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Alzheimer’s disease (AD) is the leading cause of dementia in older adults. Although AD progression is characterized by stereotyped accumulation of proteinopathies, the affected cellular populations remain understudied. Here we use multiomics, spatial genomics and reference atlases from the BRAIN Initiative to study middle temporal gyrus cell types in 84 donors with varying AD pathologies. This cohort includes 33 male donors and 51 female donors, with an average age at time of death of 88 years. We used quantitative neuropathology to place donors along a disease pseudoprogression score. Pseudoprogression analysis revealed two disease phases: an early phase with a slow increase in pathology, presence of inflammatory microglia, reactive astrocytes, loss of somatostatin + inhibitory neurons, and a remyelination response by oligodendrocyte precursor cells; and a later phase with exponential increase in pathology, loss of excitatory neurons and Pvalb + and Vip + inhibitory neuron subtypes. These findings were replicated in other major AD studies. The affected cellular populations during Alzheimer’s disease progression remain understudied. Here the authors use a cohort of 84 donors, quantitative neuropathology and multimodal datasets from the BRAIN Initiative. Their pseudoprogression analysis revealed two disease phases.

Background Dysfunction of the Basal Ganglia is implicated in several neurodegenerative diseases such as Parkinson’s and Huntington’s. A substructure of the Basal Ganglia, the caudate nucleus, is observed to have diffuse amyloid plaques in Alzheimer’s disease (AD), in Thal phase III. Additionally, literature suggests the presence of AD ‐related tangles. Functionally, the caudate is known to be involved in cognitive functions impacted by AD such as memory. The caudate also receives signals and has efferent projections to significantly affected regions in AD such as cortex and hippocampus respectively. Despite these connections, caudate nucleus remains understudied in AD. Method AT8 (pTau) and 6e10 (Aβ) immunohistochemical staining was performed on the caudate from 42 donors with only canonical proteionopathies and no comorbities. Single nucleus RNA and ATAC‐seq (multiome or singleome) was collected for all donors in the cohort. Spatial transcriptomics was performed on a subset of 5 Thal I‐III and 5 Thal IV‐V donors, with post‐hoc immunostaining of AT8 and 6e10. Cells were labeled using deep learning with a reference caudate dataset from healthy BRAIN Initiative donors. Changes in expression and cell type abundance were modeled in terms of levels of AT8 and 6e10 using Bayesian and general linear mixed effects models respectively. Result We identified caudate specific pTau associated abundance increases in astrocyte and microglia types. These microglia types were not the stereotypical disease associated types described in cortex. We also identified pTau associated abundance decreases in oliogodendrocyte subtypes consistent with cortex. Almost all neuronal populations in the caudate show little change in their cellular abundances. Most effects in cellular composition or differential expression were observed specifically with respect to level of pTau and not Aβ. Conclusion AD’s impact in caudate head contrasts with established effects on the cortex. Regionally unique increases in certain non‐neuronal populations suggest a caudate specific response to AD. Additionally, little neuronal loss, even with respect to significant pTau pathology suggests either environmental or cellular factors that confer resilience, or distinct pTau conditions in the caudate. Finally, our data suggests that the predominantly diffuse plaques in caudate are not sufficient for a plaque induced response in microglia.

Dysfunction of the Basal Ganglia is implicated in several neurodegenerative diseases such as Parkinson's and Huntington's. A substructure of the Basal Ganglia, the caudate nucleus, is observed to have diffuse amyloid plaques in Alzheimer's disease (AD), in Thal phase III. Additionally, literature suggests the presence of AD -related tangles. Functionally, the caudate is known to be involved in cognitive functions impacted by AD such as memory. The caudate also receives signals and has efferent projections to significantly affected regions in AD such as cortex and hippocampus respectively. Despite these connections, caudate nucleus remains understudied in AD. AT8 (pTau) and 6e10 (Aβ) immunohistochemical staining was performed on the caudate from 42 donors with only canonical proteionopathies and no comorbities. Single nucleus RNA and ATAC-seq (multiome or singleome) was collected for all donors in the cohort. Spatial transcriptomics was performed on a subset of 5 Thal I-III and 5 Thal IV-V donors, with post-hoc immunostaining of AT8 and 6e10. Cells were labeled using deep learning with a reference caudate dataset from healthy BRAIN Initiative donors. Changes in expression and cell type abundance were modeled in terms of levels of AT8 and 6e10 using Bayesian and general linear mixed effects models respectively. We identified caudate specific pTau associated abundance increases in astrocyte and microglia types. These microglia types were not the stereotypical disease associated types described in cortex. We also identified pTau associated abundance decreases in oliogodendrocyte subtypes consistent with cortex. Almost all neuronal populations in the caudate show little change in their cellular abundances. Most effects in cellular composition or differential expression were observed specifically with respect to level of pTau and not Aβ. AD's impact in caudate head contrasts with established effects on the cortex. Regionally unique increases in certain non-neuronal populations suggest a caudate specific response to AD. Additionally, little neuronal loss, even with respect to significant pTau pathology suggests either environmental or cellular factors that confer resilience, or distinct pTau conditions in the caudate. Finally, our data suggests that the predominantly diffuse plaques in caudate are not sufficient for a plaque induced response in microglia.

