Feasibility of ultra-performance liquid chromatography-ion mobility-time-of-flight mass spectrometry in analyzing oxysterols

Oxysterols are oxygenated cholesterols that are important in many cell functions and they may also be indicative of certain diseases. The purpose of this work was to study the feasibility of ultra-performance liquid chromatography-ion mobility-time-of-flight mass spectrometry (UPLC-IM-TOFMS) using traveling wave cell in analyzing oxysterols and especially their isomers in biological samples. Oxysterols were analyzed as their p-toluenesulfonyl isocyanate derivatives, which improved the separation of isomeric oxysterols by ion mobility and ionization efficiency in the electrospray ionization step. The UPLC-IM-TOFMS method was shown to be fast and to provide good quantitative performance. The feasibility of the method was demonstrated in the analyses of oxysterols in fibroblast cell samples. (C) 2017 Elsevier B.V. All rights reserved.Peer reviewe

Phaseguide assisted liquid lamination for magnetic particle-based assays

We have developed a magnetic particle-based assay platform in which functionalised magnetic particles are transferred sequentially through laminated volumes of reagents and washing buffers. Lamination of aqueous liquids is achieved via the use of phaseguide technology; microstructures that control the advancing air–liquid interface of solutions as they enter a microfluidic chamber. This allows manual filling of the device, eliminating the need for external pumping systems, and preparation of the system requires only a few minutes. Here, we apply the platform to two on-chip strategies: (i) a one-step streptavidin–biotin binding assay, and (ii) a two-step C-reactive protein immunoassay. With these, we demonstrate how condensing multiple reaction and washing processes into a single step significantly reduces procedural times, with both assay procedures requiring less than 8 seconds

Human metabolomics: strategies to understand biology

Metabolomics provides a direct functional read-out of the physiological status of an organism and is in principle ideally suited to describe someone's health status. Whereas only a limited number of small metabolites are used in the clinics, in inborn errors of metabolism an extensive repertoire of metabolites are used as biomarkers. We discuss that the proper clinical phenotyping is crucial to find biomarkers and obtain biological insights for multifactorial diseases. This requires to study the phenotype dynamics including the concepts of homeostasis and allostasis, that is, the ability to adapt and cope with a challenge. We also elaborate that biology-driven metabolomics platforms (i.e. development of metabolomics technology driven by the need of studying and answering important biomedical questions) addressing clinically relevant pathways and at the same time providing absolute concentrations are key to allow discovery and validation of biomarkers across studies and labs. Following individuals over years will require high throughput metabolomics approaches, which are emerging for nuclear magnetic resonance spectroscopy and direct-infusion mass spectrometry, but should also include the biochemical networks needed for personalized health monitoring

Metabolic characterization of the natural progression of chronic hepatitis B

Background: Worldwide, over 350 million people are chronically infected with the hepatitis B virus (HBV) and are at increased risk of developing progressive liver diseases. The confinement of HBV replication to the liver, which also acts as the central hub for metabolic and nutritional regulation, emphasizes the interlinked nature of host metabolism and the disease. Still, the metabolic processes operational during the distinct clinical phases of a chronic HBV infection-immune tolerant, immune active, inactive carrier, and HBeAg-negative hepatitis phases-remains unexplored. Methods: To investigate this, we conducted a targeted metabolomics approach on serum to determine the metabolic progression over the clinical phases of chronic HBV infection, using patient samples grouped based on their HBV DNA, alanine aminotransferase, and HBeAg serum levels. Results: Our data illustrate the strength of metabolomics to provide insight into the metabolic dysregulation experienced during chronic HBV. The immune tolerant phase is characterized by the speculated viral hijacking of the glycerol-3-phosphate-NADH shuttle, explaining the reduced glycerophospholipid and increased plasmalogen species, indicating a strong link to HBV replication. The persisting impairment of the choline glycerophospholipids, even during the inactive carrier phase with minimal HBV activity, alludes to possible metabolic imprinting effects. The progression of chronic HBV is associated with increased concentrations of very long chain triglycerides together with citrulline and ornithine, reflective of a dysregulated urea cycle peaking in the HBV envelope antigen-negative phase. Conclusions: The work presented here will aid in future studies to (i) validate and understand the implication of these metabolic changes using a thorough systems biology approach, (ii) monitor and predict disease severity, as well as (iii) determine the therapeutic value of the glycerol-3-phosphate-NADH shuttle

Baseline urinary metabolites predict albuminuria response to spironolactone in type 2 diabetes

