Lipidomics is providing new insight into the metabolic syndrome and its sequelae

Lipoprotein Lipidomics as a Frontier in Non-Alcoholic Fatty Liver Disease Biomarker Discovery

Non-alcoholic fatty liver disease (NAFLD) is a progressive liver disease characterized by the build-up of fat in the liver of individuals in the absence of alcohol consumption. This condition has become a burden in modern societies aggravated by the lack of appropriate predictive biomarkers (other than liver biopsy). To better understand this disease and to find appropriate biomarkers, a new technology has emerged in the last two decades with the ability to explore the unmapped role of lipids in this disease: lipidomics. This technology, based on the combination of chromatography and mass spectrometry, has been extensively used to explore the lipid metabolism of NAFLD. In this review, we aim to summarize the knowledge gained through lipidomics assays exploring tissues, plasma, and lipoproteins from individuals with NAFLD. Our goal is to identify common features and active pathways that could facilitate the finding of a reliable biomarker from this field. The most frequent observation was a variable decrease (1-9%) in polyunsaturated fatty acids in phospholipids and non-esterified fatty acids in NAFLD patients, both in plasma and liver. Additionally, a reduction in phosphatidylcholines is a common feature in the liver. Due to the scarcity of studies, further research is needed to properly detect lipoprotein, plasma, and tissue lipid signatures of NAFLD etiologies, and NAFLD subtypes, and to define the relevance of this technology in disease management strategies in the push toward personalized medicine.

Exposure to per- and polyfluoroalkyl substance and metabolic syndrome: A nationally representative cross-sectional study from NHANES, 2003-2018

Per- and polyfluoroalkyl substances(PFAS) are widespread organic pollutants with endocrine-disrupting effects on human health, but the association of PFAS exposure with metabolic syndrome remains conflicting. National Health and Nutrition Examination Survey(NHANES) program was utilized to evaluate the association of individual PFAS exposure and metabolic disorders and further determined the joint effect of PFAS co-exposures. 13921 participants and five PFAS exposures(PFHxS, MPAH, PFDE, PFNA, and PFUA) were included for analysis. The association between individual PFAS and metabolic syndrome varied in the specific PFAS and the specific metabolic disorder examined. PFHxS was negatively associated with obesity(Q4; OR = 0.75; P < 0.001), but positively associated with hyperlipidemia (Q3; OR = 1.2; P = 0.013). PFUA was negatively associated with obesity (Q4; OR = 0.6; P < 0.001), hyperlipidemia (Q3; OR = 0.85; P = 0.03), and non-alcoholic fatty liver disease (NAFLD, Q4; OR = 0.64; P = 0.015), but positively associated with hyperglycemia(Q3; OR = 1.27; P = 0.004). Furthermore, PFAS co-exposures were negatively associated with obesity(OR = 0.63; P < 0.001) and NAFLD(OR = 0.85; P = 0.021), and positively associated with hyperlipidemia(OR = 1.05; P = 0.022), but not significantly associated with hyperglycemia or hypertension. Overall, there was a negative association between PFAS co-exposures and metabolic severity score(β = -0.15; P < 0.001). Subgroup analysis stratified by gender and obesity consistently showed the negative association of PFAS co-exposures with metabolic severity score, and the positive association with hyperlipidemia. However, subgroup analysis showed a negative association with NAFLD in females but not in males, and a negative association with hyperglycemia in the obesity group, but not in the non-obesity group. Collectively, our study showed a negative association of PFAS co-exposures with metabolic syndrome severity score, but did not support a consistent association between PFAS co-exposures and individual components of metabolic syndrome. Additionally, there were gender-specific as well as BMI-specific differences in these associations. Further studies are needed to rule out the reverse causality and clarify the relationship of PFAS co-exposures with the specific metabolic disorder.

Characterizing the metabolic divide: distinctive metabolites differentiating CAD-T2DM from CAD patients

OBJECTIVE

To delineate the metabolomic differences in plasma samples between patients with coronary artery disease (CAD) and those with concomitant CAD and type 2 diabetes mellitus (T2DM), and to pinpoint distinctive metabolites indicative of T2DM risk.

METHOD

Plasma samples from CAD and CAD-T2DM patients across three centers underwent comprehensive metabolomic and lipidomic analyses. Multivariate logistic regression was employed to discern the relationship between the identified metabolites and T2DM risk. Characteristic metabolites' metabolic impacts were further probed through hepatocyte cellular experiments. Subsequent transcriptomic analyses elucidated the potential target sites explaining the metabolic actions of these metabolites.

RESULTS

Metabolomic analysis revealed 192 and 95 significantly altered profiles in the discovery (FDR < 0.05) and validation (P < 0.05) cohorts, respectively, that were associated with T2DM risk in univariate logistic regression. Further multivariate regression analyses identified 22 characteristic metabolites consistently associated with T2DM risk in both cohorts. Notably, pipecolinic acid and L-pipecolic acid, lysine derivatives, exhibited negative association with CAD-T2DM and influenced cellular glucose metabolism in hepatocytes. Transcriptomic insights shed light on potential metabolic action sites of these metabolites.

CONCLUSIONS

This research underscores the metabolic disparities between CAD and CAD-T2DM patients, spotlighting the protective attributes of pipecolinic acid and L-pipecolic acid. The comprehensive metabolomic and transcriptomic findings provide novel insights into the mechanism research, prophylaxis and treatment of comorbidity of CAD and T2DM.

Plasma lipidomic profiling reveals six candidate biomarkers for the prediction of incident stroke in patients with hypertension

INTRODUCTION

The burden of stroke in patients with hypertension is very high, and its prediction is critical.

OBJECTIVES

We aimed to use plasma lipidomics profiling to identify lipid biomarkers for predicting incident stroke in patients with hypertension.

METHODS

This was a nested case-control study. Baseline plasma samples were collected from 30 hypertensive patients with newly developed stroke, 30 matched patients with hypertension, 30 matched patients at high risk of stroke, and 30 matched healthy controls. Lipidomics analysis was performed by ultrahigh-performance liquid chromatography-tandem mass spectrometry, and differential lipid metabolites were screened using multivariate and univariate statistical methods. Machine learning methods (least absolute shrinkage and selection operator, random forest) were used to identify candidate biomarkers for predicting stroke in patients with hypertension.

RESULTS

Co-expression network analysis revealed that the key molecular alterations of the lipid network in stroke implicate glycerophospholipid metabolism and choline metabolism. Six lipid metabolites were identified as candidate biomarkers by multivariate statistical and machine learning methods, namely phosphatidyl choline(40:3p)(rep), cholesteryl ester(20:5), monoglyceride(29:5), triglyceride(18:0p/18:1/18:1), triglyceride(18:1/18:2/21:0) and coenzyme(q9). The combination of these six lipid biomarkers exhibited good diagnostic and predictive ability, as it could indicate a risk of stroke at an early stage in patients with hypertension (area under the curve = 0.870; 95% confidence interval: 0.783-0.957).

