Biology subjects

Deep-Soboslay, A.

Publications and source records attributed to Deep-Soboslay, A..

13 recordsLinked to original sources

bioRxiv2026

Overlapping yet distinct spatiomolecular profiles across mood disorders and biological sex in the human prefrontal cortex

Major depressive disorder (MDD) and bipolar disorder (BD) exhibit both overlapping and distinct clinical features, including sex differences in prevalence and symptomatology, but how these similarities and differences are reflected at the molecular and cellular level in the human brain remains poorly understood. Here, we applied spatial transcriptomics to the human dorsolateral prefrontal cortex from individuals with MDD, BD, and neurotypical controls to resolve molecular programs associated with diagnosis and biological sex. Our analysis revealed sex- and diagnosis-specific differences across white matter, the neurovascular unit (NVU), and neuronal compartments. Within white matter, we identified female-specific survival-response programs shared in both MDD and BD, and divergent myelin-related gene expression patterns across disorders (CLDN11, CNDP1). Within the NVU, transcriptional evidence of impaired vascular integrity was accompanied by astrocytic response profiles in females with MDD and males with BD, with inflammatory responses further evident in females with MDD (IFITM3, CEBPD, IL1R1). In donors with BD of both sexes and in females with MDD, inhibitory neurons exhibited impaired neuropeptide expression (SST, CORT, CRH). Integration with donor genotype information highlighted that genetic risk for mood disorders influences MAPK3 expression, implicating altered ERK signaling, which was further supported by disorder-associated changes in Ras/MEK/ERK pathway components in neurons (MAPK3, DUSP6, RASD1, ELK1). Together, these findings reveal coordinated, cell type- and spatial domain-specific molecular programs that distinguish shared and disorder-specific transcriptomic changes across mood disorders in a sex-dependent manner.

neuroscience↗

bioRxiv2026

Multi-omic spatial mapping of the human habenula defines the molecular and anatomical organization of medial and lateral subregions

The habenula (Hb) is a small epithalamic midline structure critical for reward processing and mood regulation that is implicated in many complex brain disorders, including depression and addiction. The molecular anatomy of the Hb has been well-characterized in model organisms, but little is known about its organization in the human brain, including the transcriptomic and epigenetic signatures of spatially-organized lateral (LHb) and medial (MHb) cell types. Here, we generated a high resolution spatiomolecular map of the human Hb using both multiomic single nucleus sequencing (snMultiome) and spatially-resolved transcriptomics. We measured gene expression and chromatin accessibility across 4 MHb and 5 LHb neuronal cell types as defined by transcriptomic conservation with rodents and zebrafish. We identified cell type-specific molecular specializations related to GABAergic and glutamatergic signaling as well as regulatory relationships between open chromatin regions, transcription factors, and target genes associated with depression and addiction. High resolution spatial transcriptomics identified the anatomical location of heterogeneous LHb subpopulations, including two putative inhibitory populations in the LHb. We further characterized cell-type relationships between Hb neurons and glial subtypes and predicted ligand-receptor interactions between LHb and MHb neurons. Finally, we delineated Hb cell types and spatial domains enriched in genes associated with genetic risk for psychiatric disorders, identifying the strongest enrichment in the MHb. Collectively, the generated data and analyses resolve the spatiomolecular organization of the human Hb and identify molecular-genetic associations with neuropsychiatric disease.

neuroscience↗

bioRxiv2024

Transcriptomics and proteomics of projection neurons in a circuit linking hippocampus with dorsolateral prefrontal cortex in human brain

