Untargeted Lipidomics Research Articles

Lipidomic Approaches to Study HDL Metabolism in Patients with Central Obesity Diagnosed with Metabolic Syndrome.

The metabolic syndrome (MetS) is a cluster of cardiovascular risk factors characterised by central obesity, atherogenic dyslipidaemia, and changes in the circulating lipidome; the underlying mechanisms that lead to this lipid remodelling have only been partially elucidated. This study used an integrated “omics” approach (untargeted whole serum lipidomics, targeted proteomics, and lipoprotein lipidomics) to study lipoprotein remodelling and HDL composition in subjects with central obesity diagnosed with MetS (vs. controls). Compared with healthy subjects, MetS patients showed higher free fatty acids, diglycerides, phosphatidylcholines, and triglycerides, particularly those enriched in products of de novo lipogenesis. On the other hand, the “lysophosphatidylcholines to phosphatidylcholines” and “cholesteryl ester to free cholesterol” ratios were reduced, pointing to a lower activity of lecithin cholesterol acyltransferase (LCAT) in MetS; LCAT activity (directly measured and predicted by lipidomic ratios) was positively correlated with high-density lipoprotein cholesterol (HDL-C) and negatively correlated with body mass index (BMI) and insulin resistance. Moreover, many phosphatidylcholines and sphingomyelins were significantly lower in the HDL of MetS patients and strongly correlated with BMI and clinical metabolic parameters. These results suggest that MetS is associated with an impairment of phospholipid metabolism in HDL, partially led by LCAT, and associated with obesity and underlying insulin resistance. This study proposes a candidate strategy to use integrated “omics” approaches to gain mechanistic insights into lipoprotein remodelling, thus deepening the knowledge regarding the molecular basis of the association between MetS and atherosclerosis.

Combination of Salviae Miltiorrhizae Radix et Rhizoma and Carthami Flos improves cardiac function of diabetic cardiomyopathy mice by regulating the unfolded protein response signaling pathway.

Diabetic cardiomyopathy (DCM) is a unique clinical entity elicited by diabetes independent of other cardiovascular risk factors, of which the pathological mechanisms and treatment strategies remain largely undefined. This study aimed to clarify the role of unfolded protein response (UPR) signaling pathway in the pathogenesis of DCM, and to explore the effect of aqueous extract of Salviae Miltiorrhizae Radix et Rhizoma and Carthami Flos (DH) on DCM mice. Cardiac function of DCM mice was evaluated by echocardiography, and lipid profile of left ventricular was analyzed by untargeted lipidomics. The results showed that DH significantly improved the diabetic symptoms, cardiac dyslipidemia, and systolic dysfunction of DCM mice. UPR signaling pathway was significantly down-regulated in the left ventricular of DCM mice. DH significantly up-regulated the transcriptions of key transducers in UPR signaling pathway. Conditional knockout of Xbp1 in cardiomyocyte (a key regulator in UPR signaling pathway) eliminated the protective effect of DH on cardiac systolic function of DCM mice, which suggested that UPR signaling pathway, especially the Xbp1, was required for DH protection against DCM. In conclusion, DH improved cardiac function of DCM mice, and this effect was dependent on its regulation of UPR signaling pathway.

Abstract 5811: Ovarian cancer cell fate is regulated by the balance between saturated and unsaturated fatty acids