CONCLUSIONS

We determined lipidomic signatures associated with future stroke development and identified new lipid biomarkers for predicting stroke in patients with hypertension. The biomarkers have translational potential and thus may serve as blood-based biomarkers for predicting hypertensive stroke.

Triterpenoids from the genus Ilex attenuate free fatty acid-induced lipid accumulation in HepG2 cells by regulating lipid metabolism disorder and the AMPK signalling pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Various traditional Chinese medicines from the genus Ilex (Aquifoliaceae) have been reported to have excellent hypolipidaemic effects. Although triterpenoids have been found to be the main active components, the underlying mechanisms have not been clarified.

AIM OF THE STUDY

This study aimed to investigate the lipid-lowering effect, structure-activity relationship and action mechanism of triterpenoids from the genus Ilex.

MATERIALS AND METHODS

FFA was used to induce HepG2 cells to establish a classical lipid-lowering activity screening model for the activities of 31 triterpenoids, and the contents of intracellular lipids, TC, and TG were measured. Furthermore, the structure-activity relationship was discussed. Mechanistically, UPLC-Q/TOF-MS-based metabolomics and lipidomics studies were performed, and metabolic pathways were analysed to investigate the lipid-lowering mechanism. Moreover, western blotting was performed to analyse the expression of key proteins of lipid metabolism and predict the targets of action.

RESULTS

Thirteen triterpenoids significantly reduced intracellular lipid accumulation and decreased the levels of TG and TC. Among them, rotundic acid (RA) showed stronger lipid-lowering activity than the simvastatin-positive group, and structure-activity relationship analysis indicated that the hydroxyl groups at C-3 and C-19, hydroxymethyl groups at C-23, and carboxyl groups at C-28 may be the key groups for biological activity. Twenty-two metabolites in the metabolomics study and 19 metabolites in the lipidomics study were identified. The identified biomarkers were primarily glycerophosphocholine, LysoPCs, PCs, TAGs, LysoPEs, LysoPIs and sphingolipids, which are involved in glycerophospholipid and sphingolipid metabolism. Moreover, western blotting analysis showed that the expression of SREBP-1 and HMGCR decreased, while AMPK and ACC phosphorylation and the expression of CPT1A and CYP7A1 increased in the RA-treated group.

CONCLUSION

The results suggested that triterpenoids from the genus Ilex showed significant lipid-lowering effects and that RA may be a novel hypolipidaemic drug candidate. Moreover, the underlying mechanism indicated that RA showed a lipid-lowering effect by regulating glycerophospholipid and sphingolipid metabolism and activating the AMPK pathway.

Dietary squalene supplementation decreases triglyceride species and modifies phospholipid lipidomic profile in the liver of a porcine model of non-alcoholic steatohepatitis

Squalene is a key minor component of virgin olive oil, the main source of fat in the Mediterranean diet, and had shown to improve the liver metabolism in rabbits and mice. The present research was carried out to find out whether this effect was conserved in a porcine model of hepatic steatohepatitis and to search for the lipidomic changes involved. The current study revealed that a 0.5% squalene supplementation to a steatotic diet for a month led to hepatic accumulation of squalene and decreased triglyceride content as well as area of hepatic lipid droplets without influencing cholesterol content or fiber areas. However, ballooning score was increased and associated with the hepatic squalene content. Of forty hepatic transcripts related to lipid metabolism and hepatic steatosis, only citrate synthase and a non-coding RNA showed decreased expressions. The hepatic lipidome, assessed by liquid chromatography-mass spectrometry in a platform able to analyze 467 lipids, revealed that squalene supplementation increased ceramide, Cer(36:2), and phosphatidylcholine (PC[32:0], PC[33:0] and PC[34:0]) species and decreased cardiolipin, CL(69:5), and triglyceride (TG[54:2], TG[55:0] and TG[55:2]) species. Plasma levels of interleukin 12p40 increased in pigs receiving the squalene diet. The latter also modified plasma lipidome by increasing TG(58:12) and decreasing non-esterified fatty acid (FA 14:0, FA 16:1 and FA 18:0) species without changes in total NEFA levels. Together this shows that squalene-induced changes in hepatic and plasma lipidomic profiles, non-coding RNA and anti-inflammatory interleukin are suggestive of an alleviation of the disease despite the increase in the ballooning score.

Multiomics Analysis-Based Biomarkers in Diagnosis of Polycystic Ovary Syndrome

Polycystic ovarian syndrome is an utmost communal endocrine, psychological, reproductive, and metabolic disorder that occurs in women of reproductive age with extensive range of clinical manifestations. This may even lead to long-term multiple morbidities including obesity, diabetes mellitus, insulin resistance, cardiovascular disease, infertility, cerebrovascular diseases, and ovarian and endometrial cancer. Women affliction from PCOS in midst assemblage of manifestations allied with menstrual dysfunction and androgen exorbitance, which considerably affects eminence of life. PCOS is recognized as a multifactorial disorder and systemic syndrome in first-degree family members; therefore, the etiology of PCOS syndrome has not been copiously interpreted. The disorder of PCOS comprehends numerous allied health conditions and has influenced various metabolic processes. Due to multifaceted pathophysiology engaging several pathways and proteins, single genetic diagnostic tests cannot be supportive to determine in straight way. Clarification of cellular and biochemical pathways and various genetic players underlying PCOS could upsurge our consideration of pathophysiology of this syndrome. It is requisite to know pathophysiological relationship between biomarker and their reflection towards PCOS disease. Biomarkers deliver vibrantly and potent ways to apprehend the spectrum of PCOS with applications in screening, diagnosis, characterization, and monitoring. This paper relies on the endeavor to point out many candidates as potential biomarkers based on omics technologies, thus highlighting correlation between PCOS disease with innovative technologies. Therefore, the objective of existing review is to encapsulate more findings towards cutting-edge advances in prospective use of biomarkers for PCOS disease. Discussed biomarkers may be fruitful in guiding therapies, addressing disease risk, and predicting clinical outcomes in future.

Lipidomics profiling of biological aging in American Indians: the Strong Heart Family Study

Telomeres shorten with age and shorter leukocyte telomere length (LTL) has been associated with various age-related diseases. Thus, LTL has been considered a biomarker of biological aging. Dyslipidemia is an established risk factor for most age-related metabolic disorders. However, little is known about the relationship between LTL and dyslipidemia. Lipidomics is a new biochemical technique that can simultaneously identify and quantify hundreds to thousands of small molecular lipid species. In a large population comprising 1843 well-characterized American Indians in the Strong Heart Family Study, we examined the lipidomic profile of biological aging assessed by LTL. Briefly, LTL was quantified by qPCR. Fasting plasma lipids were quantified by untargeted liquid chromatography-mass spectrometry. Lipids associated with LTL were identified by elastic net modeling. Of 1542 molecular lipids identified (518 known, 1024 unknown), 174 lipids (36 knowns) were significantly associated with LTL, independent of chronological age, sex, BMI, hypertension, diabetes status, smoking status, bulk HDL-C, and LDL-C. These findings suggest that altered lipid metabolism is associated with biological aging and provide novel insights that may enhance our understanding of the relationship between dyslipidemia, biological aging, and age-related diseases in American Indians.

