Cross-Laboratory Standardization of Preclinical Lipidomics Using Differential Mobility Spectrometry and Multiple Reaction Monitoring

A lipidome landscape of aging in mice

Understanding the molecular mechanisms of aging is crucial for enhancing healthy longevity. We conducted untargeted lipidomics across 13 biological samples from mice at various life stages (2, 12, 19 and 24 months) to explore the potential link between aging and lipid metabolism, considering sex (male or female) and microbiome (specific pathogen-free or germ-free) dependencies. By analyzing 2,704 molecules from 109 lipid subclasses, we characterized common and tissue-specific lipidome alterations associated with aging. For example, the levels of bis(monoacylglycero)phosphate containing polyunsaturated fatty acids increased in various organs during aging, whereas the levels of other phospholipids containing saturated and monounsaturated fatty acids decreased. In addition, we discovered age-dependent sulfonolipid accumulation, absent in germ-free mice, correlating with Alistipes abundance determined by 16S ribosomal RNA gene amplicon sequencing. In the male kidney, glycolipids such as galactosylceramides, galabiosylceramides (Gal2Cer), trihexosylceramides (Hex3Cer), and mono- and digalactosyldiacylglycerols were detected, with two lipid classes-Gal2Cer and Hex3Cer-being significantly enriched in aged mice. Integrated analysis of the kidney transcriptome revealed uridine diphosphate galactosyltransferase 8A (UGT8a), alkylglycerone phosphate synthase and fatty acyl-coenzyme A reductase 1 as potential enzymes responsible for the male-specific glycolipid biosynthesis in vivo, which would be relevant to sex dependency in kidney diseases. Inhibiting UGT8 reduced the levels of these glycolipids and the expression of inflammatory cytokines in the kidney. Our study provides a valuable resource for clarifying potential links between lipid metabolism and aging.

ALISTER - Application for lipid stability evaluation and research

BACKGROUND AND AIMS

In lipidomic and metabolomic studies, pre-analytical pitfalls enhance the risk of misusing resources such as time and money, as samples that are analyzed may not yield accurate or reliable data due to poor sample handling. Guidance and pre-analytic know-how are necessary for translation of omics technologies into routine clinical testing. The present work aims to enable decision making regarding sample stability in every phase of lipidomics- and metabolomics-centered studies.

MATERIALS AND METHODS

Data of multiple pre-analytic studies were aggregated into a database. Flexible approaches for evaluating these data were implemented in an RShiny-based web-application, tailored towards broad applicability in clinical and bioanalytic research.

RESULTS

Our "Application for lipid stability evaluation & research" - ALISTER facilitates decision making on blood sample stability during lipidomic and metabolomic studies, such as biomarker research, analysis of biobank samples and clinical testing. The interactive tool gives sampling recommendations when planning sample collection or aids in the assessment of sample quality of experiments retrospectively.

CONCLUSION

ALISTER is available for use under https://itmp.shinyapps.io/alister/. The application enables and simplifies data-driven decision making concerning pre-analytic blood sample handling and fits the needs of clinical investigations from multiple perspectives.

Deep phenotyping of post-infectious myalgic encephalomyelitis/chronic fatigue syndrome

Post-infectious myalgic encephalomyelitis/chronic fatigue syndrome (PI-ME/CFS) is a disabling disorder, yet the clinical phenotype is poorly defined, the pathophysiology is unknown, and no disease-modifying treatments are available. We used rigorous criteria to recruit PI-ME/CFS participants with matched controls to conduct deep phenotyping. Among the many physical and cognitive complaints, one defining feature of PI-ME/CFS was an alteration of effort preference, rather than physical or central fatigue, due to dysfunction of integrative brain regions potentially associated with central catechol pathway dysregulation, with consequences on autonomic functioning and physical conditioning. Immune profiling suggested chronic antigenic stimulation with increase in naïve and decrease in switched memory B-cells. Alterations in gene expression profiles of peripheral blood mononuclear cells and metabolic pathways were consistent with cellular phenotypic studies and demonstrated differences according to sex. Together these clinical abnormalities and biomarker differences provide unique insight into the underlying pathophysiology of PI-ME/CFS, which may guide future intervention.

Comparing the Extraction Performance in Mouse Plasma of Different Biphasic Methods for Polar and Nonpolar Compounds

Many metabolomic studies are interested in both polar and nonpolar analyses. However, the available sample volume often precludes multiple separate extractions. Therefore, there are major advantages in performing a biphasic extraction and retaining both phases for subsequent separate analyses. To be successful, such approaches require the method to be robust and repeatable for both phases. Hence, we determined the performance of three extraction protocols, plus two variant versions, using 25 μL of commercially available mouse plasma. The preferred option for nonpolar lipids was a modified diluted version of a method employing methyl tert-butyl ether (MTBE) suggested by Matyash and colleagues due to its high repeatability for nonpolar compounds. For polar compounds, the Bligh-Dyer method performs best for sensitivity but with consequentially poorer lipid performance. Overall, the scaled-down version of the MTBE method gave the best overall performance, with high sensitivity for both polar and nonpolar compounds and good repeatability for polar compounds in particular.

