Discovering and validating between-subject variations in plasma lipids in healthy subjects

Sphingolipid Analysis in Clinical Research

Sphingolipids are the most diverse class of lipids due to the numerous variations in their structural components. This diversity is also reflected in their extremely different functions. Sphingolipids are not only constituents of cell membranes but have emerged as key signaling molecules involved in a variety of cellular functions, such as cell growth and differentiation, proliferation and apoptotic cell death. Lipidomic analyses in clinical research have identified pathways and products of sphingolipid metabolism that are altered in several human pathologies. In this article, we describe how to properly design a lipidomic experiment in clinical research, how to handle plasma and serum samples for this purpose, and how to measure sphingolipids using liquid chromatography-mass spectrometry.

Streamlining Phenotype Classification and Highlighting Feature Candidates: A Screening Method for Non-Targeted Ion Mobility Spectrometry-Mass Spectrometry (IMS-MS) Data

Nontargeted analysis (NTA) is increasingly utilized for its ability to identify key molecular features beyond known targets in complex samples. NTA is particularly advantageous in exploratory studies aimed at identifying phenotype-associated features or molecules able to classify various sample types. However, implementing NTA involves extensive data analyses and labor-intensive annotations. To address these limitations, we developed a rapid data screening capability compatible with NTA data collected on a liquid chromatography, ion mobility spectrometry, and mass spectrometry (LC-IMS-MS) platform that allows for sample classification while highlighting potential features of interest. Specifically, this method aggregates the thousands of IMS-MS spectra collected across the LC space for each sample and collapses the LC dimension, resulting in a single summed IMS-MS spectrum for screening. The summed IMS-MS spectra are then analyzed with a bootstrapped Lasso technique to identify key regions or coordinates for phenotype classification via support vector machines. Molecular annotations are then performed by examining the features present in the selected coordinates, highlighting potential molecular candidates. To demonstrate this summed IMS-MS screening approach, we applied it to clinical plasma lipidomic NTA data and exposomic NTA data from water sites with varying contaminant levels. Distinguishing coordinates were observed in both studies, enabling the evaluation of phenotypic molecular annotations and resulting in screening models capable of classifying samples with up to a 25% increase in accuracy compared to models using annotated data.

Maternal diet quality and associations with plasma lipid profiles and pregnancy-related cardiometabolic health

PURPOSE

To assess the relationship of early pregnancy maternal diet quality (DQ) with maternal plasma lipids and indicators of cardiometabolic health, including blood pressure (BP), gestational diabetes mellitus (GDM) and gestational weight gain (GWG).

METHODS

Women (n = 215) aged 18-40 years with singleton pregnancies were recruited at 10-20 weeks gestation. Diet quality was assessed by the Dietary Guideline Index, calculated at early ([mean ± SD]) (15 ± 3 weeks) and late (35 ± 2 weeks) pregnancy. Lipidomic analysis was performed, and 698 species across 37 lipid classes were measured from plasma blood samples collected at early (15 ± 3 weeks) and mid (27 ± 3 weeks)-pregnancy. Clinical measures (BP, GDM diagnosis, weight) and blood samples were collected across pregnancy. Multiple linear and logistic regression models assessed associations of early pregnancy DQ with plasma lipids at early and mid-pregnancy, BP at three antenatal visits, GDM diagnosis and total GWG.

RESULTS

Maternal DQ scores ([mean ± SD]) decreased significantly from early (70.7 ± 11.4) to late pregnancy (66.5 ± 12.6) (p < 0.0005). At a false discovery rate of 0.2, early pregnancy DQ was significantly associated with 13 plasma lipids at mid-pregnancy, including negative associations with six triglycerides (TGs); TG(54:0)[NL-18:0] (neutral loss), TG(50:1)[NL-14:0], TG(48:0)[NL-18:0], TG(52:1)[NL-18:0], TG(54:1)[NL-18:1], TG(50:0)[NL-18:0]. No statistically significant associations were found between early pregnancy DQ and BP, GDM or GWG.

CONCLUSION

Maternal diet did not adhere to Australian Dietary Guidelines. Diet quality was inversely associated with multiple plasma TGs. This study provides novel insights into the relationship between DQ, lipid biomarkers and cardiometabolic health during pregnancy.

Dietary Quality and Circulating Lipidomic Profiles in 2 Cohorts of Middle-Aged and Older Male Finnish Smokers and American Populations

BACKGROUND

Higher dietary quality is associated with lower disease risks and has not been examined extensively with lipidomic profiles.

OBJECTIVES

Our goal was to examine associations of the Healthy Eating Index (HEI)-2015, Alternate HEI-2010 (AHEI-2010), and alternate Mediterranean Diet Index (aMED) diet quality indices with serum lipidomic profiles.

METHODS

We conducted a cross-sectional analysis of HEI-2015, AHEI-2010, and aMED with lipidomic profiles from 2 nested case-control studies within the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (n = 627) and the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (n = 711). We used multivariable linear regression to determine associations of the indices, derived from baseline food-frequency questionnaires (Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial: 1993-2001, Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study: 1985-1988) with serum concentrations of 904 lipid species and 252 fatty acids (FAs) across 15 lipid classes and 28 total FAs, within each cohort and meta-analyzed results using fixed-effect models for lipids significant at Bonferroni-corrected threshold in common in both cohorts.

RESULTS

Adherence to HEI-2015, AHEI-2010, or aMED was associated positively with 31, 41, and 54 lipid species and 8, 6, and 10 class-specific FAs and inversely with 2, 8, and 34 lipid species and 1, 3, and 5 class-specific FAs, respectively. Twenty-five lipid species and 5 class-specific FAs were common to all indices, predominantly triacylglycerols, FA22:6 [docosahexaenoic acid (DHA)]-containing species, and DHA. All indices were positively associated with total FA22:6. AHEI-2010 and aMED were inversely associated with total FA18:1 (oleic acid) and total FA17:0 (margaric acid), respectively. The identified lipids were most associated with components of seafood and plant proteins and unsaturated:saturated fat ratio in HEI-2015; eicosapentaenoic acid plus DHA in AHEI-2010; and fish and monounsaturated:saturated fat ratio in aMED.

CONCLUSIONS

Adherence to HEI-2015, AHEI-2010, and aMED is associated with serum lipidomic profiles, mostly triacylglycerols or FA22:6-containing species, which are related to seafood and plant proteins, eicosapentaenoic acid-DHA, fish, or fat ratio index components.

The effects of fatty acid-based dietary interventions on circulating bioactive lipid levels as intermediate biomarkers of health, cardiovascular disease, and cardiovascular disease risk factors: a systematic review and meta-analysis of randomized clinical trials

CONTEXT

Dietary fatty acids (FAs), primarily n-3 polyunsaturated FAs, have been associated with enrichment of the circulating bioactive lipidome and changes in the enzymatic precursor lipoprotein-associated phospholipase A2 (Lp-PLA2) mass; however, the magnitude of this effect remains unclear.

OBJECTIVE

The aim of this systematic review and meta-analysis was to evaluate the effect of different dietary FAs on the bioactive lipid profile of healthy participants and those with cardiovascular disease (CVD) and CVD risk factors.