Abstract Background: Fat represents an important source of energy for ovarian cancer (OC) cells and is supplied either through import from the tumor milieu or via de novo lipogenesis. During fast tumor growth, when nutrients are scarce, lipogenesis becomes the primary source of fatty acids. Stearoyl-CoA desaturase (SCD), a rate-limiting enzyme in this pathway converts saturated (SFAs) into unsaturated fatty acids (UFAs) and is highly expressed in OC. The goal of this study was to determine how the balance between SFAs and UFAs tightly controlled by SCD, regulates OC cell survival and tumorigenicity. Methods: SCD was knocked down by shRNA or inhibited by using the small molecule CAY10566 and global effects on the lipidome and transcriptome were examined by targeted and untargeted lipidomics, stimulated Raman spectroscopy (SRS), and RNA sequencing. In OC cells in which SCD was blocked or knocked down, the effects of exogenous SFAs and UFAs on cell survival and endoplasmic reticulum (ER) stress pathway were assessed by using annexin V staining, XBP1 splicing assay and Western blotting of PERK/eIF2α/ATF4. Tumorigenicity was assessed by using an intraperitoneal (i.p.) xenograft model in nude mice. Results: RNA-seq analysis of SCD knockdown cells cultured under low serum conditions revealed activation of ER stress response pathways. Targeted lipidomics and SRS microscopy showed downregulation of UFAs vs. SFAs, while untargeted lipidomics discovered decreased fatty acyl chain plasticity among phosphatidylcholines. Activation of IRE1α/XBP1 and PERK/eIF2α/ATF4 axes was observed in cells accumulating SFAs. Stiff and disorganized ER membrane was detected by electron microscopy and Raman spectroscopy. Annexin V staining demonstrated apoptosis of OC cells under long-term mild ER stress or short-time severe ER stress induced by increased levels of SFAs. ER stress and apoptosis were rescued by addition of UFAs. In vivo SCD knockdown suppressed tumor growth and treatment with the SCD inhibitor CAY10566 reduced the number of metastases and the volume of ascites in mice fed with SFA enriched diet, but not in mice fed a balanced diet. Conclusion: Our data support that OC cells are highly susceptible to unbalanced intracellular SFAs/UFAs, undergoing ER stress and apoptosis in the presence of excessive intracellular SFAs. SCD inhibition coupled with a diet rich in saturated fats decreased cancer progression in vivo. These results support SCD as a key regulator of cancer cell fate during metabolic stress in growing tumors and point to new treatment strategies targeting lipid metabolism. Citation Format: Guangyuan Zhao, Yuying Tan, Horacio Cardenas, David Vayngart, Yinu Wang, Christina Ferreira, Ji-Xin Cheng, Daniela Matei. Ovarian cancer cell fate is regulated by the balance between saturated and unsaturated fatty acids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5811.

226-OR: Reduced Fatty Acid Oxidation Prevents Intralipid-Induced Hepatic Insulin Resistance in Humans

Mitochondrial handling of excess lipid substrate may be an important determinant of insulin resistance. Animal models support insulin signaling defects resulting from both defective fatty acid oxidation (FAO) with subsequent intra-cellular lipid accumulation on the one hand and enhanced FAO flux on the other. To explore the relationship between FAO and insulin sensitivity, we measured the change in intra-hepatic lipids (IHL) by MRS and hepatic insulin sensitivity during a 5-hour hyperinsulinemic euglycemic clamp with co-infusion of either a control glycerol solution versus a 20% intralipid solution, in random order and separated by 4 months. The study cohort included 18 subjects with an inherited defect in FAO (FAOD; including Carnitine Palmitoyltransferase 2, Long chain 3-Hydroxyacyl-CoA Dehydrogenase, Very Long-chain or Medium-chain Acyl-CoA Dehydrogenase Deficiencies) and 18 matched normal healthy controls. Endogenous glucose production (EGP) before the start of the insulin infusion was similar between FAOD and controls. In controls, insulin suppressed EGP during the glycerol control clamp but this effect was significantly reduced during intralipid infusion (P<0.05, reduced hepatic insulin sensitivity) . In FAOD subjects, insulin suppressed EGP similarly during the glycerol and intralipid clamps (no impairment in insulin action) . Untargeted lipidomics /metabolomics of plasma measured at the end of the intralipid clamp demonstrated significant elevations of plasma acylcarnitines and some triglyceride species but lower production of ketones, and several phospholipids in subjects with FAOD compared to controls. Neither increased IHL nor elevated plasma acylcarnitines in FAOD subjects were associated with hepatic insulin resistance. In fact, impaired FAO protected against intralipid-induced hepatic insulin resistance suggesting that increased FAO flux rather than impaired mitochondrial function is a major determinant of insulin resistance in the liver. Disclosure J.Q.Purnell: Advisory Panel; Novo Nordisk. A.N.Gregor: None. D.Choi: None. E.Baetscher: None. W.Rooney: Consultant; Ultragenix, Research Support; Italofarmco, Revalesio. C.O.Harding: None. M.B.Gillingham: None. Funding NIH/NIDDK: R01DK102813NIH/NCATS: UL1TR002369