Image-based spatial transcriptomics platforms are powerful tools often used to identify cell populations and describe gene expression in intact tissue. Spatial experiments return large, high-dimensional datasets and several open-source software packages are available to facilitate analysis and visualization. The outputs of spatial transcriptomics platforms are typically imperfect. For example, local variations in transcript detection probability are common. Software tools to characterize imperfections and their impact on downstream analyses are lacking so the data quality is assessed manually, a laborious and often a subjective process. Here we describe imperfections in a dataset of 641 fresh-frozen adult mouse brain sections collected using the Vizgen MERSCOPE. Common imperfections included the local loss of tissue from the section, tissue outside the imaging volume due to detachment from the coverslip, transcripts missing due to dropped images, varying detection probability through space, and differences in transcript detection probability between experiments. We describe the incidence of each imperfection and the likely impact on the accuracy of cell type labels. We develop MerQuaCo, open-source code that detects and quantifies imperfections without user input, facilitating the selection of sections for further analysis with existing packages. Together, our results and MerQuaCo facilitate rigorous, objective assessment of the quality of spatial transcriptomics results.

The human neocortex underlies higher cognition and is the engine of complex thought. Yet our understanding of its neuronal diversity is limited by sparse access to tissue, inconsistent sampling across studies, and a lack of multiple modality data. Although single-cell transcriptomic taxonomies are an important framework for characterizing cell type diversity, transcriptomic information alone cannot reveal the cellular properties that define neuronal computations. To address this, we performed Patch-seq, a method for collecting Morphology, Electrophysiology, and Transcriptomic data from a single neuron. We focused on glutamatergic, neocortical, excitatory neurons, the principal long-range projecting neurons of the cortex, and systematically integrated their morphoelectric features with transcriptomic identity. In combination with spatial transcriptomic data, we interrogated 39 of 42 transcriptomically-defined neuron types with a layer-centric perspective. Morphoelectric properties, such as cortical depth, apical dendrite structure, and excitability clearly distinguish transcriptomic subclasses and support many finer transcriptomic types. Morphoelectric properties are influenced by spatial location in supragranular layers, while deeper layers exhibit greater heterogeneity. Cross-species comparisons reveal conserved subclass organization but pronounced differences in apical dendrite arborization between mouse and human, and surprising similarities between human and macaque. Together, these datasets provide a unified multimodal reference that advances our understanding of human cortical circuitry and establishes a foundation for experimental and computational studies of human brain function and disease.

Aβ presence in the caudate nucleus (Ca) partially defines Thal stage III in Alzheimer's disease (AD), but little is known about AD's cellular impact on the region. Leveraging a public basal ganglia taxonomy of cellular populations, we generated a cellular resolution atlas of AD-associated pathological changes in Ca. Unlike cortex, we found that Ca AD pathology is dominated by two key features: phosphorylated tau (pTau)-containing neuropil threads enriched near oligodendrocytes in white matter tracts and amyloid-β diffuse plaques enriched in gray matter. Although AD pathology in affected cortical regions results in neuronal loss, we find no AD-driven reductions in neuron proportions in Ca. However, there were observable changes in multiple cellular populations. Protoplasmic astrocytes and FLT1+/IL1B+ microglia increased in abundance with global pTau levels. We also observe gene expression changes in fast-spiking PTHLH-PVALB interneurons indicative of disrupted signaling pathways and altered intrinsic physiological properties. This work provides a cellular-resolution framework for understanding AD pathology in Ca.

The mammalian brain is composed of diverse neuron types that play different functional roles. Recent single-cell RNA sequencing approaches have led to a whole brain taxonomy of transcriptomically-defined cell types, yet cell type definitions that include multiple cellular properties can offer additional insights into a neuron's role in brain circuits. While the Patch-seq method can investigate how transcriptomic properties relate to the local morphological and electrophysiological properties of cell types, linking transcriptomic identities to long-range projections is a major unresolved challenge. To address this, we collected coordinated Patch-seq and whole brain morphology data sets of excitatory neurons in mouse visual cortex. From the Patch-seq data, we defined 16 integrated morpho-electric-transcriptomic (MET)-types; in parallel, we reconstructed the complete morphologies of 300 neurons. We unified the two data sets with a multi-step classifier, to integrate cell type assignments and interrogate cross-modality relationships. We find that transcriptomic variations within and across MET-types correspond with morphological and electrophysiological phenotypes. In addition, this variation, along with the anatomical location of the cell, can be used to predict the projection targets of individual neurons. We also shed new light on infragranular cell types and circuits, including cell-type-specific, interhemispheric projections. With this approach, we establish a comprehensive, integrated taxonomy of excitatory neuron types in mouse visual cortex and create a system for integrated, high-dimensional cell type classification that can be extended to the whole brain and potentially across species.

