Biology subjects

Menon, V.

Publications and source records attributed to Menon, V..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

A Multi-Modal AI/ML-based Framework for Protein Conformation Selection and Prediction in Drug Discovery Applications

The development of pharmaceutical drugs is a time-intensive and costly process, with more than 90% of drug candidates failing during preclinical or clinical testing. A major challenge lies in accurately predicting protein-ligand interactions, especially given that traditional computational methods often rely on a single protein conformation, failing to capture biologically relevant structural variability. To address this, we present an AI/ML-based multi-modal framework based on Graph Convolutional Network (GCN) that integrates both global and local protein descriptors to classify binding and non-binding conformations more effectively. Global descriptors capture overarching physico-chemical and structural properties of proteins, while local descriptors--such as pharmacophores--provide site-specific information crucial for modeling ligand interactions. Our GCN based approach demonstrates that integrating local and global structural perspectives significantly improves predictive accuracy and robustness. By enabling more reliable protein conformation classification, this work contributes toward scalable, AI-driven drug discovery--an increasingly critical goal in response to global health challenges.

molecular biology↗

bioRxiv2026

Th17 effector cytokines induce shared and distinct microglial and endothelial cell responses in post-streptococcal encephalitis

Group A Streptococcus (GAS) infections can lead to neuropsychiatric sequelae in children, yet the mechanisms driving post-infectious brain pathology remain poorly defined. In a mouse disease model, Th17 lymphocytes induce microglial activation, blood-brain barrier (BBB) dysfunction, and neural circuit impairment; however, the transcriptional programs underlying these effects, and the specific Th17-derived cytokines involved are unclear. Using mouse genetics, single-cell RNA sequencing, and spatial transcriptomics, we show that GAS infections induce inflammatory gene programs in microglia and brain endothelial cells (BECs), accompanied by downregulation of BBB-associated transcripts in BECs. Spatial transcriptomic analyses reveal that GAS-responsive microglia are enriched near infiltrating T cells. Several chemokines upregulated in microglia following GAS infection in mice are elevated in sera from affected patients. Conditional ablation of GM-CSF in CD4+ T cells partially attenuates microglial chemokine gene expression, but does not restore BBB integrity. Neutralization of IL-17A partially rescues BBB transcriptional changes in BECs and reduces microglial chemokine expression; however, compensatory peripheral immune responses associated with persistent infection exacerbate BBB disruption. In contrast, microglia/macrophage-specific deletion of IL-17 receptor A partially rescues BBB deficits following GAS infection. Together, these findings identify IL-17A-IL-17RA signaling in microglia as a critical driver of BBB dysfunction after GAS infections.

neuroscience↗

bioRxiv2025

A stem cell knockout village reveals lineage rewiring and a non-canonical islet cell fate in monogenic diabetes

Genetics studies have identified a core set of regulators essential for pancreatic {beta} cell development, many of which are mutated in monogenic diabetes. However, how these mutations alter developmental trajectories to produce pathological cell states remains elusive. Here we introduce a knockout village framework that enables longitudinal scRNA-seq profiling of 79 human pluripotent stem cell mutant lines targeting 30 developmental regulators, including 15 diabetes genes, across five islet differentiation stages. We show that loss of lineage regulators impairs {beta} cell formation in a stage-specific manner and rewires developmental trajectories towards competing lineages. Notably, several monogenic diabetes gene mutations drive a shift from {beta} cells to enterochromaffin (EC)-like cells, a recently recognized non-canonical islet cell fate. These EC-like cells exhibit incomplete activation of hormone regulation programs, along with elevated neuron signatures. Leveraging the diversity of cell fate outcomes across mutants, we predicted and experimentally validated ISL1 as a key downstream effector of PDX1 and PAX6 that safeguards {beta} cell identity against an EC-like fate. Together, our findings reveal cell fate rewiring as a widespread, previously underappreciated pathological mechanism in monogenic diabetes and establish a scalable platform for uncovering developmental vulnerabilities in human genetic disorders.

developmental biology↗

bioRxiv2025

Dynamic brain states during encoding and their post-encoding reinstatement predicts episodic memory in children

