Biology subjects

Flandreau, E. I.

Publications and source records attributed to Flandreau, E. I..

6 recordsLinked to original sources

bioRxiv2026

A Meta-Analysis of the Converging Effects of Different Classes of Antipsychotics on the Frontal Cortex Transcriptome in Laboratory Rodents and Non-Human Primates

BackgroundPsychotic illnesses are among the most debilitating classes of psychiatric disorders, requiring targeted and effective treatment strategies. Although antipsychotics are the primary pharmacological therapy for psychosis, their full range of effects remain unclear, including effects within the frontal cortex, a brain region linked structurally and functionally to psychotic disorders. MethodsTo examine the effects of antipsychotic treatment on the frontal cortex, we conducted a meta-analysis of publicly available rodent (rat, mice) transcriptional profiling datasets (microarray, RNA-Seq). Five datasets (GSE45229, GSE93918, GSE2547, GSE4031.1, GSE66275) were identified within the Gemma database using pre-specified search terms and inclusion/exclusion criteria (date: 7/7/2024), yielding differential expression results for eight drug vs. control comparisons (collective n=68). A random-effects meta-analysis model was fit to the log2 fold changes for each gene, and p-values adjusted for false discovery rate (FDR), with follow-up analyses exploring robustness, heterogeneity, and publication bias. To increase the power and generalizability of our findings, an exploratory meta-analysis was also run incorporating antipsychotic effects from both rodents and nonhuman primates (collective n=101), and compared to findings from individuals with schizophrenia. ResultsOur meta-analysis yielded stable estimates for 12,190 genes, identifying 63 genes that were differentially expressed following antipsychotic treatment ("DEGs", FDR<0.05). Differential expression included genes important for serotonergic and cholinergic signalling, and was enriched within pathways linked to oligodendrocyte development and myelination, physiological and cellular stress responses, and cardiovascular function. An exploratory meta-analysis combining rodent and nonhuman primate results confirmed these observations and yielded additional findings (117 DEGs total). Comparisons with human post-mortem findings suggested that some schizophrenia-related gene expression may instead reflect antipsychotic treatment. ConclusionFurther validation is necessary, but our findings suggest that antipsychotics may assist in the regulation of specific structural and functional changes within the frontal cortex linked to psychotic disorders. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/734301v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1aaa2ecorg.highwire.dtl.DTLVardef@1ae6819org.highwire.dtl.DTLVardef@13454a2org.highwire.dtl.DTLVardef@a0877c_HPS_FORMAT_FIGEXP M_FIG C_FIG Key PointsO_LIPsychosis is treated using two broad types of antipsychotic medication: first-generation (typical) and second-generation (atypical). C_LIO_LIUnderstanding the congruent effects of different types of antipsychotics on regions important for psychosis, such as the frontal cortex, can highlight essential mechanisms. C_LIO_LIA meta-analysis of public transcriptional profiling datasets identified genes and functional gene sets that are differentially expressed across antipsychotic categories. C_LI

neuroscience↗

bioRxiv2025

A Meta-Analysis of the Effects of Chronic Stress on the Prefrontal Transcriptome in Animal Models and Convergence with Existing Human Data