The mineralocorticoid receptor antagonist spironolactone significantly reduces albuminuria in subjects with diabetic kidney disease, albeit with a large variability between individuals. Identifying novel biomarkers that predict response to therapy may help to tailor spironolactone therapy. We aimed to identify a set of metabolites for prediction of albuminuria response to spironolactone in subjects with type 2 diabetes. Systems biology molecular process analysis was performed a priori to identify metabolites linked to molecular disease processes and drug mechanism of action. Individual subject data and urine samples were used from 2 randomized placebo controlled double blind clinical trials (NCT01062763, NCT00381134). A urinary metabolite score was developed to predict albuminuria response to spironolactone therapy using penalized ridge regression with leave-one-out cross validation. Bioinformatic analysis identified a set of 18 metabolites linked to a diabetic kidney disease molecular model and potentially affected by spironolactone mechanism of action. Spironolactone reduced UACR relative to placebo by median -42% (25th to 75% percentile -65 to 6) and -29% (25th to 75% percentile -37 to -1) in the test and replication cohorts, respectively. In the test cohort, UACR reduction was higher in the lowest tertile of the baseline urinary metabolite score compared with middle and upper tertiles -58% (25th to 75% percentile -78 to 33), -28% (25th to 75% percentile -46 to 8), -40% (25th to 75% percentile -52% to 31), respectively, P= 0.001 for trend). In the replication cohort, UACR reduction was -54% (25th to 75% percentile -65 to -50), -41 (25th to 75% percentile -46% to 30), and -17% (25th to 75% percentile -36 to 5), respectively, P= 0.010 for trend). We identified a set of 18 urinary metabolites through systems biology to predict albuminuria response to spironolactone in type 2 diabetes. These data suggest that urinary metabolites may be used as a tool to tailor optimal therapy and move in the direction of personalized medicine

Sub-Typing of Rheumatic Diseases Based on a Systems Diagnosis Questionnaire

The future of personalized medicine depends on advanced diagnostic tools to characterize responders and non-responders to treatment. Systems diagnosis is a new approach which aims to capture a large amount of symptom information from patients to characterize relevant sub-groups.49 patients with a rheumatic disease were characterized using a systems diagnosis questionnaire containing 106 questions based on Chinese and Western medicine symptoms. Categorical principal component analysis (CATPCA) was used to discover differences in symptom patterns between the patients. Two Chinese medicine experts where subsequently asked to rank the Cold and Heat status of all the patients based on the questionnaires. These rankings were used to study the Cold and Heat symptoms used by these practitioners.The CATPCA analysis results in three dimensions. The first dimension is a general factor (40.2% explained variance). In the second dimension (12.5% explained variance) 'anxious', 'worrying', 'uneasy feeling' and 'distressed' were interpreted as the Internal disease stage, and 'aggravate in wind', 'fear of wind' and 'aversion to cold' as the External disease stage. In the third dimension (10.4% explained variance) 'panting s', 'superficial breathing', 'shortness of breath s', 'shortness of breath f' and 'aversion to cold' were interpreted as Cold and 'restless', 'nervous', 'warm feeling', 'dry mouth s' and 'thirst' as Heat related. 'Aversion to cold', 'fear of wind' and 'pain aggravates with cold' are most related to the experts Cold rankings and 'aversion to heat', 'fullness of chest' and 'dry mouth' to the Heat rankings.This study shows that the presented systems diagnosis questionnaire is able to identify groups of symptoms that are relevant for sub-typing patients with a rheumatic disease

Cold-induced changes in plasma signaling lipids are associated with a healthier cardiometabolic profile independently of brown adipose tissue

