Biology subjects

Liang, E.

Publications and source records attributed to Liang, E..

At least 19 recordsLinked to original sources

bioRxiv2026

A Comparison of Brain Metabolic Connectivity Methods Topology, Cognition, Age, Structure, and Genetics

Brain metabolic connectivity is increasingly studied using positron emission tomography (PET), but multiple analytical approaches exist with unknown comparability. Here we compared metabolic connectivity approaches in 80 participants who underwent simultaneous dynamic PET with 18F-fluorodeoxyglucose and functional magnetic resonance imaging (fMRI) scans and cognitive testing. Six connectivity approaches were compared, including the traditional across-subject method (often labelled metabolic covariance) and five approaches that estimate individual-level connectivity: across-subject metabolic covariance with individual scores derived using leave one out (LOO); functional PET (fPET) within-subject correlations of regional timeseries; and three approaches that use distance-based measures to estimate individual-level connectivity based on within-region tracer distribution and kinetic compartment C1 and C2 time activity curves. fMRI connectivity was also calculated. Each method showed distinct topological, behavioural, structural and genetic signatures. fPET connectivity demonstrated the strongest cognitive associations and largest age-related declines, with unique predictive power for cognition independent of age. Tracer distribution showed strong age group discrimination although with mixed direction of age and cognitive effects. Metabolic covariance (LOO) and kinetic C2 showed no significant age group differences and their cognition associations reflected age-related variance. Gene expression associations implicated a shared core glycolytic-insulin machinery in all approaches, but the direction of the association with regional connectivity diverged across approaches and unique gene signatures further distinguished most methods. Collectively, these results indicate that the optimal connectivity approach depends on the research question. fPET connectivity with dynamic scans offers utility for cognition and ageing studies, tracer distribution for single-scan designs with careful interpretation of age and cognition relationships, kinetic approaches for novel biological insights into glucose kinetics and fMRI for multi-modal integration. Metabolic covariance (LOO) should be used with caution for brain-behaviour investigations. Researchers should weigh trade-offs between physiological specificity, analytical complexity, acquisition requirements and interpretability when selecting a metabolic connectivity approach.

neuroscience↗

bioRxiv2026

Spatiotemporal isoform profiling identifies a central activator of microexon splicing in C. elegans

Dynamic alternative splicing programs drive tissue specification and organismal development. Here, we present the most comprehensive, tissue-resolved alternative splicing dataset in Caenorhabditis elegans to date, spanning three major tissue types from early embryogenesis to adulthood. We uncovered broad developmental and tissue-regulated alternative splicing trends and identified putative RNA-binding proteins (RBPs) coordinating co-regulated splicing networks governing tissue identity. Among the network of regulated splice variants, we uncovered additional, unannotated microexons for further study in C. elegans. Through a forward genetic screen, we identified RBM-25, a U1 snRNP-associated regulatory protein, as a key regulator that preferentially enhances the inclusion of short exons and microexons alongside its binding partner PRP-40. Phenotypic profiling of rbm-25 mutants demonstrated significant defects in behviour, reproductive fitness, lifespan, and synaptic signalling, indicating a key role for RBM-25-regulated target transcripts in normal physiology and behaviour. Together, these findings expand our appreciation for spatiotemporal isoform diversity during animal development, and provide mechanistic insights into how microexon splicing is regulated.

