Quantitative Metabolomics and Lipoprotein Analysis of PDAC Patients Suggests Serum Marker Categories for Pancreatic Function, Pancreatectomy, Cancer Metabolism, and Systemic Disturbances

Pancreatic ductal adenocarcinoma (PDAC) is difficult to diagnose in the early stages and lacks reliable biomarkers. The scope of this project was to establish quantitative nuclear magnetic resonance (NMR) spectroscopy to comprehensively study blood serum alterations in PDAC patients. Serum samples from 34 PDAC patients obtained before and after pancreatectomy as well as 83 age- and sex-matched control samples from healthy donors were analyzed with in vitro diagnostics research (IVDr) proton NMR spectroscopy at 600 MHz. Uni- and multivariate statistics were applied to identify significant biofluid alterations. We identified 29 significantly changed metabolites and 98 lipoproteins when comparing serum from healthy controls with those of PDAC patients. The most prominent features were assigned to (i) markers of pancreatic function (e.g., glucose and blood triglycerides), (ii) markers related to surgery (e.g., ketone bodies and blood cholesterols), (iii) PDAC-associated markers (e.g., amino acids and creatine), and (iv) markers for systemic disturbances in PDAC (e.g., gut metabolites DMG, TMAO, DMSO2, and liver lipoproteins). Quantitative serum NMR spectroscopy is suited as a diagnostic tool to investigate PDAC. Remarkably, 2-hydroxybutyrate (2-HB) as a previously suggested marker for insulin resistance was found in extraordinarily high levels only after pancreatectomy, suggesting this metabolite is the strongest marker for pancreatic loss of function.

Validation of a Microwave-Assisted Derivatization Gas Chromatography-Mass Spectrometry Method for the Quantification of 2-Hydroxybutyrate in Human Serum as an Early Marker of Diabetes Mellitus

Circulating levels of 2-hydroxybutyrate (2HB) are highly related to glycemic status in different metabolomic studies. According to recent evidence, 2HB is an early biomarker of the future development of dysglycemia and type 2 diabetes mellitus and may be causally related to the progression of normal subjects to impaired fasting glucose or insulin resistance. In the present study, we developed and validated a simple, specific and sensitive gas chromatography-mass spectrometry (GC-MS) method specifically intended to quantify serum levels of 2HB. Liquid–liquid extraction with ethyl acetate was followed by 2 min of microwave-assisted derivatization. The method presented acceptable accuracy, precision and recovery, and the limit of quantification was 5 µM. Levels of 2HB were found to be stable in serum after three freeze-thaw cycles, and at ambient temperature and at a temperature of 4 °C for up to 24 h. Extracts derivatized under microwave irradiation were stable for up to 96 h. No differences were found in 2HB concentrations measured in serum or plasma EDTA samples. In summary, the method is useful for a rapid, precise and accurate quantification of 2HB in serum samples assessed for the evaluation of dysglycemia and diabetes mellitus.

Atlas of exercise metabolism reveals time-dependent signatures of metabolic homeostasis

Tissue sensitivity and response to exercise vary according to the time of day and alignment of circadian clocks, but the optimal exercise time to elicit a desired metabolic outcome is not fully defined. To understand how tissues independently and collectively respond to timed exercise, we applied a systems biology approach. We mapped and compared global metabolite responses of seven different mouse tissues and serum after an acute exercise bout performed at different times of the day. Comparative analyses of intra- and inter-tissue metabolite dynamics, including temporal profiling and blood sampling across liver and hindlimb muscles, uncovered an unbiased view of local and systemic metabolic responses to exercise unique to time of day. This comprehensive atlas of exercise metabolism provides clarity and physiological context regarding the production and distribution of canonical and novel time-dependent exerkine metabolites, such as 2-hydroxybutyrate (2-HB), and reveals insight into the health-promoting benefits of exercise on metabolism.

