Cell Type-specific Analysis Research Articles

CRISPR screening by AAV episome-sequencing (CrAAVe-seq) is a highly scalable cell type-specific in vivo screening platform.

There is a significant need for scalable CRISPR-based genetic screening methods that can be applied directly in mammalian tissues in vivo while enabling cell type-specific analysis. To address this, we developed an adeno-associated virus (AAV)-based CRISPR screening platform, CrAAVe-seq, that incorporates a Cre-sensitive sgRNA construct for pooled screening within targeted cell populations in the mouse tissues. We demonstrate the utility of this approach by screening two distinct large sgRNA libraries, together targeting over 5,000 genes, in mouse brains to create a robust profile of neuron-essential genes. We validate two genes as strongly neuron-essential in both primary mouse neurons and in vivo, confirming the predictive power of our platform. By comparing results from individual mice and across different cell populations, we highlight the reproducibility and scalability of the platform and show that it is highly sensitive even for screening smaller neuronal subpopulations. We systematically characterize the impact of sgRNA library size, mouse cohort size, the size of the targeted cell population, viral titer, and multiplicity of infection on screen performance to establish general guidelines for large-scale in vivo screens.

Identification of nitric oxide-mediated necroptosis as the predominant death route in Parkinson’s disease

Parkinson's disease (PD) involves multiple forms of neuronal cell death, but the dominant pathway involved in disease progression remains unclear. This study employed RNA sequencing (RNA-seq) of brain tissue to explore gene expression patterns across different stages of PD. Using the Scaden deep learning algorithm, we predicted neurocyte subtypes and modelled dynamic interactions for five classic cell death pathways to identify the predominant routes of neuronal death during PD progression. Our cell type-specific analysis revealed an increasing shift towards necroptosis, which was strongly correlated with nitric oxide synthase (NOS) expression across most neuronal subtypes. In vitro experiments confirmed that nitric oxide (NO) is a key mediator of necroptosis, leading to nuclear shrinkage and decreased mitochondrial membrane potential via phosphorylation of the PIP1/PIP3/MLKL signalling cascade. Importantly, specific necroptosis inhibitors significantly mitigated neuronal damage in both in vitro and in vivo PD models. Further analysis revealed that NO-mediated necroptosis is prevalent in early-onset Alzheimer's disease (AD) and amyotrophic lateral sclerosis (ALS) and across multiple brain regions but not in brain tumours. Our findings suggest that NO-mediated necroptosis is a critical pathway in PD and other neurodegenerative disorders, providing potential targets for therapeutic intervention.

Emotional dysregulation following prenatal stress is associated with altered prefrontal cortex responsiveness to an acute challenge in adolescence

Exposure to prenatal stress (PNS) has the potential to elicit multiple neurobiological alterations and increase the susceptibility to psychiatric disorders. Moreover, gestational stress may sensitize the brain toward an altered response to subsequent challenges. Here, we investigated the effects of PNS in rats and assessed whether these animals exhibit an altered brain responsiveness to an acute stress (AS) during adolescence. From gestational day 14 until delivery, Sprague Dawley dams were exposed to PNS or left undisturbed. During adolescence (PND38 to PND41), offspring were tested in the social interaction and splash test. At PND44 half of the animals were exposed to 5 min of forced swim stress. Males and Females exposed to PNS showed reduced sociability and increased anhedonic-like behavior. At the molecular level, exposure of adolescent rats to AS produced increased activation of the amygdala and ventral and dorsal hippocampus. Regarding the prefrontal cortex (PFC), we observed a pronounced activation in PNS males exposed to AS. Cell-type specific transcriptional analyses revealed a significant imbalance in the activation of PFC excitatory and inhibitory neurons in PNS males and females exposed to AS. Furthermore, stressed males exhibited disrupted HPA-axis function, while females showed impairments in the modulation of antioxidant genes. Our study shows that PNS induces emotional dysregulation and alters the responsiveness of the PFC to an acute stressor. Moreover, the disruption of excitatory and inhibitory balance during adolescence could influence the ability to respond to challenging events that may contribute to precipitate a full-blown pathologic condition.