DATA SOURCES

PubMed, SCOPUS and the Cochrane Library databases were searched for relevant articles published between October 2010 and May 2022.

DATA EXTRACTION

Data were screened for relevance and then retrieved in full and evaluated for eligibility by 2 reviewers independently.

DATA ANALYSIS

The net difference in the bioactive lipid mean values between the endpoint and the baseline, and the corresponding SDs or SEs, were used for the qualitative synthesis. For the meta-analysis, a fixed-effects model was used.

RESULTS

Twenty-seven randomized clinical trials (representing >2560 participants) were included. Over 78% of the enrolled participants had ≥1 associated CVD risk factor, whereas <22% were healthy. In the meta-analysis, marine n-3 supplements (dose range, 0.37-1.9 g/d) significantly increased pro-inflammatory lysophosphatidylcholines (lyso-PCs; for lyso-PC(16:0): mean, +0.52 [95% confidence interval (CI), 0.02-1.01] µM; for lyso-PC(18:0): mean, +0.58 [95%CI, 0.09-1.08] µM) in obese participants. Additionally, n-3 supplementation (1-5.56 g/d) decreased plasma Lp-PLA2 mass, a well-known inflammation marker, in healthy (-0.35 [95%CI, -0.59 to -0.10] ng/mL), dyslipidemic (-0.36 [95%CI, -0.47 to -0.25] ng/mL), and stable coronary artery disease participants (-0.52 [95%CI, -0.91 to -0.12] ng/mL).

CONCLUSIONS

Daily n-3 provided as EPA+DHA supplements and consumed from 1 to 6 months reduced plasma Lp-PLA2 mass in healthy participants and those with CVD and CVD risk factors, suggesting an anti-inflammatory effect. However, the saturated lyso-PC response to n-3 was impaired in obese participants.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration no. CRD42021218335.

Sources of Variability in Serum Lipidomic Measurements and Implications for Epidemiologic Studies

Epidemiological studies using lipidomic approaches can identify lipids associated with exposures and diseases. We evaluated the sources of variability of lipidomic profiles measured in blood samples and the implications when designing epidemiologic studies. We measured 918 lipid species in nonfasting baseline serum from 693 participants in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial, with 570 participants having serial blood samples separated by 1-5 years and 72 blinded replicate quality control samples. Blood samples were collected during 1993-2006. For each lipid species, we calculated the between-individual, within-individual, and technical variances, and we estimated the statistical power to detect associations in case-control studies. The technical variability was moderate, with a median intraclass correlation coefficient of 0.79. The combination of technical and within-individual variances accounted for most of the variability in 74% of the lipid species. For an average true relative risk of 3 (comparing upper and lower quartiles) after correction for multiple comparisons at the Bonferroni significance threshold (α = 0.05/918 = 5.45 ×10-5), we estimated that a study with 500, 1,000, and 5,000 total participants (1:1 case-control ratio) would have 19%, 57%, and 99% power, respectively. Epidemiologic studies examining associations between lipidomic profiles and disease require large samples sizes to detect moderate effect sizes associations.

Tuberculostearic Acid-Containing Phosphatidylinositols as Markers of Bacterial Burden in Tuberculosis

One-fourth of the global human population is estimated to be infected with strains of the Mycobacterium tuberculosis complex (MTBC), the causative agent of tuberculosis (TB). Using lipidomic approaches, we show that tuberculostearic acid (TSA)-containing phosphatidylinositols (PIs) are molecular markers for infection with clinically relevant MTBC strains and signify bacterial burden. For the most abundant lipid marker, detection limits of ∼10² colony forming units (CFUs) and ∼10³ CFUs for bacterial and cell culture systems were determined, respectively. We developed a targeted lipid assay, which can be performed within a day including sample preparation—roughly 30-fold faster than in conventional methods based on bacterial culture. This indirect and culture-free detection approach allowed us to determine pathogen loads in infected murine macrophages, human neutrophils, and murine lung tissue. These marker lipids inferred from mycobacterial PIs were found in higher levels in peripheral blood mononuclear cells of TB patients compared to healthy individuals. Moreover, in a small cohort of drug-susceptible TB patients, elevated levels of these molecular markers were detected at the start of therapy and declined upon successful anti-TB treatment. Thus, the concentration of TSA-containing PIs can be used as a correlate for the mycobacterial burden in experimental models and in vitro systems and may prospectively also provide a clinically relevant tool to monitor TB severity.

Variability of the Plasma Lipidome and Subclinical Coronary Atherosclerosis

Supplemental Digital Content is available in the text.

Objective:

While the risk of acute coronary events has been associated with biological variability of circulating cholesterol, the association with variability of other atherogenic lipids remains less understood. We evaluated the longitudinal variability of 284 lipids and investigated their association with asymptomatic coronary atherosclerosis.

Approach and Results:

Circulating lipids were extracted from fasting blood samples of 83 community-sampled symptom-free participants (age 41–75 years), collected longitudinally over 6 months. Three types of coronary plaque volume (calcified, lipid-rich, and fibrotic) were quantified using computed tomography coronary angiogram. We first deconvoluted between-subject (CV_g) and within-subject (CV_w) lipid variabilities. We then tested whether the mean lipid abundance was different across groups categorized by Framingham risk score and plaques phenotypes (lipid-rich, fibrotic, and calcified). Finally, we investigated whether visit-to-visit variability of each lipid was associated with plaque burden. Most lipids (72.5%) exhibited higher CV_g than CV_w. Among the lipids (n=145) with 1.2-fold higher CV_g than CV_w, 26 species including glycerides and ceramides were significantly associated with Framingham risk score and the 3 plaque phenotypes (false discovery rate <0.05). In an exploratory analysis of person-specific visit-to-visit variability without multiple testing correction, high variability of 3 lysophospholipids (lysophosphatidylethanolamines 16:0, 18:0, and lysophosphatidylcholine O-18:1) was associated with lipid-rich and fibrotic (noncalcified) plaque volume while high variability of diacylglycerol 18:1_20:0, triacylglycerols 52:2, 52:3, and 52:4, ceramide d18:0/20:0, dihexosylceramide d18:1/16:0, and sphingomyelin 36:3 was associated with calcified plaque volume.

Conclusions:

High person-specific longitudinal variation of specific nonsterol lipids is associated with the burden of subclinical coronary atherosclerosis. Larger studies are needed to confirm these exploratory findings.

Plasma lipidomics profile in pregnancy and gestational diabetes risk: a prospective study in a multiracial/ethnic cohort

INTRODUCTION

Disruption of lipid metabolism is implicated in gestational diabetes (GDM). However, prospective studies on lipidomics and GDM risk in race/ethnically diverse populations are sparse. Here, we aimed to (1) identify lipid networks in early pregnancy to mid-pregnancy that are associated with subsequent GDM risk and (2) examine the associations of lipid networks with glycemic biomarkers to understand the underlying mechanisms.

