Dopamine signaling enriched striatal gene set predicts striatal dopamine synthesis and physiological activity in vivo

The polygenic architecture of schizophrenia implicates several molecular pathways involved in synaptic function. However, it is unclear how polygenic risk funnels through these pathways to translate into syndromic illness. Using tensor decomposition, we analyze gene co-expression in the caudate nucleus, hippocampus, and dorsolateral prefrontal cortex of post-mortem brain samples from 358 individuals. We identify a set of genes predominantly expressed in the caudate nucleus and associated with both clinical state and genetic risk for schizophrenia that shows dopaminergic selectivity. A higher polygenic risk score for schizophrenia parsed by this set of genes predicts greater dopamine synthesis in the striatum and greater striatal activation during reward anticipation. These results translate dopamine-linked genetic risk variation into in vivo neurochemical and hemodynamic phenotypes in the striatum that have long been implicated in the pathophysiology of schizophrenia.

Benchmark of cellular deconvolution methods using a multi-assay reference dataset from postmortem human prefrontal cortex

Background

Cellular deconvolution of bulk RNA-sequencing (RNA-seq) data using single cell or nuclei RNA-seq (sc/snRNA-seq) reference data is an important strategy for estimating cell type composition in heterogeneous tissues, such as human brain. Computational methods for deconvolution have been developed and benchmarked against simulated data, pseudobulked sc/snRNA-seq data, or immunohistochemistry reference data. A major limitation in developing improved deconvolution algorithms has been the lack of integrated datasets with orthogonal measurements of gene expression and estimates of cell type proportions on the same tissue sample. Deconvolution algorithm performance has not yet been evaluated across different RNA extraction methods (cytosolic, nuclear, or whole cell RNA), different library preparation types (mRNA enrichment vs. ribosomal RNA depletion), or with matched single cell reference datasets.

Results

A rich multi-assay dataset was generated in postmortem human dorsolateral prefrontal cortex (DLPFC) from 22 tissue blocks. Assays included spatially-resolved transcriptomics, snRNA-seq, bulk RNA-seq (across six library/extraction RNA-seq combinations), and RNAScope/Immunofluorescence (RNAScope/IF) for six broad cell types. The Mean Ratio method, implemented in the DeconvoBuddies R package, was developed for selecting cell type marker genes. Six computational deconvolution algorithms were evaluated in DLPFC and predicted cell type proportions were compared to orthogonal RNAScope/IF measurements.

Conclusions

Bisque and hspe were the most accurate methods, were robust to differences in RNA library types and extractions. This multi-assay dataset showed that cell size differences, marker genes differentially quantified across RNA libraries, and cell composition variability in reference snRNA-seq impact the accuracy of current deconvolution methods.

Transcriptomic analysis of the human habenula in schizophrenia

Importance

Habenula (Hb) pathophysiology is involved in many neuropsychiatric disorders, including schizophrenia. Deep brain stimulation and pharmacological targeting of the Hb are emerging as promising therapeutic treatments. However, little is known about the cell type-specific transcriptomic organization of the human Hb or how it is altered in schizophrenia.

Objective

To define the molecular neuroanatomy of the human habenula and identify transcriptomic changes in individuals with schizophrenia compared to neurotypical controls.

Design Setting and Participants

This study utilized Hb-enriched postmortem human brain tissue. Single nucleus RNA-sequencing (snRNA-seq) and single molecule fluorescent in situ hybridization (smFISH) experiments were conducted to identify molecularly defined Hb cell types and map their spatial location (n=3-7 donors). Bulk RNA-sequencing and cell type deconvolution were used to investigate transcriptomic changes in Hb-enriched tissue from 35 individuals with schizophrenia and 33 neurotypical controls. Gene expression changes associated with schizophrenia in the Hb were compared to those previously identified in the dorsolateral prefrontal cortex (DLPFC), hippocampus, and caudate.

Main Outcomes and Measures

Semi-supervised snRNA-seq cell type clustering. Transcript visualization and quantification of smFISH probes. Bulk RNA-seq cell type deconvolution using reference snRNA-seq data. Schizophrenia-associated gene differential expression analysis adjusting for Hb and thalamus fractions, RNA degradation-associated quality surrogate variables, and other covariates. Cross-brain region schizophrenia-associated gene expression comparison.

Results

snRNA-seq identified 17 cell type clusters across 16,437 nuclei, including 3 medial and 7 lateral Hb populations. Cell types were conserved with those identified in a rodent model. smFISH for cell type marker genes validated snRNA-seq Hb cell types and depicted the spatial organization of subpopulations. Bulk RNA-seq analyses yielded 45 schizophrenia-associated differentially expressed genes (FDR < 0.05), with 32 (71%) unique to Hb-enriched tissue.

Conclusions

These results identify topographically organized cell types with distinct molecular signatures in the human Hb. They further demonstrate unique transcriptomic changes in the epithalamus associated with schizophrenia, thereby providing molecular insights into the role of Hb in neuropsychiatric disorders.

Human archetypal pluripotent stem cells differentiate into trophoblast stem cells via endogenous BMP5/7 induction without transitioning through naive state

Primary human trophoblast stem cells (TSCs) and TSCs derived from human pluripotent stem cells (hPSCs) can potentially model placental processes in vitro. Yet, the pluripotent states and factors involved in the differentiation of hPSCs to TSCs remain poorly understood. In this study, we demonstrate that the primed pluripotent state can generate TSCs by activating pathways such as Epidermal Growth Factor (EGF) and Wingless-related integration site (WNT), and by suppressing tumor growth factor beta (TGFβ), histone deacetylases (HDAC), and Rho-associated protein kinase (ROCK) signaling pathways, all without the addition of exogenous Bone morphogenetic protein 4 (BMP4)-a condition we refer to as the TS condition. We characterized this process using temporal single-cell RNA sequencing to compare TS conditions with differentiation protocols involving BMP4 activation alone or BMP4 activation in conjunction with WNT inhibition. The TS condition consistently produced a stable, proliferative cell type that closely mimics first-trimester placental cytotrophoblasts, marked by the activation of endogenous retroviral genes and the absence of amnion expression. This was observed across multiple cell lines, including various primed induced pluripotent stem cell (iPSC) and embryonic stem cell (ESC) lines. Primed-derived TSCs can proliferate for over 30 passages and further specify into multinucleated syncytiotrophoblasts and extravillous trophoblast cells. Our research establishes that the differentiation of primed hPSCs to TSC under TS conditions triggers the induction of TMSB4X, BMP5/7, GATA3, and TFAP2A without progressing through a naive state. These findings propose that the primed hPSC state is part of a continuum of potency with the capacity to differentiate into TSCs through multiple routes.

scMeFormer: a transformer-based deep learning model for imputing DNA methylation states in single cells enhances the detection of epigenetic alterations in schizophrenia

DNA methylation (DNAm), a crucial epigenetic mark, plays a key role in gene regulation, mammalian development, and various human diseases. Single-cell technologies enable the profiling of DNAm states at cytosines within the DNA sequence of individual cells, but they often suffer from limited coverage of CpG sites. In this study, we introduce scMeFormer, a transformer-based deep learning model designed to impute DNAm states for each CpG site in single cells. Through comprehensive evaluations, we demonstrate the superior performance of scMeFormer compared to alternative models across four single-nucleus DNAm datasets generated by distinct technologies. Remarkably, scMeFormer exhibits high-fidelity imputation, even when dealing with significantly reduced coverage, as low as 10% of the original CpG sites. Furthermore, we applied scMeFormer to a single-nucleus DNAm dataset generated from the prefrontal cortex of four schizophrenia patients and four neurotypical controls. This enabled the identification of thousands of differentially methylated regions associated with schizophrenia that would have remained undetectable without imputation and added granularity to our understanding of epigenetic alterations in schizophrenia within specific cell types. Our study highlights the power of deep learning in imputing DNAm states in single cells, and we expect scMeFormer to be a valuable tool for single-cell DNAm studies.

