Alzheimer's disease risk allele of PICALM causes detrimental lipid droplets in microglia.

Despite genome-wide association studies of late-onset Alzheimer's disease (LOAD) having identified many genetic risk loci1-6, the underlying disease mechanisms remain largely unknown. Determining causal disease variants and their LOAD-relevant cellular phenotypes has been a challenge. Leveraging our approach for identifying functional GWAS risk variants showing allele-specific open chromatin (ASoC)7, we systematically identified putative causal LOAD risk variants in human induced pluripotent stem cells (iPSC)-derived neurons, astrocytes, and microglia (MG) and linked PICALM risk allele to a previously unappreciated MG-specific role of PICALM in lipid droplet (LD) accumulation. ASoC mapping uncovered functional risk variants for 26 LOAD risk loci, mostly MG-specific. At the MG-specific PICALM locus, the LOAD risk allele of rs10792832 reduced transcription factor (PU.1) binding and PICALM expression, impairing the uptake of amyloid beta (Aß) and myelin debris. Interestingly, MG with PICALM risk allele showed transcriptional enrichment of pathways for cholesterol synthesis and LD formation. Genetic and pharmacological perturbations of MG further established a causal link between the reduced PICALM expression, LD accumulation, and phagocytosis deficits. Our work elucidates the selective LOAD vulnerability in microglia for the PICALM locus through detrimental LD accumulation, providing a neurobiological basis that can be exploited for developing novel clinical interventions.

Scaled and Efficient Derivation of Loss of Function Alleles in Risk Genes for Neurodevelopmental and Psychiatric Disorders in Human iPSC.

Translating genetic findings for neurodevelopmental and psychiatric disorders (NPD) into actionable disease biology would benefit from large-scale and unbiased functional studies of NPD genes. Leveraging the cytosine base editing (CBE) system, here we developed a pipeline for clonal loss-of-function (LoF) allele mutagenesis in human induced pluripotent stem cells (hiPSCs) by introducing premature stop-codons (iSTOP) that lead to mRNA nonsense-mediated-decay (NMD) or protein truncation. We tested the pipeline for 23 NPD genes on 3 hiPSC lines and achieved highly reproducible, efficient iSTOP editing in 22 NPD genes. Using RNAseq, we confirmed their pluripotency, absence of chromosomal abnormalities, and NMD. Interestingly, for three schizophrenia risk genes (SETD1A, TRIO, CUL1), despite the high efficiency of base editing, we only obtained heterozygous LoF alleles, suggesting their essential roles for cell growth. We replicated the reported neural phenotypes of SHANK3-haploinsufficiency and found CUL1-LoF reduced neurite branches and synaptic puncta density. This iSTOP pipeline enables a scaled and efficient LoF mutagenesis of NPD genes, yielding an invaluable shareable resource.

Brain Lipids and Lipid Droplet Dysregulation in Alzheimer's Disease and Neuropsychiatric Disorders.

Background: Lipids are essential components of the structure and for the function of brain cells. The intricate balance of lipids, including phospholipids, glycolipids, cholesterol, cholesterol ester, and triglycerides, is crucial for maintaining normal brain function. The roles of lipids and lipid droplets and their relevance to neurodegenerative and neuropsychiatric disorders (NPDs) remain largely unknown. Summary: Here, we reviewed the basic role of lipid components as well as a specific lipid organelle, lipid droplets, in brain function, highlighting the potential impact of altered lipid metabolism in the pathogenesis of Alzheimer's disease (AD) and NDPs. Key Messages: Brain lipid dysregulation plays a pivotal role in the pathogenesis and progression of neurodegenerative and NPDs including AD and schizophrenia. Understanding the cell type-specific mechanisms of lipid dysregulation in these diseases is crucial for identifying better diagnostic biomarkers and for developing therapeutic strategies aiming at restoring lipid homeostasis.

Multiple genes in a single GWAS risk locus synergistically mediate aberrant synaptic development and function in human neurons.