1352-P: Differential Metabolomics and Lipidomics Profiles in Low-Birth-Weight Men Unmasked by Four-Weeks High-Carbohydrate Overfeeding

Background: We hypothesized that low birth weight (LBW) subjects with a known increased risk of type 2 diabetes exhibit increased sensitivity towards the deleterious metabolic effects of 4-weeks high carbohydrate overfeeding (HCOF) compared with normal birth weight (NBW) controls. Methods: Untargeted serum metabolomics and lipidomics were measured before and after 4-weeks HCOF (+25% energy) in 26 non-obese men with LBW (2789±174 g) and 21 normal birth weight (NBW) men/controls (3804±172 g) matched for BMI and age. Data were analyzed using a combination of advanced statistical and bioinformatical tools. Results: Among 65 identified metabolites, 8 metabolites were affected differentially by HCOF between the two groups (p<0.05) . In response to HCOF, ingenuity pathway analysis (IPA) revealed increased accumulation and peroxidation of lipids in LBW subjects. In contrast, NBW controls increased albumin synthesis after HCOF. Changes in upstream regulators such as nicotinamide nucleotide transhydrogenase (NNT) , uncoupling protein 1 (UCP1) , and carbonic anhydrase 9 (CA9) were observed in both groups in response to HCOF. NBW controls displayed increased NNT and UCP1 activation, whereas LBW subjects responded with paradoxically decreased NNT and UCP1 activation. CA9 expression was decreased in both groups. Network correlation analysis revealed an upregulation of fatty acids in LBW subjects, contrasting a downregulation among NBW controls. Among 279 lipids identified, the LBW subjects exhibited a significantly higher number of lipids to be increased in response to HCOF (n=26) compared to NBW subjects (n=6) (PFisher=0.0004) , and IPA analysis revealed an activation of the PPARG pathway in NBW as opposed to a paradoxical inhibition in LBW subjects. Conclusion: The results document severe differential perturbations of lipid metabolism in LBW men exposed to HCOF. Public health initiatives promoting low carbohydrate diets in LBW subjects are warranted. Disclosure S.O.Villumsen: None. A.A.Vaag: Stock/Shareholder; AstraZeneca. L.Justesen: None. L.Elingaard-larsen: None. A.B.Thuesen: None. M.Kim: None. C.Legido-quigley: None. E.R.Danielsen: None. T.Hansen: None. C.Brøns: Stock/Shareholder; Novo Nordisk.

98-OR: Prediction of Cardiovascular Disease in People with Type 1 Diabetes with Novel Omics Biomarkers

Introduction: Type 1 diabetes (T1D) increases risk for cardiovascular disease (CVD) at least 2-4 fold, with only half the excess risk explained by known risk factors. We sought to identify novel proteomic, lipidomic, and metabolomic biomarkers of CVD in T1D. Methods: We first built a predictive model of coronary artery calcium progression (CACp) using LASSO regression of clinical variables measured at baseline in 365 participants with T1D in the Coronary Artery Calcification in Type 1 Diabetes (CACTI) study. The selected model was refit to a subgroup of 102 participants with complete clinical information and measured omics markers (targeted and untargeted metabolomics, global proteomics, glycated proteomics, and lipidomics) . Omics biomarkers were identified for inclusion in the final model by retaining the top markers that predicted CACp by moderated t-tests and sPLS-DA models. Results: The table shows variables retained in the clinical model (AUC=0.91) and in the model with biomarkers added (AUC=0.94) . Higher age, urine albumin:creatinine, and insulin dose predicted CACp in both models. Longer duration of T1D predicted CACp in the clinical model. In the model with D-Glucosamine/D-galactosamine and glycated fibrinogen peptides, D-Glucosamine/D-Galactosamine predicted CACp. Conclusion: Novel metabolites improved prediction of CACp in people with T1D. Disclosure L.Pyle: None. T.B.Vigers: None. R.K.Johnson: None. Q.Zhang: None. J.K.Snell-bergeon: Stock/Shareholder; GlaxoSmithKline plc. Funding American Heart Association (17CSA33570025) , NIH (P30-DK116073)

Analysis and comparison of lipids in Saanen goat milk from different geographic regions in China based on UHPLC-QTOF-MS lipidomics