molecular biology↗

bioRxiv2026

Directed information flow across the metabolic network of the human brain

Brain function is organised in distributed circuits in which regional engagement unfolds over time, reflecting coordinated and temporally ordered patterns of neural computation and information flow. Neural activity also depends on a reliable and scalable supply of glucose. Yet, the temporal order and direction of metabolic signalling in brain circuits remain unknown. Here, we combine functional Positron Emission Tomography (fPET) with [18F]-flurodeoxyglucose and Granger causality analysis to characterise directed metabolic connectivity in cognitive control, memory and affective regulatory circuits in 86 healthy adults. We observed widespread directed metabolic influences within the circuits, with the strength of connections a significant predictor of cognition and affect. The behavioural value of the connections was also governed by the efficiency with which baseline glucose metabolism was converted into adaptive functional connections. We conclude that the brain is organised into metabolic circuits that coordinate temporally ordered connectivity to support information transfer. Directed connections vary in their efficiency of glucose use and functional benefit, suggesting that metabolic signalling does not follow a simple "more is better" rule but reflects context-dependent optimisation across cognitive systems. Author SummaryActivity in the regions of brain circuits unfolds over time, reflecting coordinated and temporally ordered patterns of neural computation. However, it is currently unclear how the intrinsic architecture of the human brains metabolic network supports temporally ordered information flow. Using functional Positron Emission Tomography (fPET) and Granger causality analysis, we identify widespread directed metabolic influences within cognitive control, memory, and affective regulatory circuits. We report that metabolic signalling reflects structured, hierarchical dynamics that predict cognitive performance and psychosocial function. Our results indicate that the brain optimises energetic resources through context-dependent signalling: proactive control requires high metabolic investment, while memory circuits benefit from economical use of glucose. These findings suggest that the brains metabolic architecture is organised to support information flow in functional circuits.

neuroscience↗

bioRxiv2026

A consensus spinal cord cell type atlas across mouse, macaque, and human

The spinal cord contains evolutionarily conserved cell types critical for motor function, sensory processing, and autonomic regulation, many of which are implicated in diverse neurological diseases and injuries. Yet the field lacks a comprehensive molecular characterization of cellular diversity in human, macaque, and mouse spinal cord. Here, we present a unified, cross-species cell type atlas based on the integration of single-nucleus gene expression, chromatin accessibility, and spatial transcriptomic data from segments within cervical, thoracic, lumbar, and sacral regions, including motor neurons (MNs) sampled across the entire rostro-caudal axis of the macaque spinal cord. Leveraging the spatial distributions of our molecularly defined cell types, we generated a cell type-guided anatomical map of spinal cord laminae and nuclei. We identified both conserved and species-specific cellular features, including gene expression patterns across distinct MN subtypes in the primate spinal cord. Cross-species cis-regulatory analysis and deep learning sequence models dissected the enhancer logic underlying viral targeting, uncovering conserved transcription factor grammar encoding cellular identity. Together, these results establish a unifying molecular and anatomical taxonomy of spinal cord cell types across species.

neuroscience↗

bioRxiv2026

Divergent Electrophysiological Responses in the Human Hippocampus During Verbal Memory Processing

The profile of electrophysiological responses in the human hippocampus (HPC) during verbal memory processing has remained complex and unclear. Here, we studied 26 patients implanted with intracranial electrodes across 187 HPC sites (50% left, 2-18 per patient). During memory encoding and retrieval, a subset of HPC responsive sites demonstrated increased ripple events, along with elevated high-frequency (HFA >50 Hz), and low-frequency (LFA 1-8 Hz) activity. A nearly equal number of sites showed no changes in ripple rate but increased LFA power and a delayed response-locked decrease in HFA power. More importantly, both successful encoding as well as recognition of remembered words were strongly associated with the coordination of the timing of LFA and HFA increases across the two clusters of responsive HPC sites. Using direct cortical electrical stimulations, we confirmed overlapping, but partially distinct, cortical connections to the functionally distinct HPC clusters. Our findings suggest a mesoscale mosaic functional organization within the human HPC where adjacent sites with divergent electrophysiological responses may have specialized roles during verbal memory processing. More importantly, our findings suggest that successful human memory depends on the coordination of the timing of low and high frequency local fields generated across these functionally divergent neuronal population sites.

neuroscience↗

bioRxiv2026

Metabolic Connectivity Gradients of the Human Brain

The functional architecture of the brain is organised along continuous, macro-scale gradients. However, it is unknown if the metabolic architecture of the brain displays similar gradient characteristics. Here, we use functional positron emission tomography (fPET) with 18F-fluorodeoxyglucose (FDG) to characterise the brains metabolic connectivity gradients and determine how neurobiological mechanisms shape these gradients to support cognition across the adult lifespan. We identified four principal metabolic connectivity gradients, with the primary axis recapitulating the canonical unimodal-to-transmodal hierarchy from other imaging modalities. Subsequent gradients delineated specialised dimensions of metabolic organisation, including association system differentiation, hemispheric asymmetry, and sensory system segregation. These gradients were coupled to cortical thickness, baseline rates of glucose metabolism, blood flow, and gene expression related to energy metabolism, such that transmodal, control and default mode poles were more metabolically active, more interconnected, had greater cortical thickness, and were more strongly related to the expression of genes related to cellular energy production, than unimodal and sensory poles. A reduction in gradient strength at the gradient poles was associated with older age and predicted worse cognitive performance. We conclude that the brains metabolic organisation constitutes a genetically grounded, structurally and energetically constrained gradient hierarchy that supports cognitive function and undergoes a reorganisation in ageing. TeaserThe brains metabolic architecture forms macro-scale gradients linking genes, neurobiology, and cognitive ageing.

