Lipidomics Reveals Myocardial Lipid Composition in a Murine Model of Insulin Resistance Induced by a High-Fat Diet.

Ectopic fat accumulation in non-adipose tissues is closely related to diabetes-related myocardial dysfunction. Nevertheless, the complete picture of the lipid metabolites involved in the metabolic-related myocardial alterations is not fully characterized. The aim of this study was to characterize the specific lipid profile in hearts in an animal model of obesity/insulin resistance induced by a high-fat diet (HFD). The cardiac lipidome profiles were assessed via liquid chromatography-mass spectrometry (LC-MS)/MS-MS and laser desorption/ionization-mass spectrometry (LDI-MS) tissue imaging in hearts from C57BL/6J mice fed with an HFD or standard-diet (STD) for 12 weeks. Targeted lipidome analysis identified a total of 63 lipids (i.e., 48 triacylglycerols (TG), 5 diacylglycerols (DG), 1 sphingomyelin (SM), 3 phosphatidylcholines (PC), 1 DihydroPC, and 5 carnitines) modified in hearts from HFD-fed mice compared to animals fed with STD. Whereas most of the TG were up-regulated in hearts from animals fed with an HFD, most of the carnitines were down-regulated, thereby suggesting a reduction in the mitochondrial ß-oxidation. Roughly 30% of the identified metabolites were oxidated, pointing to an increase in lipid peroxidation. Cardiac lipidome was associated with a specific biochemical profile and a specific liver TG pattern. Overall, our study reveals a specific cardiac lipid fingerprint associated with metabolic alterations induced by HFD.

Serum metabolomics profiling by proton nuclear magnetic resonance spectrometry of the response to single oral macronutrient challenges in women with polycystic ovary syndrome (PCOS) compared with male and female controls.

BACKGROUND: The polycystic ovary syndrome (PCOS) is associated with insulin resistance, obesity and cardiometabolic comorbidities. We here challenged the hypothesis, using state-of-the-art proton nuclear magnetic resonance spectrometry (1H-NMRS) metabolomics profiling, that androgen excess in women induces a certain masculinization of postprandial metabolism that is modulated by obesity. MATERIALS AND METHODS: Participants were 53 Caucasian young adults, including 17 women with classic PCOS consisting of hyperandrogenism and ovulatory dysfunction, 17 non-hyperandrogenic women presenting with regular menses, and 19 healthy men, selected to be similar in terms of age and body mass index (BMI). Half of the subjects had obesity. Patients were submitted to isocaloric separate glucose, lipid and protein oral challenges in alternate days and fasting and postprandial serum samples were submitted to 1H-NMRS metabolomics profiling for quantification of 36 low-molecular-weight polar metabolites. RESULTS: The largest postprandial changes were observed after glucose and protein intake, with lipid ingestion inducing smaller differences. Changes after glucose intake consisted of a marked increase in carbohydrates and byproducts of glycolysis, and an overall decrease in byproducts of proteolysis, lipolysis and ketogenesis. After the protein load, most amino acids and derivatives increased markedly, in parallel to an increase in pyruvate and a decrease in 3-hydroxybutyric acid and glycerol. Obesity increased ß- and D-glucose and pyruvate levels, with this effect being observed mostly after glucose ingestion in women with PCOS. Regardless of the type of macronutrient, men presented increased lysine and decreased 3-hydroxybutyric acid. In addition, non-obese men showed increased postprandial ß-glucose and decreased pyroglutamic acid, compared with non-obese control women. We observed a common pattern of postprandial changes in branched-chain and aromatic amino acids, where men showed greater amino acids increases after protein intake than control women and patients with PCOS but only within the non-obese participants. Conversely, this increase was blunted in obese men but not in obese women, who even presented a larger increase in some amino acids compared with their non-obese counterparts. Interestingly, regardless of the type of macronutrient, only obese women with PCOS showed increased leucine, lysine, phenylalanine and tryptophan levels compared with non-obese patients. CONCLUSIONS: Serum 1H-NMRS metabolomics profiling indicated sexual dimorphism in the responses to oral macronutrient challenges, which were apparently driven by the central role of postprandial insulin effects with obesity, and to a lesser extent PCOS, exerting modifying roles derived from insulin resistance. Hence, obesity impaired metabolic flexibility in young adults, yet sex and sex hormones also influenced the regulation of postprandial metabolism.