The gene expression landscape of the human locus coeruleus revealed by single-nucleus and spatially-resolved transcriptomics

Norepinephrine (NE) neurons in the locus coeruleus (LC) make long-range projections throughout the central nervous system, playing critical roles in arousal and mood, as well as various components of cognition including attention, learning, and memory. The LC-NE system is also implicated in multiple neurological and neuropsychiatric disorders. Importantly, LC-NE neurons are highly sensitive to degeneration in both Alzheimer's and Parkinson's disease. Despite the clinical importance of the brain region and the prominent role of LC-NE neurons in a variety of brain and behavioral functions, a detailed molecular characterization of the LC is lacking. Here, we used a combination of spatially-resolved transcriptomics and single-nucleus RNA-sequencing to characterize the molecular landscape of the LC region and the transcriptomic profile of LC-NE neurons in the human brain. We provide a freely accessible resource of these data in web-accessible and downloadable formats.

Alcohol Use Disorder-Associated DNA Methylation in the Nucleus Accumbens and Dorsolateral Prefrontal Cortex

Background

Alcohol use disorder (AUD) has a profound public health impact. However, understanding of the molecular mechanisms underlying the development and progression of AUD remain limited. Here, we interrogate AUD-associated DNA methylation (DNAm) changes within and across addiction-relevant brain regions: the nucleus accumbens (NAc) and dorsolateral prefrontal cortex (DLPFC).

Methods

Illumina HumanMethylation EPIC array data from 119 decedents of European ancestry (61 cases, 58 controls) were analyzed using robust linear regression, with adjustment for technical and biological variables. Associations were characterized using integrative analyses of public gene regulatory data and published genetic and epigenetic studies. We additionally tested for brain region-shared and -specific associations using mixed effects modeling and assessed implications of these results using public gene expression data.

Results

At a false discovery rate ≤ 0.05, we identified 53 CpGs significantly associated with AUD status for NAc and 31 CpGs for DLPFC. In a meta-analysis across the regions, we identified an additional 21 CpGs associated with AUD, for a total of 105 unique AUD-associated CpGs (120 genes). AUD-associated CpGs were enriched in histone marks that tag active promoters and our strongest signals were specific to a single brain region. Of the 120 genes, 23 overlapped with previous genetic associations for substance use behaviors; all others represent novel associations.

Conclusions

Our findings identify AUD-associated methylation signals, the majority of which are specific within NAc or DLPFC. Some signals may constitute predisposing genetic and epigenetic variation, though more work is needed to further disentangle the neurobiological gene regulatory differences associated with AUD.

Spatially-resolved transcriptomics of human dentate gyrus across postnatal lifespan reveals heterogeneity in markers for proliferation, extracellular matrix, and neuroinflammation

The dentate gyrus of the anterior hippocampus is important for many human cognitive functions, including regulation of learning, memory, and mood. However, the postnatal development and aging of the dentate gyrus throughout the human lifespan has yet to be fully characterized in the same molecular and spatial detail as other species. Here, we generated a spatially-resolved molecular atlas of the dentate gyrus in postmortem human tissue using the 10x Genomics Visium platform to retain extranuclear transcripts and identify changes in molecular topography across the postnatal lifespan. We found enriched expression of extracellular matrix markers during infancy and increased expression of GABAergic cell-type markers GAD1, LAMP5, and CCK after infancy. While we identified a conserved gene signature for mouse neuroblasts in the granule cell layer (GCL), many of those genes are not specific to the GCL, and we found no evidence of signatures for other granule cell lineage stages at the GCL post-infancy. We identified a wide-spread hippocampal aging signature and an age-dependent increase in neuroinflammation associated genes. Our findings suggest major changes to the putative neurogenic niche after infancy and identify molecular foci of brain aging in glial and neuropil enriched tissue.

VistoSeg: Processing utilities for high-resolution images for spatially resolved transcriptomics data

Spatially resolved transcriptomics (SRT) is a growing field that links gene expression to anatomical context. SRT approaches that use next-generation sequencing (NGS) combine RNA sequencing with histological or fluorescent imaging to generate spatial maps of gene expression in intact tissue sections. These technologies directly couple gene expression measurements with high-resolution histological or immunofluorescent images that contain rich morphological information about the tissue under study. While broad access to NGS-based spatial transcriptomic technology is now commercially available through the Visium platform from the vendor 10× Genomics, computational tools for extracting image-derived metrics for integration with gene expression data remain limited. We developed VistoSeg as a MATLAB pipeline to process, analyze and interactively visualize the high-resolution images generated in the Visium platform. VistoSeg outputs can be easily integrated with accompanying transcriptomic data to facilitate downstream analyses in common programing languages including R and Python. VistoSeg provides user-friendly tools for integrating image-derived metrics from histological and immunofluorescent images with spatially resolved gene expression data. Integration of this data enhances the ability to understand the transcriptional landscape within tissue architecture. VistoSeg is freely available at http://research.libd.org/VistoSeg/.

Comparison of gene expression in living and postmortem human brain

Molecular mechanisms of neuropsychiatric disorders are challenging to study in human brain. For decades, the preferred model has been to study postmortem human brain samples despite the limitations they entail. A recent study generated RNA sequencing data from biopsies of prefrontal cortex from living patients with Parkinson's Disease and compared gene expression to postmortem tissue samples, from which they found vast differences between the two. This led the authors to question the utility of postmortem human brain studies. Through re-analysis of the same data, we unexpectedly found that the living brain tissue samples were of much lower quality than the postmortem samples across multiple standard metrics. We also performed simulations that illustrate the effects of ignoring RNA degradation in differential gene expression analyses, showing the effects can be substantial and of similar magnitude to what the authors find. For these reasons, we believe the authors' conclusions are unjustified. To the contrary, while opportunities to study gene expression in the living brain are welcome, evidence that this eclipses the value of postmortem analyses is not apparent.

Recapitulation of Perturbed Striatal Gene Expression Dynamics of Donors' Brains With Ventral Forebrain Organoids Derived From the Same Individuals With Schizophrenia

OBJECTIVE

Schizophrenia is a brain disorder that originates during neurodevelopment and has complex genetic and environmental etiologies. Despite decades of clinical evidence of altered striatal function in affected patients, studies examining its cellular and molecular mechanisms in humans are limited. To explore neurodevelopmental alterations in the striatum associated with schizophrenia, the authors established a method for the differentiation of induced pluripotent stem cells (iPSCs) into ventral forebrain organoids (VFOs).

METHODS

VFOs were generated from postmortem dural fibroblast-derived iPSCs of four individuals with schizophrenia and four neurotypical control individuals for whom postmortem caudate genotypes and transcriptomic data were profiled in the BrainSeq neurogenomics consortium. Individuals were selected such that the two groups had nonoverlapping schizophrenia polygenic risk scores (PRSs).

RESULTS

Single-cell RNA sequencing analyses of VFOs revealed differences in developmental trajectory between schizophrenia and control individuals in which inhibitory neuronal cells from the patients exhibited accelerated maturation. Furthermore, upregulated genes in inhibitory neurons in schizophrenia VFOs showed a significant overlap with upregulated genes in postmortem caudate tissue of individuals with schizophrenia compared with control individuals, including the donors of the iPSC cohort.

CONCLUSIONS

The findings suggest that striatal neurons derived from high-PRS individuals with schizophrenia carry abnormalities that originated during early brain development and that the VFO model can recapitulate disease-relevant cell type-specific neurodevelopmental phenotypes in a dish.

Identification of a specific APOE transcript and functional elements associated with Alzheimer's disease

INTRODUCTION

The APOE gene is the strongest genetic risk factor for late-onset Alzheimer's Disease (LOAD). However, the gene regulatory mechanisms at this locus have not been fully characterized.

METHODS

To identify novel AD-linked functional elements within the APOE locus, we integrated SNP variants with RNA-seq, DNA methylation, and ChIP-seq data from human postmortem brains.

RESULTS

We identified an AD-linked APOE transcript (jxn1.2.2) observed in the dorsolateral prefrontal cortex (DLPFC). The APOE jxn1.2.2 transcript is associated with brain neuropathological features in DLPFC. We prioritized an independent functional SNP, rs157580, significantly associated with jxn1.2.2 transcript abundance and DNA methylation levels. rs157580 is located within active chromatin regions and predicted to affect brain-related transcriptional factors binding affinity. rs157580 shared the effects on the jxn1.2.2 transcript between European and African ethnic groups.