Genetic Architecture of Untargeted Lipidomics in Cardiometabolic-Disease Patients Combines Strong Polygenic Control and Pleiotropy

Analysis of the genetic control of small metabolites provides powerful information on the regulation of the endpoints of genome expression. We carried out untargeted liquid chromatography−high-resolution mass spectrometry in 273 individuals characterized for pathophysiological elements of the cardiometabolic syndrome. We quantified 3013 serum lipidomic features, which we used in both genome-wide association studies (GWAS), using a panel of over 2.5 M imputed single-nucleotide polymorphisms (SNPs), and metabolome-wide association studies (MWAS) with phenotypes. Genetic analyses showed that 926 SNPs at 551 genetic loci significantly (q-value < 10−8) regulate the abundance of 74 lipidomic features in the group, with evidence of monogenic control for only 22 of these. In addition to this strong polygenic control of serum lipids, our results underscore instances of pleiotropy, when a single genetic locus controls the abundance of several distinct lipid features. Using the LIPID MAPS database, we assigned putative lipids, predominantly fatty acyls and sterol lipids, to 77% of the lipidome signals mapped to the genome. We identified significant correlations between lipids and clinical and biochemical phenotypes. These results demonstrate the power of untargeted lipidomic profiling for high-density quantitative molecular phenotyping in human-genetic studies and illustrate the complex genetic control of lipid metabolism.

Sphingolipid Profiling: A Promising Tool for Stratifying the Metabolic Syndrome-Associated Risk

Metabolic syndrome (MetS) is a multicomponent risk condition that reflects the clustering of individual cardiometabolic risk factors related to abdominal obesity and insulin resistance. MetS increases the risk for cardiovascular diseases (CVD) and type 2 diabetes mellitus (T2DM). However, there still is not total clinical consensus about the definition of MetS, and its pathophysiology seems to be heterogeneous. Moreover, it remains unclear whether MetS is a single syndrome or a set of diverse clinical conditions conferring different metabolic and cardiovascular risks. Indeed, traditional biomarkers alone do not explain well such heterogeneity or the risk of associated diseases. There is thus a need to identify additional biomarkers that may contribute to a better understanding of MetS, along with more accurate prognosis of its various chronic disease risks. To fulfill this need, omics technologies may offer new insights into associations between sphingolipids and cardiometabolic diseases. Particularly, ceramides –the most widely studied sphingolipid class– have been shown to play a causative role in both T2DM and CVD. However, the involvement of simple glycosphingolipids remains controversial. This review focuses on the current understanding of MetS heterogeneity and discuss recent findings to address how sphingolipid profiling can be applied to better characterize MetS-associated risks.

Integrative Lipidomics and Metabolomics for System-Level Understanding of the Metabolic Syndrome in Long-Term Treated HIV-Infected Individuals

People living with HIV (PLWH) require life-long anti-retroviral treatment and often present with comorbidities such as metabolic syndrome (MetS). Systematic lipidomic characterization and its association with the metabolism are currently missing. We included 100 PLWH with MetS and 100 without MetS from the Copenhagen Comorbidity in HIV Infection (COCOMO) cohort to examine whether and how lipidome profiles are associated with MetS in PLWH. We combined several standard biostatistical, machine learning, and network analysis techniques to investigate the lipidome systematically and comprehensively and its association with clinical parameters. Additionally, we generated weighted lipid-metabolite networks to understand the relationship between lipidomic profiles with those metabolites associated with MetS in PLWH. The lipidomic dataset consisted of 917 lipid species including 602 glycerolipids, 228 glycerophospholipids, 61 sphingolipids, and 26 steroids. With a consensus approach using four different statistical and machine learning methods, we observed 13 differentially abundant lipids between PLWH without MetS and PLWH with MetS, which mainly belongs to diacylglyceride (DAG, n = 2) and triacylglyceride (TAG, n = 11). The comprehensive network integration of the lipidomics and metabolomics data suggested interactions between specific glycerolipids' structural composition patterns and key metabolites involved in glutamate metabolism. Further integration of the clinical data with metabolomics and lipidomics resulted in the association of visceral adipose tissue (VAT) and exposure to earlier generations of antiretroviral therapy (ART). Our integrative omics data indicated disruption of glutamate and fatty acid metabolism, suggesting their involvement in the pathogenesis of PLWH with MetS. Alterations in the lipid homeostasis and glutaminolysis need clinical interventions to prevent accelerated aging in PLWH with MetS.

Serumal Lipidomics Reveals the Anti-inflammatory Effect of Flax Lignans and Sinapic Acid in High-Fat-Diet-Fed Mice

Flax lignans (SDG) and sinapic acid (SA) both have the function of antioxidation and anti-inflammation. However, previous studies have focused mainly on biochemical measurements, gene expression analysis, and clinical assessments. There are limited studies that systematically reveal the underlying mechanism of the anti-inflammation effect of SDG or SA from the lipidomic point of view. Herein, the integrated lipidomic profiling platform was used for the analysis of free fatty acids (FFAs), phospholipids (PLs), triacylglycerols (TAGs), and oxylipins in high-fat (HF)-diet-fed mice after SDG or SA administration. Dietary supplementation of SDG or SA downregulated the levels of total TAGs and FFAs in the ApoE^-/- mice model. Furthermore, 28 potential lipids were screened out and considered as key evaluation factors to understand the anti-inflammation function and mechanism of SDG and SA. The results indicated that the anti-inflammatory effect of SDG and SA was principally exerted via regulation of lipid homeostasis.

Plasma Sphingolipid Profile in Association with Incident Metabolic Syndrome in a Chinese Population-Based Cohort Study

Although bioactive sphingolipids have been shown to regulate cardiometabolic homeostasis and inflammatory signaling pathways in rodents, population-based longitudinal studies of relationships between sphingolipids and onset of metabolic syndrome (MetS) are sparse. We aimed to determine associations of circulating sphingolipids with inflammatory markers, adipokines, and incidence of MetS. Among 1242 Chinese people aged 50–70 years who completed the 6-year resurvey, 76 baseline plasma sphingolipids were quantified by high-throughput liquid chromatography-tandem mass spectrometry. There were 431 incident MetS cases at 6-year revisit. After multivariable adjustment including lifestyle characteristics and BMI, 21 sphingolipids mainly from ceramide and hydroxysphingomyelin subclasses were significantly associated with incident MetS. Meanwhile, the baseline ceramide score was positively associated (RR_{Q4 versus Q1} = 1.31; 95% CI 1.05, 1.63; p_trend = 0.010) and the hydroxysphingomyelin score was inversely associated (RR_{Q4 versus Q1} = 0.60; 95% CI 0.45, 0.79; p_trend < 0.001) with incident MetS. When further controlling for clinical lipids, both associations were attenuated but remained significant. Comparing extreme quartiles, RRs (95% CIs) of MetS risk were 1.34 (95% CI 1.06, 1.70; p_trend = 0.010) for ceramide score and 0.71 (95% CI 0.51, 0.97; p_trend = 0.018) for hydroxysphingomyelin score, respectively. Furthermore, a stronger association between ceramide score and incidence of MetS was evidenced in those having higher inflammation levels (RR_{Q4 versus Q1} 1.57; 95% CI 1.16, 2.12; p_interaction = 0.004). Our data suggested that elevated ceramide concentrations were associated with a higher MetS risk, whereas raised hydroxysphingomyelin levels were associated with a lower MetS risk beyond traditional clinical lipids.

