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.
40 individuals with self-reported diabetes and 60 controls (male, over 54 years) were randomly selected from the participants of the population-based KORA (Cooperative Health Research in the Region of Augsburg) study, representing an extensively phenotyped sample of the general German population. Concentrations of over 420 unique small molecules were determined in overnight-fasting blood using three different techniques, covering nuclear magnetic resonance and tandem mass spectrometry. Known biomarkers of diabetes could be replicated by this multiple metabolomic platform approach, including sugar metabolites (1,5-anhydroglucoitol), ketone bodies (3-hydroxybutyrate), and branched chain amino acids. In some cases, diabetes-related medication can be detected (pioglitazone, salicylic acid).
Our study depicts the promising potential of metabolomics in diabetes research by identification of a series of known and also novel, deregulated metabolites that associate with diabetes. Key observations include perturbations of metabolic pathways linked to kidney dysfunction (3-indoxyl sulfate), lipid metabolism (glycerophospholipids, free fatty acids), and interaction with the gut microflora (bile acids). Our study suggests that metabolic markers hold the potential to detect diabetes-related complications already under sub-clinical conditions in the general population.
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. High resolution urinary proteome analysis was blindly performed in the 53 non-anuric out of the 76 CKD patients. In addition to routine clinical parameters, CKD273, a urinary proteomics-based classifier and its peptides were quantified. The baseline values were analyzed with regard to the clinical parameters and the occurrence of death or renal death during follow-up (3.6 years) as the main outcome measurements. None of the patients with CKD273<0.55 required dialysis or died while all fifteen patients that reached an endpoint had a CKD273 score >0.55. Unsupervised clustering analysis of the CKD273 peptides separated the patients into two main groups differing in CKD associated parameters. Among the 273 biomarkers, peptides derived from serum proteins were relatively increased in patients with lower glomerular filtration rate, while collagen-derived peptides were relatively decreased (p<0.05; Spearman). CKD273 was different in the groups with different renal function (p<0.003). The CKD273 classifier separated CKD patients according to their renal function and informed on the likelihood of experiencing adverse outcome. Recently defined in a large population, CKD273 is the first proteomic-based classifier successfully tested for prognosis of CKD progression in an independent cohort.
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. To test this hypothesis, we conducted what is, to the best of our knowledge, the first GWA study with metabolomics based on the quantitative measurement of 363 metabolites in serum of 284 male participants of the KORA study. We found associations of frequent single nucleotide polymorphisms (SNPs) with considerable differences in the metabolic homeostasis of the human body, explaining up to 12% of the observed variance. Using ratios of certain metabolite concentrations as a proxy for enzymatic activity, up to 28% of the variance can be explained (p-values 10(-16) to 10(-21)). We identified four genetic variants in genes coding for enzymes (FADS1, LIPC, SCAD, MCAD) where the corresponding metabolic phenotype (metabotype) clearly matches the biochemical pathways in which these enzymes are active. Our results suggest that common genetic polymorphisms induce major differentiations in the metabolic make-up of the human population. This may lead to a novel approach to personalized health care based on a combination of genotyping and metabolic characterization. These genetically determined metabotypes may subscribe the risk for a certain medical phenotype, the response to a given drug treatment, or the reaction to a nutritional intervention or environmental challenge.