ScRNAbox: empowering single-cell RNA sequencing on high performance computing systems

BackgroundSingle-cell RNA sequencing (scRNAseq) offers powerful insights, but the surge in sample sizes demands more computational power than local workstations can provide. Consequently, high-performance computing (HPC) systems have become imperative. Existing web apps designed to analyze scRNAseq data lack scalability and integration capabilities, while analysis packages demand coding expertise, hindering accessibility.ResultsIn response, we introduce scRNAbox, an innovative scRNAseq analysis pipeline meticulously crafted for HPC systems. This end-to-end solution, executed via the SLURM workload manager, efficiently processes raw data from standard and Hashtag samples. It incorporates quality control filtering, sample integration, clustering, cluster annotation tools, and facilitates cell type-specific differential gene expression analysis between two groups. We demonstrate the application of scRNAbox by analyzing two publicly available datasets.ConclusionScRNAbox is a comprehensive end-to-end pipeline designed to streamline the processing and analysis of scRNAseq data. By responding to the pressing demand for a user-friendly, HPC solution, scRNAbox bridges the gap between the growing computational demands of scRNAseq analysis and the coding expertise required to meet them.

Proteomic evidence of depression-associated astrocytic dysfunction in the human male olfactory bulb

The olfactory bulb (OB), a major structure of the limbic system, has been understudied in human investigations of psychopathologies such as depression. To explore more directly the molecular features of the OB in depression, a global comparative proteome analysis was carried out with human post-mortem OB samples from 11 males having suffered from depression and 12 healthy controls. We identified 188 differentially abundant proteins (with adjusted p < 0.05) between depressed cases and controls. Gene ontology and gene enrichment analyses suggested that these proteins are involved in biological processes including the complement and coagulation cascades. Cell type enrichment analysis displayed a significant reduction in several canonical astrocytic proteins in OBs from depressed patients. Furthermore, using RNA-fluorescence in-situ hybridization, we observed a decrease in the percentage of ALDH1L1+ cells expressing canonical astrocytic markers including ALDOC, NFIA, GJA1 (connexin 43) and SLC1A3 (EAAT1). These results are consistent with previous reports of downregulated astrocytic marker expression in other brain regions in depressed patients. We also conducted a comparative phosphoproteomic analysis of OB samples and found a dysregulation of proteins involved in neuronal and astrocytic functions. To determine whether OB astrocytic abnormalities is specific to humans, we also performed proteomics on the OB of socially defeated male mice, a commonly used model of depression. Cell-type specific analysis revealed that in socially defeated animals, the most striking OB protein alterations were associated with oligodendrocyte-lineage cells rather than with astrocytes, highlighting an important species difference. Overall, this study further highlights cerebral astrocytic abnormalities as a consistent feature of depression in humans.

Resolving the 22q11.2 deletion using CTLR-Seq reveals chromosomal rearrangement mechanisms and individual variance in breakpoints

We developed a generally applicable method, CRISPR/Cas9-targeted long-read sequencing (CTLR-Seq), to resolve, haplotype-specifically, the large and complex regions in the human genome that had been previously impenetrable to sequencing analysis, such as large segmental duplications (SegDups) and their associated genome rearrangements. CTLR-Seq combines in vitro Cas9-mediated cutting of the genome and pulse-field gel electrophoresis to isolate intact large (i.e., up to 2,000 kb) genomic regions that encompass previously unresolvable genomic sequences. These targets are then sequenced (amplification-free) at high on-target coverage using long-read sequencing, allowing for their complete sequence assembly. We applied CTLR-Seq to the SegDup-mediated rearrangements that constitute the boundaries of, and give rise to, the 22q11.2 Deletion Syndrome (22q11DS), the most common human microdeletion disorder. We then performed de novo assembly to resolve, at base-pair resolution, the full sequence rearrangements and exact chromosomal breakpoints of 22q11.2DS (including all common subtypes). Across multiple patients, we found a high degree of variability for both the rearranged SegDup sequences and the exact chromosomal breakpoint locations, which coincide with various transposons within the 22q11.2 SegDups, suggesting that 22q11DS can be driven by transposon-mediated genome recombination. Guided by CTLR-Seq results from two 22q11DS patients, we performed three-dimensional chromosomal folding analysis for the 22q11.2 SegDups from patient-derived neurons and astrocytes and found chromosome interactions anchored within the SegDups to be both cell type-specific and patient-specific. Lastly, we demonstrated that CTLR-Seq enables cell-type specific analysis of DNA methylation patterns within the deletion haplotype of 22q11DS.

