Biology subjects

Al-Dalahmah, O.

Publications and source records attributed to Al-Dalahmah, O..

10 recordsLinked to original sources

bioRxiv2026

The human-specific lncRNA HD-LINC drives lipid droplet-associated neurodegeneration in Huntington's disease

Huntington's disease (HD) is characterized by degeneration of striatal medium spiny neurons (MSNs), yet the human-specific regulatory mechanisms that contribute to neuronal vulnerability remain poorly understood. Here, we identify HD-LINC (LINC01139), a human-specific long intergenic noncoding RNA selectively induced in symptomatic HD patient-derived MSNs (HD-MSNs) and human HD caudate. Single-cell transcriptomic analysis in HD-MSNs revealed that HD-LINC was enriched in a symptomatic HD neuronal state associated with lipid metabolic and protein clearance regulation, while not observed in non-degenerative reprogrammed MSNs derived from pre-manifest HD individuals. Reducing HD-LINC attenuated mutant HTT aggregation, dystrophic neurites, DNA damage, and neuronal death, whereas HD-LINC overexpression exacerbated these phenotypes. Transcriptomic and lipidomic analyses further implicated HD-LINC in neuronal lipid regulation. We found that HD-MSNs exhibited aberrant accumulation of enlarged, low-mobility lipid droplets (LDs) within neurites, a previously unrecognized phenotype in patient-derived neurons. Critically, increased lipid peroxidation was observed within LD-enriched dystrophic neurites in HD-MSNs. HD-LINC knockdown cleared neuritic LD accumulation, restored soma-enriched LD distribution, and reduced lipid peroxidation. Finally, we developed antisense oligonucleotides that effectively reduced HD-LINC and reversed HD-LINC-associated phenotypes, nominating HD-LINC lowering as a potential therapeutic strategy in HD. These results identify HD-LINC as a human-specific regulator of neuronal LD spatial organization, lipid peroxidation, and neuronal degeneration in HD. They further reveal dysregulated neuritic LD accumulation driven by HD-LINC, and highlight lincRNA-mediated lipid dysregulation as a significant contributor to neuronal vulnerability to degeneration.

neuroscience↗

bioRxiv2026

Stage-Specific NF-κB RelA and IRF4 Programs Drive -Synuclein-Induced Disease-Associated Microglia Differentiation

Microglial activation in response to aggregated -synuclein (-syn) accumulation is a pathological hallmark of Parkinson disease (PD). A distinct activated microglial state, disease-associated microglia (DAM), has been identified across multiple neurodegenerative disorders, including PD. However, the transcriptional and epigenetic programs governing DAM differentiation remain unclear. Here, we show that neuronal -syn overexpression drives progressive microglial state transitions toward DAM, accompanied by increased phagocytic activity and enhanced cytokine and chemokine production. Integrative transcriptomic and chromatin accessibility analyses reveal a hierarchical NF-{kappa}B--AP-1--IRF regulatory program underlying these state transitions. Microglial NF-{kappa}B p65 (RelA) or IRF4 deficiency impairs microglial progression toward DAM, with RelA and IRF4 governing early microglial activation and subsequent DAM differentiation, respectively. Enrichment of NF-{kappa}B, AP-1, and IRF motifs in DAM in human PD supports conservation of this regulatory program across species. Together, our findings establish RelA and IRF4 as sequential, stage-specific regulators that coordinate -syn-induced DAM differentiation in PD.

immunology↗

bioRxiv2026

Electrophysiologically Targeted Biopsies Reveal the Transcriptional Landscape of Focal Epilepsy

