14 research outputs found

    Early retinal neurodegeneration and impaired Ran-mediated nuclear import of TDP-43 in progranulin-deficient FTLD

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    Frontotemporal dementia (FTD) is the most common cause of dementia in people under 60 yr of age and is pathologically associated with mislocalization of TAR DNA/RNA binding protein 43 (TDP-43) in approximately half of cases (FLTD-TDP). Mutations in the gene encoding progranulin (GRN), which lead to reduced progranulin levels, are a significant cause of familial FTLD-TDP. Grn-KO mice were developed as an FTLD model, but lack cortical TDP-43 mislocalization and neurodegeneration. Here, we report retinal thinning as an early disease phenotype in humans with GRN mutations that precedes dementia onset and an age-dependent retinal neurodegenerative phenotype in Grn-KO mice. Retinal neuron loss in Grn-KO mice is preceded by nuclear depletion of TDP-43 and accompanied by reduced expression of the small GTPase Ran, which is a master regulator of nuclear import required for nuclear localization of TDP-43. In addition, TDP-43 regulates Ran expression, likely via binding to its 3′-UTR. Augmented expression of Ran in progranulin-deficient neurons restores nuclear TDP-43 levels and improves their survival. Our findings establish retinal neurodegeneration as a new phenotype in progranulin-deficient FTLD, and suggest a pathological loop involving reciprocal loss of Ran and nuclear TDP-43 as an underlying mechanism

    Insights into Computational Drug Repurposing for Neurodegenerative Disease

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    Computational drug repurposing has the ability to remarkably reduce drug development time and cost in an era where these factors are prohibitively high. Several examples of successful repurposed drugs exist in fields such as oncology, diabetes, leprosy, inflammatory bowel disease, among others, however computational drug repurposing in neurodegenerative disease has presented several unique challenges stemming from the lack of validation methods and difficulty in studying heterogenous diseases of aging. Here, we examine existing approaches to computational drug repurposing, including molecular, clinical, and biophysical methods, and propose data sources and methods to advance computational drug repurposing in neurodegenerative disease using Alzheimer's disease as an example

    Sex-Specific Cross Tissue Meta-Analysis Identifies Immune Dysregulation in Women With Alzheimer's Disease.

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    Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the most common cause of dementia in the United States. In spite of evidence of females having a greater lifetime risk of developing Alzheimer's Disease (AD) and greater apolipoprotein E4-related (APOE ε4) AD risk compared to males, molecular signatures underlying these differences remain elusive. Methods: We took a meta-analysis approach to study gene expression in the brains of 1,084 AD patients and age-matched controls and whole blood from 645 AD patients and age-matched controls in seven independent datasets. Sex-specific gene expression patterns were investigated through use of gene-based, pathway-based and network-based approaches. The ability of a sex-specific AD gene expression signature to distinguish Alzheimer's disease from healthy controls was assessed using a linear support vector machine model. Cell type deconvolution from whole blood gene expression data was performed to identify differentially regulated cells in males and females with AD. Results: Strikingly gene-expression, network-based analysis and cell type deconvolution approaches revealed a consistent immune signature in the brain and blood of female AD patients that was absent in males. In females, network-based analysis revealed a coordinated program of gene expression involving several zinc finger nuclease genes related to Herpes simplex viral infection whose expression was modulated by the presence of the APOE ε4 allele. Interestingly, this gene expression program was missing in the brains of male AD patients. Cell type deconvolution identified an increase in neutrophils and naïve B cells and a decrease in M2 macrophages, memory B cells, and CD8+ T cells in AD samples compared to controls in females. Interestingly, among males with AD, no significant differences in immune cell proportions compared to controls were observed. Machine learning-based classification of AD using gene expression from whole blood in addition to clinical features produced an improvement in classification accuracy upon stratifying by sex, achieving an AUROC of 0.91 for females and 0.80 for males. Conclusion: These results help identify sex and APOE ε4 genotype-specific transcriptomic signatures of AD and underscore the importance of considering sex in the development of biomarkers and therapeutic strategies for AD