The mechanistic tie between genome-wide association study (GWAS)-implicated risk variants and disease-relevant cellular phenotypes remains largely unknown. Here, using human induced pluripotent stem cell (hiPSC)-derived neurons as a neurodevelopmental model, we identify multiple schizophrenia (SZ) risk variants that display allele-specific open chromatin (ASoC) and are likely to be functional. Editing the strongest ASoC SNP, rs2027349, near vacuolar protein sorting 45 homolog (VPS45) alters the expression of VPS45, lncRNA AC244033.2, and a distal gene, C1orf54. Notably, the transcriptomic changes in neurons are associated with SZ and other neuropsychiatric disorders. Neurons carrying the risk allele exhibit increased dendritic complexity and hyperactivity. Interestingly, individual/combinatorial gene knockdown shows that these genes alter cellular phenotypes in a non-additive synergistic manner. Our study reveals that multiple genes at a single GWAS risk locus mediate a compound effect on neural function, providing a mechanistic link between a non-coding risk variant and disease-related cellular phenotypes.

Excitatory Dysfunction Drives Network and Calcium Handling Deficits in 16p11.2 Duplication Schizophrenia Induced Pluripotent Stem Cell-Derived Neurons.

BACKGROUND: Schizophrenia (SCZ) is a debilitating psychiatric disorder with a large genetic contribution; however, its neurodevelopmental substrates remain largely unknown. Modeling pathogenic processes in SCZ using human induced pluripotent stem cell-derived neurons (iNs) has emerged as a promising strategy. Copy number variants confer high genetic risk for SCZ, with duplication of the 16p11.2 locus increasing the risk 14.5-fold. METHODS: To dissect the contribution of induced excitatory neurons (iENs) versus GABAergic (gamma-aminobutyric acidergic) neurons (iGNs) to SCZ pathophysiology, we induced iNs from CRISPR (clustered regularly interspaced short palindromic repeats)-Cas9 isogenic and SCZ patient-derived induced pluripotent stem cells and analyzed SCZ-related phenotypes in iEN monocultures and iEN/iGN cocultures. RESULTS: In iEN/iGN cocultures, neuronal firing and synchrony were reduced at later, but not earlier, stages of in vitro development. These were fully recapitulated in iEN monocultures, indicating a primary role for iENs. Moreover, isogenic iENs showed reduced dendrite length and deficits in calcium handling. iENs from 16p11.2 duplication-carrying patients with SCZ displayed overlapping deficits in network synchrony, dendrite outgrowth, and calcium handling. Transcriptomic analysis of both iEN cohorts revealed molecular markers of disease related to the glutamatergic synapse, neuroarchitecture, and calcium regulation. CONCLUSIONS: Our results indicate the presence of 16p11.2 duplication-dependent alterations in SCZ patient-derived iENs. Transcriptomics and cellular phenotyping reveal overlap between isogenic and patient-derived iENs, suggesting a central role of glutamatergic, morphological, and calcium dysregulation in 16p11.2 duplication-mediated pathogenesis. Moreover, excitatory dysfunction during early neurodevelopment is implicated as the basis of SCZ pathogenesis in 16p11.2 duplication carriers. Our results support network synchrony and calcium handling as outcomes directly linked to this genetic risk variant.

Human stem cell modeling of neuropsychiatric disorders: from polygenicity to convergence.

Neuropsychiatric disorders (NPD) are prevalent and devastating, posing an enormous socioeconomic burden to modern society. Recent genetic studies of NPD have identified a plethora of common genetic risk variants with small effect sizes and rare risk variants of high penetrance. While exciting, there is a pressing need to translate these genetic discoveries into better understanding of disease biology and more tailored clinical interventions. Human induced pluripotent stem cell (hiPSC)-derived 2D and 3D neural cultures are becoming a promising cellular model for bridging the gap between genetic findings and disease biology for NPD. Leveraging the accessibility of patient biospecimen to convert into stem cells and the power of genome editing technology to engineer disease risk variants, hiPSC model holds the promise to disentangle the disease polygenicity, model genetic interaction with environmental factors, and uncover convergent gene pathways that may be targeted for more tailored clinical intervention.

Function and development of interneurons involved in brain tissue oxygen regulation.

