Single-nucleus transcriptomics of the prefrontal cortex in major depressive disorder implicates oligodendrocyte precursor cells and excitatory neurons

Single cell spatial biology over developmental time can decipher pediatric brain pathologies

Pediatric low grade brain tumors and neurodevelopmental disorders share proteins, signaling pathways, and networks. They also share germline mutations and an impaired prenatal differentiation origin. They may differ in the timing of the events and proliferation. We suggest that their pivotal distinct, albeit partially overlapping, outcomes relate to the cell states, which depend on their spatial location, and timing of gene expression during brain development. These attributes are crucial as the brain develops sequentially, and single-cell spatial organization influences cell state, thus function. Our underlying premise is that the root cause in neurodevelopmental disorders and pediatric tumors is impaired prenatal differentiation. Data related to pediatric brain tumors, neurodevelopmental disorders, brain cell (sub)types, locations, and timing of expression in the developing brain are scant. However, emerging single cell technologies, including transcriptomic, spatial biology, spatial high-resolution imaging performed over the brain developmental time, could be transformational in deciphering brain pathologies thereby pharmacology.

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.

iTRAQ-Based Serum Proteomic Analysis Reveals Multifactorial Cellular Function Impairment and Aggravated Systematic Inflammation in Drug-free Obsessive-Compulsive Disorders

Obsessive-compulsive disorder (OCD) is a debilitating mental disorder with obvious difficulties in treatment. Its pathogenesis has not been fully elucidated. Further understanding of etiology and mechanism needs to be explored further. We employed the isobaric tag for relative and absolute quantitation (iTRAQ)-based proteomic analysis to compare serum proteome profile between OCD patients and healthy controls, in order to find out the possible mechanism of OCD in the downstream biological process. Eighty-one drug-free OCD patients and 78 healthy controls were enrolled. A total of 475 proteins were identified. Totally, 80 proteins with p < 0.05 were selected for gene set enrichment analysis (GSEA), and only those with a fold change ≥1.2 and q value <0.2 between groups were accepted as differentially expressed proteins (DEPs). We observed a significant enrichment of immuno-inflammation-related pathways, along with intriguing expression trends that immuno-inflammation-related proteins were upregulated in GSEA. After that, 2 up-regulated proteins and 13 down-regulated ones were accepted as DEP. According to the available literature, most of the DEPs have not been reported in OCD. These DEPs were enriched in 121 gene ontology (GO) terms, including hepatocyte growth factor receptor activity, angiogenin-PRI complex, and so on. DEPs were enriched in pathways including adherens junction in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Alterations in DEPs including STXBP5L, GRN, and ANG were validated in OCD animal models. Our study suggested that OCD patients manifested multifactorial impairment in neuronal or non-neuronal cellular function under the inflammatory background. Further research employing larger sample sizes, longitudinal design, stratified analysis, and multiomics methodology will be needed. Experiments in laboratories were essential in illuminating the mechanism.

Cell-type-specific effects of autism-associated 15q duplication syndrome in the human brain

Recurrent copy-number variation represents one of the most well-established genetic drivers in neurodevelopmental disorders, including autism spectrum disorder. Duplication of 15q11-q13 (dup15q) is a well-described neurodevelopmental syndrome that increases the risk of autism more than 40-fold. However, the effects of this duplication on gene expression and chromatin accessibility in specific cell types in the human brain remain unknown. To identify the cell-type-specific transcriptional and epigenetic effects of dup15q in the human frontal cortex, we conducted single-nucleus RNA sequencing and multi-omic sequencing on dup15q-affected individuals (n = 6) as well as individuals with non-dup15q autism (n = 7) and neurotypical control individuals (n = 7). Cell-type-specific differential expression analysis identified significantly regulated genes, critical biological pathways, and differentially accessible genomic regions. Although there was overall increased gene expression across the duplicated genomic region, cellular identity represented an important factor mediating gene-expression changes. As compared to other cell types, neuronal subtypes showed greater upregulation of gene expression across a critical region within the duplication. Genes that fell within the duplicated region and had high baseline expression in control individuals showed only modest changes in dup15q, regardless of cell type. Of note, dup15q and autism had largely distinct signatures of chromatin accessibility but shared the majority of transcriptional regulatory motifs, suggesting convergent biological pathways. However, the transcriptional binding-factor motifs implicated in each condition implicated distinct biological mechanisms: neuronal JUN and FOS networks in autism vs. an inflammatory transcriptional network in dup15q microglia. This work provides a cell-type-specific analysis of how dup15q changes gene expression and chromatin accessibility in the human brain, and it finds evidence of marked cell-type-specific effects of this genetic driver. These findings have implications for guiding therapeutic development in dup15q syndrome, as well as understanding the functional effects of copy-number variants more broadly in neurodevelopmental disorders.

Single-cell multiomics analysis reveals cell/tissue-specific associations in bipolar disorder

This study investigates the cellular origin and tissue heterogeneity in bipolar disorder (BD) by integrating multiomics data. Four distinct datasets were employed, including single-cell RNA sequencing (scRNA-seq) data (embryonic and fetal brain, n = 8, 1,266 cells), BD Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) data (adult brain, n = 210), BD bulk RNA-seq data (adult brain, n = 314), and BD genome-wide association study (GWAS) summary data (n = 413,466). The integration of scRNA-seq data with multiomics data relevant to BD was accomplished using the single-cell disease relevance score (scDRS) algorithm. We have identified a novel brain cell cluster named ADCY1, which exhibits distinct genetic characteristics. From a high-resolution genetic perspective, glial cells emerge as the primary cytopathology associated with BD. Specifically, astrocytes were significantly related to BD at the RNA-seq level, while microglia showed a strong association with BD across multiple panels, including the transcriptome-wide association study (TWAS), ATAC-seq, and RNA-seq. Additionally, oligodendrocyte precursor cells displayed a significant association with BD in both ATAC-seq and RNA-seq panel. Notably, our investigation of brain regions affected by BD revealed significant associations between BD and all three types of glial cells in the dorsolateral prefrontal cortex (DLPFC). Through comprehensive analyses, we identified several BD-associated genes, including CRMP1, SYT4, UCHL1, and ZBTB18. In conclusion, our findings suggest that glial cells, particularly in specific brain regions such as the DLPFC, may play a significant role in the pathogenesis of BD. The integration of multiomics data has provided valuable insights into the etiology of BD, shedding light on potential mechanisms underlying this complex psychiatric disorder.

Cerebral hypoperfusion exacerbates vascular dysfunction after traumatic brain injury

Traumatic brain injuries are extremely common, and although most patients recover from their injuries many TBI patients suffer prolonged symptoms and remain at a higher risk for developing cardiovascular disease and neurodegeneration. Moreover, it remains challenging to identify predictors of poor long-term outcomes. Here, we tested the hypothesis that preexisting cerebrovascular impairment exacerbates metabolic and vascular dysfunction and leads to worse outcomes after TBI. Male mice underwent a mild surgical reduction in cerebral blood flow using a model of bilateral carotid artery stenosis (BCAS) wherein steel microcoils were implanted around the carotid arteries. Then, 30 days post coil implantation, mice underwent TBI or sham surgery. Gene expression profiles, cerebral blood flow, metabolic function, oxidative damage, vascular health and angiogenesis were assessed. Single nuclei RNA sequencing of endothelial cells isolated from mice after TBI showed differential gene expression profiles after TBI and BCAS, that were further altered when mice underwent both challenges. TBI but not BCAS increased mitochondrial oxidative metabolism. Both BCAS and TBI decreased cerebrovascular responses to repeated whisker stimulation. BCAS induced oxidative damage and inflammation in the vasculature as well as loss of vascular density, and reduced the numbers of angiogenic tip cells. Finally, intravascular protein accumulation was increased among mice that experienced both BCAS and TBI. Overall, our findings reveal that a prior vascular impairment significantly alters the profile of vascular health and function of the cerebrovasculature, and when combined with TBI may result in worsened outcomes.