BackgroundChronic stress is a major risk factor for psychiatric disorders, including anxiety, depression, and post-traumatic stress disorder. Chronic stress can cause structural alterations like grey matter atrophy in key emotion-related areas such as the prefrontal cortex (PFC). To identify biological pathways affected by chronic stress in the PFC, researchers have performed transcriptional profiling (RNA-sequencing, microarray) to measure gene expression in rodent models. However, transcriptional signatures in the PFC that are shared across different chronic stress paradigms and laboratories remain relatively unexplored. MethodsWe performed a meta-analysis of publicly available transcriptional profiling datasets within the Gemma database. We identified six datasets that characterized the effects of either chronic social defeat stress (CSDS) or chronic unpredictable mild stress (CUMS) on gene expression in the PFC in mice (n=117). We fit a random effects meta-analysis model to the chronic stress effect sizes (log(2) fold changes) for each transcript (n=21,379) measured in most datasets. We then compared our results with two other published chronic stress meta-analyses, as well as transcriptional signatures associated with psychiatric disorders. ResultsWe identified 133 genes that were consistently differentially expressed across chronic stress studies and paradigms (false discovery rate (FDR)<0.05). Fast Gene Set Enrichment Analysis (fGSEA) revealed 53 gene sets enriched with differential expression (FDR<0.05), dominated by glial and neurovascular markers (e.g., oligodendrocyte, astrocyte, endothelial/vascular) and stress-related signatures (e.g., major depressive disorder, hormonal responses). Immediate-early gene markers of neuronal activity (Fos, Junb, Arc, Dusp1) were consistently suppressed. Many of the identified effects resembled those seen in previous meta-analyses characterizing stress effects (CSDS, early life stress), despite minimal overlap in included samples. Moreover, some effects resembled previous observations from psychiatric disorders, including alcohol abuse disorder, major depressive disorder, bipolar disorder, and schizophrenia. ConclusionOur study demonstrates that chronic stress induces a robust, cross-paradigm PFC signature characterized by down-regulation of glia/myelin and vascular pathways and suppression of immediate-early gene activity, highlighting cellular processes linking chronic stress exposure, PFC dysfunction, and psychiatric disorders. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=92 SRC="FIGDIR/small/683091v2_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@1062c5eorg.highwire.dtl.DTLVardef@4ae148org.highwire.dtl.DTLVardef@c747corg.highwire.dtl.DTLVardef@1b3a713_HPS_FORMAT_FIGEXP M_FIG C_FIG Key PointsO_LIChronic stress is linked to many human psychiatric disorders involving the prefrontal cortex (PFC). C_LIO_LIMeta-analysis showed that stressed mice had less gene expression for glia and neural activity in the PFC. C_LIO_LIPFC gene expression in chronically stressed mice mirrors patterns seen in psychiatric patients. C_LI Plain Language SummaryChronic stress has been shown to have lasting effects on the brain, contributing to cognitive impairments and the risk of psychiatric disorders such as anxiety, depression, and post-traumatic stress disorder. The prefrontal cortex, a brain region that is important for behavioral and attentional control, is sensitive to chronic stress. We combined information from six public mouse datasets to identify consistent effects of chronic stress on gene expression (mRNA) in the prefrontal cortex. In these studies, mice that had experienced chronic stress showed a decreased amount of mRNA related to a variety of non-neuronal support cells (glia) and blood vessels, and general neural activity. The mouse chronic stress signature overlapped with gene-activity patterns reported in human psychiatric conditions, suggesting a biological bridge between chronic stress and the onset of psychopathology.

neuroscience↗

bioRxiv2025

Effect of Chronic Stress on Whole Blood Transcriptome: A Meta-Analysis of Publicly Available Datasets from Rodent Models

BackgroundChronic stress increases risk for neuropsychiatric disorders in humans. By modeling stress-induced changes in animals, we may improve diagnosis or treatment of these disorders. Successful translation benefits from studies with sufficient statistical power and outcome measurements that can be directly compared across species. We performed a meta-analysis to examine the impact of chronic stress on the whole blood transcriptome. MethodsDatasets were systematically identified in Gemma, a database of reprocessed public transcriptional profiling studies; datasets GSE68076, GSE72262, and GSE84185 met inclusion/exclusion parameters. Each study exposed eight-week old mice to chronic stress (5-10 days social defeat stress or 6-8 weeks chronic mild stress). The final sample size was n=92 (n=45 Non-Stress/n=47 Stress). Stress-related differential expression in each dataset was quantified using the Limma pipeline followed by empirical Bayes moderation. For the 9,219 genes represented in all three datasets, we ran a meta-analysis of Log(2) Fold Changes using a random effects model and corrected for false discovery rate (FDR). Functional patterns were assessed with fast Gene Set Enrichment Analysis. Cell type specific enrichment for each of the differentially expressed genes was further explored using a public 10x genomics scRNA-Seq dataset from mouse peripheral blood mononuclear cells. ResultsFindings included 23 downregulated and 16 upregulated transcripts in stress-exposed mice (FDR<0.05). Results indicated a down-regulation in gene sets related to B cells, immune response, DNA and chromatin regulation, ribosomal activity, translation, and catabolic cellular processes. Upregulated gene sets related to erythrocytes and oxygen binding. ConclusionOur results provide molecular insight into stress-related immune dysregulation and add weight to the hypothesis that environmental stress escalates cellular aging, supporting the use of blood transcriptome as a bridge between human and rodent models. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC="FIGDIR/small/657043v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@161fc2eorg.highwire.dtl.DTLVardef@1f358b9org.highwire.dtl.DTLVardef@145ef33org.highwire.dtl.DTLVardef@5b1169_HPS_FORMAT_FIGEXP M_FIG C_FIG Key pointsSuccessful translational research benefits from studies with outcome measurements that can be directly compared across species and sufficient statistical power. The present report is a meta-analysis of three mouse experiments examining the impact of chronic stress on the whole blood transcriptome. Our results provide insight into stress-related immune dysregulation and add weight to the hypothesis that environmental stress escalates cellular aging. These findings illustrate the utility of the blood transcriptome as a bridge between human and rodent models.

genomics↗

bioRxiv2025

Short Report: A Meta-Analysis of the Effects of Sleep Deprivation on the Cortical Transcriptome in Animal Models