Aberrant proximal tubule DNA methylation underlies phenotypic changes related to kidney dysfunction in patients with diabetes.

Epigenetic mechanisms are considered to contribute to diabetic nephropathy by maintaining memory of poor glycemic control during the early stages of diabetes. However, DNA methylation changes in the human kidney are poorly characterized, because of the lack of cell type-specific analysis. We examined DNA methylation in proximal tubules purified from diabetic nephropathy patients and identified differentially methylated CpG sites, given the critical role of proximal tubules in the kidney injury. Hypermethylation was observed at CpG sites annotated to genes responsible for proximal tubule functions, including gluconeogenesis, nicotinamide adenine dinucleotide synthesis, transporters of glucose, water, phosphate, and drugs, in diabetic kidneys, while genes involved in oxidative stress and the cytoskeleton exhibited demethylation. Methylation levels of CpG sites annotated to ACTN1, BCAR1, MYH9, UBE4B, AFMID, TRAF2, TXNIP, FOXO3, and HNF4A were correlated with the estimated glomerular filtration rate, while methylation of the CpG site in RUNX1 was associated with interstitial fibrosis and tubular atrophy. Hypermethylation of G6PC and HNF4A was accompanied by decreased expression in diabetic kidneys. Proximal tubule-specific hypomethylation of metabolic genes related to HNF4A observed in control kidneys was compromised in diabetic kidneys, suggesting a role for aberrant DNA methylation in the dedifferentiation process. Multiple genes with aberrant DNA methylation in diabetes overlapped genes with altered expressions in maladaptive proximal tubule cells, including transcription factors PPARA and RREB1. In conclusion, DNA methylation derangement in the proximal tubules of patients with diabetes may drive phenotypic changes, characterized by inflammatory and fibrotic features, along with impaired function in metabolism and transport.

Spatiomolecular Characterization of Dopamine D2 Receptors Cells in the Mouse External Globus Pallidus.

The external globus pallidus (GPe) is part of the basal ganglia circuit and plays a key role in controlling the actions. Although, many evidence indicate that dopamine through its activation of dopamine D2 receptors (D2Rs) modulates the GPe neuronal activity, the precise spatiomolecular characterization of cell populations expressing D2Rs in the mouse GPe is still lacking. By combining single molecule in situ hybridization, cell type-specific imaging analyses, and electrophysiology slice recordings, we found that GPe D2R cells are neurons preferentially localized in the caudal portion of GPe. These neurons comprising pallido-striatal, pallido-nigral, and pallido-cortical neurons segregate into two distinct populations displaying molecular and electrophysiological features of GPe GABAergic PV/NKX2.1 and cholinergic neurons respectively. By clarifying the spatial molecular identity of GPe D2R neurons in the mouse, this work provides the basis for future studies aiming at disentangling the action of dopamine within the GPe.

Cell-type specific inference from bulk RNA-sequencing data by integrating single cell reference profiles via EPIC-unmix.

Cell type specific (CTS) analysis is essential to reveal biological insights obscured in bulk tissue data. However, single-cell (sc) or single-nuclei (sn) resolution data are still cost-prohibitive for large-scale samples. Thus, computational methods to perform deconvolution from bulk tissue data are highly valuable. We here present EPIC-unmix, a novel two-step empirical Bayesian method integrating reference sc/sn RNA-seq data and bulk RNA-seq data from target samples to enhance the accuracy of CTS inference. We demonstrate through comprehensive simulations across three tissues that EPIC-unmix achieved 4.6% - 109.8% higher accuracy compared to alternative methods. By applying EPIC-unmix to human bulk brain RNA-seq data from the ROSMAP and MSBB cohorts, we identified multiple genes differentially expressed between Alzheimer's disease (AD) cases versus controls in a CTS manner, including 57.4% novel genes not identified using similar sample size sc/snRNA-seq data, indicating the power of our in-silico approach. Among the 6-69% overlapping, 83%-100% are in consistent direction with those from sc/snRNA-seq data, supporting the reliability of our findings. EPIC-unmix inferred CTS expression profiles similarly empowers CTS eQTL analysis. Among the novel eQTLs, we highlight a microglia eQTL for AD risk gene AP3B2, obscured in bulk and missed by sc/snRNA-seq based eQTL analysis. The variant resides in a microglia-specific cCRE, forming chromatin loop with AP3B2 promoter region in microglia. Taken together, we believe EPIC-unmix will be a valuable tool to enable more powerful CTS analysis.