Spatial enrichment and genomic analyses reveal the link of NOMO1 with amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a severe motor neuron disease with uncertain genetic predisposition in most sporadic cases. The spatial architecture of cell types and gene expression are the basis of cell-cell interactions, biological function and disease pathology, but are not well investigated in the human motor cortex, a key ALS-relevant brain region. Recent studies indicated single nucleus transcriptomic features of motor neuron vulnerability in ALS motor cortex. However, the brain regional vulnerability of ALS-associated genes and the genetic link between region-specific genes and ALS risk remain largely unclear. Here, we developed an entropy-weighted differential gene expression matrix-based tool (SpatialE) to identify the spatial enrichment of gene sets in spatial transcriptomics. We benchmarked SpatialE against another enrichment tool (multimodal intersection analysis) using spatial transcriptomics data from both human and mouse brain tissues. To investigate regional vulnerability, we analysed three human motor cortex and two dorsolateral prefrontal cortex tissues for spatial enrichment of ALS-associated genes. We also used Cell2location to estimate the abundance of cell types in ALS-related cortex layers. To dissect the link of regionally expressed genes and ALS risk, we performed burden analyses of rare loss-of-function variants detected by whole-genome sequencing in ALS patients and controls, then analysed differential gene expression in the TargetALS RNA-sequencing dataset. SpatialE showed more accurate and specific spatial enrichment of regional cell type markers than multimodal intersection analysis in both mouse brain and human dorsolateral prefrontal cortex. Spatial transcriptomic analyses of human motor cortex showed heterogeneous cell types and spatial gene expression profiles. We found that 260 manually curated ALS-associated genes are significantly enriched in layer 5 of the motor cortex, with abundant expression of upper motor neurons and layer 5 excitatory neurons. Burden analyses of rare loss-of-function variants in Layer 5-associated genes nominated NOMO1 as a novel ALS-associated gene in a combined sample set of 6814 ALS patients and 3324 controls (P = 0.029). Gene expression analyses in CNS tissues revealed downregulation of NOMO1 in ALS, which is consistent with a loss-of-function disease mechanism. In conclusion, our integrated spatial transcriptomics and genomic analyses identified regional brain vulnerability in ALS and the association of a layer 5 gene (NOMO1) with ALS risk.

Cerebral hypoperfusion exacerbates traumatic brain injury in male but not female mice

Mild-moderate traumatic brain injuries (TBIs) are prevalent, and while many individuals recover, there is evidence that a significant number experience long-term health impacts, including increased vulnerability to neurodegenerative diseases. These effects are influenced by other risk factors, such as cardiovascular disease. Our study tested the hypothesis that a pre-injury reduction in cerebral blood flow (CBF), mimicking cardiovascular disease, worsens TBI recovery. We induced bilateral carotid artery stenosis (BCAS) and a mild-moderate closed-head TBI in male and female mice, either alone or in combination, and analyzed CBF, spatial learning, memory, axonal damage, and gene expression. Findings showed that BCAS and TBI independently caused a ~10% decrease in CBF. Mice subjected to both BCAS and TBI experienced more significant CBF reductions, notably affecting spatial learning and memory, particularly in males. Additionally, male mice showed increased axonal damage with both BCAS and TBI compared to either condition alone. Females exhibited spatial memory deficits due to BCAS, but these were not worsened by subsequent TBI. Gene expression analysis in male mice highlighted that TBI and BCAS individually altered neuronal and glial profiles. However, the combination of BCAS and TBI resulted in markedly different transcriptional patterns. Our results suggest that mild cerebrovascular impairments, serving as a stand-in for preexisting cardiovascular conditions, can significantly worsen TBI outcomes in males. This highlights the potential for mild comorbidities to modify TBI outcomes and increase the risk of secondary diseases.

The Antidepressant Action of Fluoxetine Involves the Inhibition of Dlx5/6 in Cortical GABAergic Neurons through a TrkB-Dependent Pathway

Major depressive disorder (MDD) is a complex and devastating illness that affects people of all ages. Despite the large use of antidepressants in current medical practice, neither their mechanisms of action nor the aetiology of MDD are completely understood. Experimental evidence supports the involvement of Parvalbumin-positive GABAergic neurons (PV-neurons) in the pathogenesis of MDD. DLX5 and DLX6 (DLX5/6) encode two homeodomain transcription factors involved in cortical GABAergic differentiation and function. In the mouse, the level of expression of these genes is correlated with the cortical density of PV-neurons and with anxiety-like behaviours. The same genomic region generates the lncRNA DLX6-AS1, which, in humans, participates in the GABAergic regulatory module downregulated in schizophrenia and ASD. Here, we show that the expression levels of Dlx5/6 in the adult mouse brain are correlated with the immobility time in the forced swim test, which is used to measure depressive-like behaviours. We show that the administration of the antidepressant fluoxetine (Flx) to normal mice induces, within 24 h, a rapid and stable reduction in Dlx5, Dlx6 and Dlx6-AS1 expression in the cerebral cortex through the activation of the TrkB-CREB pathway. Experimental Dlx5 overexpression counteracts the antidepressant effects induced by Flx treatment. Our findings show that one of the short-term effects of Flx administration is the reduction in Dlx5/6 expression in GABAergic neurons, which, in turn, has direct consequences on PV expression and on behavioural profiles. Variants in the DLX5/6 regulatory network could be implicated in the predisposition to depression and in the variability of patients' response to antidepressant treatment.

Lysophosphatidic Acid (LPA) and Its Receptors in Mood Regulation: A Systematic Review of the Molecular Mechanisms and Therapeutic Potential

Mood disorders affect over 300 million individuals worldwide, often characterized by their chronic and refractory nature, posing significant threats to patient life. There has been a notable increase in mood disorders among American adolescents and young adults, with a rising number of suicide attempts and fatalities, highlighting a growing association between mood disorders and suicidal outcomes. Dysregulation within the neuroimmune-endocrine system is now recognized as one of the fundamental biological mechanisms underlying mood and mood disorders. Lysophosphatidic acid (LPA), a novel mediator of mood behavior, induces anxiety-like and depression-like phenotypes through its receptors LPA1 and LPA5, regulating synaptic neurotransmission and plasticity. Consequently, LPA has garnered substantial interest in the study of mood regulation. This study aimed to elucidate the molecular mechanisms of lysophosphatidic acid and its receptors, along with LPA receptor ligands, in mood regulation and to explore their potential therapeutic efficacy in treating mood disorders. A comprehensive literature search was conducted using the PubMed and Web of Science databases, identifying 208 articles through keyword searches up to June 2024. After excluding duplicates, irrelevant publications, and those restricted by open access limitations, 21 scientific papers were included in this review. The findings indicate that LPA/LPA receptor modulation could be beneficial in treating mood disorders, suggesting that pharmacological agents or gintonin, an extract from ginseng, may serve as effective therapeutic strategies. This study opens new avenues for future research into how lysophosphatidic acid and its receptors, as well as lysophosphatidic acid receptor ligands, influence emotional behavior in animals and humans.

A Single-Nucleus Transcriptome-Wide Association Study Implicates Novel Genes in Depression Pathogenesis

BACKGROUND

Depression, a common psychiatric illness and global public health problem, remains poorly understood across different life stages, which hampers the development of novel treatments.

METHODS

To identify new candidate genes for therapeutic development, we performed differential gene expression analysis of single-nucleus RNA sequencing data from the dorsolateral prefrontal cortex of older adults (n = 424) in relation to antemortem depressive symptoms. Additionally, we integrated genome-wide association study results for depression (n = 500,199) along with genetic tools for inferring the expression of 14,048 unique genes in 7 cell types and 52 cell subtypes to perform a transcriptome-wide association study of depression followed by Mendelian randomization.

RESULTS

Our single-nucleus transcriptome-wide association study analysis identified 68 candidate genes for depression and showed the greatest number being in excitatory and inhibitory neurons. Of the 68 genes, 53 were novel compared to previous studies. Notably, gene expression in different neuronal subtypes had varying effects on depression risk. Traits with high genetic correlations with depression, such as neuroticism, shared more transcriptome-wide association study genes than traits that were not highly correlated with depression. Complementing these analyses, differential gene expression analysis across 52 neocortical cell subtypes showed that genes such as KCNN2, SCAI, WASF3, and SOCS6 were associated with late-life depressive symptoms in specific cell subtypes.

CONCLUSIONS

These 2 sets of analyses illustrate the utility of large single-nucleus RNA sequencing data both to uncover genes whose expression is altered in specific cell subtypes in the context of depressive symptoms and to enhance the interpretation of well-powered genome-wide association studies so that we can prioritize specific susceptibility genes for further analysis and therapeutic development.

