Biology subjects

Lee, A. J.

Publications and source records attributed to Lee, A. J..

At least 19 recordsLinked to original sources

bioRxiv2026

A functional genomics screen of human B-cell differentiation reveals convergent mechanisms of inherited childhood leukemia predisposition

B-cell acute lymphoblastic leukemia (B-ALL) is the most common childhood cancer, yet the mechanisms by which inherited risk variants predispose to leukemia development remain poorly understood. A major challenge to studying these mechanisms has been the lack of model systems that faithfully capture the transient developmental states in which predisposition alleles are thought to act. Here, we establish a human B-cell differentiation platform from hematopoietic stem/progenitor cells that enables CRISPR-based engineering, recapitulates early B-cell lymphopoiesis, and enriches for rare developmental intermediates. By applying systematic perturbations with multiplexed single-cell transcriptomic profiling to mimic the effects of mutations in nine familial B-ALL predisposition genes, we decipher mechanisms by which B-cell development can be altered by such inherited variation to predispose to B-ALL. Through these studies, we identify convergent delays in B-cell differentiation at progenitor stages characterized by high-level RAG1/2 recombination activity. We propose that these delays at progenitor stages increase the likelihood that cells can undergo illegitimate RAG-mediated recombination to promote transformation, a finding consistent with similar rates of illegitimate RAG-associated genomic alterations in those with B-ALL associated with familial predisposition variants compared to sporadic cases.

cancer biology↗

bioRxiv2026

Single-cell multiomic mapping of genetic predisposition to childhood B-cell acute lymphoblastic leukemia

Inherited genetic variation substantially increases the risk for developing childhood B-cell acute lymphoblastic leukemia (B-ALL), the most common cancer in children, yet the underlying mechanisms remain poorly understood. To address this limitation, we employ a single-cell multiomic framework to functionally dissect common regulatory variants associated with B-ALL risk. Coupling this multiomic analysis with assessment of allelic skews in chromatin accessibility, we reveal the impact of risk alleles and disruptions in transcription factor networks specific to B-cell progenitors, thereby providing mechanistic insights into altered regulatory programs underlying B-ALL predisposition. By constructing long-range variant-to-target gene maps, we identify 34 high-confidence B-ALL susceptibility genes. Among these, we uncover and functionally validate a risk allele that selectively upregulates expression of ELK3, a previously unrecognized regulator of B-cell development and leukemogenesis. Together, these findings establish a comprehensive variant-to-function map of cell state-specific regulatory disruptions underlying inherited predisposition to B-ALL and define new risk mechanisms, which could pave the way for future targeted prevention approaches.

cancer biology↗

bioRxiv2026

The exocyst is an insulin-sensitive regulator of amyloid precursor protein trafficking and amyloid-beta generation in neurons

Intracellular trafficking of amyloid precursor protein (APP) critically influences amyloidogenic processing, yet the mechanisms regulating this pathway remain incompletely defined. The exocyst is a highly conserved, insulin-responsive, eight-protein Rab effector complex that directs intracellular transport vesicle targeting and docking. We identified APP in a proteomics screen of neuronal cell surface proteins altered after chemical inhibition of exocyst activity. In SH-SY5Y cells expressing a mutant APP that enhances amyloidogenic processing, RNAi-mediated silencing of exocyst subunits significantly decreased sAPP and A{beta} secretion, leading to significant intracellular APP accumulation. We found high-resolution co-localization of APP with exocyst subunits in soma and neurites of differentiated human SH-SY5Y neurons and mouse primary hippocampal neurons, and live-cell TIRF microscopy identified highly coordinated movement between fluorescently-tagged exocyst and APP proteins. These interactions were confirmed in these cells and in mouse brain histological sections by proximity ligation assays (PLAs) demonstrating close (<40nm) APP-EXOC5 association. To examine if exocyst activity in neurons is regulated by insulin, as it is in adipocytes and muscle, we generated a SH-SY5Y cell line with pHluorin-tagged GLUT4. Inhibition of the exocyst prevented exocytosis of GLUT4 to the plasma membrane in response to insulin. Additionally, using PLAs in mouse primary hippocampal neurons and SH-SY5Y neurons, we found that GLUT4-EXOC5 associations were increased by insulin signaling, but APP-EXOC5 associations were markedly reduced, indicating insulin-dependent retargeting of the exocyst complex away from APP+ vesicles towards GLUT+ vesicles. All together, these data identify the exocyst as a novel insulin-regulated mediator of neuronal APP trafficking and A{beta} secretion. In BriefWe show that the insulin-responsive exocyst regulates amyloidogenic processing of APP in neurons and that insulin signaling shifts the exocyst away from APP trafficking to promote the translocation of GLUT4-containing vesicles to the plasma membrane of neurons.