Cell type-specific network analysis in Diversity Outbred mice identifies genes potentially responsible for human bone mineral density GWAS associations.

Genome-wide association studies (GWASs) have identified many sources of genetic variation associated with bone mineral density (BMD), a clinical predictor of fracture risk and osteoporosis. Aside from the identification of causal genes, other difficult challenges to informing GWAS include characterizing the roles of predicted causal genes in disease and providing additional functional context, such as the cell type predictions or biological pathways in which causal genes operate. Leveraging single-cell transcriptomics (scRNA-seq) can assist in informing BMD GWAS by linking disease-associated variants to genes and providing a cell type context for which these causal genes drive disease. Here, we use large-scale scRNA-seq data from bone marrow-derived stromal cells cultured under osteogenic conditions (BMSC-OBs) from Diversity Outbred (DO) mice to generate cell type-specific networks and contextualize BMD GWAS-implicated genes. Using trajectories inferred from the scRNA-seq data, we identify networks enriched with genes that exhibit the most dynamic changes in expression across trajectories. We discover 21 network driver genes, which are likely to be causal for human BMD GWAS associations that colocalize with expression/splicing quantitative trait loci (eQTL/sQTL). These driver genes, including Fgfrl1 and Tpx2, along with their associated networks, are predicted to be novel regulators of BMD via their roles in the differentiation of mesenchymal lineage cells. In this work, we showcase the use of single-cell transcriptomics from mouse bone-relevant cells to inform human BMD GWAS and prioritize genetic targets with potential causal roles in the development of osteoporosis.

Distinct roles of excitatory and inhibitory neurons in the medial prefrontal cortex in the expression and reconsolidation of methamphetamine-associated memory in male mice.

Methamphetamine, a commonly abused drug, is known for its high relapse rate. The persistence of addictive memories associated with methamphetamine poses a significant challenge in preventing relapse. Memory retrieval and subsequent reconsolidation provide an opportunity to disrupt addictive memories. However, the key node in the brain network involved in methamphetamine-associated memory retrieval has not been clearly defined. In this study, using the conditioned place preference in male mice, whole brain c-FOS mapping and functional connectivity analysis, together with chemogenetic manipulations of neural circuits, we identified the medial prefrontal cortex (mPFC) as a critical hub that integrates inputs from the retrosplenial cortex and the ventral tegmental area to support both the expression and reconsolidation of methamphetamine-associated memory during its retrieval. Surprisingly, with further cell-type specific analysis and manipulation, we also observed that methamphetamine-associated memory retrieval activated inhibitory neurons in the mPFC to facilitate memory reconsolidation, while suppressing excitatory neurons to aid memory expression. These findings provide novel insights into the neural circuits and cellular mechanisms involved in the retrieval process of addictive memories. They suggest that targeting the balance between excitation and inhibition in the mPFC during memory retrieval could be a promising treatment strategy to prevent relapse in methamphetamine addiction.

Cell Type-Specific Multi-Omics Analysis of Cocaine Use Disorder in the Human Caudate Nucleus Suggests Phosphodiesterases as a Pharmacological Target

Cell Type-Specific Multi-Omics Analysis of Cocaine Use Disorder in the Human Caudate Nucleus Suggests Phosphodiesterases as a Pharmacological Target

302 Diagnostic Evidence Gauge of Spatial Transcriptomics (DEGAS-ST): Using transfer learning to map clinical data to spatial transcriptomics in prostate cancer