RESEARCH DESIGN AND METHODS

This study included 107 GDM cases confirmed using the Carpenter and Coustan criteria and 214 non-GDM matched controls from the National Institute of Child Health and Human Development Fetal Growth Studies-Singleton cohort, untargeted lipidomics data of 420 metabolites (328 annotated and 92 unannotated), and information on glycemic biomarkers in maternal plasma at visit 0 (10-14 weeks) and visit 1 (15-26 weeks). We constructed lipid networks using weighted correlation network analysis technique. We examined prospective associations of lipid networks and individual lipids with GDM risk using linear mixed effect models. Furthermore, we calculated Pearson's partial correlation for GDM-related lipid networks and individual lipids with plasma glucose, insulin, C-peptide and glycated hemoglobin at both study visits.

RESULTS

Lipid networks primarily characterized by elevated plasma diglycerides and short, saturated/low unsaturated triglycerides and lower plasma cholesteryl esters, sphingomyelins and phosphatidylcholines were associated with higher risk of developing GDM (false discovery rate (FDR) <0.05). Among individual lipids, 58 metabolites at visit 0 and 96 metabolites at visit 1 (40 metabolites at both time points) significantly differed between women who developed GDM and who did not (FDR <0.05). Furthermore, GDM-related lipid networks and individual lipids showed consistent correlations with maternal glycemic markers particularly in early pregnancy at visit 0.

CONCLUSIONS

Plasma lipid metabolites in early pregnancy both individually and interactively in distinct networks were associated with subsequent GDM risk in race/ethnically diverse US women. Future research is warranted to assess lipid metabolites as etiologic markers of GDM.

Dietary Fat and Protein Intake in Relation to Plasma Sphingolipids as Determined by a Large-Scale Lipidomic Analysis

Sphingolipid concentrations have been associated with risk of type 2 diabetes and cardiovascular diseases. Because sphingolipids can be synthesized de novo from saturated fatty acids (SFA), dietary fatty acids may affect plasma sphingolipid concentrations. We aimed to evaluate dietary fat and protein intakes in relation to circulating sphingolipid levels. We used cross-sectional data from 2860 ethnic Chinese Singaporeans collected from 2004–2007. Nutrient intakes were estimated on the basis of a validated 159-item food frequency questionnaire. We quantified 79 molecularly distinct sphingolipids in a large-scale lipidomic evaluation from plasma samples. Higher saturated fat intake was associated with higher concentrations of 16:1;O2 sphingolipids including ceramides, monohexosylcermides, dihexosylceramides, sphingomyelins, and sphingosine 1-phosphates. Higher polyunsaturated fat intake was associated with lower plasma long-chain ceramides and long-chain monohexosylcermide concentrations. Protein intake was inversely associated with concentrations of most subclasses of sphingolipids, with the exception of sphingolipids containing a 16:1;O2 sphingoid base. Lower intake of saturated fat and higher intake of polyunsaturated fat and protein may decrease plasma concentrations of several sphingolipid classes. These findings may represent a novel biological mechanism for the impact of nutrient intakes on cardio-metabolic health.

Structural-based connectivity and omic phenotype evaluations (SCOPE): a cheminformatics toolbox for investigating lipidomic changes in complex systems

Since its inception, the main goal of the lipidomics field has been to characterize lipid species and their respective biological roles. However, difficulties in both full speciation and biological interpretation have rendered these objectives extremely challenging and as a result, limited our understanding of lipid mechanisms and dysregulation. While mass spectrometry-based advancements have significantly increased the ability to identify lipid species, less progress has been made surrounding biological interpretations. We have therefore developed a Structural-based Connectivity and Omic Phenotype Evaluations (SCOPE) cheminformatics toolbox to aid in these evaluations. SCOPE enables the assessment and visualization of two main lipidomic associations: structure/biological connections and metadata linkages either separately or in tandem. To assess structure and biological relationships, SCOPE utilizes key lipid structural moieties such as head group and fatty acyl composition and links them to their respective biological relationships through hierarchical clustering and grouped heatmaps. Metadata arising from phenotypic and environmental factors such as age and diet is then correlated with the lipid structures and/or biological relationships, utilizing Toxicological Prioritization Index (ToxPi) software. Here, SCOPE is demonstrated for various applications from environmental studies to clinical assessments to showcase new biological connections not previously observed with other techniques.

Plasma sphingolipids and risk of cardiovascular diseases: a large-scale lipidomic analysis

INTRODUCTION

Sphingolipids are a diverse class of lipids with various roles in cell functions and subclasses such as ceramides have been associated with cardiovascular diseases (CVD) in previous studies.

OBJECTIVES

We aimed to measure molecularly-distinct sphingolipids via a large-scale lipidomic analysis and expand the literature to an Asian population.

METHODS

We performed a lipidomics evaluation of 79 molecularly distinct sphingolipids in the plasma of 2627 ethnically-Chinese Singaporeans.

RESULTS

During a mean follow-up of 12.9 years, we documented 152 cases of major CVD (non-fatal myocardial infarction, stroke and cardiovascular death). Total ceramide concentrations were not associated with CVD risk [hazard ratio (HR), 0.99; 95% CI 0.81-1.21], but higher circulating total monohexosylceramides (HR, 1.22; 95% CI 1.03, 1.45), total long-chain sphingolipids (C16-C18) (HR, 1.22; 95% CI 1.02, 1.45) and total 18:1 sphingolipids (HR, 1.21; 95% CI 1.01, 1.46) were associated with higher CVD risk after adjusting for conventional CVD risk factors.

CONCLUSIONS

Our results do not support the hypothesis that higher ceramide concentrations are linked to higher CVD risk, but suggest that other classes of sphingolipids may affect CVD risk.

Goos-Hänchen and Imbert-Fedorov shifts on hyperbolic crystals

We investigated Goos-Hänchen (GH) and Imbert-Fedorov (IF) shifts on a uniaxial hyperbolic crystal, where a circularly-polarized beam was incident on the crystal from the free space. The GH- and IF-shifts were analytically obtained and numerically calculated for the hexagonal boron nitride. Our results demonstrate that the GH- and IF-shift spectra are complicated and completely different in and out the hyperbolic frequency-bands (the reststrahlen bands in the infrared region). At the critical or Brewster angle, concisely analytical expressions of GH-shift was found, which explicitly state the optical-loss dependence of GH-shift at these special angles. We found the GH-shifts are very large at the critical and Brewster angles. It is very necessary to know these effects since hyperbolic materials are usually applied in the nano- and micro-optics or technology fields.

Genetic and environmental determinants of variation in the plasma lipidome of older Australian twins

The critical role of blood lipids in a broad range of health and disease states is well recognised but less explored is the interplay of genetics and environment within the broader blood lipidome. We examined heritability of the plasma lipidome among healthy older-aged twins (75 monozygotic/55 dizygotic pairs) enrolled in the Older Australian Twins Study (OATS) and explored corresponding gene expression and DNA methylation associations. 27/209 lipids (13.3%) detected by liquid chromatography-coupled mass spectrometry (LC-MS) were significantly heritable under the classical ACE twin model (h2 = 0.28-0.59), which included ceramides (Cer) and triglycerides (TG). Relative to non-significantly heritable TGs, heritable TGs had a greater number of associations with gene transcripts, not directly associated with lipid metabolism, but with immune function, signalling and transcriptional regulation. Genome-wide average DNA methylation (GWAM) levels accounted for variability in some non-heritable lipids. We reveal a complex interplay of genetic and environmental influences on the ageing plasma lipidome.

