42 research outputs found

    Developmental interneuron subtype deficits after targeted loss of Arx

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    Abstract Background Aristaless-related homeobox (ARX) is a paired-like homeodomain transcription factor that functions primarily as a transcriptional repressor and has been implicated in neocortical interneuron specification and migration. Given the role interneurons appear to play in numerous human conditions including those associated with ARX mutations, it is essential to understand the consequences of mutations in this gene on neocortical interneurons. Previous studies have examined the effect of germline loss of Arx, or targeted mutations in Arx, on interneuron development. We now present the effect of conditional loss of Arx on interneuron development. Results To further elucidate the role of Arx in forebrain development we performed a series of anatomical and developmental studies to determine the effect of conditional loss of Arx specifically from developing interneurons in the neocortex and hippocampus. Analysis and cell counts were performed from mouse brains using immunohistochemical and in situ hybridization assays at 4 times points across development. Our data indicate that early in development, instead of a loss of ventral precursors, there is a shift of these precursors to more ventral locations, a deficit that persists in the adult nervous system. The result of this developmental shift is a reduced number of interneurons (all subtypes) at early postnatal and later time periods. In addition, we find that X inactivation is stochastic, and occurs at the level of the neural progenitors. Conclusion These data provide further support that the role of Arx in interneuron development is to direct appropriate migration of ventral neuronal precursors into the dorsal cortex and that the loss of Arx results in a failure of interneurons to reach the cortex and thus a deficiency in interneurons.http://deepblue.lib.umich.edu/bitstream/2027.42/134595/1/12868_2016_Article_265.pd

    Anti-MOG encephalitis mimicking small vessel CNS vasculitis

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    Objective: To report 2 patients with anti-myelin oligodendrocyte glycoprotein (MOG)-associated encephalitis who were initially misdiagnosed with small vessel primary CNS vasculitis. Methods: Review of symptoms, MRI and neuropathologic features, and response to treatment. MOG antibodies were determined in serum and CSF using a cell-based assay. Results: Symptoms included fever, headache, and progressive mental status changes and focal neurologic deficits. CSF studies revealed lymphocytic pleocytosis, and both patients had abnormal brain MRIs. Brain biopsy samples showed prominent lymphocytic infiltration of the wall of small vessels; these findings initially suggested small vessel CNS vasculitis, and both patients were treated accordingly. Although 1 patient had a relapsing-remitting course not responsive to cyclophosphamide, the other one (also treated with cyclophosphamide) did not relapse. Retrospective assessment of serum and CSF demonstrated MOG antibodies in both cases, and review of biopsy specimens showed absence of fibrinoid necrosis (a pathologic requirement for small vessel CNS vasculitis). Conclusions: Anti-MOG-associated encephalitis can be mistaken for small vessel CNS vasculitis. This is important because the diagnosis of anti-MOG-associated encephalitis does not require brain biopsy and can be established with a serologic test

    Non-invasive detection of 2-hydroxyglutarate in IDH-mutated gliomas using two-dimensional localized correlation spectroscopy (2D L-COSY) at 7 Tesla

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    BACKGROUND: Mutations in the isocitrate dehydrogenase enzyme are present in a majority of lower-grade gliomas and secondary glioblastomas. This mis-sense mutation results in the neomorphic reduction of isocitrate dehydrogenase resulting in an accumulation of the “oncometabolite” 2-hydroxyglutarate (2HG). Detection of 2HG can thus serve as a surrogate biomarker for these mutations, with significant translational implications including improved prognostication. Two dimensional localized correlated spectroscopy (2D L-COSY) at 7T is a highly-sensitive non-invasive technique for assessing brain metabolism. This study aims to assess tumor metabolism using 2D L-COSY at 7T for the detection of 2HG in IDH-mutant gliomas. METHODS: Nine treatment-naïve patients with suspected intracranial neoplasms were scanned at 7T MRI/MRS scanner using the 2D L-COSY technique. 2D-spectral processing and analyses were performed using a MATLAB-based reconstruction algorithm. Cross and diagonal peak volumes were quantified in the 2D L-COSY spectra and normalized with respect to the creatine peak at 3.0 ppm and quantified data were compared with previously-published data from six normal subjects. Detection of 2HG was validated using findings from immunohistochemical (IHC) staining in patients who subsequently underwent surgical resection. RESULTS: 2HG was detected in both of the IDH-mutated gliomas (grade III Anaplastic Astrocytoma and grade II Diffuse Astrocytoma) and was absent in IDH wild-type gliomas and in a patient with breast cancer metastases. 2D L-COSY was also able to resolve complex and overlapping resonances including phosphocholine (PC) from glycerophosphocholine (GPC), lactate (Lac) from lipids and glutamate (Glu) from glutamine (Gln). CONCLUSIONS: This study demonstrates the ability of 2D L-COSY to unambiguously detect 2HG in addition to other neuro metabolites. These findings may aid in establishing 2HG as a biomarker of malignant progression as well as for disease monitoring in IDH-mutated gliomas