OBJECTIVES/GOALS: The 'field effect' is a concept in pathology that pre-malignant tissue changes forecast health. Spatial transcriptomics could detect these changes earlier than histopathology, suggesting new early cancer screening methods. Knowing how normal tissue damage relates to cancer’s origin and progression may improve long-term outcomes. METHODS/STUDY POPULATION: We trained DEGAS, our machine learning framework, with prostate cancer data, combining both general cancer patterns and in-depth genetic information from individual tumors. The Tumor Cancer Genome Atlas (TCGA) shows how gene patterns in tumors relate to patient outcomes, emphasizing the differences between tumors from different patients (intertumor). On the other hand, spatial transcriptomics (ST) shows the genetic variety within a single tumor (intratumor) but has limited samples, making it hard to know which genetic differences are important for treatment. DEGAS bridges these areas by finding tissue sections that resemble those in TCGA profiles and are key indicators of patient survival. DEGAS serves as a valuable tool for generating clinically-important hypotheses. RESULTS/ANTICIPATED RESULTS: DEGAS identified benign-appearing glands in a normal prostate as being highly associated with poor progression-free survival. These glands have transcriptional signatures similar to high-grade prostate cancer. We confirmed this finding in a separate prostate cancer ST dataset. By integrating single cell (SC) data we demonstrated that cells annotated as cancerous in the SC data map to regions of benign glands in the ST dataset. We pinpoint several genes, chiefly Microseminoprotein-β (MSMB, PSP94), where reduced expression is highly correlated with poor progression-free survival. Cell type specific differential expression analysis further revealed that loss of MSMB expression associated with poor outcomes occurs specifically in luminal epithelia, the putative progenitor of prostate cancer. DISCUSSION/SIGNIFICANCE: DEGAS reveals that normal-appearing tissue can be highly-associated with tumor progression and underscores the importance of the 'field effect' in cancer research. Traditional analysis may miss such nuance, hiding key transitional cell states. Validating gene markers could boost early cancer detection and understanding of metastasis.

Regional analysis to delineate intrasample heterogeneity with RegionalST.

Spatial transcriptomics has greatly contributed to our understanding of spatial and intra-sample heterogeneity, which could be crucial for deciphering the molecular basis of human diseases. Intra-tumor heterogeneity, e.g. may be associated with cancer treatment responses. However, the lack of computational tools for exploiting cross-regional information and the limited spatial resolution of current technologies present major obstacles to elucidating tissue heterogeneity. To address these challenges, we introduce RegionalST, an efficient computational method that enables users to quantify cell type mixture and interactions, identify sub-regions of interest, and perform cross-region cell type-specific differential analysis for the first time. Our simulations and real data applications demonstrate that RegionalST is an efficient tool for visualizing and analyzing diverse spatial transcriptomics data, thereby enabling accurate and flexible exploration of tissue heterogeneity. Overall, RegionalST provides a one-stop destination for researchers seeking to delve deeper into the intricacies of spatial transcriptomics data. The implementation of our method is available as an open-source R/Bioconductor package with a user-friendly manual available at https://bioconductor.org/packages/release/bioc/html/RegionalST.html.

Single nuclear RNA sequencing of terminal ileum in patients with cirrhosis demonstrates multi-faceted alterations in the intestinal barrier

Patients with cirrhosis have intestinal barrier dysfunction but the role of the individual cell types in human small intestine is unclear. We performed single-nuclear RNA sequencing (snRNAseq) in the pinch biopsies of terminal ileum of four age-matched men [56 years, healthy control, compensated, early (ascites and lactulose use) and advanced decompensated cirrhosis (ascites and rifaximin use)]. Cell type proportions, differential gene expressions, cell-type specific pathway analysis using IPA, and cellular crosstalk dynamics were compared. Stem cells, enterocytes and Paneth cells were lowest in advanced decompensation. Immune cells like naive CD4 + T cells were lowest while ITGAE + cells were highest in advanced decompensation patients. MECOM had lowest expression in stem cells in advanced decompensation. Defensin and mucin sulfation gene (PAPSS2) which can stabilize the mucus barrier expression were lowest while IL1, IL6 and TNF-related genes were significantly upregulated in the enterocytes, goblet, and Paneth cells in decompensated subjects. IPA analysis showed higher inflammatory pathways in enterocytes, stem, goblet, and Paneth cells in decompensated patients. Cellular crosstalk analysis showed that desmosome, protease-activated receptors, and cadherin-catenin complex interactions were most perturbed in decompensated patients. In summary, the snRNAseq of the human terminal ileum in 4 subjects (1 control and three cirrhosis) identified multidimensional alteration in the intestinal barrier with lower stem cells and altered gene expression focused on inflammation, mucin sulfation and cell–cell interactions with cirrhosis decompensation.

