A multi-metabolite analysis of serum by 1H NMR spectroscopy: Early systemic signs of Alzheimer’s disease

Effect of woohwangchungsimwon and donepezil co-treatment on cognitive function and serum metabolic profiles in a scopolamine-induced model of Alzheimer's disease

ETHNOPHARMACOLOGICAL RELEVANCE

Woohwangchungsimwon (WCW) is a traditional medicine used in East Asian countries to treat central nervous system disorders. Reported pharmacological properties include antioxidant effects, enhanced learning and memory, and protection against ischemic neuronal cell death, supporting its use in treating neurodegenerative diseases like Alzheimer's disease (AD).

AIM OF THE STUDY

The study aims to assess the effects of co-treatment with WCW and donepezil on cognitive functions and serum metabolic profiles in a scopolamine-induced AD model.

MATERIALS AND METHODS

Cell viability and reactive oxygen species (ROS) levels were measured in amyloid β-peptide25-35 (Aβ25-35)-induced SH-SY5Y cells. An AD model was established in ICR mice by intraperitoneal scopolamine administration. Animals underwent the step-through passive avoidance test (PAT) and Morris water maze (MWM) test. Hippocampal tissues were collected to examine specific protein expression. Serum metabolic profiles were analyzed using nuclear magnetic resonance (NMR) spectroscopy.

RESULTS

Co-treatment with WCW and donepezil increased cell viability and reduced ROS production in Aβ25-35-induced SH-SY5Y cells compared to that with donepezil treatment alone. Co-treatment improved cognitive functions and was comparable to donepezil treatment alone in the PAT and MWM tests. Pathways related to tyrosine, phenylalanine, and tryptophan biosynthesis, phenylalanine metabolism, and cysteine and methionine metabolism were altered by co-treatment. Levels of tyrosine and methionine, major serum metabolites in these pathways, were significantly reduced after co-treatment.

CONCLUSIONS

Co-treatment with WCW and donepezil shows promise as a therapeutic strategy for AD and is comparable to donepezil alone in improving cognitive function. Reduced tyrosine and methionine levels after co-treatment may enhance cognitive function by mitigating hypertyrosinemia and hyperhomocysteinemia, known risk factors for AD. The serum metabolic profiles obtained in this study can serve as a foundation for developing other bioactive compounds using a scopolamine-induced mouse model.

Impact of Sea Warming and 17-α-Ethinylestradiol Exposure on the Lipid Metabolism of Ruditapes philippinarum Clams

This paper reports on an NMR metabolomics study of lipophilic extracts of Ruditapes philippinarum clams exposed to the hormonal contaminant 17-α-ethinylestradiol (EE2), at 17 °C and 21 °C. The results reveal that exposure at 17 °C triggers a weak response at low EE2 concentrations, suggestive of a slight increase in membrane rigidity, followed by lipid metabolic stability at higher EE2 concentrations. On the other hand, at 21 °C, lipid metabolism begins to respond at 125 ng/L EE2, with antioxidant docosahexaenoic acid (DHA) helping to tackle high-oxidative-stress conditions, in tandem with enhanced storage of triglycerides. Exposure to 625 ng/L EE2 (highest concentration) enhances phosphatidylcholine (PtdCho) and polyunsaturated fatty acid (PUFA) levels, their direct intercorrelation suggesting PUFA incorporation in new membrane phospholipids. This should lead to increased membrane fluidity, probably aided by a decrease in cholesterol. PUFA levels, considered a measure of membrane fluidity, were strongly (and positively) correlated to intracellular glycine levels, thus identifying glycine as the main osmolyte entering the cells under high stress. Membrane fluidity also seems to elicit the loss of taurine. This work contributes to the understanding of the mechanisms of response of R. philippinarum clams to EE2 in tandem with warming while unveiling novel potential markers of stress mitigation, namely high levels of PtdCho, PUFAs (or PtdCho/glycerophosphocholine and PtdCho/acetylcholine ratios) and linoleic acid and low PUFA/glycine ratios.

1H NMR Metabolomics and Lipidomics To Monitor Positive Responses in Children with Autism Spectrum Disorder Following a Guided Parental Intervention: A Pilot Study

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition that is characterized by patients displaying at least two out of the classical symptoms, such as impaired social communication, impaired interactions, and restricted repetitive behavior. Early parent-mediated interventions, such as video modeling for parental training, were demonstrated to be a successful low-cost way to deliver care for children with ASD. Nuclear magnetic resonance (NMR)-based metabolomics/lipidomics has been successfully employed in several mental disorder studies. Metabolomics and lipidomics of 37 ASD patients (children, aged 3-8 years), who were divided into two groups, one control group with no parental-training intervention (N = 18) and the other in which the parents were trained by a video modeling intervention (ASD parental training, N = 19), were analyzed by proton NMR spectroscopy. Patients in the ASD parental-training group sera were seen to have increased glucose, myo-inositol, malonate, proline, phenylalanine, and gangliosides in their blood serum, while cholesterol, choline, and lipids were decreased, compared to the control group, who received no parental-training. Taken together, we demonstrated here significant changes in serum metabolites and lipids in ASD children, previously demonstrated to show clinical positive effects following a parental training intervention based on video modeling, delivered over 22 weeks. We demonstrate the value of applying metabolomics and lipidomics to identify potential biomarkers for clinical interventions follow-up in ASD.

Quantitative NMR-Based Lipoprotein Analysis Identifies Elevated HDL-4 and Triglycerides in the Serum of Alzheimer’s Disease Patients

Alzheimer’s disease (AD) is the most common form of dementia in the elderly and has been associated with changes in lipoprotein metabolism. We performed quantitative lipoprotein analysis in a local cohort of cognitively impaired elderly and control subjects using standardized nuclear magnetic resonance (NMR) spectroscopy. A commercially available quantitative NMR-based assay covering 112 lipoprotein main and subtype variables was used to investigate blood serum samples from a moderate cohort size of 161 persons (71 female, 90 male), including measures of quality control. Additionally, clinical metadata and cerebrospinal fluid AD biomarkers were collected and used for analysis. High-density lipoprotein (HDL) HDL-4 subfraction levels were mostly high in female individuals with mild cognitive impairment (MCI), followed by AD. Low-density lipoprotein (LDL) LDL-2 cholesterol was slightly elevated in male AD patients. HDL-2 apolipoprotein Apo-A1, HDL-2 phospholipids, and HDL-3 triglycerides were highly abundant in AD and MCI women compared to men. When considering clinical biomarkers (Aβ, tau), very low-density lipoprotein (VLDL) VLDL-1 and intermediate-density lipoprotein (IDL) triglycerides were substantially higher in AD compared to MCI. In addition, triglyceride levels correlated positively with dementia. Different lipoprotein serum patterns were identified for AD, MCI, and control subjects. Interestingly, HDL-4 and LDL-2 cholesterol parameters revealed strong gender-specific changes in the context of AD-driven dementia. As gender-based comparisons were based on smaller sub-groups with a low n-number, several statistical findings did not meet the significance threshold for multiple comparisons testing. Still, our finding suggests that serum HDL-4 parameters and various triglycerides correlate positively with AD pathology which could be a read-out of extended lipids traveling through the blood-brain barrier, supporting amyloid plaque formation processes. Thereof, we see herein a proof of concept that this quantitative NMR-based lipoprotein assay can generate important and highly interesting data for refined AD diagnosis and patient stratification, especially when larger cohorts are available.

NMR and Metabolomics-A Roadmap for the Future

Metabolomics investigates global metabolic alterations associated with chemical, biological, physiological, or pathological processes. These metabolic changes are measured with various analytical platforms including liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS) and nuclear magnetic resonance spectroscopy (NMR). While LC-MS methods are becoming increasingly popular in the field of metabolomics (accounting for more than 70% of published metabolomics studies to date), there are considerable benefits and advantages to NMR-based methods for metabolomic studies. In fact, according to PubMed, more than 926 papers on NMR-based metabolomics were published in 2021-the most ever published in a given year. This suggests that NMR-based metabolomics continues to grow and has plenty to offer to the scientific community. This perspective outlines the growing applications of NMR in metabolomics, highlights several recent advances in NMR technologies for metabolomics, and provides a roadmap for future advancements.