Deciphering brain cellular and behavioral mechanisms: Insights from single-cell and spatial RNA sequencing

The brain is a complex computing system composed of a multitude of interacting neurons. The computational outputs of this system determine the behavior and perception of every individual. Each brain cell expresses thousands of genes that dictate the cell's function and physiological properties. Therefore, deciphering the molecular expression of each cell is of great significance for understanding its characteristics and role in brain function. Additionally, the positional information of each cell can provide crucial insights into their involvement in local brain circuits. In this review, we briefly overview the principles of single-cell RNA sequencing and spatial transcriptomics, the potential issues and challenges in their data processing, and their applications in brain research. We further outline several promising directions in neuroscience that could be integrated with single-cell RNA sequencing, including neurodevelopment, the identification of novel brain microstructures, cognition and behavior, neuronal cell positioning, molecules and cells related to advanced brain functions, sleep-wake cycles/circadian rhythms, and computational modeling of brain function. We believe that the deep integration of these directions with single-cell and spatial RNA sequencing can contribute significantly to understanding the roles of individual cells or cell types in these specific functions, thereby making important contributions to addressing critical questions in those fields. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA in Disease and Development > RNA in Development RNA in Disease and Development > RNA in Disease.

Translating Molecular Approaches to Oligodendrocyte-Mediated Neurological Circuit Modulation

The central nervous system (CNS) exhibits remarkable adaptability throughout life, enabled by intricate interactions between neurons and glial cells, in particular, oligodendrocytes (OLs) and oligodendrocyte precursor cells (OPCs). This adaptability is pivotal for learning and memory, with OLs and OPCs playing a crucial role in neural circuit development, synaptic modulation, and myelination dynamics. Myelination by OLs not only supports axonal conduction but also undergoes adaptive modifications in response to neuronal activity, which is vital for cognitive processing and memory functions. This review discusses how these cellular interactions and myelin dynamics are implicated in various neurocircuit diseases and disorders such as epilepsy, gliomas, and psychiatric conditions, focusing on how maladaptive changes contribute to disease pathology and influence clinical outcomes. It also covers the potential for new diagnostics and therapeutic approaches, including pharmacological strategies and emerging biomarkers in oligodendrocyte functions and myelination processes. The evidence supports a fundamental role for myelin plasticity and oligodendrocyte functionality in synchronizing neural activity and high-level cognitive functions, offering promising avenues for targeted interventions in CNS disorders.

Identifying Novel Proteins for Chronic Pain: Integration of Human Brain Proteomes and Genome-wide Association Data

Numerous genome-wide association studies have identified risk genes for chronic pain, yet the mechanisms by which genetic variants modify susceptibility have remained elusive. We sought to identify key genes modulating chronic pain risk by regulating brain protein expression. We integrated brain proteomic data with the largest genome-wide dataset for multisite chronic pain (N = 387,649) in a proteome-wide association study (PWAS) using discovery and confirmatory proteomic datasets (N = 376 and 152) from the dorsolateral prefrontal cortex. Leveraging summary data-based Mendelian randomization and Bayesian colocalization analysis, we pinpointed potential causal genes, while a transcriptome-wide association study integrating 452 human brain transcriptomes investigated whether cis-effects on protein abundance extended to the transcriptome. Single-cell RNA-sequencing data and single-nucleus transcriptomic data revealed cell-type-specific expression patterns for identified causal genes in the dorsolateral prefrontal cortex and dorsal root ganglia (DRG), complemented by RNA microarray analysis of expression profiles in other pain-related brain regions. Of the 22 genes cis-regulating protein abundance identified by the discovery PWAS, 18 (82%) were deemed causal by summary data-based Mendelian randomization or Bayesian colocalization analysis analyses, with 7 of these 18 genes (39%) replicating in the confirmatory PWAS, including guanosine diphosphate-mannose pyrophosphorylase B, which also associated at the transcriptome level. Several causal genes exhibited selective expression in excitatory and inhibitory neurons, oligodendrocytes, and astrocytes, while most identified genes were expressed across additional pain-related brain regions. This integrative proteogenomic approach identified 18 high-confidence causal genes for chronic pain, regulated by cis-effects on brain protein levels, suggesting promising avenues for treatment research and indicating a contributory role for the DRG. PERSPECTIVE: The current post genome-wide association study analyses identified 18 high-confidence causal genes regulating chronic pain risk via cis-modulation of brain protein abundance, suggesting promising avenues for future chronic pain therapies. Additionally, the significant expression of these genes in the DRG indicated a potential contributory role, warranting further investigation.

scRank infers drug-responsive cell types from untreated scRNA-seq data using a target-perturbed gene regulatory network

Cells respond divergently to drugs due to the heterogeneity among cell populations. Thus, it is crucial to identify drug-responsive cell populations in order to accurately elucidate the mechanism of drug action, which is still a great challenge. Here, we address this problem with scRank, which employs a target-perturbed gene regulatory network to rank drug-responsive cell populations via in silico drug perturbations using untreated single-cell transcriptomic data. We benchmark scRank on simulated and real datasets, which shows the superior performance of scRank over existing methods. When applied to medulloblastoma and major depressive disorder datasets, scRank identifies drug-responsive cell types that are consistent with the literature. Moreover, scRank accurately uncovers the macrophage subpopulation responsive to tanshinone IIA and its potential targets in myocardial infarction, with experimental validation. In conclusion, scRank enables the inference of drug-responsive cell types using untreated single-cell data, thus providing insights into the cellular-level impacts of therapeutic interventions.

Omics approaches open new horizons in major depressive disorder: from biomarkers to precision medicine

Major depressive disorder (MDD) is a recurrent episodic mood disorder that represents the third leading cause of disability worldwide. In MDD, several factors can simultaneously contribute to its development, which complicates its diagnosis. According to practical guidelines, antidepressants are the first-line treatment for moderate to severe major depressive episodes. Traditional treatment strategies often follow a one-size-fits-all approach, resulting in suboptimal outcomes for many patients who fail to experience a response or recovery and develop the so-called "therapy-resistant depression". The high biological and clinical inter-variability within patients and the lack of robust biomarkers hinder the finding of specific therapeutic targets, contributing to the high treatment failure rates. In this frame, precision medicine, a paradigm that tailors medical interventions to individual characteristics, would help allocate the most adequate and effective treatment for each patient while minimizing its side effects. In particular, multi-omic studies may unveil the intricate interplays between genetic predispositions and exposure to environmental factors through the study of epigenomics, transcriptomics, proteomics, metabolomics, gut microbiomics, and immunomics. The integration of the flow of multi-omic information into molecular pathways may produce better outcomes than the current psychopharmacological approach, which targets singular molecular factors mainly related to the monoamine systems, disregarding the complex network of our organism. The concept of system biomedicine involves the integration and analysis of enormous datasets generated with different technologies, creating a "patient fingerprint", which defines the underlying biological mechanisms of every patient. This review, centered on precision medicine, explores the integration of multi-omic approaches as clinical tools for prediction in MDD at a single-patient level. It investigates how combining the existing technologies used for diagnostic, stratification, prognostic, and treatment-response biomarkers discovery with artificial intelligence can improve the assessment and treatment of MDD.

Single-cell RNA-seq reveals the role of YAP1 in prefrontal cortex microglia in depression

BACKGROUND

Depression is a complex mood disorder whose pathogenesis involves multiple cell types and molecular pathways. The prefrontal cortex, as a key brain region for emotional regulation, plays a crucial role in depression. Microglia, as immune cells of the central nervous system, have been closely linked to the development and progression of depression through their dysfunctional states. This study aims to utilize single-cell RNA-seq technology to reveal the pathogenic mechanism of YAP1 in prefrontal cortex microglia in depression.

METHODS

Firstly, we performed cell type identification and differential analysis on normal and depressed prefrontal cortex tissues by mining single-cell RNA-seq datasets from public databases. Focusing on microglia, we conducted sub-clustering, differential gene KEGG enrichment analysis, intercellular interaction analysis, and pseudotime analysis. Additionally, a cross-species analysis was performed to explore the similarities and differences between human and rhesus monkey prefrontal cortex microglia. To validate our findings, we combined bulk RNA-Seq and WGCNA analysis to reveal key genes associated with depression and verified the relationship between YAP1 and depression using clinical samples.

