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Although bariatric surgery is known to change the metabolome, it is unclear if this is specific for the intervention or a consequence of the induced bodyweight loss. As the weight loss after Roux-en-Y Gastric Bypass (RYGB) can hardly be mimicked with an evenly effective diet in humans, translational research efforts might be helpful. A group of 188 plasma metabolites of 46 patients from the randomized controlled Würzburg Adipositas Study (WAS) and from RYGB-treated rats (n = 6) as well as body-weight-matched controls (n = 7) were measured using liquid chromatography tandem mass spectrometry. WAS participants were randomized into intensive lifestyle modification (LS, n = 24) or RYGB (OP, n = 22). In patients in the WAS cohort, only bariatric surgery achieved a sustained weight loss (BMI −34.3% (OP) vs. −1.2% (LS), p ≤ 0.01). An explicit shift in the metabolomic profile was found in 57 metabolites in the human cohort and in 62 metabolites in the rodent model. Significantly higher levels of sphingolipids and lecithins were detected in both surgical groups but not in the conservatively treated human and animal groups. RYGB leads to a characteristic metabolomic profile, which differs distinctly from that following non-surgical intervention. Analysis of the human and rat data revealed that RYGB induces specific changes in the metabolome independent of weight loss.
Predicting hypertension subtypes with machine learning using targeted metabolites and their ratios
(2022)
Hypertension is a major global health problem with high prevalence and complex associated health risks. Primary hypertension (PHT) is most common and the reasons behind primary hypertension are largely unknown. Endocrine hypertension (EHT) is another complex form of hypertension with an estimated prevalence varying from 3 to 20% depending on the population studied. It occurs due to underlying conditions associated with hormonal excess mainly related to adrenal tumours and sub-categorised: primary aldosteronism (PA), Cushing’s syndrome (CS), pheochromocytoma or functional paraganglioma (PPGL). Endocrine hypertension is often misdiagnosed as primary hypertension, causing delays in treatment for the underlying condition, reduced quality of life, and costly antihypertensive treatment that is often ineffective. This study systematically used targeted metabolomics and high-throughput machine learning methods to predict the key biomarkers in classifying and distinguishing the various subtypes of endocrine and primary hypertension. The trained models successfully classified CS from PHT and EHT from PHT with 92% specificity on the test set. The most prominent targeted metabolites and metabolite ratios for hypertension identification for different disease comparisons were C18:1, C18:2, and Orn/Arg. Sex was identified as an important feature in CS vs. PHT classification.
Despite considerable morbidity and mortality, numerous cases of endocrine hypertension (EHT) forms, including primary aldosteronism (PA), pheochromocytoma and functional paraganglioma (PPGL), and Cushing’s syndrome (CS), remain undetected. We aimed to establish signatures for the different forms of EHT, investigate potentially confounding effects and establish unbiased disease biomarkers. Plasma samples were obtained from 13 biobanks across seven countries and analyzed using untargeted NMR metabolomics. We compared unstratified samples of 106 PHT patients to 231 EHT patients, including 104 PA, 94 PPGL and 33 CS patients. Spectra were subjected to a multivariate statistical comparison of PHT to EHT forms and the associated signatures were obtained. Three approaches were applied to investigate and correct confounding effects. Though we found signatures that could separate PHT from EHT forms, there were also key similarities with the signatures of sample center of origin and sample age. The study design restricted the applicability of the corrections employed. With the samples that were available, no biomarkers for PHT vs. EHT could be identified. The complexity of the confounding effects, evidenced by their robustness to correction approaches, highlighted the need for a consensus on how to deal with variabilities probably attributed to preanalytical factors in retrospective, multicenter metabolomics studies.
Nonlimited proliferation is one of the most striking features of neoplastic cells. The basis of cell division is the sufficient presence of mass (amino acids) and energy (ATP and NADH). A sophisticated intracellular network permanently measures the mass and energy levels. Thus, in vivo restrictions in the form of amino acid, protein, or caloric restrictions strongly affect absolute lifespan and age-associated diseases such as cancer. The induction of permanent low energy metabolism (LEM) is essential in this process. The murine cell line L929 responds to methionine restriction (MetR) for a short time period with LEM at the metabolic level defined by a characteristic fingerprint consisting of the molecules acetoacetate, creatine, spermidine, GSSG, UDP-glucose, pantothenate, and ATP. Here, we used mass spectrometry (LC/MS) to investigate the influence of proliferation and contact inhibition on the energy status of cells. Interestingly, the energy status was essentially independent of proliferation or contact inhibition. LC/MS analyses showed that in full medium, the cells maintain active and energetic metabolism for optional proliferation. In contrast, MetR induced LEM independently of proliferation or contact inhibition. These results are important for cell behaviour under MetR and for the optional application of restrictions in cancer therapy.