neuroscience↗

bioRxiv2026

Enhancer-based AAV approach for selective AADC delivery reduces motor symptoms and dyskinesia in Parkinson's mouse models

Degeneration of midbrain dopamine (DA) neurons and the resulting loss of striatal dopamine signaling are hallmarks of Parkinsons disease (PD). Although the dopamine precursor levodopa (L-DOPA) provides symptomatic relief, prolonged treatment often leads to abnormal involuntary movements (dyskinesia). Previous adeno-associated virus (AAV) approaches delivering aromatic L-amino acid decarboxylase (AADC) to the striatum under a ubiquitous promoter enhanced local dopamine synthesis and improved PD motor deficits, but this broad targeting strategy limited insight into the cellular populations underlying the behavioral improvements. Here, we engineered enhancer-driven AAVs to direct AADC expression to defined striatal and midbrain cell populations and paired these regulatory elements with a blood-brain barrier-penetrant capsid to enable both systemic and direct delivery. Targeted expression restored motor performance at reduced L-DOPA doses and decreased dyskinesia-like behaviors, producing improvements comparable to or greater than those achieved with ubiquitous expression. Distinct neuronal and non-neuronal populations each supported motor rescue but improved different behavioral domains to different extents, indicating complementary cell type-specific roles within PD-relevant circuits. Together, these findings establish enhancer-driven, cell type-specific AADC delivery as a better-tolerated strategy that enables rescue of motor deficits at lower L-DOPA doses in PD models.

neuroscience↗

bioRxiv2025

Glucodynamic Network Transitions of the Human Brain

The human brain achieves cognitive flexibility by rapidly switching between large-scale functional network states. While state switching is assumed to be energetically demanding, the direct metabolic foundation underpinning state switching has not been characterised. Here, we combine functional FDG-PET (fPET) imaging and sliding-window analyses to characterise metabolic network state switching in 85 adults (20-89 years). Four recurring metabolic network states were identified: a highly prevalent, sparsely connected baseline alongside three transient, globally integrated network states of cognitive control and attention. Cognitive performance relied on the capacity to mobilise the integrated associative system states. Flexible network switching was enabled by the moment-to-moment dynamic range of the underlying regional glucose signals. Neurotransmitter analyses revealed a low-dimensional neurochemical hierarchy that mapped to the dynamic network states, anchored by a dominant axis of endocannabinoid, metabolic, serotonergic and GABAergic systems. The dynamic metabolic network architecture was also attenuated in older adults, who exhibited a loss of network flexibility and were anchored to the sparsely connected baseline state. These findings reveal that functional network state switching is an emergent property of the brains metabolic architecture. This understanding may provide critical new insights into the metabolic basis of brain ageing, neurodegeneration and psychiatric conditions.

neuroscience↗

bioRxiv2025

Phosphoantigen-Driven Dissociation of Butyrophilin Oligomers Activates γδ T Cells

{gamma}{delta} T cells represent a promising avenue for cancer immunotherapy. The V{gamma}9V{delta}2 T cell receptor (TCR), expressed by the predominant subset of {gamma}{delta} T cells, responds to phosphoantigen (pAg)-engaged butyrophilins (BTNs) on various cancer cells. However, the molecular mechanism underlying pAg-mediated activation of V{gamma}9V{delta}2 TCRs remains a subject of debate. Here, we employed an integrative approach to elucidate the mechanism of pAg reactivity in V{gamma}9V{delta}2 T cells. Our results demonstrate that BTNs form higher-order oligomers in the absence of pAg. Upon pAg binding, these oligomers dissociate into tetramers, enabling V{gamma}9V{delta}2 TCR engagement. This pAg-induced dissociation of higher-order BTN complexes is critical for pAg-mediated activation of {gamma}{delta} T cells. Our findings reveal a mechanism of BTN dissociation-driven pAg sensing, providing valuable insight for future immunotherapeutic strategies.