Transcriptome and proteome sequencing of brain tissue homogenate has helped unravel processes underlying schizophrenia (SCZ). However, most studies have lacked granularity at the cell type level and have focused on individual brain regions, rather than examining expression dynamics across multiple regions or illness-relevant circuitries. We used laser capture microdissection to collect excitatory neuron-enriched samples from hippocampal subregions CA1 and presubiculum (SUB), and from dorsolateral prefrontal cortex (DLPFC), a circuit prominently implicated in schizophrenia. Using RNA sequencing and quantitative proteomics, we show significantly superior discrimination of brain regional identity in the transcriptomic (>90% accuracy) and proteomic data (>97% accuracy) compared with gene-level expression data (<70% in bulk). Patients with SCZ show hippocampal-specific differential protein phosphorylation. SCZ risk co-expression gene-sets that replicate across transcript and protein networks are enriched for transmembrane transporters in the DLPFC and CA1 and postsynaptic processes in the SUB. We demonstrate a strong directional connectivity effect of SCZ risk in that excitatory synaptic genes in CA1 unidirectionally predict gene expression in SUB. Finally, parallel CA1 snRNA-seq results suggest that in SCZ excitatory efferents in CA1 are affected by interactions with glia and by downregulation of inhibitory neuropeptide inputs. Our study proposes molecular mechanisms by which hippocampal communication, previously associated with SCZ at the macroscopic level, may be altered at the inter-field and interregional circuit level.

neuroscience↗

bioRxiv2021

Decoding shared versus divergent transcriptomic signatures across cortico-amygdala circuitry in PTSD and depressive disorders

Post-traumatic stress disorder (PTSD) is a debilitating neuropsychiatric disease with a projected lifetime risk of 8.7%. PTSD is highly comorbid with depressive disorders including major depressive disorder (MDD) and bipolar disorder (BD). It is hypothesized that the overlap in symptoms stems from partially shared underlying neurobiological mechanisms. To better understand shared and unique transcriptional patterns of PTSD and MDD we performed RNA-sequencing in the postmortem brain of two prefrontal cortex (PFC) regions and two amygdala (AMY) regions, from neurotypical donors (N=109) as well as donors with diagnoses of PTSD (N=107) or MDD (N=109) across 1285 RNA-seq samples. We identified a small number of differentially expressed genes (DEGs) specific to PTSD, mostly in the cortex compared to amygdala. PTSD-specific DEGs were preferentially enriched in cortistatin-expressing cells, a subpopulation of somatostatin interneurons. These PTSD DEGs also showed strong enrichment for gene sets associated with immune-related pathways and microglia, largely driven by decreased expression of these genes in PTSD donors. While we identified a greater number of DEGs for MDD, there were only a few that were specific to MDD as they showed high overlap with PTSD DEGs. Finally, we used weighted gene co-expression network analysis (WGCNA) as an orthogonal approach to confirm the observed cellular and molecular associations. These findings highlight the sub-population of cortistatin-expressing interneurons as having potential functional significance in PTSD and provide supporting evidence for dysregulated neuroinflammation and immune signaling in MDD and PTSD pathophysiology.

neuroscience↗

bioRxiv2020

Differential Expression of NPAS4 in the Dorsolateral Prefrontal Cortex Following Acute Opioid Intoxication

Background and AimsThe physical, emotional, and social impacts of opioid abuse are well known; although preclinical models reveal the neurobiological pathways altered through opioid abuse, comprehensive assessments of gene expression in human brain samples are lacking. The goals of the present study were to compare gene expression in the prefrontal cortex between brain samples of individuals who died of acute opioid intoxication and group-matched controls, and to test if differential gene expression was enriched in gene sets related to opioid use. DesignCross-sectional study using human brains donated to the Lieber Institute for Brain Development. Study groups included 72 brain samples from individuals who died of acute opioid intoxication, 53 group-matched psychiatric control samples, and 28 group-matched normal control samples. SettingMaryland, USA. ParticipantsPostmortem tissue samples of the dorsolateral prefrontal cortex from 153 deceased individuals (Mage = 35.42, SD = 9.43 years; 62% male; 77% White). MeasurementsWhole transcriptome RNA sequencing was used to generate exon counts, and differential expression was tested using limma-voom. Analyses controlled for relevant sociodemographic characteristics, technical covariates, and cryptic relatedness and batch effects using quality surrogate variable analysis. Gene set enrichment analyses (GSEA) also were conducted. FindingsSixteen genes were differentially expressed (i.e., FDR-corrected p < .10) in opioid samples compared to control samples. The top differentially expressed gene, NPAS4 (FDR adjusted p = .005), was downregulated in opioid samples and has previously been implicated in cocaine use. Enrichment analyses did not provide evidence for enrichment in pathways obviously related to opioid use. ConclusionsNPAS4 is differentially expressed in the prefrontal cortex of subjects that died of an opioid overdose, providing evidence for another gene with functional relevance to opioid use and overdose.