DISCUSSION

The novel APOE functional elements provide potential therapeutic targets with mechanistic insight into the disease's etiology.

Genetic and environmental contributions to ancestry differences in gene expression in the human brain

Ancestral differences in genomic variation are determining factors in gene regulation; however, most gene expression studies have been limited to European ancestry samples or adjusted for ancestry to identify ancestry-independent associations. We instead examined the impact of genetic ancestry on gene expression and DNA methylation (DNAm) in admixed African/Black American neurotypical individuals to untangle effects of genetic and environmental factors. Ancestry-associated differentially expressed genes (DEGs), transcripts, and gene networks, while notably not implicating neurons, are enriched for genes related to immune response and vascular tissue and explain up to 26% of heritability for ischemic stroke, 27% of heritability for Parkinson's disease, and 30% of heritability for Alzhemier's disease. Ancestry-associated DEGs also show general enrichment for heritability of diverse immune-related traits but depletion for psychiatric-related traits. The cell-type enrichments and direction of effects vary by brain region. These DEGs are less evolutionarily constrained and are largely explained by genetic variations; roughly 15% are predicted by DNAm variation implicating environmental exposures. We also compared Black and White Americans, confirming most of these ancestry-associated DEGs. Our results highlight how environment and genetic background affect genetic ancestry differences in gene expression in the human brain and affect risk for brain illness.

Investigating trait variability of gene co-expression network architecture in brain by controlling for genomic risk of schizophrenia

The effect of schizophrenia (SCZ) genetic risk on gene expression in brain remains elusive. A popular approach to this problem has been the application of gene co-expression network algorithms (e.g., WGCNA). To improve reliability with this method it is critical to remove unwanted sources of variance while also preserving biological signals of interest. In this WCGNA study of RNA-Seq data from postmortem prefrontal cortex (78 neurotypical donors, EUR ancestry), we tested the effects of SCZ genetic risk on co-expression networks. Specifically, we implemented a novel design in which gene expression was adjusted by linear regression models to preserve or remove variance explained by biological signal of interest (GWAS genomic scores for SCZ risk-(GS-SCZ), and genomic scores- GS of height (GS-Ht) as a negative control), while removing variance explained by covariates of non-interest. We calculated co-expression networks from adjusted expression (GS-SCZ and GS-Ht preserved or removed), and consensus between them (representative of a "background" network free of genomic scores effects). We then tested the overlap between GS-SCZ preserved modules and background networks reasoning that modules with reduced overlap would be most affected by GS-SCZ biology. Additionally, we tested these modules for convergence of SCZ risk (i.e., enrichment in PGC3 SCZ GWAS priority genes, enrichment in SCZ risk heritability and relevant biological ontologies. Our results highlight key aspects of GS-SCZ effects on brain co-expression networks, specifically: 1) preserving/removing SCZ genetic risk alters the co-expression modules; 2) biological pathways enriched in modules affected by GS-SCZ implicate processes of transcription, translation and metabolism that converge to influence synaptic transmission; 3) priority PGC3 SCZ GWAS genes and SCZ risk heritability are enriched in modules associated with GS-SCZ effects. Overall, our results indicate that gene co-expression networks that selectively integrate information about genetic risk can reveal novel combinations of biological pathways involved in schizophrenia.

Dopamine and schizophrenia from bench to bedside: Discovery of a striatal co-expression risk gene set that predicts in vivo measures of striatal function

Schizophrenia (SCZ) is characterized by a polygenic risk architecture implicating diverse molecular pathways important for synaptic function. However, how polygenic risk funnels through these pathways to translate into syndromic illness is unanswered. To evaluate biologically meaningful pathways of risk, we used tensor decomposition to characterize gene co-expression in post-mortem brain (of neurotypicals: N=154; patients with SCZ: N=84; and GTEX samples N=120) from caudate nucleus (CN), hippocampus (HP), and dorsolateral prefrontal cortex (DLPFC). We identified a CN-predominant gene set showing dopaminergic selectivity that was enriched for genes associated with clinical state and for genes associated with SCZ risk. Parsing polygenic risk score for SCZ based on this specific gene set (parsed-PRS), we found that greater pathway-specific SCZ risk predicted greater in vivo striatal dopamine synthesis capacity measured by [ 18 F]-FDOPA PET in three independent cohorts of neurotypicals and patients (total N=235) and greater fMRI striatal activation during reward anticipation in two additional independent neurotypical cohorts (total N=141). These results reveal a 'bench to bedside' translation of dopamine-linked genetic risk variation in driving in vivo striatal neurochemical and hemodynamic phenotypes that have long been implicated in the pathophysiology of SCZ.

Smoking-informed methylation and expression QTLs in human brain and colocalization with smoking-associated genetic loci

Smoking is a leading cause of preventable morbidity and mortality. Smoking is heritable, and genome-wide association studies (GWAS) of smoking behaviors have identified hundreds of significant loci. Most GWAS-identified variants are noncoding with unknown neurobiological effects. We used genome-wide genotype, DNA methylation, and RNA sequencing data in postmortem human nucleus accumbens (NAc) to identify cis-methylation/expression quantitative trait loci (meQTLs/eQTLs), investigate variant-by-cigarette smoking interactions across the genome, and overlay QTL evidence at smoking GWAS-identified loci to evaluate their regulatory potential. Active smokers (N=52) and nonsmokers (N=171) were defined based on cotinine biomarker levels and next-of-kin reporting. We simultaneously tested variant and variant-by-smoking interaction effects on methylation and expression, separately, adjusting for biological and technical covariates and using a two-stage multiple testing approach with eigenMT and Bonferroni corrections. We found >2 million significant meQTL variants (padj<0.05) corresponding to 41,695 unique CpGs. Results were largely driven by main effects; five meQTLs, mapping to NUDT12, FAM53B, RNF39, and ADRA1B, showed a significant interaction with smoking. We found 57,683 significant eQTLs for 958 unique eGenes (padj<0.05) and no smoking interactions. Colocalization analyses identified loci with smoking-associated GWAS variants that overlapped meQTLs/eQTLs, suggesting that these heritable factors may influence smoking behaviors through functional effects on methylation/expression. One locus containing MUSTIN1 and ITIH4 colocalized across all data types (GWAS + meQTL + eQTL). In this first genome-wide meQTL map in the human NAc, the enriched overlap with smoking GWAS-identified genetic loci provides evidence that gene regulation in the brain helps explain the neurobiology of smoking behaviors.

Chronic traumatic encephalopathy neuropathologic change is uncommon in men who played amateur American football

Introduction

We examined postmortem brain tissue from men, over the age of 50, for chronic traumatic encephalopathy neuropathologic change (CTE-NC). We hypothesized that (i) a small percentage would have CTE-NC, (ii) those who played American football during their youth would be more likely to have CTE-NC than those who did not play contact or collision sports, and (iii) there would be no association between CTE-NC and suicide as a manner of death.

Methods

Brain tissue from 186 men and accompanying clinical information were obtained from the Lieber Institute for Brain Development. Manner of death was determined by a board-certified forensic pathologist. Information was obtained from next of kin telephone interviews, including medical, social, demographic, family, and psychiatric history. The 2016 and 2021 consensus definitions were used for CTE-NC. Two authors screened all cases, using liberal criteria for identifying "possible" CTE-NC, and five authors examined the 15 selected cases.

Results

The median age at the time of death was 65 years (interquartile range = 57-75; range = 50-96). There were 25.8% with a history of playing American football and 36.0% who had suicide as their manner of death. No case was rated as definitively having "features" of CTE-NC by all five authors. Ten cases were rated as having features of CTE-NC by three or more authors (5.4% of the sample), including 8.3% of those with a personal history of playing American football and 3.9% of those who did not play contact or collision sports. Of those with mood disorders during life, 5.5% had features of CTE-NC compared to 6.0% of those who did not have a reported mood disorder. Of those with suicide as a manner of death, 6.0% had features of CTE-NC compared to 5.0% of those who did not have suicide as a manner of death.