Alzheimer's disease (AD) is the most common cause of dementia in older adults. Neuropathological and imaging studies have demonstrated a progressive and stereotyped accumulation of protein aggregates, but the underlying molecular and cellular mechanisms driving AD progression and vulnerable cell populations affected by disease remain coarsely understood. The current study harnesses single cell and spatial genomics tools and knowledge from the BRAIN Initiative Cell Census Network to understand the impact of disease progression on middle temporal gyrus cell types. We used image-based quantitative neuropathology to place 84 donors spanning the spectrum of AD pathology along a continuous disease pseudoprogression score and multiomic technologies to profile single nuclei from each donor, mapping their transcriptomes, epigenomes, and spatial coordinates to a common cell type reference with unprecedented resolution. Pseudo-progression analysis showed two major epochs corresponding with a slow early increase in pathology and a later exponential increase that correlated with cognitive decline. The early phase included inflammatory microglial and reactive astrocyte component, as well as a selective loss of Sst+ inhibitory neuron types in superficial cortical layers, loss of myelinating oligodendrocytes, and up-regulation of a re-myelination program by OPCs. The later phase involved loss of excitatory neurons and Pvalb and Vip neuron subtypes also predominantly in superficial layers. These cell vulnerabilities were also seen in prefrontal cortex and replicated by other independent studies when integrated with the BRAIN Initiative reference. Study data and exploratory tools are freely available to accelerate progress in AD research at SEA-AD.org.Competing Interest StatementThe authors have declared no competing interest.Footnotes* The revised manuscript now features: 1) Description of a single nucleus RNA sequencing dataset generated from a new cortical region, the dorsolateral prefrontal cortex (DLPFC) 2) An integrated atlas across 10 publicly available single cell studies that also profiled the DLPFC in AD donors 3) New data and analysis of MERFISH spatial analyses 4) Additional analyses on non-neuronal cells* http://sea-ad.org* https://adknowledgeportal.synapse.org/Explore/Studies/DetailsPage?Study=syn26223298* https://registry.opendata.aws/allen-sea-ad-atlas/

The mammalian brain is composed of diverse neuron types that play different functional roles. Recent single-cell RNA sequencing approaches have led to a whole brain taxonomy of transcriptomically-defined cell types, yet cell type definitions that include multiple cellular properties can offer additional insights into a neuron's role in brain circuits. While the Patch-seq method can investigate how transcriptomic properties relate to the local morphological and electrophysiological properties of cell types, linking transcriptomic identities to long-range projections is a major unresolved challenge. To address this, we collected coordinated Patch-seq and whole brain morphology data sets of excitatory neurons in mouse visual cortex. From the Patch-seq data, we defined 16 integrated morpho-electric-transcriptomic (MET)-types; in parallel, we re- constructed the complete morphologies of 300 neurons. We unified the two data sets with a multi-step classifier, to integrate cell type assignments and interrogate cross-modality relationships. We find that transcriptomic vari- ations within and across MET-types correspond with morphological and electrophysiological phenotypes. In addition, this variation, along with the anatomical location of the cell, can be used to predict the projection targets of individual neurons. We also shed new light on infragranular cell types and circuits, including cell-type-specific, interhemispheric projections. With this approach, we establish a comprehensive, integrated taxonomy of excitatory neuron types in mouse visual cortex and create a system for integrated, high-dimensional cell type classification that can be extended to the whole brain and potentially across species.Competing Interest StatementThe authors have declared no competing interest.

To elucidate cortical microcircuit structure and synaptic properties we present a unique, extensive, and public synaptic physiology dataset and analysis platform. Through its application, we reveal principles that relate cell type to synapse properties and intralaminar circuit organization in the mouse and human cortex. The dynamics of excitatory synapses align with the postsynaptic cell subclass, whereas inhibitory synapse dynamics partly align with presynaptic cell subclass but with considerable overlap. Despite these associations, synaptic properties are heterogeneous in most subclass to subclass connections. The two main axes of heterogeneity are strength and variability. Cell subclasses divide along the variability axis, while the strength axis accounts for significant heterogeneity within the subclass. In human cortex, excitatory to excitatory synapse dynamics are distinct from those in mouse and short-term plasticity varies with depth across layers 2 and 3. With a novel connectivity analysis that enables fair comparisons between circuit elements, we find that intralaminar connection probability among cell subclasses exhibits a strong layer dependence.These and other findings combined with the analysis platform create new opportunities for the neuroscience community to advance our understanding of cortical microcircuits.