The lipids in goat milk from Guangdong Province (GGM), Shaanxi Province (SGM), and Inner Mongolia Province (NGM) were analyzed and compared using untargeted lipidomics. A total of 16 lipid sub-classes and 638 lipid molecules were identified in the three groups. The main lipids were diacylglycerol (DG), triacylglycerol (TG), and glycerophosphatidylethanolamine (PE). The contents of glycerophosphatidylcholine (PC), PE, glycerophosphatidylinositol (PI), sphingomyelin (SM), glucosylceramide (GlcCer), lactosylceramide (LacCer), DG, and TG were significantly different (P < 0.05) in three groups. Moreover, 173 significantly different lipids were screened out, and 13 lipid molecules could be applied as potential lipid markers for identifying the geographic region of goat milk. In addition, the related metabolic pathways were also analyzed. A hypothetical scheme was drawn by linking the most relevant metabolic pathways. This work will provide basics for the establishment of the Saanen goat milk traceability system and provide comprehensive lipid information for the goat milk of different regions.

Maternal Pyrroloquinoline Quinone Supplementation Improves Offspring Liver Bioactive Lipid Profiles throughout the Lifespan and Protects against the Development of Adult NAFLD.

Maternal obesity and consumption of a high-fat diet significantly elevate risk for pediatric nonalcoholic fatty liver disease (NAFLD), affecting 10% of children in the US. Almost half of these children are diagnosed with nonalcoholic steatohepatitis (NASH), a leading etiology for liver transplant. Animal models show that signs of liver injury and perturbed lipid metabolism associated with NAFLD begin in utero; however, safe dietary therapeutics to blunt developmental programming of NAFLD are unavailable. Using a mouse model of maternal Western-style diet (WD), we previously showed that pyrroloquinoline quinone (PQQ), a potent dietary antioxidant, protected offspring of WD-fed dams from development of NAFLD and NASH. Here, we used untargeted mass spectrometry-based lipidomics to delineate lipotoxic effects of WD on offspring liver and identify lipid targets of PQQ. PQQ exposure during pregnancy altered hepatic lipid profiles of WD-exposed offspring, upregulating peroxisome proliferator-activated receptor (PPAR) α signaling and mitochondrial fatty acid oxidation to markedly attenuate triglyceride accumulation beginning in utero. Surprisingly, the abundance of very long-chain ceramides, important in promoting gut barrier and hepatic function, was significantly elevated in PQQ-treated offspring. PQQ exposure reduced the hepatic phosphatidylcholine/phosphatidylethanolamine (PC/PE) ratio in WD-fed offspring and improved glucose tolerance. Notably, levels of protective n − 3 polyunsaturated fatty acids (PUFAs) were elevated in offspring exposed to PQQ, beginning in utero, and the increase in n − 3 PUFAs persisted into adulthood. Our findings suggest that PQQ supplementation during gestation and lactation augments pathways involved in the biosynthesis of long-chain fatty acids and plays a unique role in modifying specific bioactive lipid species critical for protection against NAFLD risk in later life.

UHPLC‐Q‐Orbitrap‐based untargeted lipidomics reveals the variation of yolk lipids during egg storage

Egg yolk is recognized for its excellent nutritional benefit and economic value; however, egg is a perishable food, potentially losing quality if not handled properly between the time from farm production to consumption. Knowledge of the changes of yolk lipid composition under an extreme storage condition close to vitelline membrane breaking, which results in an inedible condition for shelf-eggs, remains incomplete. Considering the complexity of yolk lipids, the architectural features of yolk lipids at high-temperature storage (30°C for 10 days versus fresh) were classified through lipidomics. This strategy yielded 1508 features within the lipid database coupled with 74 significantly different lipids (P< 0.05, fold change > 1.2 or < 0.83), mainly triglycerides, phospholipids, and sphingolipids. Most of them were decreased after storage; for example, triglycerides were assumed to play a role as a 'buffer' to maintain the system stability during storage by balancing fatty acid saturation, which strongly reduces the egg edible value for humans. Furthermore, phospholipids, especially the highly unsaturated phosphatidylcholine, decreased significantly and were suggested to be the primary cause for the variation in yolk emulsifying properties and flavor. Altogether, these results deriving from oxidation and lipolysis reactions enhance our understanding of lipid transformation and the biochemical mechanisms, at the molecular level, of the deteriorative process of the egg yolk. These findings may lay the foundation for identifying processes, including some modifications of the lipid composition of rations fed to laying hens, aiming to improve the long-term shelf-stability of shell eggs and egg products. © 2022 Society of Chemical Industry.