The polycystic ovary syndrome (PCOS) is a common endocrine disorder in women. PCOS is associated with diabetes, obesity and cardiometabolic disease. Mild excess of androgens (male hormones) characterize PCOS, and facilitate that body fat accumulates in the visceral abdominal area. Visceral fat promotes insulin resistance increasing the risk for diabetes and cardiometabolic disease, and further androgen excess. We here explored intermediate metabolism after the separate administration of either carbohydrates, fats or proteins, in young adult women with or without PCOS and in men, using state-of-the-art proton nuclear magnetic resonance metabolomics profiling. Results suggest that postprandial metabolomics profiles reflect mostly insulin actions, with changes derived from insulin resistance being more important with obesity but also being influenced by male sex and PCOS in women.

rMSIfragment: improving MALDI-MSI lipidomics through automated in-source fragment annotation.

Matrix-Assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) spatially resolves the chemical composition of tissues. Lipids are of particular interest, as they influence important biological processes in health and disease. However, the identification of lipids in MALDI-MSI remains a challenge due to the lack of chromatographic separation or untargeted tandem mass spectrometry. Recent studies have proposed the use of MALDI in-source fragmentation to infer structural information and aid identification. Here we present rMSIfragment, an open-source R package that exploits known adducts and fragmentation pathways to confidently annotate lipids in MALDI-MSI. The annotations are ranked using a novel score that demonstrates an area under the curve of 0.7 in ROC analyses using HPLC-MS and Target-Decoy validations. rMSIfragment applies to multiple MALDI-MSI sample types and experimental setups. Finally, we demonstrate that overlooking in-source fragments increases the number of incorrect annotations. Annotation workflows should consider in-source fragmentation tools such as rMSIfragment to increase annotation confidence and reduce the number of false positives.

LC/MS-Based Untargeted Metabolomics Study in Women with Nonalcoholic Steatohepatitis Associated with Morbid Obesity.

This study investigated the importance of a metabolomic analysis in a complex disease such as nonalcoholic steatohepatitis (NASH) associated with obesity. Using an untargeted metabolomics technique, we studied blood metabolites in 216 morbidly obese women with liver histological diagnosis. A total of 172 patients were diagnosed with nonalcoholic fatty liver disease (NAFLD), and 44 were diagnosed with normal liver (NL). Patients with NAFLD were classified into simple steatosis (n = 66) and NASH (n = 106) categories. A comparative analysis of metabolites levels between NASH and NL demonstrated significant differences in lipid metabolites and derivatives, mainly from the phospholipid group. In NASH, there were increased levels of several phosphatidylinositols and phosphatidylethanolamines, as well as isolated metabolites such as diacylglycerol 34:1, lyso-phosphatidylethanolamine 20:3 and sphingomyelin 38:1. By contrast, there were decreased levels of acylcarnitines, sphingomyelins and linoleic acid. These findings may facilitate identification studies of the main pathogenic metabolic pathways related to NASH and may also have a possible applicability in a panel of metabolites to be used as biomarkers in future algorithms of the disease diagnosis and its follow-up. Further confirmatory studies in groups with different ages and sexes are necessary.

Gradual Increase in Inflammation-Linked Glycoproteins and a Proatherogenic Lipoprotein Profile in the Early Stages of Psychosis as Characterized by 1H NMR Blood Analysis.