Die Fähigkeit sich an die Rotation der Erde und den daraus resultierenden Tag- und Nacht-Rhythmus anzupassen, basiert auf einer komplexen Regulation verschiedener physiologischer Prozesse. Auf molekularer Ebene liegt diesen Prozessen eine Orchestration von Uhr-Genen zugrunde – auch als innere Uhr bezeichnet – die einen aktivierenden bzw. reprimierenden Einfluss auf die Expression einer Vielzahl weiterer Gene hat. Ausgehend von dieser Regulation lassen sich auf unterschiedlichsten Ebenen tageszeitabhängige, wiederkehrende Rhythmen beobachten.
Während diese wiederkehrenden Rhythmen auf einigen Ebenen bereits gut erforscht und beschrieben sind, gibt es weitere Ebenen wie den Metabolismus, über die das Wissen bisher noch begrenzt ist.
So handelt es sich bei Drosophila beispielsweise um den Organismus, dessen innere Uhr auf molekularer Ebene wahrscheinlich mit am besten charakterisiert ist. Dennoch ist bisher nur wenig über Stoffklassen bekannt, deren Metabolismus durch die innere Uhr kontrolliert wird.
Zwar konnte bereits gezeigt werden, dass sich eine gestörte innere Uhr auf die Anlage der Energiespeicher auswirkt, inwiefern dies allerdings einen Einfluss auf dem intermediären Stoffwechsel hat, blieb bisher weitgehend unerforscht. Auch die Frage, welche Metaboliten wiederkehrende, tageszeitabhängige Rhythmen aufweisen, wurde bisher nur für eine begrenzte Anzahl Metaboliten untersucht.
Bei der hier durchgeführten Arbeit wurden deshalb zunächst die globalen Metabolit-Profile von Fliegen mit einer auf molekularer Ebene gestörten inneren Uhr (per01) mit Fliegen, die über eine funktionale Uhr verfügen (CantonS), zu zwei Zeitpunkten verglichen. Um die Anzahl der zeitgleich untersuchten Gewebe und somit die Komplexität der Probe zu reduzieren, wurden hierfür die Köpfe von den Körpern der Fliegen getrennt und separat analysiert. Beide Körperteile wurden sowohl auf kleine hydrophile als auch auf hydrophobe Metaboliten hin mittels UPLC-ESI-qTOF-MS untersucht. Die anschließend durchgeführte, statistische Analyse brachte hervor, dass sich Unterschiede zwischen den beiden Fliegenlinien besonders in den Spiegeln der essentiellen Aminosäuren, den Kynureninen, den Pterinaten sowie den Spiegeln der Glycero(phospho)lipiden und Fettsäureester zeigten. Bei den Lipiden zeigte sich, dass die Auswirkungen weniger ausgeprägt für die Anlage der Speicher- und Strukturlipide als für die Intermediate des Lipidabbaus, die Diacylglycerole (DAGs) sowie die Acylcarnitine (ACs), waren.