neuroscience↗

bioRxiv2026

Epigenome editing of human hematopoietic stem cells enables sustained and reversible thrombosis prevention

Thrombosis remains a major cause of cardiovascular and cerebrovascular diseases, driven in large part by platelet activation and aggregation. Because platelets are continuously produced from hematopoietic stem cells (HSCs), durable reprogramming of HSC output offers a unique opportunity for a one-time antithrombotic intervention. Here, we show that DNA methylation-based epigenome editors delivered transiently as RNA result in stable, heritable gene silencing in primary human HSCs that persists through long-term self-renewal and megakaryocytic differentiation, while remaining reversible through targeted demethylation. Targeting the platelet integrin {beta}3 (ITGB3), this approach achieves robust, sustained repression and yields platelets with impaired aggregation. Extending this framework to additional genetically-nominated platelet targets establishes HSC epigenome editing as a durable and reversible strategy to modulate thrombotic risk and highlights broader opportunities to engineer hematopoiesis.

genomics↗

bioRxiv2026

Multi-omics characterization of vascular, neurodegenerative, and mixed neuropathology in the aging human brain

Late-life cognitive impairment most commonly occurs in the setting of mixed neurodegenerative and cerebrovascular pathology, yet the molecular programs distinguishing vascular, neurodegenerative, and mixed pathology in the aging human brain remain incompletely defined. We performed neuropathology-stratified proteomic and transcriptomic profiling of postmortem brain tissue from participants in the Religious Orders Study and Rush Memory and Aging Project. Dorsolateral prefrontal cortex proteomics (n = 733) were analyzed alongside bulk RNA sequencing from dorsolateral prefrontal cortex (n = 938), posterior cingulate cortex (n = 569), and anterior caudate (n = 632). Participants were classified into vascular, neurodegenerative, and mixed pathology groups based on comprehensive autopsy assessment. Neurodegenerative and mixed pathology, relative to vascular pathology, showed coordinated upregulation of immune and inflammatory pathways and downregulation of mitochondrial and oxidative phosphorylation programs across molecular layers. Although few individual proteins differed between mixed and neurodegenerative groups, pathway-level analyses identified additional remodeling programs in mixed pathology, including extracellular matrix organization and vesicle-mediated transport. Proteomic co-expression network analysis identified immune-stress modules associated with amyloid burden, tau pathology, and cognitive decline, whereas a mitochondrial bioenergetic module showed relative preservation in vascular pathology. Cross-omics concordance was robust at the pathway level but limited at the level of individual genes and proteins. These findings define conserved molecular programs distinguishing vascular, neurodegenerative, and mixed pathology and demonstrate that pathway-level organization provides a stable framework for interpreting molecular heterogeneity in late-life dementia.

genomics↗

bioRxiv2026

SpotGraphs: Graph-based analysis of spatially resolved transcriptional data in R

IntroductionCommon spatial transcriptomic analysis pipelines in R focus on pre-processing and visualization, while providing limited and indirect methods to leverage true spatially resolved quantification of transcripts. Often, x,y-coordinates in spatial transcriptomics (ST) data are integrated into analysis via "spatially aware" normalization (Salim et al., 2024), clustering methods (Zhao et al., 2021), or the identification of spatially variable genes (Yan et al., 2025). Though useful, these methods do not provide any opportunity for analysts to adjust or interrogate the underlying graphs that define adjacencies between spots in their data. Here, we present SpotGraphs, a package that allows the user a more direct and flexible option to interact with the x,y-coordinates of their ST data in R through the existing igraph infrastructure (Antonov et al., 2023; Csardi et al., 2025; Csardi & Nepusz, 2006). Similar functionality exists in Python through SquidPys graph API (Palla et al., 2022), and we compare results obtained from both packages, demonstrating similar performance. Additionally, we provide a set of tools that are useful for ST data analysis, including a toolkit to filter low quality spots laying on tissue debris, beyond arbitrary thresholds, edit spot-level adjacencies based on spatial clusters, and identify centers or boundaries of user-defined neighborhoods of interest.