Minimally invasive prognostic markers of inflammation and dyslipidemia in individuals with a risk of psychosis, also called "at-risk mental state" (ARMS), or in the first episode of psychosis (FEP) are of utmost clinical importance to prevent cardiovascular disorders. We analyzed the plasma concentration of inflammation-linked glycoproteins (Glycs) and lipoprotein subclasses by proton nuclear magnetic resonance (1H NMR) in a single acquisition. Study participants were healthy controls (HCs, N = 67) and patients with ARMS (N = 58), FEP (N = 110), or early psychosis diagnosis with ≥2 episodes (critical period (CP), N = 53). Clinical biomarkers such as high-sensitivity C-reactive protein, interleukin 6, fibrinogen, insulin, and lipoproteins were also measured. Although all participants had normal lipoprotein profiles and no inflammation according to conventional biomarkers, a gradual increase in the Glyc 1H NMR levels was observed from HCs to CP patients; this increase was statistically significant for GlycA (CP vs HC). In parallel, a progressive and significant proatherogenic 1H NMR lipoprotein profile was also identified across stages of psychosis (ARMS and CP vs HC). These findings highlight the potential of using 1H NMR Glyc and lipoprotein profiling to identify blood changes in individuals with ARMS or FEP and pave the way for applications using this technology to monitor metabolic and cardiovascular risks in clinical psychiatry.

LC/MS-Based Untargeted Metabolomics Analysis in Women with Morbid Obesity and Associated Type 2 Diabetes Mellitus.

Obesity is a chronic and complex disease, with an increasing incidence worldwide that is associated with metabolic disorders such as type 2 diabetes mellitus (T2DM). Thus, it is important to determine the differences between metabolically healthy obese individuals and those with metabolic disorders. The aim of this study was to perform an untargeted metabolomics assay in women with morbid obesity (MO) compared to a normal weight group, and to differentiate the metabolome of these women with MO who present with T2DM. We carried out a liquid chromatography-mass spectrometry-based untargeted metabolomics assay using serum samples of 209 Caucasian women: 73 with normal weight and 136 with MO, of which 71 had T2DM. First, we found increased levels of choline and acylglycerols and lower levels of bile acids, steroids, ceramides, glycosphingolipids, lysophosphatidylcholines, and lysophosphatidylethanolamines in MO women than in the control group. Then, in MO women with T2DM, we found increased levels of glutamate, propionyl-carnitine, bile acids, ceramides, lysophosphatidylcholine 14:0, phosphatidylinositols and phosphoethanolamines, and lower levels of Phe-Ile/Leu. Thus, we found metabolites with opposite trends of concentration in the two metabolomic analyses. These metabolites could be considered possible new factors of study in the pathogenesis of MO and associated T2DM in women.

Serum metabolomics profiling by proton nuclear magnetic resonance spectroscopy reveals sexual dimorphism and masculinization of intermediate metabolism in women with polycystic ovary syndrome (PCOS).

BACKGROUND: The polycystic ovary syndrome (PCOS) is associated with insulin resistance, obesity and cardiometabolic comorbidities. We here challenged the hypothesis, using state-of-the art proton nuclear magnetic resonance spectroscopy metabolomics profiling, that androgen excess in women induces also a certain masculinization of intermediate metabolism that is modulated by obesity. METHODS: Participants were 53 Caucasian young adults, including 17 women with classic PCOS consisting of hyperandrogenism and ovulatory dysfunction, 17 non-hyperandrogenic women presenting with regular menses, and 19 healthy men, selected in order to be similar in terms of age and body mass index (BMI). Half of the subjects had obesity defined by a body mass index ≥ 30 kg/m2. Subjects maintained the same diet unrestricted in carbohydrates for 3 days before sampling and maintained their lifestyle and exercise patterns prior and during the study. Plasma samples were submitted to proton nuclear magnetic resonance spectroscopy metabolomics profiling. RESULTS: Obesity associated a metabolomics profile mainly characterized by increased branched chain and aromatic aminoacids. Regardless of obesity, this unfavorable profile also characterized men as compared with control women, and was shared by women with PCOS. Notably, the negative impact of obesity on metabolomics profile was restricted to women, with obese men showing no further deterioration when compared with their non-obese counterparts. CONCLUSIONS: Serum metabolomics profiling by proton nuclear magnetic resonance spectroscopy reveals sexual dimorphism, and masculinization of intermediate metabolism in women with PCOS, further suggesting a role for sex and sex hormones in the regulation of intermediate metabolism.

