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- ceramides (4)
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Sphingosine 1-phosphate (S1P) signaling influences numerous cell biological mechanisms such as differentiation, proliferation, survival, migration, and angiogenesis. Intriguingly, our current knowledge is based solely on the role of S1P with an 18-carbon long-chain base length, S1P d18:1. Depending on the composition of the first and rate-limiting enzyme of the sphingolipid de novo metabolism, the serine palmitoyltransferase, other chain lengths have been described in vivo. While cells are also able to produce S1P d20:1, its abundance and function remains elusive so far. Our experiments are highlighting the role of S1P d20:1 in the mouse central nervous system (CNS) and human glioblastoma. We show here that S1P d20:1 and its precursors are detectable in both healthy mouse CNS-tissue and human glioblastoma. On the functional level, we focused our work on one particular, well-characterized pathway, the induction of cyclooxygenase (COX)-2 expression via the S1P receptor 2 (S1P2). Intriguingly, S1P d20:1 only fairly induces COX-2 expression and can block the S1P d18:1-induced COX-2 expression mediated via S1P2 activation in the human glioblastoma cell line LN229. This data indicates that S1P d20:1 might act as an endogenous modulator of S1P signaling via a partial agonism at the S1P2 receptor. While our findings might stimulate further research on the relevance of long-chain base lengths in sphingolipid signaling, the metabolism of S1P d20:1 has to be considered as an integral part of S1P signaling pathways in vivo.
Background: Sphingolipids are versatile signaling molecules derived from membrane lipids of eukaryotic cells. Ceramides regulate cellular processes such as proliferation, differentiation and apoptosis and are involved in cellular stress responses. Experimental evidence suggests a pivotal role of sphingolipids in the pathogenesis of cardiovascular diseases, including ischemic stroke. A neuroprotective effect has been shown for beta-adrenergic antagonists in rodent stroke models and supported by observational clinical data. However, the exact underlying pathophysiological mechanisms are still under investigation. We aimed to examine the influence of propranolol on the ceramide metabolism in the stroke-affected brain.
Methods: Mice were subjected to 60 or 180 min transient middle cerebral artery occlusion (tMCAO) and infarct size, functional neurological deficits, glucose tolerance, and brain ceramide levels were assessed after 12, 24, and 72 h to evaluate whether the latter two processes occur in a similar time frame. Next, we assessed the effects of propranolol (10 mg/kg bw) at 0, 4 and 8 h after tMCAO and FTY720 (fingolimod; 1 mg/kg) on infarct size, functional outcome, immune cell counts and brain ceramide levels at 24 h after 60 min tMCAO.
Results: We found a temporal coincidence between stroke-associated impaired glucose tolerance and brain ceramide accumulation. Whereas propranolol reduced ischemic lesion size, improved functional outcome and reduced brain ceramide accumulation without an effect on circulating immune cells, FTY720 showed the known neuroprotective effect and strong reduction of circulating immune cells without affecting brain ceramide accumulation.
Conclusions: Propranolol ameliorates both stroke-associated impairment of glucose tolerance and brain ceramide accumulation which are temporally linked, strengthening the evidence for a role of the sympathetic nervous system in regulating post-stroke glucose metabolism and its metabolic consequences in the brain.
With increasing distribution of endovascular stroke therapies, transient middle cerebral artery occlusion (tMCAO) in mice now more than ever depicts a relevant patient population with recanalized M1 occlusion. In this case, the desired therapeutic effect of blood flow restauration is accompanied by breakdown of the blood-brain barrier (BBB) and secondary reperfusion injury. The aim of this study was to elucidate short and intermediate-term transcriptional patterns and the involved pathways covering the different cellular players at the neurovascular unit after transient large vessel occlusion. To achieve this, male C57Bl/6J mice were treated according to an intensive post-stroke care protocol after 60 min occlusion of the middle cerebral artery or sham surgery to allow a high survival rate. After 24 h or 7 days, RNA from microvessel fragments from the ipsilateral and the contralateral hemispheres was isolated and used for mRNA sequencing. Bioinformatic analyses allowed us to depict gene expression changes at two timepoints of neurovascular post-stroke injury and regeneration. We validated our dataset by quantitative real time PCR of BBB-associated targets with well-characterized post-stroke dynamics. Hence, this study provides a well-controlled transcriptome dataset of a translationally relevant mouse model 24 h and 7 days after stroke which might help to discover future therapeutic targets in cerebral ischemia/reperfusion injury.