RESULTS

Our study found significant changes in the proportion and transcriptional profiles of microglia in depressed prefrontal cortex tissues. Further analysis revealed multiple subpopulations of microglia and their associated differential genes and signaling pathways related to depression. YAP1 was identified as a key molecule contributing to the development of depression and was significantly elevated in depression patients. Moreover, the expression level of YAP1 was positively correlated with HAMD scores, suggesting its potential as a biomarker for predicting the onset of depression.

CONCLUSION

This study utilized single-cell RNA-seq technology to reveal the pathogenic mechanism of YAP1 in prefrontal cortex microglia in depression, providing a new perspective for a deeper understanding of the pathophysiology of depression and identifying potential targets for developing novel treatment strategies.

Decoding frontotemporal and cell-type-specific vulnerabilities to neuropsychiatric disorders and psychoactive drugs

Frontotemporal lobe abnormalities are linked to neuropsychiatric disorders and cognition, but the role of cellular heterogeneity between temporal lobe (TL) and frontal lobe (FL) in the vulnerability to genetic risk factors remains to be elucidated. We integrated single-nucleus transcriptome analysis in 'fresh' human FL and TL with genetic susceptibility, gene dysregulation in neuropsychiatric disease and psychoactive drug response data. We show how intrinsic differences between TL and FL contribute to the vulnerability of specific cell types to both genetic risk factors and psychoactive drugs. Neuronal populations, specifically PVALB neurons, were most highly vulnerable to genetic risk factors for psychiatric disease. These psychiatric disease-associated genes were mostly upregulated in the TL, and dysregulated in the brain of patients with obsessive-compulsive disorder, bipolar disorder and schizophrenia. Among these genes, GRIN2A and SLC12A5, implicated in schizophrenia and bipolar disorder, were significantly upregulated in TL PVALB neurons and in psychiatric disease patients' brain. PVALB neurons from the TL were twofold more vulnerable to psychoactive drugs than to genetic risk factors, showing the influence and specificity of frontotemporal lobe differences on cell vulnerabilities. These studies provide a cell type resolved map of the impact of brain regional differences on cell type vulnerabilities in neuropsychiatric disorders.

Omics Approaches to Investigate the Pathogenesis of Suicide

Suicide is the second leading cause of death in U.S. adolescents and young adults and is generally associated with a psychiatric disorder. Suicidal behavior has a complex etiology and pathogenesis. Moderate heritability suggests genetic causes. Associations between childhood and recent life adversity indicate contributions from epigenetic factors. Genomic contributions to suicide pathogenesis remain largely unknown. This article is based on a workshop held to design strategies to identify molecular drivers of suicide neurobiology that would be putative new treatment targets. The panel determined that while bulk tissue studies provide comprehensive information, single-nucleus approaches that identify cell type-specific changes are needed. While single-nuclei techniques lack information on cytoplasm, processes, spines, and synapses, spatial multiomic technologies on intact tissue detect cell alterations specific to brain tissue layers and subregions. Because suicide has genetic and environmental drivers, multiomic approaches that combine cell type-specific epigenome, transcriptome, and proteome provide a more complete picture of pathogenesis. To determine the direction of effect of suicide risk gene variants on RNA and protein expression and how these interact with epigenetic marks, single-nuclei and spatial multiomics quantitative trait loci maps should be integrated with whole-genome sequencing and genome-wide association databases. The workshop concluded with a recommendation for the formation of an international suicide biology consortium that will bring together brain banks and investigators with expertise in cutting-edge omics technologies to delineate the biology of suicide and identify novel potential treatment targets to be tested in cellular and animal models for drug and biomarker discovery to guide suicide prevention.

Repurposing Ketamine in the Therapy of Depression and Depression-Related Disorders: Recent Advances and Future Potential

Depression represents a prevalent and enduring mental disorder of significant concern within the clinical domain. Extensive research indicates that depression is very complex, with many interconnected pathways involved. Most research related to depression focuses on monoamines, neurotrophic factors, the hypothalamic-pituitary-adrenal axis, tryptophan metabolism, energy metabolism, mitochondrial function, the gut-brain axis, glial cell-mediated inflammation, myelination, homeostasis, and brain neural networks. However, recently, Ketamine, an ionotropic N-methyl-D-aspartate (NMDA) receptor antagonist, has been discovered to have rapid antidepressant effects in patients, leading to novel and successful treatment approaches for mood disorders. This review aims to summarize the latest findings and insights into various signaling pathways and systems observed in depression patients and animal models, providing a more comprehensive view of the neurobiology of anxious-depressive-like behavior. Specifically, it highlights the key mechanisms of ketamine as a rapid-acting antidepressant, aiming to enhance the treatment of neuropsychiatric disorders. Moreover, we discuss the potential of ketamine as a prophylactic or therapeutic intervention for stress-related psychiatric disorders.

SpatialPrompt: spatially aware scalable and accurate tool for spot deconvolution and domain identification in spatial transcriptomics

Efficiently mapping of cell types in situ remains a major challenge in spatial transcriptomics. Most spot deconvolution tools ignore spatial coordinate information and perform extremely slow on large datasets. Here, we introduce SpatialPrompt, a spatially aware and scalable tool for spot deconvolution and domain identification. SpatialPrompt integrates gene expression, spatial location, and single-cell RNA sequencing (scRNA-seq) dataset as reference to accurately infer cell-type proportions of spatial spots. SpatialPrompt uses non-negative ridge regression and graph neural network to efficiently capture local microenvironment information. Our extensive benchmarking analysis on Visium, Slide-seq, and MERFISH datasets demonstrated superior performance of SpatialPrompt over 15 existing tools. On mouse hippocampus dataset, SpatialPrompt achieves spot deconvolution and domain identification within 2 minutes for 50,000 spots. Overall, domain identification using SpatialPrompt was 44 to 150 times faster than existing methods. We build a database housing 40 plus curated scRNA-seq datasets for seamless integration with SpatialPrompt for spot deconvolution.

Glial Markers of Suicidal Behavior in the Human Brain-A Systematic Review of Postmortem Studies

Suicide is a major public health priority, and its molecular mechanisms appear to be related to glial abnormalities and specific transcriptional changes. This study aimed to identify and synthesize evidence of the relationship between glial dysfunction and suicidal behavior to understand the neurobiology of suicide. As of 26 January 2024, 46 articles that met the inclusion criteria were identified by searching PubMed and ISI Web of Science. Most postmortem studies, including 30 brain regions, have determined no density or number of total Nissl-glial cell changes in suicidal patients with major psychiatric disorders. There were 17 astrocytic, 14 microglial, and 9 oligodendroglial studies using specific markers of each glial cell and further on their specific gene expression. Those studies suggest that astrocytic and oligodendroglial cells lost but activated microglia in suicides with affective disorder, bipolar disorders, major depression disorders, or schizophrenia in comparison with non-suicided patients and non-psychiatric controls. Although the data from previous studies remain complex and cannot fully explain the effects of glial cell dysfunction related to suicidal behaviors, they provide risk directions potentially leading to suicide prevention.

Single-cell multi-cohort dissection of the schizophrenia transcriptome

The complexity and heterogeneity of schizophrenia have hindered mechanistic elucidation and the development of more effective therapies. Here, we performed single-cell dissection of schizophrenia-associated transcriptomic changes in the human prefrontal cortex across 140 individuals in two independent cohorts. Excitatory neurons were the most affected cell group, with transcriptional changes converging on neurodevelopment and synapse-related molecular pathways. Transcriptional alterations included known genetic risk factors, suggesting convergence of rare and common genomic variants on neuronal population-specific alterations in schizophrenia. Based on the magnitude of schizophrenia-associated transcriptional change, we identified two populations of individuals with schizophrenia marked by expression of specific excitatory and inhibitory neuronal cell states. This single-cell atlas links transcriptomic changes to etiological genetic risk factors, contextualizing established knowledge within the human cortical cytoarchitecture and facilitating mechanistic understanding of schizophrenia pathophysiology and heterogeneity.

Systems biology dissection of PTSD and MDD across brain regions, cell types, and blood

The molecular pathology of stress-related disorders remains elusive. Our brain multiregion, multiomic study of posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) included the central nucleus of the amygdala, hippocampal dentate gyrus, and medial prefrontal cortex (mPFC). Genes and exons within the mPFC carried most disease signals replicated across two independent cohorts. Pathways pointed to immune function, neuronal and synaptic regulation, and stress hormones. Multiomic factor and gene network analyses provided the underlying genomic structure. Single nucleus RNA sequencing in dorsolateral PFC revealed dysregulated (stress-related) signals in neuronal and non-neuronal cell types. Analyses of brain-blood intersections in >50,000 UK Biobank participants were conducted along with fine-mapping of the results of PTSD and MDD genome-wide association studies to distinguish risk from disease processes. Our data suggest shared and distinct molecular pathology in both disorders and propose potential therapeutic targets and biomarkers.