Circulating markers of NADH-reductive stress correlate with mitochondrial disease severity

Mitochondrial disorders represent a large collection of rare syndromes that are difficult to manage both because we do not fully understand biochemical pathogenesis and because we currently lack facile markers of severity. The m.3243A>G variant is the most common heteroplasmic mitochondrial DNA mutation and underlies a spectrum of diseases, notably mitochondrial encephalomyopathy lactic acidosis and stroke-like episodes (MELAS). To identify robust circulating markers of m.3243A>G disease, we first performed discovery proteomics, targeted metabolomics, and untargeted metabolomics on plasma from a deeply phenotyped cohort (102 patients, 32 controls). In a validation phase, we measured concentrations of prioritized metabolites in an independent cohort using distinct methods. We validated 20 analytes (1 protein, 19 metabolites) that distinguish patients with MELAS from controls. The collection includes classic (lactate, alanine) and more recently identified (GDF-15, α-hydroxybutyrate) mitochondrial markers. By mining untargeted mass-spectra we uncovered 3 less well-studied metabolite families: N-lactoyl-amino acids, β-hydroxy acylcarnitines, and β-hydroxy fatty acids. Many of these 20 analytes correlate strongly with established measures of severity, including Karnofsky status, and mechanistically, nearly all markers are attributable to an elevated NADH/NAD+ ratio, or NADH-reductive stress. Our work defines a panel of organelle function tests related to NADH-reductive stress that should enable classification and monitoring of mitochondrial disease.

Exercise plasma metabolomics and xenometabolomics in obese, sedentary, insulin-resistant women: impact of a fitness and weight loss intervention

Insulin resistance has wide-ranging effects on metabolism, but there are knowledge gaps regarding the tissue origins of systemic metabolite patterns and how patterns are altered by fitness and metabolic health. To address these questions, plasma metabolite patterns were determined every 5 min during exercise (30 min, ∼45% of V̇o_2peak, ∼63 W) and recovery in overnight-fasted sedentary, obese, insulin-resistant women under controlled conditions of diet and physical activity. We hypothesized that improved fitness and insulin sensitivity following a ∼14-wk training and weight loss intervention would lead to fixed workload plasma metabolomics signatures reflective of metabolic health and muscle metabolism. Pattern analysis over the first 15 min of exercise, regardless of pre- versus postintervention status, highlighted anticipated increases in fatty acid tissue uptake and oxidation (e.g., reduced long-chain fatty acids), diminution of nonoxidative fates of glucose [e.g., lowered sorbitol-pathway metabolites and glycerol-3-galactoside (possible glycerolipid synthesis metabolite)], and enhanced tissue amino acid use (e.g., drops in amino acids; modest increase in urea). A novel observation was that exercise significantly increased several xenometabolites ("non-self" molecules, from microbes or foods), including benzoic acid-salicylic acid-salicylaldehyde, hexadecanol-octadecanol-dodecanol, and chlorogenic acid. In addition, many nonannotated metabolites changed with exercise. Although exercise itself strongly impacted the global metabolome, there were surprisingly few intervention-associated differences despite marked improvements in insulin sensitivity, fitness, and adiposity. These results and previously reported plasma acylcarnitine profiles support the principle that most metabolic changes during submaximal aerobic exercise are closely tethered to absolute ATP turnover rate (workload), regardless of fitness or metabolic health status.

1H-NMR Metabolomics Identifies Significant Changes in Metabolism over Time in a Porcine Model of Severe Burn and Smoke Inhalation

