GAGA-associated factor fosters loop formation in the Drosophila genome.

The impact of genome organization on the control of gene expression persists as a major challenge in regulatory biology. Most efforts have focused on the role of CTCF-enriched boundary elements and TADs, which enable long-range DNA-DNA associations via loop extrusion processes. However, there is increasing evidence for long-range chromatin loops between promoters and distal enhancers formed through specific DNA sequences, including tethering elements, which bind the GAGA-associated factor (GAF). Previous studies showed that GAF possesses amyloid properties in vitro, bridging separate DNA molecules. In this study, we investigated whether GAF functions as a looping factor in Drosophila development. We employed Micro-C assays to examine the impact of defined GAF mutants on genome topology. These studies suggest that the N-terminal POZ/BTB oligomerization domain is important for long-range associations of distant GAGA-rich tethering elements, particularly those responsible for promoter-promoter interactions that coordinate the activities of distant paralogous genes.

Distinct subnetworks of the thalamic reticular nucleus.

The thalamic reticular nucleus (TRN), the major source of thalamic inhibition, regulates thalamocortical interactions that are critical for sensory processing, attention and cognition1-5. TRN dysfunction has been linked to sensory abnormality, attention deficit and sleep disturbance across multiple neurodevelopmental disorders6-9. However, little is known about the organizational principles that underlie its divergent functions. Here we performed an integrative study linking single-cell molecular and electrophysiological features of the mouse TRN to connectivity and systems-level function. We found that cellular heterogeneity in the TRN is characterized by a transcriptomic gradient of two negatively correlated gene-expression profiles, each containing hundreds of genes. Neurons in the extremes of this transcriptomic gradient express mutually exclusive markers, exhibit core or shell-like anatomical structure and have distinct electrophysiological properties. The two TRN subpopulations make differential connections with the functionally distinct first-order and higher-order thalamic nuclei to form molecularly defined TRN-thalamus subnetworks. Selective perturbation of the two subnetworks in vivo revealed their differential role in regulating sleep. In sum, our study provides a comprehensive atlas of TRN neurons at single-cell resolution and links molecularly defined subnetworks to the functional organization of thalamocortical circuits.

CellAnn: a comprehensive, super-fast, and user-friendly single-cell annotation web server.

MOTIVATION: Single-cell sequencing technology has become a routine in studying many biological problems. A core step of analyzing single-cell data is the assignment of cell clusters to specific cell types. Reference-based methods are proposed for predicting cell types for single-cell clusters. However, the scalability and lack of preprocessed reference datasets prevent them from being practical and easy to use. RESULTS: Here, we introduce a reference-based cell annotation web server, CellAnn, which is super-fast and easy to use. CellAnn contains a comprehensive reference database with 204 human and 191 mouse single-cell datasets. These reference datasets cover 32 organs. Furthermore, we developed a cluster-to-cluster alignment method to transfer cell labels from the reference to the query datasets, which is superior to the existing methods with higher accuracy and higher scalability. Finally, CellAnn is an online tool that integrates all the procedures in cell annotation, including reference searching, transferring cell labels, visualizing results, and harmonizing cell annotation labels. Through the user-friendly interface, users can identify the best annotation by cross-validating with multiple reference datasets. We believe that CellAnn can greatly facilitate single-cell sequencing data analysis. AVAILABILITY AND IMPLEMENTATION: The web server is available at www.cellann.io, and the source code is available at https://github.com/Pinlyu3/CellAnn_shinyapp.

TCF12 haploinsufficiency causes autosomal dominant Kallmann syndrome and reveals network-level interactions between causal loci.

Dysfunction of the gonadotropin-releasing hormone (GnRH) axis causes a range of reproductive phenotypes resulting from defects in the specification, migration and/or function of GnRH neurons. To identify additional molecular components of this system, we initiated a systematic genetic interrogation of families with isolated GnRH deficiency (IGD). Here, we report 13 families (12 autosomal dominant and one autosomal recessive) with an anosmic form of IGD (Kallmann syndrome) with loss-of-function mutations in TCF12, a locus also known to cause syndromic and non-syndromic craniosynostosis. We show that loss of tcf12 in zebrafish larvae perturbs GnRH neuronal patterning with concomitant attenuation of the orthologous expression of tcf3a/b, encoding a binding partner of TCF12, and stub1, a gene that is both mutated in other syndromic forms of IGD and maps to a TCF12 affinity network. Finally, we report that restored STUB1 mRNA rescues loss of tcf12 in vivo. Our data extend the mutational landscape of IGD, highlight the genetic links between craniofacial patterning and GnRH dysfunction and begin to assemble the functional network that regulates the development of the GnRH axis.

