Biology subjects

Buchanan, J.

Publications and source records attributed to Buchanan, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Semaphorin 3G (SEMA3G) is a highly selective marker of cerebral amyloid angiopathy

Biomarkers of cerebral amyloid angiopathy (CAA) are critically needed. We recently identified semaphorin 3G (SEMA3G) as a novel protein selectively enriched in CAA. Here, we aimed to determine if SEMA3G was a selective marker of CAA in a large cohort of human brain tissue spanning multiple neurodegenerative diseases and three brain regions, and to determine if SEMA3G directly interacts with amyloid beta (A{beta}). Multiplexed immunofluorescence showed that SEMA3G significantly accumulated only in CAA+ blood vessels in the brain in all cases. We also showed that SEMA3G preferentially associated with A{beta}40, A{beta}pS8 and A{beta}pE3, but not A{beta}42. Thioflavin T assays and transmission electron microscopy showed that SEMA3G directly interacted with A{beta} and slowed A{beta} aggregation in vitro, and that this effect was more pronounced for A{beta}40 than A{beta}42. Together our results demonstrate that SEMA3G is a highly specific marker of CAA in the brain.

neuroscience↗

bioRxiv2026

Microglia extract neuronal proteolytic organelles via skoupocytosis

Neurons face unique challenges in maintaining protein homeostasis due to their tortuous morphology and extended processes. Proteolytic organelles are typically transported retrogradely towards their soma for degradation where lysosomes are enriched, but some organelles are larger than these neuronal processes, questioning how these organelles are degraded. Here we show that microglia, the resident immune cells of the brain, extract proteolytic organelles from neurons both in vitro and in vivo. Microglia make transient contact with neuronal membranes where proteolytic organelles are stationed beneath. At these sites of interaction, microglia pinch off a small portion of the neuronal process containing the organelle, leaving the rest of the process intact. We term this process skoupocytosis after the Greek word for garbage. Phosphatidylserine (PS) lipase ABHD16a accumulates near these proteolytic organelles and converts PS into lyso-PS to initiate microglial skoupocytosis. Skoupocytosis bypasses the need for retrograde organelle transport, providing homeostatic advantages for neurons that must maintain function in processes that extend extraordinarily long distances from the cell soma.

neuroscience↗

bioRxiv2026

Cell-type specific impact of opioid use disorder and HIV on the human forebrain and cerebellum

Opioid use disorder (OUD), which frequently co-occurs with HIV infection, causes long-term neurological disease, yet the epigenetic and transcriptomic effects of OUD and HIV on specific cell types and regions of the brain are poorly understood. To assess the cell-type specific impacts of OUD and HIV across the human brain, we measured single cell transcriptomes and epigenomes of 580,353 cells in the prefrontal cortex, amygdala and cerebellum of 44 donors. We cataloged over 750k candidate cis-regulatory elements (cCREs) and identified gene regulatory networks (GRNs) of transcription factor activity across 35 neuronal and non-neuronal cell types. We identified specific neuronal and glial populations whose cCREs were significantly enriched for genetic risk of addiction-related traits. In OUD donors, we found evidence for reduced metabolic function in neurons in the PFC and cerebellum as well as increased gene expression related to voltage-gated calcium channel activity in the cerebellum. Using a cerebellar organoid model, fentanyl treatment reduced metabolic activity while increasing neuronal activity. Across brain regions, HIV activated immune-related pathways in glial populations, while comorbid OUD and HIV exacerbated metabolic changes in cortical glial cells. Cerebellum-specific Bergmann glia, in addition to forebrain microglia and astrocytes, showed expansion of reactive state identity in HIV. These results highlight shared and specific changes to immune, synaptic, and metabolic processes in OUD and HIV across brain regions and reveal that cerebellar cell types are distinctly affected by opioid abuse.

genomics↗

bioRxiv2025

Loss of tight junction protein claudin 18 uncovers alveolar epithelial stem cell plasticity and emergence of non-fibrogenic transitional progenitors