A data-driven single-cell and spatial transcriptomic map of the human prefrontal cortex

The molecular organization of the human neocortex historically has been studied in the context of its histological layers. However, emerging spatial transcriptomic technologies have enabled unbiased identification of transcriptionally defined spatial domains that move beyond classic cytoarchitecture. We used the Visium spatial gene expression platform to generate a data-driven molecular neuroanatomical atlas across the anterior-posterior axis of the human dorsolateral prefrontal cortex. Integration with paired single-nucleus RNA-sequencing data revealed distinct cell type compositions and cell-cell interactions across spatial domains. Using PsychENCODE and publicly available data, we mapped the enrichment of cell types and genes associated with neuropsychiatric disorders to discrete spatial domains.

Genetic regulation of cell type-specific chromatin accessibility shapes brain disease etiology

Nucleotide variants in cell type-specific gene regulatory elements in the human brain are risk factors for human disease. We measured chromatin accessibility in 1932 aliquots of sorted neurons and non-neurons from 616 human postmortem brains and identified 34,539 open chromatin regions with chromatin accessibility quantitative trait loci (caQTLs). Only 10.4% of caQTLs are shared between neurons and non-neurons, which supports cell type-specific genetic regulation of the brain regulome. Incorporating allele-specific chromatin accessibility improves statistical fine-mapping and refines molecular mechanisms that underlie disease risk. Using massively parallel reporter assays in induced excitatory neurons, we screened 19,893 brain QTLs and identified the functional impact of 476 regulatory variants. Combined, this comprehensive resource captures variation in the human brain regulome and provides insights into disease etiology.

Cell-type-specific effects of autism-associated chromosome 15q11.2-13.1 duplications in human brain

Recurrent copy number variation represents one of the most well-established genetic drivers in neurodevelopmental disorders, including autism spectrum disorder (ASD). Duplication of 15q11.2-13.1 (dup15q) is a well-described neurodevelopmental syndrome that increases the risk of ASD by over 40-fold. However, the effects of this duplication on gene expression and chromatin accessibility in specific cell types in the human brain remain unknown. To identify the cell-type-specific transcriptional and epigenetic effects of dup15q in the human frontal cortex we conducted single-nucleus RNA-sequencing and multi-omic sequencing on dup15q cases (n=6) as well as non-dup15q ASD (n=7) and neurotypical controls (n=7). Cell-type-specific differential expression analysis identified significantly regulated genes, critical biological pathways, and differentially accessible genomic regions. Although there was overall increased gene expression across the duplicated genomic region, cellular identity represented an important factor mediating gene expression changes. Neuronal subtypes, showed greater upregulation of gene expression across a critical region within the duplication as compared to other cell types. Genes within the duplicated region that had high baseline expression in control individuals showed only modest changes in dup15q, regardless of cell type. Of note, dup15q and ASD had largely distinct signatures of chromatin accessibility, but shared the majority of transcriptional regulatory motifs, suggesting convergent biological pathways. However, the transcriptional binding factor motifs implicated in each condition implicated distinct biological mechanisms; neuronal JUN/FOS networks in ASD vs. an inflammatory transcriptional network in dup15q microglia. This work provides a cell-type-specific analysis of how dup15q changes gene expression and chromatin accessibility in the human brain and finds evidence of marked cell-type-specific effects of this genetic driver. These findings have implications for guiding therapeutic development in dup15q syndrome, as well as understanding the functional effects CNVs more broadly in neurodevelopmental disorders.

ITPR2 Mediated Calcium Homeostasis in Oligodendrocytes is Essential for Myelination and Involved in Depressive-Like Behavior in Adolescent Mice

Ca2+ signaling is essential for oligodendrocyte (OL) development and myelin formation. Inositol 1,4,5-trisphosphate receptor type 2 (ITPR2) is an endoplasmic reticulum calcium channel and shows stage-dependent high levels in postmitotic oligodendrocyte precursor cells (OPCs). The role and potential mechanism of ITPR2 in OLs remain unclear. In this study, it is revealed that loss of Itpr2 in OLs disturbs Ca2+ homeostasis and inhibits myelination in adolescent mice. Animals with OL-specific deletion of Itpr2 exhibit anxiety/depressive-like behaviors and manifest with interrupted OPC proliferation, leading to fewer mature OLs in the brain. Detailed transcriptome profiling and signal pathway analysis suggest that MAPK/ERK-CDK6/cyclin D1 axis underlies the interfered cell cycle progression in Itpr2 ablated OPCs. Besides, blocking MAPK/ERK pathway significantly improves the delayed OPC differentiation and myelination in Itpr2 mutant. Notably, the resting [Ca2+]i is increased in Itpr2 ablated OPCs, with the elevation of several plasma calcium channels. Antagonists against these plasma calcium channels can normalize the resting [Ca2+]i level and enhance lineage progression in Itpr2-ablated OPCs. Together, the findings reveal novel insights for calcium homeostasis in manipulating developmental transition from OPCs to pre-OLs; additionally, the involvement of OLs-originated ITPR2 in depressive behaviors provides new therapeutic strategies to alleviate myelin-associated psychiatric disorders.

Characterizing cell type specific transcriptional differences between the living and postmortem human brain

Single-nucleus RNA sequencing (snRNA-seq) is often used to define gene expression patterns characteristic of brain cell types as well as to identify cell type specific gene expression signatures of neurological and mental illnesses in postmortem human brains. As methods to obtain brain tissue from living individuals emerge, it is essential to characterize gene expression differences associated with tissue originating from either living or postmortem subjects using snRNA-seq, and to assess whether and how such differences may impact snRNA-seq studies of brain tissue. To address this, human prefrontal cortex single nuclei gene expression was generated and compared between 31 samples from living individuals and 21 postmortem samples. The same cell types were consistently identified in living and postmortem nuclei, though for each cell type, a large proportion of genes were differentially expressed between samples from postmortem and living individuals. Notably, estimation of cell type proportions by cell type deconvolution of pseudo-bulk data was found to be more accurate in samples from living individuals. To allow for future integration of living and postmortem brain gene expression, a model was developed that quantifies from gene expression data the probability a human brain tissue sample was obtained postmortem. These probabilities are established as a means to statistically account for the gene expression differences between samples from living and postmortem individuals. Together, the results presented here provide a deep characterization of both differences between snRNA-seq derived from samples from living and postmortem individuals, as well as qualify and account for their effect on common analyses performed on this type of data.

Antipsychotic-induced epigenomic reorganization in frontal cortex of individuals with schizophrenia

Genome-wide association studies have revealed >270 loci associated with schizophrenia risk, yet these genetic factors do not seem to be sufficient to fully explain the molecular determinants behind this psychiatric condition. Epigenetic marks such as post-translational histone modifications remain largely plastic during development and adulthood, allowing a dynamic impact of environmental factors, including antipsychotic medications, on access to genes and regulatory elements. However, few studies so far have profiled cell-specific genome-wide histone modifications in postmortem brain samples from schizophrenia subjects, or the effect of antipsychotic treatment on such epigenetic marks. Here, we conducted ChIP-seq analyses focusing on histone marks indicative of active enhancers (H3K27ac) and active promoters (H3K4me3), alongside RNA-seq, using frontal cortex samples from antipsychotic-free (AF) and antipsychotic-treated (AT) individuals with schizophrenia, as well as individually matched controls (n=58). Schizophrenia subjects exhibited thousands of neuronal and non-neuronal epigenetic differences at regions that included several susceptibility genetic loci, such as NRG1, DISC1, and DRD3. By analyzing the AF and AT cohorts separately, we identified schizophrenia-associated alterations in specific transcription factors, their regulatees, and epigenomic and transcriptomic features that were reversed by antipsychotic treatment; as well as those that represented a consequence of antipsychotic medication rather than a hallmark of schizophrenia in postmortem human brain samples. Notably, we also found that the effect of age on epigenomic landscapes was more pronounced in frontal cortex of AT-schizophrenics, as compared to AF-schizophrenics and controls. Together, these data provide important evidence of epigenetic alterations in the frontal cortex of individuals with schizophrenia, and remark for the first time on the impact of age and antipsychotic treatment on chromatin organization.