Discussion

We did not identify a single definitive case of CTE-NC, from the perspective of all raters, and only 5.4% of cases were identified as having possible features of CTE-NC by some raters. CTE-NC was very uncommon in men who played amateur American football, those with mood disorders during life, and those with suicide as a manner of death.

Orthogonal approaches required to measure proteasome composition and activity in mammalian brain tissue

Proteasomes are large macromolecular complexes with multiple distinct catalytic activities that are each vital to human brain health and disease. Despite their importance, standardized approaches to investigate proteasomes have not been universally adapted. Here, we describe pitfalls and define straightforward orthogonal biochemical approaches essential to measure and understand changes in proteasome composition and activity in the mammalian central nervous system. Through our experimentation in the mammalian brain, we determined an abundance of catalytically active proteasomes exist with and without a 19S cap(s), the regulatory particle essential for ubiquitin-dependent degradation. Moreover, we learned that in-cell measurements using activity-based probes (ABPs) are more sensitive in determining the available activity of the 20S proteasome without the 19S cap and in measuring individual catalytic subunit activities of each β subunit within all neuronal proteasomes. Subsequently, applying these tools to human brain samples, we were surprised to find that post-mortem tissue retained little to no 19S-capped proteasome, regardless of age, sex, or disease state. Comparing brain tissues (parahippocampal gyrus) from human Alzheimer's disease (AD) patients and unaffected subjects, available 20S proteasome activity was significantly elevated in severe cases of AD, an observation not previously noted. Taken together, our study establishes standardized approaches for comprehensive investigation of proteasomes in mammalian brain tissue, and we reveal new insight into brain proteasome biology.

Deoxyhypusine hydroxylase: A novel therapeutic target differentially expressed in short-term vs long-term survivors of glioblastoma

Glioblastoma (GB) is the most aggressive neoplasm of the brain. Poor prognosis is mainly attributed to tumor heterogeneity, invasiveness and drug resistance. Only a small fraction of GB patients survives longer than 24 months from the time of diagnosis (ie, long-term survivors [LTS]). In our study, we aimed to identify molecular markers associated with favorable GB prognosis as a basis to develop therapeutic applications to improve patients' outcome. We have recently assembled a proteogenomic dataset of 87 GB clinical samples of varying survival rates. Following RNA-seq and mass spectrometry (MS)-based proteomics analysis, we identified several differentially expressed genes and proteins, including some known cancer-related pathways and some less established that showed higher expression in short-term (<6 months) survivors (STS) compared to LTS. One such target found was deoxyhypusine hydroxylase (DOHH), which is known to be involved in the biosynthesis of hypusine, an unusual amino acid essential for the function of the eukaryotic translation initiation factor 5A (eIF5A), which promotes tumor growth. We consequently validated DOHH overexpression in STS samples by quantitative polymerase chain reaction (qPCR) and immunohistochemistry. We further showed robust inhibition of proliferation, migration and invasion of GB cells following silencing of DOHH with short hairpin RNA (shRNA) or inhibition of its activity with small molecules, ciclopirox and deferiprone. Moreover, DOHH silencing led to significant inhibition of tumor progression and prolonged survival in GB mouse models. Searching for a potential mechanism by which DOHH promotes tumor aggressiveness, we found that it supports the transition of GB cells to a more invasive phenotype via epithelial-mesenchymal transition (EMT)-related pathways.

Consensus molecular environment of schizophrenia risk genes in coexpression networks shifting across age and brain regions

Schizophrenia is a neurodevelopmental brain disorder whose genetic risk is associated with shifting clinical phenomena across the life span. We investigated the convergence of putative schizophrenia risk genes in brain coexpression networks in postmortem human prefrontal cortex (DLPFC), hippocampus, caudate nucleus, and dentate gyrus granule cells, parsed by specific age periods (total N = 833). The results support an early prefrontal involvement in the biology underlying schizophrenia and reveal a dynamic interplay of regions in which age parsing explains more variance in schizophrenia risk compared to lumping all age periods together. Across multiple data sources and publications, we identify 28 genes that are the most consistently found partners in modules enriched for schizophrenia risk genes in DLPFC; twenty-three are previously unidentified associations with schizophrenia. In iPSC-derived neurons, the relationship of these genes with schizophrenia risk genes is maintained. The genetic architecture of schizophrenia is embedded in shifting coexpression patterns across brain regions and time, potentially underwriting its shifting clinical presentation.

Associations of psychiatric disease and ageing with FKBP5 expression converge on superficial layer neurons of the neocortex

Identification and characterisation of novel targets for treatment is a priority in the field of psychiatry. FKBP5 is a gene with decades of evidence suggesting its pathogenic role in a subset of psychiatric patients, with potential to be leveraged as a therapeutic target for these individuals. While it is widely reported that FKBP5/FKBP51 mRNA/protein (FKBP5/1) expression is impacted by psychiatric disease state, risk genotype and age, it is not known in which cell types and sub-anatomical areas of the human brain this occurs. This knowledge is critical to propel FKBP5/1-targeted treatment development. Here, we performed an extensive, large-scale postmortem study (n = 1024) of FKBP5/1, examining neocortical areas (BA9, BA11 and ventral BA24/BA24a) derived from subjects that lived with schizophrenia, major depression or bipolar disorder. With an extensive battery of RNA (bulk RNA sequencing, single-nucleus RNA sequencing, microarray, qPCR, RNAscope) and protein (immunoblot, immunohistochemistry) analysis approaches, we thoroughly investigated the effects of disease state, ageing and genotype on cortical FKBP5/1 expression including in a cell type-specific manner. We identified consistently heightened FKBP5/1 levels in psychopathology and with age, but not genotype, with these effects strongest in schizophrenia. Using single-nucleus RNA sequencing (snRNAseq; BA9 and BA11) and targeted histology (BA9, BA24a), we established that these disease and ageing effects on FKBP5/1 expression were most pronounced in excitatory superficial layer neurons of the neocortex, and this effect appeared to be consistent in both the granular and agranular areas examined. We then found that this increase in FKBP5 levels may impact on synaptic plasticity, as FKBP5 gex levels strongly and inversely correlated with dendritic mushroom spine density and brain-derived neurotrophic factor (BDNF) levels in superficial layer neurons in BA11. These findings pinpoint a novel cellular and molecular mechanism that has potential to open a new avenue of FKBP51 drug development to treat cognitive symptoms in psychiatric disorders.

Cross-ancestry, cell-type-informed atlas of gene, isoform, and splicing regulation in the developing human brain

Genomic regulatory elements active in the developing human brain are notably enriched in genetic risk for neuropsychiatric disorders, including autism spectrum disorder (ASD), schizophrenia, and bipolar disorder. However, prioritizing the specific risk genes and candidate molecular mechanisms underlying these genetic enrichments has been hindered by the lack of a single unified large-scale gene regulatory atlas of human brain development. Here, we uniformly process and systematically characterize gene, isoform, and splicing quantitative trait loci (xQTLs) in 672 fetal brain samples from unique subjects across multiple ancestral populations. We identify 15,752 genes harboring a significant xQTL and map 3,739 eQTLs to a specific cellular context. We observe a striking drop in gene expression and splicing heritability as the human brain develops. Isoform-level regulation, particularly in the second trimester, mediates the greatest proportion of heritability across multiple psychiatric GWAS, compared with eQTLs. Via colocalization and TWAS, we prioritize biological mechanisms for ~60% of GWAS loci across five neuropsychiatric disorders, nearly two-fold that observed in the adult brain. Finally, we build a comprehensive set of developmentally regulated gene and isoform co-expression networks capturing unique genetic enrichments across disorders. Together, this work provides a comprehensive view of genetic regulation across human brain development as well as the stage-and cell type-informed mechanistic underpinnings of neuropsychiatric disorders.