Um zu bestätigen, dass die inneren Uhr tatsächlich einen regulatorischen Einfluss auf die ausgemachten Stoffwechselwege hat, wurden anschließend die Spiegel aller Mitglieder darauf hin untersucht, ob diese wiederkehrende, tageszeitabhängige Schwankungen aufweisen. Hierfür wurden Proben alle zwei Stunden über drei aufeinanderfolgende Tage genommen und analysiert, bevor mittels JTK_CYCLE eine statistische Analyse der Daten durchgeführt und die Metaboliten herausgefiltert wurden, die ein rhythmisches Verhalten bei einer Periodenlänge von 24h zeigten. Hierbei bestätigte sich, dass besonders die Mitglieder des intermediären Lipidmetablismus hiervon betroffen waren. So konnten zwar auch für einige Aminosäuren robuste Rhythmen ausgemacht werden, besonders ausgeprägt waren diese jedoch erneut bei den DAGs und den ACs. Die abschließende Untersuchung letzterer unter Freilaufbedingungen (DD) sowie in per01 brachte hervor, dass die ausgemachten Rhythmen unter diesen Bedingungen entweder nicht mehr detektiert werden konnten oder deutlich abgeschwächt vorlagen. Lediglich zwei kurzkettige ACs zeigten auch unter DD-Bedingungen statistisch signifikante Rhythmen in ihren Spiegeln. Dies spricht dafür, dass neben der Regulation durch die innere Uhr weitere Faktoren, wie beispielsweise das Licht, eine entscheidende Rolle zu spielen scheinen.
In the last few years, quantitative analysis of metabolites in body fluids using LC/MS has become an established method in laboratory medicine and toxicology. By preparing metabolite profiles in biological specimens, we are able to understand pathophysiological mechanisms at the biochemical and thus the functional level. An innovative investigative method, which has not yet been used widely in the forensic context, is to use the clinical application of metabolomics. In a metabolomic analysis of 41 samples of postmortem cerebrospinal fluid (CSF) samples divided into cohorts of four different causes of death, namely, cardiovascular fatalities, isoIated torso trauma, traumatic brain injury, and multi-organ failure, we were able to identify relevant differences in the metabolite profile between these individual groups. According to this preliminary assessment, we assume that information on biochemical processes is not gained by differences in the concentration of individual metabolites in CSF, but by a combination of differently distributed metabolites forming the perspective of a new generation of biomarkers for diagnosing (fatal) TBI and associated neuropathological changes in the CNS using CSF samples.
The fruit fly Drosophila is a prime model in circadian research, but still little is known about its circadian regulation of metabolism. Daily rhythmicity in levels of several metabolites has been found, but knowledge about hydrophobic metabolites is limited. We here compared metabolite levels including lipids between period\(^{01}\) (per\(^{01}\)) clock mutants and Canton-S wildtype (WT\(_{CS}\)) flies in an isogenic and non-isogenic background using LC–MS. In the non-isogenic background, metabo-lites with differing levels comprised essential amino acids, kynurenines, pterinates, glycero(phospho)lipids, and fatty acid esters. Notably, detectable diacylglycerols (DAG) and acylcarnitines (AC), involved in lipid metabolism, showed lower levels in per\(^{01}\) mutants. Most of these differences disappeared in the isogenic background, yet the level differences for AC as well as DAG were consistent for fly bodies. AC levels were dependent on the time of day in WTCS in phase with food consumption under LD conditions, while DAGs showed weak daily oscillations. Two short-chain ACs continued to cycle even in constant darkness. per\(^{01}\) mutants in LD showed no or very weak diel AC oscillations out of phase with feeding activity. The low levels of DAGs and ACs in per\(^{01}\) did not correlate with lower total food consumption, body mass or weight. Clock mutant flies showed higher sensitivity to starvation independent of their background-dependent activity level. Our results suggest that neither feeding, energy storage nor mobilisation is significantly affected in per\(^{01}\) mutants, but point towards impaired mitochondrial activity, supported by upregulation of the mitochondrial stress marker 4EBP in the clock mutants
Experimental high-throughput analysis of molecular networks is a central approach to characterize the adaptation of plant metabolism to the environment. However, recent studies have demonstrated that it is hardly possible to predict in situ metabolic phenotypes from experiments under controlled conditions, such as growth chambers or greenhouses. This is particularly due to the high molecular variance of in situ samples induced by environmental fluctuations. An approach of functional metabolome interpretation of field samples would be desirable in order to be able to identify and trace back the impact of environmental changes on plant metabolism. To test the applicability of metabolomics studies for a characterization of plant populations in the field, we have identified and analyzed in situ samples of nearby grown natural populations of Arabidopsis thaliana in Austria. A. thaliana is the primary molecular biological model system in plant biology with one of the best functionally annotated genomes representing a reference system for all other plant genome projects. The genomes of these novel natural populations were sequenced and phylogenetically compared to a comprehensive genome database of A. thaliana ecotypes. Experimental results on primary and secondary metabolite profiling and genotypic variation were functionally integrated by a data mining strategy, which combines statistical output of metabolomics data with genome-derived biochemical pathway reconstruction and metabolic modeling. Correlations of biochemical model predictions and population-specific genetic variation indicated varying strategies of metabolic regulation on a population level which enabled the direct comparison, differentiation, and prediction of metabolic adaptation of the same species to different habitats. These differences were most pronounced at organic and amino acid metabolism as well as at the interface of primary and secondary metabolism and allowed for the direct classification of population-specific metabolic phenotypes within geographically contiguous sampling sites.