Distinct guard cell-specific remodeling of chromatin accessibility during abscisic acid- and CO2-dependent stomatal regulation.

In plants, epidermal guard cells integrate and respond to numerous environmental signals to control stomatal pore apertures, thereby regulating gas exchange. Chromatin structure controls transcription factor (TF) access to the genome, but whether large-scale chromatin remodeling occurs in guard cells during stomatal movements, and in response to the hormone abscisic acid (ABA) in general, remains unknown. Here, we isolate guard cell nuclei from Arabidopsis thaliana plants to examine whether the physiological signals, ABA and CO2 (carbon dioxide), regulate guard cell chromatin during stomatal movements. Our cell type-specific analyses uncover patterns of chromatin accessibility specific to guard cells and define cis-regulatory sequences supporting guard cell-specific gene expression. We find that ABA triggers extensive and dynamic chromatin remodeling in guard cells, roots, and mesophyll cells with clear patterns of cell type specificity. DNA motif analyses uncover binding sites for distinct TFs enriched in ABA-induced and ABA-repressed chromatin. We identify the Abscisic Acid Response Element (ABRE) Binding Factor (ABF) bZIP-type TFs that are required for ABA-triggered chromatin opening in guard cells and roots and implicate the inhibition of a clade of bHLH-type TFs in controlling ABA-repressed chromatin. Moreover, we demonstrate that ABA and CO2 induce distinct programs of chromatin remodeling, whereby elevated atmospheric CO2 had only minimal impact on chromatin dynamics. We provide insight into the control of guard cell chromatin dynamics and propose that ABA-induced chromatin remodeling primes the genome for abiotic stress resistance.

FastCAR: fast correction for ambient RNA to facilitate differential gene expression analysis in single-cell RNA-sequencing datasets

Cell type-specific differential gene expression analyses based on single-cell transcriptome datasets are sensitive to the presence of cell-free mRNA in the droplets containing single cells. This so-called ambient RNA contamination may differ between samples obtained from patients and healthy controls. Current ambient RNA correction methods were not developed specifically for single-cell differential gene expression (sc-DGE) analyses and might therefore not sufficiently correct for ambient RNA-derived signals. Here, we show that ambient RNA levels are highly sample-specific. We found that without ambient RNA correction, sc-DGE analyses erroneously identify transcripts originating from ambient RNA as cell type-specific disease-associated genes. We therefore developed a computationally lean and intuitive correction method, Fast Correction for Ambient RNA (FastCAR), optimized for sc-DGE analysis of scRNA-Seq datasets generated by droplet-based methods including the 10XGenomics Chromium platform. FastCAR uses the profile of transcripts observed in libraries that likely represent empty droplets to determine the level of ambient RNA in each individual sample, and then corrects for these ambient RNA gene expression values. FastCAR can be applied as part of the data pre-processing and QC in sc-DGE workflows comparing scRNA-Seq data in a health versus disease experimental design. We compared FastCAR with two methods previously developed to remove ambient RNA, SoupX and CellBender. All three methods identified additional genes in sc-DGE analyses that were not identified in the absence of ambient RNA correction. However, we show that FastCAR performs better at correcting gene expression values attributed to ambient RNA, resulting in a lower frequency of false-positive observations. Moreover, the use of FastCAR in a sc-DGE workflow increases the cell-type specificity of sc-DGE analyses across disease conditions.