HILIC/MS quantitation of low-abundant phospholipids and sphingolipids in human plasma and serum: Dysregulation in pancreatic cancer

A new hydrophilic interaction liquid chromatography - mass spectrometry method is developed for low-abundant phospholipids and sphingolipids in human plasma and serum. The optimized method involves the Cogent Silica type C hydride column, the simple sample preparation by protein precipitation, and the removal of highly abundant lipid classes using the postcolumn valve directed to waste during two elution windows. The method allows a highly confident and sensitive identification of low-abundant lipid classes in human plasma (246 lipid species from 24 lipid subclasses) based on mass accuracy and retention dependencies in both polarity modes. The method is validated for quantitation using two internal standards (if available) for each lipid class and applied to human plasma and serum samples obtained from patients with pancreatic ductal adenocarcinoma (PDAC), healthy controls, and NIST SRM 1950. Multivariate data analysis followed by various statistical projection methods is used to determine the most dysregulated lipids. Significant downregulation is observed for lysophospholipids with fatty acyl composition 16:0, 18:0, 18:1, and 18:2. Distinct trends are observed for phosphatidylethanolamines (PE) in relation to the bonding type of fatty acyls, where most PE with acyl bonds are upregulated, while ether/plasmenyl PE are downregulated. For the sphingolipid category, sphingolipids with very long N-acyl chains are downregulated, while sphingolipids with shorter N-acyl chains were upregulated in PDAC. These changes are consistently observed for various classes of sphingolipids, ranging from ceramides to glycosphingolipids, indicating a possible metabolic disorder in ceramide biosynthesis caused by PDAC.

A polyphenol-rich plant extract prevents hypercholesterolemia and modulates gut microbiota in western diet-fed mice

Introduction

Totum-070 is a combination of five plant extracts enriched in polyphenols to target hypercholesterolemia, one of the main risk factors for cardiovascular diseases. The aim of this study was to investigate the effects of Totum-070 on cholesterol levels in an animal model of diet-induced hypercholesterolemia.

Methods

C57BL/6JOlaHsd male mice were fed a Western diet and received Totum-070, or not, by daily gavage (1g/kg and 3g/kg body weight) for 6 weeks.

Results

The Western diet induced obesity, fat accumulation, hepatic steatosis and increased plasma cholesterol compared with the control group. All these metabolic perturbations were alleviated by Totum-070 supplementation in a dose-dependent manner. Lipid excretion in feces was higher in mice supplemented with Totum-070, suggesting inhibition of intestinal lipid absorption. Totum-070 also increased the fecal concentration of short chain fatty acids, demonstrating a direct effect on intestinal microbiota.

Discussion

The characterization of fecal microbiota by 16S amplicon sequencing showed that Totum-070 supplementation modulated the dysbiosis associated with metabolic disorders. Specifically, Totum-070 increased the relative abundance of Muribaculum (a beneficial bacterium) and reduced that of Lactococcus (a genus positively correlated with increased plasma cholesterol level). Together, these findings indicate that the cholesterol-lowering effect of Totum-070 bioactive molecules could be mediated through multiple actions on the intestine and gut microbiota.

Ethnic Disparities in Lipid Metabolism and Clinical Outcomes between Dutch South Asians and Dutch White Caucasians with Type 2 Diabetes Mellitus

Type 2 diabetes mellitus (T2DM) poses a higher risk for complications in South Asian individuals compared to other ethnic groups. To shed light on potential mediating factors, we investigated lipidomic changes in plasma of Dutch South Asians (DSA) and Dutch white Caucasians (DwC) with and without T2DM and explore their associations with clinical features. Using a targeted quantitative lipidomics platform, monitoring over 1000 lipids across 17 classes, along with 1H NMR based lipoprotein analysis, we studied 51 healthy participants (21 DSA, 30 DwC) and 92 T2DM patients (47 DSA, 45 DwC) from the MAGNetic resonance Assessment of VICTOza efficacy in the Regression of cardiovascular dysfunction in type 2 dIAbetes mellitus (MAGNA VICTORIA) study. This comprehensive mapping of the circulating lipidome allowed us to identify relevant lipid modules through unbiased weighted correlation network analysis, as well as disease and ethnicity related key mediatory lipids. Significant differences in lipidomic profiles, encompassing various lipid classes and species, were observed between T2DM patients and healthy controls in both the DSA and DwC populations. Our analyses revealed that healthy DSA, but not DwC, controls already exhibited a lipid profile prone to develop T2DM. Particularly, in DSA-T2DM patients, specific lipid changes correlated with clinical features, particularly diacylglycerols (DGs), showing significant associations with glycemic control and renal function. Our findings highlight an ethnic distinction in lipid modules influencing clinical outcomes in renal health. We discover distinctive ethnic disparities of the circulating lipidome and identify ethnicity-specific lipid markers. Jointly, our discoveries show great potential as personalized biomarkers for the assessment of glycemic control and renal function in DSA-T2DM individuals.

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.

Recent advances towards mass spectrometry-based clinical lipidomics

The objective of this review is to provide a comprehensive summary of the latest methodological advancements and emerging patterns in utilizing lipidomics in clinical research.In this review, we assess the recent advancements in lipidomics methodologies that exhibit high levels of selectivity and sensitivity, capable of generating numerous molecular lipid species from limited quantities of biological matrices. The reviewed studies demonstrate that molecular lipid signatures offer new opportunities for precision medicine by providing sensitive diagnostic tools for disease prediction and monitoring. Moreover, the latest innovations in microsampling techniques have the potential to make a substantial contribution to clinical lipidomics. The review also shows that more work is needed to harmonize results across diverse lipidomics platforms and avoid significant errors in analysis and reporting. The increased implementation of internal standards and standard reference materials in analytical workflows will aid in this direction.