Norm ISWSVR: A Data Integration and Normalization Approach for Large-Scale Metabolomics.

Large-scale and long-period metabolomics study is more susceptible to various sources of systematic errors, resulting in nonreproducibility and poor data quality. A reliable and robust batch correction method removes unwanted systematic variations and improves the statistical power of metabolomics data, which undeniably becomes an important issue for the quality control of metabolomics. This study proposed a novel data normalization and integration method, Norm ISWSVR. It is a two-step approach via combining the best-performance internal standard correction with support vector regression normalization, comprehensively removing the systematic and random errors and matrix effects. This method was investigated in three untargeted lipidomics or metabolomics datasets, and the performance was further evaluated systematically in comparison with that of 11 other normalization methods. As a result, Norm ISWSVR decreased the data's median cross-validated relative standard deviation (cvRSD), increased the correlation between QCs, improved the classification accuracy of biomarkers, and was well-compatible with quantitative data. More importantly, Norm ISWSVR also allows a low frequency of QCs, which could significantly decrease the burden of a large-scale experiment. Correspondingly, Norm ISWSVR favorably improves the data quality of large-scale metabolomics data.

Lipidomics for the Prediction of Progressive Liver Disease in Patients with Alcohol Use Disorder.

Alcohol-related liver disease is a public health care burden globally. Only 10–20% of patients with alcohol use disorder have progressive liver disease. This study aimed to identify lipid biomarkers for the early identification of progressive alcohol-related liver disease, which is a key step for early intervention. We performed untargeted lipidomics analysis in serum and fecal samples for a cohort of 49 subjects, including 17 non-alcoholic controls, 16 patients with non-progressive alcohol-related liver disease, and 16 patients with progressive alcohol-related liver disease. The serum and fecal lipidome profiles in the two patient groups were different from that in the controls. Nine lipid biomarkers were identified that were significantly different between patients with progressive liver disease and patients with non-progressive liver disease in both serum and fecal samples. We further built a random forest model to predict progressive alcohol-related liver disease using nine lipid biomarkers. Fecal lipids performed better (Area Under the Curve, AUC = 0.90) than serum lipids (AUC = 0.79). The lipid biomarkers identified are promising candidates for the early identification of progressive alcohol-related liver disease.

Untargeted lipidomics reveals specific lipid profiles in COVID-19 patients with different severity from Campania region (Italy)

COVID-19 infection evokes various systemic alterations that push patients not only towards severe acute respiratory syndrome but causes an important metabolic dysregulation with following multi-organ alteration and potentially poor outcome. To discover novel potential biomarkers able to predict disease’s severity and patient’s outcome, in this study we applied untargeted lipidomics, by a reversed phase ultra-high performance liquid chromatography-trapped ion mobility mass spectrometry platform (RP-UHPLC-TIMS-MS), on blood samples collected at hospital admission in an Italian cohort of COVID-19 patients (45 mild, 54 severe, 21 controls). In a subset of patients, we also collected a second blood sample in correspondence of clinical phenotype modification (longitudinal population). Plasma lipid profiles revealed several lipids significantly modified in COVID-19 patients with respect to controls and able to discern between mild and severe clinical phenotype. Severe patients were characterized by a progressive decrease in the levels of LPCs, LPC-Os, PC-Os, and, on the contrary, an increase in overall TGs, PEs, and Ceramides. A machine learning model was built by using both the entire dataset and with a restricted lipid panel dataset, delivering comparable results in predicting severity (AUC= 0.777, CI: 0.639–0.904) and outcome (AUC= 0.789, CI: 0.658–0.910). Finally, re-building the model with 25 longitudinal (t1) samples, this resulted in 21 patients correctly classified. In conclusion, this study highlights specific lipid profiles that could be used monitor the possible trajectory of COVID-19 patients at hospital admission, which could be used in targeted approaches.

