Dataset Information

Microglial phenotypes in the human epileptic temporal lobe.

ABSTRACT: Microglia, the immune cells of the brain, are highly plastic and possess multiple functional phenotypes. Differences in phenotype in different regions and different states of epileptic human brain have been little studied. Here we use transcriptomics, anatomy, imaging of living cells and ELISA measurements of cytokine release to examine microglia from patients with temporal lobe epilepsies. Two distinct microglial phenotypes were explored. First we asked how microglial phenotype differs between regions of high and low neuronal loss in the same brain. Second, we asked how microglial phenotype is changed by a recent seizure. In sclerotic areas with few neurons, microglia have an amoeboid rather than ramified shape, express activation markers and respond faster to purinergic stimuli. The repairing interleukin, IL-10, regulates the basal phenotype of microglia in the CA1 and CA3 regions with neuronal loss and gliosis. To understand changes in phenotype induced by a seizure, we estimated the delay from the last seizure until tissue collection from changes in reads for immediate early gene transcripts. Pseudotime ordering of these data was validated by comparison with results from kainate-treated mice. It revealed a local and transient phenotype in which microglia secrete the human interleukin CXCL8, IL-1B and other cytokines. This secretory response is mediated in part via the NRLP3 inflammasome.

SUBMITTER: Morin-Brureau M

PROVIDER: S-EPMC6277010 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Microglial phenotypes in the human epileptic temporal lobe.

Morin-Brureau Mélanie M Milior Giampaolo G Royer Juliette J Chali Farah F Le Duigou Caroline C Savary Etienne E Blugeon Corinne C Jourdren Laurent L Akbar David D Dupont Sophie S Navarro Vincent V Baulac Michel M Bielle Franck F Mathon Bertrand B Clemenceau Stéphane S Miles Richard R

Brain : a journal of neurology 20181201 12

Microglia, the immune cells of the brain, are highly plastic and possess multiple functional phenotypes. Differences in phenotype in different regions and different states of epileptic human brain have been little studied. Here we use transcriptomics, anatomy, imaging of living cells and ELISA measurements of cytokine release to examine microglia from patients with temporal lobe epilepsies. Two distinct microglial phenotypes were explored. First we asked how microglial phenotype differs between ...[more]

PMID: 30462183

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Project description:ObjectiveTo identity phenotypes of self-reported symptoms of psychopathology and their correlates in patients with temporal lobe epilepsy (TLE).Method96 patients with TLE and 82 controls were administered the Symptom Checklist 90-Revised (SCL-90-R) to characterize emotional-behavioral status. The nine symptom scales of the SCL-90-R were analyzed by unsupervised machine learning techniques to identify latent TLE groups. Identified clusters were contrasted to controls to characterize their association with sociodemographic, clinical epilepsy, neuropsychological, psychiatric, and neuroimaging factors.ResultsTLE patients as a group exhibited significantly higher (abnormal) scores across all SCL-90-R scales compared to controls. However, cluster analysis identified three latent groups: (1) unimpaired with no scale elevations compared to controls (Cluster 1, 42% of TLE patients), (2) mild-to-moderate symptomatology characterized by significant elevations across several SCL-90-R scales compared to controls (Cluster 2, 35% of TLE patients), and (3) marked symptomatology with significant elevations across all scales compared to controls and the other TLE phenotype groups (Cluster 3, 23% of TLE patients). There were significant associations between cluster membership and demographic (education), clinical epilepsy (perceived seizure severity, bitemporal lobe seizure onset), and neuropsychological status (intelligence, memory, executive function), but with minimal structural neuroimaging correlates. Concurrent validity of the behavioral phenotype grouping was demonstrated through association with psychiatric (current and lifetime-to-date DSM IV Axis 1 disorders and current treatment) and quality-of-life variables.SignificanceSymptoms of psychopathology in patients with TLE are characterized by a series of discrete phenotypes with accompanying sociodemographic, cognitive, and clinical correlates. Similar to cognition in TLE, machine learning approaches suggest a developing taxonomy of the comorbidities of epilepsy.

