Publications by authors named "Alice Taubes"

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 (apo) E4-related AD. We first established apoE-genotype-dependent transcriptomic signatures of AD by analyzing publicly-available human brain database.

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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 genotype-specific transcriptomic differences; however, these differences have not been explored at a single-cell level.

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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. 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.

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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.

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Despite its clear impact on Alzheimer's disease (AD) risk, apolipoprotein (apo) E4's contributions to AD etiology remain poorly understood. Progress in answering this and other questions in AD research has been limited by an inability to model human-specific phenotypes in an in vivo environment. Here we transplant human induced pluripotent stem cell (hiPSC)-derived neurons carrying normal apoE3 or pathogenic apoE4 into human apoE3 or apoE4 knockin mouse hippocampi, enabling us to disentangle the effects of apoE4 produced in human neurons and in the brain environment.

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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.

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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.

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Retinal tissue is damaged during inflammation in Multiple Sclerosis. We assessed molecular changes in inflamed murine retinal cultures by Raman spectroscopy. Partial Least Squares-Discriminant analysis (PLS-DA) was able to classify retina cultures as inflamed with high accuracy.

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