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  • 1
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2024
    In:  Neuropsychopharmacology Vol. 49, No. 1 ( 2024-01), p. 303-304
    In: Neuropsychopharmacology, Springer Science and Business Media LLC, Vol. 49, No. 1 ( 2024-01), p. 303-304
    Type of Medium: Online Resource
    ISSN: 0893-133X , 1740-634X
    RVK:
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2024
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  • 2
    In: Neurobiology of Aging, Elsevier BV, Vol. 36, No. 11 ( 2015-11), p. 3079-3089
    Type of Medium: Online Resource
    ISSN: 0197-4580
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2015
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    SSG: 12
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  • 3
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2021
    In:  Molecular Neurodegeneration Vol. 16, No. 1 ( 2021-09-17)
    In: Molecular Neurodegeneration, Springer Science and Business Media LLC, Vol. 16, No. 1 ( 2021-09-17)
    Abstract: In response to extracellular and intracellular stressors, the nucleus and nuclear compartments undergo distinct molecular changes to maintain cell homeostasis. In the context of Alzheimer’s disease, misfolded proteins and various cellular stressors lead to profound structural and molecular changes at the nucleus. This review summarizes recent research on nuclear alterations in AD development, from the nuclear envelope changes to chromatin and epigenetic regulation and then to common nuclear stress responses. Finally, we provide our thoughts on the importance of understanding cell-type-specific changes and identifying upstream causal events in AD pathogenesis and highlight novel sequencing and gene perturbation technologies to address those challenges.
    Type of Medium: Online Resource
    ISSN: 1750-1326
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
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  • 4
    In: Frontiers in Endocrinology, Frontiers Media SA, Vol. 13 ( 2023-1-16)
    Abstract: There is growing interest in the role of DNA methylation in regulating the transcription of mitochondrial genes, particularly in brain disorders characterized by mitochondrial dysfunction. Here, we present a novel approach to interrogate the mitochondrial DNA methylome at single base resolution using targeted bisulfite sequencing. We applied this method to investigate mitochondrial DNA methylation patterns in post-mortem superior temporal gyrus and cerebellum brain tissue from seven human donors. Results We show that mitochondrial DNA methylation patterns are relatively low but conserved, with peaks in DNA methylation at several sites, such as within the D-LOOP and the genes MT-ND2 , MT-ATP6 , MT-ND4 , MT-ND5 and MT-ND6 , predominantly in a non-CpG context. The elevated DNA methylation we observe in the D-LOOP we validate using pyrosequencing. We identify loci that show differential DNA methylation patterns associated with age, sex and brain region. Finally, we replicate previously reported differentially methylated regions between brain regions from a methylated DNA immunoprecipitation sequencing study. Conclusions We have annotated patterns of DNA methylation at single base resolution across the mitochondrial genome in human brain samples. Looking to the future this approach could be utilized to investigate the role of mitochondrial epigenetic mechanisms in disorders that display mitochondrial dysfunction.
    Type of Medium: Online Resource
    ISSN: 1664-2392
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
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  • 5
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 384, No. 6698 ( 2024-05-24)
    Abstract: Genome-wide association studies (GWASs) have identified thousands of loci associated with neurodevelopmental and psychiatric disorders, yet our lack of understanding of the target genes and biological mechanisms underlying these associations remains a major challenge. GWAS signals for many neuropsychiatric disorders, including autism spectrum disorder, schizophrenia, and bipolar disorder, are particularly enriched for gene-regulatory elements active during human brain development. However, the lack of a unified population-scale, ancestrally diverse gene-regulatory atlas of human brain development has been a major obstacle for the functional assessment of top loci and post-GWAS integrative analyses. RATIONALE To address this critical gap in knowledge, we have uniformly processed and systematically characterized gene, isoform, and splicing quantitative trait loci (cumulatively referred to as xQTLs) in the developing human brain across 672 unique samples from 4 to 39 postconception weeks spanning European, African-American, and Latino/admixed American ancestries). With this expanded atlas, we sought to specifically localize the timing and molecular features mediating the greatest proportion of neuropsychiatric GWAS heritability, to prioritize candidate risk genes and mechanisms for top loci, and to compare with analogous results using larger adult brain functional genomic reference panels. RESULTS In total, we identified 15,752 genes harboring a gene, isoform and/or splicing cis -xQTL, including 49 genes associated with four large, recurrent inversions. Highly concordant effect sizes were observed across populations, and our diverse reference panel improved resolution to fine-map underlying candidate causal regulatory variants. Substantially more genes were found to harbor QTLs in the first versus second trimester of brain development, with a notable drop in gene expression and splicing heritability observed from 10 to 18 weeks coinciding with a period of rapidly increasing cellular