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Cancer-induced pain occurs frequently in patients when tumors or their metastases grow in the proximity of nerves. Although this cancer-induced pain states poses an important therapeutical problem, the underlying pathomechanisms are not understood. Here, we implanted adenocarcinoma, fibrosarcoma and melanoma tumor cells in proximity of the sciatic nerve. All three tumor types caused mechanical hypersensitivity, thermal hyposensitivity and neuronal damage. Surprisingly the onset of the hypersensitivity was independent of physical contact of the nerve with the tumors and did not depend on infiltration of cancer cells in the sciatic nerve. However, macrophages and dendritic cells appeared on the outside of the sciatic nerves with the onset of the hypersensitivity. At the same time point downregulation of perineural tight junction proteins was observed, which was later followed by the appearance of microlesions. Fitting to the changes in the epi-/perineurium, a dramatic decrease of triglycerides and acylcarnitines in the sciatic nerves as well as an altered localization and appearance of epineural adipocytes was seen. In summary, the data show an inflammation at the sciatic nerves as well as an increased perineural and epineural permeability. Thus, interventions aiming to suppress inflammatory processes at the sciatic nerve or preserving peri- and epineural integrity may present new approaches for the treatment of tumor-induced pain.
High glucosylceramides and low anandamide contribute to sensory loss and pain in Parkinson's disease
(2020)
Background: Parkinson's disease (PD) causes chronic pain in two‐thirds of patients, in part originating from sensory neuropathies. The aim of the present study was to describe the phenotype of PD‐associated sensory neuropathy and to evaluate its associations with lipid allostasis, the latter motivated by recent genetic studies associating mutations of glucocerebrosidase with PD onset and severity. Glucocerebrosidase catalyzes the metabolism of glucosylceramides.
Methods: We used quantitative sensory tests, pain ratings, and questionnaires and analyzed plasma levels of multiple bioactive lipid species using targeted lipidomic analyses. The study comprised 2 sets of patients and healthy controls: the first 128 Israeli PD patients and 224 young German healthy controls for exploration, the second 50/50 German PD patients and matched healthy controls for deeper analyses.
Results: The data showed a 70% prevalence of PD pain and sensory neuropathies with a predominant phenotype of thermal sensory loss plus mechanical hypersensitivity. Multivariate analyses of lipids revealed major differences between PD patients and healthy controls, mainly originating from glucosylceramides and endocannabinoids. Glucosylceramides were increased, whereas anandamide and lysophosphatidic acid 20:4 were reduced, stronger in patients with ongoing pain and with a linear relationship with pain intensity and sensory losses, particularly for glucosylceramide 18:1 and glucosylceramide 24:1.
Conclusions: Our data suggest that PD‐associated sensory neuropathies and PD pain are in part caused by accumulations of glucosylceramides, raising the intriguing possibility of reducing PD pain and sensory loss by glucocerebrosidase substituting or refolding approaches. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Die Aufdeckung krankheitsbedingter Unterschiede und die Identifizierung neuer Biomarker sind essenziell für Diagnose und Behandlung verschiedener Erkrankungen. Unterschiede zwischen Erkrankungen können u.a. durch Analyse des Lipidprofils aufgedeckt werden, da dieses eng mit dem Phänotyp verknüpft ist. Ein unvoreingenommenes Screening gewährt einen umfassenderen Einblick in den metabolischen Zustand als eine gezielte Untersuchung weniger Analyten und kann neue Hypothesen generieren. Deshalb wurde im Rahmen dieser Arbeit eine Screening-Methode zur untargeted Untersuchung des Lipidoms in biologischen Proben entwickelt. Durch die Kombination aus Umkehrphasenchromatographie und hochauflösender Massenspektrometrie mit datenabhängiger Aufnahme von MS/MS-Spektren konnten in Humanplasma 440 Lipide aus mehr als 15 Lipidklassen identifiziert werden. Die mehrstufige Identifizierung der Analyten, basierend auf der exakten Masse ±5 ppm, der Isotopenverteilung, der MS/MS-Fragmentierungsmuster in beiden Ionisationsmodi sowie der chromatographischen Auftrennung von Isomeren und Isobaren, erfolgte mit hoher Selektivität. Mit der vorgestellten Methode können sowohl Lipidklassen als auch einzelne Lipide relativ zu den internen Standards quantifiziert werden.