Dynamic lipidome alterations associated with human health, disease and ageing

Lipids can be of endogenous or exogenous origin and affect diverse biological functions, including cell membrane maintenance, energy management and cellular signalling. Here, we report >800 lipid species, many of which are associated with health-to-disease transitions in diabetes, ageing and inflammation, as well as cytokine-lipidome networks. We performed comprehensive longitudinal lipidomic profiling and analysed >1,500 plasma samples from 112 participants followed for up to 9 years (average 3.2 years) to define the distinct physiological roles of complex lipid subclasses, including large and small triacylglycerols, ester- and ether-linked phosphatidylethanolamines, lysophosphatidylcholines, lysophosphatidylethanolamines, cholesterol esters and ceramides. Our findings reveal dynamic changes in the plasma lipidome during respiratory viral infection, insulin resistance and ageing, suggesting that lipids may have roles in immune homoeostasis and inflammation regulation. Individuals with insulin resistance exhibit disturbed immune homoeostasis, altered associations between lipids and clinical markers, and accelerated changes in specific lipid subclasses during ageing. Our dataset based on longitudinal deep lipidome profiling offers insights into personalized ageing, metabolic health and inflammation, potentially guiding future monitoring and intervention strategies.

Improving Quantitative Accuracy in Nontargeted Lipidomics by Evaluating Adduct Formation

For large-scale lipidomic analyses, accurate and reproducible quantification of endogenous lipids is crucial for comparing results within and across studies. Many lipids present in liquid chromatography-electrospray ionization-mass spectrometry form various adducts with buffer components. The mechanisms and conditions that dictate adduct formation are still poorly understood. In a positive mode, neutral lipids like mono-, di-, and triacylglycerides and cholesteryl esters typically generate [M + NH4]+ adduct ions, although [M + Na]+, [M + K]+, and other (more complex) species can also be significantly abundant in MS1 precursor ion spectra. Variations in the ratios of these adducts (within and between matrices) can lead to dramatic inaccuracies during quantification. Here, we examine 48 unique diacylglycerol (DAG) species across 2366 mouse samples for eight matrix-specific data sets of plasma, liver, kidney, brain, heart muscle, gastrocnemius muscle, gonadal, and inguinal fat. Typically, no single adduct ion species accounted for more than 60% of the total observed abundance across each data set. Even within a single matrix, DAGs showed a high variability of adduct ratios. The ratio of [M + NH4]+ adduct ions was increased for longer-chain DAGs and for polyunsaturated DAGs, at the expense of reduced ratios of [M + Na]+ adducts. When using three deuterated internal DAG standards, we found that absolute concentrations were estimated with up to 70% error when only one adduct ion was used instead of all adducts combined. Importantly, when combining [M + NH4]+ and [M + Na]+ adduct ions, quantification results were within 5% accuracy compared to all adduct ions combined. Additional variance can be caused by other factors, such as instrument conditions or matrix effects.

Metabolomics in drug research and development: The recent advances in technologies and applications

Emerging evidence has demonstrated the vital role of metabolism in various diseases or disorders. Metabolomics provides a comprehensive understanding of metabolism in biological systems. With advanced analytical techniques, metabolomics exhibits unprecedented significant value in basic drug research, including understanding disease mechanisms, identifying drug targets, and elucidating the mode of action of drugs. More importantly, metabolomics greatly accelerates the drug development process by predicting pharmacokinetics, pharmacodynamics, and drug response. In addition, metabolomics facilitates the exploration of drug repurposing and drug-drug interactions, as well as the development of personalized treatment strategies. Here, we briefly review the recent advances in technologies in metabolomics and update our knowledge of the applications of metabolomics in drug research and development.

Metabolomic and Lipidomic Analysis of the Colorectal Adenocarcinoma Cell Line HT29 in Hypoxia and Reoxygenation

The poor availability of oxygen and nutrients in malignant tumors drives the activation of various molecular responses and metabolic reprogramming in cancer cells. Hypoxic tumor regions often exhibit resistance to chemotherapy and radiotherapy. One approach to enhance cancer therapy is to indirectly increase tumor oxygen availability through targeted metabolic reprogramming. Thus, understanding the underlying metabolic changes occurring during hypoxia and reoxygenation is crucial for improving therapy efficacy. In this study, we utilized the HT29 colorectal adenocarcinoma cell line as a hypoxia-reoxygenation model to investigate central carbon and lipid metabolism. Through quantitative NMR spectroscopy and flow injection analysis - differential mobility spectroscopy-tandem mass spectrometry (FIA-DMS-MS/MS) analysis, we observed alterations in components of mitochondrial metabolism, redox status, specific lipid classes, and structural characteristics of lipids during hypoxia and up to 24 h of reoxygenation. These findings contribute to our understanding of the metabolic changes occurring during reoxygenation and provide the basis for functional studies aimed at metabolic pathways in cancer cells.