Persistence of senescent alveolar transitional progenitors following lung injury is implicated in the pathogenesis of fibrosis. We identified transitional cells in uninjured Cldn18 knockout (KO) mouse lungs distinct from previously reported damage-associated transitional progenitors (DATPs) with a less fibrogenic transcriptomic profile. Cldn18 KO mice are protected from bleomycin-induced fibrosis, with early restoration of cellular homeostasis. Lineage tracing implicates accelerated differentiation as a mechanism for protection from fibrosis, leading us to name these cells regeneration-associated transitional progenitors (RATPs). Multiome confirms that RATPs and DATPs are epigenetically distinct, with RATPs comprised of RATP2s and RATP1s based on epigenomic proximity to AT2s and AT1s, respectively, and suggests dynamic regulatory remodeling during AT2-to-AT1 differentiation, with NKX2.1 and AP-1 active in early transitions and TEAD factors in later stages. These results reveal an unexpected role for Cldn18 in regulation of AEC plasticity, while identification of RATPs challenges the notion that persistence of transitional alveolar cells is invariably pathologic.

cell biology↗

bioRxiv2025

Multi-omic analysis of photoreceptor alterations during early-onset retinal degeneration in Mfrp-/- mice

Loss-of-function mutations in the membrane frizzled-related protein (MFRP) gene are associated with autosomal recessive ocular disorders such as nanophthalmos, posterior microphthalmia, and retinitis pigmentosa, yet the molecular mechanisms underlying MFRP-related retinal degeneration remain poorly defined. To investigate these mechanisms, we generated and characterized Mfrp-/- mice and conducted an integrated multi-omic analysis to map the onset and progression of transcriptional changes during retinal degeneration. Using longitudinal in vivo imaging, histological and immunohistochemical analysis, qRT-PCR, single-nucleus RNA sequencing (snRNA-seq), snATAC seq (single-nucleus Assay for Transposase-Accessible Chromatin using sequencing) and spatial transcriptomics (GeoMx DSP), we identified early and progressive photoreceptor loss in Mfrp-/- mice, beginning by 28d. Retinal thinning and autofluorescent deposits in Mfrp-/- mice were accompanied by decreased expression of rod and cone opsins. Transcriptomic profiling by snRNA-seq revealed distinct, photoreceptor-specific gene expression changes, including early upregulation of inflammatory and stress-related genes and later downregulation of genes involved in chromatin remodeling, synaptic function, and neurodevelopment. Spatial transcriptomic analysis of the outer nuclear layer (ONL) revealed disruptions in mitochondrial function, mTORC1 signaling, and G protein-coupled receptor pathways. These findings define a temporally and spatially coordinated program of degeneration triggered by Mfrp loss and demonstrate that Mfrp is required for the maintenance of photoreceptor integrity and gene regulatory homeostasis during retinal development. Our work establishes Mfrp-/- mice as a robust model for dissecting photoreceptor vulnerability and provides a transcriptomic atlas of disease progression with potential relevance for therapeutic development in MFRP-associated retinal dystrophies.

genomics↗

bioRxiv2025

Hebb's Vision: The Structural Underpinnings of Hebbian Assemblies

1In 1949, Donald Hebb proposed that groups of neurons that activate stereotypically form the organizational building blocks of perception, cognition, and behavior. Finding the structural underpinning of such assemblies has been technically challenging, due to a lack of large-scale structure-activity maps. Here, we analyze this relation using a novel dataset that links in vivo optical physiology to connectivity using postmortem elec-tron microscopy (EM). From the fluorescence traces, we extract neural assemblies from higher-order correlations in neural activity. Physiologically, we show that these assemblies exhibit properties consistent with Hebbs theory, including more reliable responses to repeated natural movie inputs than size-matched random ensembles and superior decoding of visual stimuli. Structurally, we find that neurons that participate in assemblies are significantly more integrated into the structural network than those that do not. Contrary to Hebbs original prediction, we do not observe a marked increase in the strength of monosynaptic excitatory connections between cells participating in the same assembly. However, we find significantly stronger indirect feed-forward inhibitory connections targeting cells in other assemblies. These results show that assemblies can be useful components of perception, and, surprisingly, they are delineated by mutual inhibition.

neuroscience↗

bioRxiv2024

Single-cell analysis of the epigenome and 3D chromatin architecture in the human retina