What are we imaging? Software tools and experimental strategies for annotation and identification of small molecules in mass spectrometry imaging.

Mass spectrometry imaging (MSI) has become a widespread analytical technique to perform nonlabeled spatial molecular identification. The Achilles' heel of MSI is the annotation and identification of molecular species due to intrinsic limitations of the technique (lack of chromatographic separation and the difficulty to apply tandem MS). Successful strategies to perform annotation and identification combine extra analytical steps, like using orthogonal analytical techniques to identify compounds; with algorithms that integrate the spectral and spatial information. In this review, we discuss different experimental strategies and bioinformatics tools to annotate and identify compounds in MSI experiments. We target strategies and tools for small molecule applications, such as lipidomics and metabolomics. First, we explain how sample preparation and the acquisition process influences annotation and identification, from sample preservation to the use of orthogonal techniques. Then, we review twelve software tools for annotation and identification in MSI. Finally, we offer perspectives on two current needs of the MSI community: the adaptation of guidelines for communicating confidence levels in identifications; and the creation of a standard format to store and exchange annotations and identifications in MSI.

Urinary Metabolomics Study on the Protective Role of Cocoa in Zucker Diabetic Rats via 1H-NMR-Based Approach.

Cocoa constitutes one of the richest sources of dietary flavonoids with demonstrated anti-diabetic potential. However, the metabolic impact of cocoa intake in a diabetic context remains unexplored. In this study, metabolomics tools have been used to investigate the potential metabolic changes induced by cocoa in type 2 diabetes (T2D). To this end, male Zucker diabetic fatty rats were fed on standard (ZDF) or 10% cocoa-rich diet (ZDF-C) from week 10 to 20 of life. Cocoa supplementation clearly decreased serum glucose levels, improved glucose metabolism and produced significant changes in the urine metabolome of ZDF animals. Fourteen differential urinary metabolites were identified, with eight of them significantly modified by cocoa. An analysis of pathways revealed that butanoate metabolism and the synthesis and degradation of branched-chain amino acids and ketone bodies are involved in the beneficial impact of cocoa on diabetes. Moreover, correlation analysis indicated major associations between some of these urine metabolites (mainly valine, leucine, and isoleucine) and body weight, glycemia, insulin sensitivity, and glycated hemoglobin levels. Overall, this untargeted metabolomics approach provides a clear metabolic fingerprint associated to chronic cocoa intake that can be used as a marker for the improvement of glucose homeostasis in a diabetic context.

Measurement of Serum N-Glycans in the Assessment of Early Vascular Aging (Arterial Stiffness) in Adults With Type 1 Diabetes.

OBJECTIVE: Vascular aging (arterial stiffness [AS]) is an inflammation-linked process that predicts macro- and microvascular complications in adults with type 1 diabetes (T1D). We evaluated the utility of measuring the inflammation-linked N-glycans GlycA and GlycB to assess vascular aging in adults with T1D. RESEARCH DESIGN AND METHODS: Eighty-four adults with T1D (>10-year duration without cardiovascular events) and 68 healthy control subjects were evaluated for clinical characteristics (including microvascular complications in patients with T1D), aortic pulse wave velocity (aPWV) (surrogate measure of AS), and serum GlycA and GlycB (peak area [concentration] and height/width [H/W] ratio) using 1H-nuclear magnetic resonance spectroscopy. RESULTS: Patients with T1D had higher median (interquartile range) values than healthy control subjects for (P < 0.001 for all comparisons) aPWV 7.9 (6.9-9.1) vs. 6.1 (5.5-6.7) m/s, GlycA 850.4 (781.3-916.1) vs. 652.4 (581.5-727.1) µmoL; GlycB 386.1 (353.2-426.3) vs. 310.0 (280.5-331.9) µmol/L), H/W ratio of GlycA 16.5 (14.9-18.1) vs. 15.0 (13.7-16.7), and H/W ratio of GlycB 5.0 (4.6-5.5) vs. 4.0 (3.4-4.3). Moreover, aPWV correlated (P < 0.001 for all correlations) with GlycA (r = 0.550) and GlycB (r = 0.423) concentrations and with H/W ratios of GlycA (r = 0.453) and GlycB (r = 0.510). Adjusting for potential confounders, GlycA concentration (ß = 0.212, P < 0.001) and the H/W ratios of GlycA (ß = 0.150, P = 0.009) and GlycB (ß = 0.155, P = 0.011) remained independently associated with aPWV. C-statistics for detecting individuals with aPWV >10 m/s were 0.866 (95% CI 0.794-0.937) for GlycA levels and 0.862 (0.780-0.943) for H/W ratio of GlycB. CONCLUSIONS: Measurement of serum GlycA and GlycB may have utility in assessing vascular aging in adults with T1D of >10-year duration and no previous cardiovascular events.

