Analysis of microisolated frontal cortex excitatory layer III and V pyramidal neurons reveals a neurodegenerative phenotype in individuals with Down syndrome.

We elucidated the molecular fingerprint of vulnerable excitatory neurons within select cortical lamina of individuals with Down syndrome (DS) for mechanistic understanding and therapeutic potential that also informs Alzheimer's disease (AD) pathophysiology. Frontal cortex (BA9) layer III (L3) and layer V (L5) pyramidal neurons were microisolated from postmortem human DS and age- and sex-matched controls (CTR) to interrogate differentially expressed genes (DEGs) and key biological pathways relevant to neurodegenerative programs. We identified > 2300 DEGs exhibiting convergent dysregulation of gene expression in both L3 and L5 pyramidal neurons in individuals with DS versus CTR subjects. DEGs included over 100 triplicated human chromosome 21 genes in L3 and L5 neurons, demonstrating a trisomic neuronal karyotype in both laminae. In addition, thousands of other DEGs were identified, indicating gene dysregulation is not limited to trisomic genes in the aged DS brain, which we postulate is relevant to AD pathobiology. Convergent L3 and L5 DEGs highlighted pertinent biological pathways and identified key pathway-associated targets likely underlying corticocortical neurodegeneration and related cognitive decline in individuals with DS. Select key DEGs were interrogated as potential hub genes driving dysregulation, namely the triplicated DEGs amyloid precursor protein (APP) and superoxide dismutase 1 (SOD1), along with key signaling DEGs including mitogen activated protein kinase 1 and 3 (MAPK1, MAPK3) and calcium calmodulin dependent protein kinase II alpha (CAMK2A), among others. Hub DEGs determined from multiple pathway analyses identified potential therapeutic candidates for amelioration of cortical neuron dysfunction and cognitive decline in DS with translational relevance to AD.

Hippocampal CA1 Pyramidal Neurons Display Sublayer and Circuitry Dependent Degenerative Expression Profiles in Aged Female Down Syndrome Mice.

Background: Individuals with Down syndrome (DS) have intellectual disability and develop Alzheimer's disease (AD) pathology during midlife, particularly in the hippocampal component of the medial temporal lobe memory circuit. However, molecular and cellular mechanisms underlying selective vulnerability of hippocampal CA1 neurons remains a major knowledge gap during DS/AD onset. This is compounded by evidence showing spatial (e.g., deep versus superficial) localization of pyramidal neurons (PNs) has profound effects on activity and innervation within the CA1 region. Objective: We investigated whether there is a spatial profiling difference in CA1 PNs in an aged female DS/AD mouse model. We posit dysfunction may be dependent on spatial localization and innervation patterns within discrete CA1 subfields. Methods: Laser capture microdissection was performed on trisomic CA1 PNs in an established mouse model of DS/AD compared to disomic controls, isolating the entire CA1 pyramidal neuron layer and sublayer microisolations of deep and superficial PNs from the distal CA1 (CA1a) region. Results: RNA sequencing and bioinformatic inquiry revealed dysregulation of CA1 PNs based on spatial location and innervation patterns. The entire CA1 region displayed the most differentially expressed genes (DEGs) in trisomic mice reflecting innate DS vulnerability, while trisomic CA1a deep PNs exhibited fewer but more physiologically relevant DEGs, as evidenced by bioinformatic inquiry. Conclusions: CA1a deep neurons displayed numerous DEGs linked to cognitive functions whereas CA1a superficial neurons, with approximately equal numbers of DEGs, were not linked to pathways of dysregulation, suggesting the spatial location of vulnerable CA1 PNs plays an important role in circuit dissolution.

Single-cell multi-cohort dissection of the schizophrenia transcriptome.

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

Evaluating performance and applications of sample-wise cell deconvolution methods on human brain transcriptomic data.

Sample-wise deconvolution methods estimate cell-type proportions and gene expressions in bulk tissue samples, yet their performance and biological applications remain unexplored, particularly in human brain transcriptomic data. Here, nine deconvolution methods were evaluated with sample-matched data from bulk tissue RNA sequencing (RNA-seq), single-cell/nuclei (sc/sn) RNA-seq, and immunohistochemistry. A total of 1,130,767 nuclei per cells from 149 adult postmortem brains and 72 organoid samples were used. The results showed the best performance of dtangle for estimating cell proportions and bMIND for estimating sample-wise cell-type gene expressions. For eight brain cell types, 25,273 cell-type eQTLs were identified with deconvoluted expressions (decon-eQTLs). The results showed that decon-eQTLs explained more schizophrenia GWAS heritability than bulk tissue or single-cell eQTLs did alone. Differential gene expressions associated with Alzheimer's disease, schizophrenia, and brain development were also examined using the deconvoluted data. Our findings, which were replicated in bulk tissue and single-cell data, provided insights into the biological applications of deconvoluted data in multiple brain disorders.

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

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

Single-cell genomics and regulatory networks for 388 human brains.

Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multiomics datasets into a resource comprising >2.8 million nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550,000 cell type-specific regulatory elements and >1.4 million single-cell expression quantitative trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.

Single-cell genomics and regulatory networks for 388 human brains.

Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet, little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multi-omics datasets into a resource comprising >2.8M nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550K cell-type-specific regulatory elements and >1.4M single-cell expression-quantitative-trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.

Sex differences in brain cell-type specific chromatin accessibility in schizophrenia.

Our understanding of the sex-specific role of the non-coding genome in serious mental illness remains largely incomplete. To address this gap, we explored sex differences in 1,393 chromatin accessibility profiles, derived from neuronal and non-neuronal nuclei of two distinct cortical regions from 234 cases with serious mental illness and 235 controls. We identified sex-specific enhancer-promoter interactions and showed that they regulate genes involved in X-chromosome inactivation (XCI). Examining chromosomal conformation allowed us to identify sex-specific cis- and trans-regulatory domains (CRDs and TRDs). Co-localization of sex-specific TRDs with schizophrenia common risk variants pinpointed male-specific regulatory regions controlling a number of metabolic pathways. Additionally, enhancers from female-specific TRDs were found to regulate two genes known to escape XCI, (XIST and JPX), underlying the importance of TRDs in deciphering sex differences in schizophrenia. Overall, these findings provide extensive characterization of sex differences in the brain epigenome and disease-associated regulomes.

Alzheimer's disease transcriptional landscape in ex-vivo human microglia.

Microglia are resident immune cells of the brain and are implicated in the etiology of Alzheimer's Disease (AD) and other diseases. Yet the cellular and molecular processes regulating their function throughout the course of the disease are poorly understood. Here, we present the transcriptional landscape of primary microglia from 189 human postmortem brains, including 58 healthy aging individuals and 131 with a range of disease phenotypes, including 63 patients representing the full spectrum of clinical and pathological severity of AD. We identified transcriptional changes associated with multiple AD phenotypes, capturing the severity of dementia and neuropathological lesions. Transcript-level analyses identified additional genes with heterogeneous isoform usage and AD phenotypes. We identified changes in gene-gene coordination in AD, dysregulation of co-expression modules, and disease subtypes with distinct gene expression. Taken together, these data further our understanding of the key role of microglia in AD biology and nominate candidates for therapeutic intervention.

Convergence of the dysregulated regulome in schizophrenia with polygenic risk and evolutionarily constrained enhancers.

Enhancers play an essential role in the etiology of schizophrenia; however, the dysregulation of enhancer activity and its impact on the regulome in schizophrenia remains understudied. To address this gap in our knowledge, we assessed enhancer and gene expression in 1,382 brain samples comprising cases with schizophrenia and unaffected controls. Dysregulation of enhancer expression was concordant with changes in gene expression, and was more closely associated with schizophrenia polygenic risk, suggesting that enhancer dysregulation is proximal to the genetic etiology of the disease. Modeling the shared variance of cis-coordinated genes and enhancers revealed a gene regulatory program that was highly associated with genetic vulnerability to schizophrenia. By integrating coordinated factors with evolutionary constraints, we found that enhancers acquired during human evolution are more likely to regulate genes that are implicated in neuropsychiatric disorders and, thus, hold potential as therapeutic targets. Our analysis provides a systematic view of regulome dysregulation in schizophrenia and highlights its convergence with schizophrenia polygenic risk and human-gained enhancers.

Activity-Dependent Transcriptional Program in NGN2+ Neurons Enriched for Genetic Risk for Brain-Related Disorders.

BACKGROUND: Converging evidence from large-scale genetic and postmortem studies highlights the role of aberrant neurotransmission and genetic regulation in brain-related disorders. However, identifying neuronal activity-regulated transcriptional programs in the human brain and understanding how changes contribute to disease remain challenging. METHODS: To better understand how the activity-dependent regulome contributes to risk for brain-related disorders, we profiled the transcriptomic and epigenomic changes following neuronal depolarization in human induced pluripotent stem cell-derived glutamatergic neurons (NGN2) from 6 patients with schizophrenia and 5 control participants. RESULTS: Multiomic data integration associated global patterns of chromatin accessibility with gene expression and identified enhancer-promoter interactions in glutamatergic neurons. Within 1 hour of potassium chloride-induced depolarization, independent of diagnosis, glutamatergic neurons displayed substantial activity-dependent changes in the expression of genes regulating synaptic function. Depolarization-induced changes in the regulome revealed significant heritability enrichment for schizophrenia and Parkinson's disease, adding to mounting evidence that sequence variation within activation-dependent regulatory elements contributes to the genetic risk for brain-related disorders. Gene coexpression network analysis elucidated interactions among activity-dependent and disease-associated genes and pointed to a key driver (NAV3) that interacted with multiple genes involved in axon guidance. CONCLUSIONS: Overall, we demonstrated that deciphering the activity-dependent regulome in glutamatergic neurons reveals novel targets for advanced diagnosis and therapy.