The regulation of oxygen in brain tissue is one of the most important fundamental questions in neuroscience and medicine. The brain is a metabolically demanding organ, and its health directly depends on maintaining oxygen concentrations within a relatively narrow range that is both sufficiently high to prevent hypoxia, and low enough to restrict the overproduction of oxygen species. Neurovascular interactions, which are responsible for oxygen delivery, consist of neuronal and glial components. GABAergic interneurons play a particularly important role in neurovascular interactions. The involvement of interneurons extends beyond the perspective of inhibition, which prevents excessive neuronal activity and oxygen consumption, and includes direct modulation of the microvasculature depending upon their sub-type. Namely, nitric oxide synthase-expressing (NOS), vasoactive intestinal peptide-expressing (VIP), and somatostatin-expressing (SST) interneurons have shown modulatory effects on microvessels. VIP interneurons are known to elicit vasodilation, SST interneurons typically cause vasoconstriction, and NOS interneurons have to propensity to induce both effects. Given the importance and heterogeneity of interneurons in regulating local brain tissue oxygen concentrations, we review their differing functions and developmental trajectories. Importantly, VIP and SST interneurons display key developmental milestones in adolescence, while NOS interneurons mature much earlier. The implications of these findings point to different periods of critical development of the interneuron-mediated oxygen regulatory systems. Such that interference with normal maturation processes early in development may effect NOS interneuron neurovascular interactions to a greater degree, while insults later in development may be more targeted toward VIP- and SST-mediated mechanisms of oxygen regulation.

Loss of function of OTUD7A in the schizophrenia- associated 15q13.3 deletion impairs synapse development and function in human neurons.

Identifying causative gene(s) within disease-associated large genomic regions of copy-number variants (CNVs) is challenging. Here, by targeted sequencing of genes within schizophrenia (SZ)-associated CNVs in 1,779 SZ cases and 1,418 controls, we identified three rare putative loss-of-function (LoF) mutations in OTU deubiquitinase 7A (OTUD7A) within the 15q13.3 deletion in cases but none in controls. To tie OTUD7A LoF with any SZ-relevant cellular phenotypes, we modeled the OTUD7A LoF mutation, rs757148409, in human induced pluripotent stem cell (hiPSC)-derived induced excitatory neurons (iNs) by CRISPR-Cas9 engineering. The mutant iNs showed a ∼50% decrease in OTUD7A expression without undergoing nonsense-mediated mRNA decay. The mutant iNs also exhibited marked reduction of dendritic complexity, density of synaptic proteins GluA1 and PSD-95, and neuronal network activity. Congruent with the neuronal phenotypes in mutant iNs, our transcriptomic analysis showed that the set of OTUD7A LoF-downregulated genes was enriched for those relating to synapse development and function and was associated with SZ and other neuropsychiatric disorders. These results suggest that OTUD7A LoF impairs synapse development and neuronal function in human neurons, providing mechanistic insight into the possible role of OTUD7A in driving neuropsychiatric phenotypes associated with the 15q13.3 deletion.

Annotating functional effects of non-coding variants in neuropsychiatric cell types by deep transfer learning.

Genomewide association studies (GWAS) have identified a large number of loci associated with neuropsychiatric traits, however, understanding the molecular mechanisms underlying these loci remains difficult. To help prioritize causal variants and interpret their functions, computational methods have been developed to predict regulatory effects of non-coding variants. An emerging approach to variant annotation is deep learning models that predict regulatory functions from DNA sequences alone. While such models have been trained on large publicly available dataset such as ENCODE, neuropsychiatric trait-related cell types are under-represented in these datasets, thus there is an urgent need of better tools and resources to annotate variant functions in such cellular contexts. To fill this gap, we collected a large collection of neurodevelopment-related cell/tissue types, and trained deep Convolutional Neural Networks (ResNet) using such data. Furthermore, our model, called MetaChrom, borrows information from public epigenomic consortium to improve the accuracy via transfer learning. We show that MetaChrom is substantially better in predicting experimentally determined chromatin accessibility variants than popular variant annotation tools such as CADD and delta-SVM. By combining GWAS data with MetaChrom predictions, we prioritized 31 SNPs for Schizophrenia, suggesting potential risk genes and the biological contexts where they act. In summary, MetaChrom provides functional annotations of any DNA variants in the neuro-development context and the general method of MetaChrom can also be extended to other disease-related cell or tissue types.