Most genetic risk variants linked to ocular diseases are non-protein coding and presumably contribute to disease through dysregulation of gene expression, however, deeper understanding of their mechanisms of action has been impeded by an incomplete annotation of the transcriptional regulatory elements across different retinal cell types. To address this knowledge gap, we carried out single-cell multiomics assays to investigate gene expression, chromatin accessibility, DNA methylome and 3D chromatin architecture in human retina, macula, and retinal pigment epithelium (RPE)/choroid. We identified 420,824 unique candidate regulatory elements and characterized their chromatin states in 23 sub-classes of retinal cells. Comparative analysis of chromatin landscapes between human and mouse retina cells further revealed both evolutionarily conserved and divergent retinal gene-regulatory programs. Leveraging the rapid advancements in deep-learning techniques, we developed sequence-based predictors to interpret non-coding risk variants of retina diseases. Our study establishes retina-wide, single-cell transcriptome, epigenome, and 3D genome atlases, and provides a resource for studying the gene regulatory programs of the human retina and relevant diseases.

genomics↗

bioRxiv2024

The inactive X chromosome drives sex differences in microglial inflammatory activity in human glioblastoma

Whether an individual is a biological female or male affects cancer risk, but the responsible mechanisms and cell types remain obscure. Glioblastoma multiforme (GBM) is a male-biased cancer that is highly aggressive, and resistant to treatment, with poor patient survival. Dismal prognoses in GBM are due in part to the specialized immune system of the brain, consisting largely of microglia, which regulate GBM development and progression. We hypothesized that microglia function differently in females and males and thereby contribute to the observed male bias in GBM. We sorted TAM-MGs (tumor-associated macrophages - microglia) from human GBMs and low-grade gliomas and performed bulk transcriptomic and epigenomic assays to identify sex-biased gene expression. We used published single-cell transcriptomic data from human GBMs to predict sex-biased TAM-MG interactions with other cell types. We found that female and male TAM-MGs mount different inflammatory responses, with female TAM-MGs displaying stronger interferon signaling and cytotoxic T-cell interactions that should enhance anti-tumor immunity in GBM. We validated these sex-differential inflammatory responses experimentally, and determined that genes on the sex chromosomes, specifically those expressed by Xi (the "inactive" X chromosome), drive these differences. Together, our results suggest that sex-differential TAM-MG inflammatory responses contribute to the higher incidence and mortality of GBM in males.

genomics↗

bioRxiv2023

Nanometer-scale views of visual cortex reveal anatomical features of primary cilia poised to detect synaptic spillover

A primary cilium is a thin membrane-bound extension off a cell surface that contains receptors for perceiving and transmitting signals that modulate cell state and activity. While many cell types have a primary cilium, little is known about primary cilia in the brain, where they are less accessible than cilia on cultured cells or epithelial tissues and protrude from cell bodies into a deep, dense network of glial and neuronal processes. Here, we investigated cilia frequency, internal structure, shape, and position in large, high-resolution transmission electron microscopy volumes of mouse primary visual cortex. Cilia extended from the cell bodies of nearly all excitatory and inhibitory neurons, astrocytes, and oligodendrocyte precursor cells (OPCs), but were absent from oligodendrocytes and microglia. Structural comparisons revealed that the membrane structure at the base of the cilium and the microtubule organization differed between neurons and glia. OPC cilia were distinct in that they were the shortest and contained pervasive internal vesicles only occasionally observed in neuron and astrocyte cilia. Investigating cilia-proximal features revealed that many cilia were directly adjacent to synapses, suggesting cilia are well poised to encounter locally released signaling molecules. Cilia proximity to synapses was random, not enriched, in the synapse-rich neuropil. The internal anatomy, including microtubule changes and centriole location, defined key structural features including cilium placement and shape. Together, the anatomical insights both within and around neuron and glia cilia provide new insights into cilia formation and function across cell types in the brain.

cell biology↗

bioRxiv2023

The Synaptic Architecture of Layer 5 Thick Tufted Excitatory Neurons in the Visual Cortex of Mice