Application of Machine Learning Solutions to Optimize Parameter Prediction to Enhance Automatic NMR Metabolite Profiling.

The quality of automatic metabolite profiling in NMR datasets from complex matrices can be affected by the numerous sources of variability. These sources, as well as the presence of multiple low-intensity signals, cause uncertainty in the metabolite signal parameters. Lineshape fitting approaches often produce suboptimal resolutions to adapt them in a complex spectrum lineshape. As a result, the use of software tools for automatic profiling tends to be restricted to specific biological matrices and/or sample preparation protocols to obtain reliable results. However, the analysis and modelling of the signal parameters collected during initial iteration can be further optimized to reduce uncertainty by generating narrow and accurate predictions of the expected signal parameters. In this study, we show that, thanks to the predictions generated, better profiling quality indicators can be outputted, and the performance of automatic profiling can be maximized. Our proposed workflow can learn and model the sample properties; therefore, restrictions in the biological matrix, or sample preparation protocol, and limitations of lineshape fitting approaches can be overcome.

Muscular carnosine is a marker for cardiorespiratory fitness and cardiometabolic risk factors in men with type 1 diabetes.

PURPOSE: Muscle is an essential organ for glucose metabolism and can be influenced by metabolic disorders and physical activity. Elevated muscle carnosine levels have been associated with insulin resistance and cardiometabolic risk factors. Little is known about muscle carnosine in type 1 diabetes (T1D) and how it is influenced by physical activity. The aim of this study was to characterize muscle carnosine in vivo by proton magnetic resonance spectroscopy (1H MRS) and evaluate the relationship with physical activity, clinical characteristics and lipoprotein subfractions. METHODS: 16 men with T1D (10 athletes/6 sedentary) and 14 controls without diabetes (9/5) were included. Body composition by DXA, cardiorespiratory capacity (VO2peak) and serum lipoprotein profile by proton nuclear magnetic resonance (1H NMR) were obtained. Muscle carnosine scaled to water (carnosineW) and to creatine (carnosineCR), creatine and intramyocellular lipids (IMCL) were quantified in vivo using 1H MRS in a 3T MR scanner in soleus muscle. RESULTS: Subjects with T1D presented higher carnosine CR levels compared to controls. T1D patients with a lower VO2peak presented higher carnosineCR levels compared to sedentary controls, but both T1D and control groups presented similar levels of carnosineCR at high VO2peak levels. CarnosineW followed the same trend. Integrated correlation networks in T1D demonstrated that carnosineW and carnosineCR were associated with cardiometabolic risk factors including total and abdominal fat, pro-atherogenic lipoproteins (very low-density lipoprotein subfractions), low VO2peak, and IMCL. CONCLUSIONS: Elevated muscle carnosine levels in persons with T1D and their effect on atherogenic lipoproteins can be modulated by physical activity.

Statistical mediation of the relationships between chronological age and lipoproteins by nonessential amino acids in healthy men.