Development and application of a fast ultra-high performance liquid chromatography-trapped ion mobility mass spectrometry method for untargeted lipidomics

The alteration of lipid profile in biological specimens, such as plasma, mirrors abnormalities in their homeostasis and offers pivotal information for disease comprehension. Fast analytical methods are needed to highlight changes in plasma lipid profile and deliver rapid results. In this study we developed a fast reversed phase ultra high performance liquid chromatography-trapped ion mobility mass spectrometry (RP-UHPLC-TIMS-MS) method for untargeted lipidomics. A short, narrow-bore fully porous particle CSH column (50 mm × 2.1 mm, 1.7 µm) was used, and by selecting appropriate flow rate, temperature and gradient conditions, the total analysis time was reduced from 20 to 4 min. TIMS was operated in parallel accumulation serial fragmentation mode (PASEF) which allowed to select multiple precursors for MS/MS and separate co-eluting lipids based on their different mobility. Lipid annotation was performed by rule-based approach, comparison with LipidBlast spectral library and manual data curation, by taking into account class-specific fragmentation pattern, accurate mass, adduct form, retention behavior in RP and comparison of their collision cross-section (CCS) values for increased confidence. 306 unique lipids from 21 subclasses were annotated from 20 µL of plasma, while their concentration was estimated by class-specific deuterated internal standards. The analytical method was validated and finally applied to elucidate the alteration of plasma lipid profiles in a small cohort of amyotrophic lateral sclerosis (ALS) patients. Univariate and multivariate statistics evidenced significant differences with respect to control patients, particularly in the levels of ether linked lipids (PC-O, PE-O, PE-P and LPC-O), sphingolipids (Ceramides), and triacylglycerols, showing the usefulness of this fast approach in providing accurate and rapid results with respect to longer (≥15 min) untargeted UHPLC-HRMS methods.

Trapped ion mobility spectrometry-mass spectrometry improves the coverage and accuracy of four-dimensional untargeted lipidomics

Lipids play vital roles in many physiological and pathological processes in living organisms. Due to the high structural diversity and the numerous isomers and isobars of lipids, high-coverage and high-accuracy lipidomic analysis of complex biological samples remain the bottleneck to investigate lipid metabolism. Here, we developed the trapped ion mobility spectrometry-mass spectrometry (TIMS-MS) based four-dimensional untargeted lipidomics to support accurate lipid identification and quantification in biological samples. We first demonstrated that the TIMS based multi-dimensional separation improved the differentiations of isomeric and isobaric lipids, and increased the purity of precursor ion isolation and the quality of MS/MS spectra. Hyphenation of TIMS and PASEF technologies significantly improved the coverages of MS/MS spectra. These technological advantages jointly improved the coverage and accuracy of lipid identification in untargeted lipidomics. We further demonstrated that the CCS values of lipids acquired using TIMS were highly consistent with those from drift tube ion mobility spectrometry (DTIMS). Lipid identification and quantification results of NIST human plasma samples were also verified with inter-laboratory reports. Finally, we applied the TIMS-MS based untargeted lipidomics to characterize the spatial distributions of 1393 distinctive lipids in the mouse brain, and demonstrated that diverse lipid distributions and compositions among brain regions contributed to different functions of brain regions. Altogether, TIMS-MS based four-dimensional untargeted lipidomics significantly improved the coverage and accuracy of untargeted metabolomics, thereby facilitating a system-level understanding of lipid metabolism in biological organisms.

Lipidomics identifies novel circulating markers of CVD risk in African American and Caucasian women

Cardiovascular disease (CVD) is the leading cause of mortality for women in the USA. Women with dyslipidemia have at increased risk of CVD. The parameters of dyslipidemia have primarily been defined using Caucasian male populations. Current lipid markers of dyslipidemia such as high density lipoprotein (HDL), low density lipoprotein (LDL), and triglycerides have been shown to be poor predictors of CVD risk in African American populations. We aim to identify marks of dyslipidemia in African American populations that better predict risk and development of CVD.Untargeted lipidomics (total lipid #) was performed on sera from middle‐age African American and Caucasian women (n=872). Machine learning was used to identify predictive lipid markers of CVD risk. Findings were validated using an independent cohort of women (n=200).We identified unique and shared signatures of CVD in women based on race. Arachidonic acid containing lipids are positively correlated with elevated blood pressure and cardiomyopathy. Because these lipids are important in inflammatory signaling, we also assessed interleukin‐6 and c‐reactive protein. Through machine learning we were able to determine that markers of inflammation and inflammatory lipids were predictive of CVD in both Caucasian and African American women. Next, we will perform targeted lipidomics on these lipids of interest.Regardless of class, lipid species containing arachidonic acid were increased in circulation of women with hypertension. We propose the consideration of an inflammatory marker panel that includes arachidonic acid to assess CVD risk in women.

