Critical factors in gene expression in postmortem human brain: Focus on studies in schizophrenia

An integrated single-nucleus and spatial transcriptomics atlas reveals the molecular landscape of the human hippocampus

The hippocampus contains many unique cell types, which serve the structure's specialized functions, including learning, memory and cognition. These cells have distinct spatial organization, morphology, physiology, and connectivity, highlighting the importance of transcriptome-wide profiling strategies that retain cytoarchitectural organization. Here, we generated spatially-resolved transcriptomics (SRT) and single-nucleus RNA-sequencing (snRNA-seq) data from adjacent tissue sections of the anterior human hippocampus in ten adult neurotypical donors to define molecular profiles for hippocampal cell types and spatial domains. Using non-negative matrix factorization (NMF) and label transfer, we integrated these data by defining gene expression patterns within the snRNA-seq data and inferring their expression in the SRT data. We identified NMF patterns that captured transcriptional variation across neuronal cell types and indicated that the response of excitatory and inhibitory postsynaptic specializations were prioritized in different SRT spatial domains. We used the NMF and label transfer approach to leverage existing rodent datasets, identifying patterns of activity-dependent transcription and subpopulations of dentate gyrus granule cells in our SRT dataset that may be predisposed to participate in learning and memory ensembles. Finally, we characterized the spatial organization of NMF patterns corresponding to non-cornu ammonis pyramidal neurons and identified snRNA-seq clusters mapping to distinct regions of the retrohippocampus, to three subiculum layers, and to a population of presubiculum neurons. To make this comprehensive molecular atlas accessible to the scientific community, both raw and processed data are freely available, including through interactive web applications.

Integrating gene expression and imaging data across Visium capture areas with visiumStitched

BACKGROUND

Visium is a widely-used spatially-resolved transcriptomics assay available from 10x Genomics. Standard Visium capture areas (6.5mm by 6.5mm) limit the survey of larger tissue structures, but combining overlapping images and associated gene expression data allow for more complex study designs. Current software can handle nested or partial image overlaps, but is designed for merging up to two capture areas, and cannot account for some technical scenarios related to capture area alignment.

RESULTS

We generated Visium data from a postmortem human tissue sample such that two capture areas were partially overlapping and a third one was adjacent. We developed the R/Bioconductor package visiumStitched, which facilitates stitching the images together with Fiji (ImageJ), and constructing SpatialExperiment R objects with the stitched images and gene expression data. visiumStitched constructs an artificial hexagonal array grid which allows seamless downstream analyses such as spatially-aware clustering without discarding data from overlapping spots. Data stitched with visiumStitched can then be interactively visualized with spatialLIBD.

CONCLUSIONS

visiumStitched provides a simple, but flexible framework to handle various multi-capture area study design scenarios. Specifically, it resolves a data processing step without disrupting analysis workflows and without discarding data from overlapping spots. visiumStitched relies on affine transformations by Fiji, which have limitations and are less accurate when aligning against an atlas or other situations. visiumStitched provides an easy-to-use solution which expands possibilities for designing multi-capture area study designs.

Schizophrenia risk-associated SNPs affect expression of microRNA 137 host gene: a postmortem study

Common variants in the MicroRNA 137 host gene MIR137HG and its adjacent gene DPYD have been associated with schizophrenia risk and the latest Psychiatric Genomics Consortium (PGC). Genome-Wide Association Study on schizophrenia has confirmed and extended these findings. To elucidate the association of schizophrenia risk-associated SNPs in this genomic region, we examined the expression of both mature and immature transcripts of the miR-137 host gene (MIR137HG) in the dorsolateral prefrontal cortex (DLPFC) and subgenual anterior cingulate cortex (sgACC) of postmortem brain samples of donors with schizophrenia and psychiatrically-unaffected controls using qPCR and RNA-Seq approaches. No differential expression of miR-137, MIR137HG, or its transcripts was observed. Two schizophrenia risk-associated SNPs identified in the PGC study, rs11165917 (DLPFC: P = 2.0e-16; sgACC: P = 6.4e-10) and rs4274102 (DLPFC: P = 0.036; sgACC: P = 0.002), were associated with expression of the MIR137HG long non-coding RNA transcript MIR137HG-203 (ENST00000602672.2) in individuals of European ancestry. Carriers of the minor (risk) allele of rs11165917 had significantly lower expression of MIR137HG-203 compared with those carrying the major allele. However, we were unable to validate this result by short-read sequencing of RNA extracted from DLPFC or sgACC tissue. This finding suggests that immature transcripts of MIR137HG may contribute to genetic risk for schizophrenia.

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 that underlie the development and progression of AUD remains limited. Here, we investigated AUD-associated DNA methylation changes within and across 2 addiction-relevant brain regions, the nucleus accumbens and dorsolateral prefrontal cortex.

Methods

Illumina HumanMethylation EPIC array data from 119 decedents (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 annotation data and published genetic and epigenetic studies. We also tested for brain region-shared and brain region-specific associations using mixed-effects modeling and assessed implications of these results using public gene expression data from human brain.

Results

At a false discovery rate of ≤.05, we identified 105 unique AUD-associated CpGs (annotated to 120 genes) within and across brain regions. AUD-associated CpGs were enriched in histone marks that tag active promoters, and our strongest signals were specific to a single brain region. Some concordance was found between our results and those of earlier published alcohol use or dependence methylation studies. Of the 120 genes, 23 overlapped with previous genetic associations for substance use behaviors, some of which also overlapped with previous addiction-related methylation studies.

Conclusions

Our findings identify AUD-associated methylation signals and provide evidence of overlap with previous genetic and methylation studies. These signals may constitute predisposing genetic differences or robust methylation changes associated with AUD, although more work is needed to further disentangle the mechanisms that underlie these associations and their implications for AUD.