immunology↗

bioRxiv2025

Brain glucodynamic variability is an essential feature of the metabolism-cognition relationship

Variability ensures that complex biological systems, including the brain, are capable of responding to changing environmental demands. While the importance of neural variability in electrophysiological and haemodynamic aspects of brain activity is beginning to be understood, little is known about how variability in molecular activity influences brain function. Here we examine how temporal variability in glucodynamics, or time-varying glucose use, is related to cognition in 35 younger and 43 older adults. Stationary metabolic rates of glucose were not directly associated with cognition. Rather, higher glucodynamic variability, and its coherence into metabolic networks, was associated with better cognitive performance. Lower glucodynamic variability in ageing was associated with altered metabolic network efficiency and reduced cognitive performance. Our results demonstrate for the first time that variability in cerebral glucose metabolism is biologically and functionally relevant to cognition and the network architecture of the brain. Cognition is influenced by time-varying glucose metabolism and its coherent fluctuations in metabolic networks. A loss of glucodynamics in ageing reduces the efficiency of the metabolic connectome and contributes to reduced cognitive performance. The study of glucodynamics significantly advances our understanding of metabolic brain changes in health, ageing and disease. Significance statementThe human brain has a high energy requirement and must be able to dynamically adjust its energy supply as needed. However, the dynamic nature of brain glucose use is not well understood. In this work, we identify the variability in glucodynamics - the moment-to-moment fluctuations in glucose use - as an important biological feature supporting cognition and mediating age-related changes in brain function. We report that higher glucodynamic variability is associated with higher metabolic network efficiency and enhanced cognitive performance. Older adults exhibit reduced glucodynamic variability, reduced network efficiency and impaired cognition. Our results demonstrate that glucodynamics are important to our understanding of energy-dependent cognitive processes, the efficiency of metabolic brain networks, and the energetic basis of cognitive ageing.

neuroscience↗

bioRxiv2025

Dual targeting of transferrin receptor and CD98hc enhances brain exposure of large molecules

Targeting proteins highly expressed at the blood-brain barrier, including transferrin receptor (TfR) and CD98hc, is a transformative approach enabling more effective brain delivery of biotherapeutics for treatment of neurological diseases. TfR-mediated delivery promotes rapid, high brain uptake, while CD98hc-mediated delivery is slower with more prolonged exposure. Here, we engineer a huIgG Fc domain to bind both TfR and CD98hc to create a dual transport vehicle (TV) platform that drives distinct brain delivery properties. Dual TVs achieve significantly higher brain concentrations than TVs targeting either TfR or CD98hc alone. Modulation of TfR and CD98hc affinities shifts dual TV brain exposure kinetics and biodistribution. Stronger TfR affinity drives faster brain uptake and clearance, while stronger CD98hc affinity yields higher, more sustained concentrations, likely due to CD98hc affinity-dependent reduction in TfR-mediated neuronal internalization. This dual targeting strategy leverages the complementary properties of TfR and CD98hc-mediated brain exposure to increase optionality for brain delivery of biotherapeutics.

neuroscience↗

bioRxiv2024

MerQuaCo: a computational tool for quality control in image-based spatial transcriptomics

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.

bioinformatics↗

bioRxiv2024

Lysosomes cell autonomously regulate myeloid cell states and immune responses

Myeloid cells maintain tissue homeostasis via the recognition, engulfment, and lysosomal clearance of dying cells and cellular debris, which is often accompanied by changes from homeostatic to reactive states. While a role for phagocytic receptors in gating these transitions has been described1,2, less is known about if and how lysosomes can contribute to transcriptional and functional plasticity. To determine how lysosomal health impacts myeloid cell states, we evaluated microglia and macrophages deficient for progranulin (encoded by Grn), a lysosomal protein with pleiotropic functions whose loss is associated with several neurodegenerative diseases3-8. Single-cell RNA-sequencing of the aged mouse brain identified a Grn knockout (KO)-specific microglial subpopulation marked by high GPNMB expression that displays hallmarks of lysosomal dysfunction, including lipofuscin accumulation. Epigenetic analysis of aged microglia revealed MITF/TFE transcription factors as key mediators of the transcriptional states associated with Grn deficiency. In addition to identifying a core myeloid cell transcriptional response to diverse lysosomal stressors, targeted perturbations of various lysosomal properties in vitro uncovered a cell autonomous, TREM2- independent, response to lysosomal deacidification (via v-ATPase or VPS34 loss of function) that overlaps with Grn KO microglia phenotypes, including the induction of a lysosomal gene program, increased proliferation, and secretion of pro-inflammatory cytokines. Compound loss-of-function approaches established GPNMB upregulation upon lysosomal stress is required for the compensatory response to enhance lysosomal function via promoting acidification. Finally, pharmacological endolysosomal reacidification through sodium/proton exchanger inhibition partially rescued Grn KO microglia phenotypes. Overall, these data establish a fundamental link between lysosomal health and myeloid cell epigenetic, transcriptional, and functional states observed in neurodegeneration models.