The neocortex is one of the most critical structures that makes us human, and it is involved in a variety of cognitive functions from perception to sensory integration and motor control. Composed of repeated modules, or microcircuits, the neocortex relies on distinct cell types as its fundamental building blocks. Despite significant progress in characterizing these cell types 1-5, an understanding of the complete synaptic partners associated with individual excitatory cell types remain elusive. Here, we investigate the connectivity of arguably the most well recognized and studied excitatory neuron in the neocortex: the thick tufted layer 5 pyramidal cell 6-10 also known as extra telencephalic (ET) 11 neurons. Although the synaptic interactions of ET neurons have been extensively explored, a comprehensive characterization of their local connectivity remains lacking. To address this knowledge gap, we leveraged a 1 mm3 electron microscopic (EM) dataset. We found that ET neurons primarily establish connections with inhibitory cells in their immediate vicinity. However, when they extend their axons to other cortical regions, they tend to connect more with excitatory cells. We also find that the inhibitory cells targeted by ET neurons are a specific group of cell types, and they preferentially inhibit ET cells. Finally, we observed that the most common excitatory targets of ET neurons are layer 5 IT neurons and layer 6 pyramidal cells, whereas synapses with other ET neurons are not as common. These findings challenge current views of the connectivity of ET neurons and suggest a circuit design that involves local competition among ET neurons and collaboration with other types of excitatory cells. Our results also highlight a specific circuit pattern where a subclass of excitatory cells forms a network with specific inhibitory cell types, offering a framework for exploring the connectivity of other types of excitatory cells.

neuroscience↗

bioRxiv2023

CAVE: Connectome Annotation Versioning Engine

Advances in Electron Microscopy, image segmentation and computational infrastructure have given rise to large-scale and richly annotated connectomic datasets which are increasingly shared across communities. To enable collaboration, users need to be able to concurrently create new annotations and correct errors in the automated segmentation by proofreading. In large datasets, every proofreading edit relabels cell identities of millions of voxels and thousands of annotations like synapses. For analysis, users require immediate and reproducible access to this constantly changing and expanding data landscape. Here, we present the Connectome Annotation Versioning Engine (CAVE), a computational infrastructure for immediate and reproducible connectome analysis in up-to petascale datasets ([~]1mm3) while proofreading and annotating is ongoing. For segmentation, CAVE provides a distributed proofreading infrastructure for continuous versioning of large reconstructions. Annotations in CAVE are defined by locations such that they can be quickly assigned to the underlying segment which enables fast analysis queries of CAVEs data for arbitrary time points. CAVE supports schematized, extensible annotations, so that researchers can readily design novel annotation types. CAVE is already used for many connectomics datasets, including the largest datasets available to date.

neuroscience↗

bioRxiv2023

Integrating EM and Patch-seq data: Synaptic connectivity and target specificity of predicted Sst transcriptomic types

Neural circuit function is shaped both by the cell types that comprise the circuit and the connections between those cell types1. Neural cell types have previously been defined by morphology 2, 3, electrophysiology 4, 5, transcriptomic expression 6-8, connectivity 9-13, or even a combination of such modalities 14-16. More recently, the Patch-seq technique has enabled the characterization of morphology (M), electrophysiology (E), and transcriptomic (T) properties from individual cells 17-20. Using this technique, these properties were integrated to define 28, inhibitory multimodal, MET-types in mouse primary visual cortex 21. It is unknown how these MET-types connect within the broader cortical circuitry however. Here we show that we can predict the MET-type identity of inhibitory cells within a large-scale electron microscopy (EM) dataset and these MET-types have distinct ultrastructural features and synapse connectivity patterns. We found that EM Martinotti cells, a well defined morphological cell type 22, 23 known to be Somatostatin positive (Sst+) 24, 25, were successfully predicted to belong to Sst+ MET-types. Each identified MET-type had distinct axon myelination patterns and synapsed onto specific excitatory targets. Our results demonstrate that morphological features can be used to link cell type identities across imaging modalities, which enables further comparison of connectivity in relation to transcriptomic or electrophysiological properties. Furthermore, our results show that MET-types have distinct connectivity patterns, supporting the use of MET-types and connectivity to meaningfully define cell types.

neuroscience↗

bioRxiv2023

NEURD: A mesh decomposition framework forautomated proofreading and morphologicalanalysis of neuronal EM reconstructions