Genetic regulation of human brain proteome reveals proteins implicated in psychiatric disorders

Psychiatric disorders are highly heritable yet polygenic, potentially involving hundreds of risk genes. Genome-wide association studies have identified hundreds of genomic susceptibility loci with susceptibility to psychiatric disorders; however, the contribution of these loci to the underlying psychopathology and etiology remains elusive. Here we generated deep human brain proteomics data by quantifying 11,608 proteins across 268 subjects using 11-plex tandem mass tag coupled with two-dimensional liquid chromatography-tandem mass spectrometry. Our analysis revealed 788 cis-acting protein quantitative trait loci associated with the expression of 883 proteins at a genome-wide false discovery rate <5%. In contrast to expression at the transcript level and complex diseases that are found to be mainly influenced by noncoding variants, we found protein expression level tends to be regulated by non-synonymous variants. We also provided evidence of 76 shared regulatory signals between gene expression and protein abundance. Mediation analysis revealed that for most (88%) of the colocalized genes, the expression levels of their corresponding proteins are regulated by cis-pQTLs via gene transcription. Using summary data-based Mendelian randomization analysis, we identified 4 proteins and 19 genes that are causally associated with schizophrenia. We further integrated multiple omics data with network analysis to prioritize candidate genes for schizophrenia risk loci. Collectively, our findings underscore the potential of proteome-wide linkage analysis in gaining mechanistic insights into the pathogenesis of psychiatric disorders.

Modeling common and rare genetic risk factors of neuropsychiatric disorders in human induced pluripotent stem cells

Recent genome-wide association studies (GWAS) and whole-exome sequencing of neuropsychiatric disorders, especially schizophrenia, have identified a plethora of common and rare disease risk variants/genes. Translating the mounting human genetic discoveries into novel disease biology and more tailored clinical treatments is tied to our ability to causally connect genetic risk variants to molecular and cellular phenotypes. When combined with the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated (Cas) nuclease-mediated genome editing system, human induced pluripotent stem cell (hiPSC)-derived neural cultures (both 2D and 3D organoids) provide a promising tractable cellular model for bridging the gap between genetic findings and disease biology. In this review, we first conceptualize the advances in understanding the disease polygenicity and convergence from the past decade of iPSC modeling of different types of genetic risk factors of neuropsychiatric disorders. We then discuss the major cell types and cellular phenotypes that are most relevant to neuropsychiatric disorders in iPSC modeling. Finally, we critically review the limitations of iPSC modeling of neuropsychiatric disorders and outline the need for implementing and developing novel methods to scale up the number of iPSC lines and disease risk variants in a systematic manner. Sufficiently scaled-up iPSC modeling and a better functional interpretation of genetic risk variants, in combination with cutting-edge CRISPR/Cas9 gene editing and single-cell multi-omics methods, will enable the field to identify the specific and convergent molecular and cellular phenotypes in precision for neuropsychiatric disorders.

Transcriptomic diversity of amygdalar subdivisions across humans and nonhuman primates

The amygdaloid complex mediates learning, memory, and emotions. Understanding the cellular and anatomical features that are specialized in the amygdala of primates versus other vertebrates requires a systematic, anatomically-resolved molecular analysis of constituent cell populations. We analyzed five nuclear subdivisions of the primate amygdala with single-nucleus RNA sequencing in macaques, baboons, and humans to examine gene expression profiles for excitatory and inhibitory neurons and confirmed our results with single-molecule FISH analysis. We identified distinct subtypes of FOXP2 + interneurons in the intercalated cell masses and protein-kinase C-δ interneurons in the central nucleus. We also establish that glutamatergic, pyramidal-like neurons are transcriptionally specialized within the basal, lateral, or accessory basal nuclei. Understanding the molecular heterogeneity of anatomically-resolved amygdalar neuron types provides a cellular framework for improving existing models of how amygdalar neural circuits contribute to cognition and mental health in humans by using nonhuman primates as a translational bridge.

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

BACKGROUND

The APOE gene is the strongest genetic risk factor for late-onset Alzheimer's Disease (LOAD). However, the gene regulatory mechanisms at this locus remain incompletely characterized.

METHODS

To identify novel AD-linked functional elements within the APOE locus, we integrated SNP variants with multi-omics data from human postmortem brains including 2,179 RNA-seq samples from 3 brain regions and two ancestries (European and African), 667 DNA methylation samples, and ChIP-seq samples. Additionally, we plotted the expression trajectory of APOE transcripts in human brains during development.

RESULTS

We identified an AD-linked APOE transcript (jxn1.2.2) particularly observed in the dorsolateral prefrontal cortex (DLPFC). The APOE jxn1.2.2 transcript is associated with brain neuropathological features, cognitive impairment, and the presence of the APOE4 allele in DLPFC. We prioritized two independent functional SNPs (rs157580 and rs439401) significantly associated with jxn1.2.2 transcript abundance and DNA methylation levels. These SNPs are located within active chromatin regions and affect brain-related transcription factor-binding affinities. The two SNPs shared effects on the jxn1.2.2 transcript between European and African ethnic groups.