Up to 30% of patients with epilepsy have intractable seizures, yet the mechanisms of focal ictogenesis remain unclear. Tissue involvement in ictal regions is heterogeneous, with different regions playing distinct roles in ictogenesis, seizure propagation, and resistance to spread. These roles are reflected in electrophysiologic differences between the seizure focus and the ictal penumbra, where evidence of synaptic spread is present but excitatory firing is constrained by largely intact inhibition. Investigation of the disruption of the normal interplay between excitatory and inhibitory activity, thought to underlie ictogenesis across a range of epilepsy etiologies, is limited by network complexity and cellular heterogeneity in human tissue samples. In this study, we relate cellular and molecular alterations to excitatory-inhibitory disruption in network dynamics defined by electrophysiologic features. This work may aid in the identification of clinically relevant tissue biomarkers and support novel preclinical therapeutic approaches for treatment-resistant focal epilepsy disorders. We developed a novel intracranial EEG guided, MRI-localized approach to sample paired biopsies from 11 patients with drug-resistant focal epilepsy with diverse etiologies, which were then studied using single-nucleus RNA sequencing (snRNAseq) and immunohistochemistry (IHC). EEG recorded from stereotactically implanted depth arrays (sEEG) was used to identify regions of epileptic involvement, based on findings from prior simultaneous clinical and microelectrode recordings. This approach addresses the intrinsic heterogeneity due to etiology and cortical architecture through paired, within-patient comparisons. We identified distinct cell-type specific transcriptional signatures that differentiate cellular populations in the seizure focus and ictal penumbra in intractable focal epilepsies. Our findings provide a link between tissue composition and gene expression that correlate with electrographic features in a heterogeneous seizure landscape. Our findings support common pathways of seizure generation and spread that are conserved across disease etiologies. Relative depletion of interneuron populations in the seizure focus supports the hypothesis of disrupted inhibition as a driver of epileptiform activity in the seizure focus. The enrichment of plasticity-associated gene signatures in the penumbra suggests a complex interaction of these regions with the seizure focus, as well as the role of the penumbra in enabling or limiting seizure expansion. This study provides a novel methodology for tissue sampling in epilepsy and uncovers biologically relevant tissue signatures that provide grounds for future work in targeting cellular and molecular alterations present in focal epilepsies.

neuroscience↗

bioRxiv2024

The landscape of glial pathology and T-call response in Parkinson's substantia nigra

Parkinsons Disease (PD) is a progressive neurodegenerative disease that leads to debilitating movement disorders and often dementia. Recent evidence, including identification of specific peripheral T-cell receptor sequences, indicates that the adaptive immune response is associated with disease pathogenesis. However, the properties of T-cells in the brain regions where neurons degenerate are not well characterized. We have analyzed the identities and interactions of T-cells in PD in post-mortem brain tissue using single nucleus RNA sequencing, spatial transcriptomics and T-cell receptor sequencing. We found that T-cells in the substantia nigra of PD brain donors exhibit a CD8+ resident memory phenotype, increased clonal expansion, and altered spatial relationships with astrocytes, myeloid cells, and endothelial cells. We also describe regional differences in astrocytic responses to neurodegeneration. Our findings nominate potential molecular and cellular candidates that allow a deeper understanding of the pathophysiology of neurodegeneration in PD. Together, our work represents a major single nucleus and spatial transcriptional resource for the fields of neurodegeneration and PD.

neuroscience↗

bioRxiv2023

Multi-OMIC analysis of Huntington disease reveals a neuroprotective astrocyte state

Huntington disease (HD) is an incurable neurodegenerative disease characterized by neuronal loss and astrogliosis. One hallmark of HD is the selective neuronal vulnerability of striatal medium spiny neurons. To date, the underlying mechanisms of this selective vulnerability have not been fully defined. Here, we employed a multi-omic approach including single nucleus RNAseq (snRNAseq), bulk RNAseq, lipidomics, HTT gene CAG repeat length measurements, and multiplexed immunofluorescence on post-mortem brain tissue from multiple brain regions of HD and control donors. We defined a signature of genes that is driven by CAG repeat length and found it enriched in astrocytic and microglial genes. Moreover, weighted gene correlation network analysis showed loss of connectivity of astrocytic and microglial modules in HD and identified modules that correlated with CAG-repeat length which further implicated inflammatory pathways and metabolism. We performed lipidomic analysis of HD and control brains and identified several lipid species that correlate with HD grade, including ceramides and very long chain fatty acids. Integration of lipidomics and bulk transcriptomics identified a consensus gene signature that correlates with HD grade and HD lipidomic abnormalities and implicated the unfolded protein response pathway. Because astrocytes are critical for brain lipid metabolism and play important roles in regulating inflammation, we analyzed our snRNAseq dataset with an emphasis on astrocyte pathology. We found two main astrocyte types that spanned multiple brain regions; these types correspond to protoplasmic astrocytes, and fibrous-like - CD44-positive, astrocytes. HD pathology was differentially associated with these cell types in a region-specific manner. One protoplasmic astrocyte cluster showed high expression of metallothionein genes, the depletion of this cluster positively correlated with the depletion of vulnerable medium spiny neurons in the caudate nucleus. We confirmed that metallothioneins were increased in cingulate HD astrocytes but were unchanged or even decreased in caudate astrocytes. We combined existing genome-wide association studies (GWAS) with a GWA study conducted on HD patients from the original Venezuelan cohort and identified a single-nucleotide polymorphism in the metallothionein gene locus associated with delayed age of onset. Functional studies found that metallothionein overexpressing astrocytes are better able to buffer glutamate and were neuroprotective of patient-derived directly reprogrammed HD MSNs as well as against rotenone-induced neuronal death in vitro. Finally, we found that metallothionein-overexpressing astrocytes increased the phagocytic activity of microglia in vitro and increased the expression of genes involved in fatty acid binding. Together, we identified an astrocytic phenotype that is regionally-enriched in less vulnerable brain regions that can be leveraged to protect neurons in HD.

