Biology subjects

Cruceanu, C.

Publications and source records attributed to Cruceanu, C..

6 recordsLinked to original sources

bioRxiv2024

Chronic exposure to glucocorticoids amplifies inhibitory neuron cell fate during human neurodevelopment in organoids

Disruptions in the tightly regulated process of human brain development have been linked to increased risk for brain and mental illnesses. While the genetic contribution to these diseases is well established, important environmental factors have been less studied at molecular and cellular levels. In this study, we used single-cell and cell-type-specific techniques to investigate the effect of glucocorticoid (GC) exposure, a mediator of antenatal environmental risk, on gene regulation and lineage specification in unguided human neural organoids. We characterized the transcriptional response to chronic GC exposure during neural differentiation and studied the underlying gene regulatory networks by integrating single-cell transcriptomics-with chromatin accessibility data. We found lasting cell type-specific changes that included autism risk genes and several transcription factors associated with neurodevelopment. Chronic GCs influenced lineage specification primarily by priming the inhibitory neuron lineage through key transcription factors like PBX3. We provide evidence for convergence of genetic and environmental risk factors through a common mechanism of altering lineage specification.

neuroscience↗

bioRxiv2022

Temporal regulation of ZBTB16 expression by glucocorticoids alters human cortical neurogenesis

Glucocorticoids are important for proper organ maturation and their levels are tightly regulated during development. Here we use human cerebral organoids and mice to study cell-type specific effects of glucocorticoids on neurogenesis. We show that glucocorticoids increase a specific type of basal progenitors (co-expressing PAX6 and EOMES) that has been shown to drive cortical expansion in gyrified species. This effect is mediated via the transcription factor ZBTB16 and leads to increased production of neurons. A phenome-wide mendelian randomization analysis of an enhancer variant that moderates glucocorticoid-induced ZBTB16 levels, reveals causal relationships with higher educational attainment and altered brain structure. The relationship with postnatal cognition is supported by data from a prospective pregnancy cohort. This study provides a novel cellular and molecular pathway for the effects of glucocorticoids on human neurogenesis that relates to lasting postnatal phenotypes.

neuroscience↗

bioRxiv2022

DiffBrainNet: differential analyses add new insights into the response to glucocorticoids at the level of genes, networks and brain regions

Genome-wide gene expression analyses are invaluable tools for increasing our knowledge of biological and disease processes, allowing a hypothesis-free comparison of gene expression profiles across experimental groups, tissues and cell types. Traditionally, transcriptomic data analysis has focused on gene-level effects found by differential expression. In recent years, network analysis has emerged as an important additional level of investigation, providing information on molecular connectivity, especially for diseases associated with a large number of linked effects of smaller magnitude, like neuropsychiatric disorders and their risk factors, including stress. In this manuscript, we describe how combined differential expression and prior-knowledge-based differential network analysis can be used to explore complex datasets. As an example, we analyze the transcriptional responses following administration of the glucocorticoid/stress hormone receptor agonist dexamethasone in C57Bl/6 mice, in 8 brain regions important for stress processing: the prefrontal cortex, the amygdala, the paraventricular nucleus of the hypothalamus, the cerebellar cortex, and sub regions of the hippocampus: the dorsal and ventral Cornu Ammonis 1, the dorsal and ventral dentate gyrus. By applying a combination of differential network- and differential expression-analyses, we find that these explain distinct but complementary aspects and biological mechanisms of the responses to the stimulus. In addition, network analysis identifies new differentially connected partners of important genes and can be used to generate hypotheses on specific molecular pathways affected. With this work, we provide an analysis framework and a publicly available resource for the study of the transcriptional landscape of the mouse brain: DiffBrainNet (http://diffbrainnet.psych.mpg.de), which can identify molecular pathways important for basic functioning and response to glucocorticoids in a brain-region specific manner.

genomics↗

bioRxiv2021

Genotype and age influence cortical-FKBP5 at multiple regulatory and single-cell-type levels in severe psychiatric disorders