genomics↗

bioRxiv2020

Epigenome-wide study of brain DNA methylation among opioid users and controls

Opioid abuse poses significant risk to individuals in the United States and epigenetic changes are a leading potential biomarker of abuse. Current evidence, however, is mostly limited to candidate gene analysis in whole blood. To clarify the association between opioid abuse and DNA methylation, we conducted an epigenome-wide analysis (EWAS) of DNA methylation in brains of individuals who died from opioid intoxication and controls. Tissue samples were extracted from the dorsolateral prefrontal cortex of 160 deceased individuals (Mage = 35.15, SD = 9.42 years; 62% male; 78% White). The samples included 73 individuals who died of opioid intoxication, 59 group-matched psychiatric controls, and 28 group-matched normal controls. EWAS was implemented using the Illumina Infinium MethylationEPIC BeadChip; analyses adjusted for sociodemographic characteristics, negative control and ancestry principal components, cellular composition, and surrogate variables. Epigenetic age was calculated using the Horvath and Levine clocks, and gene ontology (GO) analyses were performed. No CpG sites were epigenome-wide significant after multiple testing correction, but 13 sites reached nominal significance (p < 1.0 x 10-5). There was a significant association between opioid use and Levine phenotypic age (b = 2.24, se = 1.11, p = .045). Opioid users were approximately two years phenotypically older compared to controls. GO analyses revealed enriched pathways related to cell function and neuron differentiation, but no terms survived multiple testing correction. Results inform our understanding of the neurobiology of opioid use, and future research with larger samples across stages of opioid use will elucidate the complex genomics of opioid abuse.

genomics↗

bioRxiv2019

Genome-wide DNA methylation differences in nucleus accumbens of smokers vs. nonsmokers

Numerous DNA methylation (DNAm) biomarkers of cigarette smoking have been identified in peripheral blood studies, but their relevance as neurobiological indicators is unknown due to DNAm tissue-specificity. In contrast, blood-based studies may not detect brain-specific smoking-related DNAm differences that may provide greater insight into the neurobiology of smoking behaviors. We report the first epigenome-wide association study (EWAS) of smoking in human postmortem brain, focusing on nucleus accumbens (NAc) as a key brain region in developing addiction. Following Illumina HumanMethylation EPIC array data generation and quality control, 221 decedents (120 European American [23% current smokers], 101 African American [26% current smokers]) were analyzed. DNAm by smoking (current vs. nonsmoking) was tested using robust linear regression models adjusted for age, sex, cell-type proportion, DNAm-derived negative control principal components (PCs), and genotype-derived PCs. Separate ancestry-specific results were combined via meta-analysis, resulting in 7 CpGs that exceeded false discovery rate (FDR)<0.05. Using published smoking EWAS results in blood, we extended our NAc findings to identify DNAm smoking effects that are unique (tissue-specific) versus shared between tissues (tissue-shared). Of the 7 CpGs identified in NAc, 3 CpGs were located near genes previously indicated with blood-based smoking DNAm biomarkers: ZIC1, ZCCHC24, and PRKDC. The other 4 CpGs are novel for smoking-related DNAm changes: ABLIM3, APCDD1L, MTMR6, and CTCF. Our results provide the first evidence for smoking-related DNAm changes in human NAc, highlighting CpGs that were previously undetected as peripheral biomarkers and may reflect brain-specific processes.

neuroscience↗

bioRxiv2019

Cell type-specific genetic regulation of expression in the granule cell layer of the human dentate gyrus