Atorvastatin Attenuates Diet-Induced Non-Alcoholic Steatohepatitis in APOE*3-Leiden Mice by Reducing Hepatic Inflammation

Patients with metabolic syndrome are often prescribed statins to prevent the development of cardiovascular disease. Conversely, data on their effects on non-alcoholic steatohepatitis (NASH) are lacking. We evaluated these effects by feeding APOE*3-Leiden mice a Western-type diet (WTD) with or without atorvastatin to induce NASH and hepatic fibrosis. Besides the well-known plasma cholesterol lowering (-30%) and anti-atherogenic effects (severe lesion size -48%), atorvastatin significantly reduced hepatic steatosis (-22%), the number of aggregated inflammatory cells in the liver (-80%) and hepatic fibrosis (-92%) compared to WTD-fed mice. Furthermore, atorvastatin-treated mice showed less immunohistochemically stained areas of inflammation markers. Atorvastatin prevented accumulation of free cholesterol in the form of cholesterol crystals (-78%). Cholesterol crystals are potent inducers of the NLRP3 inflammasome pathway and atorvastatin prevented its activation, which resulted in reduced expression of the pro-inflammatory cytokines interleukin (IL)-1β (-61%) and IL-18 (-26%). Transcriptome analysis confirmed strong reducing effects of atorvastatin on inflammatory mediators, including NLRP3, NFκB and TLR4. The present study demonstrates that atorvastatin reduces hepatic steatosis, inflammation and fibrosis and prevents cholesterol crystal formation, thereby precluding NLRP3 inflammasome activation. This may render atorvastatin treatment as an attractive approach to reduce NAFLD and prevent progression into NASH in dyslipidemic patients.

Demographic, Health and Lifestyle Factors Associated with the Metabolome in Older Women

Demographic and clinical factors influence the metabolome. The discovery and validation of disease biomarkers are often challenged by potential confounding effects from such factors. To address this challenge, we investigated the magnitude of the correlation between serum and urine metabolites and demographic and clinical parameters in a well-characterized observational cohort of 444 post-menopausal women participating in the Women’s Health Initiative (WHI). Using LC-MS and lipidomics, we measured 157 aqueous metabolites and 756 lipid species across 13 lipid classes in serum, along with 195 metabolites detected by GC-MS and NMR in urine and evaluated their correlations with 29 potential disease risk factors, including demographic, dietary and lifestyle factors, and medication use. After controlling for multiple testing (FDR < 0.01), we found that log-transformed metabolites were mainly associated with age, BMI, alcohol intake, race, sample storage time (urine only), and dietary supplement use. Statistically significant correlations were in the absolute range of 0.2–0.6, with the majority falling below 0.4. Incorporation of important potential confounding factors in metabolite and disease association analyses may lead to improved statistical power as well as reduced false discovery rates in a variety of data analysis settings.

Small molecule biomarker discovery: Proposed workflow for LC-MS-based clinical research projects

Mass spectrometry focusing on small endogenous molecules has become an integral part of biomarker discovery in the pursuit of an in-depth understanding of the pathophysiology of various diseases, ultimately enabling the application of personalized medicine. While LC-MS methods allow researchers to gather vast amounts of data from hundreds or thousands of samples, the successful execution of a study as part of clinical research also requires knowledge transfer with clinicians, involvement of data scientists, and interactions with various stakeholders. The initial planning phase of a clinical research project involves specifying the scope and design, and engaging relevant experts from different fields. Enrolling subjects and designing trials rely largely on the overall objective of the study and epidemiological considerations, while proper pre-analytical sample handling has immediate implications on the quality of analytical data. Subsequent LC-MS measurements may be conducted in a targeted, semi-targeted, or non-targeted manner, resulting in datasets of varying size and accuracy. Data processing further enhances the quality of data and is a prerequisite for in-silico analysis. Nowadays, the evaluation of such complex datasets relies on a mix of classical statistics and machine learning applications, in combination with other tools, such as pathway analysis and gene set enrichment. Finally, results must be validated before biomarkers can be used as prognostic or diagnostic decision-making tools. Throughout the study, quality control measures should be employed to enhance the reliability of data and increase confidence in the results. The aim of this graphical review is to provide an overview of the steps to be taken when conducting an LC-MS-based clinical research project to search for small molecule biomarkers.

Pre-analytical sample handling standardization for reliable measurement of metabolites and lipids in LC-MS-based clinical research

The emerging disciplines of lipidomics and metabolomics show great potential for the discovery of diagnostic biomarkers, but appropriate pre-analytical sample-handling procedures are critical because several analytes are prone to ex vivo distortions during sample collection. To test how the intermediate storage temperature and storage period of plasma samples from K3EDTA whole-blood collection tubes affect analyte concentrations, we assessed samples from non-fasting healthy volunteers (n = 9) for a broad spectrum of metabolites, including lipids and lipid mediators, using a well-established LC-MS-based platform. We used a fold change-based approach as a relative measure of analyte stability to evaluate 489 analytes, employing a combination of targeted LC-MS/MS and LC-HRMS screening. The concentrations of many analytes were found to be reliable, often justifying less strict sample handling; however, certain analytes were unstable, supporting the need for meticulous processing. We make four data-driven recommendations for sample-handling protocols with varying degrees of stringency, based on the maximum number of analytes and the feasibility of routine clinical implementation. These protocols also enable the simple evaluation of biomarker candidates based on their analyte-specific vulnerability to ex vivo distortions. In summary, pre-analytical sample handling has a major effect on the suitability of certain metabolites as biomarkers, including several lipids and lipid mediators. Our sample-handling recommendations will increase the reliability and quality of samples when such metabolites are necessary for routine clinical diagnosis.

