Cell-type specific transcriptomics of the the dlPFC in females with MDD [single-nucleus RNA-seq]
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA883411 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR21678800_1.fastq.gz | Fastqsanger.gz | |||
| SRR21678800_2.fastq.gz | Fastqsanger.gz | |||
| SRR21678801_1.fastq.gz | Fastqsanger.gz | |||
| SRR21678801_2.fastq.gz | Fastqsanger.gz | |||
| SRR21678802_1.fastq.gz | Fastqsanger.gz |
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Project description:We performed high-throughput snRNA-seq using the 10X Genomics Chromium platform on archived post-mortem dorsolateral prefrontal cortex (BA9) tissue in female MDD subjects who died by suicide and in female control subjects to identify cell-type specific differentially expressed genes. We further re-processed in parallel a previously generated snRNA-seq dataset in males with or without MDD to generate comparable differential expression results and compare the cell-type specific MDD-associated differences between the sexes.
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Project description:MicroRNAs (miRNAs) are postulated as pivotal epigenetic regulators in Major Depressive Disorder (MDD), yet distinguishing causal drivers from secondary associations remains a significant challenge due to cross-species barriers and tissue specificity. Here, we present a cross-species integrative framework rooted in human genetics and functionally validated in rodents to identify pathogenic miRNAs. By integrating large-scale cis-eQTLs and MDD GWAS data using Mendelian Randomization, we identified miR-130a-3p as a robust causal risk factor. Multivariable MR and neuroimaging integration further pinpointed the Dorsolateral Prefrontal Cortex (DLPFC) as the primary mediator of its pathogenic effects, characterized by disrupted related functional connectivity. Validating these findings, viral-mediated overexpression of miR-130a-3p in the murine medial prefrontal cortex (the functional homolog of human DLPFC) was sufficient to induce core depressive-like behaviors, including anhedonia and despair. Transcriptomic profiling revealed that miR-130a-3p predominantly downregulated genes enriched in immune-related pathways and specifically in microglia, suggesting a suppression of local neuroimmune signaling and an interruption of microglia-driven homeostasis. Finally, integrating these results with human Transcriptome-Wide Association Studies (TWAS) revealed that the expression levels of some miR-130a-3p downstream genes in the human DLPFC are significantly associated with MDD risk, completing a translational closed-loop that reinforces the relevance of the identified pathway. Collectively, our study identifies miR-130a-3p as a causal neuroimmune modulator in MDD and demonstrates the utility of a genetics-anchored, cross-species pipeline for dissecting the molecular etiology of psychiatric disorders.
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Project description:Single-nucleus spatial transcriptomic RNA-seq in the dlPFC of macaque
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Project description:The dorsolateral prefrontal cortex (dlPFC) is a derived cortical area in primates that is involved in myriad high-cognitive functions and is associated with several neuropsychiatric disorders. Here, we performed patch-seq and single-nucleus multiomic analyses of the rhesus macaque dlPFC to identify genes governing neuronal maturation during midfetal to late-fetal development. We also employed patch-seq analysis to assess the impact of CHD8 knockdown on human midfetal neuronal development with human organotypic dlPFC slices.
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Project description:Impairments in certain cognitive processes (e.g., working memory) are typically most pronounced in schizophrenia (SZ), intermediate in bipolar disorder (BP) and least in major depressive disorder (MDD). Given that working memory depends, in part, on neural circuitry that includes pyramidal neurons in layer 3 (L3) and layer 5 (L5) of the dorsolateral prefrontal cortex (DLPFC), we sought to determine if transcriptome alterations in these neurons were shared or distinctive for each diagnosis.