LipidCreator workbench to probe the lipidomic landscape

Mass spectrometry (MS)-based targeted lipidomics enables the robust quantification of selected lipids under various biological conditions but comprehensive software tools to support such analyses are lacking. Here we present LipidCreator, a software that fully supports targeted lipidomics assay development. LipidCreator offers a comprehensive framework to compute MS/MS fragment masses for over 60 lipid classes. LipidCreator provides all functionalities needed to define fragments, manage stable isotope labeling, optimize collision energy and generate in silico spectral libraries. We validate LipidCreator assays computationally and analytically and prove that it is capable to generate large targeted experiments to analyze blood and to dissect lipid-signaling pathways such as in human platelets.

Plasma Lipidomic Analyses in Cohorts With mTBI and/or PTSD Reveal Lipids Differentially Associated With Diagnosis and APOE ε4 Carrier Status

The differential diagnosis between mild Traumatic Brain Injury (mTBI) sequelae and Post-Traumatic Stress Disorder (PTSD) is challenging due to their symptomatic overlap and co-morbidity. As such, there is a need to develop biomarkers which can help with differential diagnosis of these two conditions. Studies from our group and others suggest that blood and brain lipids are chronically altered in both mTBI and PTSD. Therefore, examining blood lipids presents a minimally invasive and cost-effective approach to identify promising biomarkers of these conditions. Using liquid chromatography-mass spectrometry (LC-MS) we examined hundreds of lipid species in the blood of healthy active duty soldiers (n = 52) and soldiers with mTBI (n = 21), PTSD (n = 34) as well as co-morbid mTBI and PTSD (n = 13) to test whether lipid levels were differentially altered with each. We also examined if the apolipoprotein E (APOE) ε4 allele can affect the association between diagnosis and peripheral lipid levels in this cohort. We show that several lipid classes are altered with diagnosis and that there is an interaction between diagnosis and the ε4 carrier status on these lipids. Indeed, total lipid levels as well as both the degree of unsaturation and chain lengths are differentially altered with diagnosis and ε4 status, specifically long chain unsaturated triglycerides (TG) and both saturated and mono-unsaturated diglycerides (DG). Additionally, an examination of lipid species reveals distinct profiles in each diagnostic group stratified by ε4 status, mainly in TG, saturated DG species and polyunsaturated phosphatidylserines. In summary, we show that peripheral lipids are promising biomarker candidates to assist with the differential diagnosis of mTBI and PTSD. Further, ε4 carrier status alone and in interaction with diagnosis has a strong influence on peripheral lipid levels. Therefore, examining ε4 status along with peripheral lipid levels could help with differential diagnosis of mTBI and PTSD.

Validation of lipidomic analysis of human plasma and serum by supercritical fluid chromatography-mass spectrometry and hydrophilic interaction liquid chromatography-mass spectrometry

Ultrahigh-performance supercritical fluid chromatography-mass spectrometry (UHPSFC/MS) has a great potential for the high-throughput lipidomic quantitation of biological samples; therefore, the full optimization and method validation of UHPSFC/MS is compared here with ultrahigh-performance liquid chromatography-mass spectrometry (UHPLC/MS) in hydrophilic interaction liquid chromatography (HILIC) mode as the second powerful technique for the lipid class separation. First, the performance of six common extraction protocols is investigated, where the Folch procedure yields the best results with regard to recovery rate, matrix effect, and precision. Then, the full optimization and analytical validation for eight lipid classes using UHPSFC/MS and HILIC-UHPLC/MS methods are performed for the same sample set and applied for the lipidomic characterization of pooled samples of human plasma, human serum, and NIST SRM 1950 human plasma. The choice of appropriate internal standards (IS) for individual lipid classes has a key importance for reliable quantitative workflows illustrated by the selectivity while validation and the calculation of the quantitation error using multiple internal standards per lipid class. Validation results confirm the applicability of both methods, but UHPSFC/MS provides some distinct advantages, such as the successful separation of both non-polar and polar lipid classes unlike to HILIC-UHPLC/MS, shorter total run times (8 vs. 10.5 min), and slightly higher robustness. Various types of correlations between methods (UHPSFC/MS and HILIC-UHPLC/MS), biological material (plasma and serum), IS (laboratory and commercially mixtures), and literature data on the standard reference material show the intra- and inter-laboratory comparison in the quantitation of lipid species from eight lipid classes, the concentration differences in serum and plasma as well as the applicability of non-commercially available internal standard mixtures for lipid quantitation.

Shared reference materials harmonize lipidomics across MS-based detection platforms and laboratories

Quantitative MS of human plasma lipids is a promising technology for translation into clinical applications. Current MS-based lipidomic methods rely on either direct infusion (DI) or chromatographic lipid separation methods (including reversed phase and hydrophilic interaction LC). However, the use of lipid markers in laboratory medicine is limited by the lack of reference values, largely because of considerable differences in the concentrations measured by different laboratories worldwide. These inconsistencies can be explained by the use of different sample preparation protocols, method-specific calibration procedures, and other experimental and data-reporting parameters, even when using identical starting materials. Here, we systematically investigated the roles of some of these variables in multiple approaches to lipid analysis of plasma samples from healthy adults by considering: 1) different sample introduction methods (separation vs. DI methods); 2) different MS instruments; and 3) between-laboratory differences in comparable analytical platforms. Each of these experimental variables resulted in different quantitative results, even with the inclusion of isotope-labeled internal standards for individual lipid classes. We demonstrated that appropriate normalization to commonly available reference samples (i.e., "shared references") can largely correct for these systematic method-specific quantitative biases. Thus, to harmonize data in the field of lipidomics, in-house long-term references should be complemented by a commonly available shared reference sample, such as NIST SRM 1950, in the case of human plasma.

High throughput pSTAT signaling profiling by fluorescent cell barcoding and computational analysis

Fluorescent cell barcoding (FCB) is a multiplexing technique for high-throughput flow cytometry (FCM). Although powerful in minimizing staining variability, it remains a subjective FCM technique because of inter-operator variability and differences in data analysis. FCB was implemented by combining two-dye barcoding (DyLight 350 plus Pacific Orange) with five-color surface marker antibody and intracellular staining for phosphoprotein signaling analysis. We proposed a robust method to measure intra- and inter-assay variability of FCB in T/B cells and monocytes by combining range and ratio of variability to standard statistical analyses. Data analysis was carried out by conventional and semi-automated workflows and built with R software. Results obtained from both analyses were compared to assess feasibility and reproducibility of FCB data analysis by machine-learning methods. Our results showed efficient FCB using DyLight 350 and Pacific Orange at concentrations of 0, 15 or 30, and 250 μg/mL, and a high reproducibility of FCB in combination with surface marker and intracellular antibodies. Inter-operator variability was minimized by adding an internal control bridged across matrices used as rejection criterion if significant differences were present between runs. Computational workflows showed comparable results to conventional gating strategies. FCB can be used to study phosphoprotein signaling in T/B cells and monocytes with high reproducibility across operators, and the addition of bridge internal controls can further minimize inter-operator variability. This FCB protocol, which has high throughput analysis and low intra- and inter-assay variability, can be a powerful tool for clinical trial studies. Moreover, FCB data can be reliably analyzed using computational software.