Multiplatform metabolomics for an integrative exploration of metabolic syndrome in older men

BACKGROUND

Metabolic syndrome (MetS), a cluster of factors associated with risks of developing cardiovascular diseases, is a public health concern because of its growing prevalence. Considering the combination of concomitant components, their development and severity, MetS phenotypes are largely heterogeneous, inducing disparity in diagnosis.

METHODS

A case/control study was designed within the NuAge longitudinal cohort on aging. From a 3-year follow-up of 123 stable individuals, we present a deep phenotyping approach based on a multiplatform metabolomics and lipidomics untargeted strategy to better characterize metabolic perturbations in MetS and define a comprehensive MetS signature stable over time in older men.

FINDINGS

We characterize significant changes associated with MetS, involving modulations of 476 metabolites and lipids, and representing 16% of the detected serum metabolome/lipidome. These results revealed a systemic alteration of metabolism, involving various metabolic pathways (urea cycle, amino-acid, sphingo- and glycerophospholipid, and sugar metabolisms…) not only intrinsically interrelated, but also reflecting environmental factors (nutrition, microbiota, physical activity…).

INTERPRETATION

These findings allowed identifying a comprehensive MetS signature, reduced to 26 metabolites for future translation into clinical applications for better diagnosing MetS.

FUNDING

The NuAge Study was supported by a research grant from the Canadian Institutes of Health Research (CIHR; MOP-62842). The actual NuAge Database and Biobank, containing data and biologic samples of 1,753 NuAge participants (from the initial 1,793 participants), are supported by the Fonds de recherche du Québec (FRQ; 2020-VICO-279753), the Quebec Network for Research on Aging, a thematic network funded by the Fonds de Recherche du Québec - Santé (FRQS) and by the Merck-Frost Chair funded by La Fondation de l'Université de Sherbrooke. All metabolomics and lipidomics analyses were funded and performed within the metaboHUB French infrastructure (ANR-INBS-0010). All authors had full access to the full data in the study and accept responsibility to submit for publication.

Profiling of Cerebrospinal Fluid Lipids and Their Relationship with Plasma Lipids in Healthy Humans

Lipidomics provides an overview of lipid profiles in biological systems. Although blood is commonly used for lipid profiling, cerebrospinal fluid (CSF) is more suitable for exploring lipid homeostasis in brain diseases. However, whether an individual’s background affects the CSF lipid profile remains unclear, and the association between CSF and plasma lipid profiles in heathy individuals has not yet been defined. Herein, lipidomics approaches were employed to analyze CSF and plasma samples obtained from 114 healthy Japanese subjects. Results showed that the global lipid profiles differed significantly between CSF and plasma, with only 13 of 114 lipids found to be significantly correlated between the two matrices. Additionally, the CSF total protein content was the primary factor associated with CSF lipids. In the CSF, the levels of major lipids, namely, phosphatidylcholines, sphingomyelins, and cholesterolesters, correlated with CSF total protein levels. These findings indicate that CSF lipidomics can be applied to explore changes in lipid homeostasis in patients with brain diseases.

Changes in the lipidome in type 1 diabetes following low carbohydrate diet: Post-hoc analysis of a randomized crossover trial

Aims

Lipid metabolism might be compromised in type 1 diabetes, and the understanding of lipid physiology is critically important. This study aimed to compare the change in plasma lipid concentrations during carbohydrate dietary changes in individuals with type 1 diabetes and identify links to early-stage dyslipidaemia. We hypothesized that (1) the lipidomic profiles after ingesting low or high carbohydrate diet for 12 weeks would be different; and (2) specific annotated lipid species could have significant associations with metabolic outcomes.

Methods

Ten adults with type 1 diabetes (mean ± SD: age 43.6 ± 13.8 years, diabetes duration 24.5 ± 13.4 years, BMI 24.9 ± 2.1 kg/m2, HbA1c 57.6 ± 2.6 mmol/mol) using insulin pumps participated in a randomized 2-period crossover study with a 12-week intervention period of low carbohydrate diet (< 100 g carbohydrates/day) or high carbohydrate diet (> 250 g carbohydrates/day), respectively, separated by a 12-week washout period. A large-scale non-targeted lipidomics was performed with mass spectrometry in fasting plasma samples obtained before and after each diet intervention. Longitudinal lipid levels were analysed using linear mixed-effects models.

Results

In total, 289 lipid species were identified from 14 major lipid classes. Comparing the two diets, 11 lipid species belonging to sphingomyelins, phosphatidylcholines and LPC(O-16:0) were changed. All the 11 lipid species were significantly elevated during low carbohydrate diet. Two lipid species were most differentiated between diets, namely SM(d36:1) (β ± SE: 1.44 ± 0.28, FDR = 0.010) and PC(P-36:4)/PC(O-36:5) (β ± SE: 1.34 ± 0.25, FDR = 0.009) species. Polyunsaturated PC(35:4) was inversely associated with BMI and positively associated with HDL cholesterol (p < .001).

Conclusion

Lipidome-wide outcome analysis of a randomized crossover trial of individuals with type 1 diabetes following a low carbohydrate diet showed an increase in sphingomyelins and phosphatidylcholines which are thought to reduce dyslipidaemia. The polyunsaturated phosphatidylcholine 35:4 was inversely associated with BMI and positively associated with HDL cholesterol (p < .001). Results from this study warrant for more investigation on the long-term effect of single lipid species in type 1 diabetes.

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

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

Circadian Lipidomics: Analysis of Lipid Metabolites Around the Clock

Lipidomics has been defined as the large-scale analysis of lipids in organelles, cells, tissues, or whole organisms. Including the temporal aspects of lipid metabolic changes into this analysis allows to access yet another important aspect of lipid regulation. The resulting methodology, circadian lipidomics, has thus emerged as a novel tool to address the enormous complexity, which is present among cellular lipids. Here, we describe how mass spectrometry-based circadian lipidomics can be applied to study the impact of peripheral clocks on lipid metabolism in human primary cells and tissues, exemplified by studies in human pancreatic islets and skeletal myotubes.