Translational characterization of the temporal dynamics of metabolic dysfunctions in liver, adipose tissue and the gut during diet-induced NASH development in Ldlr-/-.Leiden mice

Background

NAFLD progression, from steatosis to inflammation and fibrosis, results from an interplay of intra- and extrahepatic mechanisms. Disease drivers likely include signals from white adipose tissue (WAT) and gut. However, the temporal dynamics of disease development remain poorly understood.

Methods

High-fat-diet (HFD)-fed Ldlr-/-.Leiden mice were compared to chow-fed controls. At t = 0, 8, 16, 28 and 38w mice were euthanized, and liver, WAT depots and gut were analyzed biochemically, histologically and by lipidomics and transcriptomics together with circulating factors to investigate the sequence of pathogenic events and organ cross-talk during NAFLD development.

Results

HFD-induced obesity was associated with an increase in visceral fat, plasma lipids and hyperinsulinemia at t = 8w, along with increased liver steatosis and circulating liver damage biomarkers. In parallel, upstream regulator analysis predicted that lipid catabolism regulators were deactivated and lipid synthesis regulators were activated. Subsequently, hepatocyte hypertrophy, oxidative stress and hepatic inflammation developed. Hepatic collagen accumulated from t = 16 w and became pronounced at t = 28-38 w. Epididymal WAT was maximally hypertrophic from t = 8 w, which coincided with inflammation development. Mesenteric and subcutaneous WAT hypertrophy developed slower and did not appear to reach a maximum, with minimal inflammation. In gut, HFD significantly increased permeability, induced a shift in microbiota composition from t = 8 w and changed circulating gut-derived metabolites.

Conclusion

HFD-fed Ldlr-/-.Leiden mice develop obesity, dyslipidemia and insulin resistance, essentially as observed in obese NAFLD patients, underlining their translational value. We demonstrate that marked epididymal-WAT inflammation, and gut permeability and dysbiosis precede the development of NAFLD stressing the importance of a multiple-organ approach in the prevention and treatment of NAFLD.

Omic-Scale High-Throughput Quantitative LC-MS/MS Approach for Circulatory Lipid Phenotyping in Clinical Research

Lipid analysis at the molecular species level represents a valuable opportunity for clinical applications due to the essential roles that lipids play in metabolic health. However, a comprehensive and high-throughput lipid profiling remains challenging given the lipid structural complexity and exceptional diversity. Herein, we present an 'omic-scale targeted LC-MS/MS approach for the straightforward and high-throughput quantification of a broad panel of complex lipid species across 26 lipid (sub)classes. The workflow involves an automated single-step extraction with 2-propanol, followed by lipid analysis using hydrophilic interaction liquid chromatography in a dual-column setup coupled to tandem mass spectrometry with data acquisition in the timed-selective reaction monitoring mode (12 min total run time). The analysis pipeline consists of an initial screen of 1903 lipid species, followed by high-throughput quantification of robustly detected species. Lipid quantification is achieved by a single-point calibration with 75 isotopically labeled standards representative of different lipid classes, covering lipid species with diverse acyl/alkyl chain lengths and unsaturation degrees. When applied to human plasma, 795 lipid species were measured with median intra- and inter-day precisions of 8.5 and 10.9%, respectively, evaluated within a single and across multiple batches. The concentration ranges measured in NIST plasma were in accordance with the consensus intervals determined in previous ring-trials. Finally, to benchmark our workflow, we characterized NIST plasma materials with different clinical and ethnic backgrounds and analyzed a sub-set of sera (n = 81) from a clinically healthy elderly population. Our quantitative lipidomic platform allowed for a clear distinction between different NIST materials and revealed the sex-specificity of the serum lipidome, highlighting numerous statistically significant sex differences.

The lipidomes of C. elegans with mutations in asm-3/acid sphingomyelinase and hyl-2/ceramide synthase show distinct lipid profiles during aging

Lipid metabolism affects cell and physiological functions that mediate animal healthspan and lifespan. Lipidomics approaches in model organisms have allowed us to better understand changes in lipid composition related to age and lifespan. Here, using the model C. elegans, we examine the lipidomes of mutants lacking enzymes critical for sphingolipid metabolism; specifically, we examine acid sphingomyelinase (asm-3), which breaks down sphingomyelin to ceramide, and ceramide synthase (hyl-2), which synthesizes ceramide from sphingosine. Worm asm-3 and hyl-2 mutants have been previously found to be long- and short-lived, respectively. We analyzed longitudinal lipid changes in wild type animals compared to mutants at 1-, 5-, and 10-days of age. We detected over 700 different lipids in several lipid classes. Results indicate that wildtype animals exhibit increased triacylglycerols (TAG) at 10-days compared to 1-day, and decreased lysophoshatidylcholines (LPC). We find that 10-day hyl-2 mutants have elevated total polyunsaturated fatty acids (PUFA) and increased LPCs compared to 10-day wildtype animals. These changes mirror another short-lived model, the daf-16/FOXO transcription factor that is downstream of the insulin-like signaling pathway. In addition, we find that hyl-2 mutants have poor oxidative stress response, supporting a model where mutants with elevated PUFAs may accumulate more oxidative damage. On the other hand, 10-day asm-3 mutants have fewer TAGs. Intriguingly, asm-3 mutants have a similar lipid composition as the long-lived, caloric restriction model eat-2/mAChR mutant. Together, these analyses highlight the utility of lipidomic analyses to characterize metabolic changes during aging in C. elegans.