Dysregulation of blood sphingolipids is an emerging topic in clinical science. The objective of this study was to determine preanalytical biases that typically occur in clinical and translational studies and that influence measured blood sphingolipid levels. Therefore, we collected blood samples from four healthy male volunteers to investigate the effect of storage conditions (time, temperature, long-term storage, freeze–thaw cycles), blood drawing (venous or arterial sampling, prolonged venous compression), and sample preparation (centrifugation, freezing) on sphingolipid levels measured by LC-MS/MS. Our data show that sphingosine 1-phosphate (S1P) and sphinganine 1-phosphate (SA1P) were upregulated in whole blood samples in a time- and temperature-dependent manner. Increased centrifugation at higher speeds led to lower amounts of S1P and SA1P. All other preanalytical biases did not significantly alter the amounts of S1P and SA1P. Further, in almost all settings, we did not detect differences in (dihydro)ceramide levels. In summary, besides time-, temperature-, and centrifugation-dependent changes in S1P and SA1P levels, sphingolipids in blood remained stable under practically relevant preanalytical conditions.
Genes encoding endocannabinoid and sphingolipid metabolism pathways were suggested to contribute to the genetic risk towards attention deficit hyperactivity disorder (ADHD). The present pilot study assessed plasma concentrations of candidate endocannabinoids, sphingolipids and ceramides in individuals with adult ADHD in comparison with healthy controls and patients with affective disorders. Targeted lipid analyses of 23 different lipid species were performed in 71 mental disorder patients and 98 healthy controls (HC). The patients were diagnosed with adult ADHD (n = 12), affective disorder (major depression, MD n = 16 or bipolar disorder, BD n = 6) or adult ADHD with comorbid affective disorders (n = 37). Canonical discriminant analysis and CHAID analyses were used to identify major components that predicted the diagnostic group. ADHD patients had increased plasma concentrations of sphingosine-1-phosphate (S1P d18:1) and sphinganine-1-phosphate (S1P d18:0). In addition, the endocannabinoids, anandamide (AEA) and arachidonoylglycerol were increased. MD/BD patients had increased long chain ceramides, most prominently Cer22:0, but low endocannabinoids in contrast to ADHD patients. Patients with ADHD and comorbid affective disorders displayed increased S1P d18:1 and increased Cer22:0, but the individual lipid levels were lower than in the non-comorbid disorders. Sphingolipid profiles differ between patients suffering from ADHD and affective disorders, with overlapping patterns in comorbid patients. The S1P d18:1 to Cer22:0 ratio may constitute a diagnostic or prognostic tool.
Dysregulation of lysophosphatidic acids in multiple sclerosis and autoimmune encephalomyelitis
(2017)
Bioactive lipids contribute to the pathophysiology of multiple sclerosis. Here, we show that lysophosphatidic acids (LPAs) are dysregulated in multiple sclerosis (MS) and are functionally relevant in this disease. LPAs and autotaxin, the major enzyme producing extracellular LPAs, were analyzed in serum and cerebrospinal fluid in a cross-sectional population of MS patients and were compared with respective data from mice in the experimental autoimmune encephalomyelitis (EAE) model, spontaneous EAE in TCR1640 mice, and EAE in Lpar2 -/- mice. Serum LPAs were reduced in MS and EAE whereas spinal cord LPAs in TCR1640 mice increased during the ‘symptom-free’ intervals, i.e. on resolution of inflammation during recovery hence possibly pointing to positive effects of brain LPAs during remyelination as suggested in previous studies. Peripheral LPAs mildly re-raised during relapses but further dropped in refractory relapses. The peripheral loss led to a redistribution of immune cells from the spleen to the spinal cord, suggesting defects of lymphocyte homing. In support, LPAR2 positive T-cells were reduced in EAE and the disease was intensified in Lpar2 deficient mice. Further, treatment with an LPAR2 agonist reduced clinical signs of relapsing-remitting EAE suggesting that the LPAR2 agonist partially compensated the endogenous loss of LPAs and implicating LPA signaling as a novel treatment approach.
Based on increasing evidence suggesting that MS pathology involves alterations in bioactive lipid metabolism, the present analysis was aimed at generating a complex serum lipid-biomarker. Using unsupervised machine-learning, implemented as emergent self-organizing maps of neuronal networks, swarm intelligence and Minimum Curvilinear Embedding, a cluster structure was found in the input data space comprising serum concentrations of d = 43 different lipid-markers of various classes. The structure coincided largely with the clinical diagnosis, indicating that the data provide a basis for the creation of a biomarker (classifier). This was subsequently assessed using supervised machine-learning, implemented as random forests and computed ABC analysis-based feature selection. Bayesian statistics-based biomarker creation was used to map the diagnostic classes of either MS patients (n = 102) or healthy subjects (n = 301). Eight lipid-markers passed the feature selection and comprised GluCerC16, LPA20:4, HETE15S, LacCerC24:1, C16Sphinganine, biopterin and the endocannabinoids PEA and OEA. A complex classifier or biomarker was developed that predicted MS at a sensitivity, specificity and accuracy of approximately 95% in training and test data sets, respectively. The present successful application of serum lipid marker concentrations to MS data is encouraging for further efforts to establish an MS biomarker based on serum lipidomics.