Precision and Accuracy of Single-Cell/Nuclei RNA Sequencing Data

Single-cell/nuclei RNA sequencing (sc/snRNA-Seq) is widely used for profiling cell-type gene expressions in biomedical research. An important but underappreciated issue is the quality of sc/snRNA-Seq data that would impact the reliability of downstream analyses. Here we evaluated the precision and accuracy in 18 sc/snRNA-Seq datasets. The precision was assessed on data from human brain studies with a total of 3,483,905 cells from 297 individuals, by utilizing technical replicates. The accuracy was evaluated with sample-matched scRNA-Seq and pooled-cell RNA-Seq data of cultured mononuclear phagocytes from four species. The results revealed low precision and accuracy at the single-cell level across all evaluated data. Cell number and RNA quality were highlighted as two key factors determining the expression precision, accuracy, and reproducibility of differential expression analysis in sc/snRNA-Seq. This study underscores the necessity of sequencing enough high-quality cells per cell type per individual, preferably in the hundreds, to mitigate noise in expression quantification.

Contrasting somatic mutation patterns in aging human neurons and oligodendrocytes

Characterizing somatic mutations in the brain is important for disentangling the complex mechanisms of aging, yet little is known about mutational patterns in different brain cell types. Here, we performed whole-genome sequencing (WGS) of 86 single oligodendrocytes, 20 mixed glia, and 56 single neurons from neurotypical individuals spanning 0.4-104 years of age and identified >92,000 somatic single-nucleotide variants (sSNVs) and small insertions/deletions (indels). Although both cell types accumulate somatic mutations linearly with age, oligodendrocytes accumulated sSNVs 81% faster than neurons and indels 28% slower than neurons. Correlation of mutations with single-nucleus RNA profiles and chromatin accessibility from the same brains revealed that oligodendrocyte mutations are enriched in inactive genomic regions and are distributed across the genome similarly to mutations in brain cancers. In contrast, neuronal mutations are enriched in open, transcriptionally active chromatin. These stark differences suggest an assortment of active mutagenic processes in oligodendrocytes and neurons.

Neuronal cell cycle reentry events in the aging brain are more prevalent in neurodegeneration and lead to cellular senescence

Increasing evidence indicates that terminally differentiated neurons in the brain may recommit to a cell cycle-like process during neuronal aging and under disease conditions. Because of the rare existence and random localization of these cells in the brain, their molecular profiles and disease-specific heterogeneities remain unclear. Through a bioinformatics approach that allows integrated analyses of multiple single-nucleus transcriptome datasets from human brain samples, these rare cell populations were identified and selected for further characterization. Our analyses indicated that these cell cycle-related events occur predominantly in excitatory neurons and that cellular senescence is likely their immediate terminal fate. Quantitatively, the number of cell cycle re-engaging and senescent neurons decreased during the normal brain aging process, but in the context of late-onset Alzheimer's disease (AD), these cells accumulate instead. Transcriptomic profiling of these cells suggested that disease-specific differences were predominantly tied to the early stage of the senescence process, revealing that these cells presented more proinflammatory, metabolically deregulated, and pathology-associated signatures in disease-affected brains. Similarly, these general features of cell cycle re-engaging neurons were also observed in a subpopulation of dopaminergic neurons identified in the Parkinson's disease (PD)-Lewy body dementia (LBD) model. An extended analysis conducted in a mouse model of brain aging further validated the ability of this bioinformatics approach to determine the robust relationship between the cell cycle and senescence processes in neurons in this cross-species setting.

Altered intersubject functional variability of brain white-matter in major depressive disorder and its association with gene expression profiles

Major depressive disorder (MDD) is a clinically heterogeneous disorder. Its mechanism is still unknown. Although the altered intersubject variability in functional connectivity (IVFC) within gray-matter has been reported in MDD, the alterations to IVFC within white-matter (WM-IVFC) remain unknown. Based on the resting-state functional MRI data of discovery (145 MDD patients and 119 healthy controls [HCs]) and validation cohorts (54 MDD patients, and 78 HCs), we compared the WM-IVFC between the two groups. We further assessed the meta-analytic cognitive functions related to the alterations. The discriminant WM-IVFC values were used to classify MDD patients and predict clinical symptoms in patients. In combination with the Allen Human Brain Atlas, transcriptome-neuroimaging association analyses were further conducted to investigate gene expression profiles associated with WM-IVFC alterations in MDD, followed by a set of gene functional characteristic analyses. We found extensive WM-IVFC alterations in MDD compared to HCs, which were associated with multiple behavioral domains, including sensorimotor processes and higher-order functions. The discriminant WM-IVFC could not only effectively distinguish MDD patients from HCs with an area under curve ranging from 0.889 to 0.901 across three classifiers, but significantly predict depression severity (r = 0.575, p = 0.002) and suicide risk (r = 0.384, p = 0.040) in patients. Furthermore, the variability-related genes were enriched for synapse, neuronal system, and ion channel, and predominantly expressed in excitatory and inhibitory neurons. Our results obtained good reproducibility in the validation cohort. These findings revealed intersubject functional variability changes of brain WM in MDD and its linkage with gene expression profiles, providing potential implications for understanding the high clinical heterogeneity of MDD.

Recent advances in differential expression analysis for single-cell RNA-seq and spatially resolved transcriptomic studies

Differential expression (DE) analysis is a necessary step in the analysis of single-cell RNA sequencing (scRNA-seq) and spatially resolved transcriptomics (SRT) data. Unlike traditional bulk RNA-seq, DE analysis for scRNA-seq or SRT data has unique characteristics that may contribute to the difficulty of detecting DE genes. However, the plethora of DE tools that work with various assumptions makes it difficult to choose an appropriate one. Furthermore, a comprehensive review on detecting DE genes for scRNA-seq data or SRT data from multi-condition, multi-sample experimental designs is lacking. To bridge such a gap, here, we first focus on the challenges of DE detection, then highlight potential opportunities that facilitate further progress in scRNA-seq or SRT analysis, and finally provide insights and guidance in selecting appropriate DE tools or developing new computational DE methods.

Single-cell RNA-sequencing of cellular heterogeneity and pathogenic mechanisms in paraquat-induced Parkinson's disease with depression

Parkinson's disease (PD) is among the most prevalent neurodegenerative diseases, and approximately one third of patients with PD are estimated to have depression. Paraquat (PQ) exposure is an important environmental risk factor for PD. In this study, we established a mouse model of PQ-induced PD with depression to comprehensively investigate cellular heterogeneity and the mechanisms underlying the progression of depression in the context of PD. We utilized single-cell RNA-seq (scRNA-seq) to acquire the transcriptomic atlas of individual cells from model mice and characterize the gene expression profiles in each differentially expressed cell type. We identified a specific glutamatergic neuron cluster responsible for the development of heterogeneous depression-associated changes and established a comprehensive gene expression atlas. Furthermore, functional enrichment and cell trajectory analyses revealed that the mechanisms underlying the progression of PD with depression were associated with specific glutamatergic neurons. Together, our findings provide a valuable resource for deciphering the cellular heterogeneity of PD with depression. The suggested connection between intrinsic transcriptional states of neurons and the progression of depression can provide insight into potential biomarkers and specific targets for anti-depression treatment in patients with PD. SYNOPSIS: Our results obtained using model mice confirm the core effects of PQ exposure on glutamatergic neurons and their potential role in the development of PD with depression.

Drug targeting in psychiatric disorders - how to overcome the loss in translation?

In spite of major efforts and investment in development of psychiatric drugs, many clinical trials have failed in recent decades, and clinicians still prescribe drugs that were discovered many years ago. Although multiple reasons have been discussed for the drug development deadlock, we focus here on one of the major possible biological reasons: differences between the characteristics of drug targets in preclinical models and the corresponding targets in patients. Importantly, based on technological advances in single-cell analysis, we propose here a framework for the use of available and newly emerging knowledge from single-cell and spatial omics studies to evaluate and potentially improve the translational predictivity of preclinical models before commencing preclinical and, in particular, clinical studies. We believe that these recommendations will improve preclinical models and the ability to assess drugs in clinical trials, reducing failure rates in expensive late-stage trials and ultimately benefitting psychiatric drug discovery and development.