Endo- and Exometabolome Crosstalk in Mesenchymal Stem Cells Undergoing Osteogenic Differentiation

This paper describes, for the first time to our knowledge, a lipidome and exometabolome characterization of osteogenic differentiation for human adipose tissue stem cells (hAMSCs) using nuclear magnetic resonance (NMR) spectroscopy. The holistic nature of NMR enabled the time-course evolution of cholesterol, mono- and polyunsaturated fatty acids (including ω-6 and ω-3 fatty acids), several phospholipids (phosphatidylcholine, phosphatidylethanolamine, sphingomyelins, and plasmalogens), and mono- and triglycerides to be followed. Lipid changes occurred almost exclusively between days 1 and 7, followed by a tendency for lipidome stabilization after day 7. On average, phospholipids and longer and more unsaturated fatty acids increased up to day 7, probably related to plasma membrane fluidity. Articulation of lipidome changes with previously reported polar endometabolome profiling and with exometabolome changes reported here in the same cells, enabled important correlations to be established during hAMSC osteogenic differentiation. Our results supported hypotheses related to the dynamics of membrane remodelling, anti-oxidative mechanisms, protein synthesis, and energy metabolism. Importantly, the observation of specific up-taken or excreted metabolites paves the way for the identification of potential osteoinductive metabolites useful for optimized osteogenic protocols.

Study on the Association of Dietary Fatty Acid Intake and Serum Lipid Profiles With Cognition in Aged Subjects With Type 2 Diabetes Mellitus

Background

The correlation between dietary fatty acid (FA) intake and serum lipid profile levels with cognition in the aged population has been reported by previous studies. However, the association of dietary FA intake and serum lipid profile levels with cognition in subjects with type 2 diabetes mellitus (T2DM) is seldom reported.

Objective

A cross-sectional study was conducted to explore the correlation between dietary FA intake and serum lipid profiles with cognition in the aged Chinese population with T2DM.

Methods

A total of 1,526 aged Chinese subjects were recruited from communities. Fasting blood samples were collected for parameter measurement. The food frequency questionnaire (FFQ) method was applied for a dietary survey. Cognition was assessed using the Montreal Cognitive Assessment (MoCA) test. Dietary FA intake and serum lipid levels were compared between subjects with T2DM and control subjects. A logistic regression analysis was carried out for analyzing the association of FA intake and serum lipid levels with the risk of mild cognitive impairment (MCI) in subjects with T2DM and control subjects.

Results

There was a significant difference in the serum lipid level between the T2DM group and the control group. Results of the logistic regression analysis demonstrated the potential associations of serum total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c), and dietary n-3 polyunsaturated fatty acids (PUFAs) intake with the risk of MCI in subjects with T2DM, but the associations were not observed in control subjects.

Conclusion

The T2DM phenotype might affect the relationship between dietary FA intake, circulating lipids, and cognitive performance. Large prospective cohort studies are needed to uncover the underlying mechanism of how dietary FA intake and serum lipid levels affect cognition in aged subjects with T2DM.

Reactive Thread Spray Mass Spectrometry for Localization of C═C Bonds in Free Fatty Acids: Applications for Obesity Diagnosis

Cellulose thread substrates offer a platform for microsampling and reactive ionization of free fatty acid (FFA) isomers for direct differentiation by mass spectrometry. Ambient corona discharge forms when direct current high voltage is applied to the tiny subfibers on the thread substrate in the presence of a polar spray solvent (MeOH/H2O, 2:1, v/v), facilitating chemical reactions across a C═C bond of unsaturated fatty acids. The process was applied for diagnosis of obesity, which we observed to show better discriminatory power when compared to determinations based on body mass index. Overall, the integrated reactive thread-based platform is capable of (i) microsampling and dry-state, room-temperature storage (>30 days) of the biofluids, (ii) in-capillary liquid/liquid extraction, and (iii) in situ epoxidation reactions to locate the C═C bond position in unsaturated fatty acids via reactions with reactive oxygen species present in ambient corona discharge. The study showcased the ability to correctly characterize FFAs, including degree of unsaturation, and the determination of their relative concentrations in clinical biofluid samples.

Clinical lipidomics: realizing the potential of lipid profiling

Dysregulation of lipid metabolism plays a major role in the etiology and sequelae of inflammatory disorders, cardiometabolic and neurological diseases, and several forms of cancer. Recent advances in lipidomic methodology allow comprehensive lipidomic profiling of clinically relevant biological samples, enabling researchers to associate lipid species and metabolic pathways with disease onset and progression. The resulting data serve not only to advance our fundamental knowledge of the underlying disease process but also to develop risk assessment models to assist in the diagnosis and management of disease. Currently, clinical applications of in-depth lipidomic profiling are largely limited to the use of research-based protocols in the analysis of population or clinical sample sets. However, we foresee the development of purpose-built clinical platforms designed for continuous operation and clinical integration-assisting health care providers with disease risk assessment, diagnosis, and monitoring. Herein, we review the current state of clinical lipidomics, including the use of research-based techniques and platforms in the analysis of clinical samples as well as assays already available to clinicians. With a primary focus on MS-based strategies, we examine instrumentation, analysis techniques, statistical models, prospective design of clinical platforms, and the possible pathways toward implementation of clinical lipidomics.

Integrative analysis of metabolomic, genomic, and imaging-based phenotypes identify very-low-density lipoprotein as a potential risk factor for lumbar Modic changes

PURPOSE

Modic changes (MC) on magnetic resonance imaging (MRI) have been associated with the development and severity of low back pain (LBP). The etiology of MC remains elusive, but it has been suggested that altered metabolism may be a risk factor. As such, this study aimed to identify metabolomic biomarkers for MC phenotypes of the lumbar spine via a combined metabolomic-genomic approach.

METHODS

A population cohort of 3,584 southern Chinese underwent lumbar spine MRI. Blood samples were genotyped with single-nucleotide polymorphisms (SNP) arrays (n = 2,482) and serum metabolomics profiling using magnetic resonance spectroscopy (n = 757), covering 130 metabolites representing three molecular windows, were assessed. Genome-wide association studies (GWAS) were performed on each metabolite, to construct polygenic scores for predicting metabolite levels in subjects who had GWAS but not metabolomic data. Associations between predicted metabolite levels and MC phenotypes were assessed using linear/logistic regression and least absolute shrinkage and selection operator (LASSO). Two-sample Mendelian randomization analysis tested for causal relationships between metabolic biomarkers and MC.

RESULTS

20.4% had MC (10.6% type 1, 67.2% type 2, 22.2% mixed types). Significant MC metabolomic biomarkers were mean diameter of very-low-density lipoprotein (VLDL)/low-density lipoprotein (LDL) particles and cholesterol esters/phospholipids in large LDL. Mendelian randomization indicated that decreased VLDL mean diameter may lead to MC.

CONCLUSIONS

This large-scale study is the first to address metabolomics in subject with/without lumbar MC. Causality studies implicate VLDL related to MC, noting a metabolic etiology. Our study substantiates the field of "spino-metabolomics" and illustrates the power of integrating metabolomics-genomics-imaging phenotypes to discover biomarkers for spinal disorders, paving the way for more personalized spine care for patients.

NMR analysis of the correlation of metabolic changes in blood and cerebrospinal fluid in Alzheimer model male and female mice

The development of effective therapies as well as early, molecular diagnosis of Alzheimer's disease is impeded by the lack of understanding of the underlying pathological mechanisms. Metabolomics studies of body fluids as well as brain tissues have shown major changes in metabolic profiles of Alzheimer's patients. However, with analysis performed at the late stages of the disease it is not possible to distinguish causes and consequence. The mouse model APP/PS1 expresses a mutant amyloid precursor protein resulting in early Amyloid β (Aβ) accumulation as well as many resulting physiological changes including changes in metabolic profile and metabolism. Analysis of metabolic profile of cerebrospinal fluid (CSF) and blood of APP/PS1 mouse model can provide information about metabolic changes in these body fluids caused by Aβ accumulation. Using our novel method for analysis of correlation and mathematical ranking of significant correlations between metabolites in CSF and blood, we have explored changes in metabolite correlation and connectedness in APP/PS1 and wild type mice. Metabolites concentration and correlation changes in CSF, blood and across the blood brain barrier determined in this work are affected by the production of amyloid plaque. Metabolite changes observed in the APP/PS1 mouse model are the response to the mutation causing plaque formation, not the cause for the plaque suggesting that they are less relevant in the context of early treatment and prevention then the metabolic changes observed only in humans.