Machine learning of human plasma lipidomes for obesity estimation in a large population cohort

Obesity is associated with changes in the plasma lipids. Although simple lipid quantification is routinely used, plasma lipids are rarely investigated at the level of individual molecules. We aimed at predicting different measures of obesity based on the plasma lipidome in a large population cohort using advanced machine learning modeling. A total of 1,061 participants of the FINRISK 2012 population cohort were randomly chosen, and the levels of 183 plasma lipid species were measured in a novel mass spectrometric shotgun approach. Multiple machine intelligence models were trained to predict obesity estimates, i.e., body mass index (BMI), waist circumference (WC), waist-hip ratio (WHR), and body fat percentage (BFP), and validated in 250 randomly chosen participants of the Malmö Diet and Cancer Cardiovascular Cohort (MDC-CC). Comparison of the different models revealed that the lipidome predicted BFP the best (R2 = 0.73), based on a Lasso model. In this model, the strongest positive and the strongest negative predictor were sphingomyelin molecules, which differ by only 1 double bond, implying the involvement of an unknown desaturase in obesity-related aberrations of lipid metabolism. Moreover, we used this regression to probe the clinically relevant information contained in the plasma lipidome and found that the plasma lipidome also contains information about body fat distribution, because WHR (R2 = 0.65) was predicted more accurately than BMI (R2 = 0.47). These modeling results required full resolution of the lipidome to lipid species level, and the predicting set of biomarkers had to be sufficiently large. The power of the lipidomics association was demonstrated by the finding that the addition of routine clinical laboratory variables, e.g., high-density lipoprotein (HDL)- or low-density lipoprotein (LDL)- cholesterol did not improve the model further. Correlation analyses of the individual lipid species, controlled for age and separated by sex, underscores the multiparametric and lipid species-specific nature of the correlation with the BFP. Lipidomic measurements in combination with machine intelligence modeling contain rich information about body fat amount and distribution beyond traditional clinical assays.

Lipid profiling of suction blister fluid: comparison of lipids in interstitial fluid and plasma

BACKGROUND

Recent technical advances in the extraction of dermal interstitial fluid (ISF) have stimulated interest in using this rather unexploited biofluid as an alternative to blood for detection and prediction of disease. However, knowledge about the presence of useful biomarkers for health monitoring in ISF is still limited. In this study, we characterized the lipidome of human suction blister fluid (SBF) as a surrogate for pure ISF and compared it to that of plasma.

METHODS

Plasma and SBF samples were obtained from 18 healthy human volunteers after an overnight fast. Total lipids were extracted and analyzed by liquid chromatography-tandem mass spectrometry. One hundred ninety-three lipid species covering 10 complex lipid classes were detected and quantified in both plasma and SBF using multiple reaction monitoring. A fraction of the lipid extract was subjected to alkaline transesterification and fatty acid methyl esters were analyzed by gas chromatography-mass spectrometry.

RESULTS

The total concentration of lipids in SBF was 17% of the plasma lipid concentration. The molar fraction of lipid species within lipid classes, as well as total fatty acids, showed a generally high correlation between plasma and SBF. However, SBF had larger fractions of lysophospholipids and diglycerides relative to plasma, and consequently less diacylphospholipids and triglycerides. Principal component analysis revealed that the interindividual variation in SBF lipid profiles was considerably larger than the within-subject variation between plasma and SBF.

CONCLUSIONS

Plasma and SBF lipid profiles show high correlation and SBF could be used interchangeably with blood for the analysis of major lipids used in health monitoring.

Comparison of Single Phase and Biphasic Extraction Protocols for Lipidomic Studies Using Human Plasma

Lipidomic profiling of plasma is an emerging field, given the importance of lipids in major cellular pathways, and is dependent on efficient lipid extraction protocols. Recent attention has turned to plasma lipidomics as a means to identify potential diagnostic and prognostic biomarkers related to dementia, neuropsychiatric health and disease. Although several solvent-based lipid extraction protocols have been developed and are currently in use, novel and more efficient methods could greatly simplify lipid analysis in plasma and warrant investigation. Human plasma from normolipidemic adult volunteers was collected to evaluate three different solvent extraction protocols, including the classical Folch method, the methanol/tert-butyl methyl ether (MTBE) (Matyash) method, and a recent single-phase methanol/1-butanol (Alshehry) method. Extracted lipids were analyzed using liquid chromatography mass spectrometry (LC-MS) in positive and negative ion mode. Overall, more than 500 different lipids were identified in positive and negative ion mode combined. Our data show that the single phase Alshehry method was as effective as the Folch and Matyash methods in extracting most lipid classes and was more effective in extraction of polar lipids. Normalized peak areas of the Alshehry method were highly and positively correlated with both the Folch and Matyash methods (r 2 = 0.99 and 0.97, respectively). Within- and between- subject correlations were r = 0.99 and 0.96, respectively. Median intra-assay coefficient of variation (CV%) in positive mode was 14.1, 15.1, and 21.8 for the Alshehry, Folch and Matyash methods, respectively. Median Alshehry inter-assay CV (collected over 5 separate days) was 14.4%. In conclusion, the novel Alshehry method was at least as good as, if not better than the established biphasic extraction methods in detecting a wide range of lipid classes, using as little as 10 μL of plasma, and was highly reproducible, safer and more environmentally-friendly as it doesn't require chloroform.

Metabolomics reveals plausible interactive effects between dairy product consumption and metabolic syndrome in humans

BACKGROUND & AIMS

Metabolic syndrome (MetS) induces major disturbances in plasma metabolome, reflecting abnormalities of several metabolic pathways. Recent evidences have demonstrated that the consumption of dairy products may protect from MetS, but the mechanisms remains unknown. The present study aimed at identify how the consumption of different types of dairy products could modify the changes in plasma metabolome during MetS.

METHODS

In this observational study, we analyzed how the consumption of dairy products could modify the perturbations in the plasma metabolome induced by MetS in a sample of 298 participants (61 with MetS) from the French MONA LISA survey. Metabolomic profiling was analyzed with UPLC-MS/MS.

RESULTS

Subjects with MetS exhibited major changes in plasma metabolome. Significant differences in plasma levels of branched chain amino acids, gamma-glutamyl amino acids, and metabolites from arginine and proline metabolism were observed between healthy control and Mets subjects. Plasma levels of many lipid species were increased with MetS (mono- and diacylglycerols, eicosanoids, lysophospholipids and lysoplasmalogens), with corresponding decreases in short chain fatty acids and plasmalogens. The consumption of dairy products, notably with a low fat content (milk and fresh dairy products), altered metabolite profiles in plasma from MetS subjects. Specifically, increasing consumption of dairy products promoted accumulation of plasma C15:0 fatty acid and was inversely associated to some circulating lysophospholipids, sphingolipids, gamma-glutamyl amino acids, leukotriene B4 and lysoplasmalogens.