Abstract 356: Phospholipid Profile Of Cerebral Thrombi In Acute Ischemic Stroke

Background and Purpose: The University of Washington Clot Bank (UWCB) has established a tissue banking protocol optimized for “omic” analysis for cerebral thrombi retrieved during standard-of-care thrombectomy. Thrombi from cerebral arteries of acute ischemic stroke (AIS) patients are a novel resource that allow for the evaluation of lipid biological markers present at the time of ictus. The pathophysiological processes following AIS are complex, and involve ischemia, inflammation, and disturbances of lipid metabolism. The purpose of this study was to characterize the lipid profile from cerebral thrombi in AIS patients. Methods: The UWCB study is a non-probability, convenience sampling of adult subjects (&gt; 18 years of age) who undergo thrombectomy for vascular occlusion. Lipidomics analysis was performed using LC-MS of untargeted lipids on thrombi taken from cerebral arteries of AIS subjects who underwent thrombectomy. Random forest, a supervised machine learning method, was employed to identify lipids associated with cerebral thrombi. Results: Five subjects (age = 53 ± 26.4, 3 males) were included from the UWCB registry. The most common comorbid conditions were atrial fibrillation (40%) and hypertension (40%). The top 10 metabolites identified from the random forest analysis, were of phosphatidylethanolamine molecular species. Phospholipids are involved in structural and functional integrity of cellular membranes and mediate host inflammatory responses. They are a key component of bacterial membranes. Changes in the structure or function of membrane phospholipids of host or relevant human microbiota may lead to alterations in membrane permeability and contribute to pathology of diseases such as neurodegeneration. Conclusion: An untargeted LC-MS lipidomics approach was used to identify lipids in cerebral thrombi at the time of mechanical thrombectomy. The top 10 lipids present in cerebral thrombi were identified, which included significant concentrations of phosphatidylethanolamine species. Because phospholipids play a key regulatory role in complex downstream cellular function, these findings may be of great significance in understanding AIS pathophysiology that has the potential to inform personalized preventive strategies.

Simulated Night-Shift Schedule Disrupts the Plasma Lipidome and Reveals Early Markers of Cardiovascular Disease Risk.

IntroductionThe circadian system coordinates daily rhythms in lipid metabolism, storage and utilization. Disruptions of internal circadian rhythms due to altered sleep/wake schedules, such as in night-shift work, have been implicated in increased risk of cardiovascular disease and metabolic disorders. To determine the impact of a night-shift schedule on the human blood plasma lipidome, an in-laboratory simulated shift work study was conducted.MethodsFourteen healthy young adults were assigned to 3 days of either a simulated day or night-shift schedule, followed by a 24-h constant routine protocol with fixed environmental conditions, hourly isocaloric snacks, and constant wakefulness to investigate endogenous circadian rhythms. Blood plasma samples collected at 3-h intervals were subjected to untargeted lipidomics analysis.ResultsMore than 400 lipids were identified and quantified across 21 subclasses. Focusing on lipids with low between-subject variation per shift condition, alterations in the circulating plasma lipidome revealed generally increased mean triglyceride levels and decreased mean phospholipid levels after night-shift relative to day-shift. The circadian rhythms of triglycerides containing odd chain fatty acids peaked earlier during constant routine after night-shift. Regardless of shift condition, triglycerides tended to either peak or be depleted at 16:30 h, with chain-specific differences associated with the direction of change.DiscussionThe simulated night-shift schedule was associated with altered temporal patterns in the lipidome. This may be premorbid to the elevated cardiovascular risk that has been found epidemiologically in night-shift workers.

Variants in mitochondrial amidoxime reducing component 1 and hydroxysteroid 17-beta dehydrogenase 13 reduce severity of nonalcoholic fatty liver disease in children and suppress fibrotic pathways through distinct mechanisms.

