Smokers with COPD Show a Shift in Energy and Nitrogen Metabolism at Rest and During Exercise.

Purpose: There is an ongoing demand for easily accessible biomarkers that reflect the physiological and pathophysiological mechanisms of COPD. To test if an exercise challenge could help to identify clinically relevant metabolic biomarkers in COPD.

Patients And Methods: We performed two constant-load exercise challenges separated by 4 weeks including smokers with COPD (n=23/19) and sex- and age-matched healthy smokers (n=23/20).

Ensemble Based Approach for Time Series Classification in Metabolomics.

Background: Machine learning is one important application in the area of health informatics, however classification methods for longitudinal data are still rare.

Objectives: The aim of this work is to analyze and classify differences in metabolite time series data between groups of individuals regarding their athletic activity.

Methods: We propose a new ensemble-based 2-tier approach to classify metabolite time series data.

The CKD plasma lipidome varies with disease severity and outcome.

Background: Various alterations in lipid metabolism have been observed in patients with chronic kidney disease (CKD).

Objectives: To determine the levels of lipid species in plasma from CKD and hemodialysis (HD) patients and test their association with CKD severity and patient outcome.

Methods: Seventy-seven patients with CKD stage 2 to HD were grouped into classes of CKD severity at baseline and followed-up for 3.

Modeling and Classification of Kinetic Patterns of Dynamic Metabolic Biomarkers in Physical Activity.

The objectives of this work were the classification of dynamic metabolic biomarker candidates and the modeling and characterization of kinetic regulatory mechanisms in human metabolism with response to external perturbations by physical activity. Longitudinal metabolic concentration data of 47 individuals from 4 different groups were examined, obtained from a cycle ergometry cohort study. In total, 110 metabolites (within the classes of acylcarnitines, amino acids, and sugars) were measured through a targeted metabolomics approach, combining tandem mass spectrometry (MS/MS) with the concept of stable isotope dilution (SID) for metabolite quantitation.

Metabolic biomarkers for chronic kidney disease.

Chronic kidney disease (CKD) is an increasingly recognized burden for patients and health care systems with high (and growing) global incidence and prevalence, significant mortality, and disproportionately high treatment costs. Yet, the available diagnostic tools are either impractical in clinical routine or have serious shortcomings impeding a well-informed disease management although optimized treatment strategies with proven benefits for the patients have become available. Advances in bioanalytical technologies have facilitated studies that identified genomic, proteomic, and metabolic biomarker candidates, and confirmed some of them in independent cohorts.

Assessment of metabolomic and proteomic biomarkers in detection and prognosis of progression of renal function in chronic kidney disease.

Chronic kidney disease (CKD) is part of a number of systemic and renal diseases and may reach epidemic proportions over the next decade. Efforts have been made to improve diagnosis and management of CKD. We hypothesised that combining metabolomic and proteomic approaches could generate a more systemic and complete view of the disease mechanisms.

Plasma and urinary amino acid metabolomic profiling in patients with different levels of kidney function.

Background And Objectives: Patients with CKD display altered plasma amino acid profiles. This study estimated the association between the estimated GFR and urinary and plasma amino acid profiles in CKD patients.

Design, Setting, Participants, & Measurements: Urine and plasma samples were taken from 52 patients with different stages of CKD, and plasma samples only were taken from 25 patients on maintenance hemodialysis.

Oxidative stress in hypobaric hypoxia and influence on vessel-tone modifying mediators.

Increased pulmonary artery pressure is a well-known phenomenon of hypoxia and is seen in patients with chronic pulmonary diseases, and also in mountaineers on high altitude expedition. Different mediators are known to regulate pulmonary artery vessel tone. However, exact mechanisms are not fully understood and a multimodal process consisting of a whole panel of mediators is supposed to cause pulmonary artery vasoconstriction.

CKD273, a new proteomics classifier assessing CKD and its prognosis.

National Kidney Foundation CKD staging has allowed uniformity in studies on CKD. However, early diagnosis and predicting progression to end stage renal disease are yet to be improved. Seventy six patients with different levels of CKD, including outpatients and dialysed patients were studied for transcriptome, metabolome and proteome description.

A network-based feature selection approach to identify metabolic signatures in disease.

The identification and interpretation of metabolic biomarkers is a challenging task. In this context, network-based approaches have become increasingly a key technology in systems biology allowing to capture complex interactions in biological systems. In this work, we introduce a novel network-based method to identify highly predictive biomarker candidates for disease.

Profiling the human response to physical exercise: a computational strategy for the identification and kinetic analysis of metabolic biomarkers.

Background: In metabolomics, biomarker discovery is a highly data driven process and requires sophisticated computational methods for the search and prioritization of novel and unforeseen biomarkers in data, typically gathered in preclinical or clinical studies. In particular, the discovery of biomarker candidates from longitudinal cohort studies is crucial for kinetic analysis to better understand complex metabolic processes in the organism during physical activity.

Findings: In this work we introduce a novel computational strategy that allows to identify and study kinetic changes of putative biomarkers using targeted MS/MS profiling data from time series cohort studies or other cross-over designs.

Bioinformatics for mass spectrometry-based metabolomics.

The broad view of the state of biological systems cannot be complete without the added value of integrating proteomic and genomic data with metabolite measurement. By definition, metabolomics aims at quantifying not less than the totality of small molecules present in a biofluid, tissue, organism, or any material beyond living systems. To cope with the complexity of the task, mass spectrometry (MS) is the most promising analytical environment to fulfill increasing appetite for more accurate and larger view of the metabolome while providing sufficient data generation throughput.

Questionnaire-based self-reported nutrition habits associate with serum metabolism as revealed by quantitative targeted metabolomics.