BIN1 is a key regulator of proinflammatory and neurodegeneration-related activation in microglia.

BACKGROUND: The BIN1 locus contains the second-most significant genetic risk factor for late-onset Alzheimer's disease. BIN1 undergoes alternate splicing to generate tissue- and cell-type-specific BIN1 isoforms, which regulate membrane dynamics in a range of crucial cellular processes. Whilst the expression of BIN1 in the brain has been characterized in neurons and oligodendrocytes in detail, information regarding microglial BIN1 expression is mainly limited to large-scale transcriptomic and proteomic data. Notably, BIN1 protein expression and its functional roles in microglia, a cell type most relevant to Alzheimer's disease, have not been examined in depth. METHODS: Microglial BIN1 expression was analyzed by immunostaining mouse and human brain, as well as by immunoblot and RT-PCR assays of isolated microglia or human iPSC-derived microglial cells. Bin1 expression was ablated by siRNA knockdown in primary microglial cultures in vitro and Cre-lox mediated conditional deletion in adult mouse brain microglia in vivo. Regulation of neuroinflammatory microglial signatures by BIN1 in vitro and in vivo was characterized using NanoString gene panels and flow cytometry methods. The transcriptome data was explored by in silico pathway analysis and validated by complementary molecular approaches. RESULTS: Here, we characterized microglial BIN1 expression in vitro and in vivo and ascertained microglia expressed BIN1 isoforms. By silencing Bin1 expression in primary microglial cultures, we demonstrate that BIN1 regulates the activation of proinflammatory and disease-associated responses in microglia as measured by gene expression and cytokine production. Our transcriptomic profiling revealed key homeostatic and lipopolysaccharide (LPS)-induced inflammatory response pathways, as well as transcription factors PU.1 and IRF1 that are regulated by BIN1. Microglia-specific Bin1 conditional knockout in vivo revealed novel roles of BIN1 in regulating the expression of disease-associated genes while counteracting CX3CR1 signaling. The consensus from in vitro and in vivo findings showed that loss of Bin1 impaired the ability of microglia to mount type 1 interferon responses to proinflammatory challenge, particularly the upregulation of a critical type 1 immune response gene, Ifitm3. CONCLUSIONS: Our convergent findings provide novel insights into microglial BIN1 function and demonstrate an essential role of microglial BIN1 in regulating brain inflammatory response and microglial phenotypic changes. Moreover, for the first time, our study shows a regulatory relationship between Bin1 and Ifitm3, two Alzheimer's disease-related genes in microglia. The requirement for BIN1 to regulate Ifitm3 upregulation during inflammation has important implications for inflammatory responses during the pathogenesis and progression of many neurodegenerative diseases.

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.

Potential diagnostic biomarkers for schizophrenia.

Schizophrenia (SCH) is a complex and severe mental disorder with high prevalence, disability, mortality and carries a heavy disease burden, the lifetime prevalence of SCH is around 0.7%-1.0%, which has a profound impact on the individual and society. In the clinical practice of SCH, key problems such as subjective diagnosis, experiential treatment, and poor overall prognosis are still challenging. In recent years, some exciting discoveries have been made in the research on objective biomarkers of SCH, mainly focusing on genetic susceptibility genes, metabolic indicators, immune indices, brain imaging, electrophysiological characteristics. This review aims to summarize the biomarkers that may be used for the prediction and diagnosis of SCH.

Publicly Available hiPSC Lines with Extreme Polygenic Risk Scores for Modeling Schizophrenia.