Plasma Lipid Profiling of Three Types of Drug-Induced Liver Injury in Japanese Patients: A Preliminary Study

Drug-induced liver injury (DILI) is a major adverse event caused by drug treatment, which can be categorized into three types: hepatocellular, mixed, and cholestatic. Although nearly every class of drugs can cause DILI, an overall understanding of lipid profiles in DILI patients is lacking. We used lipidomics to analyze the plasma lipid profiles of patients to understand their hepatic pathophysiology and identify DILI biomarkers. We identified 463 lipids and compared their levels between the acute and recovery phases of the three types of DILI patients. Mixed and cholestatic types demonstrated specific plasma lipid alterations between the phases, but the hepatocellular type did not. Moreover, as specific indicators of mixed-type DILI, levels of several ceramides increased in the acute phase, while those of arachidonic acid-containing ether-linked phosphoglycerolipids decreased. In contrast, as specific indicators of cholestatic-type DILI, levels of palmitic acid-containing saturated or monounsaturated phosphatidylcholines increased in the acute phase, while those of arachidonic acid- or docosahexaenoic acid-containing ether-linked phosphoglycerolipids and phosphatidylinositols decreased. We also identified lipids with a relatively high capacity to discriminate the acute phase from the recovery phase and healthy subjects. These findings may help with understanding the pathophysiology of different DILI types and identify candidate biomarkers.

Mass spectrometry-based lipidomics in food science and nutritional health: A comprehensive review

With the advance in science and technology as well as the improvement of living standards, the function of food is no longer just to meet the needs of survival. Food science and its associated nutritional health issues have been increasingly debated. Lipids, as complex metabolites, play a key role both in food and human health. Taking advantages of mass spectrometry (MS) by combining its high sensitivity and accuracy with extensive selective determination of all lipid classes, MS-based lipidomics has been employed to resolve the conundrum of addressing both qualitative and quantitative aspects of high-abundance and low-abundance lipids in complex food matrices. In this review, we systematically summarize current applications of MS-based lipidomics in food field. First, common MS-based lipidomics procedures are described. Second, the applications of MS-based lipidomics in food science, including lipid composition characterization, adulteration, traceability, and other issues, are discussed. Third, the application of MS-based lipidomics for nutritional health covering the influence of food on health and disease is introduced. Finally, future research trends and challenges are proposed. MS-based lipidomics plays an important role in the field of food science, promoting continuous development of food science and integration of food knowledge with other disciplines. New methods of MS-based lipidomics have been developed to improve accuracy and sensitivity of lipid analysis in food samples. These developments offer the possibility to fully characterize lipids in food samples, identify novel functional lipids, and better understand the role of food in promoting healt.

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.

Irradiation impairs mitochondrial function and skeletal muscle oxidative capacity: significance for metabolic complications in cancer survivors

BACKGROUND

Metabolic complications are highly prevalent in cancer survivors treated with irradiation but the underlying mechanisms remain unknown.

METHODS

Chow or high fat-fed C57Bl/6J mice were irradiated (6Gy) before investigating the impact on whole-body or skeletal muscle metabolism and profiling their lipidomic signature. Using a transgenic mouse model (Tg:Pax7-nGFP), we isolated muscle progenitor cells (satellite cells) and characterised their metabolic functions. We recruited childhood cancer survivors, grouped them based on the use of total body irradiation during their treatment and established their lipidomic profile.

RESULTS

In mice, irradiation delayed body weight gain and impaired fat pads and muscle weights. These changes were associated with impaired whole-body fat oxidation in chow-fed mice and altered ex vivo skeletal muscle fatty acid oxidation, potentially due to a reduction in oxidative fibres and reduced mitochondrial enzyme activity. Irradiation led to fasting hyperglycaemia and impaired glucose uptake in isolated skeletal muscles. Cultured satellite cells from irradiated mice showed decreased fatty acid oxidation and reduced glucose uptake, recapitulating the host metabolic phenotype. Irradiation resulted in a remodelling of lipid species in skeletal muscles, with the extensor digitorum longus muscle being particularly affected. A large number of lipid species were reduced, with several of these species showing a positive correlation with mitochondrial enzymes activity. In cancer survivors exposed to irradiation, we found a similar decrease in systemic levels of most lipid species, and lipid species that increased were positively correlated with insulin resistance (HOMA-IR).

CONCLUSION

Irradiation leads to long-term alterations in body composition, and lipid and carbohydrate metabolism in skeletal muscle, and affects muscle progenitor cells. Such changes result in persistent impairment of metabolic functions, providing a new mechanism for the increased prevalence of metabolic diseases reported in irradiated individuals. In this context, changes in the lipidomic signature in response to irradiation could be of diagnostic value.

Overall Similarities and a Possible Factor Affecting Plasma Metabolome Profiles Between Venous and Capillary Blood Samples From 20 Healthy Human Males

Amino acids and lipids are biomarkers used to assess the presence and severity of disease, as well as the toxicological response to drugs. Although upper-extremity venipuncture is a well-used standard technique, fingertip capillary sampling is a more convenient procedure. Delineating the global differences in amino acid and lipid levels in capillary and venous blood samples is paramount for expanding the application of capillary blood tests in biomarker assays. We recruited 20 healthy male subjects and collected plasma obtained from both fingertip capillary and antecubital venous blood. The samples were analyzed to determine the overall profiles of amino acids and lipids and to test for differences in their levels between both vessel types. The results demonstrated that the differences between capillary and venous blood had a lower impact than interindividual variations; however, trends of separation between them were observed for amino acids. The levels of 5 out of 28 amino acids scored fold changes over 30%, while 9 out of 498 lipids had a fold change over 30%. The time required for fingertip blood collection could be a factor for the differences in 3 metabolites. These findings provide useful information for the application of fingertip capillary blood sampling in biomarker assays.

Characterization of Bulk Phosphatidylcholine Compositions in Human Plasma Using Side-Chain Resolving Lipidomics

Kit-based assays, such as AbsoluteIDQ^TM p150, are widely used in large cohort studies and provide a standardized method to quantify blood concentrations of phosphatidylcholines (PCs). Many disease-relevant associations of PCs were reported using this method. However, their interpretation is hampered by lack of functionally-relevant information on the detailed fatty acid side-chain compositions as only the total number of carbon atoms and double bonds is identified by the kit. To enable more substantiated interpretations, we characterized these PC sums using the side-chain resolving Lipidyzer^TM platform, analyzing 223 samples in parallel to the AbsoluteIDQ^TM. Combining these datasets, we estimated the quantitative composition of PC sums and subsequently tested their replication in an independent cohort. We identified major constituents of 28 PC sums, revealing also various unexpected compositions. As an example, PC 16:0_22:5 accounted for more than 50% of the PC sum with in total 38 carbon atoms and 5 double bonds (PC aa 38:5). For 13 PC sums, we found relatively high abundances of odd-chain fatty acids. In conclusion, our study provides insights in PC compositions in human plasma, facilitating interpretation of existing epidemiological data sets and potentially enabling imputation of PC compositions for future meta-analyses of lipidomics data.