Integrated single cell and unsupervised spatial transcriptomic analysis defines molecular anatomy of the human dorsolateral prefrontal cortex

Generation of a molecular neuroanatomical map of the human prefrontal cortex reveals novel spatial domains and cell-cell interactions relevant for psychiatric disease. The molecular organization of the human neocortex has been historically 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. Here 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 (DLPFC). 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 map the enrichment of cell types and genes associated with neuropsychiatric disorders to discrete spatial domains. Finally, we provide resources for the scientific community to explore these integrated spatial and single cell datasets at research.libd.org/spatialDLPFC/.

Multi-ancestry transcriptome-wide association analyses yield insights into tobacco use biology and drug repurposing

Most transcriptome-wide association studies (TWASs) so far focus on European ancestry and lack diversity. To overcome this limitation, we aggregated genome-wide association study (GWAS) summary statistics, whole-genome sequences and expression quantitative trait locus (eQTL) data from diverse ancestries. We developed a new approach, TESLA (multi-ancestry integrative study using an optimal linear combination of association statistics), to integrate an eQTL dataset with a multi-ancestry GWAS. By exploiting shared phenotypic effects between ancestries and accommodating potential effect heterogeneities, TESLA improves power over other TWAS methods. When applied to tobacco use phenotypes, TESLA identified 273 new genes, up to 55% more compared with alternative TWAS methods. These hits and subsequent fine mapping using TESLA point to target genes with biological relevance. In silico drug-repurposing analyses highlight several drugs with known efficacy, including dextromethorphan and galantamine, and new drugs such as muscle relaxants that may be repurposed for treating nicotine addiction.

SUFI: an automated approach to spectral unmixing of fluorescent multiplex images captured in mouse and post-mortem human brain tissues

BACKGROUND

Multispectral fluorescence imaging coupled with linear unmixing is a form of image data collection and analysis that allows for measuring multiple molecular signals in a single biological sample. Multiple fluorescent dyes, each measuring a unique molecule, are simultaneously measured and subsequently "unmixed" to provide a read-out for each molecular signal. This strategy allows for measuring highly multiplexed signals in a single data capture session, such as multiple proteins or RNAs in tissue slices or cultured cells, but can often result in mixed signals and bleed-through problems across dyes. Existing spectral unmixing algorithms are not optimized for challenging biological specimens such as post-mortem human brain tissue, and often require manual intervention to extract spectral signatures. We therefore developed an intuitive, automated, and flexible package called SUFI: spectral unmixing of fluorescent images.

RESULTS

This package unmixes multispectral fluorescence images by automating the extraction of spectral signatures using vertex component analysis, and then performs one of three unmixing algorithms derived from remote sensing. We evaluate these remote sensing algorithms' performances on four unique biological datasets and compare the results to unmixing results obtained using ZEN Black software (Zeiss). We lastly integrate our unmixing pipeline into the computational tool dotdotdot, which is used to quantify individual RNA transcripts at single cell resolution in intact tissues and perform differential expression analysis, and thereby provide an end-to-end solution for multispectral fluorescence image analysis and quantification.

CONCLUSIONS

In summary, we provide a robust, automated pipeline to assist biologists with improved spectral unmixing of multispectral fluorescence images.

A single-cell transcriptome atlas of glial diversity in the human hippocampus across the postnatal lifespan

The molecular diversity of glia in the human hippocampus and their temporal dynamics over the lifespan remain largely unknown. Here, we performed single-nucleus RNA sequencing to generate a transcriptome atlas of the human hippocampus across the postnatal lifespan. Detailed analyses of astrocytes, oligodendrocyte lineages, and microglia identified subpopulations with distinct molecular signatures and revealed their association with specific physiological functions, age-dependent changes in abundance, and disease relevance. We further characterized spatiotemporal heterogeneity of GFAP-enriched astrocyte subpopulations in the hippocampal formation using immunohistology. Leveraging glial subpopulation classifications as a reference map, we revealed the diversity of glia differentiated from human pluripotent stem cells and identified dysregulated genes and pathological processes in specific glial subpopulations in Alzheimer's disease (AD). Together, our study significantly extends our understanding of human glial diversity, population dynamics across the postnatal lifespan, and dysregulation in AD and provides a reference atlas for stem-cell-based glial differentiation.

Analysis of the caudate nucleus transcriptome in individuals with schizophrenia highlights effects of antipsychotics and new risk genes

Most studies of gene expression in the brains of individuals with schizophrenia have focused on cortical regions, but subcortical nuclei such as the striatum are prominently implicated in the disease, and current antipsychotic drugs target the striatum's dense dopaminergic innervation. Here, we performed a comprehensive analysis of the genetic and transcriptional landscape of schizophrenia in the postmortem caudate nucleus of the striatum of 443 individuals (245 neurotypical individuals, 154 individuals with schizophrenia and 44 individuals with bipolar disorder), 210 from African and 233 from European ancestries. Integrating expression quantitative trait loci analysis, Mendelian randomization with the latest schizophrenia genome-wide association study, transcriptome-wide association study and differential expression analysis, we identified many genes associated with schizophrenia risk, including potentially the dopamine D2 receptor short isoform. We found that antipsychotic medication has an extensive influence on caudate gene expression. We constructed caudate nucleus gene expression networks that highlight interactions involving schizophrenia risk. These analyses provide a resource for the study of schizophrenia and insights into risk mechanisms and potential therapeutic targets.

TRIOBP-1 Protein Aggregation Exists in Both Major Depressive Disorder and Schizophrenia, and Can Occur through Two Distinct Regions of the Protein

The presence of proteinopathy, the accumulation of specific proteins as aggregates in neurons, is an emerging aspect of the pathology of schizophrenia and other major mental illnesses. Among the initial proteins implicated in forming such aggregates in these conditions is Trio and F-actin Binding Protein isoform 1 (TRIOBP-1), a ubiquitously expressed protein involved in the stabilization of the actin cytoskeleton. Here we investigate the insolubility of TRIOBP-1, as an indicator of aggregation, in brain samples from 25 schizophrenia patients, 25 major depressive disorder patients and 50 control individuals (anterior cingulate cortex, BA23). Strikingly, insoluble TRIOBP-1 is considerably more prevalent in both of these conditions than in controls, further implicating TRIOBP-1 aggregation in schizophrenia and indicating a role in major depressive disorder. These results were only seen using a high stringency insolubility assay (previously used to study DISC1 and other proteins), but not a lower stringency assay that would be expected to also detect functional, actin-bound TRIOBP-1. Previously, we have also determined that a region of 25 amino acids in the center of this protein is critical for its ability to form aggregates. Here we attempt to refine this further, through the expression of various truncated mutant TRIOBP-1 vectors in neuroblastoma cells and examining their aggregation. In this way, it was possible to narrow down the aggregation-critical region of TRIOBP-1 to just 8 amino acids (333–340 of the 652 amino acid-long TRIOBP-1). Surprisingly our results suggested that a second section of TRIOBP-1 is also capable of independently inducing aggregation: the optionally expressed 59 amino acids at the extreme N-terminus of the protein. As a result, the 597 amino acid long version of TRIOBP-1 (also referred to as “Tara” or “TAP68”) has reduced potential to form aggregates. The presence of insoluble TRIOBP-1 in brain samples from patients, combined with insight into the mechanism of aggregation of TRIOBP-1 and generation of an aggregation-resistant mutant TRIOBP-1 that lacks both these regions, will be of significant use in further investigating the mechanism and consequences of TRIOBP-1 aggregation in major mental illness.

Decoding Shared Versus Divergent Transcriptomic Signatures Across Cortico-Amygdala Circuitry in PTSD and Depressive Disorders

OBJECTIVE

Posttraumatic stress disorder (PTSD) is a debilitating neuropsychiatric disease that is highly comorbid with major depressive disorder (MDD) and bipolar disorder. The overlap in symptoms is hypothesized to stem from partially shared genetics and underlying neurobiological mechanisms. To delineate conservation between transcriptional patterns across PTSD and MDD, the authors examined gene expression in the human cortex and amygdala in these disorders.

METHODS

RNA sequencing was performed in the postmortem brain of two prefrontal cortex regions and two amygdala regions from donors diagnosed with PTSD (N=107) or MDD (N=109) as well as from neurotypical donors (N=109).