Episodic memory, the ability to rapidly learn and explicitly remember past events and experiences, plays a critical role in childrens academic learning and knowledge acquisition. The formation of lasting memories relies on the brains ability to dynamically organize its activity. How these neural configurations unfold moment-by-moment across encoding and offline phases remains poorly understood. To probe these dynamics, we applied a novel Bayesian Switching Dynamic Systems approach, a hidden Markov model with automatic state detection, to fMRI data from children performing scene encoding followed by an offline post-encoding rest. We identified four distinct brain states during encoding with unique activation modes between visual, medial temporal lobe, and frontoparietal and default mode network nodes. An "active-encoding" state with integrated visual-hippocampal and frontoparietal activity dominated encoding and predicted individual memory performance, while an inactive state negatively predicted performance. State transition dynamics revealed that flexible shifts into the active-encoding state enhanced memory formation, whereas transitions toward inactive states impaired it, demonstrating that memory success depends on dynamic neural flexibility. Critically, encoding states spontaneously reemerged during post-encoding rest. A "default-mode" state characterized by enhanced default mode network activity showed sustained maintenance during rest and robustly predicted memory outcomes, an effect specific to post-encoding, not pre-encoding rest. These findings establish that episodic memory emerges from coordinated brain state sequences bridging online encoding with offline consolidation, providing a computational framework for how moment-to-moment neural dynamics support memory formation in children. This work has broad implications for optimizing educational interventions and understanding developmental disorders affecting learning and memory.

neuroscience↗

bioRxiv2025

Recurrent neural network models reveal unified mechanisms generating event-related potentials from MMN to P300

The brain must continuously extract salient cues from an immense sensory stream and represent them across regions. Multiregional responses to salient stimuli, notably mismatch negativity (MMN) in sensory and P300 in frontal areas, are among the best-characterized signals in human electrophysiology, yet the mechanisms relating them are unclear, and whether one mechanism accounts for both is unknown. We develop a hierarchical, multiregional recurrent neural network of sensory and frontal cortex to test whether short-term synaptic depression (STD) can explain both. In sensory regions, STD produces stimulus-specific adaptation, generating MMN-like responses; propagation to frontal regions produces the amplification and delay characteristic of the P300, while enhancing noise robustness, with rare stimuli occupying expanded regions of neural state space. When STD acts on frontal feedback predicting upcoming stimuli, it further amplifies responses to unexpected stimuli, suggesting attention sharpens predictions. Our results bridge synaptic-scale mechanisms and brain-wide representations, with relevance to precision psychiatry.

neuroscience↗

bioRxiv2025

Integration of aged brain multi-omics reveals cross-system mechanisms underlying Alzheimer's disease heterogeneity

The molecular correlates of Alzheimers disease (AD) are increasingly being defined by omics. Yet, the findings from different data types or cohorts are often difficult to reconcile. Collecting multiple omics from the same individuals allows a comprehensive view of disease-related molecular mechanisms, while addressing conflicting findings derived from single omics. Such same-sample multi-omics can reveal, for instance, when changes observed in the transcriptome share distinct but coordinated signals in epigenetics and proteomics, relationships otherwise unclear. Here, we apply a data-driven multi-omic framework to integrate epigenomic, transcriptomic, proteomic, metabolomic, and cell-type-specific population data from up to 1,358 aged human brain samples from the Religious Orders Study (ROS) and Rush Memory and Aging Project (MAP). We demonstrate the existence of sprawling cross-omics cross-system biological factors that also relate to AD phenotypes. The strongest AD-associated factor (factor 8) involved elevated immune activity at the epigenetic level, decreased expression of heat shock genes in the transcriptome, and disrupted energy metabolism and cytoskeletal dynamics in the proteome. We also showed immune-related factors (factors 2 and 3) with discordant enrichments, reflecting reactive-like glial subpopulations and protective contributions from surveillance microglia. Both were negatively associated with AD pathology, suggesting potential immune resilience mechanisms. Finally, unsupervised clustering of participants revealed eleven molecular subtypes of the aging brain, including three clusters strongly associated with AD but displaying distinct molecular signatures and phenotypic characteristics. Our findings provide a comprehensive map of molecular mechanisms underlying AD heterogeneity, highlighting the complex role of neuroinflammatory processes, and yielding potential novel biomarkers and therapeutic targets for precision medicine approaches to AD treatment.

molecular biology↗

bioRxiv2025

Early neuronal reprogramming and cell cycle reentry shape Alzheimer's disease progression