US medical student perspectives on asian american patient inclusion in medical education: a qualitative Study.

BACKGROUND: Asian American (AsAm) representation is lacking in conversations surrounding cultural humility in healthcare. We aimed to investigate US medical student perspectives on AsAm patient inclusion in cultural humility training in medical education. METHODS: This qualitative study analyzed free-text responses to an optional, open-ended question presented at the conclusion of an online survey assessing medical student experiences with and perceptions regarding AsAm patients in their medical education. This survey was distributed to a convenience sample of nine US medical schools. Medical students who completed at least one clinical rotation were eligible to participate in the survey. Qualitative analysis of free-text responses was conducted in an iterative process to generate emergent themes. RESULTS: There was a total of 195 optional free-text responses from 688 participants (28%). Motivation to learn about AsAm population included shared identity and desire to better serve the AsAm population in their local community and future careers. Topics of interest included healthcare-related cultural preferences, healthcare delivery strategies, and health disparities for the AsAm population and other minority patients. Students reported that they drew on personal experiences and some pre-clinical or clinical exposures to learn about AsAm patients. Respondents cited the lack of exposure in the medical school curriculum and clinical experiences as the main challenge to learning about AsAm health and provided suggestions for the delivery of this education in their pre-clinical and clinical education. Respondents emphasized that AsAms are treated as a monolith in medical education and healthcare, despite their heterogeneity. CONCLUSIONS: Medical students identified a need and interest for greater inclusion of AsAm topics in medical education on cultural humility and minority health.

GeNets: a unified web platform for network-based genomic analyses.

Functional genomics networks are widely used to identify unexpected pathway relationships in large genomic datasets. However, it is challenging to compare the signal-to-noise ratios of different networks and to identify the optimal network with which to interpret a particular genetic dataset. We present GeNets, a platform in which users can train a machine-learning model (Quack) to carry out these comparisons and execute, store, and share analyses of genetic and RNA-sequencing datasets.

Knowledge and attitudes of U.S. medical students regarding the care of Asian American patients: a cross-sectional survey study.

BACKGROUND: Asian Americans (AsAm) are a rapidly growing population in the U.S. With this growing population, U.S. healthcare providers must be equipped to provide culturally competent care for AsAm patients. This project surveyed U.S. medical students on their knowledge of and attitudes towards AsAm to assess predictors of readiness to care for AsAm patients. METHOD: This cross-sectional study surveyed medical students who had completed at least one clinical rotation. The survey was distributed online to nine medical schools throughout the U.S. The survey measured self-rated knowledge of, comfort with, cultural competency (CC) towards, and explicit biases towards AsAm patients. The first three domains were analyzed in a multivariate regression model including sociodemographic characteristics and past clinical, curricular, and social experiences with AsAm. Explicit bias questions were reported descriptively. RESULTS: There were 688 respondents. Asian race, AsAm-prevalent hometown, AsAm-related extracurricular activities, Asian language knowledge, and having taken a population health course predicted increased AsAm knowledge. Social interactions with AsAm increased comfort with AsAm patients. Increasing year in medical school, more frequent exposure to AsAm patients on rotations, and prior travel to an Asian country were predictors of increased CC toward AsAm. Importantly, having completed a CC course was a significant predictor in all domains. In terms of explicit bias, students felt that AsAm patients were more compliant than Caucasian patients. Students also believed that Caucasian patients were generally more likely to receive self-perceived "preferred" versus "acceptable" care, but that in their own clinical experiences neither group received preferred care. CONCLUSION: Experience with and exposure to AsAm prior to and during medical school and CC courses may increase medical student knowledge, comfort, and CC with AsAm patients. Standardized and longitudinal CC training, increased simulations with AsAm patients, diverse student recruitment, and support for students to engage in AsAm-related activities and interact with AsAm may improve CC of future physicians towards AsAm patients and possibly other minority populations.

A scored human protein-protein interaction network to catalyze genomic interpretation.

