Biology subjects

An, A.

Publications and source records attributed to An, A..

5 recordsLinked to original sources

bioRxiv2025

Neuronal APOE4 reduction with an APOE-I3-targeting ASO protects against neurodegeneration and neuroinflammation in an Alzheimer's disease mouse model

Apolipoprotein E4 (APOE4) is the strongest genetic risk factor for late-onset Alzheimers disease (AD). Within the central nervous system (CNS), APOE is produced by a variety of cell types, with differential roles in AD pathogenesis. Studies have shown that APOE4 produced by neurons plays a central role in promoting the development of major AD pathologies, including p-tau accumulation, neuroinflammation, and neurodegeneration, highlighting its role as an upstream initiating factor that affects other cell types and downstream AD-related pathologies. Here, we demonstrate that antisense oligonucleotides (ASOs) targeting APOE-I3, a neuron-specific splicing variant of APOE mRNA, effectively reduce APOE expression in neurons in vitro and in vivo. Treating PS19 tauopathy mice expressing APOE4 with this APOE-I3-targeting ASO reduces neuronal APOE4, rescues neurodegeneration, and diminishes neuroinflammation. Strikingly, the extent of neuronal APOE4 reduction predicts the efficacy of rescuing neurodegeneration. Single nucleus RNA-sequencing demonstrated that APOE-I3-targeting ASO treatment decreases disease associated neuronal and glial subtypes and increases a disease-protective microglial subtype. These findings suggest that preferential knockdown of neuronal APOE4 with an APOE-I3-targeting ASO protects against key hallmarks of AD pathology, elucidating a potential therapeutic approach for treating APOE4-driven AD.

neuroscience↗

bioRxiv2024

Data-driven discovery of cell-type-directed network-correcting combination therapy for Alzheimer's disease

Alzheimers disease (AD) is a multifactorial neurodegenerative disorder characterized by heterogeneous molecular changes across diverse cell types, posing significant challenges for treatment development. To address this, we introduced a cell-type-specific, multi-target drug discovery strategy grounded in human data and real-world evidence. This approach integrates single-cell transcriptomics, drug perturbation databases, and clinical records. Using this framework, letrozole and irinotecan were identified as a potential combination therapy, each targeting AD-related gene expression changes in neurons and glial cells, respectively. In an AD mouse model, this combination therapy significantly improved memory function and reduced AD-related pathologies compared to vehicle and single-drug treatments. Single-nuclei transcriptomic analysis confirmed that the therapy reversed disease-associated gene networks in a cell-type-specific manner. These results highlight the promise of cell-type-directed combination therapies in addressing multifactorial diseases like AD and lay the groundwork for precision medicine tailored to patient-specific transcriptomic and clinical profiles. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC="FIGDIR/small/627436v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@1e67fd5org.highwire.dtl.DTLVardef@1d2b779org.highwire.dtl.DTLVardef@10b6efforg.highwire.dtl.DTLVardef@1a44394_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2023

Dynamic gene expression analysis reveals distinct severity phases of immune and cellular dysregulation in COVID-19