Alzheimers disease (AD) is a progressive neurodegenerative disorder characterized by hallmark pathologies, synaptic dysfunction, neuronal loss, gliosis and cognitive decline-dementia. Recent large-scale cell atlases of human AD brains exposed vulnerability of specific neuronal subtypes and highlighted early, coordinated glial responses, suggesting glial involvement in disease progression. However, the timing and nature of neuronal changes, differences between neuronal subtypes, and their coordination with glia remain unclear. Here, we used non-negative matrix factorization to identify co-expression gene programs in single-nucleus RNA profiles from the prefrontal cortex of 437 samples from donors whose clinical symptoms ranged between no cognitive impairment and AD dementia. This approach identified early coordinated transcriptional changes across all neuronal subtypes, preceding clinical symptoms of cognitive decline, and validated in independent snRNA-seq, proteomics, and ELISA datasets. We found neurons in AD undergo rapid modulation of synaptic genes, accompanied by convergence of neurons into two distinct programs: An oxidative stress and apoptosis program abundant in vulnerable neuronal subtypes, and a DNA damage and cell-cycle reentry program associated with resilient subtypes. Moreover, neuronal reprogramming was closely tied to glial responses, and diverged between AD to non-AD brain aging, suggesting neuro-glial coordinated reprogramming shapes the AD cascade and influences disease outcomes.

neuroscience↗

bioRxiv2025

Cytokine expression profile in the human brain of older adults

Alzheimers disease (AD) is a complex neurodegenerative condition linked to chronic neuroinflammation. This study investigates the cytokine gene expression profile in cortical tissue samples from elderly individuals with and without AD to identify potential biomarkers and enhance our understanding of disease pathogenesis. Utilizing high-depth RNA sequencing data, we identified a set of cytokines whose expression significantly associated with different aspects of the AD phenotype, including measures of neurofibrillary tangles, amyloid-{beta} deposition, and a person-specific rate of cognitive decline. Single-nucleus transcriptomics data facilitated the identification of specific cell types, such as microglia and oligodendrocytes, that significantly contribute to the inflammatory response in AD. Additionally, we observed a strong correlation between the expression of certain cytokines and genetic risk for the disease. Our findings indicate that cytokine-mediated neuroinflammation plays a vital role in AD progression and that modulating the immune response may offer a promising strategy for developing new therapies.

molecular biology↗

bioRxiv2025

Brain Multi-Omic Subtypes of Neuroticism Reveal Molecular Signatures linked to Alzheimer's Disease

ImportanceMolecular mechanisms linking neuroticism with Alzheimers disease traits are unknown. ObjectiveTo identify molecular subtypes of neuroticism and examine their association with ADRD traits. DesignThree ongoing cohort studies were used; Religious Orders Study (ROS), Rush Memory and Aging Project (MAP) and Minority Aging Research Study (MARS), that began enrollment in 1994, 1997, and 2004, respectively. SettingOlder priests, nuns, and brothers from across the U.S. (ROS), older adults (MAP) and older African-American adults (MARS) from across the greater Chicago metropolitan area. Participants1,028 decedents with multi-omic data from the dorsolateral prefrontal cortex (DLPFC), the anterior cingulate cortex (AC), and the posterior cingulate gyrus (PCG). Exposure(s)Eight layers of omics (DNA methylation and histone acetylation from DLPFC; RNA seq from AC, DLPFC, and PCG, single-nucleus RNA, TMT proteomics and metabolomics from DLPFC) and Neuroticism using the 12-item version from the NEO Five-Factor Inventory. Main outcome(s) and measure(s)Person-specific multi-omic molecular pseudotime representing molecular progression from low to high phenotypic expression of neuroticism, and three multi-omic brain molecular subtypes of neuroticism which represent distinct omic pathways from no/low neuroticism to high neuroticism that differ by their omic constituents. Participants are exclusively assigned to the subtype which aligns mostly with their multi-omic profile. ResultsThe top drivers of subtype differentiation were transcriptomic alterations across three brain regions (DLPFC, AC, PCG) which extensively and differentially characterized the subtypes. The subtypes were also differentially associated with AD pathology, temporal lobe atrophy, and AD dementia, with subtype N1 showing the strongest associations. Conclusions and RelevanceNeuroticism may be driven by three distinct molecular subtypes, with subtype N1 driving ADRD-related associations, N2 showing some ADRD associations, and N3 being completely independent of these outcomes. Our data provide novel insights into the biology of individual differences in predispositions of neuroticism and its associations with ADRD traits. Key pointsO_ST_ABSQuestionC_ST_ABSWhat are the brain multi-omics molecular signatures linking neuroticism with Alzheimers diseases and related dementias (AD/ADRDs)? FindingsWe identified three distinct brain multi-omic molecular subtypes reflecting different molecular pathways underlying neuroticism. Top omic features of the subtypes were extensively and differentially characterized by transcriptomic alterations across three brain regions - dorsolateral prefrontal cortex, anterior cingulate cortex, and posterior cingulate gyrus. Subtype N1 was strongly associated with AD pathology, AD dementia, and temporal lobe atrophy. MeaningThe association we typically observe between phenotypic neuroticism and ADRD clinical traits might be largely driven by a molecular pathway underlying this trait.