Aging is a major risk factor for metabolic impairment that may lead to age-related diseases such as cardiovascular disease. Different mechanisms that may explain the interplay between aging and lipoproteins, and between aging and low-molecular-weight metabolites (LMWMs), in the metabolic dysregulation associated with age-related diseases have been described separately. Here, we statistically evaluated the possible mediation effects of LMWMs on the relationships between chronological age and lipoprotein concentrations in healthy men ranging from 19 to 75 years of age. Relative and absolute concentrations of LMWMs and lipoproteins, respectively, were assessed by nuclear magnetic resonance (NMR) spectroscopy. Multivariate linear regression and mediation analysis were conducted to explore the associations between age, lipoproteins and LMWMs. The statistical significance of the identified mediation effects was evaluated using the bootstrapping technique, and the identified mediation effects were validated on a publicly available dataset. Chronological age was statistically associated with five lipoprotein classes and subclasses. The mediation analysis showed that serine mediated 24.1% (95% CI: 22.9 - 24.7) of the effect of age on LDL-P, and glutamate mediated 17.9% (95% CI: 17.6 - 18.5) of the effect of age on large LDL-P. In the publicly available data, glutamate mediated the relationship between age and an NMR-derived surrogate of cholesterol. Our results suggest that the age-related increase in LDL particles may be mediated by a decrease in the nonessential amino acid glutamate. Future studies may contribute to a better understanding of the potential biological role of glutamate and LDL particles in aging mechanisms and age-related diseases.

Glycoprotein Profile Measured by a 1H-Nuclear Magnetic Resonance Based on Approach in Patients with Diabetes: A New Robust Method to Assess Inflammation.

Patients with type 2 diabetes mellitus (T2DM) and atherogenic dyslipidemia (AD) are at higher risk of developing cardiovascular diseases (CVDs), so an interest in discovering inflammation biomarkers as indicators of processes related to CVD progression is increasing. This study aims (a) to characterize the plasma glycoprotein profile of a cohort of 504 participants, including patients with and without T2DM and/or AD and controls, and (b) to study the associations between the glycoprotein profile and other lipid and clinical variables in these populations. We characterized the plasma glycoprotein profiles by using 1H-NMR. We quantified the two peaks associated with the concentration of plasma glycoproteins (GlycA and GlycB) and their height/width ratios (H/W GlycA and H/W GlycB), as higher and narrower signals have been related to inflammation. We also quantified GlycF, the signal of which is proportional to the concentration of the acetyl groups of free N-acetylglucosamine, N-acetylgalactosamine, and N-acetylneuraminic in the samples. The lipoprotein profile was also determined (Liposcale®). Standard clinical and anthropometric measurements were taken. Multivariate classification models were developed to study the differences between the study groups. Reduced HDL-C levels, increased small dense LDL and HDL particles, and elevated TG levels were significantly associated with glycoprotein variables. Glycoprotein values in the diagnostic groups were significantly different from those in the CT groups. AD and DM conditions together contribute to a positive and significant synergetic effect on the GlycA area (<0.05) and the H/W ratios of GlycA (<0.01) and GlycB (<0.05). By adding the new glycoprotein variables to the traditionally used marker of inflammation C-reactive protein (CRP), the AUC increased sharply for classification models between the CT group and the rest (0.68 to 0.84), patients with and without dyslipidemia (0.54 to 0.86), and between patients with and without diabetes (0.55 to 0.75). 1H-NMR-derived glycoproteins can be used as possible markers of the degree of inflammation associated with T2DM and AD.

Unravelling the metabolic alterations of liver damage induced by thirdhand smoke.