neuroscience↗

bioRxiv2022

Biologically-informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in post-treatment glioblastoma

Intratumoral heterogeneity poses a significant challenge to the diagnosis and treatment of glioblastoma (GBM). This heterogeneity is further exacerbated during GBM recurrence, as treatment-induced reactive changes produce additional intratumoral heterogeneity that is ambiguous to differentiate on clinical imaging. There is an urgent need to develop non-invasive approaches to map the heterogeneous landscape of histopathological alterations throughout the entire lesion for each patient. We propose to predictively fuse Magnetic Resonance Imaging (MRI) with the underlying intratumoral heterogeneity in recurrent GBM using machine learning (ML) by leveraging image-localized biopsies with their associated locoregional MRI features. To this end, we develop BioNet, a biologically-informed neural network model, to predict regional distributions of three tissue-specific gene modules: proliferating tumor, reactive/inflammatory cells, and infiltrated brain tissue. BioNet offers valuable insights into the integration of multiple implicit and qualitative biological domain knowledge, which are challenging to describe in mathematical formulations. BioNet performs significantly better than a range of existing methods on cross-validation and blind test datasets. Voxel-level prediction maps of the gene modules by BioNet help reveal intratumoral heterogeneity, which can improve surgical targeting of confirmatory biopsies and evaluation of neuro-oncological treatment effectiveness. The non-invasive nature of the approach can potentially facilitate regular monitoring of the gene modules over time, and making timely therapeutic adjustment. These results also highlight the emerging role of ML in precision medicine.

cancer biology↗

bioRxiv2022

Single nuclei RNAseq analysis of HD mouse models and human brain reveals impaired oligodendrocyte maturation and potential role for thiamine metabolism

The complexity of affected brain regions and cell types is a challenge for Huntingtons disease (HD) treatment. Here we used single nucleus RNA sequencing (snRNAseq) to investigate mechanism of pathology in the cortex and striatum from R6/2 mice at 8 and 12w and in three regions of human HD post-mortem tissue. We identified cell type-specific and cell agnostic signatures and found changes suggesting oligodendrocytes (OLs) and oligodendrocyte precursors (OPCs) were arrested in intermediate maturation states. OL-lineage regulators OLIG1 and OLIG2 were negatively correlated with CAG length in human OPCs, and ATACseq analysis of HD mouse NeuN-negative cells showed decreased accessibility of sites regulated by OL maturation genes. Glucose and lipid metabolism were implicated in abnormal cell maturation and PRKCE and Thiamine Pyrophosphokinase 1 were identified as central genes. High dose thiamine/biotin treatment of R6/1 HD mice to target thiamine metabolism not only restored OL maturation, but also rescued pathology in neurons. These findings reveal insights into HD OL pathology that spans multiple brain regions and link OL maturation deficits to abnormal thiamine metabolism.

neuroscience↗

bioRxiv2022

Glioblastoma states are defined by cohabitating cellular populations with progression-, imaging- and sex-distinct patterns