The red blood cell as a mediator of endothelial dysfunction in patients with familial hypercholesterolemia and dyslipidemia

BACKGROUND

Patients with familial hypercholesterolemia (FH) display high levels of low-density lipoprotein cholesterol (LDL-c), endothelial dysfunction, and increased risk of premature atherosclerosis. We have previously shown that red blood cells (RBCs) from patients with type 2 diabetes induce endothelial dysfunction through increased arginase 1 and reactive oxygen species (ROS).

OBJECTIVE

To test the hypothesis that RBCs from patients with FH (FH-RBCs) and elevated LDL-c induce endothelial dysfunction.

METHODS AND RESULTS

FH-RBCs and LDL-c >5.0 mM induced endothelial dysfunction following 18-h incubation with isolated aortic rings from healthy rats compared to FH-RBCs and LDL-c <2.5 mM or RBCs from healthy subjects (H-RBCs). Inhibition of vascular but not RBC arginase attenuated the degree of endothelial dysfunction induced by FH-RBCs and LDL-c >5.0 mM. Furthermore, arginase 1 but not arginase 2 was elevated in the vasculature of aortic segments after incubation with FH-RBCs and LDL-c >5.0 mM. A superoxide scavenger, present throughout the 18-h incubation, attenuated the degree of endothelial dysfunction induced by FH-RBCs and LDL-c >5.0 mM. ROS production was elevated in these RBCs in comparison with H-RBCs. Scavenging of vascular ROS through various antioxidants also attenuated the degree of endothelial dysfunction induced by FH-RBCs and LDL-c >5.0 mM. This was corroborated by an increase in the lipid peroxidation product 4-hydroxynonenal. Lipidomic analysis of RBC lysates did not reveal any significant changes across the groups.

CONCLUSION

FH-RBCs induce endothelial dysfunction dependent on LDL-c levels via arginase 1 and ROS-dependent mechanisms.

Cold exposure induces dynamic changes in circulating triacylglycerol species, which is dependent on intracellular lipolysis: A randomized cross-over trial

BACKGROUND

The application of cold exposure has emerged as an approach to enhance whole-body lipid catabolism. The global effect of cold exposure on the lipidome in humans has been reported with mixed results depending on intensity and duration of cold.

METHODS

This secondary study was based on data from a previous randomized cross-over trial (ClinicalTrials.gov ID: NCT03012113). We performed sequential lipidomic profiling in serum during 120 min cold exposure of human volunteers. Next, the intracellular lipolysis was blocked in mice (eighteen 10-week-old male wild-type mice C57BL/6J) using a small-molecule inhibitor of adipose triglyceride lipase (ATGL; Atglistatin), and mice were exposed to cold for a similar duration. The quantitative lipidomic profiling was assessed in-depth using the Lipidyzer platform.

FINDINGS

In humans, cold exposure gradually increased circulating free fatty acids reaching a maximum at 60 min, and transiently decreased total triacylglycerols (TAGs) only at 30 min. A broad range of TAG species was initially decreased, in particular unsaturated and polyunsaturated TAG species with ≤5 double bonds, while after 120 min a significant increase was observed for polyunsaturated TAG species with ≥6 double bonds in humans. The mechanistic study in mice revealed that the cold-induced increase in polyunsaturated TAGs was largely prevented by blocking adipose triglyceride lipase.

INTERPRETATION

We interpret these findings as that cold exposure feeds thermogenic tissues with TAG-derived fatty acids for combustion, resulting in a decrease of circulating TAG species, followed by increased hepatic production of polyunsaturated TAG species induced by liberation of free fatty acids stemming from adipose tissue.

FUNDING

This work was supported by the Netherlands CardioVascular Research Initiative: 'the Dutch Heart Foundation, Dutch Federation of University Medical Centers, the Netherlands Organisation for Health Research and Development and the Royal Netherlands Academy of Sciences' [CVON2017-20 GENIUS-II] to Patrick C.N. Rensen. Borja Martinez-Tellez is supported by individual postdoctoral grant from the Fundación Alfonso Martin Escudero and by a Maria Zambrano fellowship by the Ministerio de Universidades y la Unión Europea - NextGenerationEU (RR_C_2021_04). Lucas Jurado-Fasoli was supported by an individual pre-doctoral grant from the Spanish Ministry of Education (FPU19/01609) and with an Albert Renold Travel Fellowship from the European Foundation for the Study of Diabetes (EFSD). Martin Giera was partially supported by NWO XOmics project #184.034.019.

Congruence and Complementarity of Differential Mobility Spectrometry and NMR Spectroscopy for Plasma Lipidomics

The lipid composition of lipoprotein particles is determinative of their respective formation and function. In turn, the combination and correlation of nuclear magnetic resonance (NMR)-based lipoprotein measurements with mass spectrometry (MS)-based lipidomics is an appealing technological combination for a better understanding of lipid metabolism in health and disease. Here, we developed a combined workflow for subsequent NMR- and MS-based analysis on single sample aliquots of human plasma. We evaluated the quantitative agreement of the two platforms for lipid quantification and benchmarked our combined workflow. We investigated the congruence and complementarity between the platforms in order to facilitate a better understanding of patho-physiological lipoprotein and lipid alterations. We evaluated the correlation and agreement between the platforms. Next, we compared lipid class concentrations between healthy controls and rheumatoid arthritis patient samples to investigate the consensus among the platforms on differentiating the two groups. Finally, we performed correlation analysis between all measured lipoprotein particles and lipid species. We found excellent agreement and correlation (r > 0.8) between the platforms and their respective diagnostic performance. Additionally, we generated correlation maps detailing lipoprotein/lipid interactions and describe disease-relevant correlations.

