PEG Minocycline-Liposomes Ameliorate CNS Autoimmune Disease

Minocycline is an oral tetracycline derivative with good bioavailability in the central nervous system (CNS). Minocycline, a potent inhibitor of matrix metalloproteinase (MMP)-9, attenuates disease activity in experimental autoimmune encephalomyelitis (EAE), an animal model of multiple sclerosis (MS). Potential adverse effects associated with long-term daily minocycline therapy in human patients are concerning. Here, we investigated whether less frequent treatment with long-circulating polyethylene glycol (PEG) minocycline liposomes are effective in treating EAE.Performing in vitro time kinetic studies of PEG minocycline-liposomes in human peripheral blood mononuclear cells (PBMCs), we determined that PEG minocycline-liposome preparations stabilized with CaCl(2) are effective in diminishing MMP-9 activity. Intravenous injections of PEG minocycline-liposomes every five days were as effective in ameliorating clinical EAE as daily intraperitoneal injections of minocycline. Treatment of animals with PEG minocycline-liposomes significantly reduced the number of CNS-infiltrating leukocytes, and the overall expression of MMP-9 in the CNS. There was also a significant suppression of MMP-9 expression and proteolytic activity in splenocytes of treated animals, but not in CNS-infiltrating leukocytes. Thus, leukocytes gaining access to the brain and spinal cord require the same absolute amount of MMP-9 in all treatment groups, but minocycline decreases the absolute cell number.Our data indicate that less frequent injections of PEG minocycline-liposomes are an effective alternative pharmacotherapy to daily minocycline injections for the treatment of CNS autoimmune diseases. Also, inhibition of MMP-9 remains a promising treatment target in EAE and patients with MS

Role of Kv1 Potassium Channels in Regulating Dopamine Release and Presynaptic D2 Receptor Function

Dopamine (DA) release in the CNS is critical for motor control and motivated behaviors. Dysfunction of its regulation is thought to be implicated in drug abuse and in diseases such as schizophrenia and Parkinson's. Although various potassium channels located in the somatodendritic compartment of DA neurons such as G-protein-gated inward rectifying potassium channels (GIRK) have been shown to regulate cell firing and DA release, little is presently known about the role of potassium channels localized in the axon terminals of these neurons. Here we used fast-scan cyclic voltammetry to study electrically-evoked DA release in rat dorsal striatal brain slices. We find that although G-protein-gated inward rectifying (GIRK) and ATP-gated (KATP) potassium channels play only a minor role, voltage-gated potassium channels of the Kv1 family play a major role in regulating DA release. The use of Kv subtype-selective blockers confirmed a role for Kv1.2, 1.3 and 1.6, but not Kv1.1, 3.1, 3.2, 3.4 and 4.2. Interestingly, Kv1 blockers also reduced the ability of quinpirole, a D2 receptor agonist, to inhibit evoked DA overflow, thus suggesting that Kv1 channels also regulate presynaptic D2 receptor function. Our work identifies Kv1 potassium channels as key regulators of DA release in the striatum

Genetics and not shared environment explains familial resemblance in adult metabolomics data

Metabolites are small molecules involved in cellular metabolism where they act as reaction substrates or products. The term 'metabolomics' refers to the comprehensive study of these molecules. The concentrations of metabolites in biological tissues are under genetic control, but this is limited by environmental factors such as diet. In adult mono- and dizygotic twin pairs, we estimated the contribution of genetic and shared environmental influences on metabolite levels by structural equation modeling and tested whether the familial resemblance for metabolite levels is mainly explained by genetic or by environmental factors that are shared by family members. Metabolites were measured across three platforms: two based on proton nuclear magnetic resonance techniques and one employing mass spectrometry. These three platforms comprised 237 single metabolic traits of several chemical classes. For the three platforms, metabolites were assessed in 1407, 1037 and 1116 twin pairs, respectively. We carried out power calculations to establish what percentage of shared environmental variance could be detected given these sample sizes. Our study did not find evidence for a systematic contribution of shared environment, defined as the influence of growing up together in the same household, on metabolites assessed in adulthood. Significant heritability was observed for nearly all 237 metabolites; significant contribution of the shared environment was limited to 6 metabolites. The top quartile of the heritability distribution was populated by 5 of the 11 investigated chemical classes. In this quartile, metabolites of the class lipoprotein were significantly overrepresented, whereas metabolites of classes glycerophospholipids and glycerolipids were significantly underrepresented.Analytical BioScience

Metabolic Age Based on the BBMRI-NL H-1-NMR Metabolomics Repository as Biomarker of Age-related Disease

BACKGROUND: The blood metabolome incorporates cues from the environment and the host's genetic background, potentially offering a holistic view of an individual's health status.METHODS: We have compiled a vast resource of proton nuclear magnetic resonance metabolomics and phenotypic data encompassing over 25 000 samples derived from 26 community and hospital-based cohorts.RESULTS: Using this resource, we constructed a metabolomics-based age predictor (metaboAge) to calculate an individual's biological age. Exploration in independent cohorts demonstrates that being judged older by one's metabolome, as compared with one's chronological age, confers an increased risk on future cardiovascular disease, mortality, and functionality in older individuals. A web-based tool for calculating metaboAge (metaboage.researchlumc.nl) allows easy incorporation in other epidemiological studies. Access to data can be requested at bmri.nl/samples-images-data.CONCLUSIONS: In summary, we present a vast resource of metabolomics data and illustrate its merit by constructing a metabolomics-based score for biological age that captures aspects of current and future cardiometabolic health.Stress-related psychiatric disorders across the life spa

Metabolic age based on the BBMRI-NL 1H-NMR metabolomics repository as biomarker of age-related disease

BACKGROUND: The blood metabolome incorporates cues from the environment and the host's genetic background, potentially offering a holistic view of an individual's health status. METHODS: We have compiled a vast resource of proton nuclear magnetic resonance metabolomics and phenotypic data encompassing over 25&#x2009;000 samples derived from 26 community and hospital-based cohorts. RESULTS: Using this resource, we constructed a metabolomics-based age predictor (metaboAge) to calculate an individual's biological age. Exploration in independent cohorts demonstrates that being judged older by one's metabolome, as compared with one's chronological age, confers an increased risk on future cardiovascular disease, mortality, and functionality in older individuals. A web-based tool for calculating metaboAge (metaboage.researchlumc.nl) allows easy incorporation in other epidemiological studies. Access to data can be requested at bbmri.nl/samples-images-data. CONCLUSIONS: In summary, we present a vast resource of metabolomics data and illustrate its merit by constructing a metabolomics-based score for biological age that captures aspects of current and future cardiometabolic health.</p