Biology subjects

Sharp, M.

Publications and source records attributed to Sharp, M..

14 recordsLinked to original sources

bioRxiv2026

Schizophrenia-associated DNA methylation differences in the cortex are neuron-specific

Schizophrenia is a complex neuropsychiatric disorder in which genetic risk is thought to converge on cell type-specific regulatory mechanisms in the brain. We performed a cell type-resolved epigenome-wide association study (EWAS) of schizophrenia using fluorescence-activated nuclei sorting (FANS) to isolate neuron-enriched (NeuN+), oligodendrocyte-enriched (SOX10+) and other glial-enriched (NeuN-/SOX10-) nuclei populations alongside total prefrontal cortex nuclei fractions from 216 donors (104 schizophrenia cases and 112 controls). We identified 16 differentially methylated positions (DMPs) in neuron-enriched nuclei at experiment-wide significance and more than 400 additional neuronal DMPs at a discovery threshold. In contrast, no significant associations were identified in oligodendrocyte-enriched, glial-enriched or total nuclei fractions, demonstrating that schizophrenia-associated cortical methylomic variation is highly neuron-specific and largely masked in bulk tissue analyses. Neuronal DMPs exhibited a significant bias towards hypomethylation in schizophrenia and were enriched at loci implicated by genetic studies, including CACNA1C, CACNA1G and TRIO. Pathway analyses implicated genes involved in neurodevelopment, cell adhesion, synapse organisation, neurotransmission and synaptic plasticity. Schizophrenia-associated DNA methylation signatures identified in prefrontal cortex neurons showed correlated effects in neuronal nuclei isolated from the hippocampus and striatum, indicating partial conservation of disease-associated epigenetic alterations across brain regions. Together, these findings provide strong evidence for widespread neuron-specific epigenetic dysregulation in schizophrenia and highlight the importance of cell type-resolved approaches for elucidating the molecular mechanisms underlying psychiatric disease.

genomics↗

bioRxiv2026

The practical impact of numerical variability on structural MRI measures of Parkinson's disease

Numerical variability is rarely quantified in neuroimaging despite many measures relying on subtle morphometric differences across individuals. We instrumented FreeSurfer 7.3.1, a widely used neuroimaging pipeline, to simulate numerical differences across computational environments, and used it to measure numerical variability in MRI analyses of Parkinsons disease patients and controls. In multiple cortical and subcortical regions, numerical variation reached nearly one-third of the population variability, altering statistical conclusions about group differences and clinical associations. To assess the impact of numerical noise in existing studies, we developed a practical tool that estimates the Numerical-Population Variability Ratio (NPVR) in a study, and propagates the resulting numerical variability to common statistics and associated p-values. By applying this framework to thirteen previously published studies reporting MRI measures in Parkinsons disease, we quantified the probability of numerically induced false positives and false negatives in the literature, highlighting a substantial impact of numerical variability on MRI measures of Parkinsons disease with an average significance-flip probability of 5% for cross-sectional studies and 10% for longitudinal studies. These results underscore the importance of systematically evaluating numerical stability in neuroimaging and provide a practical framework to do so.

bioinformatics↗

bioRxiv2025

Slow Spindle Trains During Daytime Naps are Associated with Improved Declarative Memory Consolidation

Memory consolidation refers to the process by which newly encoded memories are strengthened and retained over time, and ample evidence indicates that sleep supports this process for both procedural and declarative memories. Although sleep spindles during non-rapid eye movement (NREM) sleep have been associated to consolidation, it remains unclear whether all spindle types contribute equally. Spindles vary in frequency and topography-slow spindles ([≤]12.5Hz) predominating over frontal regions, whereas fast spindles (>12.5Hz) peak parietally - and recent work suggests that procedural memory consolidation during overnight sleep is related to the temporal organization of spindles in trains (i.e., events occurring <6s apart). Here we investigated whether a similar mechanism operates for declarative memory during daytime naps. Participants were assigned to a Nap (N=23) or No-Nap (N=15) group, and completed an object-spatial location task involving 36 item-location associations. Memory was assessed immediately after learning and again following a 90-minute nap or an equivalent wake period. Results showed that the Nap group exhibited significantly better delayed memory, as measured by combined recall-recognition score, and a greater proportion of participants maintained or improved their performance. In the Nap group, memory performance correlated with local spindle density at frontal and parietal sites, and, critically, with the proportion of slow spindles clustered in trains during NREM2. These findings suggest the temporal organization of slow spindles into clusters support declarative memory consolidation, pointing to a shared spindle-based mechanism across domains.