CONCLUSION

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

Brain transcriptomic signatures for mood disorders and suicide phenotypes: an anterior insula and subgenual ACC network postmortem study

Mood disorders affect over ten percent of humans, but studies dissecting the brain anatomical and molecular neurobiological mechanisms underlying mood (dys)functions have not consistently identified the patterns of pathological changes in relevant brain regions. Recent studies have identified pathological changes in the anterior insula (Ant-Ins) and subgenual anterior cingulate (sgACC) brain network in mood disorders, in line with this network's role in regulating mood/affective feeling states. Here, we applied whole-tissue RNA-sequencing measures of differentially expressed genes (DEGs) in mood disorders versus (vs.) psychiatrically unaffected controls (controls) to identify postmortem molecular pathological markers for mood disorder phenotypes. Using data-driven factor analysis of the postmortem phenotypic variables to determine relevant sources of population variances, we identified DEGs associated with mood disorder-related diagnostic phenotypes by combining gene co-expression, differential gene expression, and pathway-enrichment analyses. We found downregulation/under expression of inflammatory, and protein synthesis-related genes associated with psychiatric morbidity (i.e., all co-occurring mental disorders and suicide outcomes/death by suicide) in Ant-Ins, in contrasts to upregulation of synaptic membrane and ion channel-related genes with increased psychiatric morbidity in sgACC. Our results identified a preponderance of downregulated metabolic, protein synthesis, inflammatory, and synaptic membrane DEGs associated with suicide outcomes in relation to a factor representing longevity in the Ant-Ins and sgACC (AIAC) network. Our study revealed a critical brain network molecular repertoire for mood disorder phenotypes, including suicide outcomes and longevity, and provides a framework for defining dosage-sensitive (i.e., downregulated vs. upregulated) molecular signatures for mood disorder phenotypic complexity and pathological outcomes.

Integrating gene expression and imaging data across Visium capture areas with visiumStitched

Background

Visium is a widely-used spatially-resolved transcriptomics assay available from 10x Genomics. Standard Visium capture areas (6.5mm by 6.5mm) limit the survey of larger tissue structures, but combining overlapping images and associated gene expression data allow for more complex study designs. Current software can handle nested or partial image overlaps, but is designed for merging up to two capture areas, and cannot account for some technical scenarios related to capture area alignment.

Results

We generated Visium data from a postmortem human tissue sample such that two capture areas were partially overlapping and a third one was adjacent. We developed the R/Bioconductor package visiumStitched, which facilitates stitching the images together with Fiji (ImageJ), and constructing SpatialExperiment R objects with the stitched images and gene expression data. visiumStitched constructs an artificial hexagonal array grid which allows seamless downstream analyses such as spatially-aware clustering without discarding data from overlapping spots. Data stitched with visiumStitched can then be interactively visualized with spatialLIBD.

Conclusions

visiumStitched provides a simple, but flexible framework to handle various multi-capture area study design scenarios. Specifically, it resolves a data processing step without disrupting analysis workflows and without discarding data from overlapping spots. visiumStiched relies on affine transformations by Fiji, which have limitations and are less accurate when aligning against an atlas or other situations. visiumStiched provides an easy-to-use solution which expands possibilities for designing multi-capture area study designs.

Transcriptomic analysis of the human habenula in schizophrenia

Pathophysiology of many neuropsychiatric disorders, including schizophrenia (SCZD), is linked to habenula (Hb) function. While pharmacotherapies and deep brain stimulation targeting the Hb are emerging as promising therapeutic treatments, little is known about the cell type-specific transcriptomic organization of the human Hb or how it is altered in SCZD. Here we define the molecular neuroanatomy of the human Hb and identify transcriptomic changes in individuals with SCZD compared to neurotypical controls. Utilizing Hb-enriched postmortem human brain tissue, we performed single nucleus RNA-sequencing (snRNA-seq; n=7 neurotypical donors) and identified 17 molecularly defined Hb cell types across 16,437 nuclei, including 3 medial and 7 lateral Hb populations, several of which were conserved between rodents and humans. Single molecule fluorescent in situ hybridization (smFISH; n=3 neurotypical donors) validated snRNA-seq Hb cell types and mapped their spatial locations. Bulk RNA-sequencing and cell type deconvolution in Hb-enriched tissue from 35 individuals with SCZD and 33 neurotypical controls yielded 45 SCZD-associated differentially expressed genes (DEGs, FDR < 0.05), with 32 (71%) unique to Hb-enriched tissue. eQTL analysis identified 717 independent SNP-gene pairs (FDR < 0.05), where either the SNP is a SCZD risk variant (16 pairs) or the gene is a SCZD DEG (7 pairs). eQTL and SCZD risk colocalization analysis identified 16 colocalized genes. These results identify topographically organized cell types with distinct molecular signatures in the human Hb and demonstrate unique genetic changes associated with SCZD, thereby providing novel molecular insights into the role of Hb in neuropsychiatric disorders.

One Sentence Summary

Transcriptomic analysis of the human habenula and identification of molecular changes associated with schizophrenia risk and illness state.

Postmortem tissue biomarkers of menopausal transition

The menopausal transition (MT) is associated with an increased risk for many disorders including neurological and mental disorders. Brain imaging studies in living humans show changes in brain metabolism and structure that may contribute to the MT-associated brain disease risk. Although deficits in ovarian hormones have been implicated, cellular and molecular studies of the brain undergoing MT are currently lacking, mostly due to a difficulty in studying MT in postmortem human brain. To enable this research, we explored 39 candidate biomarkers for menopausal status in 42 pre-, peri-, and post-menopausal subjects across three postmortem tissues: blood, the hypothalamus, and pituitary gland. We identified thirteen significant and seven strongest menopausal biomarkers across the three tissues. Using these biomarkers, we generated multi-tissue and tissue-specific composite measures that allow the postmortem identification of the menopausal status across different age ranges, including the "perimenopausal", 45-55-year-old group. Our findings enable the study of cellular and molecular mechanisms underlying increased neuropsychiatric risk during the MT, opening the path for hormone status-informed, precision medicine approach in women's mental health.