Der Probendurchsatz wurde erhöht, um den Einsatz der Methode im Rahmen größerer klinischer Studien zu ermöglichen und vorhandene Ressourcen effizient einzusetzen. Dabei wurden die Inkubationszeiten während der Flüssig-Flüssig-Extraktion mit MTBE:Methanol deutlich reduziert und die Handhabung vereinfacht bei gleichbleibend hoher Wiederfindung. Der hohe Probendurchsatz wird weiter unterstützt durch die kurze chromatographische Laufzeit von 17 min pro Ionisationsmodus. Die Auswertung der Ergebnisse ist der heikelste und zeitintensivste Schritt bei der Entwicklung und Anwendung von Screening-Methoden, deshalb wurde der Arbeitsablauf zur univariaten Analyse durch Entwicklung von R Skripten vereinfacht und beschleunigt.
Die Qualität und Reproduzierbarkeit der Ergebnisse sind essenziell. Aus diesem Grund wurde die Qualität der entwickelten Methode, angelehnt an den strikten Vorgaben der FDA und EMA zur Validierung von quantitativen Methoden, sichergestellt, obwohl eine Methodenüberprüfung im Bereich von untargeted Methoden nicht verbreitet ist. Die Reproduzierbarkeit der relativen Lipidkonzentrationen konnte z.B. durch die Messung von Kontrollplasmaproben über einen Zeitraum von 10 Monaten gezeigt werden. Außerdem wurde die Linearität der Verdünnung von Plasmaproben bestätigt und eine Verschleppung in darauffolgende Proben ausgeschlossen. Die Stabilität der Proben muss in jeder Messphase inklusive der Präanalytik durch geeignete Untersuchungen und Maßnahmen sichergestellt werden. Anhand einer Studie zur präanalytischen Stabilität humaner Blutproben konnte ein Protokoll zur Probennahme und -vorbereitung für weitere klinische Studien erarbeitet werden. Die Stabilität des Lipidoms in Vollblut und Plasma konnte durch den Einsatz von Natriumfluorid/Citrat als Antikoagulans verbessert werden. Auch die Stabilität der Proben während der Lipidextraktion und Messung konnte gezeigt werden. Es wurden 16 verschiedene Probenarten analysiert, darunter Plasmaproben, verschiedene Mausgewebe und Zellpellets.
Mit der entwickelten Methode wurden die Unterschiede im Lipidprofil im Plasma und Gewebe von Mäusen mit einer akuten Entzündung durch LPS bzw. Zymosan-Injektion aufgedeckt. Dabei wurden die Ether-Phosphatidylcholine als potenzielle Entzündungsmarker identifiziert. Die entwickelte Methode wurde außerdem erfolgreich im Rahmen anderer Arbeiten für die Untersuchung verschiedener Erkrankungen angewendet.
In der vorliegenden Arbeit wird demnach eine schnelle, reproduzierbare und vor allem selektive LC-MS-Screening-Methode vorgestellt, die Veränderungen des Lipidstoffwechsels aufdecken und potenzielle Biomarker identifizieren kann.
Immune-mediated inflammatory diseases (IMIDs), such as rheumatoid arthritis (RA), psoriatic arthritis (PsA), and psoriasis (Ps), represent autoinflammatory and autoimmune disorders, as well as conditions that have an overlap of both categories. Understanding the underlying pathogeneses, making diagnoses, and choosing individualized treatments remain challenging due to heterogeneous disease phenotypes and the lack of reliable biomarkers that drive the treatment choice. In this review, we provide an overview of the low-molecular-weight metabolites that might be employed as biomarkers for various applications, e.g., early diagnosis, disease activity monitoring, and treatment-response prediction, in RA, PsA, and Ps. The literature was evaluated, and putative biomarkers in different matrices were identified, categorized, and summarized. While some of these candidate biomarkers appeared to be disease-specific, others were shared across multiple IMIDs, indicating common underlying disease mechanisms. However, there is still a long way to go for their application in a routine clinical setting. We propose that studies integrating omics analyses of large patient cohorts from different IMIDs should be performed to further elucidate their pathomechanisms and treatment options. This could lead to the identification and validation of biomarkers that might be applied in the context of precision medicine to improve the clinical outcomes of these IMID patients.
The lipid status in patients with ulcerative colitis : Sphingolipids are disease-dependent regulated
(2019)
The factors that contribute to the development of ulcerative colitis (UC), are still not fully identified. Disruption of the colon barrier is one of the first events leading to invasion of bacteria and activation of the immune system. The colon barrier is strongly influenced by sphingolipids. Sphingolipids impact cell–cell contacts and function as second messengers. We collected blood and colon tissue samples from UC patients and healthy controls and investigated the sphingolipids and other lipids by LC-MS/MS or LC-QTOFMS. The expression of enzymes of the sphingolipid pathway were determined by RT-PCR and immunohistochemistry. In inflamed colon tissue, the de novo-synthesis of sphingolipids is reduced, whereas lactosylceramides are increased. Reduction of dihydroceramides was due to posttranslational inhibition rather than altered serine palmitoyl transferase or ceramide synthase expression in inflamed colon tissue. Furthermore, in human plasma from UC-patients, several sphinglipids change significantly in comparison to healthy controls. Beside sphingolipids free fatty acids, lysophosphatidylcholines and triglycerides changed significantly in the blood of colitis patients dependent on the disease severity. Our data indicate that detraction of the sphingolipid de novo synthesis in colon tissue might be an important trigger for UC. Several lipids changed significantly in the blood, which might be used as biomarkers for disease control; however, diet-related variabilities need to be considered.