Project description:This study explored the taxonomy of cognitive impairment within temporal lobe epilepsy and characterized the sociodemographic, clinical and neurobiological correlates of identified cognitive phenotypes. 111 temporal lobe epilepsy patients and 83 controls (mean ages 33 and 39, 57% and 61% female, respectively) from the Epilepsy Connectome Project underwent neuropsychological assessment, clinical interview, and high resolution 3T structural and resting-state functional MRI. A comprehensive neuropsychological test battery was reduced to core cognitive domains (language, memory, executive, visuospatial, motor speed) which were then subjected to cluster analysis. The resulting cognitive subgroups were compared in regard to sociodemographic and clinical epilepsy characteristics as well as variations in brain structure and functional connectivity. Three cognitive subgroups were identified (intact, language/memory/executive function impairment, generalized impairment) which differed significantly, in a systematic fashion, across multiple features. The generalized impairment group was characterized by an earlier age at medication initiation (P < 0.05), fewer patient (P < 0.001) and parental years of education (P < 0.05), greater racial diversity (P < 0.05), and greater number of lifetime generalized seizures (P < 0.001). The three groups also differed in an orderly manner across total intracranial (P < 0.001) and bilateral cerebellar cortex volumes (P < 0.01), and rate of bilateral hippocampal atrophy (P < 0.014), but minimally in regional measures of cortical volume or thickness. In contrast, large-scale patterns of cortical-subcortical covariance networks revealed significant differences across groups in global and local measures of community structure and distribution of hubs. Resting-state fMRI revealed stepwise anomalies as a function of cluster membership, with the most abnormal patterns of connectivity evident in the generalized impairment group and no significant differences from controls in the cognitively intact group. Overall, the distinct underlying cognitive phenotypes of temporal lobe epilepsy harbor systematic relationships with clinical, sociodemographic and neuroimaging correlates. Cognitive phenotype variations in patient and familial education and ethnicity, with linked variations in total intracranial volume, raise the question of an early and persisting socioeconomic-status related neurodevelopmental impact, with additional contributions of clinical epilepsy factors (e.g., lifetime generalized seizures). The neuroimaging features of cognitive phenotype membership are most notable for disrupted large scale cortical-subcortical networks and patterns of functional connectivity with bilateral hippocampal and cerebellar atrophy. The cognitive taxonomy of temporal lobe epilepsy appears influenced by features that reflect the combined influence of socioeconomic, neurodevelopmental and neurobiological risk factors.

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Project description:Excessive activation of mammalian target of rapamycin (mTOR) signaling is epileptogenic in genetic epilepsy. However, the exact role of microglial mTOR in acquired epilepsy remains to be clarified. In the present study, we found that mTOR is strongly activated in microglia following excitatory injury elicited by status epilepticus. To determine the role of microglial mTOR signaling in excitatory injury and epileptogenesis, we generated mice with restrictive deletion of mTOR in microglia. Both male and female mice were used in the present study. We found that mTOR-deficient microglia lost their typical proliferative and inflammatory responses to excitatory injury, whereas the proliferation of astrocytes was preserved. In addition, mTOR-deficient microglia did not effectively engulf injured/dying neurons. More importantly, microglial mTOR-deficient mice displayed increased neuronal loss and developed more severe spontaneous seizures. These findings suggest that microglial mTOR plays a protective role in mitigating neuronal loss and attenuating epileptogenesis in the excitatory injury model of epilepsy.SIGNIFICANCE STATEMENT The mammalian target of rapamycin (mTOR) pathway is strongly implicated in epilepsy. However, the effect of mTOR inhibitors in preclinical models of acquired epilepsy is inconsistent. The broad presence of mTOR signaling in various brain cells could prevent mTOR inhibitors from achieving a net therapeutic effect. This conundrum has spurred further investigation of the cell type-specific effects of mTOR signaling in the CNS. We found that activation of microglial mTOR is antiepileptogenic. Thus, microglial mTOR activation represents a novel antiepileptogenic route that appears to parallel the proepileptogenic route of neuronal mTOR activation. This may explain why the net effect of mTOR inhibitors is paradoxical in the acquired models of epilepsy. Our findings could better guide the use of mTOR inhibitors in preventing acquired epilepsy.

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Microglial phenotypes in the human epileptic temporal lobe.

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Microglial phenotypes in the human epileptic temporal lobe.

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