Effects of Psychostimulants and Antipsychotics on Serum Lipids in an Animal Model for Schizophrenia

Schizophrenia (SCZ) treatment is essentially limited to the use of typical or atypical antipsychotic drugs, which suppress the main symptoms of this mental disorder. Metabolic syndrome is often reported in patients with SCZ under long-term drug treatment, but little is known about the alteration of lipid metabolism induced by antipsychotic use. In this study, we evaluated the blood serum lipids of a validated animal model for SCZ (Spontaneously Hypertensive Rat, SHR), and a normal control rat strain (Normotensive Wistar Rat, NWR), after long-term treatment (30 days) with typical haloperidol (HAL) or atypical clozapine (CLZ) antipsychotics. Moreover, psychostimulants, amphetamine (AMPH) or lisdexamfetamine (LSDX), were administered to NWR animals aiming to mimic the human first episode of psychosis, and the effects on serum lipids were also evaluated. Discrepancies in lipids between SHR and NWR animals, which included increased total lipids and decreased phospholipids in SHR compared with NWR, were similar to the differences previously reported for SCZ patients relative to healthy controls. Administration of psychostimulants in NWR decreased omega-3, which was also decreased in the first episode of psychosis of SCZ. Moreover, choline glycerophospholipids allowed us to distinguish the effects of CLZ in SHR. Thus, changes in the lipid metabolism in SHR seem to be reversed by the long-term treatment with the atypical antipsychotic CLZ, which was under the same condition described to reverse the SCZ-like endophenotypes of this validated animal model for SCZ. These data open new insights for understanding the potential influence of the treatment with typical or atypical antipsychotics on circulating lipids. This may represent an outcome effect from metabolic pathways that regulate lipids synthesis and breakdown, which may be reflecting a cell lipids dysfunction in SCZ.

1H-NMR metabolomics reveals a multitarget action of Crithmum maritimum ethyl acetate extract in inhibiting hepatocellular carcinoma cell growth

Hepatocellular carcinoma (HCC) is nowadays the sixth cause of tumour-related deceases worldwide, estimated to become the third in Western countries by 2030. New drugs for HCC treatment still have many adverse effects. Several lines of evidence indicate that plant metabolites offer concrete opportunities for developing new therapeutic strategies for many diseases, including cancer. We previously reported that ethyl acetate extract of a spontaneous edible plant harvested in Apulia, Crithmum maritimum, significantly inhibited cell growth in HCC cells. By ¹H-NMR spectroscopy, here we show that Crithmum maritimum ethyl acetate extract counteracts the Warburg effect, by reducing intracellular lactate, inhibits protein anabolism, by decreasing amino acid level, and affects membrane biosynthesis by lowering choline and phosphocholine. Also, we observed an effect on lipid homeostasis, with a reduction in triglycerides, cholesterol, monounsaturated fatty acids (MUFA), and diunsaturated fatty acids (DUFA), and an increase in polyunsaturated fatty acids (PUFA). Taken together, these data demonstrate that Crithmum maritimum-induced cytostasis is exerted through a multi-effect action, targeting key metabolic processes in HCC cells. Overall, our findings highlight the role of Crithmum maritimum as a promising tool for the prevention and the improvement of the therapeutic options for HCC and other types of tumours.

The role of peripheral fatty acids as biomarkers for Alzheimer's disease and brain inflammation

Alzheimer's disease (AD) is a complex and heterogeneous neurodegenerative disease. A wide range of techniques have been proposed to facilitate early diagnosis of AD, including biomarkers from the cerebrospinal fluid and blood. Although phosphorylated tau and amyloid beta are amongst the most promising biomarkers of AD, other peripheral biomarkers have been identified and in this review we synthesize the current knowledge on circulating fatty acids. Fatty acids are involved in different biological process including neurotransmission and inflammation. Interestingly, some fatty acids appear to be modulated during disease progression, including long chain saturated fatty acids, and polyunsaturated fatty acids, such as docosahexaenoic acid . However, discrepant results have been reported in the literature and there is the need for further validation and method standardization. Nonetheless, our literature review suggests that fatty acid analyses could potentially provide a valuable source of data to further inform the pathology and progression of AD.

Urine Untargeted Metabolomic Profiling Is Associated with the Dietary Pattern of Successful Aging among Malaysian Elderly

Food intake biomarkers (FIBs) can reflect the intake of specific foods or dietary patterns (DP). DP for successful aging (SA) has been widely studied. However, the relationship between SA and DP characterized by FIBs still needs further exploration as the candidate markers are scarce. Thus, 1H-nuclear magnetic resonance (¹H-NMR)-based urine metabolomics profiling was conducted to identify potential metabolites which can act as specific markers representing DP for SA. Urine sample of nine subjects from each three aging groups, SA, usual aging (UA), and mild cognitive impairment (MCI), were analyzed using the ¹H-NMR metabolomic approach. Principal components analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) were applied. The association between SA urinary metabolites and its DP was assessed using the Pearson’s correlation analysis. The urine of SA subjects was characterized by the greater excretion of citrate, taurine, hypotaurine, serotonin, and melatonin as compared to UA and MCI. These urinary metabolites were associated with alteration in “taurine and hypotaurine metabolism” and “tryptophan metabolism” in SA elderly. Urinary serotonin (r = 0.48, p < 0.05) and melatonin (r = 0.47, p < 0.05) were associated with oat intake. These findings demonstrate that a metabolomic approach may be useful for correlating DP with SA urinary metabolites and for further understanding of SA development.

Metabolomics markers in Neurology: current knowledge and future perspectives for therapeutic targeting

INTRODUCTION

Metabolomics is an emerging approach providing new insights into the metabolic changes and underlying mechanisms involved in the pathogenesis of neurological disorders.

AREAS COVERED

Here, the authors present an overview of the current knowledge of metabolic profiling (metabolomics) to provide critical insight on the role of biochemical markers and metabolic alterations in neurological diseases.

EXPERT OPINION

Elucidation of characteristic metabolic alterations in neurological disorders is crucial for a better understanding of their pathogenesis, and for identifying potential biomarkers and drug targets. Nevertheless, discrepancies in diagnostic criteria, sample handling protocols, and analytical methods still affect the generalizability of current study results.

Circulating Fatty Acids and Risk of Coronary Heart Disease and Stroke: Individual Participant Data Meta-Analysis in Up to 16 126 Participants

Background We aimed at investigating the association of circulating fatty acids with coronary heart disease (CHD) and stroke risk. Methods and Results We conducted an individual-participant data meta-analysis of 5 UK-based cohorts and 1 matched case-control study. Fatty acids (ie, omega-3 docosahexaenoic acid, omega-6 linoleic acid, monounsaturated and saturated fatty acids) were measured at baseline using an automated high-throughput serum nuclear magnetic resonance metabolomics platform. Data from 3022 incident CHD cases (13 104 controls) and 1606 incident stroke cases (13 369 controls) were included. Logistic regression was used to model the relation between fatty acids and odds of CHD and stroke, adjusting for demographic and lifestyle variables only (ie, minimally adjusted model) or with further adjustment for other fatty acids (ie, fully adjusted model). Although circulating docosahexaenoic acid, but not linoleic acid, was related to lower CHD risk in the fully adjusted model (odds ratio, 0.85; 95% CI, 0.76-0.95 per standard unit of docosahexaenoic acid), there was evidence of high between-study heterogeneity and effect modification by study design. Stroke risk was consistently lower with increasing circulating linoleic acid (odds ratio for fully adjusted model, 0.82; 95% CI, 0.75-0.90). Circulating monounsaturated fatty acids were associated with higher CHD risk across all models and with stroke risk in the fully adjusted model (odds ratio, 1.22; 95% CI, 1.03-1.44). Saturated fatty acids were not related to increased CHD risk in the fully adjusted model (odds ratio, 0.94; 95% CI, 0.82-1.09), or stroke risk. Conclusions We found consistent evidence that linoleic acid was associated with decreased risk of stroke and that monounsaturated fatty acids were associated with increased risk of CHD. The different pattern between CHD and stroke in terms of fatty acids risk profile suggests future studies should be cautious about using composite events. Different study designs are needed to assess which, if any, of the associations observed is causal.