bioinformatics↗

bioRxiv2026

Growth-adaptive spring electronics for long-term, same-neuron mapping in the developing rat brain

Neural activity reorganizes profoundly after birth, transitioning from highly synchronous population events to sparse, decorrelated firing in the mature brain. Although inhibitory maturation and shifts in excitation-inhibition balance have been implicated in this process, how individual neurons implement the transition remains unclear because rapid brain growth has prevented long-term, same-neuron mapping. Here, we introduce growth-adaptive spring electronics that provide depth-wise compliance during tissue expansion, maintaining a stable electrode-tissue interface over weeks of neonatal development. We developed a vision-language model-assisted spike processing pipeline for the developing brain that probabilistically matches units across days using high-density waveform spatial footprints, despite developmental changes in the neonatal brain. Together, these innovations enable spike-resolved mapping of the same neurons in rat visual cortex and medial prefrontal cortex from postnatal day 10 to 45. Using population coupling to quantify each neurons coordination with local population activity, we show that developmental decorrelation is driven primarily by a distinct subset of neurons that progressively shifts from strong to weak coupling during postnatal weeks 3 to 5, whereas other neurons remain stably weakly or strongly coupled throughout development. These results resolve population-level desynchronization into identifiable neuron-specific trajectories. This framework enables direct tests in neurodevelopmental disorder models, including schizophrenia and autism, of whether altered maturation reflects global circuit imbalance or selective disruption and mistiming of specific developmental programs.

bioengineering↗

bioRxiv2025

DeviceAgent: An autonomous multimodal AI agent for flexible bioelectronics

The development of flexible bioelectronics remains a complex, multidisciplinary process that demands specialized expertise and labor-intensive efforts, limiting scalability, adaptability and accessibility. Here, we introduce DeviceAgent, an autonomous multimodal AI agent that integrates large language models (LLMs), vision-language models (VLMs), and domain-specific computational tools into a unified framework for bioelectronics research. Leveraging the emergent reasoning abilities of LLMs and VLMs, DeviceAgent enables zero and few-shot generalization, contextual learning, and flexible task execution across modalities. A multimodal context memory system orchestrates these capabilities, providing end-to-end support across the experimental pipeline-from high-level design objectives to fabrication protocol generation, visual defect inspection, and electrophysiological signal analysis, while maintaining human oversight at critical decision points. We demonstrate its capabilities through the development of stretchable mesh electronics for interfacing with human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), a representative application involving complex device architectures, heterogeneous material nanofabrication, and electrophysiology analysis. DeviceAgent autonomously (1) generates customized bioelectronic layouts; (2) creates comprehensive fabrication protocols tailored to specific materials and processes; (3) identifies microscopic defects using visual reasoning; and (4) analyzes cardiac electrophysiological recordings in an interpretable manner. By embedding LLMs and VLMs within a structured, tool-augmented architecture, DeviceAgent establishes a scalable and accessible paradigm for AI-scientist collaboration in nanofabrication and bioelectronics research.

bioengineering↗

bioRxiv2025

An AI Agent for cell-type specific brain computer interfaces

Decoding how specific neuronal subtypes contribute to brain function requires linking extracellular electrophysiological features to underlying molecular identities, yet reliable in vivo electrophysiological signal classification remains a major challenge for neuroscience and clinical brain-computer interfaces (BCI). Here, we show that pretrained, general-purpose vision-language models (VLMs) can be repurposed as few-shot learners to classify neuronal cell types directly from electrophysiological features, without task-specific fine-tuning. Validated against optogenetically tagged datasets, this approach enables robust and generalizable subtype inference with minimal supervision. Building on this capability, we developed the BCI AI Agent (BCI-Agent), an autonomous AI framework that integrates vision-based cell-type inference, stable neuron tracking, and automated molecular atlas validation with real-time literature synthesis. BCI-Agent addresses three critical challenges for in vivo electrophysiology: (1) accurate, training-free cell-type classification; (2) automated cross-validation of predictions using molecular atlas references and peer-reviewed literature; and (3) embedding molecular identities within stable, low-dimensional neural manifolds for dynamic decoding. In rodent motor-learning tasks, BCI-Agent revealed stable, cell-type-specific neural trajectories across time that uncover previously inaccessible dimensions of neural computation. Additionally, when applied to human Neuropixels recordings-where direct ground-truth labeling is inherently unavailable-BCI-Agent inferred neuronal subtypes and validated them through integration with human single-cell atlases and literature. By enabling scalable, cell-type-specific inference of in vivo electrophysiology, BCI-Agent provides a new approach for dissecting the contributions of distinct neuronal populations to brain function and dysfunction.