Increased adiposity, inflammation, metabolic disruption and dyslipidemia in adult male offspring of DOSS treated C57BL/6 dams

Evidence indicates that obesity can be promoted by chemical ‘obesogens’ that drive adiposity, hunger, inflammation and suppress metabolism. Dioctyl sodium sulfosuccinate (DOSS), a lipid emulsifier and candidate obesogen in vitro, is widely used in processed foods, cosmetics and as stool softener medicines commonly used during pregnancy. In vivo testing of DOSS was performed in a developmental origins of adult obesity model. Pregnant mice were orally administered vehicle control or DOSS at times and doses comparable to stool softener use during human pregnancy. All weaned offspring consumed only standard diet. Adult male but not female offspring of DOSS-treated dams showed significantly increased body mass, overall and visceral fat masses, and decreased bone area. They exhibited significant decreases in plasma adiponectin and increases in leptin, glucose intolerance and hyperinsulinemia. Inflammatory IL-6 was elevated, as was adipose Cox2 and Nox4 gene expressions, which may be associated with promoter DNA methylation changes. Multiple significant phospholipid/sterol lipid increases paralleled profiles from long-term high-fat diet induced obesity in males. Collectively, developmental DOSS exposure leads to increased adult adiposity, inflammation, metabolic disorder and dyslipidemia in offspring fed a standard diet, suggesting that pharmaceutical and other sources of DOSS taken during human pregnancy might contribute to long-term obesity-related health concerns in offspring.

Changes in lipids composition and metabolism in colorectal cancer: a review

Altered metabolism of lipids is currently considered a hallmark characteristic of many malignancies, including colorectal cancer (CRC). Lipids are a large group of metabolites that differ in terms of their fatty acid composition. This review summarizes recent evidence, documenting many alterations in the content and composition of fatty acids, polar lipids, oxylipins and triacylglycerols in CRC patients' sera, tumor tissues and adipose tissue. Some of altered lipid molecules may be potential biomarkers of CRC risk, development and progression. Owing to a significant role of many lipids in cancer cell metabolism, some of lipid metabolism pathways may also constitute specific targets for anti-CRC therapy.

Lipidomics reveal aryl hydrocarbon receptor (Ahr)-regulated lipid metabolic pathway in alpha-naphthyl isothiocyanate (ANIT)-induced intrahepatic cholestasis

1. Ultra-performance liquid chromatography coupled with electrospray ionization quadrupole mass spectrometry (UPLC-ESI-QTOF MS)-based lipidomics was employed to elucidate new mechanism of alpha-naphthyl isothiocyanate (ANIT)-induced intrahepatic cholestasis in mice. 2. Multiple lipid components significantly increased in ANIT-induced intrahepatic cholestasis, including PC 16:0, 20:4, PC 16:0, 22:6, PC 16:0, 18:2, LPC 18:2, PC 18:2, LPC 18:1, PC 18:1, 14:0, SM 18:1, 16:0, oleoylcarnitine and palmitoylcarnitine. This alteration of lipid profile was induced by the changed expression of genes choline kinase (Chk) a, sphingomyelin phosphodiesterase (SMPD) and stearoyl-coenzyme A desaturase 1 (SCD1). 3. Knockout of aryl hydrocarbon receptor (Ahr) in mice can significantly reverse ANIT-induced intrahepatic cholestasis, as indicated by lowered ALT, AST and ALP activity, and liver histology. Aryl hydrocarbon receptor knockout significantly reversed ANIT-induced lipid metabolism alteration through regulating the expression of Chka. 4. In conclusion, this study demonstrated ANIT-induced lipid metabolism disruption might be the potential pathogenesis of ANIT-induced intrahepatic cholestasis in mice.

Feeding a slowly digestible carbohydrate diet during pregnancy of insulin-resistant rats prevents the excess of adipogenesis in their offspring

An obesogenic environment during pregnancy has been shown to increase the risk of dysregulation on adipogenesis and insulin resistance in the offspring. Being essential for the growing fetus, glucose supply is guaranteed by a number of modifications in the mother's metabolism, and thus, glucose control during pregnancy especially among obese or diabetic women is paramount to prevent adverse consequences in their children. Besides the election of low-glycemic-index carbohydrates, the rate of carbohydrate digestion could be relevant to keep a good glucose control. In the present study, we compared the effects of two high-fat diets with similar glycemic load but different rates of carbohydrate digestion given to pregnant insulin-resistant rats. After birth, all animals were fed a standard diet until age 14 weeks. We analyzed offspring body composition, plasma and adipocyte lipidomics, lipid metabolism in adipose tissue and insulin sensitivity. Those animals whose mothers were fed the rapid-digesting carbohydrate diet exhibited an excessive adipogenesis. Thus, these animals showed a marked lipidemia, increased lipid synthesis in the adipose tissue and reduced glucose transporter amount in the adipose. On the contrary, those animals whose mothers were fed the slow-digesting carbohydrate diet showed a profile in the measured parameters closer to that of the offspring of healthy mothers. These results support the hypothesis that not only glycemic index but the rate of carbohydrate digestion during gestation may be critical to regulate the programming of adipogenesis in the offspring.

Long-chain polyunsaturated fatty acids and extensively hydrolyzed casein-induced browning in a Ucp-1 reporter mouse model of obesity

Browning in adipose tissues, which can be affected by diet, may mitigate the detrimental effects of adiposity and improve longer-term metabolic health. Here, browning-inducing effects of long-chain polyunsaturated fatty acids, e.g., arachidonic acid (ARA)/docosahexaenoic acid (DHA) and extensively hydrolyzed casein (eHC) were investigated in uncoupling protein 1 (Ucp-1) reporter mice. To address the overall functionality, their potential role in supporting a healthy metabolic profile under obesogenic dietary challenges later in life was evaluated. At weaning Ucp1+/LUC reporter mice were fed a control low fat diet (LFD) with or without ARA + DHA, eHC or eHC + ARA + DHA for 8 weeks until week 12 after which interventions continued for another 12 weeks under a high-fat diet (HFD) challenge. Serology (metabolic responses and inflammation) and in vivo and ex vivo luciferase activity were determined; in the meantime browning-related proteins UCP-1 and the genes peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC1α), PR domain containing 16 (PRDM16) and Ucp-1 were examined. ARA + DHA, eHC or their combination reduced body weight gain and adipose tissue weight compared to the HFD mice. The interventions induced Ucp-1 expression in adipose tissues prior to and during the HFD exposure. Ucp-1 induction was accompanied by higher PGC1a and PRDM16 expression. Glucose tolerance and insulin sensitivity were improved coinciding with lower serum cholesterol, triglycerides, free fatty acids, insulin, leptin, resistin, fibroblast growth factor 21, alanine aminotransferase, aspartate aminotransferase and higher adiponectin than the HFD group. HFD-associated increased systemic (IL-1β and TNF-α) and adipose tissue inflammation (F4/80, IL-1β, TNF-α, IL-6) was reduced. Studies in a Ucp-1 reporter mouse model revealed that early intervention with ARA/DHA and eHC improves metabolic flexibility and attenuates obesity during HFD challenge later in life. Increased browning is suggested as, at least, part of the underlying mechanism.