heterogeneity in the developing brain. Isoform-level regulation, particularly in the second trimester, mediated a greater proportion of heritability across multiple psychiatric GWASs compared with gene expression regulation. Through colocalization and transcriptome-wide association studies, we prioritized biological mechanisms for ~60% of GWAS loci across five neuropsychiatric disorders, with 〉 2-fold more colocalizations observed compared with larger adult brain functional genomic reference panels. We observed convergence between common and rare-variant associations, including a cryptic splicing event in the high-confidence schizophrenia risk gene SP4 . Finally, we constructed a comprehensive set of developmentally regulated gene and isoform coexpression networks harboring unique cell-type specificity and genetic enrichments. Leveraging this cell-type specificity, we identified 〉 8000 module interaction QTLs, many of which exhibited additional GWAS colocalizations. Overall, neuropsychiatric GWASs and rare variant signals localized more strongly within maturing excitatory- and interneuron-associated modules compared with those enriched for neural progenitor cell types. Results can be visualized at devbrainhub.gandallab.org . CONCLUSION We have generated a large-scale, cross-population resource of gene, isoform, and splicing regulation in the developing human brain, providing comprehensive developmental and cell-type-informed mechanistic insights into the genetic underpinnings of complex neurodevelopmental and psychiatric disorders. A comprehensive transcriptome regulatory atlas of the developing human neocortex. RNA-sequencing and single-nucleotide polymorphism genotypes were uniformly integrated within a diverse set of 672 samples of the developing human neocortex. Gene regulation was systematically assessed across the gene, isoform expression, and local splicing levels, yielding 15,752 genes harboring a significant xQTL. Gene regulation was highly dynamic, with a substantial drop observed in gene expression heritability over development. Integrative analyses with neuropsychiatric GWASs uncovered hundreds of candidate risk genes and mechanisms, providing insights into the cellular, molecular, and developmental specificity underlying disease-associated genetic variation.
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
    RVK:
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    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2024
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  • 6
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 384, No. 6698 ( 2024-05-24)
    Abstract: The cortical layers of the human neocortex were classically defined by histological distinction of cell types according to size, shape, and density. However, emerging single-cell and spatially resolved transcriptomic technologies have facilitated the identification of molecularly defined cell populations and spatial domains that move beyond classic cell type definitions and cytoarchitectural boundaries. RATIONALE Given the close relationship between brain structure and function, assigning gene expression to distinct anatomical subdivisions and cell populations within the human brain improves our understanding of these highly specialized regions and how they contribute to brain disorders. We sought to create a data-driven molecular neuroanatomical map of the human dorsolateral prefrontal cortex (DLPFC) at cellular resolution using unsupervised transcriptomic approaches to identify spatial domains associated with neuropsychiatric and neurodevelopmental disorders. RESULTS We generated complementary single-cell and spatial transcriptomic data from 10 adult, neurotypical control donors across the anterior-posterior axis of the DLPFC. Unsupervised spatial clustering revealed fine-resolution data-driven spatial domains with distinct molecular signatures, including deep cortical sublayers and a vasculature-enriched meninges layer. Cell type clustering of single-nucleus RNA-sequencing (snRNA-seq) data revealed 29 distinct populations across seven broad neuronal and glial cell types, including 15 excitatory subpopulations. To add cellular resolution to our data-driven molecular atlas, we took two complementary approaches to integrate single-cell and spatial transcriptomics data. First, we used our previously developed spatial registration framework to map the paired snRNA-seq data to specific unsupervised spatial domains, providing anatomy-based laminar identities to excitatory neuron subpopulations. Second, we used three existing spot-level deconvolution tools to computationally predict the cell type composition of spatial domains on the basis of the paired snRNA-seq reference data. These tools were rigorously benchmarked against a newly generated gold-standard reference dataset acquired with the Visium Spatial Proteogenomics assay, which enabled us to label and quantify four broad cell types across the DLPFC on the basis of protein marker expression, including neurons, oligodendrocytes, astrocytes, and microglia. Using these approaches, we identified the proportion of cell types in each spatial domain and showed that these proportions were consistent across individuals and the DLPFC anterior-posterior axis. We demonstrated the clinical relevance of our highly integrated molecular atlas using cell-cell communication analyses to spatially map cell type–specific ligand-receptor interactions associated with genetic risk for schizophrenia (SCZ). For example, we mapped the interaction between ephrin ligand EFNA5 and ephrin receptor EPHA5 to deep-layer excitatory neuron subtypes and spatial domains. To leverage the rich single-cell data generated by PsychENCODE Consortium companion studies, we spatially