RESULTS

The authors identified a limited number of differentially expressed genes (DEGs) specific to PTSD, with nearly all mapping to cortical versus amygdala regions. PTSD-specific DEGs were enriched in gene sets associated with downregulated immune-related pathways and microglia as well as with subpopulations of GABAergic inhibitory neurons. While a greater number of DEGs associated with MDD were identified, most overlapped with PTSD, and only a few were MDD specific. The authors used weighted gene coexpression network analysis as an orthogonal approach to confirm the observed cellular and molecular associations.

CONCLUSIONS

These findings provide supporting evidence for involvement of decreased immune signaling and neuroinflammation in MDD and PTSD pathophysiology, and extend evidence that GABAergic neurons have functional significance in PTSD.

Deep learning predicts DNA methylation regulatory variants in the human brain and elucidates the genetics of psychiatric disorders

There is growing evidence for the role of DNA methylation (DNAm) quantitative trait loci (mQTLs) in the genetics of complex traits, including psychiatric disorders. However, due to extensive linkage disequilibrium (LD) of the genome, it is challenging to identify causal genetic variations that drive DNAm levels by population-based genetic association studies. This limits the utility of mQTLs for fine-mapping risk loci underlying psychiatric disorders identified by genome-wide association studies (GWAS). Here we present INTERACT, a deep learning model that integrates convolutional neural networks with transformer, to predict effects of genetic variations on DNAm levels at CpG sites in the human brain. We show that INTERACT-derived DNAm regulatory variants are not confounded by LD, are concentrated in regulatory genomic regions in the human brain, and are convergent with mQTL evidence from genetic association analysis. We further demonstrate that predicted DNAm regulatory variants are enriched for heritability of brain-related traits and improve polygenic risk prediction for schizophrenia across diverse ancestry samples. Finally, we applied predicted DNAm regulatory variants for fine-mapping schizophrenia GWAS risk loci to identify potential novel risk genes. Our study shows the power of a deep learning approach to identify functional regulatory variants that may elucidate the genetic basis of complex traits.

MCP-1/CCR2 axis inhibition sensitizes the brain microenvironment against melanoma brain metastasis progression

Development of resistance to chemo- and immunotherapies often occurs following treatment of melanoma brain metastasis (MBM). The brain microenvironment (BME), particularly astrocytes, cooperate toward MBM progression by upregulating secreted factors, among which we found that monocyte chemoattractant protein-1 (MCP-1) and its receptors, CCR2 and CCR4, were overexpressed in MBM compared with primary lesions. Among other sources of MCP-1 in the brain, we show that melanoma cells altered astrocyte secretome and evoked MCP-1 expression and secretion, which in turn induced CCR2 expression in melanoma cells, enhancing in vitro tumorigenic properties, such as proliferation, migration, and invasion of melanoma cells. In vivo pharmacological blockade of MCP-1 or molecular knockout of CCR2/CCR4 increased the infiltration of cytotoxic CD8⁺ T cells and attenuated the immunosuppressive phenotype of the BME as shown by decreased infiltration of Tregs and tumor-associated macrophages/microglia in several models of intracranially injected MBM. These in vivo strategies led to decreased MBM outgrowth and prolonged the overall survival of the mice. Our findings highlight the therapeutic potential of inhibiting interactions between BME and melanoma cells for the treatment of this disease.

Analysis of somatic mutations in 131 human brains reveals aging-associated hypermutability

We analyzed 131 human brains (44 neurotypical, 19 with Tourette syndrome, 9 with schizophrenia, and 59 with autism) for somatic mutations after whole genome sequencing to a depth of more than 200×. Typically, brains had 20 to 60 detectable single-nucleotide mutations, but ~6% of brains harbored hundreds of somatic mutations. Hypermutability was associated with age and damaging mutations in genes implicated in cancers and, in some brains, reflected in vivo clonal expansions. Somatic duplications, likely arising during development, were found in ~5% of normal and diseased brains, reflecting background mutagenesis. Brains with autism were associated with mutations creating putative transcription factor binding motifs in enhancer-like regions in the developing brain. The top-ranked affected motifs corresponded to MEIS (myeloid ectopic viral integration site) transcription factors, suggesting a potential link between their involvement in gene regulation and autism.

Variation in TAF1 expression in female carrier induced pluripotent stem cells and human brain ontogeny has implications for adult neostriatum vulnerability in X-linked Dystonia Parkinsonism

X-linked Dystonia-Parkinsonism (XDP) is an inherited, X-linked, adult-onset movement disorder characterized by degeneration in the neostriatum. No therapeutics alter disease progression. The mechanisms underlying regional differences in degeneration and adult onset are unknown. Developing therapeutics requires a deeper understanding of how XDP-relevant features vary in health and disease. XDP is possibly due, in part, to a partial loss of TAF1 function. A disease-specific SINE-VNTR-Alu (SVA) retrotransposon insertion occurs within intron 32 of TAF1, a subunit of TFIID involved in transcription initiation. While all XDP males are usually clinically affected, females are heterozygous carriers generally not manifesting the full syndrome. As a resource for disease modeling, we characterized eight iPSC lines from three XDP female carrier individuals for X chromosome inactivation status and identified clonal lines that express either the wild-type X or XDP haplotype. Furthermore, we characterized XDP-relevant transcript expression in neurotypical humans, and found that SVA-F expression decreases after 30 years of age in the brain and that TAF1 is decreased in most female samples. Uniquely in the caudate nucleus, TAF1 expression is not sexually dimorphic and decreased after adolescence. These findings indicate that regional-, age- and sex-specific mechanisms regulate TAF1, highlighting the importance of disease-relevant models and postmortem tissue. We propose that the decreased TAF1 expression in the adult caudate may synergize with the XDP-specific partial loss of TAF1 function in patients, thereby passing a minimum threshold of TAF1 function, and triggering degeneration in the neostriatum.Significance StatementXDP is an inherited, X-linked, adult-onset movement disorder characterized by degeneration in the neostriatum. No therapeutics alter disease progression. Developing therapeutics requires a deeper understanding of how XDP-relevant features vary in health and disease. XDP is possibly due to a partial loss of TAF1 function. While all XDP males are usually affected, females are heterozygous carriers generally not manifesting the full syndrome. As a resource for disease modeling, we characterized eight stem cell lines from XDP female carrier individuals. Furthermore, we found that, uniquely in the caudate nucleus, TAF1 expression decreases after adolescence in healthy humans. We hypothesize that the decrease of TAF1 after adolescence in human caudate, in general, may underlie the vulnerability of the adult neostriatum in XDP.

Differential expression of NPAS4 in the dorsolateral prefrontal cortex following opioid overdose

Background

Although preclinical models reveal the neurobiological pathways altered through opioid abuse, comprehensive assessments of gene expression in human brain samples are needed. Moreover, less is known about gene expression in response to fatal overdose. The primary goal of the present study was to compare gene expression in the dorsolateral prefrontal cortex (DLPFC) between brain samples of individuals who died of acute opioid intoxication and group-matched controls.

Methods

Postmortem tissue samples of the DLPFC from 153 deceased individuals (Mage  = 35.4; 62% male; 77% European ancestry). Study groups included 72 brain samples from individuals who died of acute opioid intoxication, 53 psychiatric controls, and 28 normal controls. Whole transcriptome RNA-sequencing was used to generate exon counts, and differential expression was tested using limma-voom. Analyses were adjusted for relevant sociodemographic characteristics, technical covariates, and cryptic relatedness using quality surrogate variables. Weighted correlation network analysis and gene set enrichment analyses also were conducted.

Results

Two genes were differentially expressed in opioid samples compared to control samples. The top gene, NPAS4, was downregulated in opioid samples (log2FC = -2.47, adj. p = .049) and has been implicated in opioid, cocaine, and methamphetamine use. Weighted correlation network analysis revealed 15 gene modules associated with opioid overdose, though no intramodular hub genes were related to opioid overdose, nor were pathways related to opioid overdose enriched for differential expression.