Reelin marks cocaine-activated striatal ensembles, promotes neuronal excitability, and regulates cocaine reward

Drugs of abuse activate defined neuronal ensembles in brain reward structures such as the nucleus accumbens (NAc), which are thought to promote the enduring synaptic, circuit, and behavioral consequences of drug exposure. While the molecular and cellular effects arising from experience with drugs like cocaine are increasingly well understood, the mechanisms that sculpt NAc ensemble participation are largely unknown. Here, we leveraged unbiased single-nucleus transcriptional profiling to identify expression of the secreted glycoprotein Reelin (encoded by the Reln gene) as a marker of cocaine-activated neuronal ensembles within the rat NAc. Multiplexed in situ detection confirmed selective expression of the immediate early gene Fos in Reln+ neurons after cocaine experience, and also revealed enrichment of Reln mRNA in Drd1 + medium spiny neurons (MSNs) in both the rat and human brain. Using a novel CRISPR interference strategy enabling selective Reln knockdown in the adult NAc, we observed altered expression of genes linked to calcium signaling, emergence of a transcriptional trajectory consistent with loss of cocaine sensitivity, and a striking decrease in MSN intrinsic excitability. At the behavioral level, loss of Reln prevented cocaine locomotor sensitization, abolished cocaine place preference memory, and decreased cocaine self-administration behavior. Together, these results identify Reelin as a critical mechanistic link between ensemble participation and cocaine-induced behavioral adaptations.

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.

Spatiotemporal analysis of gene expression in the human dentate gyrus reveals age-associated changes in cellular maturation and neuroinflammation

The dentate gyrus of the hippocampus is important for many cognitive functions, including learning, memory, and mood. Here, we investigated age-associated changes in transcriptome-wide spatial gene expression in the human dentate gyrus across the lifespan. Genes associated with neurogenesis and the extracellular matrix were enriched in infants, while gene markers of inhibitory neurons and cell proliferation showed increases and decreases in post-infancy, respectively. While we did not find evidence for neural proliferation post-infancy, we did identify molecular signatures supporting protracted maturation of granule cells. We also identified a wide-spread hippocampal aging signature and an age-associated increase in genes related to neuroinflammation. 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.

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.

Chronic Corticosterone Treatment Decreases Extracellular pH and Increases Lactate Release via PDK4 Upregulation in Cultured Astrocytes

The pathogenesis of stress-related disorders involves aberrant glucocorticoid secretion, and decreased pH and increased lactate in the brain are common phenotypes in several psychiatric disorders. Mice treated with glucocorticoids develop these phenotypes, but it is unclear how glucocorticoids affect brain pH. Therefore, we investigated the effect of corticosterone (CORT), the main glucocorticoid in rodents, on extracellular pH and lactate release in cultured astrocytes, which are the main glial cells that produce lactate in the brain. CORT treatment for one week decreased the extracellular pH and increased the extracellular lactate level via glucocorticoid receptors. CORT also increased the intracellular pyruvate level and upregulated pyruvate dehydrogenase kinase 4 (PDK4), while PDK4 overexpression increased extracellular lactate and decreased the extracellular pH. Furthermore, PDK4 inhibition suppressed the increase in extracellular lactate and the decrease in extracellular pH induced by CORT. These results suggest that increased lactate release via accumulation of intracellular pyruvate in astrocytes by chronic glucocorticoid exposure contributes to decreased brain pH.

Challenges and opportunities to computationally deconvolve heterogeneous tissue with varying cell sizes using single-cell RNA-sequencing datasets

Deconvolution of cell mixtures in "bulk" transcriptomic samples from homogenate human tissue is important for understanding disease pathologies. However, several experimental and computational challenges impede transcriptomics-based deconvolution approaches using single-cell/nucleus RNA-seq reference atlases. Cells from the brain and blood have substantially different sizes, total mRNA, and transcriptional activities, and existing approaches may quantify total mRNA instead of cell type proportions. Further, standards are lacking for the use of cell reference atlases and integrative analyses of single-cell and spatial transcriptomics data. We discuss how to approach these key challenges with orthogonal "gold standard" datasets for evaluating deconvolution methods.

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/.

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.

Data-driven identification of total RNA expression genes for estimation of RNA abundance in heterogeneous cell types highlighted in brain tissue

We define and identify a new class of control genes for next-generation sequencing called total RNA expression genes (TREGs), which correlate with total RNA abundance in cell types of different sizes and transcriptional activity. We provide a data-driven method to identify TREGs from single-cell RNA sequencing data, allowing the estimation of total amount of RNA when restricted to quantifying a limited number of genes. We demonstrate our method in postmortem human brain using multiplex single-molecule fluorescent in situ hybridization and compare candidate TREGs against classic housekeeping genes. We identify AKT3 as a top TREG across five brain regions.

Influence of Alzheimer's disease related neuropathology on local microenvironment gene expression in the human inferior temporal cortex

Neuropathological lesions in the brains of individuals affected with neurodegenerative disorders are hypothesized to trigger molecular and cellular processes that disturb homeostasis of local microenvironments. Here, we applied the 10x Genomics Visium Spatial Proteogenomics (Visium-SPG) platform, which couples spatial gene expression with immunofluorescence protein co-detection, to evaluate its ability to quantify changes in spatial gene expression with respect to amyloid-β (Aβ) and hyperphosphorylated tau (pTau) pathology in post-mortem human brain tissue from individuals with Alzheimer's disease (AD). We identified transcriptomic signatures associated with proximity to Aβ in the human inferior temporal cortex (ITC) during late-stage AD, which we further investigated at cellular resolution with combined immunofluorescence and single molecule fluorescent in situ hybridization (smFISH). The study provides a data analysis workflow for Visium-SPG, and the data represent a proof-of-principal for the power of multi-omic profiling in identifying changes in molecular dynamics that are spatially-associated with pathology in the human brain. We provide the scientific community with web-based, interactive resources to access the datasets of the spatially resolved AD-related transcriptomes at https://research.libd.org/Visium_SPG_AD/.