Nutrition plays an important role in human metabolism and health. However, it is unclear in how far self-reported nutrition intake reflects de facto differences in body metabolite composition. To investigate this question on an epidemiological scale we conducted a metabolomics study analyzing the association of self-reported nutrition habits with 363 metabolites quantified in blood serum of 284 male participants of the KORA population study, aged between 55 and 79 years.

Metabolic footprint of diabetes: a multiplatform metabolomics study in an epidemiological setting.

Background: Metabolomics is the rapidly evolving field of the comprehensive measurement of ideally all endogenous metabolites in a biological fluid. However, no single analytic technique covers the entire spectrum of the human metabolome. Here we present results from a multiplatform study, in which we investigate what kind of results can presently be obtained in the field of diabetes research when combining metabolomics data collected on a complementary set of analytical platforms in the framework of an epidemiological study.

Metabolomic profiles indicate distinct physiological pathways affected by two loci with major divergent effect on Bos taurus growth and lipid deposition.

Identifying trait-associated genetic variation offers new prospects to reveal novel physiological pathways modulating complex traits. Taking advantage of a unique animal model, we identified the I442M mutation in the non-SMC condensin I complex, subunit G (NCAPG) gene and the Q204X mutation in the growth differentiation factor 8 (GDF8) gene as substantial modulators of pre- and/or postnatal growth in cattle. In a combined metabolomic and genotype association approach, which is the first respective study in livestock, we surveyed the specific physiological background of the effects of both loci on body-mass gain and lipid deposition.

Variation in the human lipidome associated with coffee consumption as revealed by quantitative targeted metabolomics.

The effect of coffee consumption on human health is still discussed controversially. Here, we report results from a metabolomics study of coffee consumption, where we measured 363 metabolites in blood serum of 284 male participants of the Cooperative Health Research in the Region of Augsburg study population, aged between 55 and 79 years. A statistical analysis of the association of metabolite concentrations and the number of cups of coffee consumed per day showed that coffee intake is positively associated with two classes of sphingomyelins, one containing a hydroxy-group (SM(OH)) and the other having an additional carboxy-group (SM(OH,COOH)).

Dynamic simulations on the mitochondrial fatty acid beta-oxidation network.

Background: The oxidation of fatty acids in mitochondria plays an important role in energy metabolism and genetic disorders of this pathway may cause metabolic diseases. Enzyme deficiencies can block the metabolism at defined reactions in the mitochondrion and lead to accumulation of specific substrates causing severe clinical manifestations. Ten of the disorders directly affecting mitochondrial fatty acid oxidation have been well-defined, implicating episodic hypoketotic hypoglycemia provoked by catabolic stress, multiple organ failure, muscle weakness, or hypertrophic cardiomyopathy.

Metabolic profiling reveals distinct variations linked to nicotine consumption in humans--first results from the KORA study.

Exposure to nicotine during smoking causes a multitude of metabolic changes that are poorly understood. We quantified and analyzed 198 metabolites in 283 serum samples from the human cohort KORA (Cooperative Health Research in the Region of Augsburg). Multivariate analysis of metabolic profiles revealed that the group of smokers could be clearly differentiated from the groups of former smokers and non-smokers.

Genetics meets metabolomics: a genome-wide association study of metabolite profiles in human serum.

The rapidly evolving field of metabolomics aims at a comprehensive measurement of ideally all endogenous metabolites in a cell or body fluid. It thereby provides a functional readout of the physiological state of the human body. Genetic variants that associate with changes in the homeostasis of key lipids, carbohydrates, or amino acids are not only expected to display much larger effect sizes due to their direct involvement in metabolite conversion modification, but should also provide access to the biochemical context of such variations, in particular when enzyme coding genes are concerned.

Rapid sample preparation and simultaneous quantitation of prostaglandins and lipoxygenase derived fatty acid metabolites by liquid chromatography-mass spectrometry from small sample volumes.

Background: Fatty acid metabolites play a key role in numerous physiological and pathological processes. A rapid liquid chromatography-mass spectrometry assay for the simultaneous determination of prostanoids, isoprostane and lipoxygenase (LOX) derived fatty acid metabolites in a small biological sample of only 20 microL was developed.

Methods: Human plasma samples were applied to a filter spot, extracted without prior derivatization and analyzed within 13 min.

A new rule-based algorithm for identifying metabolic markers in prostate cancer using tandem mass spectrometry.

Motivation: Prostate cancer is the most prevalent tumor in males and its incidence is expected to increase as the population ages. Prostate cancer is treatable by excision if detected at an early enough stage. The challenges of early diagnosis require the discovery of novel biomarkers and tools for prostate cancer management.

[Metabolomics in diagnosing metabolic diseases].

Metabolomics, i.e. the systematic identification and quantitation of low-molecular weight compounds in a certain cell, a tissue or a body fluid is increasingly recognized as the most relevant approach in functional genomics.

Isotope correction of mass spectrometry profiles.

Isotope correction of a profile is an important step in the analysis of mass spectrometry derived data. The problem is mathematically formulated as a system of linear equations which is general enough to include previous correction methods. For the solution of these equations when applied to the whole profile an efficient algorithm is developed.

Bioinformatics analysis of targeted metabolomics--uncovering old and new tales of diabetic mice under medication.

Metabolomics is a powerful tool for identifying both known and new disease-related perturbations in metabolic pathways. In preclinical drug testing, it has a high potential for early identification of drug off-target effects. Recent advances in high-precision high-throughput mass spectrometry have brought the metabolomic field to a point where quantitative, targeted, metabolomic measurements with ready-to-use kits allow for the automated in-house screening for hundreds of different metabolites in large sets of biological samples.