CONCLUSIONS

the consumption of low fat dairy products could mitigate some of the variations induced by MetS.

Large-scale lipidomics identifies associations between plasma sphingolipids and T2DM incidence

BACKGROUND

Sphingolipids (SPs) are ubiquitous, structurally diverse molecules that include ceramides, sphingomyelins, and sphingosines. They are involved in various pathologies including obesity and type 2 diabetes mellitus (T2DM). Therefore, it is likely that perturbations in plasma concentrations of SPs are associated with disease. Identifying these associations may reveal useful biomarkers or provide insight into disease processes.

METHODS

We performed a lipidomics evaluation of molecularly-distinct SPs in the plasma of 2,302 ethnically-Chinese Singaporeans using electrospray ionization mass spectrometry coupled with liquid chromatography. SP profiles were compared to clinical and biochemical characteristics, and subjects were evaluated by follow-up visits for 11 years.

RESULTS

We found that ceramides correlate positively but hexosylceramides correlate negatively with body mass index (BMI) and homeostatic model assessment of insulin resistance (HOMA-IR). Furthermore, SPs with a d16:1 sphingoid backbone correlate more positively with BMI and HOMA-IR, while d18:2 SPs correlate less positively, relative to canonical d18:1 SPs. We also found that higher concentrations of two distinct sphingomyelins were associated with a higher risk of T2DM (HR 1.45, 95% CI 1.18-1.78 for SM d16:1/C18:0; and HR 1.40, 95% CI 1.17-1.68 for SM d18:1/C18:0).

CONCLUSION

We identified significant associations between SPs and obesity/T2DM characteristics, specifically, that of hexosylceramides, d16:1 SPs, and d18:2 SPs. This suggests that the balance of SP metabolism, rather than ceramide accumulation, is associated with the pathology of obesity. We further identified two specific SPs that may represent prognostic biomarkers for T2DM.

FUNDING

Funding sources are listed in the Acknowledgements section.

Online photochemical derivatization enables comprehensive mass spectrometric analysis of unsaturated phospholipid isomers

Mass spectrometry-based lipidomics is the primary tool for the structural analysis of lipids but the effective localization of carbon-carbon double bonds (C=C) in unsaturated lipids to distinguish C=C location isomers remains challenging. Here, we develop a large-scale lipid analysis platform by coupling online C=C derivatization through the Paternò-Büchi reaction with liquid chromatography-tandem mass spectrometry. This provides rich information on lipid C=C location isomers, revealing C=C locations for more than 200 unsaturated glycerophospholipids in bovine liver among which we identify 55 groups of C=C location isomers. By analyzing tissue samples of patients with breast cancer and type 2 diabetes plasma samples, we find that the ratios of C=C isomers are much less affected by interpersonal variations than their individual abundances, suggesting that isomer ratios may be used for the discovery of lipid biomarkers.

Online photochemical derivatization enables comprehensive mass spectrometric analysis of unsaturated phospholipid isomers

Mass spectrometry-based lipidomics is the primary tool for the structural analysis of lipids but the effective localization of carbon-carbon double bonds (C=C) in unsaturated lipids to distinguish C=C location isomers remains challenging. Here, we develop a large-scale lipid analysis platform by coupling online C=C derivatization through the Paternò-Büchi reaction with liquid chromatography-tandem mass spectrometry. This provides rich information on lipid C=C location isomers, revealing C=C locations for more than 200 unsaturated glycerophospholipids in bovine liver among which we identify 55 groups of C=C location isomers. By analyzing tissue samples of patients with breast cancer and type 2 diabetes plasma samples, we find that the ratios of C=C isomers are much less affected by interpersonal variations than their individual abundances, suggesting that isomer ratios may be used for the discovery of lipid biomarkers.

MS-based lipidomics of human blood plasma: a community-initiated position paper to develop accepted guidelines

Human blood is a self-regenerating lipid-rich biological fluid that is routinely collected in hospital settings. The inventory of lipid molecules found in blood plasma (plasma lipidome) offers insights into individual metabolism and physiology in health and disease. Disturbances in the plasma lipidome also occur in conditions that are not directly linked to lipid metabolism; therefore, plasma lipidomics based on MS is an emerging tool in an array of clinical diagnostics and disease management. However, challenges exist in the translation of such lipidomic data to clinical applications. These relate to the reproducibility, accuracy, and precision of lipid quantitation, study design, sample handling, and data sharing. This position paper emerged from a workshop that initiated a community-led process to elaborate and define a set of generally accepted guidelines for quantitative MS-based lipidomics of blood plasma or serum, with harmonization of data acquired on different instrumentation platforms across independent laboratories as an ultimate goal. We hope that other fields may benefit from and follow such a precedent.

Reproducibility of non-fasting plasma metabolomics measurements across processing delays

INTRODUCTION

Processing delays after blood collection is a common pre-analytical condition in large epidemiologic studies. It is critical to evaluate the suitability of blood samples with processing delays for metabolomics analysis as it is a potential source of variation that could attenuate associations between metabolites and disease outcomes.

OBJECTIVES

We aimed to evaluate the reproducibility of metabolites over extended processing delays up to 48 h. We also aimed to test the reproducibility of the metabolomics platform.

METHODS

Blood samples were collected from 18 healthy volunteers. Blood was stored in the refrigerator and processed for plasma at 0, 15, 30, and 48 h after collection. Plasma samples were metabolically profiled using an untargeted, ultrahigh performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) platform. Reproducibility of 1012 metabolites over processing delays and reproducibility of the platform were determined by intraclass correlation coefficients (ICCs) with variance components estimated from mixed-effects models.

RESULTS

The majority of metabolites (approximately 70% of 1012) were highly reproducible (ICCs ≥ 0.75) over 15-, 30- or 48-h processing delays. Nucleotides, energy-related metabolites, peptides, and carbohydrates were most affected by processing delays. The platform was highly reproducible with a median technical ICC of 0.84 (interquartile range 0.68-0.93).

CONCLUSION

Most metabolites measured by the UPLC-MS/MS platform show acceptable reproducibility up to 48-h processing delays. Metabolites of certain pathways need to be interpreted cautiously in relation to outcomes in epidemiologic studies with prolonged processing delays.

Shotgun Lipidomics Combined with Laser Capture Microdissection: A Tool To Analyze Histological Zones in Cryosections of Tissues

Shotgun analysis provides a quantitative snapshot of the lipidome composition of cells, tissues, or model organisms; however, it does not elucidate the spatial distribution of lipids. Here we demonstrate that shotgun analysis could quantify low-picomole amounts of lipids isolated by laser capture microdissection (LCM) of hundred micrometer-sized histological zones visualized at the cryosections of tissues. We identified metabolically distinct periportal (pp) and pericentral (pc) zones by immunostaining of 20 μm thick cryosections of a healthy mouse liver. LCM was used to ablate, catapult, and collect the tissue material from 10 to 20 individual zones covering a total area of 0.3-0.5 mm² and containing ca. 500 cells. Top-down shotgun profiling relying upon computational stitching of 61 targeted selective ion monitoring ( t-SIM) spectra quantified more than 200 lipid species from 17 lipid classes including glycero- and glycerophospholipids, sphingolipids, cholesterol esters, and cholesterol. Shotgun LCM revealed the overall commonality of the full lipidome composition of pp and pc zones along with significant ( p < 0.001) difference in the relative abundance of 13 lipid species. Follow-up proteomics analyses of pellets recovered from an aqueous phase saved after the lipid extraction identified 13 known and 7 new protein markers exclusively present in pp or in pc zones and independently validated the specificity of their visualization, isolation, and histological assignment.