Title: Human Serum/Plasma Glycoprotein Analysis by 1H-NMR, an Emerging Method of Inflammatory Assessment

Several studies suggest that variations in the concentration of plasma glycoproteins can influence cellular changes in a large number of diseases. In recent years, proton nuclear magnetic resonance (1H-NMR) has played a major role as an analytical tool for serum and plasma samples. In recent years, there is an increasing interest in the characterization of glycoproteins through 1H-NMR in order to search for reliable and robust biomarkers of disease. The objective of this review was to examine the existing studies in the literature related to the study of glycoproteins from an analytical and clinical point of view. There are currently several techniques to characterize circulating glycoproteins in serum or plasma, but in this review, we focus on 1H-NMR due to its great robustness and recent interest in its translation to the clinical setting. In fact, there is already a marker in H-NMR representing the acetyl groups of the glycoproteins, GlycA, which has been increasingly studied in clinical studies. A broad search of the literature was performed showing a general consensus that GlycA is a robust marker of systemic inflammation. The results also suggested that GlycA better captures systemic inflammation even more than C-reactive protein (CRP), a widely used classical inflammatory marker. The applications reviewed here demonstrated that GlycA was potentially a key biomarker in a wide range of diseases such as cancer, metabolic diseases, cardiovascular risk, and chronic inflammatory diseases among others. The profiling of glycoproteins through 1H-NMR launches an encouraging new paradigm for its future incorporation in clinical diagnosis.

High-resolution metabolomic profiling of Alzheimer's disease in plasma

Background

Alzheimer’s disease (AD) is a complex neurological disorder with contributions from genetic and environmental factors. High‐resolution metabolomics (HRM) has the potential to identify novel endogenous and environmental factors involved in AD. Previous metabolomics studies have identified circulating metabolites linked to AD, but lack of replication and inconsistent diagnostic algorithms have hindered the generalizability of these findings. Here we applied HRM to identify plasma metabolic and environmental factors associated with AD in two study samples, with cerebrospinal fluid (CSF) biomarkers of AD incorporated to achieve high diagnostic accuracy.

Methods

Liquid chromatography‐mass spectrometry (LC–MS)‐based HRM was used to identify plasma and CSF metabolites associated with AD diagnosis and CSF AD biomarkers in two studies of prevalent AD (Study 1: 43 AD cases, 45 mild cognitive impairment [MCI] cases, 41 controls; Study 2: 50 AD cases, 18 controls). AD‐associated metabolites were identified using a metabolome‐wide association study (MWAS) framework.

Results

An MWAS meta‐analysis identified three non‐medication AD‐associated metabolites in plasma, including elevated levels of glutamine and an unknown halogenated compound and lower levels of piperine, a dietary alkaloid. The non‐medication metabolites were correlated with CSF AD biomarkers, and glutamine and the unknown halogenated compound were also detected in CSF. Furthermore, in Study 1, the unknown compound and piperine were altered in MCI patients in the same direction as AD dementia.

Conclusions

In plasma, AD was reproducibly associated with elevated levels of glutamine and a halogen‐containing compound and reduced levels of piperine. These findings provide further evidence that exposures and behavior may modify AD risks.

Total liver phosphatidylcholine content associates with non-alcoholic steatohepatitis and glycine N-methyltransferase expression

BACKGROUND & AIMS

Alterations in liver phosphatidylcholine (PC) metabolism have been implicated in the pathogenesis of non-alcoholic fatty liver disease (NAFLD). Although genetic variation in the phosphatidylethanolamine N-methyltransferase (PEMT) enzyme synthesizing PC has been associated with disease, the functional mechanism linking PC metabolism to the pathogenesis of non-alcoholic steatohepatitis (NASH) remains unclear.

METHODS

Serum PC levels and liver PC contents were measured using proton nuclear magnetic resonance (NMR) spectroscopy in 169 obese individuals [age 46.6 ± 10 (mean ± SD) years, BMI 43.3 ± 6 kg/m² , 53 men and 116 women] with histological assessment of NAFLD; 106 of these had a distinct liver phenotype. All subjects were genotyped for PEMT rs7946 and liver mRNA expression of PEMT and glycine N-methyltransferase (GNMT) was analysed.

RESULTS

Liver PC content was lower in those with NASH (P = 1.8 x 10^-6 ) while serum PC levels did not differ between individuals with NASH and normal liver (P = 0.591). Interestingly, serum and liver PC did not correlate (r_s  = -0.047, P = 0.557). Serum PC and serum cholesterol levels correlated strongly (r_s  = 0.866, P = 7.1 x 10^-49 ), while liver PC content did not correlate with serum cholesterol (r_s  = 0.065, P = 0.413). Neither PEMT V175M genotype nor PEMT expression explained the association between liver PC content and NASH. Instead, liver GNMT mRNA expression was decreased in those with NASH (P = 3.8 x 10^-4 ) and correlated with liver PC content (r_s  = 0.265, P = 0.001).

CONCLUSIONS

Decreased liver PC content in individuals with the NASH is independent of PEMT V175M genotype and could be partly linked to decreased GNMT expression.

Evaluation of sample preparation protocols for quantitative NMR-based metabolomics

INTRODUCTION

Quantification of metabolites in biological fluids and tissues by NMR spectroscopy is challenged by the presence of abundant macromolecules and lipoproteins in samples, which give broad signals in the NMR spectra. To improve the quality of NMR spectra the different protocols for protein and lipid removal from the sample are used.

OBJECTIVES

This work is aimed at the evaluation of the effectiveness of various methods of purification of blood serum from proteins and lipids for ¹H NMR metabolomic profiling.

METHODS

The advantages and limitations of different methods of the sample preparation for NMR-based quantitative metabolomics have been compared, including ultrafiltration, methanol and ethanol extractions with and without additional lipid removal, and methanol-chloroform extraction.

RESULTS

The concentrations of 30 abundant metabolites extracted from human blood serum have been measured. It is found that ultrafiltration provides the best lipid removal, but causes significant and inhomogeneous metabolite losses. Ethanol and methanol extractions demonstrate similar performance with the minimal metabolite losses, and are ideal for fluids and tissues with low lipid content. The additional purification of alcohol extracts from lipids allows for the significant improving of NMR spectra, but causes additional metabolite losses.

CONCLUSIONS

The methanol-chloroform extraction seems to be an optimal method for tissues with the high lipid content, providing a satisfactory lipid removal and low metabolite losses. The ultrafiltration leads to large losses of metabolites (up to 60%) and for this reason is not suitable for quantitative analysis.

Blood-based molecular signature of Alzheimer's disease via spectroscopy and metabolomics

OBJECTIVES

With over 35 million cases worldwide, Alzheimer's disease (AD) represents the main cause of dementia. The differentiation of AD from other types of dementia is challenging and its early diagnosis is complicated. The established biomarkers are not only based on the invasive collection of cerebrospinal fluid, but also lack sufficient sensitivity and specificity. Therefore, much current effort is aimed at the identification of new biomarkers of AD in peripheral blood.

DESIGN AND METHODS

We focused on blood-based analyses using chiroptical spectroscopy (Raman optical activity, electronic circular dichroism) supplemented with conventional vibrational spectroscopy (infrared, Raman) and metabolomics (high-performance liquid chromatography with a high-resolution mass detection).

RESULTS

This unique approach enabled us to identify the spectral pattern of AD and variations in metabolite levels. Subsequent linear discriminant analysis of the spectral data resulted in differentiation between the AD patients and control subjects.