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Project description:Background: Major Depressive Disorder (MDD) represents a major social and economic health issue and constitutes a major risk factor for MDD suicide. The molecular pathology of suicidal depression remains poorly understood, although it has been hypothesized that regulatory genomic processes are involved in the pathology of both MDD and suicidality. Methods: Genome-wide patterns of DNA methylation were assessed in depressed MDD suicide completers (n=20) and compared to non-psychiatric, sudden-death controls (n=20) using tissue from two cortical brain regions (Brodmann Area 11 (BA11) and Brodmann Area 25 (BA25)). Analyses focussed on identifying differentially methylated regions (DMRs) associated with suicidal depression, and epigenetic variation was explored in the context of polygenic risk scores for major depression and MDD suicide. Weighted gene co-methylation network analysis was used to identify modules of co-methylated loci associated with depressed MDD suicide completers and polygenic burden for MDD and MDD suicide attempt. Results: We identified a DMR upstream of the PSORS1C3 gene, subsequently validated using bisulfite-pyrosequencing and replicated in a second set of MDD suicide samples, which is characterized by significant hypomethylation in both cortical brain regions in MDD MDD suicide cases. We also identified discrete modules of co-methylated loci associated with polygenic risk burden for MDD suicide attempt, but not major depression. MDD suicide-associated co-methylation modules were enriched among gene networks implicating biological processes relevant to depression and suicidality, including nervous system development and mitochondria function. Conclusions: Our data suggest there are coordinated changes in DNA methylation associated with MDD suicide that may offer novel insights into the molecular pathology associated with depressed MDD suicide completers.
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Project description:A cardinal symptom of Major Depressive Disorder (MDD) is the disruption of circadian patterns. Yet, to date, there is no direct evidence of circadian clock dysregulation in the brains of MDD patients. Circadian rhythmicity of gene expression has been observed in animals and peripheral human tissues, but its presence and variability in the human brain was difficult to characterize. Here we applied time-of-death analysis to gene expression data from high-quality postmortem brains, examining 24-hour cyclic patterns in six cortical and limbic regions of 55 subjects with no history of psychiatric or neurological illnesses ('Controls') and 34 MDD patients. Our dataset covered ~12,000 transcripts in the dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (AnCg), hippocampus (HC), amygdala (AMY), nucleus accumbens (NAcc) and cerebellum (CB). Several hundred transcripts in each region showed 24-hour cyclic patterns in Controls, and >100 transcripts exhibited consistent rhythmicity and phase-synchrony across regions. Among the top ranked rhythmic genes were the canonical clock genes BMAL1(ARNTL), PER1-2-3, NR1D1(REV-ERB), DBP, BHLHE40(DEC1), and BHLHE41(DEC2). The phasing of known circadian genes was consistent with data derived from other diurnal mammals. Cyclic patterns were much weaker in MDD brains, due to shifted peak timing and potentially disrupted phase relationships between individual circadian genes. This is the first transcriptome-wide analysis of cyclic patterns in the human brain and demonstrates a rhythmic rise and fall of gene expression in regions outside of the suprachiasmatic nucleus in control subjects. The description of its breakdown in MDD suggest novel molecular targets for treatment of mood disorders. Sample collection, including human subject recruitment and characterization, tissue dissection, and RNA extraction, was described previously (see Evans 2003 Neurobiol Dis 14:240-250, Li 2004 Biol Psychiatry 55:346-352). RNA samples for different regions came from the same set of brains from 86 control subjects. Sample size varied by region: AnCg (n=70 controls), DLPFC (n=83), CB (n=51), AMY (n=32), HC (n=63) and NAcc (n=66). Many of the samples were run on two or more chips, resulting in the following chip counts for each region: AnCg = 124, DLPFC = 161, CB = 79, AMY = 62, HC = 108 and NaCC = 136. We ran each sample on at least two microarrays using the Affymetrix U133-A or U133Plus-v2 GeneChips, however, we only used the U133A part of the U133Plus-v2 GeneChip in our analysis. We applied RMA (Robust Multi-array Analysis) (see Irizarry 2003 Biostatistics 4:249-264, Irizarry 2003 Nucleic Acids Res 31:e15) to summarize probe set expression levels, using a custom Chip Definition File, resulting in expression data for 11,911 ENTREZ transcripts. Microarray data for each region were analyzed separately. All downstream analyses were performed in R. Details of the data processing, including data cleaning and normalization, are located in the Supplementary Materials (section 1). After data filtering, 1,424 microarrays remained, corresponding to 776 unique RNA samples in six regions.
2013-04-20 | E-GEOD-45642 | biostudies-arrayexpress