neuroscience↗

bioRxiv2025

Neutrophil extracellular traps offer a new therapeutic target for elephant endotheliotropic herpes hemorrhagic disease (EEHV-HD)

Elephant survival is threatened by a devastating hemorrhagic disease called elephant endotheliotropic herpes virus-hemorrhagic disease (EEHV-HD). Once clinical signs are observed in elephants, the disease progresses rapidly and frequently results in death. EEHV-HD negatively impacts elephant conservation because very young, reproductively immature elephants are most at risk for death. Ongoing efforts to understand disease pathogenesis and progression may identify treatment targets and improve clinical outcomes. In some lethal EEHV-HD cases, microthrombosis has been observed in organ tissues similar to other hemorrhagic diseases in humans and animals where sticky webs of protein-coated DNA strands called neutrophil extracellular traps (NETs) exacerbate thrombosis and hemorrhage associated with disseminated intravascular coagulation (DIC). In this study, we sought to identify if NET formation occurs in elephants and could contribute to poor outcomes in EEHV-HD. Our study demonstrated NET release for the first time from elephant heterophils (neutrophils) that occurred in response to various stimuli, including plasma from EEHV-HD affected elephants. EEHV-HD affected tissues contained extensive NETs suggesting that dysregulated NET formation contributes to pathogenesis of this disease. Importantly, elephant neutrophils were blocked from releasing NETs in response to EEHV-HD plasma using known NET inhibitors. The ability to stop NETs in EEHV-HD offers a new therapeutic approach that could be combined with current therapies to improve survival for affected elephants and to positively impact conservation efforts.

immunology↗

bioRxiv2025

Drug and single-cell gene expression integration identifies sensitive and resistant glioblastoma cell populations

Glioblastoma (GBM) remains the most common and lethal adult malignant primary brain cancer with few treatment options. A significant issue hindering GBM therapeutic development is intratumor heterogeneity. GBM tumors contain neoplastic cells within a spectrum of different transcriptional states. Identifying effective therapeutics requires a platform that predicts the differential sensitivity and resistance of these states to various treatments. Here, we developed a novel framework, ISOSCELES (Inferred cell Sensitivity Operating on the integration of Single-Cell Expression and L1000 Expression Signatures), to quantify the cellular drug sensitivity and resistance landscape. Using single-cell RNA sequencing of newly diagnosed and recurrent GBM tumors, we identified compounds from the LINCS L1000 database with transcriptional response signatures selectively discordant with distinct GBM cell states. We validated the significance of these findings in vitro, ex vivo, and in vivo, and identified a novel combination of an OLIG2 inhibitor and Depatux-M for GBM. Our studies suggest that ISOSCELES identifies cell states sensitive and resistant to targeted therapies in GBM and that it can be applied to identify new synergistic combinations. HighlightsO_LIIntegration of GBM single-cell RNA sequencing data with L1000-derived drug response signatures facilitates clustering of tumor cells and small molecules on cell-drug connectivity. C_LIO_LICell-drug connectivity predicts the identities of drug-sensitive and resistant cell states. C_LIO_LIIn silico perturbation analysis using cell-drug connectivity predicts drug-induced changes in the cell-drug connectivity landscape in vivo. C_LIO_LIIn silico perturbation analysis to predict drug-induced changes in the tumor cell-drug connectivity landscape predicts drug combinations that synergize in vivo to extend survival. C_LI