CONCLUSIONS

It may be stated that this less invasive approach has strong potential for the identification of disease-related changes within essential plasmatic biomolecules and metabolites.

Cognition, psychosis risk and metabolic measures in two adolescent birth cohorts

BACKGROUND

Psychoses, especially schizophrenia, are often preceded by cognitive deficits and psychosis risk states. Altered metabolic profiles have been found in schizophrenia. However, the associations between metabolic profiles and poorer cognitive performance and psychosis risk in the population remain to be determined.

METHODS

Detailed molecular profiles were measured for up to 8976 individuals from two general population-based prospective birth cohorts: the Northern Finland Birth Cohort 1986 (NFBC 1986) and the Avon Longitudinal Study of Parents and Children (ALSPAC). A high-throughput nuclear magnetic resonance spectroscopy platform was used to quantify 70 metabolic measures at age 15-16 years in the NFBC 1986 and at ages 15 and 17 years in ALSPAC. Psychosis risk was assessed using the PROD-screen questionnaire at age 15-16 years in the NFBC 1986 or the psychotic-like symptoms assessment at age 17 years in ALSPAC. Cognitive measures included academic performance at age 16 years in both cohorts and general intelligence and executive function in ALSPAC. Logistic regression measured cross-sectional and longitudinal associations between metabolic measures and psychosis risk and cognitive performance, controlling for important covariates.

RESULTS

Seven metabolic measures, primarily fatty acid (FA) measures, showed cross-sectional associations with general cognitive performance, four across both cohorts (low density lipoprotein diameter, monounsaturated FA ratio, omega-3 ratio and docosahexaenoic acid ratio), even after controlling for important mental and physical health covariates. Psychosis risk showed minimal metabolic associations.

CONCLUSIONS

FA ratios may be important in marking risk for cognitive deficits in adolescence. Further research is needed to clarify whether these biomarkers could be causal and thereby possible targets for intervention.

Fingerprinting Acute Digestive Diseases by Untargeted NMR Based Metabolomics

Precision medicine may significantly contribute to rapid disease diagnosis and targeted therapy, but relies on the availability of detailed, subject specific, clinical information. Proton nuclear magnetic resonance (¹H–NMR) spectroscopy of body fluids can extract individual metabolic fingerprints. Herein, we studied 64 patients admitted to the Florence main hospital emergency room with severe abdominal pain. A blood sample was drawn from each patient at admission, and the corresponding sera underwent ¹H–NMR metabolomics fingerprinting. Unsupervised Principal Component Analysis (PCA) analysis showed a significant discrimination between a group of patients with symptoms of upper abdominal pain and a second group consisting of patients with diffuse abdominal/intestinal pain. Prompted by this observation, supervised statistical analysis (Orthogonal Partial Least Squares–Discriminant Analysis (OPLS-DA)) showed a very good discrimination (>90%) between the two groups of symptoms. This is a surprising finding, given that neither of the two symptoms points directly to a specific disease among those studied here. Actually herein, upper abdominal pain may result from either symptomatic gallstones, cholecystitis, or pancreatitis, while diffuse abdominal/intestinal pain may result from either intestinal ischemia, strangulated obstruction, or mechanical obstruction. Although limited by the small number of samples from each of these six conditions, discrimination of these diseases was attempted. In the first symptom group, >70% discrimination accuracy was obtained among symptomatic gallstones, pancreatitis, and cholecystitis, while for the second symptom group >85% classification accuracy was obtained for intestinal ischemia, strangulated obstruction, and mechanical obstruction. No single metabolite stands up as a possible biomarker for any of these diseases, while the contribution of the whole ¹H–NMR serum fingerprint seems to be a promising candidate, to be confirmed on larger cohorts, as a first-line discriminator for these diseases.

Next-generation biomarker discovery in Alzheimer's disease using metabolomics - from animal to human studies

Alzheimer's disease (AD) is a complex disease driven mainly by neuronal loss due to accumulation of intracellular neurofibrillary tangles and amyloid β aggregates in the brain. The diagnosis of AD currently relies on clinical symptoms while the disease can only be confirmed at autopsy. The few available biomarkers allowing for diagnosis are typically detected many years after the onset of the disease. New diagnostic approaches, particularly in easily-accessible biofluids, are essential. By providing an exhaustive information of the phenotype, metabolomics is an ideal approach for identification of new biomarkers. This review investigates the current position of metabolomics in the field of AD research, focusing on animal and human studies, and discusses the improvements carried out over the past decade.

Microbiome-metabolome signatures in mice genetically prone to develop dementia, fed a normal or fatty diet

Cognitive decline, obesity and gut dysfunction or microbial dysbiosis occur in association. Our aim was to identify gut microbiota-metabolomics signatures preceding dementia in genetically prone (3xtg) mice, with and without superimposed high-fat diet. We examined the composition and diversity of their gut microbiota, and serum and faecal metabolites. 3xtg mice showed brain hypometabolism typical of pre-demented stage, and lacked the physiological bacterial diversity between caecum and colon seen in controls. Cluster analyses revealed distinct profiles of microbiota, and serum and fecal metabolome across groups. Elevation in Firmicutes-to-Bacteroidetes abundance, and exclusive presence of Turicibacteraceae, Christensenellaceae, Anaeroplasmataceae and Ruminococcaceae, and lack of Bifidobacteriaceae, were also observed. Metabolome analysis revealed a deficiency in unsaturated fatty acids and choline, and an overabundance in ketone bodies, lactate, amino acids, TMA and TMAO in 3xtg mice, with additive effects of high-fat diet. These metabolic alterations were correlated with high prevalence of Enterococcaceae, Staphylococcus, Roseburia, Coprobacillus and Dorea, and low prevalence of S24.7, rc4.4 and Bifidobacterium, which in turn related to cognitive impairment and cerebral hypometabolism. Our results indicate an effect of transgenic background on gut microbiome-metabolome, enhanced by high-fat diet. The resulting profiles may precede overt cognitive impairment, suggesting their predictive or risk-stratifying potential.

LipSpin: A New Bioinformatics Tool for Quantitative 1H NMR Lipid Profiling

The structural similarity among lipid species and the low sensitivity and spectral resolution of nuclear magnetic resonance (NMR) have traditionally hampered the routine use of ¹H NMR lipid profiling of complex biological samples in metabolomics, which remains mostly manual and lacks freely available bioinformatics tools. However, ¹H NMR lipid profiling provides fast quantitative screening of major lipid classes (fatty acids, glycerolipids, phospholipids, and sterols) and some individual species and has been used in several clinical and nutritional studies, leading to improved risk prediction models. In this Article, we present LipSpin, a free and open-source bioinformatics tool for quantitative ¹H NMR lipid profiling. LipSpin implements a constrained line shape fitting algorithm based on voigt profiles and spectral templates from spectra of lipid standards, which automates the analysis of severely overlapped spectral regions and lipid signals with complex coupling patterns. LipSpin provides the most detailed quantification of fatty acid families and choline phospholipids in serum lipid samples by ¹H NMR to date. Moreover, analytical and clinical results using LipSpin quantifications conform with other techniques commonly used for lipid analysis.

Qualitative and Quantitative NMR Approaches in Blood Serum Lipidomics

Nuclear magnetic resonance (NMR) spectroscopy in combination with chemometrics can be applied in the analysis of complex biological samples in many ways. For example, we can analyze lipids, elucidate their structures, determine their nutritional values, and determine their distribution in blood serum. As lipids are not soluble in water, they are transported in blood as lipid-rich self-assembled particles, divided into different density assemblies from high- to very-low-density lipoproteins (HDL to VLDL), or by combining with serum proteins, such as albumins (human serum albumins (HSA)). Therefore, serum lipids can be analyzed as they are using only a 1:1 (v/v) dilution with a buffer or deuterated water prior to analysis by applying ¹H NMR or ¹H NMR edited-by-diffusion techniques. Alternatively, lipids can be extracted from the serum using liquid partition equilibrium and then analyzed using liquid-state NMR techniques. Our chapter describes protocols that are used for extraction of blood serum lipids and their quantitative ¹H NMR (¹H qNMR) analysis in lipid extracts as well as ¹H NMR edited by diffusion for direct blood serum lipid analysis.