    Neuronal ApoE upregulates MHC-I expression to drive selective neurodegeneration in Alzheimer’s disease

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    Selective neurodegeneration is a critical causal factor in Alzheimer's disease (AD); however, the mechanisms that lead some neurons to perish, whereas others remain resilient, are unknown. We sought potential drivers of this selective vulnerability using single-nucleus RNA sequencing and discovered that ApoE expression level is a substantial driver of neuronal variability. Strikingly, neuronal expression of ApoE-which has a robust genetic linkage to AD-correlated strongly, on a cell-by-cell basis, with immune response pathways in neurons in the brains of wild-type mice, human ApoE knock-in mice and humans with or without AD. Elimination or over-expression of neuronal ApoE revealed a causal relationship among ApoE expression, neuronal MHC-I expression, tau pathology and neurodegeneration. Functional reduction of MHC-I ameliorated tau pathology in ApoE4-expressing primary neurons and in mouse hippocampi expressing pathological tau. These findings suggest a mechanism linking neuronal ApoE expression to MHC-I expression and, subsequently, to tau pathology and selective neurodegeneration

    Bioinformatics Analysis of Publicly Available Single-Nuclei Transcriptomics Alzheimer's Disease Datasets Reveals APOE Genotype-Specific Changes Across Cell Types in Two Brain Regions.

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    Alzheimer's Disease (AD) is a complex neurodegenerative disease that gravely affects patients and imposes an immense burden on caregivers. Apolipoprotein E4 (APOE4) has been identified as the most common genetic risk factor for AD, yet the molecular mechanisms connecting APOE4 to AD are not well understood. Past transcriptomic analyses in AD have revealed APOE genotype-specific transcriptomic differences; however, these differences have not been explored at a single-cell level. To elucidate more complex APOE genotype-specific disease-relevant changes masked by the bulk analysis, we leverage the first two single-nucleus RNA sequencing AD datasets from human brain samples, including nearly 55,000 cells from the prefrontal and entorhinal cortices. In each brain region, we performed a case versus control APOE genotype-stratified differential gene expression analysis and pathway network enrichment in astrocytes, microglia, neurons, oligodendrocytes, and oligodendrocyte progenitor cells. We observed more global transcriptomic changes in APOE4 positive AD cells and identified differences across APOE genotypes primarily in glial cell types. Our findings highlight the differential transcriptomic perturbations of APOE isoforms at a single-cell level in AD pathogenesis and have implications for precision medicine development in the diagnosis and treatment of AD

    Experimental and real-world evidence supporting the computational repurposing of bumetanide for APOE4-related Alzheimer’s disease

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    The evident genetic, pathological and clinical heterogeneity of Alzheimer’s disease (AD) poses challenges for traditional drug development. We conducted a computational drug-repurposing screen for drugs to treat apolipoprotein E4 (APOE4)-related AD. We first established APOE genotype-dependent transcriptomic signatures of AD by analyzing publicly available human brain databases. We then queried these signatures against the Connectivity Map database, which contains transcriptomic perturbations of more than 1,300 drugs, to identify those that best reverse APOE genotype-specific AD signatures. Bumetanide was identified as a top drug for APOE4-related AD. Treatment of APOE4-knock-in mice without or with amyloid β (Aβ) accumulation using bumetanide rescued electrophysiological, pathological or cognitive deficits. Single-nucleus RNA sequencing revealed transcriptomic reversal of AD signatures in specific cell types in these mice, a finding confirmed in APOE4 induced pluripotent stem cell (iPSC)-derived neurons. In humans, bumetanide exposure was associated with a significantly lower AD prevalence in individuals over the age of 65 years in two electronic health record databases, suggesting the effectiveness of bumetanide in preventing AD.National Institutes of HealthDepto. de Estadística y Ciencia de los DatosFac. de Estudios EstadísticosTRUEpu
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