Cold exposure activates brown adipose tissue (BAT) and potentially improves cardiometabolic health through the secretion of signaling lipids by BAT. Here, we show that 2 h of cold exposure in young adults increases the levels of omega-6 and omega-3 oxylipins, the endocannabinoids (eCBs) anandamide and docosahexaenoylethanolamine, and lysophospholipids containing polyunsaturated fatty acids. Contrarily, it decreases the levels of the eCBs 1-LG and 2-LG and 1-OG and 2-OG, lysophosphatidic acids, and lysophosphatidylethanolamines. Participants overweight or obese show smaller increases in omega-6 and omega-3 oxylipins levels compared to normal weight. We observe that only a small proportion (~4% on average) of the cold-induced changes in the plasma signaling lipids are slightly correlated with BAT volume. However, cold-induced changes in omega-6 and omega-3 oxylipins are negatively correlated with adiposity, glucose homeostasis, lipid profile, and liver parameters. Lastly, a 24-week exercise-based randomized controlled trial does not modify plasma signaling lipid response to cold exposure.Junta de Andalucía, Consejería de Transformación Económica, Industria, Conocimiento y Universidades Dirección General de Investigación y Transferencia del Conocimiento (ref. P18-RT-4455, ref. SOMM17/6107/UGR, and DOC 01151) and European Regional Development Funds (ERDF)Spanish Ministry of Economy and Competitiveness via the Fondo de Investigación Sanitaria del Instituto de Salud Carlos III (PI13/01393)PTA-12264, Retos de la Sociedad (DEP2016-79512-R)Spanish Ministry of Education (FPU19/01609)Fundación Iberoamericana de Nutrición (FINUT)Redes Temáticas de Investigación Cooperativa RETIC (Red SAMID RD16/0022)AstraZeneca HealthCare FoundationUniversity of Granada Plan Propio de Investigación 2016 Excellence actions: Unit of Excellence on Exercise and Health (UCEES)Chinese Scholarship Council fellowships (no. 201707060012 and no. 201607060017)Grant for the requalification of the Spanish university system from the Ministry of Universities of the Government of Spain, financed by the European Union, NextGeneration EU (María Zambrano program, reference RR_C_2021_04

Plasma trimethylamine N-oxide (TMAO):associations with cognition, neuroimaging, and dementia

Background: The gut-derived metabolite Trimethylamine N-oxide (TMAO) and its precursors - betaine, carnitine, choline, and deoxycarnitine – have been associated with an increased risk of cardiovascular disease, but their relation to cognition, neuroimaging markers, and dementia remains uncertain. Methods: In the population-based Rotterdam Study, we used multivariable regression models to study the associations between plasma TMAO, its precursors, and cognition in 3,143 participants. Subsequently, we examined their link to structural brain MRI markers in 2,047 participants, with a partial validation in the Leiden Longevity Study (n = 318). Among 2,517 participants, we assessed the risk of incident dementia using multivariable Cox proportional hazard models. Following this, we stratified the longitudinal associations by medication use and sex, after which we conducted a sensitivity analysis for individuals with impaired renal function. Results: Overall, plasma TMAO was not associated with cognition, neuroimaging markers or incident dementia. Instead, higher plasma choline was significantly associated with poor cognition (adjusted mean difference: -0.170 [95% confidence interval (CI) -0.297;-0.043]), brain atrophy and more markers of cerebral small vessel disease, such as white matter hyperintensity volume (0.237 [95% CI: 0.076;0.397]). By contrast, higher carnitine concurred with lower white matter hyperintensity volume (-0.177 [95% CI: -0.343;-0.010]). Only among individuals with impaired renal function, TMAO appeared to increase risk of dementia (hazard ratio (HR): 1.73 [95% CI: 1.16;2.60]). No notable differences were observed in stratified analyses. Conclusions: Plasma choline, as opposed to TMAO, was found to be associated with cognitive decline, brain atrophy, and markers of cerebral small vessel disease. These findings illustrate the complexity of relationships between TMAO and its precursors, and emphasize the need for concurrent study to elucidate gut-brain mechanisms.</p

Development of an Untargeted LC-MS Metabolomics Method with Postcolumn Infusion for Matrix Effect Monitoring in Plasma and Feces

Untargeted metabolomics based on reverse phase LC-MS (RPLC-MS) plays a crucial role in biomarker discovery across physiological and disease states. Standardizing the development process of untargeted methods requires paying attention to critical factors that are under discussed or easily overlooked, such as injection parameters, performance assessment, and matrix effect evaluation. In this study, we developed an untargeted metabolomics method for plasma and fecal samples with the optimization and evaluation of these factors. Our results showed that optimizing the reconstitution solvent and sample injection amount was critical for achieving the balance between metabolites coverage and signal linearity. Method validation with representative stable isotopically labeled standards (SILs) provided insights into the analytical performance evaluation of our method. To tackle the issue of the matrix effect, we implemented a postcolumn infusion (PCI) approach to monitor the overall absolute matrix effect (AME) and relative matrix effect (RME). The monitoring revealed distinct AME and RME profiles in plasma and feces. Comparing RME data obtained for SILs through postextraction spiking with those monitored using PCI compounds demonstrated the comparability of these two methods for RME assessment. Therefore, we applied the PCI approach to predict the RME of 305 target compounds covered in our in-house library and found that targets detected in the negative polarity were more vulnerable to the RME, regardless of the sample matrix. Given the value of this PCI approach in identifying the strengths and weaknesses of our method in terms of the matrix effect, we recommend implementing a PCI approach during method development and applying it routinely in untargeted metabolomics