We are now in the era of millimeter-scale electron microscopy (EM) volumes collected at nanometer resolution (Shapson-Coe et al., 2021; Consortium et al., 2021). Dense reconstruction of cellular compartments in these EM volumes has been enabled by recent advances in Machine Learning (ML) (Lee et al., 2017; Wu et al., 2021; Lu et al., 2021; Macrina et al., 2021). Automated segmentation methods produce exceptionally accurate reconstructions of cells, but post-hoc proofreading is still required to generate large connectomes free of merge and split errors. The elaborate 3-D meshes of neurons in these volumes contain detailed morphological information at multiple scales, from the diameter, shape, and branching patterns of axons and dendrites, down to the fine-scale structure of dendritic spines. However, extracting these features can require substantial effort to piece together existing tools into custom workflows. Building on existing open-source software for mesh manipulation, here we present "NEURD", a software package that decomposes meshed neurons into compact and extensively-annotated graph representations. With these feature-rich graphs, we automate a variety of tasks such as state of the art automated proofreading of merge errors, cell classification, spine detection, axon-dendritic proximities, and other annotations. These features enable many downstream analyses of neural morphology and connectivity, making these massive and complex datasets more accessible to neuroscience researchers focused on a variety of scientific questions.

neuroscience↗

bioRxiv2023

Functional connectomics reveals general wiring rule in mouse visual cortex

Understanding the relationship between circuit connectivity and function is crucial for uncovering how the brain implements computation. In the mouse primary visual cortex (V1), excitatory neurons with similar response properties are more likely to be synaptically connected, but previous studies have been limited to within V1, leaving much unknown about broader connectivity rules. In this study, we leverage the millimeter-scale MICrONS dataset to analyze synaptic connectivity and functional properties of individual neurons across cortical layers and areas. Our results reveal that neurons with similar responses are preferentially connected both within and across layers and areas -- including feedback connections -- suggesting the universality of the like-to-like connectivity across the visual hierarchy. Using a validated digital twin model, we separated neuronal tuning into feature (what neurons respond to) and spatial (receptive field location) components. We found that only the feature component predicts fine-scale synaptic connections, beyond what could be explained by the physical proximity of axons and dendrites. We also found a higher-order rule where postsynaptic neuron cohorts downstream of individual presynaptic cells show greater functional similarity than predicted by a pairwise like-to-like rule. Notably, recurrent neural networks (RNNs) trained on a simple classification task develop connectivity patterns mirroring both pairwise and higher-order rules, with magnitude similar to those in the MICrONS data. Lesion studies in these RNNs reveal that disrupting like-to-like connections has a significantly greater impact on performance compared to lesions of random connections. These findings suggest that these connectivity principles may play a functional role in sensory processing and learning, highlighting shared principles between biological and artificial systems.

neuroscience↗

bioRxiv2023

Cell-type-specific inhibitory circuitry from a connectomic census of mouse visual cortex

Mammalian cortex features a vast diversity of neuronal cell types, each with characteristic anatomical, molecular and functional properties. Synaptic connectivity powerfully shapes how each cell type participates in the cortical circuit, but mapping connectivity rules at the resolution of distinct cell types remains difficult. Here, we used millimeter-scale volumetric electron microscopy1 to investigate the connectivity of all inhibitory neurons across a densely-segmented neuronal population of 1352 cells spanning all layers of mouse visual cortex, producing a wiring diagram of inhibitory connections with more than 70,000 synapses. Taking a data-driven approach inspired by classical neuroanatomy, we classified inhibitory neurons based on the relative targeting of dendritic compartments and other inhibitory cells and developed a novel classification of excitatory neurons based on the morphological and synaptic input properties. The synaptic connectivity between inhibitory cells revealed a novel class of disinhibitory specialist targeting basket cells, in addition to familiar subclasses. Analysis of the inhibitory connectivity onto excitatory neurons found widespread specificity, with many interneurons exhibiting differential targeting of certain subpopulations spatially intermingled with other potential targets. Inhibitory targeting was organized into "motif groups," diverse sets of cells that collectively target both perisomatic and dendritic compartments of the same excitatory targets. Collectively, our analysis identified new organizing principles for cortical inhibition and will serve as a foundation for linking modern multimodal neuronal atlases with the cortical wiring diagram.

neuroscience↗

bioRxiv2022

Large-scale unsupervised discovery of excitatory morphological cell types in mouse visual cortex

