases in PG species, which are precursors for cardiolipin biosynthesis in mitochondria, were found in fasted diabetic monkeys (n = 8).

Multidimensional approaches in LC and MS for phospholipid bioanalysis

The advancement of both LC and MS has contributed significantly to phospholipid analysis. Two major trends of developments have emerged in the past decade: application of dedicated online (or offline) LC–MS techniques including 2D and sophisticated chromatographic separations, and the development of so-called shotgun lipidomics represented by multidimensional MS-based techniques. However, neither of these techniques have been shown to be a universal solution for the increasing demand on the comprehensive information of lipid metabolomics in lipidomics studies. This is partially due to the intrinsic complexity of naturally occurring phospholipids in practice. It is evident that either chromatography or MS has to go multidimensional in order to fulfil this goal. This review focuses on recent developments of multidimensional MS, LC–MS and chromatographic approaches for lipidomics analysis. The perspectives and retrospectives of chromatography and MS in these aspects will be reviewed and discussed.

Analysis of Retina and Erythrocyte Glycerophospholipid Alterations in a Rat Model of Type 1 Diabetes

An automated tandem mass spectrometry based analysis employing precursor ion and neutral loss scans in a triple quadrupole mass spectrometer has been employed to identify and quantify changes in the abundances of glycerophospholipids extracted from retina and erythrocytes in a rat streptozotocin model of type 1 diabetes, 6 weeks and 36 weeks following induction of diabetes, compared to age matched nondiabetic controls. The utility of an 'internal standard' method compared to an 'internal standard free' method for quantification of differences in the abundances of specific lipid ions was evaluated in both retina and erythrocyte lipid extracts. In retina, equivalent results were obtained by using the internal standard and 'internal standard free' methods for quantification. In erythrocytes, the two methods of analysis yielded significantly different results, suggesting that factors intrinsic to particular sample types may influence the outcome of label-free lipidome quantification approaches.Overall increases (~25% to ~35%) in the abundances of major retina glycerophospholipid classes were demonstrated in rats at 6 weeks of diabetes, relative to control animals. However, at 36 weeks of diabetes, subsequent overall decreases in retina glycerophosphocholine and glycerophosphoethanolamine abundances of 16% and 33%, respectively, were observed. Additionally, retina and erythrocyte glycerophosphocholine lipids at both 6 week and 36 weeks of diabetes exhibited increased incorporation of linoleic acid((18:2n6)) and a decrease in docosahexaenoic acid (DHA((22:6n3))) content. Finally, an approximately 5-fold increase in the abundances of specific glycated glycerophosphoethanolamine (Amadori-GPEtn) lipids were observed in the retina of 36 week diabetic rats, with a corresponding 1.6 fold increase of Amadori-GPEtn lipids in diabetic erythrocytes.

Changes of the plasma metabolome during an oral glucose tolerance test: is there more than glucose to look at?

The oral glucose tolerance test (oGTT) is a common tool to provoke a metabolic challenge for scientific purposes, as well as for diagnostic reasons, to monitor the kinetics of glucose and insulin. Here, we aimed to follow the variety of physiological changes of the whole metabolic pattern in plasma during an oGTT in healthy subjects in a nontargeted reversed-phase ultra performance liquid chromatography coupled to electrospray ionization quadrupole time of flight mass spectrometric metabolomics approach. We detected 11,500 metabolite ion masses/individual. Applying multivariate data analysis, four major groups of metabolites have been detected as the most discriminating oGTT biomarkers: free fatty acids (FFA), acylcarnitines, bile acids, and lysophosphatidylcholines. We found in detail 1) a strong decrease of all saturated and monounsaturated FFA studied during the oGTT; 2) a significant faster decline of palmitoleate (C16:1) and oleate (C18:1) FFA levels than their saturated counterparts; 3) a strong relative increase of polyunsaturated fatty acids in the fatty acid pattern at 120 min; and 4) a clear decrease in plasma C10:0, C12:0, and C14:1 acylcarnitine levels. These data reflect the switch from beta-oxidation to glycolysis and fat storage during the oGTT. Moreover, the bile acids glycocholic acid, glycochenodeoxycholic acid, and glycodeoxycholic acid were highly discriminative, showing a biphasic kinetic with a maximum of a 4.5- to 6-fold increase at 30 min after glucose ingestion, a significant decrease over the next 60 min followed by an increase until the end of the oGTT. Lysophosphatidylcholines were also increased significantly. The findings of our metabolomics study reveal detailed insights in the complex physiological regulation of the metabolism during an oGTT offering novel perspectives of this widely used procedure.

Nystatin interferes with the effects of N-methyl-N'-nitro-N-nitrosoguanidine on sphingolipid metabolism in human FL cells

Previously we have shown that an alkylating agent N-methyl-N'-nitro-N-nitrosoguanidine (MNNG) can induce receptor clustering and the activation of a downstream signal molecule NF-kappaB, and that the receptor clustering is associated with changes in sphingolipids metabolism. On the other hand, the polyene antibiotic nystatin can block MNNG-induced receptor clustering. In this study, using a lipidomic approach, we further evaluated whether nystatin influenced the effects of MNNG on sphingolipids metabolism. It was found that nystatin itself induced changes in the sphingolipids profile in human amnion FL cells to a certain extent, including an increase or decrease of some sphingolipid species. Interestingly, nystatin can block, at least partially, the changes of sphingolipids-induced by MNNG. In addition, nystatin can also partially inhibit the activation of NF-kappaB induced by MNNG. Neither MNNG nor nystatin affects the mRNA levels of serine palmitoyltransferase, acid sphingomyelinase (ASM), and sphingomyelin synthase, key enzymes in the sphingolipids biosynthesis pathway. However, MNNG can activate ASM and neutral sphingomyelinase, while nystatin preincubation inhibits the activation. Taken together, these data suggested that nystatin interferes with the effects of MNNG, and might elicit its function through altered sphingolipids metabolism.