Identification and characterisation of novel targets for treatment is a priority in the field of psychiatry. FKBP5 is a gene with decades of evidence suggesting its pathogenic role in a subset of psychiatric patients, with potential to be leveraged as a therapeutic target for these individuals. While it is widely reported that FKBP5/FKBP51 mRNA/protein (FKBP5/1) expression is impacted by psychiatric disease state, risk genotype and age, it is not known in which cell-types and sub-anatomical areas of the human brain this occurs. This knowledge is critical to propel FKBP5/1-targeted treatment development. Here, we performed an extensive, large-scale postmortem study (n=1024) of FKBP5/1 examining prefrontal cortex (BA9, BA11, BA24) derived from subjects that lived with schizophrenia, major depression or bipolar disorder. With an extensive battery of RNA (bulk RNA sequencing, single-nucleus RNA sequencing, microarray, qPCR, RNAscope) and protein (immunoblot, immunohistochemistry) analysis approaches, we thoroughly investigated the effects of disease-state, aging and genotype on cortical FKBP5/1 expression including in a cell-type specific manner. We identified consistently heightened FKBP5/1 levels in psychopathology and with age, but not genotype, with these effects strongest in schizophrenia. Using single-nucleus RNA sequencing (snRNAseq) and targeted histology, we established that these disease- and aging-effects on FKBP5/1 expression were most pronounced in excitatory supragranular neurons. We then found that this increase in FKBP5 levels likely impacts on synaptic plasticity, as FKBP5 gex levels strongly and inversely correlated with dendritic mushroom spine density and brain-derived neurotrophic factor (BDNF) levels in supragranular neurons. These findings pinpoint a novel cellular and molecular mechanism that has significant potential to open a new avenue of FKBP51 drug development to treat cognitive symptoms in psychiatric disorders.

neuroscience↗

bioRxiv2020

Design and power analysis for multi-sample single cell genomics experiments

BackgroundThe identification of genes associated with specific experimental conditions, genotypes or phenotypes through differential expression analysis has long been the cornerstone of transcriptomic analysis. Single cell RNA-seq is revolutionizing transcriptomics and is enabling interindividual differential gene expression analysis and identification of genetic variants associated with gene expression, so called expression quantitative trait loci at cell-type resolution. Current methods for power analysis and guidance of experimental design either do not account for the specific characteristics of single cell data or are not suitable to model interindividual comparisons. ResultsHere we present a statistical framework for experimental design and power analysis of single cell differential gene expression between groups of individuals and expression quantitative trait locus analysis. The model relates sample size, number of cells per individual and sequencing depth to the power of detecting differentially expressed genes within individual cell types. Power analysis is based on data driven priors from literature or pilot experiments across a wide range of application scenarios and single cell RNA-seq platforms. Using these priors we show that, for a fixed budget, the number of cells per individual is the major determinant of power. ConclusionOur model is general and allows for systematic comparison of alternative experimental designs and can thus be used to guide experimental design to optimize power. For a wide range of applications, shallow sequencing of high numbers of cells per individual leads to higher overall power than deep sequencing of fewer cells. The model is implemented as an R package scPower.

bioinformatics↗

bioRxiv2020

Cell-type specific impact of glucocorticoid receptor activation on the developing brain

A fine-tuned balance of glucocorticoid receptor (GR) activation is essential for organ formation, with disturbances influencing health outcomes. Excess GR-activation in utero has been linked to brain-related negative outcomes, with unclear underlying mechanisms, especially regarding cell-type specific effects. To address this, we used an in vitro model of fetal human brain, induced pluripotent-stem-cell-derived cerebral organoids, and mapped GR-activation effects using single-cell transcriptomics across development. Interestingly, neurons showed targeted regulation of differentiation- and maturation-related transcripts, suggesting a delay of these processes upon GR-activation. Uniquely in neurons, differentially-expressed transcripts were significantly enriched for genes associated with behavior-related phenotypes and disorders. This suggests that aberrant GR-activation could impact proper neuronal maturation, leading to increased disease susceptibility, through neurodevelopmental processes at the interface of genetic susceptibility and environmental exposure.

neuroscience↗