Trip13 Depletion in Liver Cancer Induces a Lipogenic Response Contributing to Plin2-Dependent Mitotic Cell Death

Aberrant energy metabolism and cell cycle regulation both critically contribute to malignant cell growth and both processes represent targets for anticancer therapy. It is shown here that depletion of the AAA+-ATPase thyroid hormone receptor interacting protein 13 (Trip13) results in mitotic cell death through a combined mechanism linking lipid metabolism to aberrant mitosis. Diminished Trip13 levels in hepatocellular carcinoma cells result in insulin-receptor-/Akt-pathway-dependent accumulation of lipid droplets, which act as functional acentriolar microtubule organizing centers disturbing mitotic spindle polarity. Specifically, the lipid-droplet-coating protein perilipin 2 (Plin2) is required for multipolar spindle formation, induction of DNA damage, and mitotic cell death. Plin2 expression in different tumor cells confers susceptibility to cell death induced by Trip13 depletion as well as treatment with paclitaxel, a spindle-interfering drug commonly used against different cancers. Thus, assessment of Plin2 levels enables the stratification of tumor responsiveness to mitosis-targeting drugs, including clinically approved paclitaxel and Trip13 inhibitors currently under development.

Early-life stress and dietary fatty acids impact the brain lipid/oxylipin profile into adulthood, basally and in response to LPS

Brain lipid dysregulation is a hallmark of depression and Alzheimer's disease, also marked by chronic inflammation. Early-life stress (ELS) and dietary intake of polyunsaturated fatty acids (PUFAs) are risk factors for these pathologies and are known to impact inflammatory processes. However, if these early-life factors alter brain lipid homeostasis on the long-term and thereby contribute to this risk remains to be elucidated. We have recently shown that an early diet enriched in omega(ω)-3 PUFAs protected against the long-term negative effects of ELS on cognition and neuroinflammation. Here, we aim to understand if modulation of brain lipid and oxylipin profiles contributes to the detrimental effects of ELS and the protective ones of the diet. We therefore studied if and how ELS and early dietary PUFAs modulate the brain lipid and oxylipin profile, basally as well as in response to an inflammatory challenge, to unmask possible latent effects. Male mice were exposed to ELS via the limited bedding and nesting paradigm, received an early diet with high or low ω6/ω3 ratio (HRD and LRD) and were injected with saline or lipopolysaccharide (LPS) in adulthood. Twenty-four hours later plasma cytokines (Multiplex) and hypothalamic lipids and oxylipins (liquid chromatography tandem mass spectrometry) were measured. ELS exacerbated the LPS-induced increase in IL-6, CXCL1 and CCL2. Both ELS and diet affected the lipid/oxylipin profile long-term. For example, ELS increased diacylglycerol and LRD reduced triacylglycerol, free fatty acids and ceramides. Importantly, the ELS-induced alterations were strongly influenced by the early diet. For example, the ELS-induced decrease in eicosapentaenoic acid was reversed when fed LRD. Similarly, the majority of the LPS-induced alterations were distinct for control and ELS exposed mice and unique for mice fed with LRD or HRD. LPS decreased ceramides and lysophosphotidylcholine, increased hexosylceramides and prostaglandin E₂, reduced triacylglycerol species and ω6-derived oxylipins only in mice fed LRD and ELS reduced the LPS-induced increase in phosphatidylcholine. These data give further insights into the alterations in brain lipids and oxylipins that might contribute to the detrimental effects of ELS, to the protective ones of LRD and the possible early-origin of brain lipid dyshomeostasis characterizing ELS-related psychopathologies.

What if using certified reference materials (CRMs) was a requirement to publish in analytical/bioanalytical chemistry journals?

Certified reference materials (CRMs) are routinely used by analytical chemists to validate new analytical methods and to demonstrate the quality of their quantitative measurements. Even though CRMs for trace element and trace organic analysis have been available and widely used for over 50 years, the majority of papers published in analytical chemistry journals do not mention the use of CRMs. What if analytical/bioanalytical chemistry journals required the use of CRMs to publish a paper? This feature article attempts to address this question by providing examples of recent papers that have made exceptional use of CRMs to validate new analytical methods and to describe novel, alternative uses of CRMs that provide new characterization of the CRM. The potential benefits of using a CRM even when it does not have certified values for the analytes of interest are presented.