cancer biology↗

bioRxiv2024

Identification of disease-specific vulnerability states at the single-cell level

Intratumor heterogeneity in glioblastoma (GBM) impedes successful treatment as it is not obvious which tumor cells should be targeted. Here, we posit that single-cell-resolution transcriptomic data can be integrated with loss-of-function screens to identify the most critical cells to target within a tumor. We parsed CRISPR screen data from the Dependency Map (DepMap) Consortium and identified a GBM Dependency Signature (GDS) - 168 genes that are essential for GBM cell viability in vitro. Through similarity scoring of GDS transcriptomic profiles in single-cell RNA-sequencing (scRNA-seq) data and iterative hierarchical clustering, we identify and report 3 single-cell vulnerability states (VS) characterized in 49 GBM tumors using both scRNA-seq and spatial transcriptomic data. These VS reflect single-cell gene dependencies and differ significantly in enrichment profiles and spatial distributions. Additionally, each VS is differently sensitive to cancer drugs, with VS2 solely responsive to temozolomide treatment. Importantly, the proportion of VS in each GBM tumor is variable, suggesting a means of stratifying patients in clinical trials. Collectively, we have developed a novel computational pipeline to identify unique vulnerability states in GBM and other cancers, which can be used to identify existing or novel drugs for incurable diseases.

cancer biology↗

bioRxiv2024

The impact of FreeSurfer versions on structural neuroimaging analyses of Parkinson's disease

Image processing software impacts the quantification of brain measures, playing an important role in the search for clinical biomarkers. We investigated the impact of the variability between FreeSurfer releases on the estimation of structural brain measures in Parkinsons disease (PD). Structural brain scans from 106 controls and 209 patients were analyzed with FreeSurfer versions 5.3, 6.0.1, and 7.3.2, including longitudinal data from 125 patients. First, we measured the differences in the estimation of volume, surface area, and cortical thickness between FreeSurfer versions. Second, we focused on the relationship between MRI-derived brain measures and group differences as well as disease severity clinical outcomes, which were evaluated both cross-sectionally and longitudinally. We found high software-induced variability in the estimation of all three structural measures, which impacted clinical outcomes. There were differences between software versions in group differences between patients and healthy controls in subcortical volume and vertex-wise cortical thickness. Software variability also impacted the estimated relationship between brain structure and disease severity in patients. Hence, software variability not only relates to the estimation of structural measures, but it also impacts clinically- relevant MRI measures. Our study provides insight into the reproducibility of structural neuroimaging studies in PD populations.

neuroscience↗

bioRxiv2023

Sleep spindle density and temporal clustering are associated with sleep-dependent memory consolidation in Parkinson's disease

Sleep is required for successful memory consolidation. Sleep spindles, bursts of oscillatory activity occurring during non-REM sleep, are known to be crucial for this process and, recently, it has been proposed that the temporal organization of spindles into clusters might additionally play a role in memory consolidation. In Parkinsons disease, spindle activity is reduced, and this reduction has been found to be predictive of cognitive decline. However, it remains unknown whether alterations in sleep spindles in Parkinsons disease are predictive of sleep-dependent cognitive processes like memory consolidation, leaving open questions about the possible mechanisms linking sleep and more general cognitive state in Parkinsons patients. The current study sought to fill this gap by recording overnight polysomnography and measuring overnight declarative memory consolidation in a sample of thirty-five Parkinsons patients. Memory consolidation was measured using a verbal paired-associates task administered before and after the night of recorded sleep. We found that lower sleep spindle density at frontal leads during non-REM stage 3 was associated with worse overnight declarative memory consolidation. We also found that patients who showed less temporal clustering of spindles exhibited worse declarative memory consolidation. These results suggest alterations to sleep spindles, which are known to be a consequence of Parkinsons disease, might represent a mechanism by which poor sleep leads to worse cognitive function in Parkinsons patients. Statement of significanceSleep -- particularly spindle activity -- is critical for memory consolidation, a core cognitive process. Changes to the architecture and oscillations of sleep are well documented in Parkinsons disease (PD) and have been associated with worse overall cognition. However, whether altered sleep plays a causal role in this relationship, by directly interfering with sleep-dependent cognitive processes, or whether it represents a mere epiphenomenon of advancing disease, remains unknown. Our study is the first to investigate a possible direct relationship between sleep and cognition in PD. We show that sleep spindles and their temporal clustering into trains relate to impairments in overnight declarative memory consolidation in patients. These findings are an important first step towards identifying modifiable sources of cognitive impairment in PD.