BackgroundCOVID-19 patients experience dynamic changes in immune and cellular function over time with potential clinical implications. However, there is insufficient research investigating, on a gene expression level, the mechanisms that become activated or suppressed over time as patients deteriorate or recover, which can inform use of repurposed and novel drugs as therapies. ObjectiveTo investigate longitudinal changes in gene expression profiles throughout the COVID-19 disease timeline. MethodsThree-hundred whole blood samples from 128 adult patients were collected during hospitalization from COVID-19, with up to five samples per patient. Transcriptome sequencing (RNA-Seq), differential gene expression analysis and pathway enrichment was performed. Drug-gene set enrichment analysis was used to identify FDA-approved medications that could inhibit critical genes and proteins at each disease phase. Prognostic gene-expression signatures were generated using machine learning to distinguish 3 disease stages. ResultsSamples were longitudinally grouped by clinical criteria and gene expression into six disease phases: Mild, Moderate, Severe, Critical, Recovery, and Discharge. Distinct mechanisms with differing trajectories during COVID-19 hospitalization were apparent. Antiviral responses peaked early in COVID-19, while heme metabolism pathways became active much later during disease. Adaptive immune dysfunction, inflammation, and metabolic derangements were most pronounced during phases with higher disease severity, while hemostatic abnormalities were elevated early and persisted throughout the disease course. Drug-gene set enrichment analysis predicted repurposed medications for potential use, including platelet inhibitors in early disease, antidiabetic medications for patients with increased disease severity, and dasatinib throughout the disease course. Disease phases could be categorized using specific gene signatures for prognosis and treatment selection. Disease phases were also highly correlated to previously developed sepsis endotypes, indicating that severity and disease timing were significant contributors to heterogeneity observed in sepsis and COVID-19. ConclusionsHigher temporal resolution of longitudinal mechanisms in COVID-19 revealed multiple immune and cellular changes that were activated at different phases of COVID-19. Understanding how a patients gene expression profile changes over time can permit more accurate risk stratification of patients and provide time-dependent personalized treatments with repurposed medications. This creates an opportunity for timely intervention before patients transition to a more severe phase, potentially accelerating patients to recovery.

immunology↗

bioRxiv2022

Longitudinal monitoring of disease burden and response using ctDNA from dried blood spots in xenograft models

Whole genome sequencing (WGS) of circulating tumour DNA (ctDNA) is now a clinically important biomarker for predicting therapy response, disease burden and disease progression. However, the translation of ctDNA monitoring into vital pre-clinical PDX models has not been possible owing to low circulating blood volumes in small rodents. Here, we describe the longitudinal detection and monitoring of ctDNA from minute volumes of blood in PDX mice. We developed a xenograft Tumour Fraction (xTF) metric using shallow WGS of dried blood spots (DBS), and demonstrate its application to quantify disease burden, monitor treatment response and predict disease outcome in a pre-clinical study of PDX mice. Further, we show how our DBS-based ctDNA assay can be used to detect gene-specific copy number changes and examine the copy number landscape over time. Use of sequential DBS ctDNA assays will transform future trial designs in both mice and patients.

cancer biology↗

bioRxiv2021

Region-specific maladaptive gray matter myelination is associated with differential susceptibility to stress-induced behavior in male rodents and humans

Individual reactions to traumatic stress vary dramatically, yet the biological basis of this variation remains poorly understood. Recent studies demonstrate the surprising plasticity of oligodendrocytes and myelin with stress and experience, providing a potential mechanism by which trauma induces aberrant structural and functional changes in the adult brain. In this study, we utilized a translational approach to test the hypothesis that gray matter myelin contributes to traumatic-stress-induced behavioral variation in both rats and humans. We exposed adult, male rats to a single, severe stressor and used a multimodal approach to characterize avoidance, startle, and fear-learning behavior, as well as oligodendrocyte and myelin content in multiple brain areas. We found that oligodendrocyte cell density and myelin content were correlated with behavioral outcomes in a region-specific manner. Specifically, stress-induced avoidance positively correlated with hippocampal dentate gyrus oligodendrocytes and myelin. Viral overexpression of the oligodendrogenic factor Olig1 in the dentate gyrus was sufficient to induce an anxiety-like behavioral phenotype. In contrast, contextual fear learning positively correlated with myelin in the amygdala and spatial processing regions of the hippocampus. In a group of trauma-exposed US veterans, T1-/T2-weighted magnetic resonance imaging estimates of hippocampal and amygdala myelin associated with symptom profiles in a region-specific manner that mirrored the findings in rats. These results demonstrate a species- independent relationship between region-specific, gray matter oligodendrocytes and myelin and differential behavioral phenotypes following traumatic stress exposure. This study suggests a novel mechanism for brain plasticity that underlies individual variance in sensitivity to traumatic stress.

neuroscience↗