Quantitative Serum Nuclear Magnetic Resonance Metabolomics in Large-Scale Epidemiology: A Primer on -Omic Technologies

Detailed metabolic profiling in large-scale epidemiologic studies has uncovered novel biomarkers for cardiometabolic diseases and clarified the molecular associations of established risk factors. A quantitative metabolomics platform based on nuclear magnetic resonance spectroscopy has found widespread use, already profiling over 400,000 blood samples. Over 200 metabolic measures are quantified per sample; in addition to many biomarkers routinely used in epidemiology, the method simultaneously provides fine-grained lipoprotein subclass profiling and quantification of circulating fatty acids, amino acids, gluconeogenesis-related metabolites, and many other molecules from multiple metabolic pathways. Here we focus on applications of magnetic resonance metabolomics for quantifying circulating biomarkers in large-scale epidemiology. We highlight the molecular characterization of risk factors, use of Mendelian randomization, and the key issues of study design and analyses of metabolic profiling for epidemiology. We also detail how integration of metabolic profiling data with genetics can enhance drug development. We discuss why quantitative metabolic profiling is becoming widespread in epidemiology and biobanking. Although large-scale applications of metabolic profiling are still novel, it seems likely that comprehensive biomarker data will contribute to etiologic understanding of various diseases and abilities to predict disease risks, with the potential to translate into multiple clinical settings.

Chemotherapy-induced gastrointestinal toxicity is associated with changes in serum and urine metabolome and fecal microbiota in male Sprague-Dawley rats

Purpose

Chemotherapy-induced gastrointestinal toxicity (CIGT) is a complex process that involves multiple pathophysiological mechanisms. We have previously shown that commonly used chemotherapeutics 5-fluorouracil, oxaliplatin, and irinotecan damage the intestinal mucosa and increase intestinal permeability to iohexol. We hypothesized that CIGT is associated with alterations in fecal microbiota and metabolome. Our aim was to characterize these changes and examine how they relate to the severity of CIGT.

Methods

A total of 48 male Sprague–Dawley rats were injected intraperitoneally either with 5-fluorouracil (150 mg/kg), oxaliplatin (15 mg/kg), or irinotecan (200 mg/kg). Body weight change was measured daily after drug administration and the animals were euthanized after 72 h. Blood, urine, and fecal samples were collected at baseline and at the end of the experiment. The changes in the composition of fecal microbiota were analyzed with 16S rRNA gene sequencing. Metabolic changes in serum and urine metabolome were measured with 1 mm proton nuclear magnetic resonance (¹H-NMR).

Results

Irinotecan increased the relative abundance of Fusobacteria and Proteobacteria, while 5-FU and oxaliplatin caused only minor changes in the composition of fecal microbiota. All chemotherapeutics increased the levels of serum fatty acids and N(CH₃)₃ moieties and decreased the levels of Krebs cycle metabolites and free amino acids.

Conclusions

Chemotherapeutic drugs, 5-fluorouracil, oxaliplatin, and irinotecan, induce several microbial and metabolic changes which may play a role in the pathophysiology of CIGT. The observed changes in intestinal permeability, fecal microbiota, and metabolome suggest the activation of inflammatory processes.

Electronic supplementary material

The online version of this article (doi:10.1007/s00280-017-3364-z) contains supplementary material, which is available to authorized users.

Effects of breviscapine on amyloid beta 1-42 induced Alzheimer's disease mice: A HPLC-QTOF-MS based plasma metabonomics study

Herba Erigerontis has long been used to cure apoplexy hemiplegia and precordial pain in China. In addition, the bioactivities of its total flavonoids-breviscapine included inhibiting amyloid beta (Aβ) fibril formation, antioxidation and metal chelating, which are beneficial to treat Alzheimer's disease (AD). Hence, A HPLC-QTOF-MS based plasma metabonomics approach was applied to investigate the neuroprotective effects of breviscapine on intracerebroventricular injection of aggregated Aβ 1-42 induced AD mice for the first time in the study. Ten potential biomarkers were screened out by multivariate statistical analysis, eight of which were further identified as indoleacrylic acid, C16 sphinganine, LPE (22:6), sulfolithocholic acid, LPC (16:0), PA (22:1/0:0), taurodeoxycholic acid, and PC (0:0/18:0). According to their metabolic pathways, it was supposed that breviscapine ameliorated the learning and memory deficits of AD mice predominantly by regulating phospholipids metabolism, elevating serotonin level and lowering cholesterols content in vivo.

Lipidomics, Biomarkers, and Schizophrenia: A Current Perspective

Lipidomics is a lipid-targeted metabolomics approach aiming at comprehensive analysis of lipids in biological systems. Recent technological progresses in mass spectrometry, nuclear magnetic resonance spectroscopy, and chromatography have significantly enhanced the developments and applications of metabolic profiling of lipids in more complex biological samples. As many diseases reveal a notable change in lipid profiles compared with that of healthy people, lipidomics have also been broadly introduced to scientific research on diseases. Exploration of lipid biochemistry by lipidomics approach will not only provide insights into specific roles of lipid molecular species in health and disease, but it will also support the identification of potential biomarkers for establishing preventive or therapeutic approaches for human health. This chapter aims to illustrate how lipidomics can contribute for understanding the biological mechanisms inherent to schizophrenia and why lipids are relevant biomarkers of schizophrenia. The application of lipidomics in clinical studies has the potential to provide new insights into lipid profiling and pathophysiological mechanisms underlying schizophrenia. The future perspectives of lipidomics in mental disorders are also discussed herein.

Quantitative in vivo neurochemical profiling in humans: where are we now?

Proton nuclear magnetic resonance spectroscopy of biofluids has become one of the key techniques for metabolic profiling and phenotyping. This technique has been widely used in a number of epidemiological studies and in a variety of health disorders. However, its utilization in brain disorders is limited due to the blood-brain barrier, which not only protects the brain from unwanted substances in the blood, but also substantially limits the potential of finding biomarkers for neurological disorders in serum. This review article focuses on the potential of localized in vivo proton magnetic resonance spectroscopy (¹H-MRS) for non-invasive neurochemical profiling in the human brain. First, methodological aspects of ¹H-MRS (data acquisition, processing and metabolite quantification) that are essential for reliable non-invasive neurochemical profiling are described. Second, the power of ¹H-MRS-based neurochemical profiling is demonstrated using some examples of its application in neuroscience and neurology. Finally, the authors present their vision and propose necessary steps to establish ¹H-MRS as a method suitable for large-scale neurochemical profiling in epidemiological research.

Plasma Biomarkers for Monitoring Brain Pathophysiology in FMR1 Premutation Carriers

Premutation carriers have a 55–200 CGG expansion in the fragile X mental retardation 1 (FMR1) gene. Currently, 1.5 million individuals are affected in the United States, and carriers are at risk of developing the late-onset neurodegenerative disorder Fragile X-associated tremor ataxia syndrome (FXTAS). Limited efforts have been made to develop new methods for improved early patient monitoring, treatment response, and disease progression. To this end, plasma metabolomic phenotyping was obtained for 23 premutation carriers and 16 age- and sex-matched controls. Three biomarkers, phenylethylamine normalized by either aconitate or isocitrate and oleamide normalized by isocitrate, exhibited excellent model performance. The lower phenylethylamine and oleamide plasma levels in carriers may indicate, respectively, incipient nigrostriatal degeneration and higher incidence of substance abuse, anxiety and sleep disturbances. Higher levels of citrate, isocitrate, aconitate, and lactate may reflect deficits in both bioenergetics and neurotransmitter metabolism (Glu, GABA). This study lays important groundwork by defining the potential utility of plasma metabolic profiling to monitor brain pathophysiology in carriers before and during the progression of FXTAS, treatment efficacy and evaluation of side effects.