neuroscience↗

bioRxiv2025

Single Cell Landscape of Sex-specific Drivers of Alzheimers Disease

BackgroundSex differences in Alzheimers disease (AD) have been documented for decades, and many sex-specific molecular contributors to AD have been discovered through bulk omics analysis of brain tissues. RNA sequencing (RNAseq) at single cell resolution provides an opportunity to characterize transcript associations with AD in a cell type-specific matter. Here, we investigated sex-specific gene expression associations with neuropathology and cognitive manifestation of AD (endophenotypes) leveraging a large single-nucleus transcriptomic dataset consisting of 1.64 million nuclei from dorsolateral prefrontal cortex (DLPFC) tissue of 424 unique donors from the Religious Orders Study and Memory and Aging Project (ROS/MAP; AD Knowledge Portal syn2580853). MethodsROS/MAP single-nucleus RNAseq data (snRNA-seq) were processed through a rigorous pipeline. In total, eight major cell types from DLPFC were identified. We first performed sex-stratified and sex-interaction association analyses by fitting negative binomial mixed models in relation to {beta}-amyloid load (A{beta}), paired helical filament tau tangle density (tau), global cognitive performance at last visit, and longitudinal cognitive trajectory. We then conducted gene-set enrichment analysis to identify functional signaling pathways enriched for sex-specific associations. Lastly, we compared differential gene expression patterns and intercellular communication profiles between sexes and diagnostic groups among major cell types. For replication, sex-specific associations were examined using snRNA-seq derived from DLPFC tissue-derived of an independent set of 84 donors from The Seattle Alzheimers Disease Brain Cell Atlas (SEA-AD) study. Results68% of the ROS/MAP participants were female, and 52% were diagnosed with AD dementia. We first identified several disease-dependent or sex-dependent cell subpopulations. Then we identified 2,660 sex-specific associations involving 2,110 genes with A{beta} (51%), tau (21%), and cognitive performance (29%). 60% female-specific associations were for A{beta}, and 49% male-specific associations were with tau. The vast majority (93%) of female protective associations were from neurons, and most (76%) of female risk associations were from glial cells. Nine of the female-specific associations involving eight unique genes were replicated in the SEA-AD cohort, including ADGRV1 and OR3A3 with A{beta}; IFI27L1, LYRM1, STAP2, and TSTD2 with tau; PDYN with global cognition; and TMEM50B with longitudinal cognitive decline. All replicated associations except TMEM50B were observed in neurons. Furthermore, the preponderance of protective female-specific associations in neurons was also recapitulated in the SEA-AD cohort. Sex-specific associations were enriched for genes in the immune, inflammation, and damage-related stress response pathways, and microglia presented the most sex-specific enriched pathways. Finally, we identified six ITGB1-mediated microglia-specific incoming signals that may play a role in female-specific risk for A{beta} accumulation. ConclusionOur study highlights the transcriptome-wide, single-cell landscape of sex-specific molecular associations with AD neuropathology and cognitive decline. We delineate the full scope of sex-specific transcript associations, differential expression, signaling pathway, and cell-cell communication network changes in each major DLPFC cell type, while identifying and replicating several female-specific gene associations in neurons to help direct future mechanistic studies.