Effect of carnosine supplementation on the plasma lipidome in overweight and obese adults: a pilot randomised controlled trial

Carnosine has been shown to reduce oxidation and glycation of low density lipoprotein hence improving dyslipidaemia in rodents. The effect of carnosine on human plasma lipidome has thus far not been investigated. We aimed to determine whether carnosine supplementation improves the plasma lipidome in overweight and obese individuals. Lipid analysis was performed by liquid chromatography mass spectrometry in 24 overweight and obese adults: 13 were randomly assigned to 2 g carnosine daily and 11 to placebo, and treated for 12 weeks. Carnosine supplementation maintained trihexosylceramide (0.01 ± 0.19 vs -0.28 ± 0.34 nmol/ml, p = 0.04), phosphatidylcholine (77 ± 167 vs -81 ± 196 nmol/ml, p = 0.01) and free cholesterol (20 ± 80 vs -69 ± 80 nmol/ml, p = 0.006) levels compared to placebo. Trihexosylceramide was inversely related with fasting insulin (r = -0.6, p = 0.002), insulin resistance (r = -0.6, p = 0.003), insulin secretion (r = -0.4, p = 0.05) and serum carnosinase 1 activity (r = -0.3, p = 0.05). Both phosphatidylcholine and free cholesterol did not correlate with any cardiometabolic parameters. Our data suggest that carnosine may have beneficial effects on the plasma lipidome. Future larger clinical trials are needed to confirm this.

The mechanism of skin lipids influencing skin status

Skin lipids, compose of sebocyte-, keratinocyte-, and microbe- derived lipids, dramatically influence skin status by different mechanisms. (I) Physical chemistry function: They are "mortar" to establish the physico-chemical barrier function of skin; (II) Biochemistry function: They function as signals in the complex signaling network originating at the epidermal level; (III) Microecology function: Sebocyte- and keratinocyte-derived lipids vary the composition of microbial skin flora, and microorganisms metabolize them to produce lipids as signal starting signaling transduction. Importantly, further research needs lipidiomics, more powerful analytical ability and high-throughput manner, to identify skin lipid components into individual species. The validation of lipid structure and function to research the process that lipid species involved in. Additional, the integration of lipidomics data with other omics strategies can develop the power to study the mechanism of skin lipids influencing skin status.

Optimization of lipid extraction and analytical protocols for UHPLC-ESI-HRMS-based lipidomic analysis of adherent mammalian cancer cells

Lipidomics, which reveals comprehensive characterization of molecular lipids, is a rapidly growing technology used in biomedical research. Lipid extraction is a critical step in lipidomic analysis. However, the effectiveness of different lipid extract solvent systems from cellular samples still remains unclear. In the current study, the protocol of reverse-phase liquid chromatography mass spectrometry (LC/MS)-based lipidomics was optimized for extraction and detection of lipids from human pancreatic cancer cell line PANC-1. Four different extraction methods were compared, including methanol/methyl-tert-butyl ether (MTBE)/H₂O, methanol/chloroform, methanol/MTBE/chloroform, and hexane/isopropanol. Data were acquired using high-resolution mass spectrometry in positive and negative ion modes respectively. The number of total detected and identified lipids was assessed with the aid of automated lipid identification software LipidSearch. Results demonstrated that methanol/MTBE/H₂O provided a better extraction efficiency for different lipid classes, which was chosen as the optimized extraction solvent system. This validated method enables highly sensitive and reproducible analysis for a variety of cellular lipids, which was further applied to an untargeted lipidomic study on human pancreatic cancer PANC-1 cell lines. Moreover, this optimized extraction solvent system can be further applied to other cancer cell lines with similar chemical and physical properties. Graphical abstract Optimized UHPLC-ESI-HRMS-based lipidomic analysis of cancer cells.

Breaking Up Prolonged Sitting Alters the Postprandial Plasma Lipidomic Profile of Adults With Type 2 Diabetes

Context

Postprandial dysmetabolism in type 2 diabetes (T2D) is exacerbated by prolonged sitting and may trigger inflammation and oxidative stress. It is unknown what impact countermeasures to prolonged sitting have on the postprandial lipidome.

Objective

In this study, we investigated the effects of regular interruptions to sitting, compared with prolonged sitting, on the postprandial plasma lipidome.

Design

Randomized crossover experimental trial.

Setting

Participants underwent three 7-hour conditions: uninterrupted sitting (SIT); light-intensity walking interruptions (LW); and simple resistance activity interruptions (SRA).

Participants and Samples

Baseline (fasting) and 7-hour (postprandial) plasma samples from 21 inactive overweight/obese adults with T2D were analyzed for 338 lipid species using mass spectrometry.

Main Outcome Measures

Using mixed model analysis (controlling for baseline outcome variable, gender, body mass index, and condition order), the percentage change in lipid species (baseline to 7 hours) was compared between conditions with Benjamini-Hochberg correction.

Results

Thirty-seven lipids were different between conditions (P < 0.05). Compared with SIT, postprandial elevations in diacylglycerols, triacylglycerols, and phosphatidylethanolamines were attenuated in LW and SRA. Plasmalogens and lysoalkylphosphatidylcholines were reduced in SIT, compared with attenuated reductions or elevations in LW and SRA. Phosphatidylserines were elevated with LW, compared with reductions in SIT and SRA.

Conclusion

Compared with SIT, LW and SRA were associated with reductions in lipids associated with inflammation; increased concentrations of lipids associated with antioxidant capacity; and differential changes in species associated with platelet activation. Acutely interrupting prolonged sitting time may impart beneficial effects on the postprandial plasma lipidome of adults with T2D. Evidence on longer-term intervention is needed.

Lipidomics for studying metabolism

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

Skeletal muscle and plasma lipidomic signatures of insulin resistance and overweight/obesity in humans

OBJECTIVE

Alterations in lipids in muscle and plasma have been documented in insulin-resistant people with obesity. Whether these lipid alterations are a reflection of insulin resistance or obesity remains unclear.

METHODS

Nondiabetic sedentary individuals not treated with lipid-lowering medications were studied (n = 51). Subjects with body mass index (BMI) > 25 kg/m(2) (n = 28) were stratified based on median glucose infusion rate during a hyperinsulinemic-euglycemic clamp into insulin-sensitive and insulin-resistant groups (above and below median, obesity/insulin-sensitive and obesity/insulin-resistant, respectively). Lean individuals (n = 23) served as a reference group. Lipidomics was performed in muscle and plasma by liquid chromatography electrospray ionization-tandem mass spectrometry. Pathway analysis of gene array in muscle was performed in a subset (n = 35).

RESULTS

In muscle, insulin resistance was characterized by higher levels of C18:0 sphingolipids, while in plasma, higher levels of diacylglycerol and cholesterol ester, and lower levels of lysophosphatidylcholine and lysoalkylphosphatidylcholine, indicated insulin resistance, irrespective of overweight/obesity. The sphingolipid metabolism gene pathway was upregulated in muscle in insulin resistance independent of obesity. An overweight/obesity lipidomic signature was only apparent in plasma, predominated by higher triacylglycerol and lower plasmalogen species.