Integrative genome-wide analyses identify novel loci associated with kidney stones and provide insights into its genetic architecture

Kidney stone disease (KSD) is a complex disorder with high heritability and prevalence. We performed a large genome-wide association study (GWAS) meta-analysis for KSD to date, including 720,199 individuals with 17,969 cases in European population. We identified 44 susceptibility loci, including 28 novel loci. Cell type-specific analysis pinpointed the proximal tubule as the most relevant cells where susceptibility variants might act through a tissue-specific fashion. By integrating kidney-specific omics data, we prioritized 223 genes which strengthened the importance of ion homeostasis, including calcium and magnesium in stone formation, and suggested potential target drugs for the treatment. The genitourinary and digestive diseases showed stronger genetic correlations with KSD. In this study, we generate an atlas of candidate genes, tissue and cell types involved in the formation of KSD. In addition, we provide potential drug targets for KSD treatment and insights into shared regulation with other diseases.

Psychiatric risk gene Transcription Factor 4 (TCF4) regulates the density and connectivity of distinct inhibitory interneuron subtypes.

Transcription factor 4 (TCF4) is a basic helix-loop-helix transcription factor that is implicated in a variety of psychiatric disorders including autism spectrum disorder (ASD), major depression, and schizophrenia. Autosomal dominant mutations in TCF4 are causal for a specific ASD called Pitt-Hopkins Syndrome (PTHS). However, our understanding of etiological and pathophysiological mechanisms downstream of TCF4 mutations is incomplete. Single cell sequencing indicates TCF4 is highly expressed in GABAergic interneurons (INs). Here, we performed cell-type specific expression analysis (CSEA) and cellular deconvolution (CD) on bulk RNA sequencing data from 5 different PTHS mouse models. Using CSEA we observed differentially expressed genes (DEGs) were enriched in parvalbumin expressing (PV+) INs and CD predicted a reduction in the PV+ INs population. Therefore, we investigated the role of TCF4 in regulating the development and function of INs in the Tcf4+/tr mouse model of PTHS. In Tcf4+/tr mice, immunohistochemical (IHC) analysis of subtype-specific IN markers and reporter mice identified reductions in PV+, vasoactive intestinal peptide (VIP+), and cortistatin (CST+) expressing INs in the cortex and cholinergic (ChAT+) INs in the striatum, with the somatostatin (SST+) IN population being spared. The reduction of these specific IN populations led to cell-type specific alterations in the balance of excitatory and inhibitory inputs onto PV+ and VIP+ INs and excitatory pyramidal neurons within the cortex. These data indicate TCF4 is a critical regulator of the development of specific subsets of INs and highlight the inhibitory network as an important source of pathophysiology in PTHS.

Methylome-wide association study of anxiety disorders.

Anxiety Disorders (ANX) such as panic disorder, generalized anxiety disorder, and phobias, are highly prevalent conditions that are moderately heritable. Evidence suggests that DNA methylation may play a role, as it is involved in critical adaptations to changing environments. Applying an enrichment-based sequencing approach covering nearly 28 million autosomal CpG sites, we conducted a methylome-wide association study (MWAS) of lifetime ANX in 1132 participants (618 cases/514 controls) from the Netherlands Study of Depression and Anxiety. Using epigenomic deconvolution, we performed MWAS for the main cell types in blood: granulocytes, T-cells, B-cells and monocytes. Cell-type specific analyses identified 280 and 82 methylome-wide significant associations (q-value < 0.1) in monocytes and granulocytes, respectively. Our top finding in monocytes was located in ZNF823 on chromosome 19 (p = 1.38 × 10-10) previously associated with schizophrenia. We observed significant overlap (p < 1 × 10-06) with the same direction of effect in monocytes (210 sites), T-cells (135 sites), and B-cells (727 sites) between this Discovery MWAS signal and a comparable replication dataset from the Great Smoky Mountains Study (N = 433). Overlapping Discovery-Replication MWAS signal was enriched for findings from published GWAS of ANX, major depression, and post-traumatic stress disorder. In monocytes, two specific sites in the FZR1 gene showed significant replication after Bonferroni correction with an additional 15 nominally replicated sites in monocytes and 4 in T-cells. FZR1 regulates neurogenesis in the hippocampus, and its knockout leads to impairments in associative fear memory and long-term potentiation in mice. In the largest and most extensive methylome-wide study of ANX, we identified replicable methylation sites located in genes of potential relevance for brain mechanisms of psychiatric conditions.