The influence of tissue pH and RNA integrity number on gene expression of human postmortem brain

Background

Evaluating and controlling confounders are necessary when investigating molecular pathogenesis using human postmortem brain tissue. Particularly, tissue pH and RNA integrity number (RIN) are valuable indicators for controlling confounders. However, the influences of these indicators on the expression of each gene in postmortem brain have not been fully investigated. Therefore, we aimed to assess these effects on gene expressions of human brain samples.

Methods

We isolated total RNA from occipital lobes of 13 patients with schizophrenia and measured the RIN and tissue pH. Gene expression was analyzed and gene sets affected by tissue pH and RIN were identified. Moreover, we examined the functions of these genes by enrichment analysis and upstream regulator analysis.

Results

We identified 2,043 genes (24.7%) whose expressions were highly correlated with pH; 3,004 genes (36.3%) whose expressions were highly correlated with RIN; and 1,293 genes (15.6%) whose expressions were highly correlated with both pH and RIN. Genes commonly affected by tissue pH and RIN were highly associated with energy production and the immune system. In addition, genes uniquely affected by tissue pH were highly associated with the cell cycle, whereas those uniquely affected by RIN were highly associated with RNA processing.

Conclusion

The current study elucidated the influence of pH and RIN on gene expression profiling and identified gene sets whose expressions were affected by tissue pH or RIN. These findings would be helpful in the control of confounders for future postmortem brain studies.

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.

Cellular Diversity in Human Subgenual Anterior Cingulate and Dorsolateral Prefrontal Cortex by Single-Nucleus RNA-Sequencing

Regional cellular heterogeneity is a fundamental feature of the human neocortex; however, details of this heterogeneity are still undefined. We used single-nucleus RNA-sequencing to examine cell-specific transcriptional features in the dorsolateral PFC (DLPFC) and the subgenual anterior cingulate cortex (sgACC), regions implicated in major psychiatric disorders. Droplet-based nuclei-capture and library preparation were performed on replicate samples from 8 male donors without history of psychiatric or neurologic disorder. Unsupervised clustering identified major neural cell classes. Subsequent iterative clustering of neurons further revealed 20 excitatory and 22 inhibitory subclasses. Inhibitory cells were consistently more abundant in the sgACC and excitatory neuron subclusters exhibited considerable variability across brain regions. Excitatory cell subclasses also exhibited greater within-class transcriptional differences between the two regions. We used these molecular definitions to determine which cell classes might be enriched in loci carrying a genetic signal in genome-wide association studies or for differentially expressed genes in mental illness. We found that the heritable signals of psychiatric disorders were enriched in neurons and that, while the gene expression changes detected in bulk-RNA-sequencing studies were dominated by glial cells, some alterations could be identified in specific classes of excitatory and inhibitory neurons. Intriguingly, only two excitatory cell classes exhibited concomitant region-specific enrichment for both genome-wide association study loci and transcriptional dysregulation. In sum, by detailing the molecular and cellular diversity of the DLPFC and sgACC, we were able to generate hypotheses on regional and cell-specific dysfunctions that may contribute to the development of mental illness.SIGNIFICANCE STATEMENT Dysfunction of the subgenual anterior cingulate cortex has been implicated in mood disorders, particularly major depressive disorder, and the dorsolateral PFC, a subsection of the PFC involved in executive functioning, has been implicated in schizophrenia. Understanding the cellular composition of these regions is critical to elucidating the neurobiology underlying psychiatric and neurologic disorders. We studied cell type diversity of the subgenual anterior cingulate cortex and dorsolateral PFC of humans with no neuropsychiatric illness using a clustering analysis of single-nuclei RNA-sequencing data. Defining the transcriptomic profile of cellular subpopulations in these cortical regions is a first step to demystifying the cellular and molecular pathways involved in psychiatric disorders.

Relationships between neurotransmitter receptor densities and expression levels of their corresponding genes in the human hippocampus

Neurotransmitter receptors are key molecules in signal transmission, their alterations are associated with brain dysfunction. Relationships between receptors and their corresponding genes are poorly understood, especially in humans. We combined in vitro receptor autoradiography and RNA sequencing to quantify, in the same tissue samples (7 subjects), the densities of 14 receptors and expression levels of their corresponding 43 genes in the Cornu Ammonis (CA) and dentate gyrus (DG) of human hippocampus. Significant differences in receptor densities between both structures were found only for metabotropic receptors, whereas significant differences in RNA expression levels mostly pertained ionotropic receptors. Receptor fingerprints of CA and DG differ in shapes but have similar sizes; the opposite holds true for their "RNA fingerprints", which represent the expression levels of multiple genes in a single area. In addition, the correlation coefficients between receptor densities and corresponding gene expression levels vary widely and the mean correlation strength was weak-to-moderate. Our results suggest that receptor densities are not only controlled by corresponding RNA expression levels, but also by multiple regionally specific post-translational factors.

Consistency and Variation in Doublecortin and Ki67 Antigen Detection in the Brain Tissue of Different Mammals, including Humans

Recently, a population of "immature" neurons generated prenatally, retaining immaturity for long periods and finally integrating in adult circuits has been described in the cerebral cortex. Moreover, comparative studies revealed differences in occurrence/rate of different forms of neurogenic plasticity across mammals, the "immature" neurons prevailing in gyrencephalic species. To extend experimentation from laboratory mice to large-brained mammals, including humans, it is important to detect cell markers of neurogenic plasticity in brain tissues obtained from different procedures (e.g., post-mortem/intraoperative specimens vs. intracardiac perfusion). This variability overlaps with species-specific differences in antigen distribution or antibody species specificity, making it difficult for proper comparison. In this work, we detect the presence of doublecortin and Ki67 antigen, markers for neuronal immaturity and cell division, in six mammals characterized by widely different brain size. We tested seven commercial antibodies in four selected brain regions known to host immature neurons (paleocortex, neocortex) and newly born neurons (hippocampus, subventricular zone). In selected human brains, we confirmed the specificity of DCX antibody by performing co-staining with fluorescent probe for DCX mRNA. Our results indicate that, in spite of various types of fixations, most differences were due to the use of different antibodies and the existence of real interspecies variation.