neuroscience↗

bioRxiv2024

Enhancer AAVs for targeting spinal motor neurons and descending motor pathways in rodents and macaque

Experimental access to cell types within the mammalian spinal cord is severely limited by the availability of genetic tools. To enable access to lower motor neurons (LMNs) and LMN subtypes, we generated single cell multiome datasets from mouse and macaque spinal cords and discovered putative enhancers for each neuronal population. We cloned these enhancers into adeno-associated viral vectors (AAVs) driving a reporter fluorophore and functionally screened them in mouse. We extensively characterized the most promising candidate enhancers in rat and macaque and developed an optimized pan LMN enhancer virus. Additionally, we generated derivative viruses expressing iCre297T recombinase or ChR2-EYFP for labeling and functional studies, and we created a single vector with combined enhancer elements to achieve simultaneous labeling of layer 5 extratelencephalic projecting (ET) neurons and LMNs. This unprecedented LMN toolkit will enable future investigations of cell type function across species and potential therapeutic interventions for human neurodegenerative diseases.

neuroscience↗

bioRxiv2024

Metabolic connectivity in ageing.

Information transfer across the brain has a high energetic cost and requires the efficient use of glucose. Positron emission tomography (PET) studies have shown that ageing is associated with a decline in regional rates of cerebral glucose metabolism. However, until recently, it has not been possible to measure the timecourse of molecular activity within an individual using PET, preventing the study of metabolic network connectivity across the brain. Here we report the results of the first high temporal resolution functional PET study examining metabolic connectivity and cognitive function in ageing. The metabolic connectomes of 40 younger (mean age 27.9 years; range 20-42) and 46 older (mean 75.8; 60-89) adults were characterised by high connectivity strength in the frontal, temporal, motor, parietal and medial cortices. Ageing was associated with lower global integration of metabolic hub regions, indicating disrupted information transfer across the metabolic network in older adults. In younger adults, a high proportion of glucose was used to support hubs in the frontal regions. Older adults had a smaller energy budget in comparison to younger adults, and older adults used a higher proportion of energy to support mostly posterior hub regions. This difference in the metabolic network topology in older adults was associated with worse cognitive performance. We conclude that ageing is associated with reduced metabolic connectivity, an altered metabolic network topology and a high glucose cost in hub regions. Our results highlight the fundamental role that metabolism plays in supporting information transfer in the brain and the unique insights that metabolic connectivity provides into the ageing brain.

neuroscience↗

bioRxiv2024

Insulin resistance alters the coupling between cerebral blood flow and glucose metabolism in younger and older adults: Implications for neurovascular coupling

Rising rates of insulin resistance and an ageing population are set to exact an increasing toll on individuals and society. Here we examine the contribution of insulin resistance and age to the coupling of cerebral blood flow and glucose metabolism; a critical process in the supply of energy for the brain. Thirty-four younger (20-42 years) and 41 older (66-86 years) healthy adults underwent a simultaneous resting state MR/PET scan, including arterial spin labelling. Rates of cerebral blood flow and glucose metabolism were derived using a functional atlas of 100 brain regions. Older adults had lower cerebral blood flow than younger adults in 95 regions, reducing to 36 regions after controlling for cortical atrophy and blood pressure. Younger and older insulin sensitive adults showed small, negative correlations between relatively high rates of regional cerebral blood flow and glucose metabolism. This pattern was inverted in insulin resistant older adults, who showed hypoperfusion and hypometabolism across the cortex, and a positive coupling. In insulin resistant younger adults, coupling showed inversion to positive correlations, although not to the extent seen in older adults. Our findings suggest that the normal course of ageing and insulin resistance alter the rates and coupling of cerebral blood flow and metabolism. They underscore the criticality of insulin sensitivity to brain health across the adult lifespan.