Post-exercise hypotension (PEH) is the phenomenon of lowered blood pressure after a single bout of exercise. Only a fraction of people develops PEH but its occurrence correlates well with long-term effects of sports on blood pressure. Therefore, PEH has been suggested as a suitable predictor for the effectivity of exercise as therapy in hypertension. Local vascular bioactive lipids might play a potential role in this context. We performed a cross-over clinical pilot study with 18 healthy volunteers to investigate the occurrence of PEH after a single short-term endurance exercise. Furthermore, we investigated the plasma lipid profile with focus on arachidonic acid (AA)-derived metabolites as potential biomarkers of PEH. A single bout of ergometer cycling induced a significant PEH in healthy volunteers with the expected high inter-individual variability. Targeted lipid spectrum analysis revealed significant upregulation of several lipids in the direct post-exercise phase. Among these changes, only 15- hydroxyeicosatetranoic acid (HETE) correlated significantly with the extent of PEH but in an AA-independent manner, suggesting that 15-HETE might act as specific PEH-marker. Our data indicate that specific lipid modulation might facilitate the identification of patients who will benefit from exercise activity in hypertension therapy. However, larger trials including hypertonic patients are necessary to verify the clinical value of this hypothesis.
Depletion of the enzyme cofactor, tetrahydrobiopterin (BH4), in T-cells was shown to prevent their proliferation upon receptor stimulation in models of allergic inflammation in mice, suggesting that BH4 drives autoimmunity. Hence, the clinically available BH4 drug (sapropterin) might increase the risk of autoimmune diseases. The present study assessed the implications for multiple sclerosis (MS) as an exemplary CNS autoimmune disease. Plasma levels of biopterin were persistently low in MS patients and tended to be lower with high Expanded Disability Status Scale (EDSS). Instead, the bypass product, neopterin, was increased. The deregulation suggested that BH4 replenishment might further drive the immune response or beneficially restore the BH4 balances. To answer this question, mice were treated with sapropterin in immunization-evoked autoimmune encephalomyelitis (EAE), a model of multiple sclerosis. Sapropterin-treated mice had higher EAE disease scores associated with higher numbers of T-cells infiltrating the spinal cord, but normal T-cell subpopulations in spleen and blood. Mechanistically, sapropterin treatment was associated with increased plasma levels of long-chain ceramides and low levels of the poly-unsaturated fatty acid, linolenic acid (FA18:3). These lipid changes are known to contribute to disruptions of the blood–brain barrier in EAE mice. Indeed, RNA data analyses revealed upregulations of genes involved in ceramide synthesis in brain endothelial cells of EAE mice (LASS6/CERS6, LASS3/CERS3, UGCG, ELOVL6, and ELOVL4). The results support the view that BH4 fortifies autoimmune CNS disease, mechanistically involving lipid deregulations that are known to contribute to the EAE pathology.
The evaluation of pharmacological data using machine learning requires high data quality. Therefore, data preprocessing, that is, cleaning analytical laboratory errors, replacing missing values or outliers, and transforming data adequately before actual data analysis, is crucial. Because current tools available for this purpose often require programming skills, preprocessing tools with graphical user interfaces that can be used interactively are needed. In collaboration between data scientists and experts in bioanalytical diagnostics, a graphical software package for data preprocessing called pguIMP is proposed, which contains a fixed sequence of preprocessing steps to enable reproducible interactive data preprocessing. As an R-based package, it also allows direct integration into this data science environment without requiring any programming knowledge. The implementation of contemporary data processing methods, including machine-learning-based imputation techniques, ensures the generation of corrected and cleaned bioanalytical data sets that preserve data structures such as clusters better than is possible with classical methods. This was evaluated on bioanalytical data sets from lipidomics and drug research using k-nearest-neighbors-based imputation followed by k-means clustering and density-based spatial clustering of applications with noise. The R package provides a Shiny-based web interface designed to be easy to use for non–data analysis experts. It is demonstrated that the spectrum of methods provided is suitable as a standard pipeline for preprocessing bioanalytical data in biomedical research domains. The R package pguIMP is freely available at the comprehensive R archive network (https://cran.r-project.org/web/packages/pguIMP/index.html).