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.

Polygenic scores for psychiatric disorders in a diverse postmortem brain tissue cohort

A new era of human postmortem tissue research has emerged thanks to the development of 'omics technologies that measure genes, proteins, and spatial parameters in unprecedented detail. Also newly possible is the ability to construct polygenic scores, individual-level metrics of genetic risk (also known as polygenic risk scores/PRS), based on genome-wide association studies, GWAS. Here, we report on clinical, educational, and brain gene expression correlates of polygenic scores in ancestrally diverse samples from the Human Brain Collection Core (HBCC). Genotypes from 1418 donors were subjected to quality control filters, imputed, and used to construct polygenic scores. Polygenic scores for schizophrenia predicted schizophrenia status in donors of European ancestry (p = 4.7 × 10^-8, 17.2%) and in donors with African ancestry (p = 1.6 × 10^-5, 10.4% of phenotypic variance explained). This pattern of higher variance explained among European ancestry samples was also observed for other psychiatric disorders (depression, bipolar disorder, substance use disorders, anxiety disorders) and for height, body mass index, and years of education. For a subset of 223 samples, gene expression from dorsolateral prefrontal cortex (DLPFC) was available through the CommonMind Consortium. In this subgroup, schizophrenia polygenic scores also predicted an aggregate gene expression score for schizophrenia (European ancestry: p = 0.0032, African ancestry: p = 0.15). Overall, polygenic scores performed as expected in ancestrally diverse samples, given historical biases toward use of European ancestry samples and variable predictive power of polygenic scores across phenotypes. The transcriptomic results reported here suggest that inherited schizophrenia genetic risk influences gene expression, even in adulthood. For future research, these and additional polygenic scores are being made available for analyses, and for selecting samples, using postmortem tissue from the Human Brain Collection Core.

The miR-124-AMPAR pathway connects polygenic risks with behavioral changes shared between schizophrenia and bipolar disorder

Schizophrenia (SZ) and bipolar disorder (BP) are highly heritable major psychiatric disorders that share a substantial portion of genetic risk as well as their clinical manifestations. This raises a fundamental question of whether, and how, common neurobiological pathways translate their shared polygenic risks into shared clinical manifestations. This study shows the miR-124-3p-AMPAR pathway as a key common neurobiological mediator that connects polygenic risks with behavioral changes shared between these two psychotic disorders. We discovered the upregulation of miR-124-3p in neuronal cells and the postmortem prefrontal cortex from both SZ and BP patients. Intriguingly, the upregulation is associated with the polygenic risks shared between these two disorders. Seeking mechanistic dissection, we generated a mouse model that upregulates miR-124-3p in the medial prefrontal cortex. We demonstrated that the upregulation of miR-124-3p increases GRIA2-lacking calcium-permeable AMPARs and perturbs AMPAR-mediated excitatory synaptic transmission, leading to deficits in the behavioral dimensions shared between SZ and BP.

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.

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.

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.

Immune-Related Genomic Schizophrenic Subtyping Identified in DLPFC Transcriptome

Well-documented evidence of the physiologic, genetic, and behavioral heterogeneity of schizophrenia suggests that diagnostic subtyping may clarify the underlying pathobiology of the disorder. Recent studies have demonstrated that increased inflammation may be a prominent feature of a subset of schizophrenics. However, these findings are inconsistent, possibly due to evaluating schizophrenics as a single group. In this study, we segregated schizophrenic patients into two groups ("Type 1", "Type 2") by their gene expression in the dorsolateral prefrontal cortex and explored biological differences between the subgroups. The study included post-mortem tissue samples that were sequenced in multiple, publicly available gene datasets using different sequencing methods. To evaluate the role of inflammation, the expression of genes in multiple components of neuroinflammation were examined: complement cascade activation, glial cell activation, pro-inflammatory mediator secretion, blood-brain barrier (BBB) breakdown, chemokine production and peripheral immune cell infiltration. The Type 2 schizophrenics showed widespread abnormal gene expression across all the neuroinflammation components that was not observed in Type 1 schizophrenics. Our results demonstrate the importance of separating schizophrenic patients into their molecularly defined subgroups and provide supporting evidence for the involvement of the immune-related pathways in a schizophrenic subset.

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.

Brain transcriptomic profiling reveals common alterations across neurodegenerative and psychiatric disorders

Neurodegenerative and neuropsychiatric disorders (ND-NPs) are multifactorial, polygenic and complex behavioral phenotypes caused by brain abnormalities. Large-scale collaborative efforts have tried to identify the genetic architecture of these conditions. However, the specific and shared underlying molecular pathobiology of brain illnesses is not clear. Here, we examine transcriptome-wide characterization of eight conditions, using a total of 2,633 post-mortem brain samples from patients with Alzheimer’s disease (AD), Parkinson’s disease (PD), Progressive Supranuclear Palsy (PSP), Pathological Aging (PA), Autism Spectrum Disorder (ASD), Schizophrenia (Scz), Major Depressive Disorder (MDD), and Bipolar Disorder (BP)–in comparison with 2,078 brain samples from matched control subjects.