Conclusions

Results provide preliminary evidence that NPAS4 is implicated in opioid overdose, and more research is needed to understand its role in opioid abuse and associated outcomes.

Molecular phenotypes associated with antipsychotic drugs in the human caudate nucleus

Antipsychotic drugs are the current first-line of treatment for schizophrenia and other psychotic conditions. However, their molecular effects on the human brain are poorly studied, due to difficulty of tissue access and confounders associated with disease status. Here we examine differences in gene expression and DNA methylation associated with positive antipsychotic drug toxicology status in the human caudate nucleus. We find no genome-wide significant differences in DNA methylation, but abundant differences in gene expression. These gene expression differences are overall quite similar to gene expression differences between schizophrenia cases and controls. Interestingly, gene expression differences based on antipsychotic toxicology are different between brain regions, potentially due to affected cell type differences. We finally assess similarities with effects in a mouse model, which finds some overlapping effects but many differences as well. As a first look at the molecular effects of antipsychotics in the human brain, the lack of epigenetic effects is unexpected, possibly because long term treatment effects may be relatively stable for extended periods.

Amygdala and anterior cingulate transcriptomes from individuals with bipolar disorder reveal downregulated neuroimmune and synaptic pathways

Recent genetic studies have identified variants associated with bipolar disorder (BD), but it remains unclear how brain gene expression is altered in BD and how genetic risk for BD may contribute to these alterations. Here, we obtained transcriptomes from subgenual anterior cingulate cortex and amygdala samples from post-mortem brains of individuals with BD and neurotypical controls, including 511 total samples from 295 unique donors. We examined differential gene expression between cases and controls and the transcriptional effects of BD-associated genetic variants. We found two coexpressed modules that were associated with transcriptional changes in BD: one enriched for immune and inflammatory genes and the other with genes related to the postsynaptic membrane. Over 50% of BD genome-wide significant loci contained significant expression quantitative trait loci (QTL) (eQTL), and these data converged on several individual genes, including SCN2A and GRIN2A. Thus, these data implicate specific genes and pathways that may contribute to the pathology of BP.

Genetics and Brain Transcriptomics of Completed Suicide

OBJECTIVE

The authors sought to study the transcriptomic and genomic features of completed suicide by parsing the method chosen, to capture molecular correlates of the distinctive frame of mind of individuals who die by suicide, while reducing heterogeneity.

METHODS

The authors analyzed gene expression (RNA sequencing) from postmortem dorsolateral prefrontal cortex of patients who died by suicide with violent compared with nonviolent means, nonsuicide patients with the same psychiatric disorders, and a neurotypical group (total N=329). They then examined genomic risk scores (GRSs) for each psychiatric disorder included, and GRSs for cognition (IQ) and for suicide attempt, testing how they predict diagnosis or traits (total N=888).

RESULTS

Patients who died by suicide by violent means showed a transcriptomic pattern remarkably divergent from each of the other patient groups but less from the neurotypical group; consistently, their genomic profile of risk was relatively low for their diagnosed illness as well as for suicide attempt, and relatively high for IQ: they were more similar to the neurotypical group than to other patients. Differentially expressed genes (DEGs) associated with patients who died by suicide by violent means pointed to purinergic signaling in microglia, showing similarities to a genome-wide association study of Drosophila aggression. Weighted gene coexpression network analysis revealed that these DEGs were coexpressed in a context of mitochondrial metabolic activation unique to suicide by violent means.

CONCLUSIONS

These findings suggest that patients who die by suicide by violent means are in part biologically separable from other patients with the same diagnoses, and their behavioral outcome may be less dependent on genetic risk for conventional psychiatric disorders and be associated with an alteration of purinergic signaling and mitochondrial metabolism.

Suicide in Older Adult Men Is Not Related to a Personal History of Participation in Football

Introduction: It is reasonable to estimate that tens of millions of men in the United States played high school football. There is societal concern that participation in football confers risk for later-in-life mental health problems. The purpose of this study is to examine whether there is an association between a personal history of playing high school football and death by suicide. Methods: The subjects were obtained from the Lieber Institute for Brain Development (LIBD) brain donation program in collaboration with the Office of the Medical Examiner at Western Michigan University Homer Stryker MD School of Medicine. Donor history was documented via medical records, mental health records, and telephone interviews with the next-of-kin. Results: The sample included 198 men aged 50 or older (median = 65.0 years, interquartile range = 57-75). There were 34.8% who participated in contact sports during high school (including football), and 29.8% participated in high school football. Approximately one-third of the sample had suicide as their manner of death (34.8%). There was no statistically significant difference in the proportions of suicide as a manner of death among those men with a personal history of playing football compared to men who did not play football or who did not play sports (p = 0.070, Odds Ratio, OR = 0.537). Those who played football were significantly less likely to have a lifetime history of a suicide attempt (p = 0.012, OR = 0.352). Men with mood disorders (p < 0.001, OR = 10.712), substance use disorders (p < 0.020, OR = 2.075), and those with a history of suicide ideation (p < 0.001, OR = 8.038) or attempts (p < 0.001, OR = 40.634) were more likely to have suicide as a manner of death. Moreover, those men with a family history of suicide were more likely to have prior suicide attempts (p = 0.031, OR = 2.153) and to have completed suicide (p = 0.001, OR = 2.927). Discussion: Suicide was related to well-established risk factors such as a personal history of a mood disorder, substance abuse disorder, prior suicide ideation, suicide attempts, and a family history of suicide attempts. This study adds to a steadily growing body of evidence suggesting that playing high school football is not associated with increased risk for suicidality or suicide during adulthood.

Single molecule in situ hybridization reveals distinct localizations of schizophrenia risk-related transcripts SNX19 and AS3MT in human brain

Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) associated with schizophrenia risk. Integration of RNA-sequencing data from postmortem human brains with these risk SNPs identified transcripts associated with increased schizophrenia susceptibility, including a class of exon 9-spliced isoforms of Sorting nexin-19 (SNX19^d9) and an isoform of Arsenic methyltransferase (AS3MT) splicing out exons 2 and 3 (AS3MT^d2d3). However, the biological function of these transcript variants is unclear. Defining the cell types where these risk transcripts are dominantly expressed is an important step to understand function, in prioritizing specific cell types and/or neural pathways in subsequent studies. To identify the cell type-specific localization of SNX19 and AS3MT in the human dorsolateral prefrontal cortex (DLPFC), we used single-molecule in situ hybridization techniques combined with automated quantification and machine learning approaches to analyze 10 postmortem brains of neurotypical individuals. These analyses revealed that both pan-SNX19 and pan-AS3MT were more highly expressed in neurons than non-neurons in layers II/III and VI of DLPFC. Furthermore, pan-SNX19 was preferentially expressed in glutamatergic neurons, while pan-AS3MT was preferentially expressed in GABAergic neurons. Finally, we utilized duplex BaseScope technology, to delineate the localization of SNX19^d9 and AS3MT^d2d3 splice variants, revealing consistent trends in spatial gene expression among pan-transcripts and schizophrenia risk-related transcript variants. These findings demonstrate that schizophrenia risk transcripts have distinct localization patterns in the healthy human brains, and suggest that SNX19 transcripts might disrupt the normal function of glutamatergic neurons, while AS3MT may lead to disturbances in the GABAergic system in the pathophysiology of schizophrenia.

Epigenome-wide study of brain DNA methylation following acute opioid intoxication

BACKGROUND

Opioid abuse poses significant risk to individuals in the United States and epigenetic changes are a leading potential biomarker of opioid abuse. Current evidence, however, is mostly limited to candidate gene analysis in whole blood. To clarify the association between opioid abuse and DNA methylation, we conducted an epigenome-wide analysis of DNA methylation in brain samples of individuals who died from acute opioid intoxication and group-matched controls.

METHODS

Tissue samples were extracted from the dorsolateral prefrontal cortex of 153 deceased individuals (Mage = 35.42; 62 % male; 77 % European ancestry). The study included 72 opioid samples, 53 psychiatric controls, and 28 normal controls. The epigenome-wide analysis was implemented using the Illumina MethylationEPIC BeadChip; analyses adjusted for sociodemographic characteristics, negative control principal components, ancestry principal components, cellular composition, and surrogate variables. Horvath's epigenetic age and Levine's PhenoAge were calculated, and gene set enrichment analyses were performed.