Improving metabolome coverage and data quality: advancing metabolomics and lipidomics for biomarker discovery

This Feature Article highlights some of the key challenges within the field of metabolomics and examines what role separation and analytical sciences can play to improve the use of metabolomics in biomarker discovery and personalized medicine. Recent progress in four key areas is highlighted: (i) improving metabolite coverage, (ii) developing accurate methods for unstable metabolites including in vivo global metabolomics methods, (iii) advancing inter-laboratory studies and reference materials and (iv) improving data quality, standardization and quality control of metabolomics studies.

Sphingolipid Analysis in Clinical Research

Sphingolipids are the most diverse class of lipids due to the numerous variations in their structural components. This diversity is also reflected in their extremely different functions. Sphingolipids are not only constituents of cell membranes but have also emerged as key signaling molecules involved in a variety of cellular functions, such as cell growth and differentiation, proliferation, and apoptotic cell death. Lipidomic analyses in clinical research have identified pathways and products of sphingolipid metabolism that are altered in several human pathologies. In this article, we describe how to properly design a lipidomic experiment in clinical research, how to handle plasma and serum samples for this purpose, and how to measure sphingolipids using liquid chromatography-mass spectrometry.

Lipidomic profiling of plasma in a healthy Singaporean population to identify ethnic specific differences in lipid levels and associations with disease risk factors

Background

Plasma lipids (i.e., cholesterol, low density lipoprotein (LDL-C), high density lipoprotein (HDL-C) and triglycerides) are linked to a range of metabolic diseases, including heart disease and diabetes. Plasma lipid species have similarly been associated with the same diseases. However, neither abundance profiling of plasma lipid species in healthy populations, nor differences between ethnic groups has not been reported.

Methods

In this study, we have profiled over 280 lipid species using liquid chromatography-tandem mass spectrometry, independently across two sites, in 359 healthy Singaporean individuals of Chinese (n = 122), Indian (n = 120) and Malay (n = 117) ethnicity.

Results

We found variations in abundance (defined as % coefficient of variation) of plasma lipid species that fluctuated between 13 and 120%. Analysis of covariance (ANCOVA) identified differences between ethnic groups, particularly among alkyl and alkenylphosphatidylethanolamine species, as well as in two species of sphingosine-1-phosphate (i.e., d18:0 and d18:1), which were elevated in the Chinese group. Regression analysis identified ethnic-specific differences in the association of plasma lipids and lipid species with age, gender and body mass index (BMI). Chinese and Malay groups showed a positive association of glycerolipids (i.e., diglycerides (DG), triglycerides (TG)) and cholesteryl esters (CE) with BMI, but this was not seen in the Indian group. Furthermore, Indian and Malay groups showed a positive association between the abundance of sphingolipids and age, which was absent in the Chinese group.

Conclusions

This study provides baseline characterisation of the natural biological variation of plasma lipid species in three healthy ethnic groups, and identifies important differences in plasma lipid levels and their association with known disease risk factors.

The application of lipidomics to biomarker research and pathomechanisms in Alzheimer's disease

PURPOSE OF REVIEW

Alzheimer's disease is the most common cause of dementia. There are still no disease modifying treatments that can cure or slow disease progression. Recently, Alzheimer's disease researchers have attempted to improve early detection and diagnostic criteria for Alzheimer's disease, with the rationale that treatment of disease, or even prevention, may be more successful during the early preclinical stages of Alzheimer's disease when neurodegenerative damage is not as widespread. As the brain has a high lipid content, lipidomics may offer novel insights into the underlying pathogenesis of Alzheimer's disease. This review reports on recent developments in the relatively unexplored field of lipidomics in Alzheimer's disease, including novel biomarkers and pathomechanisms of Alzheimer's disease.

RECENT FINDINGS

Numerous biomarker panels involving phospholipids and sphingolipids have been proposed, indicating perturbed lipid metabolism in early stages of Alzheimer's disease. Future strategies targeting these metabolic changes through dietary supplementation could have therapeutic benefits in at-risk individuals.

SUMMARY

Dysregulated lipid metabolism could reflect pathological changes in synaptic function and neuronal membranes, leading to cognitive decline. However, extensive validation in large independent cohorts is required before lipid biomarkers can be used clinically to assess Alzheimer's disease risk and progression.

Dysregulation of lipids in Alzheimer's disease and their role as potential biomarkers

The brain is highly enriched in lipids, and an intensive study of these lipids may be informative, not only of normal brain function but also of changes with age and in disease. In recent years, the development of highly sensitive mass spectrometry platforms and other high-throughput technologies has enabled the discovery of complex changes in the entire lipidome. This lipidomics approach promises to be a particularly useful tool for identifying diagnostic biomarkers for early detection of age-related neurodegenerative disease, such as Alzheimer's disease (AD), which has till recently been limited to protein- and gene-centric approaches. This review highlights known lipid changes affecting the AD brain and presents an update on the progress of lipid biomarker research in AD. Important considerations for designing large-scale lipidomics experiments are discussed to help standardize findings across different laboratories, as well as challenges associated with moving toward clinical application.

Elevated GM3 plasma concentration in idiopathic Parkinson's disease: A lipidomic analysis

Parkinson's disease (PD) is a common neurodegenerative disease whose pathological hallmark is the accumulation of intracellular α-synuclein aggregates in Lewy bodies. Lipid metabolism dysregulation may play a significant role in PD pathogenesis; however, large plasma lipidomic studies in PD are lacking. In the current study, we analyzed the lipidomic profile of plasma obtained from 150 idiopathic PD patients and 100 controls, taken from the 'Spot' study at Columbia University Medical Center in New York. Our mass spectrometry based analytical panel consisted of 520 lipid species from 39 lipid subclasses including all major classes of glycerophospholipids, sphingolipids, glycerolipids and sterols. Each lipid species was analyzed using a logistic regression model. The plasma concentrations of two lipid subclasses, triglycerides and monosialodihexosylganglioside (GM3), were different between PD and control participants. GM3 ganglioside concentration had the most significant difference between PD and controls (1.531±0.037 pmol/μl versus 1.337±0.040 pmol/μl respectively; p-value = 5.96E-04; q-value = 0.048; when normalized to total lipid: p-value = 2.890E-05; q-value = 2.933E-03). Next, we used a collection of 20 GM3 and glucosylceramide (GlcCer) species concentrations normalized to total lipid to perform a ROC curve analysis, and found that these lipids compare favorably with biomarkers reported in previous studies (AUC = 0.742 for males, AUC = 0.644 for females). Our results suggest that higher plasma GM3 levels are associated with PD. GM3 lies in the same glycosphingolipid metabolic pathway as GlcCer, a substrate of the enzyme glucocerebrosidase, which has been associated with PD. These findings are consistent with previous reports implicating lower glucocerebrosidase activity with PD risk.