neuroscience↗

bioRxiv2025

TPClust: Temporal Profile-Guided Subtyping Using High-Dimensional Omics Data

Clustering is widely used to identify subtypes in heterogeneous populations, yet most approaches rarely integrate longitudinal phenotypic trajectories with high-dimensional molecular profiles, limiting their ability to resolve biologically and clinically meaningful heterogeneity in progressive diseases. We developed TPClust, a supervised, semi-parametric clustering method that integrates high-dimensional omics data with longitudinal phenotypes including outcomes and covariates for outcome-guided subtyping. TPClust jointly models latent subtype membership and longitudinal outcome trajectories using multinomial logistic regression informed by molecular features selected via structured regularization, along with spline-based regression to capture subtype-specific, time-varying covariate effects. Simulations demonstrate valid inference for time-varying effects and robust feature selection. Applied to transcriptomic profiles and longitudinal cognitive data from 1,020 older adults in the Religious Orders Study and the Rush Memory and Aging Project, TPClust identified four aging subtypes including intermediate subtypes not captured by unimodal approaches with distinct cognitive trajectories, time-varying risk profiles, clinical and neuropathological features, and multimodal molecular signatures.

bioinformatics↗

bioRxiv2025

CD33-CD45 Interaction Reveals a Mechanistic Link to Alzheimer's Disease Susceptibility

The innate immune gene CD33, encoding a myeloid inhibitory sialic acid-binding receptor, is associated with Alzheimers disease (AD) susceptibility. The AD-associated rs3865444CC risk variant reduces splicing of the sialic acid-binding domain and increases expression of the full-length (sialic acid-binding) CD33 isoform seven-fold compared to the rs3865444AA protective genotype. Here we identify CD45 as an immune cell-specific sialic acid-dependent cis CD33 binding partner, whose phosphatase activity is inhibited by CD33. Overexpression of CD33 or loss of CD45 contributes to impaired microglial clearance of amyloid beta and amyloid beta-induced loss of dendritic spines in microglial-neuronal co-cultures, aligning with a detrimental effect of CD33-mediated inhibition of CD45. CD33-CD45 interaction frequency was increased in monocytes from individuals with the rs3865444CC risk variant compared to rs3865444AA, as well as in AD compared to controls, independent of genotype. Furthermore, an interaction between CD33 and PTPRC (encoding CD45) gene expression in human brain tissue was associated with a pathological diagnosis of AD and global burden of AD pathology. Our findings thus establish a functional interaction between CD33 and CD45 relevant to AD susceptibility and systemic myeloid dysfunction in this disease.

neuroscience↗

bioRxiv2025

CD33 and Clusterin Interact Biophysically and Genetically to Modulate Alzheimer Risk

We report the results of structural, functional and genetic studies on the CD33 sialic acid- binding receptor that reveal how non-coding variants in CD33 alter risk for Alzheimers disease (AD). The full-length CD33M isoform, whose expression is upregulated by non-coding AD-risk alleles, preferentially forms dimers at the cell surface, where they interact with AD-related proteins (clusterin and A{beta}). This interaction induces CD33M inhibitory signalling and downregulates protective microglial functions including phagocytic removal of amyloid plaques. Human brain expression quantitative trait loci (eQTL) and causal mediation analyses confirm that quantitative interactions between CLU and CD33 genotypes modulate AD phenotypes and suggest that genotypes at these loci might be used to personalise future therapeutic approaches. Our work also highlights several other unexpected aspects of CD33 biology, including a soluble shed extracellular fragment of CD33M and a similar soluble secreted product arising from a truncating mutation in the CD33 extracellular domain (CD33M{Delta}4bp).