Malvaviscus arboreus Cav. is a medicinal plant belonging to family Malvaceae with both ethnomedical and culinary value; however, its phytochemical and biological profiles have been scarcely studied. Accordingly, this work was designed to explore the chemical composition and the hepatoprotective potential of M. arboreus against carbon tetrachloride (CCl\(_4\))-induced hepatotoxicity. The total extract of the aerial parts and its derived fractions (petroleum ether, dichloromethane, ethyl acetate, and aqueous) were orally administered to rats for six consecutive days, followed by injection of CCl\(_4\) (1:1 v/v, in olive oil, 1.5 ml/kg, i.p.) on the next day. Results showed that the ethyl acetate and dichloromethane fractions significantly alleviated liver injury in rats as indicated by the reduced levels of alanine transaminase (ALT), aspartate transaminase (AST), alkaline phosphatase (ALP), total bilirubin (TB), and malondialdehyde (MDA), along with enhancement of the total antioxidant capacities of their livers, with the maximum effects were recorded by the ethyl acetate fraction. Moreover, the protective actions of both fractions were comparable to those of silymarin (100 mg/kg), and have been also substantiated by histopathological evaluations. On the other hand, liquid chromatography-high resolution electrospray ionization mass spectrometry (LC‒HR‒ESI‒MS) metabolomic profiling of the crude extract of M. arboreus aerial parts showed the presence of a variety of phytochemicals, mostly phenolics, whereas the detailed chemical analysis of the most active fraction (i.e. ethyl acetate) resulted in the isolation and identification of six compounds for the first time in the genus, comprising four phenolic acids; β-resorcylic, caffeic, protocatechuic, and 4-hydroxyphenylacetic acids, in addition to two flavonoids; trifolin and astragalin. Such phenolic principles, together with their probable synergistic antioxidant and liver-protecting properties, seem to contribute to the observed hepatoprotective potential of M. arboreus.
Context:
Adrenal tumors have a prevalence of around 2% in the general population. Adrenocortical carcinoma (ACC) is rare but accounts for 2–11% of incidentally discovered adrenal masses. Differentiating ACC from adrenocortical adenoma (ACA) represents a diagnostic challenge in patients with adrenal incidentalomas, with tumor size, imaging, and even histology all providing unsatisfactory predictive values.
Objective:
Here we developed a novel steroid metabolomic approach, mass spectrometry-based steroid profiling followed by machine learning analysis, and examined its diagnostic value for the detection of adrenal malignancy.
Design:
Quantification of 32 distinct adrenal derived steroids was carried out by gas chromatography/mass spectrometry in 24-h urine samples from 102 ACA patients (age range 19–84 yr) and 45 ACC patients (20–80 yr). Underlying diagnosis was ascertained by histology and metastasis in ACC and by clinical follow-up [median duration 52 (range 26–201) months] without evidence of metastasis in ACA. Steroid excretion data were subjected to generalized matrix learning vector quantization (GMLVQ) to identify the most discriminative steroids.
Results:
Steroid profiling revealed a pattern of predominantly immature, early-stage steroidogenesis in ACC. GMLVQ analysis identified a subset of nine steroids that performed best in differentiating ACA from ACC. Receiver-operating characteristics analysis of GMLVQ results demonstrated sensitivity = specificity = 90% (area under the curve = 0.97) employing all 32 steroids and sensitivity = specificity = 88% (area under the curve = 0.96) when using only the nine most differentiating markers.
Conclusions:
Urine steroid metabolomics is a novel, highly sensitive, and specific biomarker tool for discriminating benign from malignant adrenal tumors, with obvious promise for the diagnostic work-up of patients with adrenal incidentalomas.