Laser capture microdissection followed by RNA-seq (LCM-seq) was used to profile the transcriptional landscape of the granule cell layer of the dentate gyrus (DG-GCL) in human hippocampus, and contrasted to homogenate tissue. We identified widespread cell type-specific aging and genetic effects in the DG-GCL that were either missing or directionally discordant in corresponding bulk hippocampus RNA-seq data from largely the same subjects. Of the [~]9 million eQTLs in the DG-GCL, 15% were not in bulk hippocampus, including 15 schizophrenia genome-wide association study (GWAS) risk variants. We then created custom transcriptome-wide association study (TWAS) genetic weights from the DG-GCL which identified many novel schizophrenia-associated genetic signals not found in TWAS from bulk hippocampus, including GRM3 and CACNA1C. These results highlight the biological resolution of cell type-specific expression profiling using targeted sampling strategies like LCM, and complement homogenate and single nuclei approaches in human brain.

neuroscience↗

bioRxiv2018

Integrated DNA methylation and gene expression profiling across multiple brain regions implicate novel genes in Alzheimer’s disease

BackgroundLate-onset Alzheimers disease (AD) is a complex age-related neurodegenerative disorder that likely involves epigenetic factors. To better understand the epigenetic state associated with AD represented as variation in DNA methylation (DNAm), we surveyed 420,852 DNAm sites from neurotypical controls (N=49) and late-onset AD patients (N=24) across four brain regions (hippocampus, entorhinal cortex, dorsolateral prefrontal cortex and cerebellum).\n\nResultsWe identified 858 sites with robust differential methylation, collectively annotated to 772 possible genes (FDR<5%, within 10kb). These sites were overrepresented in AD genetic risk loci (p=0.00655), and nearby genes were enriched for processes related to cell-adhesion, immunity, and calcium homeostasis (FDR<5%). We analyzed corresponding RNA-seq data to prioritize 130 genes within 10kb of the differentially methylated sites, which were differentially expressed and had expression levels associated with nearby DNAm levels (p<0.05). This validated gene set includes previously reported (e.g. ANK1, DUSP22) and novel genes involved in Alzheimers disease, such as ANKRD30B.\n\nConclusionsThese results highlight DNAm changes in Alzheimers disease that have gene expression correlates, implicating DNAm as an epigenetic mechanism underlying pathological molecular changes associated with AD. Furthermore, our framework illustrates the value of integrating epigenetic and transcriptomic data for understanding complex disease.

genomics↗

bioRxiv2018

Regional heterogeneity in gene expression, regulation and coherence in hippocampus and dorsolateral prefrontal cortex across development and in schizophrenia

Recent large-scale genomics efforts have better characterized the molecular correlates of schizophrenia in postmortem human neocortex, but not hippocampus which is a brain region prominently implicated in its pathogenesis. Here in the second phase of the BrainSeq Consortium (Phase II), we have generated RiboZero RNA-seq data for 900 samples across both the dorsolateral prefrontal cortex (DLPFC) and the hippocampus (HIPPO) for 551 individuals (286 affected by schizophrenia disorder: SCZD). We identify substantial regional differences in gene expression, in both pre- and post-natal life, and find widespread differences in how genes are regulated across development. By extending quality surrogate variable analysis (qSVA) to multiple brain regions, we identified 48 and 245 differentially expressed genes (DEG) by SCZD diagnosis (FDR<5%) in HIPPO and DLPFC, respectively, with surprisingly minimal overlap in DEG between the two brain regions. We further identified 205,618 brain region-dependent eQTLs (FDR<1%) and found that 124 GWAS risk loci contain eQTLs in at least one of the regions. We also identify potential molecular correlates of in vivo evidence of altered prefrontal-hippocampal functional coherence in schizophrenia. These results underscore the complexity and regional heterogeneity of the transcriptional correlates of schizophrenia, and suggest future schizophrenia therapeutics may need to target molecular pathologies localized to specific brain regions.

neuroscience↗

bioRxiv2018

Association of a lincRNA postmortem with suicide by violent means and in vivo with aggressive phenotypes