Gender differences of peripheral plasma and liver metabolic profiling in APP/PS1 transgenic AD mice

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive cognitive impairment. Currently, there is less knowledge of the involvement of the peripheral biofluid/organ in AD, compared with the central nervous system. In addition, with reported high morbidity in women in particular, it has become very important to explore whether gender difference in the peripheral metabolome is associated with AD. Here, we investigated metabolic responses of both plasma and liver tissues using an APP/PS1 double mutant transgenic mouse model with NMR spectroscopy, as well as analysis from serum biochemistry and histological staining. Fatty acid composition from plasma and liver extracts was analyzed using GC-FID/MS. We found clear gender differences in AD transgenic mice when compared with their wild-type counterparts. Female AD mice displayed more intensive responses, which were highlighted by higher levels of lipids, 3-hydroxybutyrate and nucleotide-related metabolites, together with lower levels of glucose. These observations indicate that AD induces oxidative stress and impairs cellular energy metabolism in peripheral organs. Disturbances in AD male mice were milder with depletion of monounsaturated fatty acids. We also observed a higher activity of delta-6-desaturate and suppressed activity of delta-5-desaturate in female mice, whereas inhibited stearoyl-CoA-desaturase in male mice suggested that AD induced by the double mutant genes results in different fatty acids catabolism depending on gender. Our results provide metabolic clues into the peripheral biofluid/organs involved in AD, and we propose that a gender-specific scheme for AD treatment in men and women may be required.

Quantitative serum nuclear magnetic resonance metabolomics in cardiovascular epidemiology and genetics

Metabolomics is becoming common in epidemiology due to recent developments in quantitative profiling technologies and appealing results from their applications for understanding health and disease. Our team has developed an automated high-throughput serum NMR metabolomics platform that provides quantitative molecular data on 14 lipoprotein subclasses, their lipid concentrations and composition, apolipoprotein A-I and B, multiple cholesterol and triglyceride measures, albumin, various fatty acids as well as on numerous low-molecular-weight metabolites, including amino acids, glycolysis related measures and ketone bodies. The molar concentrations of these measures are obtained from a single serum sample with costs comparable to standard lipid measurements. We have analyzed almost 250 000 samples from around 100 epidemiological cohorts and biobanks and the new international set-up of multiple platforms will allow an annual throughput of more than 250 000 samples. The molecular data have been used to study type 1 and type 2 diabetes etiology as well as to characterize the molecular reflections of the metabolic syndrome, long-term physical activity, diet and lipoprotein metabolism. The results have revealed new biomarkers for early atherosclerosis, type 2 diabetes, diabetic nephropathy, cardiovascular disease and all-cause mortality. We have also combined genomics and metabolomics in diverse studies. We envision that quantitative high-throughput NMR metabolomics will be incorporated as a routine in large biobanks; this would make perfect sense both from the biological research and cost point of view - the standard output of over 200 molecular measures would vastly extend the relevance of the sample collections and make many separate clinical chemistry assays redundant.

Effect of the DGAT1 K232A genotype of dairy cows on the milk metabolome and proteome

Diglyceride O-acyltransferase 1 (DGAT1) is the enzyme that catalyzes the synthesis of triglycerides from diglycerides and acyl-coenzyme A. The DGAT1 K232A polymorphism was previously shown to have a significant influence on bovine milk production characteristics (milk yield, protein content, fat content, and fatty acid composition). The mechanism of this influence has, however, not been elucidated. In this study, metabolomics ((1)H-nuclear magnetic resonance) and proteomics (laser chromatography-tandem mass spectrometry) were applied to determine the serum and lipid metabolite composition and milk fat globule membrane proteome of milk samples from cows with the DGAT1 KK and AA genotypes. The milk samples from cows with the DGAT1 KK genotype contained more stomatin, sphingomyelin, choline, and carnitine, and less citrate, creatine or phosphocreatine, glycerol-phosphocholine, mannose-like sugar, acetyl sugar phosphate, uridine diphosphate (UDP)-related sugar, and orotic acid compared with milk samples from cows with the DGAT1 AA genotype. Based on these results, we propose that the differences between the DGAT1 genotypes may be related to stomatin-sphingomyelin lipid rafts as well as structural (cell membrane) differences in epithelial cells of the mammary gland. In conclusion, our study shows that, in addition to previously described changes in triglyceride composition, cows differing in DGAT1 polymorphism differ in their milk proteome and metabolome, which may help in further understanding the effect of the DGAT1 K232A polymorphism on milk production characteristics.

Lipoprotein subclass metabolism in nonalcoholic steatohepatitis

Nonalcoholic steatohepatitis (NASH) is associated with increased synthesis of triglycerides and cholesterol coupled with increased VLDL synthesis in the liver. In addition, increased cholesterol content in the liver associates with NASH. Here we study the association of lipoprotein subclass metabolism with NASH. To this aim, liver biopsies from 116 morbidly obese individuals [age 47.3 ± 8.7 (mean ± SD) years, BMI 45.1 ± 6.1 kg/m², 39 men and 77 women] were used for histological assessment. Proton NMR spectroscopy was used to measure lipid concentrations of 14 lipoprotein subclasses in native serum samples at baseline and after obesity surgery. We observed that total lipid concentration of VLDL and LDL subclasses, but not HDL subclasses, associated with NASH [false discovery rate (FDR) < 0.1]. More specifically, total lipid and cholesterol concentration of VLDL and LDL subclasses associated with inflammation, fibrosis, and cell injury (FDR < 0.1), independent of steatosis. Cholesterol concentration of all VLDL subclasses also correlated with total and free cholesterol content in the liver. All NASH-related changes in lipoprotein subclasses were reversed by obesity surgery. High total lipid and cholesterol concentration of serum VLDL and LDL subclasses are linked to cholesterol accumulation in the liver and to liver cell injury in NASH.

NMR measurement of LDL particle number using the Vantera Clinical Analyzer

BACKGROUND

The Vantera Clinical Analyzer was developed to enable fully-automated, high-throughput nuclear magnetic resonance (NMR) spectroscopy measurements in a clinical laboratory setting. NMR-measured low-density lipoprotein particle number (LDL-P) has been shown to be more strongly associated with cardiovascular disease outcomes than LDL cholesterol (LDL-C) in individuals for whom these alternate measures of LDL are discordant.

OBJECTIVE

The aim of this study was to assess the analytical performance of the LDL-P assay on the Vantera Clinical Analyzer as per Clinical Laboratory Standards Institute (CLSI) guidelines.

RESULTS

Sensitivity and linearity were established within the range of 300-3500 nmol/L. For serum pools containing low, medium and high levels of LDL-P, the inter-assay, intra-assay precision and repeatability gave coefficients of variation (CVs) between 2.6 and 5.8%. The reference interval was determined to be 457-2282 nmol/L and the assay was compatible with multiple specimen collection tubes. Of 30 substances tested, only 2 exhibited the potential for assay interference. Moreover, the LDL-P results from samples run on two NMR platforms, Vantera Clinical Analyzer and NMR Profiler, showed excellent correlation (R(2)=0.96).

CONCLUSIONS

The performance characteristics suggest that the LDL-P assay is suitable for routine testing in the clinical laboratory on the Vantera Clinical Analyzer, the first automated NMR platform that supports NMR-based clinical assays.

Metabolomics of Ramadan fasting: an opportunity for the controlled study of physiological responses to food intake

High-throughput screening techniques that analyze the metabolic endpoints of biological processes can identify the contributions of genetic predisposition and environmental factors to the development of common diseases. Studies applying controlled physiological challenges can reveal dysregulation in metabolic responses that may be predictive for or associated with these diseases. However, large-scale epidemiological studies with well controlled physiological challenge conditions, such as extended fasting periods and defined food intake, pose logistic challenges. Culturally and religiously motivated behavioral patterns of life style changes provide a natural setting that can be used to enroll a large number of study volunteers. Here we report a proof of principle study conducted within a Muslim community, showing that a metabolomics study during the Holy Month of Ramadan can provide a unique opportunity to explore the pre-prandial and postprandial response of human metabolism to nutritional challenges. Up to five blood samples were obtained from eleven healthy male volunteers, taken directly before and two hours after consumption of a controlled meal in the evening on days 7 and 26 of Ramadan, and after an over-night fast several weeks after Ramadan. The observed increases in glucose, insulin and lactate levels at the postprandial time point confirm the expected physiological response to food intake. Targeted metabolomics further revealed significant and physiologically plausible responses to food intake by an increase in bile acid and amino acid levels and a decrease in long-chain acyl-carnitine and polyamine levels. A decrease in the concentrations of a number of phospholipids between samples taken on days 7 and 26 of Ramadan shows that the long-term response to extended fasting may differ from the response to short-term fasting. The present study design is scalable to larger populations and may be extended to the study of the metabolic response in defined patient groups such as individuals with type 2 diabetes.