Genome-scale human protein-protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein-protein interaction network (InWeb_InBioMap, or InWeb_IM) with severalfold more interactions (>500,000) and better functional biological relevance than comparable resources. We illustrate that InWeb_InBioMap enables functional interpretation of >4,700 cancer genomes and genes involved in autism.

Deep Learning and Transfer Learning for Optic Disc Laterality Detection: Implications for Machine Learning in Neuro-Ophthalmology.

BACKGROUND: Deep learning (DL) has demonstrated human expert levels of performance for medical image classification in a wide array of medical fields, including ophthalmology. In this article, we present the results of our DL system designed to determine optic disc laterality, right eye vs left eye, in the presence of both normal and abnormal optic discs. METHODS: Using transfer learning, we modified the ResNet-152 deep convolutional neural network (DCNN), pretrained on ImageNet, to determine the optic disc laterality. After a 5-fold cross-validation, we generated receiver operating characteristic curves and corresponding area under the curve (AUC) values to evaluate performance. The data set consisted of 576 color fundus photographs (51% right and 49% left). Both 30° photographs centered on the optic disc (63%) and photographs with varying degree of optic disc centration and/or wider field of view (37%) were included. Both normal (27%) and abnormal (73%) optic discs were included. Various neuro-ophthalmological diseases were represented, such as, but not limited to, atrophy, anterior ischemic optic neuropathy, hypoplasia, and papilledema. RESULTS: Using 5-fold cross-validation (70% training; 10% validation; 20% testing), our DCNN for classifying right vs left optic disc achieved an average AUC of 0.999 (±0.002) with optimal threshold values, yielding an average accuracy of 98.78% (±1.52%), sensitivity of 98.60% (±1.72%), and specificity of 98.97% (±1.38%). When tested against a separate data set for external validation, our 5-fold cross-validation model achieved the following average performance: AUC 0.996 (±0.005), accuracy 97.2% (±2.0%), sensitivity 96.4% (±4.3%), and specificity 98.0% (±2.2%). CONCLUSIONS: Small data sets can be used to develop high-performing DL systems for semantic labeling of neuro-ophthalmology images, specifically in distinguishing between right and left optic discs, even in the presence of neuro-ophthalmological pathologies. Although this may seem like an elementary task, this study demonstrates the power of transfer learning and provides an example of a DCNN that can help curate large medical image databases for machine-learning purposes and facilitate ophthalmologist workflow by automatically labeling images according to laterality.

Simultaneous paralogue knockout using a CRISPR-concatemer in mouse small intestinal organoids.

Approaches based on genetic modification have been invaluable for investigating a wide array of biological processes, with gain- and loss-of-function approaches frequently used to investigate gene function. However, the presence of paralogues, and hence possible genetic compensation, for many genes necessitates the knockout (KO) of all paralogous genes in order to observe clear phenotypic change. CRISPR technology, the most recently described tool for gene editing, can generate KOs with unprecedented ease and speed and has been used in adult stem cell-derived organoids for single gene knockout, gene knock-in and gene correction. However, the simultaneous targeting of multiple genes in organoids by CRISPR technology has not previously been described. Here we describe a rapid, scalable and cost effective method for generating double knockouts in organoids. By concatemerizing multiple gRNA expression cassettes, we generated a 'gRNA concatemer vector'. Our method allows the rapid assembly of annealed synthetic DNA oligos into the final vector in a single step. This approach facilitates simultaneous delivery of multiple gRNAs to allow up to 4 gene KO in one step, or potentially to increase the efficiency of gene knockout by providing multiple gRNAs targeting one gene. As a proof of concept, we knocked out negative regulators of the Wnt pathway in small intestinal organoids, thereby removing their growth dependence on the exogenous Wnt enhancer, R-spondin1.

The Drosophila histone methyl-transferase SET1 coordinates multiple signaling pathways in regulating male germline stem cell maintenance and differentiation.

