Biology subjects

Lawless, N.

Publications and source records attributed to Lawless, N..

7 recordsLinked to original sources

bioRxiv2025

Glucocorticoid receptors mediate reprogramming of astrocytes in depression.

Psychiatric disorders are among the most pressing problems of the modern society, with various forms of depression affecting more than 300 millions of people worldwide. Dysfunction of glial cells has consistently been reported in major depressive disorder (MDD); however, no comprehensive resource detailing glial dysfunction is available. To provide insight into neurobiological mechanisms behind severe psychiatric symptoms, we performed transcriptional analysis of post-mortem samples from a subpopulation of suicide completers with previously reported glial abnormalities. We focused on BA25, a subregion of the prefrontal cortex prioritized for targeted medical interventions, due to its metabolic aberrations in disease. We found that a significant portion of genes deregulated in MDD is enriched in glia, with astrocyte-specific genes representing the highest fraction. Then we employed a novel protocol for enriching astrocytic nuclei to provide a detailed molecular signature of astrocytes in MDD. The analysis of the gene set revealed the glucocorticoid receptor (GR) as a key regulatory transcription factor. We found that astrocyte-specific elimination of the GR in mice largely prevented transcriptional, metabolic and behavioral changes elicited by chronic stress. We also demonstrated that regional manipulation of glutamate turnover in astrocytes suffices to elicit discrete traits of depressive-like behavior. Our data points to astrocytes as a key cellular site of convergence of multiple traits of depression and provide a resource for exploring novel targets for glia-focused therapeutic approaches.

neuroscience↗

bioRxiv2023

BrainTACO: An Explorable Multi-Scale Multi-Modal Brain Transcriptomic And Connectivity Data Resource

AbstractExploring the relationships between genes, brain circuitry, and behaviour is accelerated by the joint analysis of a heterogeneous sets form 3D imaging data, anatomical data, and brain networks at varying scales, res-olutions, and modalities. Hence, generating an integrated view, beyond the individual resources original purpose, requires the fusion of these data to a common space, and a visualization that bridges the gap across scales. However, despite ever expanding datasets, few plat-forms for integration and exploration of this heterogeneous data exist. To this end, we present the BrainTACO (Brain Transcriptomic And Connectivity Data) resource, a selection of heterogeneous, and multi-scale neurobiological data spatially mapped onto a common, hierarchical reference space, combined via a holistic data integration scheme. To access BrainTACO, we extended BrainTrawler, a web-based visual ana-lytics framework for spatial neurobiological data, with comparative visualizations of multiple resources for gene expression dissection of brain networks with an unprecedented coverage. Using this platform, allows to straightforward explore and extract brain data for identifying potential genetic drivers of connectivity in both mice and humans that may contribute to the discovery of dysconnectivity phenotypes. Hence, BrainTACO reduces the need for time-consuming manual data aggregation often required for computational analyses in script based toolboxes, and supports neuroscientists by focusing on leveraging the data instead of preparing it.

bioinformatics↗

bioRxiv2022

Transcriptome and chromatin accessibility landscapes across 25 distinct human brain regions expand the susceptibility gene set for neuropsychiatric disorders

Brain region- and cell-specific transcriptomic and epigenomic molecular features are associated with heritability for neuropsychiatric traits, but a systematic view, considering cortical and subcortical regions, is lacking. Here, we provide an atlas of chromatin accessibility and gene expression in neuronal and non-neuronal nuclei across 25 distinct human cortical and subcortical brain regions from 6 neurotypical controls. We identified extensive gene expression and chromatin accessibility differences across brain regions, including variation in alternative promoter-isoform usage and enhancer-promoter interactions. Genes with distinct promoter-isoform usage across brain regions are strongly enriched for neuropsychiatric disease risk variants. Using an integrative approach, we characterized the function of the brain region-specific chromatin co-accessibility and gene-coexpression modules that are robustly associated with genetic risk for neuropsychiatric disorders. In addition, we identified a novel set of genes that is enriched for disease risk variants but is independent of cell-type specific gene expression and known susceptibility pathways. Our results provide a valuable resource for studying molecular regulation across multiple regions of the human brain and suggest a unique contribution of epigenetic modifications from subcortical areas to neuropsychiatric disorders.

neuroscience↗

bioRxiv2021

TREM2 impacts brain microglia, oligodendrocytes and endothelial co-expression modules revealing genes and pathways important in Alzheimer s disease

A microglia response to pathogenic signals in diseases such as Alzheimers disease (AD) has long been recognised, but recent genetic findings have cemented their direct causal contribution to AD and thus the potential to target them or their effector pathways as a possible treatment strategy. TREM2 is a highly penetrant microglia risk gene for AD, which appears central to the coordination of the damage response by microglia in AD. Its absence has a negative impact on Tau and amyloid symptoms and pathologies. Full knowledge of its pathway and relationships with other brain cells in AD has not been fully characterised, but will be essential to fully evaluate the impact of manipulating this pathway for treatment development and to establish the best targets for achieving this. We used whole genome RNA sequencing of hippocampus and cortical brain samples from control, AD, and AD TREM2 risk carriers to identify TREM2-dependent genes driving changes in pathways, processes and cell types in AD. Through highly influential intra and intermodular hub genes and overall changes in the levels of gene expression, TREM2-DAP12 was found to strongly influence a number of other microglia, oligodendrocyte and endothelial genes, notably those involved in complement and Fc{gamma} receptor function, microglia-associated ribosomal genes and oligodendrocyte genes, particularly proteosomal subunits. These strong TREM2 centred co-expression relationships were significantly disrupted in AD cases with a TREM2 risk variant, revealing for the first time genes and pathways directly impacted by TREM2 in the brains of AD patients. Consistent with its function as a lipid sensor, our data supports a role for TREM2 in mediating oligodendrocyte and/or myelin clearance in AD which may be essential not only for preserving healthy tissue homeostasis but may also serve to minimise the persistence of antigenic peptides and lipids which may lead to detrimental pro-inflammatory sequelae. Further work should expand our knowledge of TREM2 on complement and Fc{gamma} receptor function and its impact on oligodendcrotye and myelin integrity and further evaluate the genes and pathways we have identified as possible treatment targets for AD.