Background: Magnetic Resonance Imaging (MRI) is the mainstay for neurosurgical oncology but not for informing us about glioma biology. An obstacle to developing MR-based glioma biomarkers is the absence of rigorous correlation between MRI features and glioma biology as assessed in multi-regional biopsies, within and across patients. Methods: We directly addressed this obstacle by collating a unique cohort of 202 MRI-localized biopsies from 58 patients. We define a low-dimensional transcriptional pseudotime continuum along which heterogeneous high-grade glioma (HGG) samples organize both within and across patients. Results: We observe three polarized transcriptional tissue states: infiltrated brain, immune/inflammatory, and proliferative associated with patterns of cohabitation of cellular subpopulations. The states and deconvolved populations show correlation with enhancement status on T1Gd MRI. Moreover, discrete MRI habitats, regions sharing common imaging features, defined as combinations of high or low signal intensity across multiparametric MRI revealed 14 MRI habitats. We order the MRI habitats according to the average pseudotime on the transcriptional continuum. We find that MRI habitats with low pseudotime (associated with early tumor development and diffusely invaded brain tissue) localized at the periphery of the tumor whilst high pseudotime either proliferative or immune/inflammatory states were towards the core of the lesion. We find that composition of MRI habitats is impacted by MGMT status. Conclusion: This suggests that ongoing aggregation of MRI-localized biopsies may augment our projection of biology onto MRI habitats to support the noninvasive identification of cellular ecologies within and across each patient's tumor.

cancer biology↗

bioRxiv2021

Re-convolving the compositional landscape of primary and recurrent glioblastoma using single nucleus RNA sequencing

Glioblastoma (GBM) is an aggressive diffusely infiltrating neoplasm that spreads beyond surgical resection margins, where it intermingles with non-neoplastic brain cells. This complex microenvironment harboring infiltrating glioma and non-neoplastic brain cells is the origin of tumor recurrence. Thus, understanding the cellular and molecular features of the glioma microenvironment is therapeutically and prognostically important. We used single-nucleus RNA sequencing (snRNAseq) to determine the cellular composition and transcriptional states in primary and recurrent glioma and identified three compositional tissue-states defined by the observed patterns of cohabitation between neoplastic and non-neoplastic brain cells. These comprise states enriched in A) neurons and non-neoplastic glia, B) reactive astrocytes and inflammatory cells, and C) proliferating tumor cells. The tissue states also showed distinct associations with the different transcriptional states of GBM cells. Spatial transcriptomics revealed that the cell-types/transcriptional-states associated with each tissue state colocalize in space. Tissue states are clinically significant because they correlate with radiographic, histopathologic, and prognostic features. Importantly, we found that our compositionally-defined tissue states are enriched in distinct metabolic pathways. One such pathway is fatty acid biosynthesis, which was enriched in tissue state B - a state enriched in recurrent glioblastoma and associated with shorter overall survival- and composed of astrocyte-like/mesenchymal glioma cells, reactive astrocytes, and monocyte-like myeloid cells. We showed that treating acute slices of GBM with a fatty acid synthesis inhibitor is sufficient to deplete the transcriptional signature of tissue state B. Our findings define a novel compositional approach to analyze glioma-infiltrated tissue which allows us to discover prognostic and targetable features, paving the way to new mechanistic and therapeutic discoveries.

pathology↗

bioRxiv2019

Single-nucleus RNA-seq identifies Huntington disease astrocyte states

Huntington Disease (HD) is an inherited movement disorder caused by expanded CAG repeats in the Huntingtin gene. We have used single nucleus RNASeq (snRNASeq) to uncover cellular phenotypes that change in the disease, investigating single cell gene expression in cingulate cortex of patients with HD and comparing the gene expression to that of patients with no neurological disease. In this study, we focused on astrocytes, although we found significant gene expression differences in neurons, oligodendrocytes, and microglia as well. In particular, the gene expression profiles of astrocytes in HD showed multiple signatures, varying in phenotype from cells that had markedly upregulated metallothionein and heat shock genes, but had not completely lost the expression of genes associated with normal protoplasmic astrocytes, to astrocytes that had substantially upregulated GFAP and had lost expression of many normal protoplasmic astrocyte genes as well as metallothionein genes. When compared to astrocytes in control samples, astrocyte signatures in HD also showed downregulated expression of a number of genes, including several associated with protoplasmic astrocyte function and lipid synthesis. Thus, HD astrocytes appeared in variable transcriptional phenotypes, and could be divided into several different \"states\", defined by patterns of gene expression. Ultimately, this study begins to fill the knowledge gap of single cell gene expression in HD and provide a more detailed understanding of the variation in changes in gene expression during astrocyte \"reactions\" to the disease.

neuroscience↗