    The Aristaless-related homeobox gene in mouse brain development

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    The production and integration of GABAergic interneurons into the cortex is a crucial element of brain development. These neurons play important roles in controlling and modulating neural firing patterns by completing local circuits. The loss of the rhythm generation, synchronization and inhibition of neural signaling provided by interneurons likely leads to severe deficits in the brain, which in human patients are believed to result in intellectual disability (ID) and epilepsy. Mutations in the transcription factor Aristaless-related homeobox gene (ARX) are also associated with these clinical phenotypes, as well as defects in interneuron populations. However, the normal function of ARX and the mechanism of disease in patients with mutations are unknown. In Chapter 2, I studied the role of Arx in interneurons, using in vitro and in vivo techniques, with emphasis on understanding the mechanism of disease of an expansion of the first polyalanine tract in Arx (ArxE). This mutation is associated with ID, Infantile Spasm Syndrome and other early epileptic phenotypes in patients. Expression of ArxE in a mouse model in which Arx has been deleted in cells either in the ventral forebrain or in the entire forebrain demonstrated that this mutation causes dysfunction in the non-radial cell migration (NRCM) of ventrally-born interneurons moving to the cortex, but not in neurons born in dorsal proliferative areas migrating radially to form the cortical plate. Arx is unable to repress specific targets through a context-specific loss of binding to its repressive cofactor Tle1 at those targets. In Chapter 3, I investigated the effect of Arx deletion on interneuron subpopulations, which showed that calbindin-positive neurons are decreased in dorsal areas of the embryonic brain, and increased in ventral areas, while Nkx2.1-positive cells appear to migrate abnormally from the subpallium dorsally into the pallium. This suggests that Arx regulates guidance factors that are important for proper localization of various subsets of interneurons. Therefore, normal transcriptional repression by Arx is necessary in interneurons, and a polyalanine tract expansion leads to a partial loss of this repressive function, which is sufficient to disrupt NRCM

    SETD2 mutations in primary central nervous system tumors

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    Abstract Mutations in SETD2 are found in many tumors, including central nervous system (CNS) tumors. Previous work has shown these mutations occur specifically in high grade gliomas of the cerebral hemispheres in pediatric and young adult patients. We investigated SETD2 mutations in a cohort of approximately 640 CNS tumors via next generation sequencing; 23 mutations were detected across 19 primary CNS tumors. Mutations were found in a wide variety of tumors and locations at a broad range of allele frequencies. SETD2 mutations were seen in both low and high grade gliomas as well as non-glial tumors, and occurred in patients greater than 55 years of age, in addition to pediatric and young adult patients. High grade gliomas at first occurrence demonstrated either frameshift/truncating mutations or point mutations at high allele frequencies, whereas recurrent high grade gliomas frequently harbored subclones with point mutations in SETD2 at lower allele frequencies in the setting of higher mutational burdens. Comparison with the TCGA dataset demonstrated consistent findings. Finally, immunohistochemistry showed decreased staining for H3K36me3 in our cohort of SETD2 mutant tumors compared to wildtype controls. Our data further describe the spectrum of tumors in which SETD2 mutations are found and provide a context for interpretation of these mutations in the clinical setting

    Detecting Histologic & Clinical Glioblastoma Patterns of Prognostic Relevance

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    Glioblastoma is the most common and aggressive malignant adult tumor of the central nervous system, with a grim prognosis and heterogeneous morphologic and molecular profiles. Since adopting the current standard-of-care treatment 18 years ago, no substantial prognostic improvement has been noticed. Accurate prediction of patient overall survival (OS) from histopathology whole slide images (WSI) integrated with clinical data using advanced computational methods could optimize clinical decision-making and patient management. Here, we focus on identifying prognostically relevant glioblastoma characteristics from H&E stained WSI & clinical data relating to OS. The exact approach for WSI capitalizes on the comprehensive curation of apparent artifactual content and an interpretability mechanism via a weakly supervised attention-based multiple-instance learning algorithm that further utilizes clustering to constrain the search space. The automatically placed patterns of high diagnostic value classify each WSI as representative of short or long-survivors. Further assessment of the prognostic relevance of the associated clinical patient data is performed both in isolation and in an integrated manner, using XGBoost and SHapley Additive exPlanations (SHAP). Identifying tumor morphological & clinical patterns associated with short and long OS will enable the clinical neuropathologist to provide additional relevant prognostic information to the treating team and suggest avenues of biological investigation for understanding and potentially treating glioblastoma
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