Burn injury initiates a hypermetabolic response leading to muscle catabolism and organ dysfunction but has not been well-characterized by high-throughput metabolomics. We examined changes in metabolism over the first 72 h post-burn using proton nuclear magnetic resonance (¹H-NMR) spectroscopy and serum from a porcine model of severe burn injury. We sought to quantify the changes in metabolism that occur over time in response to severe burn and smoke inhalation in this preliminary study. Fifteen pigs received 40% total body surface area (TBSA) burns with additional pine bark smoke inhalation. Arterial blood was drawn at baseline (pre-burn) and every 24 h until 72 h post-injury or death. The aqueous portion of each serum sample was analyzed using ¹H-NMR spectroscopy and metabolite concentrations were used for principal component analysis (PCA). Thirty-eight metabolites were quantified in 39 samples. Of these, 31 showed significant concentration changes over time (p < 0.05). PCA revealed clustering of samples by time point on a 2D scores plot. The first 48 h post-burn were characterized by high concentrations of histamine, alanine, phenylalanine, and tyrosine. Later timepoints were characterized by rising concentrations of 2-hydroxybutyrate, 3-hydroxybutyrate, acetoacetate, and isovalerate. No significant differences in metabolism related to mortality were observed. Our work highlights the accumulation of organic acids resulting from fatty acid catabolism and oxidative stress. Further studies will be required to relate accumulation of the four organic carboxylates identified in this analysis to outcomes from burn injury.

Comparative analysis of cerebrospinal fluid metabolites in Alzheimer's disease and idiopathic normal pressure hydrocephalus in a Japanese cohort

Background

Alzheimer’s disease (AD) is a most common dementia in elderly people. Since AD symptoms resemble those of other neurodegenerative diseases, including idiopathic normal pressure hydrocephalus (iNPH), it is difficult to distinguish AD from iNPH for a precise and early diagnosis. iNPH is caused by the accumulation of cerebrospinal fluid (CSF) and involves gait disturbance, urinary incontinence, and dementia. iNPH is treatable with shunt operation which removes accumulated CSF from the brain ventricles.

Methods

We performed metabolomic analysis in the CSF of patients with AD and iNPH with capillary electrophoresis-mass spectrometry. We assessed metabolites to discriminate between AD and iNPH with Welch’s t-test, receiver operating characteristic (ROC) curve analysis, and multiple logistic regression analysis.

Results

We found significant increased levels of glycerate and N-acetylneuraminate and significant decreased levels of serine and 2-hydroxybutyrate in the CSF of patients with AD compared to the CSF of patients with iNPH. The ROC curve analysis with these four metabolites showed that the area under the ROC curve was 0.90, indicating good discrimination between AD and iNPH.

Conclusions

This study identified four metabolites that could possibly discriminate between AD and iNPH, which previous research has shown are closely related to the risk factors, pathogenesis, and symptoms of AD. Analyzing pathway-specific metabolites in the CSF of patients with AD may further elucidate the mechanism and pathogenesis of AD.

Electronic supplementary material

The online version of this article (10.1186/s40364-018-0119-x) contains supplementary material, which is available to authorized users.

GC-MS based Gestational Diabetes Mellitus longitudinal study: Identification of 2-and 3-hydroxybutyrate as potential prognostic biomarkers

Gestational Diabetes Mellitus (GDM) causes severe short- and long-term complications for the mother, fetus and neonate, including type 2-diabetes (T2DM) later in life. In this pilot study, GC-Q/MS analysis was applied for plasma metabolomics fingerprinting of 24 healthy and 24 women with GDM at different stages of gestation (second and third trimester) and postpartum (one and three months). Multivariate (unsupervised and supervised) statistical analysis was performed to investigate variance in the data, identify outliers and for unbiased assessment of data quality. Plasma fingerprints allowed for the discrimination of GDM pregnant women from controls both in the 2nd and 3rd trimesters of gestation. However, metabolic profiles tended to be similar after delivery. Follow up of these women revealed that 4 of them developed T2DM within 2 years postpartum. Multivariate PLS-DA models limited to women with GDM showed clear separation 3 months postpartum. In the 2nd trimester of gestation there was also a clear separation between GDM women that were normoglycemic after pregnancy and those with recognized postpartum T2DM. Metabolites that had the strongest discriminative power between these groups in the 2nd trimester of gestation were 2-hydroxybutyrate, 3-hydroxybutyrate, and stearic acid. We have described, that early GDM comprises metabotypes that are associated with the risk of future complications, including postpartum T2DM. In this pilot study, we provide evidence that 2-hydroxybutyrate and 3-hydroxybutyrate may be considered as future prognostic biomarkers to predict the onset of diabetic complications in women with gestational diabetes after delivery.