Similar transcriptome alterations were observed between NDs and NPs with the top correlations obtained between Scz-BP, ASD-PD, AD-PD, and Scz-ASD. Region-specific comparisons also revealed shared transcriptome alterations in frontal and temporal lobes across NPs and NDs. Co-expression network analysis identified coordinated dysregulations of cell-type-specific modules across NDs and NPs. This study provides a transcriptomic framework to understand the molecular alterations of NPs and NDs through their shared- and specific gene expression in the brain.

The role of mitochondria in the pathophysiology of schizophrenia: A critical review of the evidence focusing on mitochondrial complex one

There has been increasing interest in the role of mitochondrial dysfunction in the pathophysiology of schizophrenia. Mitochondrial complex one (MCI) dysfunction may represent a mechanism linking bioenergetic impairment with the alterations in dopamine signalling, glutamatergic dysfunction, and oxidative stress found in the disorder. New lines of evidence from novel approaches make it timely to review evidence for mitochondrial involvement in schizophrenia, with a specific focus on MCI. The most consistent findings in schizophrenia relative to controls are reductions in expression of MCI subunits in post-mortem brain tissue (Cohen's d> 0.8); reductions in MCI function in post-mortem brains (d> 0.7); and reductions in neural glucose utilisation (d= 0.3 to 0.6). Antipsychotics may affect glucose utilisation, and, at least in vitro, affect MC1. The findings overall are consistent with MCI dysfunction in schizophrenia, but also highlight the need for in vivo studies to determine the link between MCI dysfunction and symptoms in patients. If new imaging tools confirm MCI dysfunction in the disease, this could pave the way for new treatments targeting this enzyme.

Single-nucleus transcriptome analysis reveals cell-type-specific molecular signatures across reward circuitry in the human brain

Single-cell gene expression technologies are powerful tools to study cell types in the human brain, but efforts have largely focused on cortical brain regions. We therefore created a single-nucleus RNA-sequencing resource of 70,615 high-quality nuclei to generate a molecular taxonomy of cell types across five human brain regions that serve as key nodes of the human brain reward circuitry: nucleus accumbens, amygdala, subgenual anterior cingulate cortex, hippocampus, and dorsolateral prefrontal cortex. We first identified novel subpopulations of interneurons and medium spiny neurons (MSNs) in the nucleus accumbens and further characterized robust GABAergic inhibitory cell populations in the amygdala. Joint analyses across the 107 reported cell classes revealed cell-type substructure and unique patterns of transcriptomic dynamics. We identified discrete subpopulations of D1- and D2-expressing MSNs in the nucleus accumbens to which we mapped cell-type-specific enrichment for genetic risk associated with both psychiatric disease and addiction.

Developmental Profile of Psychiatric Risk Associated With Voltage-Gated Cation Channel Activity

BACKGROUND

Recent breakthroughs in psychiatric genetics have implicated biological pathways onto which genetic risk for psychiatric disorders converges. However, these studies do not reveal the developmental time point(s) at which these pathways are relevant.

METHODS

We aimed to determine the relationship between psychiatric risk and developmental gene expression relating to discrete biological pathways. We used postmortem RNA sequencing data (BrainSeq and BrainSpan) from brain tissue at multiple prenatal and postnatal time points, with summary statistics from recent genome-wide association studies of schizophrenia, bipolar disorder, and major depressive disorder. We prioritized gene sets for overall enrichment of association with each disorder and then tested the relationship between the association of their constituent genes with their relative expression at each developmental stage.

RESULTS

We observed relationships between the expression of genes involved in voltage-gated cation channel activity during early midfetal, adolescence, and early adulthood time points and association with schizophrenia and bipolar disorder, such that genes more strongly associated with these disorders had relatively low expression during early midfetal development and higher expression during adolescence and early adulthood. The relationship with schizophrenia was strongest for the subset of genes related to calcium channel activity, while for bipolar disorder, the relationship was distributed between calcium and potassium channel activity genes.

CONCLUSIONS

Our results indicate periods during development when biological pathways related to the activity of calcium and potassium channels may be most vulnerable to the effects of genetic variants conferring risk for psychiatric disorders. Furthermore, they indicate key time points and potential targets for disorder-specific therapeutic interventions.

Genome-wide sequencing-based identification of methylation quantitative trait loci and their role in schizophrenia risk

DNA methylation (DNAm) is an epigenetic regulator of gene expression and a hallmark of gene-environment interaction. Using whole-genome bisulfite sequencing, we have surveyed DNAm in 344 samples of human postmortem brain tissue from neurotypical subjects and individuals with schizophrenia. We identify genetic influence on local methylation levels throughout the genome, both at CpG sites and CpH sites, with 86% of SNPs and 55% of CpGs being part of methylation quantitative trait loci (meQTLs). These associations can further be clustered into regions that are differentially methylated by a given SNP, highlighting the genes and regions with which these loci are epigenetically associated. These findings can be used to better characterize schizophrenia GWAS-identified variants as epigenetic risk variants. Regions differentially methylated by schizophrenia risk-SNPs explain much of the heritability associated with risk loci, despite covering only a fraction of the genomic space. We provide a comprehensive, single base resolution view of association between genetic variation and genomic methylation, and implicate schizophrenia GWAS-associated variants as influencing the epigenetic plasticity of the brain.

The authors provide a comprehensive, single base resolution view of association between genetic variation and DNA methylation in human brain. They also show that heritability attributed to schizophrenia GWAS-associated variants reflects the epigenetic plasticity of the brain.