neuroscience↗

bioRxiv2025

Biophysical mechanisms of default mode network function and dysfunction

The default mode network (DMN) plays a fundamental role in internally focused cognition, and its disruption is implicated in numerous brain disorders. While neuroimaging has revealed DMN suppression by salient stimuli, the cellular mechanisms orchestrating this process remain unknown. Using whole-brain computational modeling informed by neuronal biophysics and retrograde tracer-derived directional mouse brain connectomics, we demonstrate that stimulation of the insula node of the salience network suppresses DMN activity, whereas cingulate cortex stimulation produces antagonistic effects, enhancing retrosplenial cortex activity. Prelimbic cortex stimulation showed intermediate patterns, partially replicating insula-mediated suppression while failing to suppress cingulate regions, suggesting its role as a functional bridge between networks. Systematic brain-wide analysis confirmed the insulas unique pattern of simulated DMN suppression. Comprehensive parameter space exploration demonstrated that DMN emergence as a functionally segregated network is robust across wide ranges of excitatory-inhibitory balance regimes and cholinergic modulation. However, outside these boundaries, DMN integrity breaks down through three distinct failure modes: loss of responsiveness, reversal of suppression to enhancement, and network fragmentation. The retrosplenial cortex emerged as a particularly vulnerable regulatory hub whose excitatory-inhibitory disruption reversed normal suppression patterns across the DMN, while prelimbic cortex demonstrated remarkable robustness. Brain-wide analysis also identified a functionally segregated frontal network displaying antagonistic dynamics with the DMN. Our findings provide mechanistic insights into DMN robustness and vulnerability, establishing a framework that links cellular excitatory-inhibitory balance to large-scale network dynamics. This model could explain how region-specific disruptions can produce the heterogeneous patterns of DMN dysfunction observed across brain disorders. Significance StatementTo respond to important external events, the brain must suppress internal thought processes implicating the default mode network. This suppression fails in psychiatric conditions, that also involve imbalances between excitatory and inhibitory neurons. However, the connection between cellular imbalances and default-mode-network dysfunction has remained unclear. We used brain-wide computer simulations incorporating neuronal properties to understand how imbalance at the cellular scale disrupts network function. Our simulations reveal the precise excitatory-inhibitory balance needed for normal suppression. Additionally, we identified distinct failure modes and discovered that certain brain hubs are more vulnerable than others to disruption. Our findings reveal how cellular alterations scale up to cause network-level dysfunction, potentially guiding treatments targeting specific brain regions in individual patients.

neuroscience↗

bioRxiv2025

Cell type-specific associations with Alzheimer's Disease conserved across racial and ethnic groups

Genomic studies at single-cell resolution have implicated multiple cell types associated with clinical and pathological traits in Alzheimers Disease (AD), but have not examined common features across broad, multi-ethnic populations, and across multiple regions. To bridge this gap, we performed single-nucleus RNA-seq and ATAC-seq profiling of cortical and subcortical brain regions from post-mortem samples across Non-Latin White, African American, and Latin donors (the latter of any race). Using discrete and continuous dissection of molecular programs, we elucidate cell-type-specific glial and neuronal signatures associated with AD across multiple population groups. Notably, we found that multiple microglial (GPNMB+, CD74+, and CR1+ subgroups) and astrocyte (SERPINH1+ and WIF1+ subgroups) signatures are associated with worse clinical and pathological phenotypes across all three population groups. We also report continuous gene expression factors in oligodendrocytes that are not captured by discrete clusters, yet still show strong associations with disease phenotypes. Finally, we observe these discrete cellular identities and continuous gene programs separate cognitively impaired donors into 6 molecularly distinct subgroups that span racial and ethnic population groups. Overall, our study identifies key cell types and gene programs implicated in AD that are shared across population groups, and provides an initial data set that underscores how representative sampling can capture conserved signatures as well as disease heterogeneity, leading to better prioritization of key cell types for further investigation.

neuroscience↗

bioRxiv2025

Heterogeneity of human insular cortex: Five principles of functional organization across multiple cognitive domains