Many cell types come from tissue-specific adult stem cells that maintain the balance between proliferation and differentiation. Here, we study how the H3K4me3 methyltransferase, Set1, regulates early-stage male germ cell proliferation and differentiation in Drosophila. Early-stage germline-specific knockdown of set1 results in a temporally progressed defects, arising as germ cell loss and developing to overpopulated early-stage germ cells. These germline defects also impact the niche architecture and cyst stem cell lineage in a non-cell-autonomous manner. Additionally, wild-type Set1, but not the catalytically inactive Set1, could rescue the set1 knockdown phenotypes, highlighting the functional importance of the methyl-transferase activity of the Set1 enzyme. Further, RNA-seq experiments reveal key signaling pathway components, such as the JAK-STAT pathway gene stat92E and the BMP pathway gene mad, that are upregulated upon set1 knockdown. Genetic interaction assays support the functional relationships between set1 and JAK-STAT or BMP pathways, as mutations of both the stat92E and mad genes suppress the set1 knockdown phenotypes. These findings enhance our understanding of the balance between proliferation and differentiation in an adult stem cell lineage. The germ cell loss followed by over-proliferation phenotypes when inhibiting a histone methyl-transferase raise concerns about using their inhibitors in cancer therapy.

Transcriptomic profiling of Schlemm's canal cells reveals a lymphatic-biased identity and three major cell states.

Schlemm's canal (SC) is central in intraocular pressure regulation but requires much characterization. It has distinct inner and outer walls, each composed of Schlemm's canal endothelial cells (SECs) with different morphologies and functions. Recent transcriptomic studies of the anterior segment added important knowledge, but were limited in power by SEC numbers or did not focus on SC. To gain a more comprehensive understanding of SC biology, we performed bulk RNA sequencing on C57BL/6J SC, blood vessel, and lymphatic endothelial cells from limbal tissue (~4500 SECs). We also analyzed mouse limbal tissues by single-cell and single-nucleus RNA sequencing (C57BL/6J and 129/Sj strains), successfully sequencing 903 individual SECs. Together, these datasets confirm that SC has molecular characteristics of both blood and lymphatic endothelia with a lymphatic phenotype predominating. SECs are enriched in pathways that regulate cell-cell junction formation pointing to the importance of junctions in determining SC fluid permeability. Importantly, and for the first time, our analyses characterize 3 molecular classes of SECs, molecularly distinguishing inner wall from outer wall SECs and discovering two inner wall cell states that likely result from local environmental differences. Further, and based on ligand and receptor expression patterns, we document key interactions between SECs and cells of the adjacent trabecular meshwork (TM) drainage tissue. Also, we present cell type expression for a collection of human glaucoma genes. These data provide a new molecular foundation that will enable the functional dissection of key homeostatic processes mediated by SECs as well as the development of new glaucoma therapeutics.

Consistency of metabolite associations with measured glomerular filtration rate in children and adults.

Background: There is interest in identifying novel filtration markers that lead to more accurate GFR estimates than current markers (creatinine and cystatin C) and are more consistent across demographic groups. We hypothesize that large-scale metabolomics can identify serum metabolites that are strongly influenced by glomerular filtration rate (GFR) and are more consistent across demographic variables than creatinine, which would be promising filtration markers for future investigation. Methods: We evaluated the consistency of associations between measured GFR (mGFR) and 887 common, known metabolites quantified by an untargeted chromatography- and spectroscopy-based metabolomics platform (Metabolon) performed on frozen blood samples from 580 participants in Chronic Kidney Disease in Children (CKiD), 674 participants in Modification of Diet in Renal Disease (MDRD) Study and 962 participants in African American Study of Kidney Disease and Hypertension (AASK). We evaluated metabolite-mGFR correlation association with metabolite class, molecular weight, assay platform and measurement coefficient of variation (CV). Among metabolites with strong negative correlations with mGFR (r < -0.5), we assessed additional variation by age (height in children), sex, race and body mass index (BMI). Results: A total of 561 metabolites (63%) were negatively correlated with mGFR. Correlations with mGFR were highly consistent across study, sex, race and BMI categories (correlation of metabolite-mGFR correlations between 0.88 and 0.95). Amino acids, carbohydrates and nucleotides were more often negatively correlated with mGFR compared with lipids, but there was no association with metabolite molecular weight, liquid chromatography/mass spectrometry platform and measurement CV. Among 114 metabolites with strong negative associations with mGFR (r < -0.5), 27 were consistently not associated with age (height in children), sex or race. Conclusions: The majority of metabolite-mGFR correlations were negative and consistent across sex, race, BMI and study. Metabolites with consistent strong negative correlations with mGFR and non-association with demographic variables may represent candidate markers to improve estimation of GFR.

Enhancing mitochondrial proteolysis alleviates alpha-synuclein-mediated cellular toxicity.