registered eight DLPFC snRNA-seq datasets collected across the consortium in the context of different neuropsychiatric disorders and demonstrated a convergence of excitatory, inhibitory, and non-neuronal cell types in relevant spatial domains. Using PsychENCODE Consortium and other publicly available gene sets, we further demonstrated the clinical relevance of our data-driven molecular atlas by mapping the enrichment of cell types and genes associated with neuropsychiatric disorders—including autism spectrum disorder, posttraumatic stress disorder, and major depressive disorder—to discrete spatial domains. CONCLUSION Our study identified high-resolution, data-driven spatial domains across the human DLPFC, providing anatomical context for cell type–specific gene expression changes associated with neurodevelopmental disorders and psychiatric illness. We provide a roadmap for the implementation and biological validation of unsupervised spatial clustering approaches in other regions of the human brain. We share interactive data resources for the scientific community to further interrogate molecular mechanisms associated with complex brain disorders. Data-driven molecular anatomy of the human DLPFC. Integrated single-nucleus and spatial transcriptomics data were generated across the anterior-posterior axis of the human DLPFC from 10 neurotypical control donors to create a data-driven molecular neuroanatomical atlas of the neocortex identifying spatial domains. Integrative analyses revealed distinct cell type compositions, cell-cell interactions, and colocalization of ligand-receptor pairs linked to schizophrenia genetic risk. t-SNE, t -distributed stochastic neighbor embedding. [Created with BioRender.com .]
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
    RVK:
    RVK:
    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2024
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  • 7
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 384, No. 6698 ( 2024-05-24)
    Abstract: Single-cell genomics offers a powerful method to understand how variants influence gene expression, especially across the numerous cell types in the human brain. Moreover, it can potentially refine our understanding of the regulatory mechanisms underlying brain-related traits. However, population-scale cohorts with a wide range of brain phenotypes are needed to infer key associations among variants and to develop models of regulation at the single-cell scale. RATIONALE To address this, the PsychENCODE Consortium performed many single-cell experiments [single-nucleus RNA sequencing (snRNA-seq), snATAC-seq (ATAC, assay for transposase-accessible chromatin), and snMultiome plus genotyping] and computational analyses on prefrontal-cortex samples of adults with a range of brain-related disorders such as schizophrenia, autism spectrum disorder, bipolar disorder, and Alzheimer’s disease, as well as controls. RESULTS We developed a uniformly processed resource comprising 〉 2.8 million nuclei from 388 individuals ( brainscope.psychencode.org ). The resource is based on harmonized cell typing, with 28 neuronal and non-neuronal cell types (registered against BICCN). Partitioning the expression variation within these types revealed higher cell-type variability than interindividual variability; this pattern was amplified in neurotransmitter and neurorelated drug-target genes such as CNR1 . Integration of expression and genotype data revealed 〉 1.4 million single-cell expression quantitative trait loci (eQTLs), many of which were not seen in bulk gene-expression datasets and a subset of which involved variants related to brain disorders. Moreover, we found that expression patterns across cell types recapitulated the spatial relationships of excitatory neurons across cortical layers and enabled the identification of “dynamic eQTLs,” with smooth changes in regulatory effect across cortical layers. The chromatin datasets in the resource allowed for identification of 〉 550,000 single-cell cis-regulatory elements, which were enriched at loci linked to brain-related traits. Combining expression, chromatin, and eQTL datasets, we built cell type–specific gene regulatory networks. In these, information-flow bottleneck genes tended to be specific to particular cell types, in contrast to hubs. We also developed cell-to-cell communication networks, which highlighted differences in signaling pathways in disorders, including altered Wnt signaling in schizophrenia and bipolar disorder. We developed an integrative deep-learning model with embedded layers for genotypes, eQTLs, and regulatory and cell-to-cell communications networks. The model allowed for accurate imputation of cell type–specific expression and phenotype from genotype. It prioritized 〉 250 risk genes and drug targets for brain-related disorders along with associated cell types. Simulated perturbation of individual genes led to predicted expression changes mirroring those for disease cases, suggesting drug targets. Lastly, we constructed predictive models for aging and Alzheimer’s disease, showing, for instance, that expression and chromatin in specific neurons were highly predictive of an individual’s age. CONCLUSION Our population-scale single-cell resource for the human brain can help facilitate precision-medicine approaches for neuropsychiatric disorders, especially by prioritizing follow-up genes and drug targets linked to cell types. brainSCOPE resource. snRNA-seq and snATAC-seq from 388 individuals allowed assessment of regulatory elements (scCREs), single-cell eQTLs (scQTLs), and gene regulatory networks across cell types. These were integrated into a model (LNCTP, Linear Network of Cell Type Phenotypes) to predict phenotypes and prioritize genes and cell types.