neuroscience↗

bioRxiv2023

Predicting Parkinson's disease progression using MRI-based white matter radiomic biomarker and machine learning: a reproducibility and replicability study

BackgroundThe availability of reliable biomarkers of Parkinsons disease (PD) progression is critical to the understanding of the disease and development of treatment options. Magnetic Resonance Imaging (MRI) provides a promising source of PD biomarkers, however, neuroimaging results have been shown to be markedly sensitive to analytical conditions and population sampling, which motivates investigations of their robustness. This study is part of a project to investigate the replicability of 11 structural MRI measures of PD identified in a recent review. ObjectiveThis paper attempts to reproduce (similar data, similar analysis) and replicate (variations in data and analysis) the design of the machine learning (ML) model described in [1] to predict PD progression from T1-weighted MRIs. MethodsWe used the Parkinsons Progression Markers Initiative dataset (PPMI, ppmi-info.org) used in [1] and we followed as closely as possible the original methods. We also investigated slight methodological variations in cohort selection, feature extraction, ML model design, and evaluation techniques. ResultsThe Area under the ROC Curve (AUC) achieved by our model closely reproducing the original study remained lower than 0.5. Across all tested models, we obtained a peak AUC of 0.685, which is better than chance performance but remained lower than the AUC value of 0.795 reported in [1]. ConclusionWe managed to train a model that predicts disease progression with a performance better than chance on a cohort extracted from the PPMI dataset, using methods adapted from [1]. However, the performance of this model remains substantially lower than the one reported in [1]. Our difficulties to reproduce or replicate the original work are likely explained by the relatively low sample size in the original study. We provide recommendations on how to improve the reproducibility of MRI-based ML models of PD in the future.

neuroscience↗

bioRxiv2023

Longitudinal brain structure changes in Parkinson's disease: a replication study

ContextAn existing major challenge in Parkinsons disease (PD) research is the identification of biomarkers of disease progression. While Magnetic Resonance Imaging (MRI) is a potential source of PD biomarkers, none of the MRI measures of PD are robust enough to warrant their adoption in clinical research. This study is part of a project that aims to replicate 11 PD studies reviewed in a recent survey (JAMA neurology, 78(10) 2021) to investigate the robustness of PD neuroimaging findings to data and analytical variations. ObjectiveThis study attempts to replicate the results in Hanganu et al. (Brain, 137(4) 2014) using data from the Parkinsons Progression Markers Initiative (PPMI). MethodsUsing 25 PD subjects and 18 healthy controls, we analyzed the rate of change of cortical thickness and of the volume of subcortical structures, and we measured the relationship between MRI structural changes and cognitive decline. We compared our findings to the results in the original study. ResultsSimilarly to the original study, PD patients with mild cognitive impairment (MCI) exhibited increased cortical thinning over time compared to patients without MCI in the right middle temporal gyrus, insula, and precuneus. (2) The rate of cortical thinning in the left inferior temporal and precentral gyri in PD patients correlated with the change in cognitive performance. (3) There were no group differences in the change of subcortical volumes. (4) We did not find a relationship between the change in subcortical volumes and the change in cognitive performance. ConclusionDespite important differences in the dataset used in this replication study, and despite differences in sample size, we were able to partially replicate the original results. We produced a publicly available reproducible notebook allowing researchers to further investigate the reproducibility of the results in Hanganu et al. (2014) when more data becomes available in PPMI.

neuroscience↗

bioRxiv2023

Construction of a searchable database for gene expression changes in spinal cord injury experiments

Spinal cord injury (SCI) is a debilitating disease resulting in an estimated 18,000 new cases in the United States on an annual basis. Significant behavioral research on animal models has led to a large amount of data, some of which has been catalogued in the Open Data Commons for Spinal Cord Injury (ODC-SCI). More recently, high throughput sequencing experiments have been utilized to understand molecular mechanisms associated with SCI, with nearly 6,000 samples from over 90 studies available in the Sequence Read Archive. However, to date, no resource is available for efficiently mining high throughput sequencing data from SCI experiments. Therefore, we have developed a protocol for processing RNA-Seq samples from high-throughput sequencing experiments related to SCI resulting in both raw and normalized data that can be efficiently mined for comparisons across studies as well as homologous discovery across species. We have processed 1,196 publicly available RNA-seq samples from 50 bulk RNA-Seq studies across nine different species, resulting in an SQLite database that can be used by the SCI research community for further discovery. We provide both the database as well as a web-based front-end that can be used to query the database for genes of interest, differential gene expression, genes with high variance, and gene set enrichments.