Single-Nucleus RNA-Seq Characterizes the Cell Types Along the Neuronal Lineage in the Adult Human Subependymal Zone and Reveals Reduced Oligodendrocyte Progenitor Abundance with Age

The subependymal zone (SEZ), also known as the subventricular zone (SVZ), constitutes a neurogenic niche that persists during postnatal life. In humans, the neurogenic potential of the SEZ declines after the first year of life. However, studies discovering markers of stem and progenitor cells highlight the neurogenic capacity of progenitors in the adult human SEZ, with increased neurogenic activity occurring under pathological conditions. In the present study, the complete cellular niche of the adult human SEZ was characterized by single-nucleus RNA sequencing, and compared between four youth (age 16-22) and four middle-aged adults (age 44-53). We identified 11 cellular clusters including clusters expressing marker genes for neural stem cells (NSCs), neuroblasts, immature neurons, and oligodendrocyte progenitor cells. The relative abundance of NSC and neuroblast clusters did not differ between the two age groups, indicating that the pool of SEZ NSCs does not decline in this age range. The relative abundance of oligodendrocyte progenitors and microglia decreased in middle-age, indicating that the cellular composition of human SEZ is remodeled between youth and adulthood. The expression of genes related to nervous system development was higher across different cell types, including NSCs, in youth as compared with middle-age. These transcriptional changes suggest ongoing central nervous system plasticity in the SEZ in youth, which declined in middle-age.

An integrative view on the cell-type-specific mechanisms of ketamine's antidepressant actions

Over the past six decades, the use of ketamine has evolved from an anesthetic and recreational drug to the first non-monoaminergic antidepressant approved for treatment-resistant major depressive disorder (MDD). Subanesthetic doses of ketamine and its enantiomer (S)-ketamine (esketamine) directly bind to several neurotransmitter receptors [including N-methyl-d-aspartic acid receptor (NMDAR), κ and μ opioid receptor (KOR and MOR)] widely distributed in the brain and across different cell types, implicating several potential molecular mechanisms underlying the action of ketamine as an antidepressant. This review examines preclinical studies investigating cell-type-specific mechanisms underlying the effects of ketamine on behavior and synapses. Cell-type-specific approaches are crucial for disentangling the critical mechanisms involved in the therapeutic effect of ketamine.

Temporal changes of gene expression in health, schizophrenia, bipolar disorder, and major depressive disorder

The molecular events underlying the development, manifestation, and course of schizophrenia, bipolar disorder, and major depressive disorder span from embryonic life to advanced age. However, little is known about the early dynamics of gene expression in these disorders due to their relatively late manifestation. To address this, we conducted a secondary analysis of post-mortem prefrontal cortex datasets using bioinformatics and machine learning techniques to identify differentially expressed gene modules associated with aging and the diseases, determine their time-perturbation points, and assess enrichment with expression quantitative trait loci (eQTL) genes. Our findings revealed early, mid, and late deregulation of expression of functional gene modules involved in neurodevelopment, plasticity, homeostasis, and immune response. This supports the hypothesis that multiple hits throughout life contribute to disease manifestation rather than a single early-life event. Moreover, the time-perturbed functional gene modules were associated with genetic loci affecting gene expression, highlighting the role of genetic factors in gene expression dynamics and the development of disease phenotypes. Our findings emphasize the importance of investigating time-dependent perturbations in gene expression before the age of onset in elucidating the molecular mechanisms of psychiatric disorders.

Major depressive disorder: hypothesis, mechanism, prevention and treatment

Worldwide, the incidence of major depressive disorder (MDD) is increasing annually, resulting in greater economic and social burdens. Moreover, the pathological mechanisms of MDD and the mechanisms underlying the effects of pharmacological treatments for MDD are complex and unclear, and additional diagnostic and therapeutic strategies for MDD still are needed. The currently widely accepted theories of MDD pathogenesis include the neurotransmitter and receptor hypothesis, hypothalamic-pituitary-adrenal (HPA) axis hypothesis, cytokine hypothesis, neuroplasticity hypothesis and systemic influence hypothesis, but these hypothesis cannot completely explain the pathological mechanism of MDD. Even it is still hard to adopt only one hypothesis to completely reveal the pathogenesis of MDD, thus in recent years, great progress has been made in elucidating the roles of multiple organ interactions in the pathogenesis MDD and identifying novel therapeutic approaches and multitarget modulatory strategies, further revealing the disease features of MDD. Furthermore, some newly discovered potential pharmacological targets and newly studied antidepressants have attracted widespread attention, some reagents have even been approved for clinical treatment and some novel therapeutic methods such as phototherapy and acupuncture have been discovered to have effective improvement for the depressive symptoms. In this work, we comprehensively summarize the latest research on the pathogenesis and diagnosis of MDD, preventive approaches and therapeutic medicines, as well as the related clinical trials.

Structural and biochemical alterations in dendritic spines as key mechanisms for severe mental illnesses

Severe mental illnesses (SMI) collectively affect approximately 20% of the global population, as estimated by the World Health Organization (WHO). Despite having diverse etiologies, clinical symptoms, and pharmacotherapies, these diseases share a common pathophysiological characteristic: the misconnection of brain areas involved in reality perception, executive control, and cognition, including the corticolimbic system. Dendritic spines play a crucial role in excitatory neurotransmission within the central nervous system. These small structures exhibit remarkable plasticity, regulated by factors such as neurotransmitter tone, neurotrophic factors, and innate immunity-related molecules, and other mechanisms - all of which are associated with the pathophysiology of SMI. However, studying dendritic spine mechanisms in both healthy and pathological conditions in patients is fraught with technical limitations. This is where animal models related to these diseases become indispensable. They have played a pivotal role in elucidating the significance of dendritic spines in SMI. In this review, the information regarding the potential role of dendritic spines in SMI was summarized, drawing from clinical and animal model reports. Also, the implications of targeting dendritic spine-related molecules for SMI treatment were explored. Specifically, our focus is on major depressive disorder and the neurodevelopmental disorders schizophrenia and autism spectrum disorder. Abundant clinical and basic research has studied the functional and structural plasticity of dendritic spines in these diseases, along with potential pharmacological targets that modulate the dynamics of these structures. These targets may be associated with the clinical efficacy of the pharmacotherapy.

Single-nucleus transcriptomic analysis reveals the relationship between gene expression in oligodendrocyte lineage and major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is a common mental illness that affects millions of people worldwide and imposes a heavy burden on individuals, families and society. Previous studies on MDD predominantly focused on neurons and employed bulk homogenates of brain tissues. This paper aims to decipher the relationship between oligodendrocyte lineage (OL) development and MDD at the single-cell resolution level.

METHODS

Here, we present the use of a guided regularized random forest (GRRF) algorithm to explore single-nucleus RNA sequencing profiles (GSE144136) of the OL at four developmental stages, which contains dorsolateral prefrontal cortex of 17 healthy controls (HC) and 17 MDD cases, generated by Nagy C et al. We prioritized and ordered differentially expressed genes (DEGs) based on Nagy et al., which could predominantly discriminate cells in the four developmental stages and two adjacent developmental stages of the OL. We further screened top-ranked genes that distinguished between HC and MDD in four developmental stages. Moreover, we estimated the performance of the GRRF model via the area under the curve value. Additionally, we validated the pivotal candidate gene Malat1 in animal models.

RESULTS

We found that, among the four developmental stages, the onset development of OL (OPC2) possesses the best predictive power for distinguishing HC and MDD, and long noncoding RNA MALAT1 has top-ranked importance value in candidate genes of four developmental stages. In addition, results of fluorescence in situ hybridization assay showed that Malat1 plays a critical role in the occurrence of depression.

CONCLUSIONS

Our work elucidates the mechanism of MDD from the perspective of OL development at the single-cell resolution level and provides novel insight into the occurrence of depression.

Developmental basis of SHH medulloblastoma heterogeneity

Many genes that drive normal cellular development also contribute to oncogenesis. Medulloblastoma (MB) tumors likely arise from neuronal progenitors in the cerebellum, and we hypothesized that the heterogeneity observed in MBs with sonic hedgehog (SHH) activation could be due to differences in developmental pathways. To investigate this question, here we perform single-nucleus RNA sequencing on highly differentiated SHH MBs with extensively nodular histology and observed malignant cells resembling each stage of canonical granule neuron development. Through innovative computational approaches, we connect these results to published datasets and find that some established molecular subtypes of SHH MB appear arrested at different developmental stages. Additionally, using multiplexed proteomic imaging and MALDI imaging mass spectrometry, we identify distinct histological and metabolic profiles for highly differentiated tumors. Our approaches are applicable to understanding the interplay between heterogeneity and differentiation in other cancers and can provide important insights for the design of targeted therapies.