neuroscience↗

bioRxiv2025

Plastic-elastomer heterostructure for robust flexible brain-computer interfaces

Electronics for neural signal recording must be robust across multiple and deep brain regions while preserving tissue-level flexibility to ensure stable tracking over months or years. However, existing electronics cannot simultaneously achieve robustness and tissue-level flexibility, limiting their potential for customizable and scalable neuroscience research and clinical applications. Here, we introduce FlexiSoft, an electronic platform based on a plastic-elastomer heterostructure that uniquely integrates mechanical robustness and tissue-level flexibility. Compared to conventional flexible electronics of similar thickness, the FlexiSoft platform demonstrates an order-of- magnitude improvement in both mechanical robustness (critical energy release rate) and flexibility (flexural rigidity). Leveraging these mechanical advantages, we developed FlexiSoft probe for robust implantation, demonstrated by its ability to withstand repeated insertion and removal, as well as to reach centimeter-scale depths comparable to those in the human brain. The platform enables long-term recording from the same neurons across the hippocampus (HPC) and primary motor cortex (M1) during a months-long motor learning task, thereby revealing long-term dynamic changes in neuronal firing patterns. Additionally, FlexiSofts unique robustness and flexibility enable curved implantation routes, opening new directions of customizable implantation pathways. In summary, we present FlexiSoft as a novel, robust, and tissue-level flexible heterostructure electronics platform that advances flexible brain-computer interfaces (BCIs) with strong translational potential for neuroscience and clinical applications.

bioengineering↗

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

Inherited resilience to clonal hematopoiesis by modifying stem cell RNA regulation

Somatic mutations that increase hematopoietic stem cell (HSC) fitness drive their expansion in clonal hematopoiesis (CH) and predispose to blood cancers. Although CH frequently occurs with aging, it rarely progresses to overt malignancy. Population variation in the growth rate and potential of mutant clones suggests the presence of genetic factors protecting against CH, but these remain largely undefined. Here, we identify a non-coding regulatory variant, rs17834140-T, that significantly protects against CH and myeloid malignancies by downregulating HSC-selective expression and function of the RNA-binding protein MSI2. By modeling variant effects and mapping MSI2 binding targets, we uncover an RNA network that maintains human HSCs and influences CH risk. Importantly, rs17834140-T is associated with slower CH expansion rates in humans, and stem cell MSI2 levels modify ASXL1-mutant HSC clonal dominance in experimental models. These findings leverage natural resilience to highlight a key role for post-transcriptional regulation in human HSCs, and offer genetic evidence supporting inhibition of MSI2 or its downstream targets as rational strategies for blood cancer prevention.

genetics↗

bioRxiv2025

Spike sorting AI agent

Spike sorting is a fundamental process for decoding neural activity, involving preprocessing, spike detection, feature extraction, clustering, and validation. However, conventional spike sorting methods are highly fragmented, labor-intensive, and heavily reliant on expert manual curation, limiting their scalability and reproducibility. This challenge has become more pressing with advances in neural recording technology, such as high-density Neuropixels for large-scale neural recording or flexible electrodes for long-term stable recording over months to years. The volume and complexity of these datasets make manual curation infeasible, requiring an automated and scalable solution. Here, we introduce SpikeAgent, a multimodal large language model (LLM)-based AI agent that automates and standardizes the entire spike sorting pipeline. Unlike traditional approaches, SpikeAgent integrates multiple LLM backends, coding functions, and established algorithms, autonomously performing spike sorting with reasoning-based decision-making and real-time interaction with intermediate results. It generates interpretable reports, providing transparent justifications for each sorting decision, enhancing transparency and reliability. We benchmarked SpikeAgent against human experts across various neural recording technology, demonstrating its versatility and ability to achieve curation consistency that are equal to, or even higher than human experts. It also drastically reduces the expertise barrier and accelerates the curation and validation time by orders of magnitude. Moreover, it enables automated interpretability of the neural spiking data, which cannot be achieved by any conventional methods. SpikeAgent presents a paradigm shift in processing signals for neuroscience and brain-computer interfaces, while laying the ground for AI agent-augmented science across various domains.

neuroscience↗

bioRxiv2025

APOE-ϵ4-induced Fibronectin at the blood-brain barrier is a conserved pathological mediator of disrupted astrocyte-endothelia interaction in Alzheimer's disease