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. To test this approach, we examined samples from a cohort of 49 patients representing different stages of CKD. Urine samples were analysed for proteomic changes using capillary electrophoresis-mass spectrometry and urine and plasma samples for metabolomic changes using different mass spectrometry-based techniques. The training set included 20 CKD patients selected according to their estimated glomerular filtration rate (eGFR) at mild (59.9±16.5 mL/min/1.73 m2; n = 10) or advanced (8.9±4.5 mL/min/1.73 m2; n = 10) CKD and the remaining 29 patients left for the test set. We identified a panel of 76 statistically significant metabolites and peptides that correlated with CKD in the training set. We combined these biomarkers in different classifiers and then performed correlation analyses with eGFR at baseline and follow-up after 2.8±0.8 years in the test set. A solely plasma metabolite biomarker-based classifier significantly correlated with the loss of kidney function in the test set at baseline and follow-up (ρ = -0.8031; p<0.0001 and ρ = -0.6009; p = 0.0019, respectively). Similarly, a urinary metabolite biomarker-based classifier did reveal significant association to kidney function (ρ = -0.6557; p = 0.0001 and ρ = -0.6574; p = 0.0005). A classifier utilising 46 identified urinary peptide biomarkers performed statistically equivalent to the urinary and plasma metabolite classifier (ρ = -0.7752; p<0.0001 and ρ = -0.8400; p<0.0001). The combination of both urinary proteomic and urinary and plasma metabolic biomarkers did not improve the correlation with eGFR. In conclusion, we found excellent association of plasma and urinary metabolites and urinary peptides with kidney function, and disease progression, but no added value in combining the different biomarkers data.
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.
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. Metabolic profiling was performed by liquid chromatography coupled with tandem mass spectrometry after phenylisothiocyanate derivatization.
Most plasma amino acid concentrations were decreased in hemodialysis patients, whereas proline, citrulline, asparagine, asymmetric dimethylarginine, and hydroxykynurenine levels were increased (P<0.05). Both plasma levels and urinary excretion of citrulline were higher in the group of patients with advanced CKD (CKD stages 2 and 3 versus CKD stages 4 and 5; in plasma: 35.9±16.3 versus 61.8±23.6 µmol/L, P<0.01; in urine: 1.0±1.2 versus 7.1±14.3 µmol/mol creatinine, P<0.001). Plasma asymmetric dimethylarginine levels were higher in advanced CKD (CKD stages 2 and 3, 0.57±0.29; CKD stages 4 and 5, 1.02±0.48, P<0.001), whereas urinary excretion was lower (2.37±0.93 versus 1.51±1.43, P<0.001). Multivariate analyses adjusting on estimated GFR, serum albumin, proteinuria, and other covariates revealed associations between diabetes and plasma citrulline (P=0.02) and between serum sodium and plasma asymmetric dimethylarginine (P=0.03). Plasma tyrosine to phenylalanine and valine to glycine ratios were lower in advanced CKD stages (P<0.01).
CKD patients have altered plasma and urinary amino acid profiles that are not corrected by dialysis. Depending on solutes, elevated plasma levels were associated with increased or decreased urinary excretion, depicting situations of uremic retention (asymmetric dimethylarginine) or systemic overproduction (citrulline). These results give some insight in the CKD-associated modifications of amino acid metabolism, which may help improve their handling.
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. This review summarizes the CKD-related markers discovered so far, and focuses on compounds and pathways, for which there is quantitative data, substantiating evidence from translational research, and a mechanistic understanding of the processes involved.
Also, multiparametric marker panels have been suggested that showed promising diagnostic and prognostic performance in initial analyses although the data basis from prospective trials is very limited. Large-scale studies, however, are underway and will provide the information for validating a set of parameters and discarding others.
Finally, the path from clinical research to a routine application is discussed, focusing on potential obstacles such as the use of mass spectrometry, and the feasibility of obtaining regulatory approval for targeted metabolomics assays.
•Targeted metabolomics is a highly promising approach for biomarker discovery in CKD.•Significant and plausible biomarkers have been identified in various pathways.•Multiparametric panels perform well in diagnostic and prognostic settings.•Metabolomics assays are suitable for routine in vitro-diagnostics applications.