Validation of a multiplexed and targeted lipidomics assay for accurate quantification of lipidomes

A major challenge of lipidomics is to determine and quantify the precise content of complex lipidomes to the exact lipid molecular species. Often, multiple methods are needed to achieve sufficient lipidomic coverage to make these determinations. Multiplexed targeted assays offer a practical alternative to enable quantitative lipidomics amenable to quality control standards within a scalable platform. Herein, we developed a multiplexed normal phase liquid chromatography-hydrophilic interaction chromatography multiple reaction monitoring method that quantifies lipid molecular species across over 20 lipid classes spanning wide polarities in a single 20-min run. Analytical challenges such as in-source fragmentation, isomer separations, and concentration dynamics were addressed to ensure confidence in selectivity, quantification, and reproducibility. Utilizing multiple MS/MS product ions per lipid species not only improved the confidence of lipid identification but also enabled the determination of relative abundances of positional isomers in samples. Lipid class-based calibration curves were applied to interpolate lipid concentrations and guide sample dilution. Analytical validation was performed following FDA Bioanalytical Method Validation Guidance for Industry. We report repeatable and robust quantitation of 900 lipid species measured in NIST-SRM-1950 plasma, with over 700 lipids achieving inter-assay variability below 25%. To demonstrate proof of concept for biomarker discovery, we analyzed plasma from mice treated with a glucosylceramide synthase inhibitor, benzoxazole 1. We observed expected reductions in glucosylceramide levels in treated animals but, more notably, identified novel lipid biomarker candidates from the plasma lipidome. These data highlight the utility of this qualified lipidomic platform for enabling biological discovery.

Deep Metabolic Profiling Assessment of Tissue Extraction Protocols for Three Model Organisms

Metabolic profiling harbors the potential to better understand various disease entities such as cancer, diabetes, Alzheimer’s, Parkinson’s disease or COVID-19. To better understand such diseases and their intricate metabolic pathways in human studies, model animals are regularly used. There, standardized rearing conditions and uniform sampling strategies are prerequisites towards a successful metabolomic study that can be achieved through model organisms. Although metabolomic approaches have been employed on model organisms before, no systematic assessment of different conditions to optimize metabolite extraction across several organisms and sample types has been conducted. We address this issue using a highly standardized metabolic profiling assay analyzing 630 metabolites across three commonly used model organisms (Drosophila, mouse, and zebrafish) to find an optimal extraction protocol for various matrices. Focusing on parameters such as metabolite coverage, concentration and variance between replicates we compared seven extraction protocols. We found that the application of a combination of 75% ethanol and methyl tertiary-butyl ether (MTBE), while not producing the broadest coverage and highest concentrations, was the most reproducible extraction protocol. We were able to determine up to 530 metabolites in mouse kidney samples, 509 in mouse liver, 422 in zebrafish and 388 in Drosophila and discovered a core overlap of 261 metabolites in these four matrices. To enable other scientists to search for the most suitable extraction protocol in their experimental context and interact with this comprehensive data, we have integrated our data set in the open-source shiny app “MetaboExtract”. Hereby, scientists can search for metabolites or compound classes of interest, compare them across the different tested extraction protocols and sample types as well as find reference concentration values.

Predictive Modeling of Alzheimer's and Parkinson's Disease Using Metabolomic and Lipidomic Profiles from Cerebrospinal Fluid

In recent years, metabolomics has been used as a powerful tool to better understand the physiology of neurodegenerative diseases and identify potential biomarkers for progression. We used targeted and untargeted aqueous, and lipidomic profiles of the metabolome from human cerebrospinal fluid to build multivariate predictive models distinguishing patients with Alzheimer's disease (AD), Parkinson's disease (PD), and healthy age-matched controls. We emphasize several statistical challenges associated with metabolomic studies where the number of measured metabolites far exceeds sample size. We found strong separation in the metabolome between PD and controls, as well as between PD and AD, with weaker separation between AD and controls. Consistent with existing literature, we found alanine, kynurenine, tryptophan, and serine to be associated with PD classification against controls, while alanine, creatine, and long chain ceramides were associated with AD classification against controls. We conducted a univariate pathway analysis of untargeted and targeted metabolite profiles and find that vitamin E and urea cycle metabolism pathways are associated with PD, while the aspartate/asparagine and c21-steroid hormone biosynthesis pathways are associated with AD. We also found that the amount of metabolite missingness varied by phenotype, highlighting the importance of examining missing data in future metabolomic studies.

Recent advances in metabolomics analysis for early drug development

The pharmaceutical industry adapted proteomics and other 'omics technologies for drug research early following their initial introduction. Although metabolomics lacked behind in this development, it has now become an accepted and widely applied approach in early drug development. Over the past few decades, metabolomics has evolved from a pure exploratory tool to a more mature and quantitative biochemical technology. Several metabolomics-based platforms are now applied during the early phases of drug discovery. Metabolomics analysis assists in the definition of the physiological response and target engagement (TE) markers as well as elucidation of the mode of action (MoA) of drug candidates under investigation. In this review, we highlight recent examples and novel developments of metabolomics analyses applied during early drug development.

Advanced nanoengineered-customized point-of-care tools for prostate-specific antigen

Change in the level of human prostate-specific antigen (PSA) is a major element in the development and progression of prostate cancer (PCa). Most of the methodologies are currently restricted to their application in routine clinical screening due to the scarcity of adequate screening tools, false reading, long assay time, and cost. Innovative techniques and the integration of knowledge from a variety of domains, such as materials science and engineering, are needed to provide sustainable solutions. The convergence of precision point-of-care (POC) diagnostic techniques, which allow patients to respond in real time to changes in PSA levels, provides promising possibilities for quantitative and quantitative detection of PSA. This solution could be interesting and relevant for use in PCa diagnosis at the POC. The approaches enable low-cost real-time detection and are simple to integrate into user-friendly sensor devices. This review focuses on the investigations, prospects, and challenges associated with integrating engineering sciences with cancer biology to develop nanotechnology-based tools for PCa diagnosis. This article intends to encourage the development of new nanomaterials to construct high-performance POC devices for PCa detection. Finally, the review concludes with closing remarks and a perspective forecast.