Schizophrenia (SZ) is a common and debilitating psychiatric disorder with limited effective treatment options. Although highly heritable, risk for this polygenic disorder depends on the complex interplay of hundreds of common and rare variants. Translating the growing list of genetic loci significantly associated with disease into medically actionable information remains an important challenge. Thus, establishing platforms with which to validate the impact of risk variants in cell-type-specific and donor-dependent contexts is critical. Towards this, we selected and characterized a collection of 12 human induced pluripotent stem cell (hiPSC) lines derived from control donors with extremely low and high SZ polygenic risk scores (PRS). These hiPSC lines are publicly available at the California Institute for Regenerative Medicine (CIRM). The suitability of these extreme PRS hiPSCs for CRISPR-based isogenic comparisons of neurons and glia was evaluated across 3 independent laboratories, identifying 9 out of 12 meeting our criteria. We report a standardized resource of publicly available hiPSCs on which we hope to perform genome engineering and generate diverse kinds of functional data, with comparisons across studies facilitated by the use of a common set of genetic backgrounds.

Cell type-specific and cross-population polygenic risk score analyses of MIR137 gene pathway in schizophrenia.

Cell type-specific pathway-based polygenic risk scores (PRSs) may better inform disease biology and improve the precision of PRS-based clinical prediction. For microRNA-137 (MIR137), a leading neuropsychiatric risk gene and a post-transcriptional master regulator, we conducted a cell type-specific gene set PRS analysis in both European and Han Chinese schizophrenia (SZ) samples. We found that the PRS of neuronal MIR137 -target genes better explains SZ risk than PRS derived from MIR137 -target genes in iPSC or from the reported gene sets showing MIR137 -altered expression. Compared with the PRS derived from the whole genome or the target genes of TCF4, the PRS of neuronal MIR137 -target genes explained a disproportionally larger (relative to SNP number) SZ risk in the European sample, but with a more modest advantage in the Han Chinese sample. Our study demonstrated a cell type-specific polygenic contribution of MIR137 -target genes to SZ risk, highlighting the value of cell type-specific pathway-based PRS analysis for uncovering disease-relevant biological features.

A computational method for direct imputation of cell type-specific expression profiles and cellular compositions from bulk-tissue RNA-Seq in brain disorders.

The importance of cell type-specific gene expression in disease-relevant tissues is increasingly recognized in genetic studies of complex diseases. However, most gene expression studies are conducted on bulk tissues, without examining cell type-specific expression profiles. Several computational methods are available for cell type deconvolution (i.e. inference of cellular composition) from bulk RNA-Seq data, but few of them impute cell type-specific expression profiles. We hypothesize that with external prior information such as single cell RNA-seq and population-wide expression profiles, it can be computationally tractable to estimate both cellular composition and cell type-specific expression from bulk RNA-Seq data. Here we introduce CellR, which addresses cross-individual gene expression variations to adjust the weights of cell-specific gene markers. It then transforms the deconvolution problem into a linear programming model while taking into account inter/intra cellular correlations and uses a multi-variate stochastic search algorithm to estimate the cell type-specific expression profiles. Analyses on several complex diseases such as schizophrenia, Alzheimer's disease, Huntington's disease and type 2 diabetes validated the efficiency of CellR, while revealing how specific cell types contribute to different diseases. In summary, CellR compares favorably against competing approaches, enabling cell type-specific re-analysis of gene expression data on bulk tissues in complex diseases.

Sex-specific nicotine sensitization and imprinting of self-administration in rats inform GWAS findings on human addiction phenotypes.

Repeated nicotine exposure leads to sensitization (SST) and enhances self-administration (SA) in rodents. However, the molecular basis of nicotine SST and SA and their biological relevance to the mounting genome-wide association study (GWAS) loci of human addictive behaviors are poorly understood. Considering a gateway drug role of nicotine, we modeled nicotine SST and SA in F1 progeny of inbred rats (F344/BN) and conducted integrative genomics analyses. We unexpectedly observed male-specific nicotine SST and a parental effect of SA only present in paternal F344 crosses. Transcriptional profiling in the ventral tegmental area (VTA) and nucleus accumbens (NAc) core and shell further revealed sex- and brain region-specific transcriptomic signatures of SST and SA. We found that genes associated with SST and SA were enriched for those related to synaptic processes, myelin sheath, and tobacco use disorder or chemdependency. Interestingly, SST-associated genes were often downregulated in male VTA but upregulated in female VTA, and strongly enriched for smoking GWAS risk variants, possibly explaining the male-specific SST. For SA, we found widespread region-specific allelic imbalance of expression (AIE), of which genes showing AIE bias toward paternal F344 alleles in NAc core were strongly enriched for SA-associated genes and for GWAS risk variants of smoking initiation, likely contributing to the parental effect of SA. Our study suggests a mechanistic link between transcriptional changes underlying the NIC SST and SA and human nicotine addiction, providing a resource for understanding the neurobiology basis of the GWAS findings on human smoking and other addictive phenotypes.