CONCLUSIONS

Muscle C18:0 sphingolipids may play a role in insulin resistance independent of excess adiposity.

Novel advances in shotgun lipidomics for biology and medicine

The field of lipidomics, as coined in 2003, has made profound advances and been rapidly expanded. The mass spectrometry-based strategies of this analytical methodology-oriented research discipline for lipid analysis are largely fallen into three categories: direct infusion-based shotgun lipidomics, liquid chromatography-mass spectrometry-based platforms, and matrix-assisted laser desorption/ionization mass spectrometry-based approaches (particularly in imagining lipid distribution in tissues or cells). This review focuses on shotgun lipidomics. After briefly introducing its fundamentals, the major materials of this article cover its recent advances. These include the novel methods of lipid extraction, novel shotgun lipidomics strategies for identification and quantification of previously hardly accessible lipid classes and molecular species including isomers, and novel tools for processing and interpretation of lipidomics data. Representative applications of advanced shotgun lipidomics for biological and biomedical research are also presented in this review. We believe that with these novel advances in shotgun lipidomics, this approach for lipid analysis should become more comprehensive and high throughput, thereby greatly accelerating the lipidomics field to substantiate the aberrant lipid metabolism, signaling, trafficking, and homeostasis under pathological conditions and their underpinning biochemical mechanisms.

An Efficient Single Phase Method for the Extraction of Plasma Lipids

Lipidomic approaches are now widely used to investigate the relationship between lipid metabolism, health and disease. Large-scale lipidomics studies typically aim to quantify hundreds to thousands of lipid molecular species in a large number of samples. Consequently, high throughput methodology that can efficiently extract a wide range of lipids from biological samples is required. Current methods often rely on extraction in chloroform:methanol with or without two phase partitioning or other solvents, which are often incompatible with liquid chromatography electrospray ionization-tandem mass spectrometry (LC ESI-MS/MS). Here, we present a fast, simple extraction method that is suitable for high throughput LC ESI-MS/MS. Plasma (10 μL) was mixed with 100 μL 1-butanol:methanol (1:1 v/v) containing internal standards resulting in efficient extraction of all major lipid classes (including sterols, glycerolipids, glycerophospholipids and sphingolipids). Lipids were quantified using positive-ion mode LC ESI-MS/MS. The method showed high recovery (>90%) and reproducibility (%CV < 20%). It showed a strong correlation of all lipid measures with an established chloroform:methanol extraction method (R2 = 0.976). This method uses non-halogenated solvents, requires no drying or reconstitution steps and is suitable for large-scale LC ESI-MS/MS-based lipidomic analyses in research and clinical laboratories.

Plasma diacylglycerol composition is a biomarker of metabolic syndrome onset in rhesus monkeys

Metabolic syndrome is linked with obesity and is often first identified clinically by elevated BMI and elevated levels of fasting blood glucose that are generally secondary to insulin resistance. Using the highly translatable rhesus monkey (Macaca mulatta) model, we asked if metabolic syndrome risk could be identified earlier. The study involved 16 overweight but healthy, euglycemic monkeys, one-half of which spontaneously developed metabolic syndrome over the course of 2 years while the other half remained healthy. We conducted a series of biometric and plasma measures focusing on adiposity, lipid metabolism, and adipose tissue-derived hormones, which led to a diagnosis of metabolic syndrome in the insulin-resistant animals. Plasma fatty acid composition was determined by gas chromatography for cholesteryl ester, FFA, diacylglycerol (DAG), phospholipid, and triacylglycerol lipid classes; plasma lipoprotein profiles were generated by NMR; and circulating levels of adipose-derived signaling peptides were determined by ELISA. We identified biomarker models including a DAG model, two lipoprotein models, and a multiterm model that includes the adipose-derived peptide adiponectin. Correlations among circulating lipids and lipoproteins revealed shifts in lipid metabolism during disease development. We propose that lipid profiling may be valuable for early metabolic syndrome detection in a clinical setting.

Lipidomic analysis of plasma samples from women with polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is a common disorder affecting between 5 and 18 % of females of reproductive age and can be diagnosed based on a combination of clinical, ultrasound and biochemical features, none of which on its own is diagnostic. A lipidomic approach using liquid chromatography coupled with accurate mass high-resolution mass-spectrometry (LC-HRMS) was used to investigate if there were any differences in plasma lipidomic profiles in women with PCOS compared with control women at different stages of menstrual cycle. Plasma samples from 40 women with PCOS and 40 controls aged between 18 and 40 years were analysed in combination with multivariate statistical analyses. Multivariate data analysis (LASSO regression and OPLS-DA) of the sample lipidomics datasets showed a weak prediction model for PCOS versus control samples from the follicular and mid-cycle phases of the menstrual cycle, but a stronger model (specificity 85 % and sensitivity 95 %) for PCOS versus the luteal phase menstrual cycle controls. The PCOS vs luteal phase model showed increased levels of plasma triglycerides and sphingomyelins and decreased levels of lysophosphatidylcholines and phosphatidylethanolamines in PCOS women compared with controls. Lipid biomarkers of PCOS were tentatively identified which may be useful in distinguishing PCOS from controls especially when performed during the menstrual cycle luteal phase.

Lipidomic assessment of plasma and placenta of women with early-onset preeclampsia

Introduction

Adipose tissue is responsible for triggering chronic systemic inflammatory response and these changes may be involved in the pathophysiology of preeclampsia.

Objective

To characterize the lipid profile in the placenta and plasma of patients with preeclampsia.

Methodology

Samples were collected from placenta and plasma of 10 pregnant women with preeclampsia and 10 controls. Lipids were extracted using the Bligh–Dyer protocol and were analysed by MALDI TOF-TOF mass spectrometry.

Results

Approximately 200 lipid signals were quantified. The most prevalent lipid present in plasma of patients with preeclampsia was the main class Glycerophosphoserines-GP03 (PS) representing 52.30% of the total lipid composition, followed by the main classes Glycerophosphoethanolamines-GP02 (PEt), Glycerophosphocholines-GP01 (PC) and Flavanoids-PK12 (FLV), with 24.03%, 9.47% and 8.39% respectively. When compared to the control group, plasma samples of patients with preeclampsia showed an increase of PS (p<0.0001), PC (p<0.0001) and FLV (p<0.0001). Placental analysis of patients with preeclampsia, revealed the PS as the most prevalent lipid representing 56.28%, followed by the main class Macrolides/polyketides-PK04 with 32.77%, both with increased levels when compared with patients control group, PS (p<0.0001) and PK04 (p<0.0001).

Conclusion

Lipids found in placenta and plasma from patients with preeclampsia differ from those of pregnant women in the control group. Further studies are needed to clarify if these changes are specific and a cause or consequence of preeclampsia.