neuroscience↗

bioRxiv2020

HieRFIT: Hierarchical Random Forest for Information Transfer

The emergence of single-cell RNA sequencing (scRNA-seq) has led to an explosion in novel methods to study biological variation among individual cells, and to classify cells into functional and biologically meaningful categories. Here, we present a new cell type projection tool, HieRFIT (Hierarchical Random Forest for Information Transfer), based on hierarchical random forests. HieRFIT uses a priori information about cell type relationships to improve classification accuracy, taking as input a hierarchical tree structure representing the class relationships, along with the reference data. We use an ensemble approach combining multiple random forest models, organized in a hierarchical decision tree structure. We show that our hierarchical classification approach improves accuracy and reduces incorrect predictions especially for inter-dataset tasks which reflect real life applications. We use a scoring scheme that adjusts probability distributions for candidate class labels and resolves uncertainties while avoiding the assignment of cells to incorrect types by labeling cells at internal nodes of the hierarchy when necessary. Using HieRFIT, we re-analyzed publicly available scRNA-seq datasets showing its effectiveness in cell type cross-projections with inter/intra-species examples. HieRFIT is implemented as an R package and it is available at (https://github.com/yasinkaymaz/HieRFIT/releases/tag/v1.0.0)

bioinformatics↗

bioRxiv2018

REM sleep: unique associations with behavior, corticosterone regulation and apoptotic pathways in chronic stress in mice

One of sleeps putative functions is mediation of adaptation to waking experiences. Chronic stress is a common waking experience, however, which specific aspect of sleep is most responsive, and how sleep changes relate to behavioral disturbances and molecular correlates remain unknown. We quantified sleep, physical, endocrine and behavioral variables and the brain and blood transcriptome in mice exposed to nine weeks of unpredictable chronic mild stress (UCMS). Comparing 46 phenotypical variables revealed that rapid-eye-movement sleep (REMS), corticosterone regulation and coat state were most responsive to UCMS. REMS theta oscillations were enhanced whereas delta oscillations in non-REMS were unaffected. Transcripts affected by UCMS in the prefrontal cortex, hippocampus, hypothalamus and blood were associated with inflammatory and immune responses. A machine learning approach controlling for unspecific UCMS effects identified transcriptomic predictors for specific phenotypes and their overlap. Transcriptomic predictor sets for the inter-individual variation in REMS continuity and theta activity shared many pathways with corticosterone regulation and in particular pathways implicated in apoptosis, including mitochondrial pathways. Predictor sets for REMS and anhedonia, one of the behavioral changes following UCMS, shared pathways involved in oxidative stress, cell proliferation and apoptosis. RNA predictor sets for non-NREMS parameters showed no overlap with other phenotypes. These novel data identify REMS as a core and early element of the response to chronic stress, and identify apoptotic pathways as a putative mechanism by which REMS mediates adaptation to stressful waking experiences.\n\nSignificance StatementSleep is responsive to experiences during wakefulness and is altered in stress-related disorders. Whether sleep changes primarily concern rapid-eye-movement sleep (REMS) or non-REM sleep, and how they correlate with stress hormones, behavioral and transcriptomic responses remained unknown. We demonstrate using unpredictable chronic (9-weeks) mild stress that REMS is the most responsive of all the measured sleep characteristics, and correlates with deficiency in corticosterone regulation. An unbiased machine learning, controlling for unspecific effects of stress, revealed that REMS correlated with RNA predictor sets enriched in apoptosis including mitochondrial pathways. Several pathways were shared with predictors of corticosterone and behavioral responses. This unbiased approach point to apoptosis as a molecular mechanism by which REMS mediates adaptation to an ecologically relevant waking experience.

neuroscience↗

bioRxiv2018

Loss of Trem2 in microglia leads to widespread disruption of cell co-expression networks in mouse brain

Rare heterozygous coding variants in the Triggering Receptor Expressed in Myeloid cells 2 (TREM2) gene, conferring increased risk of developing late-onset Alzheimer's disease, have been identified. We examined the transcriptional consequences of the loss of Trem2 in mouse brain to better understand its role in disease using differential expression and coexpression network analysis of Trem2 knockout and wild-type mice. We generated RNA-Seq data from cortex and hippocampus sampled at 4 and 8 months. Using brain cell type markers and ontology enrichment, we found subnetworks with cell type and/or functional identity. We primarily discovered changes in an endothelial-gene enriched subnetwork at 4 months, including a shift towards a more central role for the Amyloid Precursor Protein (App) gene, coupled with widespread disruption of other cell-type subnetworks, including a subnetwork with neuronal identity. We reveal an unexpected potential role of Trem2 in the homeostasis of endothelial cells that goes beyond its known functions as a microglial receptor and signalling hub, suggesting an underlying link between immune response and vascular disease in dementia.

systems biology↗