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
    RVK:
    RVK:
    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2024
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  • 8
    In: American Journal of Psychiatry, American Psychiatric Association Publishing, Vol. 180, No. 10 ( 2023-10-01), p. 739-754
    Type of Medium: Online Resource
    ISSN: 0002-953X , 1535-7228
    RVK:
    Language: English
    Publisher: American Psychiatric Association Publishing
    Publication Date: 2023
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  • 9
    In: Alzheimer's & Dementia, Wiley, Vol. 19, No. S12 ( 2023-12)
    Abstract: Alzheimer’s disease (AD) pathologies include extracellular amyloid‐beta (A‐beta) plaques, intracellular neurofibrillary tangles, neuronal cell loss, and chronic glial inflammation. Recent studies profiling gene expression in human postmortem brain tissue have uncovered cell‐type‐specific changes in AD. However, these studies did not provide simultaneous, direct measurements of AD pathologies in the native microenvironment. Method To this end, we applied the 10X Genomics Visium platform to post‐mortem dorsolateral prefrontal cortex (DLPFC) from 20 ROSMAP participants with or without AD dementia. In total, we obtained spatial transcriptomic (ST) data for ∼260,000 tissue microdomains (“spots” comprised of ∼1‐10 cells). Result We clustered spots and annotated clusters according to expression of genes with known enrichment in anatomical layers (i.e. cortical layers 1‐6, meninges, and white matter). We deconvoluted the cell type(s) comprising each spot using cell2location, and found significant changes in the abundance of specific cell types in AD. Using a two‐stage pseudobulk regression approach, we identified hundreds of genes whose spatial expression is significantly associated with nearby A‐beta plaques and/or astrocyte reactivity (GFAP). A‐beta‐associated genes are enriched for diverse biological processes, including translation, metabolism, inflammation, gliosis, and immune cell infiltration. We also detected genes that distinguish A‐beta plaques surrounded by reactive glial nets. We validated the spatial expression pattern of a subset of plaque‐associated genes by RNAScope. Conclusion In summary, our study reveals genes and pathways that shape molecular states in the spatial context of AD pathology. Our data represent a comprehensive application of ST technology in AD brains, providing a valuable resource for the research community.
    Type of Medium: Online Resource
    ISSN: 1552-5260 , 1552-5279
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2023
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  • 10
    In: Alzheimer's & Dementia, Wiley, Vol. 20, No. 1 ( 2024-01), p. 525-537
    Abstract: The secreted phosphoprotein 1 ( SPP1 ) gene expressed by CD11c + cells is known to be associated with microglia activation and neuroinflammatory diseases. As most studies rely on mouse models, we investigated these genes and proteins in the cortical brain tissue of older adults and their role in Alzheimer's disease (AD) and related disorders. METHODS We leveraged protein measurements, single‐nuclei, and RNASeq data from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP) of over 1200 samples for association analysis. RESULTS Expression of  SPP1  and its encoded protein osteopontin were associated with faster cognitive decline and greater odds of common neuropathologies. At single‐cell resolution,  integrin subunit alpha X ( ITGAX ) was highly expressed in microglia, where specific subpopulations were associated with AD and cerebral amyloid angiopathy. DISCUSSION The study provides evidence of SPP1  and  ITGAX  association with cognitive decline and common neuropathologies identifying a microglial subset associated with disease.
    Type of Medium: Online Resource
    ISSN: 1552-5260 , 1552-5279
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2024
    detail.hit.zdb_id: 2211627-8
    detail.hit.zdb_id: 2201940-6
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