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Introduction Ulcerative colitis (UC) is a chronic disease with rising incidence and unclear etiology. Deep molecular phenotyping by multi omics analyses may provide novel insights into disease processes and characteristic features of remission states. Methods UC pathomechanisms were assessed by proteome profiling of human tissue specimen, obtained from five distinct colon locations for each of the 12 patients included in the study. Systemic disease-associated alterations were evaluated thanks to a cross-sectional setting of mass spectrometry-based multi-omics analyses comprising proteins, metabolites and eicosanoids of plasma obtained from UC patients during acute episodes and upon remission in comparison to healthy controls. Results Tissue proteome profiling indicated colitis-associated activation of neutrophils, macrophages, B- and T-cells, fibroblasts, endothelial cells and platelets, and hypoxic stress, and suggested a general down-regulation of mitochondrial proteins accompanying the establishment of apparent wound healing-promoting activities including scar formation. While pro-inflammatory proteins were apparently upregulated by immune cells, the colitis-associated epithelial cells, fibroblasts, endothelial cells and platelets seemed to predominantly contribute anti-inflammatory and wound healing-promoting proteins. Blood plasma proteomics indicated chronic inflammation and platelet activation, whereas plasma metabolomics identified disease-associated deregulations of gut and gut microbiome-derived metabolites. Upon remission, several, but not all, molecular candidate biomarker levels recovered back to normal. Conclusions The findings may indicate that microvascular damage and platelet deregulation hardly resolve upon remission but apparently persist as disease-associated molecular signature. This study presents local and systemic molecular alterations integrated in a model for UC pathomechanisms potentially supporting the assessment of disease and remission states in UC patients.

Comprehensive phytochemical examination from different perspectives using preparative and analytical chromatographic techniques combined with spectroscopic/spectrometric methods of the so-called "yellow twig"

Background/aims Concerning healthcare approaches, a paradigm change from reactive medicine to predictive approaches, targeted prevention, and personalisation of medical services is highly desirable. This raises demand for biomarker signatures that support the prediction and diagnosis of diseases, as well as monitoring strategies regarding therapeutic efficacy and supporting individualised treatments. New methodological developments should preferably rely on non-invasively sampled biofluids like sweat and tears in order to provide optimal compliance, reduce costs, and ensure availability of the biomaterial. Here, we have thus investigated the metabolic composition of human tears in comparison to finger sweat in order to find biofluid-specific marker molecules derived from distinct secretory glands. The comprehensive investigation of numerous biofluids may lead to the identification of novel biomarker signatures. Moreover, tear fluid analysis may not only provide insight into eye pathologies but may also be relevant for the prediction and monitoring of disease progression and/ or treatment of systemic disorders such as type 2 diabetes mellitus. Methods Sweat and tear fluid were sampled from 20 healthy volunteers using filter paper and commercially available Schirmer strips, respectively. Finger sweat analysis has already been successfully established in our laboratory. In this study, we set up and evaluated methods for tear fluid extraction and analysis using high-resolution mass spectrometry hyphenated with liquid chromatography, using optimised gradients each for metabolites and eicosanoids. Sweat and tears were systematically compared using statistical analysis. As second approach, we performed a clinical pilot study with 8 diabetic patients and compared them to 19 healthy subjects. Results Tear fluid was found to be a rich source for metabolic phenotyping. Remarkably, several molecules previously identified by us in sweat were found significantly enriched in tear fluid, including creatine or taurine. Furthermore, other metabolites such as kahweol and various eicosanoids were exclusively detectable in tears, demonstrating the orthogonal power for biofluid analysis in order to gain information on individual health states. The clinical pilot study revealed that many endogenous metabolites that have previously been linked to type 2 diabetes such as carnitine, tyrosine, uric acid, and valine were indeed found significantly up-regulated in tears of diabetic patients. Nicotinic acid and taurine were elevated in the diabetic cohort as well and may represent new biomarkers for diabetes specifically identified in tear fluid. Additionally, systemic medications, like metformin, bisoprolol, and gabapentin, were readily detectable in tears of patients. Conclusions The high number of identified marker molecules found in tear fluid apparently supports disease development prediction, developing preventive approaches as well as tailoring individual patients’ treatments and monitoring treatment efficacy. Tear fluid analysis may also support pharmacokinetic studies and patient compliance control.