ObjectivePrevious findings suggest that differences in brain expression of a human-specific long intergenic non-coding RNA (LINC01268; GRCh37/hg19: LOC285758) may be linked to aggressive behavior and suicide. The authors sought to replicate and extend these findings in a new sample, and translate the results to the behavioral level in living healthy subjects.\n\nMethodThe authors examined RNA sequencing data in human brain to confirm the prior postmortem association of the lincRNA specifically with suicide by violent means. In addition, they used a genetic variant associated with LINC01268 expression to detect association with in vivo prefrontal physiology related to behavioral control. They finally performed weighted gene co-expression network analysis (WGCNA) and gene-ontology analysis to identify biological processes associated with a LINC01268 co-expression network.\n\nResultsIn the replication sample, prefrontal expression of LINC01268 was again higher in suicides by violent means (N=65) than both non-suicides (N=78; 1.29e-06) and suicides by non-violent means (N=46; p=1.4e-06). In a living cohort, carriers of the minor allele of a SNP associated with increased LINC01268 expression in brain scored higher on a lifetime aggression questionnaire and show diminished engagement of prefrontal cortex (BA10) when viewing angry faces during fMRI. WGCNA highlighted the immune response.\n\nConclusionsThese results suggest that LINC01268 influences emotional regulation, aggressive behavior and suicide by violent means; the underlying biological dynamics may include modulation of genes potentially engaged in the immune response.

neuroscience↗

bioRxiv2017

Developmental effects of maternal smoking during pregnancy on the human frontal cortex transcriptome

Cigarette smoking during pregnancy is a major public health concern. While there are well-described consequences in early child development, there is very little known about the effects of maternal smoking on human cortical biology during prenatal life. We therefore performed a genome-wide differential gene expression analysis using RNA sequencing (RNA-seq) on prenatal (N=33; 16 smoking-exposed) as well as adult (N=207; 57 active smokers) human post-mortem prefrontal cortices. Smoking exposure during the prenatal period was directly associated with differential expression of 14 genes; in contrast, during adulthood, despite a much larger sample size, only 2 genes showed significant differential expression (FDR<10%). Moreover, 1,315 genes showed significantly different exposure effects between maternal smoking during pregnancy and direct exposure in adulthood (FDR<10%) - these differences were largely driven by prenatal differences that were enriched for pathways previously implicated in addiction and synaptic function. Furthermore, prenatal and age-dependent differentially expressed genes were enriched for genes implicated in non-syndromic autism spectrum disorder (ASD) and were differentially expressed as a set between patients with ASD and controls in post-mortem cortical regions. These results underscore the enhanced sensitivity to the biological effect of smoking exposure in the developing brain and offer novel insight into the effects of maternal smoking during pregnancy on the prenatal human brain. They also begin to address the relationship between in utero exposure to smoking and the heightened risks for the subsequent development of neuropsychiatric disorders.\n\nOne Sentence SummaryMaternal smoking during pregnancy alters the expression of genes within the developing human cortex and these changes are enriched for genes implicated in neuropsychiatric disorders.

neuroscience↗

bioRxiv2017

Developmental And Genetic Regulation Of The Human Cortex Transcriptome In Schizophrenia

GWAS have identified 108 loci that confer risk for schizophrenia, but risk mechanisms for individual loci are largely unknown. Using developmental, genetic, and illness-based RNA sequencing expression analysis, we characterized the human brain transcriptome around these loci and found enrichment for developmentally regulated genes with novel examples of shifting isoform usage across pre- and post-natal life. We found widespread expression quantitative trait loci (eQTLs), including many with transcript specificity and previously unannotated sequence that were independently replicated. We leveraged this eQTL database to show that 48.1% of risk variants for schizophrenia associated with nearby expression. Within patients and controls, we implemented a novel algorithm for RNA quality adjustment, and identified 237 genes significantly associated with diagnosis that replicated in an independent case-control dataset. These genes implicated synaptic processes and were strongly regulated in early development (p < 10-20). These data offer new targets for modeling schizophrenia risk in cellular systems.

neuroscience↗