Network modules linking expression and methylation in prefrontal cortex of schizophrenia

Tremendous work has demonstrated the critical roles of genetics, epigenetics as well as their interplay in brain transcriptional regulations in the pathology of schizophrenia (SZ). There is great success currently in the dissection of the genetic components underlying risk-conferring transcriptomic networks. However, the study of regulating effect of epigenetics in the etiopathogenesis of SZ still faces many challenges. In this work, we investigated DNA methylation and gene expression from the dorsolateral prefrontal cortex (DLPFC) region of schizophrenia patients and healthy controls using weighted correlation network approach. We identified and replicated two expression and two methylation modules significantly associated with SZ. Among them, one pair of expression and methylation modules were significantly overlapped in the module genes which were significantly enriched in astrocyte-associated functional pathways, and specifically expressed in astrocytes. Another two linked expression-methylation module pairs were involved ageing process with module genes mostly related to oligodendrocyte development and myelination, and specifically expressed in oligodendrocytes. Further examination of underlying quantitative trait loci (QTLs) showed significant enrichment in genetic risk of most psychiatric disorders for expression QTLs but not for methylation QTLs. These results support the coherence between methylation and gene expression at the network level, and suggest a combinatorial effect of genetics and epigenetics in regulating gene expression networks specific to glia cells in relation to SZ and ageing process.

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 (SNX19d9) and an isoform of Arsenic methyltransferase (AS3MT) splicing out exons 2 and 3 (AS3MTd2d3). 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 SNX19d9 and AS3MTd2d3 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.

Transcription Factor Motifs Associated with Anterior Insula Gene Expression Underlying Mood Disorder Phenotypes

Mood disorders represent a major cause of morbidity and mortality worldwide but the brain-related molecular pathophysiology in mood disorders remains largely undefined. Because the anterior insula is reduced in volume in patients with mood disorders, RNA was extracted from the anterior insula postmortem anterior insula of mood disorder samples and compared with unaffected controls for RNA-sequencing identification of differentially expressed genes (DEGs) in (a) bipolar disorder (BD; n = 37) versus (vs.) controls (n = 33), and (b) major depressive disorder (MDD n = 30) vs. controls, and (c) low vs. high axis I comorbidity (a measure of cumulative psychiatric disease burden). Given the regulatory role of transcription factors (TFs) in gene expression via specific-DNA-binding domains (motifs), we used JASPAR TF binding database to identify TF-motifs. We found that DEGs in BD vs. controls, MDD vs. controls, and high vs. low axis I comorbidity were associated with TF-motifs that are known to regulate expression of toll-like receptor genes, cellular homeostatic-control genes, and genes involved in embryonic, cellular/organ, and brain development. Robust imaging-guided transcriptomics by using meta-analytic imaging results to guide independent postmortem dissection for RNA-sequencing was applied by targeting the gray matter volume reduction in the anterior insula in mood disorders, to guide independent postmortem identification of TF motifs regulating DEG. Our findings of TF-motifs that regulate the expression of immune, cellular homeostatic-control, and developmental genes provide novel information about the hierarchical relationship between gene regulatory networks, the TFs that control them, and proximate underlying neuroanatomical phenotypes in mood disorders.

Cortical expression of the RAPGEF1 gene in schizophrenia: investigating regional differences and suicide

Rap guanine nucleotide exchange factor 1 (RAPGEF1) is involved in cell adhesion and neuronal migration. Previously we found lower RAPGEF1 mRNA levels in Brodmann's area (BA) 9 in subjects with schizophrenia compared to controls. This study aimed to determine whether RAPGEF1 expression was altered in other brain regions implicated in schizophrenia and whether this was associated with suicide. Using qPCR, we measured the levels of RAPGEF1 in post-mortem BA 8 and 44 from 27 subjects with schizophrenia and 26 non-psychiatric control subjects. To address the effect of antipsychotic treatments, Rapgef1 mRNA levels were measured in the cortex from rats treated with typical antipsychotic drugs. There was no difference in RAPGEF1 normalised relative expression levels in BA 8 or 44. However, in BA 8, schizophrenia subjects had higher raw Ct RAPGEF1 levels compared to controls. There were higher RAPGEF1 levels in suicide completers compared to non-suicide schizophrenia subjects in BA 8. Rapgef1 expression levels in the rat cortex did not vary with antipsychotic treatment. Our findings suggest changes in RAPGEF1 expression may be limited to the dorsolateral prefrontal cortex from subjects with schizophrenia. Further investigation of the function of RAPGEF1 may lead to a greater understanding of the pathophysiology of schizophrenia.

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 ).

Correlation of cerebellar granular layer autolysis with ante-mortem systemic acid-base status

Research in neuroscience relies heavily upon postmortem human brain tissue. Cerebellar granular layer autolysis (GLA) is a surrogate marker for the quality of such tissue and suitability for molecular analysis. GLA is associated with reduced brain tissue pH. The aim of this study was to assess correlation of GLA with premortem systemic acid-base status. This is a retrospective study in which 62 consecutive adult autopsy cases were included. Sections of cerebellum were reviewed microscopically for presence of GLA. Autolysis was graded as negative, grade 1, grade 2, and grade 3. Medical records were reviewed for arterial blood gas analysis. Postmortem interval was recorded. 23 of 62 cases showed GLA. Of the 23 patients with autolysis, 22 were acidotic and 1 was alkalotic. Of these 23 cases, 15 had metabolic acidosis, 4 had respiratory acidosis, 3 had combined acidosis and 1 had respiratory alkalosis. There was no statistically significant difference in postmortem interval between the two groups. 10 cases with grade 3 autolysis had mean pH of 7.13, 7 cases with grade 2 autolysis had mean pH of 7.23 and in 6 cases with grade 1 autolysis the mean pH was 7.2. Overall, the mean pH in patients with GLA was 7.19, and in the non-autolytic cases the mean pH was 7.28 (P < 0.05). There was no correlation between the degree of acidosis and severity of autolysis. GLA is associated with premortem systemic acidosis, and premortem systemic alkalosis is associated with the absence of GLA. Premortem acid-base status may serve as an additional quality indicator for assessment of tissue for research.