Sleep deprivation (SD) causes large disturbances in mood and cognition. The molecular basis for these effects can be explored using transcriptional profiling to quantify brain gene expression. In this report, we used a meta-analysis of public transcriptional profiling data to discover SD effects on gene expression that are consistent across studies and paradigms. To conduct the meta-analysis, we used pre-specified search terms related to rodent SD paradigms to identify relevant studies within Gemma, a database containing >19,000 re-analyzed microarray and RNA-Seq datasets. Eight studies met our systematic inclusion/exclusion criteria. These studies characterized the effect of 18 SD interventions on gene expression in the mouse cerebral cortex (collective n=293). For each gene with sufficient data (n=16,290), we fit a random effects meta-analysis model to the SD effect sizes (log(2) fold changes). Our meta-analysis revealed 182 differentially expressed genes in response to SD (false discovery rate: FDR<0.05), most of which (115/182) showed similar effects (FDR<0.05) in an independent large dataset (GSE114845: n=86 RNA-Seq samples from n=222 mice). Gene-set enrichment analysis revealed down-regulation in pathways related to stress response (e.g., glucocorticoid receptor Nr3c1), vasculature, growth and development, and upregulation related to stress, inflammation, and neuropeptide signalling. Exploratory analyses suggested that recovery sleep (included in six contrasts: range: 1-18 hrs), could reverse the impact of SD on gene expression. Our meta-analysis provides a useful reference database illustrating the diverse molecular impact of SD on the rodent cerebral cortex. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/648791v2_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@52984dorg.highwire.dtl.DTLVardef@8d1174org.highwire.dtl.DTLVardef@174ed85org.highwire.dtl.DTLVardef@195e8bf_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract C_FIG

neuroscience↗

bioRxiv2025

The Effects of Antidepressants on the Hippocampus: A Meta-Analysis of Public Transcriptional Profiling Data

Depression can be treated with traditional pharmaceuticals targeting monoaminergic function, non-traditional drug classes and neuromodulatory interventions. To identify mechanisms of action shared across clinically-effective antidepressant treatment categories, we performed two systematic meta-analyses of public transcriptional profiling data from adult laboratory rodents (rats, mice). The outcome variable was gene expression, measured by microarray or RNA-Seq from bulk-dissected tissue from two depression-related brain regions (hippocampus, cortex). Relevant datasets were identified in the Gemma database of curated, reprocessed transcriptional profiling data using predefined search terms and inclusion/exclusion criteria (hippocampus: 6-24-2024, cortex: 7-10-2024). Differential expression results were extracted for all genes, minimizing bias. For each gene, a random effects meta-analysis model was fit to antidepressant vs. control effect sizes (Log2 Fold Changes) from each study for each brain region, with follow-up analyses exploring sources of effect heterogeneity. For the hippocampus, 15 relevant studies were identified, containing 22 antidepressant vs. control group comparisons (collective n=313 samples), with approximately half representing traditional versus non-traditional antidepressants. Of 16,439 analyzed genes, 58 were consistently differentially expressed (False Discovery Rate (FDR)<0.05) following treatment. Antidepressant effects were enriched in the dentate gyrus and in gene sets related to stress regulation, brain growth and plasticity, vasculature and glia, and immune function. Comparisons with single nucleus RNA-Seq confirmed effects on specific hippocampal cell types, including potential rejuvenation of dentate granule neurons. For the cortex, 13 studies were identified, containing 16 antidepressant vs. control group comparisons (collective n=233 samples). Of 15,583 analyzed genes, only one was consistently differentially expressed (FDR<0.05: Atp6v1b2), but overall expression patterns moderately resembled the hippocampus. These genes and pathways showing consistent differential expression across treatment categories may be promising targets for novel therapies. Future work should explore relevance to human clinical populations and potential heterogeneity introduced by sex and subregion. Key PointsO_LIDepression can be treated with traditional antidepressants targeting monoaminergic function, as well as other drug classes and non-pharmaceutical interventions. C_LIO_LIUnderstanding the congruent effects of different types of antidepressant treatments on sensitive brain regions, such as the hippocampus and cortex, can highlight essential mechanisms of action. C_LIO_LIA meta-analysis of public transcriptional profiling datasets identified genes and functional gene sets that are differentially expressed across antidepressant categories. C_LI Plain Language SummaryMajor depressive disorder is characterized by persistent depressed mood and loss of interest and pleasure in life. Worldwide, an estimated 5% of adults suffer from depression, making it a leading cause of disability. The current standard of care for depressed individuals includes psychotherapy and antidepressant medications that enhance signaling by monoamine neurotransmitters, such as serotonin and norepinephrine. Other treatments include non-traditional antidepressants that function via alternative, often unknown, mechanisms. To identify mechanisms of action shared across different categories of antidepressants, we performed a meta-analysis using public datasets to characterize changes in gene expression (mRNA) following treatment with both traditional and non-traditional antidepressants. We focused on the hippocampus and cortex, which are two brain regions that are sensitive to both depression and antidepressant usage. We found 59 genes that had consistently higher or lower levels of expression (mRNA) across antidepressant categories. The functions associated with these genes were diverse, including regulation of stress response, the immune system, brain growth and adaptability. These genes are worth investigating further as potential linchpins for antidepressant efficacy or as targets for novel therapies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/648805v3_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@14538e3org.highwire.dtl.DTLVardef@199c5e3org.highwire.dtl.DTLVardef@8ed8a6org.highwire.dtl.DTLVardef@31b1f8_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2024