The insular cortex serves as a critical hub for human cognition, but how its anatomically distinct subregions coordinate diverse cognitive, emotional, and social functions remains unclear. Using the Human Connectome Projects multi-task fMRI dataset (N=524), we investigated how insular subregions dynamically engage during seven different cognitive tasks spanning executive function, social cognition, emotion, language, and motor control. Our findings reveal five key principles of human insular organization. First, insular subregions maintain distinct functional signatures that enable reliable differentiation based on activation and connectivity patterns across cognitive domains. Second, these subregions dynamically reconfigure their network interactions in response to specific task demands while preserving their core functional architecture. Third, clear functional specialization exists along the insulas dorsal-ventral axis: the dorsal anterior insula selectively responds to cognitive control demands through interactions with frontoparietal networks, while the ventral anterior insula preferentially processes emotional and social information via connections with limbic and default mode networks. Fourth, we observed counterintuitive connectivity patterns during demanding cognitive tasks, with the dorsal anterior insula decreasing connectivity to frontoparietal networks while increasing connectivity to default mode networks - suggesting a complex information routing mechanism rather than simple co-activation of task-relevant networks. Fifth, while a basic tripartite model captures core functional distinctions, finer-grained parcellations revealed additional cognitive domain-specific advantages that are obscured by simpler parcellation approaches. Our results illuminate how the insulas organization supports its diverse functional roles through selective engagement of distinct neural networks, providing a new framework for understanding both normal cognitive function and clinical disorders involving insular dysfunction.

neuroscience↗

bioRxiv2025

A factor-based analysis of individual human microglia uncovers regulators of an Alzheimer-related transcriptional signature

Human microglial heterogeneity is only beginning to be appreciated at the molecular level. Here, we present a large, single-cell atlas of expression signatures from 441,088 live microglia broadly sampled across a diverse set of brain regions and neurodegenerative and neuroinflammatory diseases obtained from 161 donors sampled at autopsy or during a neurosurgical procedure. Using single-cell hierarchical Poisson factorization (scHPF), we derived a 23-factor model for continuous gene expression signatures across microglia which capture specific biological processes (e.g., metabolism, phagocytosis, antigen presentation, inflammatory signaling, disease-associated states). Using external datasets, we evaluated the aspects of microglial phenotypes that are encapsulated in various in vitro and in vivo microglia models and identified and replicated the role of two factors in human postmortem tissue of Alzheimers disease (AD). Further, we derived a complex network of transcriptional regulators for all factors, including regulators of an AD-related factor enriched for the mouse disease-associated microglia 2 (DAM2) signature: ARID5B, CEBPA, MITF, and PPARG. We replicated the role of these four regulators in the AD-related factor and then designed a multiplexed MERFISH panel to assess our microglial factors using spatial transcriptomics. We find that, unlike cells with high expression of the interferon-response factor, cells with high expression of the AD DAM2-like factor are widely distributed in neocortical tissue. We thus propose a novel analytic framework that provides a taxonomic approach for microglia that is more biologically interpretable and use it to uncover new therapeutic targets for AD.

neuroscience↗

bioRxiv2025

Translating the Post-Mortem Brain Multi-Omics Molecular Taxonomy of Alzheimer's Dementia to Living Humans

Alzheimers disease (AD) dementia is characterized by significant molecular and phenotypic heterogeneity, which confounds its mechanistic understanding, diagnosis, and effective treatment. In this study, we harness the most comprehensive dataset of paired ante-mortem blood omics, clinical, psychological, and post-mortem brain multi-omics data and neuroimaging to extensively characterize and translate the molecular taxonomy of AD dementia to living individuals. First, utilizing a comprehensive integration of eight complementary molecular layers from brain multi-omics data (N = 1,189), we identified three distinct molecular AD dementia subtypes exhibiting strong associations with cognitive decline, sex, psychological traits, brain morphology, and characterized by specific cellular and molecular drivers involving immune, vascular, and oligodendrocyte precursor cells. Next, in a significant translational effort, we developed predictive models to convert these advanced brain-derived molecular profiles (AD dementia pseudotimes and subtypes) into blood-, MRI- and psychological traits-based markers. The translation results underscore both the promise of these models and the opportunities for further enhancement. Our findings enhance the understanding of AD heterogeneity, underscore the value of multi-scale molecular approaches for elucidating causal mechanisms, and lay the groundwork for the development of novel therapies in living persons that target multi-level brain molecular subtypes of AD dementia.

neuroscience↗

bioRxiv2025

Single-cell Spatial Transcriptomics Reveals Disease-specificMicroenvironmental Niches in Neurodegeneration and COVID-19