RESULTS

Although no CpG sites survived false-discovery rate correction for multiple testing, 13 sites surpassed a relaxed significance threshold (p < 1.0 × 10-5). One of these sites was located within Netrin-1, a gene implicated in kappa opioid receptor activity. There was an association between opioid use and accelerated PhenoAge (b = 2.24, se = 1.11, p = .045). Gene set enrichment analyses revealed enrichment of differential methylation in GO and KEGG pathways broadly related to substance use.

CONCLUSIONS

Netrin-1 may be associated with opioid overdose, and future research with larger samples across stages of opioid use will elucidate the complex genomics of opioid abuse.

P-selectin axis plays a key role in microglia immunophenotype and glioblastoma progression

Glioblastoma (GB) is a highly invasive type of brain cancer exhibiting poor prognosis. As such, its microenvironment plays a crucial role in its progression. Among the brain stromal cells, the microglia were shown to facilitate GB invasion and immunosuppression. However, the reciprocal mechanisms by which GB cells alter microglia/macrophages behavior are not fully understood. We propose that these mechanisms involve adhesion molecules such as the Selectins family. These proteins are involved in immune modulation and cancer immunity. We show that P-selectin mediates microglia-enhanced GB proliferation and invasion by altering microglia/macrophages activation state. We demonstrate these findings by pharmacological and molecular inhibition of P-selectin which leads to reduced tumor growth and increased survival in GB mouse models. Our work sheds light on tumor-associated microglia/macrophage function and the mechanisms by which GB cells suppress the immune system and invade the brain, paving the way to exploit P-selectin as a target for GB therapy.

Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex

We used the 10x Genomics Visium platform to define the spatial topography of gene expression in the six-layered human dorsolateral prefrontal cortex. We identified extensive layer-enriched expression signatures and refined associations to previous laminar markers. We overlaid our laminar expression signatures on large-scale single nucleus RNA-sequencing data, enhancing spatial annotation of expression-driven clusters. By integrating neuropsychiatric disorder gene sets, we showed differential layer-enriched expression of genes associated with schizophrenia and autism spectrum disorder, highlighting the clinical relevance of spatially defined expression. We then developed a data-driven framework to define unsupervised clusters in spatial transcriptomics data, which can be applied to other tissues or brain regions in which morphological architecture is not as well defined as cortical laminae. Last, we created a web application for the scientific community to explore these raw and summarized data to augment ongoing neuroscience and spatial transcriptomics research ( http://research.libd.org/spatialLIBD ).

Sex differences in the transcription of glutamate transporters in major depression and suicide

BACKGROUND

Accumulating evidence indicates that the glutamate system contributes to the pathophysiology of major depressive disorder (MDD) and suicide. We previously reported higher mRNA expression of glutamate receptors in the dorsolateral prefrontal cortex (DLPFC) of females with MDD.

METHODS

In the current study, we measured the expression of mRNAs encoding glutamate transporters in the DLPFC of MDD subjects who died by suicide (MDD-S, n = 51), MDD non-suicide subjects (MDD-NS, n = 28), and individuals who did not have a history of neurological illness (CTRL, n = 32).

RESULTS

Females but not males with MDD showed higher expression of EAATs and VGLUTs relative to CTRLs. VGLUT expression was significantly higher in the female MDD-S group, relative to the other groups. EAAT expression was lower in the male violent suicides.

LIMITATIONS

This study has limitations common to most human studies, including medication history and demographic differences between the diagnostic groups. We mitigated the effects of confounders by including them as covariates in our analyses.

CONCLUSIONS

We report sex differences in the expression of glutamate transporter genes in the DLPFC in MDD. Increased neuronal glutamate transporter expression may increase synaptic glutamate, leading to neuronal and glial loss in the DLPFC in MDD. These deficits may lower DLPFC activity, impair problem solving and impair executive function in depression, perhaps increasing vulnerability to suicidal behavior. These data add to accumulating support for the hypothesis that glutamatergic transmission is dysregulated in MDD and suicide. Glutamate transporters may be novel targets for the development of rapidly acting antidepressant therapies.

The Subnuclear Distribution of 5-HT1A Receptors in the Human Nucleus of the Solitary Tract and Selected Structures of the Caudal Medulla

The distribution of 5-HT1A receptors in the subnuclei of the human caudal nucleus of solitary tract and adjacent structures in the dorsal vagal complex was studied using [3H]8-OH-DPAT, a highly selective 5-HT1A receptor agonist. The highest binding of the labeled ligand was found in the dorsal motor nucleus of the vagus, followed by the medial, intermediate, and subpostremal subnuclei of the nucleus of solitary tract. Previous animal studies suggest an important role for these structures in the regulation of visceral function, particularly for the gastrointestinal and cardiovascular systems. The results of this study suggest the possibility of an analogous role for 5-HT1A receptors in the regulation of these autonomic pathways in humans as well.

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

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

Association of Missense Mutation in FOLH1 With Decreased NAAG Levels and Impaired Working Memory Circuitry and Cognition

OBJECTIVE

Altering the metabotropic glutamate receptor 3 (mGluR3) by pharmacology or genetics is associated with differences in learning and memory in animals and humans. GRM3 (the gene coding for mGluR3) is also genome-wide associated with risk for schizophrenia. The neurotransmitter N-acetyl-aspartyl-glutamate (NAAG) is the selective endogenous agonist of mGluR3, and increasing NAAG may improve cognition. Glutamate carboxypeptidase II (GCPII), coded by the gene folate hydrolase 1 (FOLH1), regulates the amount of NAAG in the synapse. The goal of this study was to determine the relationship between FOLH1, NAAG levels, measures of human cognition, and neural activity associated with cognition.

METHODS

The effects of genetic variation in FOLH1 on mRNA expression in human brain and NAAG levels using 7-T magnetic resonance spectroscopy (MRS) were measured. NAAG levels and FOLH1 genetic variation were correlated with measures of cognition in subjects with psychosis and unaffected subjects. Additionally, FOLH1 genetic variation was correlated with neural activity during working memory, as measured by functional MRI (fMRI).

RESULTS

A missense mutation in FOLH1 (rs202676 G allele) was associated with increased FOLH1 mRNA in the dorsolateral prefrontal cortex of brains from unaffected subjects and schizophrenia patients. This FOLH1 variant was associated with decreased NAAG levels in unaffected subjects and patients with psychosis. NAAG levels were positively correlated with visual memory performance. Carriers of the FOLH1 variant associated with lower NAAG levels had lower IQ scores. Carriers of this FOLH1 variant had less efficient cortical activity during working memory.

CONCLUSIONS

These data show that higher NAAG levels are associated with better cognition, suggesting that increasing NAAG levels through FOLH1/GCPII inhibition may improve cognition. Additionally, NAAG levels measured by MRS and cortical efficiency during working memory measured by fMRI have the potential to be neuroimaging biomarkers for future clinical trials.

Characterizing the dynamic and functional DNA methylation landscape in the developing human cortex

DNA methylation (DNAm) is a key epigenetic regulator of gene expression across development. The developing prenatal brain is a highly dynamic tissue, but our understanding of key drivers of epigenetic variability across development is limited. We, therefore, assessed genomic methylation at over 39 million sites in the prenatal cortex using whole-genome bisulfite sequencing and found loci and regions in which methylation levels are dynamic across development. We saw that DNAm at these loci was associated with nearby gene expression and enriched for enhancer chromatin states in prenatal brain tissue. Additionally, these loci were enriched for genes associated with neuropsychiatric disorders and genes involved with neurogenesis. We also found autosomal differences in DNAm between the sexes during prenatal development, though these have less clear functional consequences. We lastly confirmed that the dynamic methylation at this critical period is specifically CpG methylation, with generally low levels of CpH methylation. Our findings provide detailed insight into prenatal brain development as well as clues to the pathogenesis of psychiatric traits seen later in life.