BACKGROUND: Thirdhand smoke (THS) is the accumulation of tobacco smoke gases and particles that become embedded in materials. Previous studies concluded that THS exposure induces oxidative stress and hepatic steatosis in liver. Despite the knowledge of the increasing danger of THS exposure, the metabolic disorders caused in liver are still not well defined. OBJECTIVES: The aim of this study is to investigate the metabolic disorders caused by THS exposure in liver of male mice and to evaluate the effects of an antioxidant treatment in the exposed mice. METHODS: We investigated liver from three mice groups: non-exposed mice, exposed to THS in conditions that mimic human exposure and THS-exposed treated with antioxidants. Liver samples were analyzed using a multiplatform untargeted metabolomics approach including nuclear magnetic resonance (1H NMR), liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) and laser desorption/ionization mass spectrometry imaging (MSI), able to map lipids in liver tissues. RESULTS: Our multiplatform approach allowed the annotation of eighty-eight metabolites altered by THS exposure, including amino acids, nucleotides and several types of lipids. The main dysregulated pathways by THS exposure were D-glutamine and D-glutamate metabolism, glycerophospholipid metabolism and oxidative phosphorylation and glutathione metabolism, being the last two related to oxidative stress. THS-exposed mice also presented higher lipid accumulation and decrease of metabolites involved in the phosphocholine synthesis, as well as choline deficiency, which is related to Non-Alcoholic Fatty Liver Disease and steatohepatitis. Interestingly, the antioxidant treatment of THS-exposed mice reduced the accumulation of some lipids, but could not revert all the metabolic alterations, including some related to the impairment of the mitochondrial function. CONCLUSIONS: THS alters liver function at a molecular level, dysregulating many metabolic pathways. The molecular evidences provided here confirm that THS is a new factor for liver steatosis and provide the basis for future research in this respect.

Analysis of LDL and HDL size and number by nuclear magnetic resonance in a healthy working population: The LipoLab Study.

BACKGROUND AND AIM: Atherosclerosis is the underlying process in cardiovascular disease (CVD), the first cause of death in developed countries. We aimed to identify people with no known CVD and normal values of LDL-C and HDL-C, but with alterations in the number and size of lipoprotein particles (as measured by nuclear magnetic resonance [NMR]) and to analyse their sociodemographic, clinical and biochemical characteristics. METHODS: Cross-sectional study in occupational risks prevention centre in Castellón (Spain) in 2017 and 2018, in consecutively recruited adults (18-65 years) with no known CVD. Sociodemographic, clinical and biochemical variables were collected. Lipid profiles were analysed (Liposcale test), along with the concentration, size and number of the main types of lipoprotein particles, determined by 2D diffusion-ordered NMR spectroscopy. Using contingency tables, we analysed the characteristics of people with normal LDL and HDL cholesterol but abnormal levels of LDL and HDL particles. The magnitude of association between explanatory variables and abnormal levels of each kind of lipoprotein was assessed with multivariable logistic regression models. RESULTS: Of the 400 total participants (31.3% women; age 46.4 ± 4.3 years), 169 had normal LDL and HDL cholesterol. Abnormal lipoprotein particle values depended on the subtype: prevalence of abnormal LDL levels ranged from 8.3% to 36.7%; and of HDL, from 28.4% to 42.6%. High systolic blood pressure and total cholesterol were significantly associated with abnormal LDL levels. Male sex and high systolic blood pressure were associated with abnormalities in HDL. CONCLUSIONS: An extended lipids profile, obtained by NMR, enables the identification of people with normal HDL-C and LDL-C levels who present abnormal levels of LDL-P and/or HDL-P. Higher total cholesterol, systolic blood pressure, BMI and male sex were significantly associated with these abnormal values.

Raman2imzML converts Raman imaging data into the standard mass spectrometry imaging format.

BACKGROUND: Multimodal imaging that combines mass spectrometry imaging (MSI) with Raman imaging is a rapidly developing multidisciplinary analytical method used by a growing number of research groups. Computational tools that can visualize and aid the analysis of datasets by both techniques are in demand. RESULTS: Raman2imzML was developed as an open-source converter that transforms Raman imaging data into imzML, a standardized common data format created and adopted by the mass spectrometry community. We successfully converted Raman datasets to imzML and visualized Raman images using open-source software designed for MSI applications. CONCLUSION: Raman2imzML enables both MSI and Raman images to be visualized using the same file format and the same software for a straightforward exploratory imaging analysis.

Hepatic Lipidomics and Molecular Imaging in a Murine Non-Alcoholic Fatty Liver Disease Model: Insights into Molecular Mechanisms.