Neurodegenerative diseases and infections can produce lasting effects on brain function, yet the spatial molecular mechanisms underlying these changes remain poorly understood. Here, we present high-resolution spatial transcriptomics of 40 postmortem brain samples from patients with Parkinsons disease, frontotemporal dementia, dementia with Lewy bodies, and severe COVID-19. Analyzing over 1.5 million spatially resolved cells across dorsolateral prefrontal cortex and anterior cingulate cortex revealed disease-specific transcriptional signatures with pronounced layer-and region-specificity. In Parkinsons disease, we identified stressed neurons creating distinctive microenvironmental gradients where metabolic and protein degradation pathways are elevated near stress epicenters, while regenerative processes increase with distance. COVID-19 brains displayed extensive peripheral immune cell infiltration, particularly in the subcortical white matter, accompanied by compromised blood-brain barrier and coordinated neuroinflammatory responses from microglia, astrocytes, and endothelial cells. Integration of miRNA sequencing with spatial transcriptomics uncovered layer-specific regulatory patterns, including neuroinflammation-associated miR-155. This atlas provides unprecedented insights into disease pathology and highlights the critical importance of spatial molecular context in understanding brain disorders. Key Messages[1] A high-resolution single-cell spatial transcriptomics atlas of the dorsolateral prefrontal cortex and anterior cingulate cortex across neurodegenerative conditions and severe COVID-19 [2] Region-and layer-specific transcriptional dysregulation across disease comparisons reveals disease-specific differential vulnerability [3] Metabolically stressed cells found selectively in the anterior cingulate cortex of Parkinsons disease patients but not in dementia with Lewy bodies, along with detailed characterization of their spatial microenvironment [4] Peripheral immune cell clusters identified in the white matter of the cerebral cortex of COVID-19 patients, with detailed characterization of their spatial microenvironment [5] Integration of bulk miRNA sequencing reveals cortical layer-specific miRNA regulatory patterns

neuroscience↗

bioRxiv2025

Ontogeny of the spinal cord dorsal horn

The dorsal horn of the mammalian spinal cord is an exquisite example of form serving function. It is comprised of diverse neuronal populations stacked into laminae, each of which receives different circuit connections and plays specialized roles in behavior. An outstanding question is how this organization emerges during development from an apparently homogeneous pool of neural progenitors. Here, we found that dorsal neurons are diversified by time, with families of related cell types born as temporal cohorts, and by a spatial-molecular gradient that specifies the full array of individual cell types. Excitatory dorsal neurons then settle in a chronotopic arrangement that transforms their progressive birthdates into anatomical order. This establishes the dorsal horn laminae, as these neurons are also required for spatial organization of inhibitory neurons and sensory axons. This work reveals essential ontogenetic principles that shape dorsal progenitors into the diverse cell types and architecture that subserve sensorimotor behavior. Highlights- Temporal cohorts of late-born dorsal neurons give rise to neuronal families - Sequentially-born excitatory neuron families form adjacent laminae - Laminar structure specifically requires excitatory (but not inhibitory or sensory) neurons - Graded expression of Zic transcription factors directs fine neuronal identity

neuroscience↗

bioRxiv2025

Reconstructed Cell-Type Specific Rhythms in Human Brain link Alzheimer's Pathology, Circadian Stress, and Ribosomal Disruption

Alzheimers disease (AD) disrupts behavioral circadian rhythms, but its effects on molecular rhythms in the human brain are poorly understood. Using single-nucleus RNA sequencing from post-mortem cortical samples, we informatically estimated the relative circadian phases of 409 persons with and without AD dementia. We then reconstructed circadian expression profiles across cell types. While core clock rhythms were preserved in AD, many cell-type specific circadian outputs were disrupted. Rhythms in ribosomal biogenesis and oxidative phosphorylation were dampened across cell types. Similar losses in ribosomal gene expression rhythms were observed in APP/PS1 mice, which showed further reductions in ribosomal protein expression and polysome-mediated translation after circadian desynchrony. Exploratory computational modeling reveals that altered translation may contribute to the increased circadian variability seen in AD patients. These findings reveal altered cell-type specific circadian output rhythms in the brains of AD affected patients, and highlight disrupted ribosomal rhythms as a feature of AD.

bioinformatics↗