Lipidomics, en route to accurate quantitation

Accurate quantitation is prerequisite for the sustainable development of lipidomics via enabling its applications in various biological and biomedical settings. In this review, the technical considerations and limitations of existent lipidomics technologies, particularly in terms of accurate quantitation; as well as the potential sources of errors along a typical lipidomic workflow that could ultimately give rise to quantitative inaccuracies will be addressed. Furthermore, the pressing need to exercise stricter definitions of terms and protocol standardization pertaining to quantitative lipidomics will be critically discussed, as quantitative accuracy may substantially impact upon the persevering development of lipidomics in the long run. This article is part of a Special Issue entitled: BBALIP_Lipidomics Opinion Articles edited by Sepp Kohlwein.

Metabolomics, Nutrition, and Potential Biomarkers of Food Quality, Intake, and Health Status

Diet, dietary patterns, and other environmental factors such as exposure to toxins are playing an important role in the prevention/development of many diseases, like obesity, type 2 diabetes, and consequently on the health status of individuals. A major challenge nowadays is to identify novel biomarkers to detect as early as possible metabolic dysfunction and to predict evolution of health status in order to refine nutritional advices to specific population groups. Omics technologies such as genomics, transcriptomics, proteomics, and metabolomics coupled with statistical and bioinformatics tools have already shown great potential in this research field even if so far only few biomarkers have been validated. For the past two decades, important analytical techniques have been developed to detect as many metabolites as possible in human biofluids such as urine, blood, and saliva. In the field of food science and nutrition, many studies have been carried out for food authenticity, quality, and safety, as well as for food processing. Furthermore, metabolomic investigations have been carried out to discover new early biomarkers of metabolic dysfunction and predictive biomarkers of developing pathologies (obesity, metabolic syndrome, type-2 diabetes, etc.). Great emphasis is also placed in the development of methodologies to identify and validate biomarkers of nutrients exposure.

High-throughput lipidomics enables discovery of the mode of action of huaxian capsule impacting the metabolism of sepsis

Severe sepsis (SS) is a major cause of mortality and morbidity in the intensive care unit and requires rapid diagnosis and treatment.

An Unbiased Lipidomics Approach Identifies Early Second Trimester Lipids Predictive of Maternal Glycemic Traits and Gestational Diabetes Mellitus

OBJECTIVE

To investigate the relationship between early second trimester serum lipidomic variation and maternal glycemic traits at 28 weeks and to identify predictive lipid biomarkers for gestational diabetes mellitus (GDM).

RESEARCH DESIGN AND METHODS

Prospective study of 817 pregnant women (discovery cohort, n = 200; validation cohort, n = 617) who provided an early second trimester serum sample and underwent an oral glucose tolerance test (OGTT) at 28 weeks. In the discovery cohort, lipids were measured using direct infusion mass spectrometry and correlated with OGTT results. Variable importance in projection (VIP) scores were used to identify candidate lipid biomarkers. Candidate biomarkers were measured in the validation cohort using liquid chromatography-mass spectrometry and tested for associations with OGTT results and GDM status.

RESULTS

Early second trimester lipidomic variation was associated with 1-h postload glucose levels but not with fasting plasma glucose levels. Of the 13 lipid species identified by VIP scores, 10 had nominally significant associations with postload glucose levels. In the validation cohort, 5 of these 10 lipids had significant associations with postload glucose levels that were independent of maternal age and BMI, i.e., TG(51.1), TG(48:1), PC(32:1), PCae(40:3), and PCae(40:4). All except the last were also associated with maternal GDM status. Together, these four lipid biomarkers had moderate ability to predict GDM (area under curve [AUC] = 0.71 ± 0.04, P = 4.85 × 10-7) and improved the prediction of GDM by age and BMI alone from AUC 0.69 to AUC 0.74.

CONCLUSIONS

Specific early second trimester lipid biomarkers can predict maternal GDM status independent of maternal age and BMI, potentially enhancing risk factor-based screening.

Mild TBI Results in a Long-Term Decrease in Circulating Phospholipids in a Mouse Model of Injury

Neurophysiological and neurological dysfunction is usually experienced for a short period of time in patients with mild traumatic brain injury (mTBI). However, around 15 % of patients exhibit symptoms months after TBI. Phospholipid (PL) changes have been observed in plasma from mTBI patients at chronic stages, suggesting a role in TBI pathology. We examined long-term plasma phospholipid profiles in a mouse model of mTBI to determine their translational value in reproducing PL changes observed in mTBI patients. Plasma samples were collected at an acute timepoint (24 h post-injury) and at several chronic stages (3, 6, 12 and 24 months post-injury) from injured mice and sham controls. Phospholipids were identified and quantified using liquid chromatography/mass spectrometry analysis. In accordance with human data, we observed significantly lower levels of several major PL classes in mTBI mice compared to controls at chronic timepoints. Saturated, monounsaturated and polyunsaturated fatty acids (PUFAs) were differently regulated over time. As PUFA levels were decreased at 3 months, we measured levels of malondialdehyde to assess lipid peroxidation, which we found to be elevated at this timepoint. Ether-containing PE species were elevated at 24 h post-injury and decreased relative to controls at chronic stages. Arachidonic acid and docosahexaenoic acid-containing species were significantly decreased within all PL classes at the chronic stages. Our findings are similar to changes in PL levels observed in human mTBI subjects. Chronic TBI biomarkers have received little attention, even though disabilities at this stage can be of major importance. Our study provides information on biochemical abnormalities that persist long after the initial injury; these abnormalities may provide useful insight into the continuing pathogenesis and serve as diagnostic biomarkers.

Gender, Contraceptives and Individual Metabolic Predisposition Shape a Healthy Plasma Lipidome

Lipidomics of human blood plasma is an emerging biomarker discovery approach that compares lipid profiles under pathological and physiologically normal conditions, but how a healthy lipidome varies within the population is poorly understood. By quantifying 281 molecular species from 27 major lipid classes in the plasma of 71 healthy young Caucasians whose 35 clinical blood test and anthropometric indices matched the medical norm, we provided a comprehensive, expandable and clinically relevant resource of reference molar concentrations of individual lipids. We established that gender is a major lipidomic factor, whose impact is strongly enhanced by hormonal contraceptives and mediated by sex hormone-binding globulin. In lipidomics epidemiological studies should avoid mixed-gender cohorts and females taking hormonal contraceptives should be considered as a separate sub-cohort. Within a gender-restricted cohort lipidomics revealed a compositional signature that indicates the predisposition towards an early development of metabolic syndrome in ca. 25% of healthy male individuals suggesting a healthy plasma lipidome as resource for early biomarker discovery.

Discovering lipid phenotypic changes of sepsis-induced lung injury using high-throughput lipidomic analysis

The aim of this study was to use lipidomics to identify lipid molecules that could predict patients with sepsis-induced lung injury.