ZEBRA: a hierarchically integrated gene expression atlas of the murine and human brain at single-cell resolution

The molecular causes and mechanisms of neurodegenerative diseases remain poorly understood. A growing number of single-cell studies have implicated various neural, glial, and immune cell subtypes to affect the mammalian central nervous system in many age-related disorders. Integrating this body of transcriptomic evidence into a comprehensive and reproducible framework poses several computational challenges. Here, we introduce ZEBRA, a large single-cell and single-nucleus RNA-seq database. ZEBRA integrates and normalizes gene expression and metadata from 33 studies, encompassing 4.2 million human and mouse brain cells sampled from 39 brain regions. It incorporates samples from patients with neurodegenerative diseases like Alzheimer's disease, Parkinson's disease, and Multiple sclerosis, as well as samples from relevant mouse models. We employed scVI, a deep probabilistic auto-encoder model, to integrate the samples and curated both cell and sample metadata for downstream analysis. ZEBRA allows for cell-type and disease-specific markers to be explored and compared between sample conditions and brain regions, a cell composition analysis, and gene-wise feature mappings. Our comprehensive molecular database facilitates the generation of data-driven hypotheses, enhancing our understanding of mammalian brain function during aging and disease. The data sets, along with an interactive database are freely available at https://www.ccb.uni-saarland.de/zebra.

Circadian misalignment impairs oligodendrocyte myelination via Bmal1 overexpression leading to anxiety and depression-like behaviors

Circadian misalignment (CM) caused by shift work can increase the risk of mood impairment. However, the pathological mechanisms underlying these deficits remain unclear. In the present study, we used long-term variable photoperiod (L-VP) in wild-type mice to better simulate real-life shift patterns and study its effects on the prefrontal cortex (PFC) and hippocampus, which are closely related to mood function. The results showed that exposure to L-VP altered the activity/rest rhythms of mice, by eliciting phase delay and decreased amplitude of the rhythms. Mice with CM developed anxiety and depression-like manifestations and the number of mature oligodendrocytes (OL) was reduced in the medial prefrontal cortex and hippocampal CA1 regions. Mood impairment and OL reduction worsened with increased exposure time to L-VP, while normal photoperiod restoration had no effect. Mechanistically, we identified upregulation of Bmal1 in the PFC and hippocampal regions of CM mice at night, when genes related to mature OL and myelination should be highly expressed. CM mice exhibited significant inhibition of the protein kinase B (AKT)/mTOR signaling pathway, which is directly associated to OL differentiation and maturation. Furthermore, we demonstrated in the OL precursor cell line Oli-Neu that overexpression of Bmal1 inhibits AKT/mTOR pathway and reduces the expression of genes OL differentiation. In conclusion, BMAL1 might play a critical role in CM, providing strong research evidence for BMAL1 as a potential target for CM therapy.

Possible roles of deep cortical neurons and oligodendrocytes in the neural basis of human sociality

Sociality is an instinctive property of organisms that live in relation to others and is a complex characteristic of higher order brain functions. However, the evolution of the human brain to acquire higher order brain functions, such as sociality, and the neural basis for executing these functions and their control mechanisms are largely unknown. Several studies have attempted to evaluate how human sociality was acquired during the course of evolution and the mechanisms controlling sociality from a neurodevelopment viewpoint. This review discusses these findings in the context of human brain evolution and the pathophysiology of autism spectrum disorder (ASD). Comparative genomic studies of postmortem primate brains have demonstrated human-specific regulatory mechanisms underlying higher order brain functions, providing evidence for the contribution of oligodendrocytes to human brain function. Functional analyses of the causative genes of ASD in animal models have demonstrated that the neural basis of social behavior is associated with layer 6 (L6) of the neocortex and oligodendrocytes. These findings demonstrate that both neurons and oligodendrocytes contribute to the neural basis and molecular mechanisms underlying human brain evolution and social functioning. This review provides novel insights into sociability and the corresponding neural bases of brain disorders and evolution.

Genome-wide transcriptomic and biochemical profiling of major depressive disorder: Unravelling association with susceptibility, severity, and antidepressant response

Identifying biomarkers for diagnosing Major Depressive Disorder (MDD), assessing its severity, and guiding treatment is crucial. We conducted whole genome transcriptomic study in North Indian population, and analyzed biochemical parameters. Our longitudinal study investigated gene-expression profiles from 72 drug-free MDD patients and 50 healthy controls(HCs) at baseline and 24 patients after 12-weeks of treatment. Gene expression analyses identified differentially expressed genes(DEGs) associated with MDD susceptibility, symptom severity and treatment response, independently validated by qPCR. Hierarchical clustering revealed distinct expression patterns between MDD and HCs, also between mild and severe cases. Enrichment analyses of significant DEGs revealed inflammatory, apoptosis, and immune-related pathways in MDD susceptibility, severity, and treatment response. Simultaneously, we assessed thirty biochemical parameters in the same cohort, showed significant differences between MDD and HCs in 13 parameters with monocytes, eosinophils, creatinine, SGPT, and total protein remained independent predictors of MDD in a multivariate-regression model. Our study supports the role of altered immune/inflammatory signaling in MDD pathophysiology, offering clinically relevant biochemical parameters and insights into transcriptomic gene regulation in MDD pathogenesis and treatment response.

Substance P, NPY, CCK and their receptors in five brain regions in major depressive disorder with transcriptomic analysis of locus coeruleus neurons

Major depressive disorder (MDD) is a serious disease and a burden to patients, families and society. Rodent experiments and human studies suggest that several neuropeptide systems are involved in mood regulation. The aim of this study is two-fold: (i) to monitor, with qPCR, transcript levels of the substance P/tachykinin (TAC), NPY and CCK systems in bulk samples from control and suicide subjects, targeting five postmortem brain regions including locus coeruleus (LC); and (ii) to analyse expression of neuropeptide family transcripts in LC neurons of 'normal' postmortem brains by using laser capture microdissection with Smart-Seq2 RNA sequencing. qPCR revealed distinct regional expression patterns in male and female controls with higher levels for the TAC system in the dorsal raphe nucleus and LC, versus higher transcripts levels of the NPY and CCK systems in prefrontal cortex. In suicide patients, TAC, TAC receptors and a few NPY family transcript levels were increased mainly in prefrontal cortex and LC. The second study on 'normal' noradrenergic LC neurons revealed expression of transcripts for GAL, NPY, TAC1, CCK, and TACR1 and many other peptides (e.g. Cerebellin4 and CARTPT) and receptors (e.g. Adcyap1R1 and GPR173). These data and our previous results on suicide brains indicates that the tachykinin and galanin systems may be valid targets for developing antidepressant medicines. Moreover, the perturbation of neuropeptide systems in MDD patients, and the detection of further neuropeptide and receptor transcripts in LC, shed new light on signalling in noradrenergic LC neurons and on mechanisms possibly associated with mood disorders.

Single-Cell Sequencing Technology and Its Application in the Study of Central Nervous System Diseases

The mammalian central nervous system consists of a large number of cells, which contain not only different types of neurons, but also a large number of glial cells, such as astrocytes, oligodendrocytes, and microglia. These cells are capable of performing highly refined electrophysiological activities and providing the brain with functions such as nutritional support, information transmission and pathogen defense. The diversity of cell types and individual differences between cells have brought inspiration to the study of the mechanism of central nervous system diseases. In order to explore the role of different cells, a new technology, single-cell sequencing technology has emerged to perform specific analysis of high-throughput cell populations, and has been continuously developed. Single-cell sequencing technology can accurately analyze single-cell expression in mixed-cell populations and collect cells from different spatial locations, time stages and types. By using single-cell sequencing technology to compare gene expression profiles of normal and diseased cells, it is possible to discover cell subsets associated with specific diseases and their associated genes. Therefore, scientists can understand the development process, related functions and disease state of the nervous system from an unprecedented depth. In conclusion, single-cell sequencing technology provides a powerful technology for the discovery of novel therapeutic targets for central nervous system diseases.