Blood-brain barrier (BBB) dysfunction is a key feature of Alzheimers disease (AD), particularly in individuals carrying the APOE-{varepsilon}4 allele. This dysfunction worsens neuroinflammation and hinders the removal of toxic proteins, such as amyloid-beta (A{beta}42), from the brain. In post-mortem brain tissues and in animal models, we previously reported that fibronectin accumulates at the BBB predominantly in APOE-{varepsilon}4 carriers. Furthermore, we found a loss-of-function variant in the fibronectin 1 (FN1) gene significantly reduces aggregated fibronectin levels and decreases AD risk among APOE-{varepsilon}4 carriers. Yet, the molecular mechanisms downstream of fibronectin at the BBB remain unclear. The extracellular matrix (ECM) plays a crucial role in maintaining BBB homeostasis and orchestrating the interactions between BBB cell types, including endothelia and astrocytes. Understanding the mechanisms affecting the ECM and BBB cell types will be critical for developing effective therapies against AD, especially among APOE-{varepsilon}4 carriers. Here, we demonstrate that APOE-{varepsilon}4, A{beta}42, and inflammation drive the induction of FN1 expression in several models including zebrafish, mice, iPSC-derived human 3D astrocyte and 3D cerebrovascular cell cultures, and in human brains. Fibronectin accumulation disrupts astroglial-endothelial interactions and the signalling cascade between vascular endothelial growth factor (VEGF), heparin-binding epidermal growth factor (HBEGF) and Insulin-like growth factor 1 (IGF1). This accumulation of fibronectin in APOE-{varepsilon}4- associated AD potentiates BBB dysfunction, which strongly implicates reducing fibronectin deposition as a potential therapeutic target for AD. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=197 SRC="FIGDIR/small/634732v1_ufig1.gif" ALT="Figure 1"> View larger version (70K): org.highwire.dtl.DTLVardef@1efff03org.highwire.dtl.DTLVardef@14f40cdorg.highwire.dtl.DTLVardef@27743aorg.highwire.dtl.DTLVardef@3fa9a9_HPS_FORMAT_FIGEXP M_FIG C_FIG Accessibility textThis image illustrates the effects of different APOE isoforms (ApoE-{varepsilon}3 and ApoE-{varepsilon}4) on blood-brain barrier (BBB) integrity, focusing on the molecular interactions between astrocytes and endothelial cells. This figure emphasizes the detrimental effects of ApoE-{varepsilon}4 on BBB integrity via fibronectin accumulation and altered signaling pathways. The top section provides a schematic overview of the blood-brain barrier, highlighting astrocytes, endothelial cells, and their interface. The left panel represents the ApoE-{varepsilon}3 condition: Normal fibronectin (FN1) levels support healthy interactions between astrocytes and endothelial cells. Growth factors, including VEGFA, HBEGF, and IGF1, maintain BBB integrity through their respective receptors (VEGFR and EGFR). Green arrows indicate activation of these signaling pathways. The right panel depicts the ApoE-{varepsilon}4 condition: Elevated fibronectin (FN1) disrupts astrocyte-endothelium interactions. FN1 binds integrins and activates focal adhesion kinase (FAK), inhibiting VEGFA, which is required for endothelial HBEGF that in turn activates IGF1 signaling. Red symbols indicate inhibition of HBEGF, VEGFA, and IGF1 pathways, leading to BBB dysfunction. HighlightsAPOE-{varepsilon}4 drives fibronectin deposition in Alzheimers, disrupting astrocyte-endothelia interactions. APOE-{varepsilon}4 and fibronectin co-localize, forming aggregates at blood-brain barrier (BBB). Fibronectin alters the signaling between VEGF, IGF1, and HBEGF impairing BBB function. Reducing fibronectin restores BBB integrity and offsets APOE-{varepsilon}4 pathology.

cell biology↗

bioRxiv2024

Relation of CMV and brain atrophy to trajectories of immunosenescence in diverse populations

Immunosenescence (ISC), the aging of the immune system, has largely been studied in populations of European descent. Here, circulating immune cell cytometric data from African-American, Hispanic, and non-Hispanic White participants were generated. Known and novel age effects were identified using either a meta-analysis approach or a parallel genetic approach. Most results are consistent across the three populations, but some cell populations display evidence of heterogeneity, such as a PD-L1+CD56+ NK cell subset. The study estimated "Immunological Age" (IA) during physiologic aging. While we found no relation of IA to Multiple Sclerosis, IA is associated with entorhinal cortex atrophy, a presymptomatic feature of Alzheimers disease, linking neurodegeneration and peripheral immunity. ISC trajectories were also inferred, highlighting age, CMV status, and genetic ancestry as key influences. Our assessment offers reference ISC trajectories for personalization of assessments of immune function over the life course in diverse populations.

immunology↗