Parkinson's disease (PD) is a progressive neurodegenerative disease characterized by mitochondrial dysfunction and accumulation of alpha-synuclein (α-Syn)-containing protein aggregates known as Lewy bodies (LB). Here, we investigated the entry of α-Syn into mitochondria to cause mitochondrial dysfunction and loss of cellular fitness in vivo. We show that α-Syn expressed in yeast and human cells is constitutively imported into mitochondria. In a transgenic mouse model, the level of endogenous α-Syn accumulation in mitochondria of dopaminergic neurons and microglia increases with age. The imported α-Syn is degraded by conserved mitochondrial proteases, most notably NLN and PITRM1 (Prd1 and Cym1 in yeast, respectively). α-Syn in the mitochondrial matrix that is not degraded interacts with respiratory chain complexes, leading to loss of mitochondrial DNA (mtDNA), mitochondrial membrane potential and cellular fitness decline. Importantly, enhancing mitochondrial proteolysis by increasing levels of specific proteases alleviated these defects in yeast, human cells, and a PD model of mouse primary neurons. Together, our results provide a direct link between α-synuclein-mediated cellular toxicity and its import into mitochondria and reveal potential therapeutic targets for the treatment of α-synucleinopathies.

Protein interaction networks in the vasculature prioritize genes and pathways underlying coronary artery disease.

Population-based association studies have identified many genetic risk loci for coronary artery disease (CAD), but it is often unclear how genes within these loci are linked to CAD. Here, we perform interaction proteomics for 11 CAD-risk genes to map their protein-protein interactions (PPIs) in human vascular cells and elucidate their roles in CAD. The resulting PPI networks contain interactions that are outside of known biology in the vasculature and are enriched for genes involved in immunity-related and arterial-wall-specific mechanisms. Several PPI networks derived from smooth muscle cells are significantly enriched for genetic variants associated with CAD and related vascular phenotypes. Furthermore, the networks identify 61 genes that are found in genetic loci associated with risk of CAD, prioritizing them as the causal candidates within these loci. These findings indicate that the PPI networks we have generated are a rich resource for guiding future research into the molecular pathogenesis of CAD.

Integrated molecular and clinical analysis of BRAF-mutant glioma in adults.

BRAF mutations are a significant driver of disease in pediatric low-grade glioma, but the implications of BRAF alterations on the clinical course and treatment response in adult glioma remain unclear. Here, we characterize a multi-institutional cohort of more than 300 patients (>200 adults) with BRAF-mutated glioma using clinical, pathological/molecular, and outcome data. We observed that adult and pediatric BRAF-mutant gliomas harbor distinct clinical and molecular features, with a higher prevalence of BRAFV600E (Class I) and BRAF fusions in pediatric tumors. BRAFV600E alterations were associated with improved survival in adults with glioma overall, though not in glioblastoma. Other genomic alterations observed within functional classes were consistent with the putative roles of those BRAF mutation classes in glioma pathogenesis. In our adult cohort, BRAFV600E alterations conferred sensitivity to targeted therapies. Overall, this large cohort of BRAF-altered adult gliomas demonstrates a broad range of molecular alterations with implications for treatment sensitivity and survival.

Clinical Outcomes and Safety Comparison of Vertebroplasty, Balloon Kyphoplasty, and Vertebral Implant for Treatment of Vertebral Compression Fractures.

BACKGROUND AND PURPOSE: Vertebral compression fracture represents a major health burden for the aging populations globally. However, limited studies exist on the relative efficacy and safety of surgical interventions for vertebral compression fracture. Here, we aim to compare clinical and patient-reported outcomes following vertebral augmentation using balloon kyphoplasty, vertebroplasty, and SpineJack vertebral implant. MATERIALS AND METHODS: An institutional review board-approved, retrospective, multi-institutional review of patients undergoing vertebral augmentation with kyphoplasty, vertebroplasty, and/or a SpineJack vertebral implant was performed between 2018 and 2021. Primary outcomes included pre- and postprocedural pain ratings and vertebral body height restoration. The secondary outcome was a change in the local kyphotic angle. The Kruskal-Wallis test was used to compare outcomes across 3 treatment options. Complications were reviewed during and 30-90 days after the procedure. RESULTS: Vertebral augmentation of 344 vertebral compression fracture levels was performed during the study period. Sixty-seven patients had 79 kyphoplasty procedures (55% women; mean age, 64.2 [SD, 12.3] years). Seventy-four patients underwent a mean of 84 vertebroplasty procedures (51% women; mean age, 63.5 [SD, 12.8] years), and 61 patients had a mean of 67 SpineJack vertebral implant procedures (57.4% women; mean age, 68.3 [SD, 10.6] years). Following kyphoplasty, vertebroplasty, and SpineJack vertebral implant, pain scores improved significantly (P < .001). Resting pain improvement was similar across the 3 procedures, whereas improvement of "worst pain" was significantly better following a SpineJack vertebral implant compared with kyphoplasty and vertebroplasty (P < .001). Patients with a SpineJack vertebral implant had greater improvement in vertebral body height restoration and local kyphotic angle compared with those undergoing kyphoplasty and vertebroplasty. Adjacent level fractures (6.7% incidence) occurred similarly in the 3 procedure types. There were no other peri- or postoperative complications. CONCLUSIONS: The SpineJack vertebral implant showed equivalent pain improvement compared with vertebroplasty and kyphoplasty, but it had superior vertebral body height restoration and local kyphotic angle improvement. This study supports the SpineJack vertebral implant as a safe and effective alternative (adjunct) for vertebral augmentation, especially in patients with moderate-to-severe vertebral compression fractures for greater improvement in vertebral body height restoration.