A meta-analysis of the effects of early life stress on the prefrontal cortex transcriptome suggests long-term effects on myelin

BackgroundEarly life stress (ELS) refers to exposure to negative childhood experiences, such as neglect, disaster, and physical, mental, or emotional abuse. ELS can permanently alter the brain, leading to cognitive impairment, increased sensitivity to future stressors, and mental health risks. The prefrontal cortex (PFC) is a key brain region implicated in the effects of ELS. MethodsTo better understand the effects of ELS on the PFC, we ran a meta-analysis of publicly available transcriptional profiling datasets. We identified five datasets (GSE89692, GSE116416, GSE14720, GSE153043, GSE124387) that characterized the long-term effects of multi-day postnatal ELS paradigms (maternal separation, limited nesting/bedding) in male and female laboratory rodents (rats, mice). The outcome variable was gene expression in the PFC later in adulthood as measured by microarray or RNA-Seq. To conduct the meta-analysis, preprocessed gene expression data were extracted from the Gemma database. Following quality control, the final sample size was n=89: n=42 controls & n=47 ELS: GSE116416 n=23 (no outliers); GSE116416 n=44 (2 outliers); GSE14720 n=7 (no outliers); GSE153043 n=9 (1 outlier), and GSE124387 n=6 (no outliers). Differential expression was calculated using the limma pipeline followed by an empirical Bayes correction. For each gene, a random effects meta-analysis model was then fit to the ELS vs. Control effect sizes (Log2 Fold Changes) from each study. ResultsOur meta-analysis yielded stable estimates for 11,885 genes, identifying five genes with differential expression following ELS (false discovery rate< 0.05): transforming growth factor alpha (Tgfa), IQ motif containing GTPase activating protein 3 (Iqgap3), collagen, type XI, alpha 1 (Col11a1), claudin 11 (Cldn11) and myelin associated glycoprotein (Mag), all of which were downregulated. Broadly, gene sets associated with oligodendrocyte differentiation, myelination, and brain development were downregulated following ELS. In contrast, genes previously shown to be upregulated in Major Depressive Disorder patients were upregulated following ELS. ConclusionThese findings suggest that ELS during critical periods of development may produce long-term effects on the efficiency of transmission in the PFC and drive changes in gene expression similar to those underlying depression. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/624315v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@1619926org.highwire.dtl.DTLVardef@8da510org.highwire.dtl.DTLVardef@14feffcorg.highwire.dtl.DTLVardef@114aae3_HPS_FORMAT_FIGEXP M_FIG C_FIG Key PointsO_LIEarly life stress (ELS) can have long-term effects on the prefrontal cortex (PFC) and its related cognitive and emotional functions. C_LIO_LITo elucidate these long-term effects, we conducted a meta-analysis of five publicly available PFC transcriptional profiling datasets from adult rodents that had previously experienced ELS. C_LIO_LIThis meta-analysis revealed a consistent downregulation of myelin-related genes in the PFC following ELS, and an upregulation of genes related to Major Depressive Disorder. C_LI Plain Language SummaryEarly life stress refers to exposure to negative childhood experiences, such as neglect, disaster, and physical, mental, or emotional abuse. Early life stress can permanently alter the brain, including the prefrontal cortex, which can lead to cognitive and emotional dysfunction that lasts into adulthood. We performed a meta-analysis using five public datasets to identify consistent long-term effects of early life stress on gene expression (mRNA) in the prefrontal cortex of adult rodents. In these studies, rodents that had experienced early life stress consistently showed a decreased amount of mRNA for genes related to myelin. Myelin is the fatty layer that insulates the axons of neurons, allowing them to transmit electrical signals more efficiently. These gene expression changes may suggest long-term effects of early life stress on the efficiency of prefrontal neurotransmission, disrupting cognitive and emotional processing.

neuroscience↗