An imbalance between hepatic fatty acid uptake and removal results in ectopic fat accumulation, which leads to non-alcoholic fatty liver disease (NAFLD). The amount and type of accumulated triglycerides seem to play roles in NAFLD progression; however, a complete understanding of how triglycerides contribute to NAFLD evolution is lacking. Our aim was to evaluate triglyceride accumulation in NAFLD in a murine model and its associations with molecular mechanisms involved in liver damage and adipose tissue-liver cross talk by employing lipidomic and molecular imaging techniques. C57BL/6J mice fed a high-fat diet (HFD) for 12 weeks were used as a NAFLD model. Standard-diet (STD)-fed animals were used as controls. Standard liver pathology was assessed using conventional techniques. The liver lipidome was analyzed by liquid chromatography-mass spectrometry (LC-MS) and laser desorption/ionization-mass spectrometry (LDI-MS) tissue imaging. Liver triglycerides were identified by MS/MS. The transcriptome of genes involved in intracellular lipid metabolism and inflammation was assessed by RT-PCR. Plasma leptin, resistin, adiponectin, and FABP4 levels were determined using commercial kits. HFD-fed mice displayed increased liver lipid content. LC-MS analyses identified 14 triglyceride types that were upregulated in livers from HFD-fed animals. Among these 14 types, 10 were identified in liver cross sections by LDI-MS tissue imaging. The accumulation of these triglycerides was associated with the upregulation of lipogenesis and inflammatory genes and the downregulation of ß-oxidation genes. Interestingly, the levels of plasma FABP4, but not of other adipokines, were positively associated with 8 of these triglycerides in HFD-fed mice but not in STD-fed mice. Our findings suggest a putative role of FABP4 in the liver-adipose tissue cross talk in NAFLD.

Glycoprotein Profile Assessed by 1H-NMR as a Global Inflammation Marker in Patients with HIV Infection. A Prospective Study.

Plasma glycoproteins are a composite biomarker of inflammation and can be detected by 1H-NMR. The aim of this study was to prospectively appraise the clinical value of plasma glycoproteins assessed by 1H-NMR in people living with HIV (PLWH). A total of 221 patients with HIV infection were recruited and studied at baseline and at 48 and 144 weeks. Patients were distributed into two groups according to baseline CD4+ T-cell number below or above 200 cells/µL. Patients with fewer than 200 cells/µL were distributed into the responders and nonresponders according to antiretroviral therapy (ART) response at 144 weeks. Glycoprotein concentrations were determined by 1H-NMR arising from the protein bond N-acetylglucosamine and N-acetylgalactosamine signals (GlycA); and N-acetylneuraminic acid signal (GlycB) associated with the sugar-protein bond concentration and aggregation state (shapes (height/width)). Basal glycoprotein concentrations were higher in patients with < 200 CD4+ T-cell/µL (Glyc A: 1040(917.9-1199.1) vs. 950.4(845.5-1050.9), p < 0.001, and Glyc B: 521(440.3-610.3) vs. 468.6(417.9-507.0) µ mol/L, p < 0.001) being reduced by ART. The height/width (H/W) ratio was the parameter showing a better association with this clinical status. Baseline glycoproteins predict the condition of responder/nonresponder. In this study, 1H-NMR glycoproteins provide novel insights to assess inflammation status and have prognostic value in PLWH.

rMSIproc: an R package for mass spectrometry imaging data processing.

SUMMARY: Mass spectrometry imaging (MSI) can reveal biochemical information directly from a tissue section. MSI generates a large quantity of complex spectral data which is still challenging to translate into relevant biochemical information. Here, we present rMSIproc, an open-source R package that implements a full data processing workflow for MSI experiments performed using TOF or FT-based mass spectrometers. The package provides a novel strategy for spectral alignment and recalibration, which allows to process multiple datasets simultaneously. This enables to perform a confident statistical analysis with multiple datasets from one or several experiments. rMSIproc is designed to work with files larger than the computer memory capacity and the algorithms are implemented using a multi-threading strategy. rMSIproc is a powerful tool able to take full advantage of modern computer systems to completely develop the whole MSI potential. AVAILABILITY AND IMPLEMENTATION: rMSIproc is freely available at https://github.com/prafols/rMSIproc. CONTACT: pere.rafols@urv.cat. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.