Advances in high-field magnetic resonance spectroscopy in Alzheimer's disease

Alzheimer's disease (AD) affects several important molecules in brain metabolism. The resulting neurochemical changes can be quantified non-invasively in localized brain regions using in vivo single-voxel proton magnetic resonance spectroscopy (SV 1H MRS). Although the often heralded diagnostic potential of MRS in AD largely remains unfulfilled, more recent use of high magnetic fields has led to significantly improved signal-to-noise ratios and spectral resolutions, thereby allowing clinical applications with increased measurement reliability. The present article provides a comprehensive review of SV 1H MRS studies on AD at high magnetic fields (3.0 Tesla and above). This review suggests that patterned regional differences and longitudinal alterations in several neurometabolites are associated with clinically established AD. Changes in multiple metabolites are identifiable even at early stages of AD development. By combining information of neurochemicals in different brain regions revealing either pathological or compensatory changes, high field MRS can be evaluated in AD diagnosis and in the detection of treatment effects. To achieve this, standardization of data acquisition and analytical approaches is needed.

Plasma metabolite profiles of Alzheimer's disease and mild cognitive impairment

Previous studies have demonstrated altered metabolites in samples of Alzheimer's disease (AD) patients. However, the sample size from many of them is relatively small and the metabolites are relatively limited. Here we applied a comprehensive platform using ultraperformance liquid chromatography-time-of-flight mass spectrometry and gas chromatography-time-of-flight mass spectrometry to analyze plasma samples from AD patients, amnestic mild cognitive impairment (aMCI) patients, and normal controls. A biomarker panel consisting of six plasma metabolites (arachidonic acid, N,N-dimethylglycine, thymine, glutamine, glutamic acid, and cytidine) was identified to discriminate AD patients from normal control. Another panel of five plasma metabolites (thymine, arachidonic acid, 2-aminoadipic acid, N,N-dimethylglycine, and 5,8-tetradecadienoic acid) was able to differentiate aMCI patients from control subjects. Both biomarker panels had good agreements with clinical diagnosis. The 2 panels of metabolite markers were all involved in fatty acid metabolism, one-carbon metabolism, amino acid metabolism, and nucleic acid metabolism. Additionally, no altered metabolites were found among the patients at different stages, as well as among those on anticholinesterase medication and those without anticholinesterase medication. These findings provide a comprehensive global plasma metabolite profiling and may contribute to making early diagnosis as well as understanding the pathogenic mechanism of AD and aMCI.

Association between serum fatty acids and lipoprotein subclass profile in healthy young adults: exploring common genetic and environmental factors

OBJECTIVE

Little is known about the associations of serum fatty acids with lipoprotein profile and the underlying genetic and environmental etiology of these relationships. We aimed to analyze the phenotypic association of serum n-6 and n-3 polyunsaturated (PUFAs), monounsaturated (MUFAs) and saturated (SFAs) fatty acids (relative proportion to total fatty acids) with lipids and lipoproteins, and to quantify common genetic and environmental factors determining their covariation.

METHODS

Two cohorts of healthy Finnish twins were assessed in young adulthood. Data were available for 1269 individual twins including 561 complete pairs. Serum metabolites were measured by nuclear magnetic resonance spectroscopy. Bivariate quantitative genetic models were used to decompose the phenotypic covariance between the pairs of traits into genetic and environmental components.

RESULTS

Among the strongest correlations observed, serum total n-6 PUFAs and linoleic acid were inversely (max. r=-0.65) and MUFAs positively (max. r=0.63) correlated with triglycerides and very low-density lipoprotein (VLDL) particle concentration, particularly with large VLDL (for n-6 PUFAs) and medium VLDL (for MUFAs). Genetic factors significantly contributed to their covariance with bivariate heritability estimates ranging from 44% to 56% for n-6 PUFAs and 58% to 66% for MUFAs. Genetic correlations with lipid traits were moderate to high (max. rA=-0.59 and 0.70 for n-6 PUFAs and MUFAs, respectively). Statistically significant, but substantially weaker phenotypic correlations of total n-3 PUFAs, docosahexaenoic acid (DHA) and SFAs with lipoprotein profile were not decomposed into their genetic and environmental components.

CONCLUSION

Shared genetic factors are important in explaining why higher concentrations of serum n-6 PUFAs and lower concentrations of serum MUFAs strongly associate with lower triglyceride and VLDL particle concentrations.

Glycerol and fatty acids in serum predict the development of hyperglycemia and type 2 diabetes in Finnish men

OBJECTIVE

We investigated the association of fasting serum glycerol and fatty acids (FAs) as predictors for worsening of hyperglycemia and incident type 2 diabetes.

RESEARCH DESIGN AND METHODS

Cross-sectional and longitudinal analyses of the population-based METabolic Syndrome in Men (METSIM) Study included 9,398 Finnish men (mean age 57 ± 7 years). At baseline, levels of serum glycerol, free FAs (FFAs), and serum FA profile, relative to total FAs, were measured with proton nuclear magnetic resonance spectroscopy.

RESULTS

At baseline, levels of glycerol, FFAs, monounsaturated FAs, saturated FAs, and monounsaturated n-7 and -9 FAs, relative to total FAs, were increased in categories of fasting and 2-h hyperglycemia, whereas the levels of n-3 and n-6 FAs, relative to total FAs, decreased (N = 9,398). Among 4,335 men with 4.5-year follow-up data available, 276 developed type 2 diabetes. Elevated levels of glycerol, FFAs, monounsaturated FAs, and saturated and monounsaturated n-7 and -9 FAs, relative to total FAs, predicted worsening of hyperglycemia and development of incident type 2 diabetes after adjustment for confounding factors. n-6 FAs, mainly linoleic acid (LA), relative to total FAs, were associated with reduced risk for the worsening of hyperglycemia and conversion to type 2 diabetes.

CONCLUSIONS

Our large population-based study shows that fasting serum levels of glycerol, FFAs, monounsaturated FAs, saturated FAs, and n-7 and -9 FAs are biomarkers for an increased risk of development of hyperglycemia and type 2 diabetes, whereas high levels of serum n-6 FAs, reflecting dietary intake of LA, were associated with reduced risk for hyperglycemia and type 2 diabetes.

Identification of biomarkers for apoptosis in cancer cell lines using metabolomics: tools for individualized medicine

BACKGROUND

Metabolomics is a versatile unbiased method to search for biomarkers of human disease. In particular, one approach in cancer therapy is to promote apoptosis in tumour cells; this could be improved with specific biomarkers of apoptosis for monitoring treatment. We recently observed specific metabolic patterns in apoptotic cell lines; however, in that study, apoptosis was only induced with one pro-apoptotic agent, staurosporine.

OBJECTIVE

The aim of this study was to find novel biomarkers of apoptosis by verifying our previous findings using two further pro-apoptotic agents, 5-fluorouracil and etoposide, that are commonly used in anticancer treatment.

METHODS

Metabolic parameters were assessed in HepG2 and HEK293 cells using the newborn screening assay adapted for cell culture approaches, quantifying the levels of amino acids and acylcarnitines with mass spectrometry.

RESULTS

We were able to identify apoptosis-specific changes in the metabolite profile. Moreover, the amino acids alanine and glutamate were both significantly up-regulated in apoptotic HepG2 and HEK293 cells irrespective of the apoptosis inducer.

CONCLUSION

Our observations clearly indicate the potential of metabolomics in detecting metabolic biomarkers applicable in theranostics and for monitoring drug efficacy.