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. Moreover, 23 lipid metabolites were identified as nicotine-dependent biomarkers. The levels of these biomarkers are all up-regulated in smokers compared to those in former and non-smokers, except for three acyl-alkyl-phosphatidylcholines (e.g. plasmalogens). Consistently significant results were further found for the ratios of plasmalogens to diacyl-phosphatidylcolines, which are reduced in smokers and regulated by the enzyme alkylglycerone phosphate synthase (alkyl-DHAP) in both ether lipid and glycerophospholipid pathways. Notably, our metabolite profiles are consistent with the strong down-regulation of the gene for alkyl-DHAP (AGPS) in smokers that has been found in a study analyzing gene expression in human lung tissues. Our data suggest that smoking is associated with plasmalogen-deficiency disorders, caused by reduced or lack of activity of the peroxisomal enzyme alkyl-DHAP. Our findings provide new insight into the pathophysiology of smoking addiction. Activation of the enzyme alkyl-DHAP by small molecules may provide novel routes for therapy.
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. Biomarker candidates were selected by combined analysis of maximum fold changes (MFCs) in concentrations and P-values resulting from statistical hypothesis testing. Characteristic kinetic signatures were identified through a mathematical modeling approach utilizing polynomial fitting. Modeled kinetic signatures were analyzed for groups with similar behavior by applying hierarchical cluster analysis. Kinetic shape templates were characterized, defining different forms of basic kinetic response patterns, such as sustained, early, late, and other forms, that can be used for metabolite classification. Acetylcarnitine (C2), showing a late response pattern and having the highest values in MFC and statistical significance, was classified as late marker and ranked as strong predictor (MFC = 1.97, P < 0.001). In the class of amino acids, highest values were shown for alanine (MFC = 1.42, P < 0.001), classified as late marker and strong predictor. Glucose yields a delayed response pattern, similar to a hockey stick function, being classified as delayed marker and ranked as moderate predictor (MFC = 1.32, P < 0.001). These findings coincide with existing knowledge on central metabolic pathways affected in exercise physiology, such as β-oxidation of fatty acids, glycolysis, and glycogenolysis. The presented modeling approach demonstrates high potential for dynamic biomarker identification and the investigation of kinetic mechanisms in disease or pharmacodynamics studies using MS data from longitudinal cohort studies.
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. Today, the field of metabolomics is, arguably, at a point where transcriptomics was about 5 yr ago. This being so, the field has a strong need for adapted bioinformatics tools and methods. In this paper we describe a systematic analysis of a targeted quantitative characterization of more than 800 metabolites in blood plasma samples from healthy and diabetic mice under rosiglitazone treatment. We show that known and new metabolic phenotypes of diabetes and medication can be recovered in a statistically objective manner. We find that concentrations of methylglutaryl carnitine are oppositely impacted by rosiglitazone treatment of both healthy and diabetic mice. Analyzing ratios between metabolite concentrations dramatically reduces the noise in the data set, allowing for the discovery of new potential biomarkers of diabetes, such as the N-hydroxyacyloylsphingosyl-phosphocholines SM(OH)28:0 and SM(OH)26:0. Using a hierarchical clustering technique on partial η2 values, we identify functionally related groups of metabolites, indicating a diabetes-related shift from lysophosphatidylcholine to phosphatidylcholine levels. The bioinformatics data analysis approach introduced here can be readily generalized to other drug testing scenarios and other medical disorders.
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.
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). Two hours after a standardized meal venous blood samples were obtained before, 5 mins after the start, at the end of submaximal exercise, and following a recovery of 20 mins. Data analysis was performed using mixed- effects model, with the metabolite level as a function of disease, time point and interaction terms and using each individual's resting level as reference.
Exercise duration was longer in healthy smokers but lactate levels were comparable between groups at all four time points. Glucose levels were increased in COPD. Glutamine was lower, while glutamate and arginine were higher in COPD. Branched-chain amino acids showed a stronger decline during exercise in healthy smokers. Carnitine and the acyl-carnitines C16 and C18:1 were increased in COPD. These metabolite levels and changes were reproducible in the second challenge.
Higher serum glucose, evidence for impaired utilization of amino acids during exercise and a shift of energy metabolism to enhanced consumption of lipids could be early signs for a developing metabolic syndrome in COPD. In COPD patients, deviations of energy and nitrogen metabolism are amplified by an exercise challenge.
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