Metabolic biomonitoring in humans is typically based on the sampling of blood, plasma or urine. Although established in the clinical routine, these sampling procedures are often associated with a variety of compliance issues, which are impeding time-course studies. Here, we show that the metabolic profiling of the minute amounts of sweat sampled from fingertips addresses this challenge. Sweat sampling from fingertips is non-invasive, robust and can be accomplished repeatedly by untrained personnel. The sweat matrix represents a rich source for metabolic phenotyping. We confirm the feasibility of short interval sampling of sweat from the fingertips in time-course studies involving the consumption of coffee or the ingestion of a caffeine capsule after a fasting interval, in which we successfully monitor all known caffeine metabolites as well as endogenous metabolic responses. Fluctuations in the rate of sweat production are accounted for by mathematical modelling to reveal individual rates of caffeine uptake, metabolism and clearance. To conclude, metabotyping using sweat from fingertips combined with mathematical network modelling shows promise for broad applications in precision medicine by enabling the assessment of dynamic metabolic patterns, which may overcome the limitations of purely compositional biomarkers., Biomonitoring of sweat from fingertips overcomes current limitations in time-resolved metabolomic profiling of humans and may prove to become a powerful, noninvasive tool for precision medicine. Here, in a feasibility study of short interval sampling of sweat from fingertips, the authors assay individual dynamic metabolic patterns of endogenous and exogenous molecules.

Exposure to bioactive compounds from nutrition, pharmaceuticals, environmental contaminants or other lifestyle habits may affect the human organism. To gain insight into the effects of these influences, as well as the fundamental biochemical mechanisms behind them, molecular profiling seems promising. To address this problem, we developed an assay for the analysis of sweat, collected from finger tips, using mass spectrometry – by far the most comprehensive and sensitive method for such analyses. To evaluate this assay, called metabo-tip, we exposed volunteers to various xenobiotics using standardized protocols and investigated their metabolic response. As early as 15 minutes after the consumption of a cup of coffee, 50g of dark chocolate or a serving of citrus fruits, significant changes in the sweat composition of the finger tips could be observed, providing relevant information in regards to the ingested substances. This included bioactive compounds such as natural flavonoids as well as potential hazardous substances such as pesticides. Furthermore, the identification of metabolites from nicotine after cigarette smoking and metabolites from orally ingested medications such as metamizole indicated the applicability of this assay to observe specific enzymatic processes. Remarkably, we found that the sweat composition fluctuated in a diurnal rhythm, supporting the hypothesis that the composition of sweat can be influenced by endogenous metabolic activities. This was further corroborated by the finding that histamine was significantly increased in the metabo-tip assay in individuals with allergic reactions. Metab-tip may thus enable direct access to individual metabolic profiles and may thus support predictive preventive personalised medicine (PPPM).

Background/aimsExposure to bioactive compounds from nutrition, pharmaceuticals, environmental contaminants or other lifestyle habits may affect the human organism. To gain insight into the effects of these influences, as well as the fundamental biochemical mechanisms behind them, individual molecular profiling seems to be a promising tool and may support the further development of predictive, preventive and personalised medicine.MethodsWe developed an assay, called metabo-tip for the analysis of sweat, collected from fingertips, using mass spectrometry—by far the most comprehensive and sensitive method for such analyses. To evaluate this assay, we exposed volunteers to various xenobiotics using standardised protocols and investigated their metabolic response.ResultsAs early as 15 min after the consumption of a cup of coffee, 50 g of dark chocolate or a serving of citrus fruits, significant changes in the sweat composition of the fingertips were observed, providing relevant information in regard to the ingested substances. This included not only health-promoting bioactive compounds but also potential hazardous substances. Furthermore, the identification of metabolites from orally ingested medications such as metamizole indicated the applicability of this assay to observe specific enzymatic processes in a personalised fashion. Remarkably, we found that the sweat composition fluctuated in a diurnal rhythm, supporting the hypothesis that the composition of sweat can be influenced by endogenous metabolic activities. This was further corroborated by the finding that histamine was significantly increased in the metabo-tip assay in individuals with allergic reactions.ConclusionMetabo-tip analysis may have a large number of practical applications due to its analytical power, non-invasive character and the potential of frequent sampling, especially regarding the individualised monitoring of specific lifestyle and influencing factors. The extraordinarily rich individualised metabolomics data provided by metabo-tip offer direct access to individual metabolic activities and will thus support predictive preventive personalised medicine.