bioinformatics↗

bioRxiv2021

Preserved motor memory in Parkinson's disease

Patients with Parkinsons disease, who lose the dopaminergic projections to the striatum, are impaired in certain aspects of motor learning. Recent evidence suggests that, in addition to its role in motor performance, the striatum plays a key role in the memory of motor learning. Whether Parkinsons patients have impaired motor memory and whether motor memory is modulated by dopamine at the time of initial learning is unknown. To address these questions, we measured memory of a learned motor sequence in Parkinsons patients who were either On or Off their dopaminergic medications. We compared them to a group of older and younger controls. Contrary to our predictions, motor memory was not impaired in patients compared to older controls, and was not influenced by dopamine state at the time of initial learning. To probe post-learning consolidation processes, we also tested whether learning a new sequence shortly after learning the initial sequence would interfere with later memory. We found that, in contrast to younger adults, neither older adults nor patients were susceptible to this interference. These findings suggest that motor memory is preserved in Parkinsons patients and raise the possibility that motor memory in patients is supported by compensatory non-dopamine sensitive mechanisms. Furthermore, given the similar performance characteristics observed in the patients and older adults and the absence of an effect of dopamine, these results raise the possibility that aging and Parkinsons disease affect motor memory in similar ways.

neuroscience↗

bioRxiv2021

Selective attention is insensitive to reward and to dopamine in Parkinson's disease

Patients with Parkinsons disease exhibit reduced reward sensitivity in addition to early cognitive deficits, among which attention impairments are common. Attention allocation is controlled at multiple levels and recent work has shown that reward, in addition to its role in the top-down goal-directed control of attention, also guides the automatic allocation of attention resources, a process thought to rely on striatal dopamine. Whether Parkinsons patients, due to their striatal dopamine loss, suffer from an inability to use reward information to guide the allocation of their attention is unknown. To address this question, we tested Parkinsons patients (n=43) ON and OFF their dopaminergic medication, and compared them to a group of older controls (n=31). We used a standard two-phase attention capture task in which subjects were first implicitly trained to make colour-reward associations. In the second phase, the previously reward-associated colours were used as distractors in a visual search task. We found that patients did not use reward information to modulate their attention; they were similarly distracted by the presence of low and high-reward distractors. However, contrary to our predictions, we did not find evidence that dopamine modulated this inability to use reward to guide attention allocation. Additionally, we found slightly increased overall distractibility in Parkinsons patients compared to older controls, but interestingly, the degree of distractibility was not influenced by dopamine replacement. Our results suggest that loss of reward-guided attention allocation may contribute to early attention deficits and raise the possibility that this inability to prioritize cognitive resource allocation could contribute to executive deficits more broadly in Parkinsons disease.

neuroscience↗

bioRxiv2019

Monoubiquitination by the Fanconi Anemia core complex locks FANCI:FANCD2 on DNA in filamentous arrays

FANCI:FANCD2 monoubiquitination is a critical event for replication fork stabilization by the Fanconi anemia (FA) DNA repair pathway. It has been proposed that at stalled replication forks, monoubiquitinated-FANCD2 serves to recruit DNA repair proteins that contain ubiquitin-binding motifs. Here we have reconstituted the FA pathway in vitro to study functional consequences of FANCI:FANCD2 monoubiquitination. We report that monoubiquitination does not promote any specific exogenous protein:protein interactions, but instead stabilizes FANCI:FANCD2 heterodimers on dsDNA. This locking of FANCI:FANCD2 complex on DNA requires monoubiquitination of only the FANCD2 subunit. We further show that purified monoubiquitinated FANCI:FANCD2 forms filament-like arrays on long dsDNA using electron microscopy. Our results reveal how monoubiquitinated FANCI:FANCD2 is activated upon DNA binding and present new insights to potentially modulate monoubiquitinated FANCI:FANCD2/DNA filaments in FA cells.

biochemistry↗