neuroscience↗

bioRxiv2023

Metabolic rates of glucose in the brain networks of healthy adults vary as a function of age and levels of peripheral insulin resistance, and predict cognition

People with insulin resistance are at increased risk for cognitive decline. Insulin resistance has previously been considered primarily a condition of ageing but it is increasingly seen in younger adults. Here, we explore the question that changes in insulin function in early adulthood have both proximal effects, and moderate or even accelerate changes in cerebral metabolism in ageing. Thirty-six younger (mean 27.8 years) and 43 older (mean 75.5) participants completed a battery of tests, including blood sampling, cognitive assessment and a simultaneous PET/MR scan. Cortical thickness and cerebral metabolic rate of glucose were derived for 100 regions and 17 functional networks. Older adults had lower rates of regional cerebral glucose metabolism than younger adults across the brain even after adjusting for lower cortical thickness in older adults. In younger adults, higher insulin resistance was associated with attenuated rates of regional cerebral glucose metabolism, but this was not seen in older adults. The largest effects of insulin resistance in younger adults were in prefrontal, parietal and temporal regions; and in the control, salience ventral attention, default and somatomotor networks. Higher rates of network glucose metabolism were associated with lower reaction time and psychomotor speed. Higher levels of insulin resistance were associated with lower working memory. Our results underscore the importance of insulin sensitivity to brain health and cognitive function across the adult lifespan, even in early adulthood. Significance StatementWe show that preventing insulin resistance in early adulthood is important for ensuring efficient fuel supply for the brain and the maintenance of cognitive health across the adult lifespan. Glucose is the primary source of energy for the brain. Decreased glucose metabolism in the brain due to clinically significant levels of insulin resistance is associated with cognitive impairment. Although sub-clinical levels of insulin resistance have also been associated with brain changes, their impact on cerebral metabolism in healthy individuals is unclear. We showed for the first time that - while older adults have lower rates of cerebral metabolism - peripheral insulin resistance attenuates cerebral metabolism more so in healthy younger than healthy older adults, and impairs working memory.

neuroscience↗

bioRxiv2023

Cell-type specific molecular signatures of aging revealed in a brain-wide transcriptomic cell-type atlas

Biological aging can be defined as a gradual loss of homeostasis across various aspects of molecular and cellular function. Aging is a complex and dynamic process which influences distinct cell types in a myriad of ways. The cellular architecture of the mammalian brain is heterogeneous and diverse, making it challenging to identify precise areas and cell types of the brain that are more susceptible to aging than others. Here, we present a high-resolution single-cell RNA sequencing dataset containing [~]1.2 million high-quality single-cell transcriptomic profiles of brain cells from young adult and aged mice across both sexes, including areas spanning the forebrain, midbrain, and hindbrain. We find age-associated gene expression signatures across nearly all 130+ neuronal and non-neuronal cell subclasses we identified. We detect the greatest gene expression changes in non-neuronal cell types, suggesting that different cell types in the brain vary in their susceptibility to aging. We identify specific, age-enriched clusters within specific glial, vascular, and immune cell types from both cortical and subcortical regions of the brain, and specific gene expression changes associated with cell senescence, inflammation, decrease in new myelination, and decreased vasculature integrity. We also identify genes with expression changes across multiple cell subclasses, pointing to certain mechanisms of aging that may occur across wide regions or broad cell types of the brain. Finally, we discover the greatest gene expression changes in cell types localized to the third ventricle of the hypothalamus, including tanycytes, ependymal cells, and Tbx3+ neurons found in the arcuate nucleus that are part of the neuronal circuits regulating food intake and energy homeostasis. These findings suggest that the area surrounding the third ventricle in the hypothalamus may be a hub for aging in the mouse brain. Overall, we reveal a dynamic landscape of cell-type-specific transcriptomic changes in the brain associated with normal aging that will serve as a foundation for the investigation of functional changes in the aging process and the interaction of aging and diseases.

neuroscience↗