Genome‐wide association studies in adults have identified variants in hydroxysteroid 17‐beta dehydrogenase 13 (HSD17B13) and mitochondrial amidoxime reducing component 1 (MTARC1) as protective against nonalcoholic fatty liver disease (NAFLD). We aimed to test their association with pediatric NAFLD liver histology and investigate their function using metabolomics. A total of 1450 children (729 with NAFLD, 399 with liver histology) were genotyped for rs72613567T>TA in HSD17B13, rs2642438G>A in MTARC1, and rs738409C>G in patatin‐like phospholipase domain‐containing protein 3 (PNPLA3). Genotype–histology associations were tested using ordinal regression. Untargeted hepatic proteomics and plasma lipidomics were performed in a subset of children. We found rs72613567T>TA in HSD17B13 to be associated with lower odds of NAFLD diagnosis (odds ratio, 0.7; 95% confidence interval, 0.6–0.9) and a lower grade of portal inflammation (p < 0.001). rs2642438G>A in MTARC1 was associated with a lower grade of hepatic steatosis (p = 0.02). Proteomics found reduced expression of HSD17B13 in carriers of the protective ‐TA allele. MTARC1 levels were unaffected by genotype. Both variants were associated with down‐regulation of fibrogenic pathways. HSD17B13 perturbs plasma phosphatidylcholines and triglycerides. In silico modeling suggested p.Ala165Thr disrupts the stability and metal binding of MTARC1. Conclusion: Both HSD17B13 and MTARC1 variants are associated with less severe pediatric NAFLD. These results provide further evidence for shared genetic mechanisms between pediatric and adult NAFLD.

Improving confidence in lipidomic annotations by incorporating empirical ion mobility regression analysis and chemical class prediction.

Mass spectrometry-based untargeted lipidomics aims to globally characterize the lipids and lipid-like molecules in biological systems. Ion mobility increases coverage and confidence by offering an additional dimension of separation and a highly reproducible metric for feature annotation, the collision cross-section (CCS). We present a data processing workflow to increase confidence in molecular class annotations based on CCS values. This approach uses class-specific regression models built from a standardized CCS repository (the Unified CCS Compendium) in a parallel scheme that combines a new annotation filtering approach with a machine learning class prediction strategy. In a proof-of-concept study using murine brain lipid extracts, 883 lipids were assigned higher confidence identifications using the filtering approach, which reduced the tentative candidate lists by over 50% on average. An additional 192 unannotated compounds were assigned a predicted chemical class. All relevant source code is available at https://github.com/McLeanResearchGroup/CCS-filter. Supplementary data are available at Bioinformatics online.

Multi-Omics Approach Reveals Dysregulation of Protein Phosphorylation Correlated with Lipid Metabolism in Mouse Non-Alcoholic Fatty Liver.

Obesity caused by overnutrition is a major risk factor for non-alcoholic fatty liver disease (NAFLD). Several lipid intermediates such as fatty acids, glycerophospholipids and sphingolipids are implicated in NAFLD, but detailed characterization of lipids and their functional links to proteome and phosphoproteome remain to be elucidated. To characterize this complex molecular relationship, we used a multi-omics approach by conducting comparative proteomic, phoshoproteomic and lipidomic analyses of high fat (HFD) and low fat (LFD) diet fed mice livers. We quantified 2447 proteins and 1339 phosphoproteins containing 1650 class I phosphosites, of which 669 phosphosites were significantly different between HFD and LFD mice livers. We detected alterations of proteins associated with cellular metabolic processes such as small molecule catabolic process, monocarboxylic acid, long- and medium-chain fatty acid, and ketone body metabolic processes, and peroxisome organization. We observed a significant downregulation of protein phosphorylation in HFD fed mice liver in general. Untargeted lipidomics identified upregulation of triacylglycerols, glycerolipids and ether glycerophosphocholines and downregulation of glycerophospholipids, such as lysoglycerophospholipids, as well as ceramides and acylcarnitines. Analysis of differentially regulated phosphosites revealed phosphorylation dependent deregulation of insulin signaling as well as lipogenic and lipolytic pathways during HFD induced obesity. Thus, this study reveals a molecular connection between decreased protein phosphorylation and lipolysis, as well as lipid-mediated signaling in diet-induced obesity.