Neurons in the neocortex exhibit astonishing morphological diversity which is critical for properly wiring neural circuits and giving neurons their functional properties. However, the organizational principles underlying this morphological diversity remain an open question. Here, we took a data-driven approach using graph-based machine learning methods to obtain a low-dimensional morphological "bar code" describing more than 30,000 excitatory neurons in mouse visual areas V1, AL and RL that were reconstructed from the millimeter scale MICrONS serial-section electron microscopy volume. Contrary to previous classifications into discrete morphological types (m-types), our data-driven approach suggests that the morphological landscape of cortical excitatory neurons is better described as a continuum, with a few notable exceptions in layers 5 and 6. Dendritic morphologies in layers 2-3 exhibited a trend towards a decreasing width of the dendritic arbor and a smaller tuft with increasing cortical depth. Inter-area differences were most evident in layer 4, where V1 contained more atufted neurons than higher visual areas. Moreover, we discovered neurons in V1 on the border to layer 5 which avoided deeper layers with their dendrites. In summary, we suggest that excitatory neurons morphological diversity is better understood by considering axes of variation than using distinct m-types.

neuroscience↗

bioRxiv2022

The generation of the first chromosome-level de-novo genome assembly and the development and validation of a 50K SNP array for North American Atlantic salmon

Given the genetic and genomic differences between Atlantic salmon of European origin and North American (N.A.) origin, it is crucial to develop unique genomic resources for each lineage. Here we describe the resources that we recently developed for genomic and genetic research in N.A. Atlantic salmon. Firstly, a new single nucleotide polymorphism (SNP) database for N.A. Atlantic salmon consisting of 3.1 million putative SNPs was generated using data from whole genome resequencing of 80 N.A. Atlantic salmon individuals; Secondly, a high density 50K SNP array enriched for the genic regions of the genome and containing three sex determination and 61 continent of origin markers was developed and validated; Thirdly, a genetic map composed of 27 linkage groups with 36K SNP markers, was generated from 2,512 individuals in 141 full-sib families; Finally, a chromosome level de-novo assembly of a male N.A. Atlantic salmon genome was generated using PacBio long-reads. Information from Hi-C proximity ligation sequences and Bionano optical mapping was used to concatenate the contigs into scaffolds. The assembly contains 1,755 scaffolds and only 1,253 gaps, with a total length of 2.83 Gb and N50 of 17.2 Mb. A BUSCO analysis detected 96.2% of conserved Actinopterygii genes in the assembly and the genetic linkage information was used to guide the formation of 27 chromosome sequences. In contrast, the karyotype of the European Atlantic salmon lineage is composed of 29 chromosomes. Comparative analysis with the reference genome assembly of the European Atlantic salmon confirmed that the karyotype differences between the two linages are caused by a fission in chromosome Ssa01 and three chromosome fusions including the p arm of chromosome Ssa01 with Ssa23, Ssa08 with Ssa29 and Ssa26 with Ssa28. The genomic resources we have generated for Atlantic salmon provide a crucial boost for genetic research and for management of farmed and wild populations in this highly valued species.

genomics↗

bioRxiv2022

Cell-associated Transcriptional Alterations in the Retinal of Alzheimer's Disease

Current approaches for studying pathologic changes in the retina associated with Alzheimers Disease (AD) remain heterogeneous, limiting the use of retinal amyloid-beta as a viable biomarker for AD. Transcriptomic profiling of the retina has provided cell-specific insight into AD progression in the brain yet is lacking in the retina. In this study, we implemented a non-biased approach through next generation sequencing to profile frozen archived retinal tissues from autopsy/pathologically confirmed AD and non-diagnosed cases (NonAD). A total of 37,211 nuclei were isolated from frozen retinal tissue punches originating from AD, and 31,326 were isolated from non-diagnosed cases. Gene expression patterns specific to the retinal region and major retinal cell types were represented in both tissue groups. AD-associated genes were differentially expressed in AD retinal glial cells, including microglia. A greater percentage of microglial nuclei from AD retinal nuclei expressed TYRO protein tyrosine kinase-binding protein (TYROBP) compared to nonAD retinal nuclei. However, compared to microglia from single retinal cell datasets from elderly non-diseased individuals, TYROBP expression is highly expressed in the single cell data set, indicating TYROBP transcripts reside within the cytoplasm. However, other AD-associated genes were differentially expressed in AD nuclei such as DOCK2, PICALM, and PLCG2 compared to non-diseased single-cell microglia, implicating a role of these genes in the AD retina. To summarize, we extracted a high number of nuclei from frozen retinal tissue that retain specific gene markers for cell classification and highlighted candidate AD-associated genes in retinal microglia that may be viable in future AD retinal studies.

neuroscience↗