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  • Wiley  (4)
  • Morabito, Samuel  (4)
  • 1
    In: Alzheimer's & Dementia, Wiley, Vol. 18, No. S4 ( 2022-12)
    Abstract: Pick’s disease (PiD), a behavioral variant of frontotemporal dementia, is one of the common neurodegenerative dementia that is characterized by tau lesions. Despite the distinct tau aggregation observed in Pick’s disease compared with the tauopathy of Alzheimer’s disease (AD), the similarity in cognitive and behavioral impairments during the progression of the disease make their diagnosis challenging. What determines the differences and similarities between PiD and AD progression, especially at the epigenetic level, are largely unknown. We believe that recent advancement in single‐cell epigenomic profiling methods, Assay for Transposase‐Accessible Chromatin (ATAC) combined with high throughput sequencing, will enable us to map the chromatin‐regulatory landscapes of disease brains at a single‐cell resolution and enable us to understand underlying molecular changes in these diseases. Method In the present study, we have isolated single nuclei from the frontal cortex region and performed single‐nucleus ATAC sequencing (snATAC‐seq) of 198,722 nuclei to generate cell‐type specific chromatin accessibility profiles of postmortem brains of PiD and AD patients and to uncover their cellular heterogeneity and similarity. We used cellranger to process the paired‐end FastQ reads of each sample to obtain its chromatin accessibility count matrix. Next, we utilized ArchR and Signac pipelines to generate 501‐bp fixed‐width peak regions and performed downstream differential accessible regions analysis. Quality control was also performed to remove the contribution of low‐quality nuclei. Result We constructed chromatin accessibility profiles from 19,690 nuclei from PiD patients, 59,148 nuclei from AD patients, and 119,884 nuclei from healthy controls. We applied UMAP dimensionality reduction and clustered nuclei through open chromatin region to the batch‐corrected epigenomic datasets. We identified seven distinct cell types, including astrocyte, excitatory neurons, inhibitory neurons, microglia, oligodendrocytes, OPC, and pericyte/endothelial cells, and we applied pseudotime trajectory analysis to characterize disease‐associated cell state in both AD and PiD at the epigenomics level. Conclusion Our data identified the cell‐type‐specific open chromatin accessible regions in AD and PiD brains. Although the causative molecular mechanisms of AD and PiD remain unknown, our work helps to identify shared epigenomic changes in AD and PiD, especially in regards to cell‐type‐specific genomic loci with disease risk.
    Type of Medium: Online Resource
    ISSN: 1552-5260 , 1552-5279
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 2201940-6
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  • 2
    In: Alzheimer's & Dementia, Wiley, Vol. 16, No. S3 ( 2020-12)
    Abstract: Alzheimer’s disease (AD) is a devastating neurodegenerative disease, characterized by changes in cell‐type proportions and marked alterations of the epigenome and transcriptome. Recent “bulk” tissue RNA‐seq on thousands of postmortem AD brain samples by AMP‐AD consortia has shed light on new AD biology. Unfortunately, cell‐type specific disease biology is completely missed or averaged out using conventional “bulk” tissue RNA‐seq approaches. Single‐cell transcriptomics using single‐nuclei RNA‐seq (snRNA‐seq) and epigenomics (single‐nuclei ATAC‐seq) promises to capture cell‐type heterogeneity and unravel relevant biology related to cell‐to‐cell variability. Such single‐cell approaches have been recently used in psychiatric diseases through PsychENCODE consortia and integrated with bulk tissue RNA‐seq to understand cellular heterogeneity in these diseases. Our work is the first to define single‐nuclear clusters based on open‐chromatin (snATAC‐seq) and gene‐expression (snRNA‐seq) that are dysregulated during the progression of the disease. Method Using snATAC‐seq, we have profiled more than 150,000 single‐nuclei open chromatin profiles from normal human (n = 10) and late‐stage AD frontal cortex (n = 11) samples. We have also used same samples to further profile gene‐expression changes at single‐cell resolution using snRNA‐seq from more than 70,000 nuclei. In addition, we have performed bulk‐tissue RNA‐seq from control and AD frontal cortex (n = 50/group) samples and developed gene co‐expression methods to integrate bulk‐tissue and snRNA‐seq to unravel cell‐type specific co‐expression changes altered in AD. Result Our analysis has identified distinct cell‐clusters based on both open‐chromatin (snATAC‐seq) and transcriptomics (snRNA‐seq) which are altered in late‐stage AD. We have identified several oligodendrocyte cell‐clusters which are increased only during disease progression. Pseudo‐time analysis of data indicates that AD‐specific oligodendrocyte clusters have a distinct developmental trajectory that define the terminal fate of these clusters. In addition, co‐expression analysis with bulk‐tissue RNA‐seq and snRNA‐seq data has identified functional modules (groups of genes) that are dysregulated in these AD‐specific oligodendrocyte clusters. These data highlight the potential role of myelination deficits that occur during the progression of disease. Conclusion Our tour‐de‐force work has identified distinct oligodendrocyte cell‐clusters that are altered in late‐stage AD. We have also identified core regulatory networks in these oligodendroglia cells that promises to provide novel therapeutic targets for AD.
    Type of Medium: Online Resource
    ISSN: 1552-5260 , 1552-5279
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2020
    detail.hit.zdb_id: 2201940-6
    Location Call Number Limitation Availability
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  • 3
    In: Alzheimer's & Dementia, Wiley, Vol. 17, No. S3 ( 2021-12)
    Type of Medium: Online Resource
    ISSN: 1552-5260 , 1552-5279
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2021
    detail.hit.zdb_id: 2201940-6
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  • 4
    In: Alzheimer's & Dementia, Wiley, Vol. 18, No. S3 ( 2022-12)
    Abstract: Transcriptomic studies of Alzheimer's disease (AD) have identified both tissue‐level and cell‐type specific gene expression changes. However, with both "bulk"‐tissue and single‐cell approaches, we lose pertinent spatial information, such as cell‐to‐cell proximity or proximity to pathological features. Recently several techniques have emerged, aiming to profile gene expression while preserving the spatial architecture, and we have leveraged one of these techniques—spatial transcriptomics—to interrogate AD gene expression changes in the 5XFAD, an amyloid mouse model, in a spatial and temporal manner. Methods We generated spatial transcriptomic (10x Genomics Visium) data from 5XFAD and wildtype mice at the ages of 4, 6, 8, and 12 months (n = 80 total samples, sex‐balanced). Prior to generating libraries, we stained our tissue sections with Amylo‐glo and the conformation‐specific antibody OC to analyze gene expression changes in spatial relativity to amyloid pathology. Results We profiled 18,000‐20,000 total genes per sample with 1,800‐2,700 genes per spatial spot and identified brain region‐specific transcriptionally distinct clusters. We also examined the spatial distribution of AD risk genes, identified by GWAS, throughout the disease progression. Further, we identified gene expression changes spatially related to amyloid pathology localization. Conclusions We have characterized the 5XFAD transcriptome, identifying spatiotemporal AD gene expression changes and providing further insight into the role of amyloid pathology in the modulation of gene expression in AD.
    Type of Medium: Online Resource
    ISSN: 1552-5260 , 1552-5279
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 2201940-6
    Location Call Number Limitation Availability
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