CCmed: cross-condition mediation analysis for identifying replicable trans-associations mediated by cis-gene expression.

MOTIVATION: Trans-acting expression quantitative trait loci (eQTLs) collectively explain a substantial proportion of expression variation, yet are challenging to detect and replicate since their effects are often individually weak. A large proportion of genetic effects on distal genes are mediated through cis-gene expression. Cis-association (between SNP and cis-gene) and gene-gene correlation conditional on SNP genotype could establish trans-association (between SNP and trans-gene). Both cis-association and gene-gene conditional correlation have effects shared across relevant tissues and conditions, and trans-associations mediated by cis-gene expression also have effects shared across relevant conditions. RESULTS: We proposed a Cross-Condition Mediation analysis method (CCmed) for detecting cis-mediated trans-associations with replicable effects in relevant conditions/studies. CCmed integrates cis-association and gene-gene conditional correlation statistics from multiple tissues/studies. Motivated by the bimodal effect-sharing patterns of eQTLs, we proposed two variations of CCmed, CCmedmost and CCmedspec for detecting cross-tissue and tissue-specific trans-associations, respectively. We analyzed data of 13 brain tissues from the Genotype-Tissue Expression (GTEx) project, and identified trios with cis-mediated trans-associations across brain tissues, many of which showed evidence of trans-association in two replication studies. We also identified trans-genes associated with schizophrenia loci in at least two brain tissues. AVAILABILITY AND IMPLEMENTATION: CCmed software is available at http://github.com/kjgleason/CCmed. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Cell-Type-Specific Proteogenomic Signal Diffusion for Integrating Multi-Omics Data Predicts Novel Schizophrenia Risk Genes.

Accumulation of diverse types of omics data on schizophrenia (SCZ) requires a systems approach to model the interplay between genome, transcriptome, and proteome. We introduce Markov affinity-based proteogenomic signal diffusion (MAPSD), a method to model intra-cellular protein trafficking paradigms and tissue-wise single-cell protein abundances. MAPSD integrates multi-omics data to amplify the signals at SCZ risk loci with small effect sizes, and reveal convergent disease-associated gene modules in the brain. We predicted a set of high-confidence SCZ risk loci followed by characterizing the subcellular localization of proteins encoded by candidate SCZ risk genes, and illustrated that most are enriched in neuronal cells in the cerebral cortex as well as Purkinje cells in the cerebellum. We demonstrated how the identified genes may be involved in neurodevelopment, how they may alter SCZ-related biological pathways, and how they facilitate drug repurposing. MAPSD is applicable in other polygenic diseases and can facilitate our understanding of disease mechanisms.

Allele-specific open chromatin in human iPSC neurons elucidates functional disease variants.

Most neuropsychiatric disease risk variants are in noncoding sequences and lack functional interpretation. Because regulatory sequences often reside in open chromatin, we reasoned that neuropsychiatric disease risk variants may affect chromatin accessibility during neurodevelopment. Using human induced pluripotent stem cell (iPSC)-derived neurons that model developing brains, we identified thousands of genetic variants exhibiting allele-specific open chromatin (ASoC). These neuronal ASoCs were partially driven by altered transcription factor binding, overrepresented in brain gene enhancers and expression quantitative trait loci, and frequently associated with distal genes through chromatin contacts. ASoCs were enriched for genetic variants associated with brain disorders, enabling identification of functional schizophrenia risk variants and their cis-target genes. This study highlights ASoC as a functional mechanism of noncoding neuropsychiatric risk variants, providing a powerful framework for identifying disease causal variants and genes.