Differential effects of aneuploidy on growth and differentiation in human intestinal stem cells.

Aneuploidy, a near ubiquitous genetic feature of tumors, is a context-dependent driver of cancer evolution; however, the mechanistic basis of this role remains unclear. Here, by inducing heterogeneous aneuploidy in non-transformed human colon organoids (colonoids), we investigate how the effects of aneuploidy on cell growth and differentiation may promote malignant transformation. Single-cell RNA sequencing reveals that the gene expression signature across over 100 unique aneuploid karyotypes is enriched with p53 responsive genes. The primary driver of p53 activation is karyotype complexity. Complex aneuploid cells with multiple unbalanced chromosomes activate p53 and undergo G1 cell-cycle arrest, independent of DNA damage and without evidence of senescence. By contrast, simple aneuploid cells with 1-3 chromosomes gained or lost continue to proliferate, demonstrated by single cell tracking in colonoids. Notably, simple aneuploid cells exhibit impaired differentiation when niche factors are withdrawn. These findings suggest that while complex aneuploid cells are eliminated from the normal epithelium due to p53 activation, simple aneuploid cells can escape this checkpoint and may contribute to niche factor-independent growth of cancer-initiating cells.

Leveraging polygenic enrichments of gene features to predict genes underlying complex traits and diseases.

Genome-wide association studies (GWASs) are a valuable tool for understanding the biology of complex human traits and diseases, but associated variants rarely point directly to causal genes. In the present study, we introduce a new method, polygenic priority score (PoPS), that learns trait-relevant gene features, such as cell-type-specific expression, to prioritize genes at GWAS loci. Using a large evaluation set of genes with fine-mapped coding variants, we show that PoPS and the closest gene individually outperform other gene prioritization methods, but observe the best overall performance by combining PoPS with orthogonal methods. Using this combined approach, we prioritize 10,642 unique gene-trait pairs across 113 complex traits and diseases with high precision, finding not only well-established gene-trait relationships but nominating new genes at unresolved loci, such as LGR4 for estimated glomerular filtration rate and CCR7 for deep vein thrombosis. Overall, we demonstrate that PoPS provides a powerful addition to the gene prioritization toolbox.

Using brain cell-type-specific protein interactomes to interpret neurodevelopmental genetic signals in schizophrenia.

Genetics have nominated many schizophrenia risk genes and identified convergent signals between schizophrenia and neurodevelopmental disorders. However, functional interpretation of the nominated genes in the relevant brain cell types is often lacking. We executed interaction proteomics for six schizophrenia risk genes that have also been implicated in neurodevelopment in human induced cortical neurons. The resulting protein network is enriched for common variant risk of schizophrenia in Europeans and East Asians, is down-regulated in layer 5/6 cortical neurons of individuals affected by schizophrenia, and can complement fine-mapping and eQTL data to prioritize additional genes in GWAS loci. A sub-network centered on HCN1 is enriched for common variant risk and contains proteins (HCN4 and AKAP11) enriched for rare protein-truncating mutations in individuals with schizophrenia and bipolar disorder. Our findings showcase brain cell-type-specific interactomes as an organizing framework to facilitate interpretation of genetic and transcriptomic data in schizophrenia and its related disorders.