Caffeine is commonly used to combat high sleep pressure on a daily basis. However, interference with sleep–wake regulation could disturb neural homeostasis and insufficient sleep could lead to alterations in human gray matter. Hence, in this double-blind, randomized, cross-over study, we examined the impact of 10-day caffeine (3 × 150 mg/day) on human gray matter volumes (GMVs) and cerebral blood flow (CBF) by fMRI MP-RAGE and arterial spin-labeling sequences in 20 habitual caffeine consumers, compared with 10-day placebo (3 × 150 mg/day). Sleep pressure was quantified by electroencephalographic slow-wave activity (SWA) in the previous nighttime sleep. Nonparametric voxel-based analyses revealed a significant reduction in GMV in the medial temporal lobe (mTL) after 10 days of caffeine intake compared with 10 days of placebo, voxel-wisely adjusted for CBF considering the decreased perfusion after caffeine intake compared with placebo. Larger GMV reductions were associated with higher individual concentrations of caffeine and paraxanthine. Sleep SWA was, however, neither different between conditions nor associated with caffeine-induced GMV reductions. Therefore, the data do not suggest a link between sleep depth during daily caffeine intake and changes in brain morphology. In conclusion, daily caffeine intake might induce neural plasticity in the mTL depending on individual metabolic processes.

Proteome profiling data of eight xenografted cutaneous and cerebellar metastasis of human melanoma cells were combined with eicosanoid and glutathione measurements as well as multiparametric morphologic analyses and immunofluorescence. The analyses revealed significant differences in the expression of molecules associated with metastatic properties, while lacking any commonalties when comparing the metastatic variants from four different donors. Apparently we lack appropriate meta-analysis strategies making use of the large number of presently identified metastasis-associated molecules for successful classification of cells., Graphical Abstract Highlights Comprehensive molecular profiling of cutaneous and cerebellar metastasis variants. Identification of differentially regulated metastasis-associated molecules. Evidence for individually distinct patterns of metastasis-associated molecules. Highlighting the evident need for establishing meta-analyses strategies., The prediction of metastatic properties from molecular analyses still poses a major challenge. Here we aimed at the classification of metastasis-related cell properties by proteome profiling making use of cutaneous and brain-metastasizing variants from single melanomas sharing the same genetic ancestry. Previous experiments demonstrated that cultured cells derived from these xenografted variants maintain a stable phenotype associated with a differential metastatic behavior: The brain metastasizing variants produce more spontaneous micro-metastases than the corresponding cutaneous variants. Four corresponding pairs of cutaneous and metastatic cells were obtained from four individual patients, resulting in eight cell-lines presently investigated. Label free proteome profiling revealed significant differences between corresponding pairs of cutaneous and cerebellar metastases from the same patient. Indeed, each brain metastasizing variant expressed several apparently metastasis-associated proteomic alterations as compared with the corresponding cutaneous variant. Among the differentially expressed proteins we identified cell adhesion molecules, immune regulators, epithelial to mesenchymal transition markers, stem cell markers, redox regulators and cytokines. Similar results were observed regarding eicosanoids, considered relevant for metastasis, such as PGE2 and 12-HETE. Multiparametric morphological analysis of cells also revealed no characteristic alterations associated with the cutaneous and brain metastasis variants. However, no correct classification regarding metastatic potential was yet possible with the present data. We thus concluded that molecular profiling is able to classify cells according to known functional categories but is not yet able to predict relevant cell properties emerging from networks consisting of many interconnected molecules. The presently observed broad diversity of molecular patterns, irrespective of restricting to one tumor type and two main classes of metastasis, highlights the important need to develop meta-analysis strategies to predict cell properties from molecular profiling data. Such base knowledge will greatly support future individualized precision medicine approaches.