IL-33 potentiates histaminergic itch.

BACKGROUND: Itch is a common symptom that can greatly diminish quality of life. Histamine is a potent endogenous pruritogen, and while antihistamines are often the first-line treatment for itch, in conditions like chronic spontaneous urticaria (CSU), many patients remain symptomatic while receiving maximal doses. Mechanisms that drive resistance to antihistamines are poorly defined. OBJECTIVES: Signaling of the alarmin cytokine IL-33 in sensory neurons is postulated to drive chronic itch by inducing neuronal sensitization to pruritogens. Thus, we sought to determine if IL-33 can augment histamine-induced (histaminergic) itch. METHODS: Itch behavior was assessed in response to histamine after IL-33 or saline administration. Various stimuli and conditional and global knockout mice were utilized to dissect cellular mechanisms. Multiple existing transcriptomic data sets were evaluated, including single-cell RNA sequencing of human and mouse skin, microarrays of isolated mouse mast cells at steady state and after stimulation with IL-33, and microarrays of skin biopsy samples from subjects with CSU and healthy controls. RESULTS: IL-33 amplifies histaminergic itch independent of IL-33 signaling in sensory neurons. Mast cells are the top expressors of the IL-33 receptor in both human and mouse skin. When stimulated by IL-33, mouse mast cells significantly increase IL-13 levels. Enhancement of histaminergic itch by IL-33 relies on a mast cell- and IL-13-dependent mechanism. IL-33 receptor expression is increased in lesional skin of subjects with CSU compared to healthy controls. CONCLUSIONS: Our findings suggest that IL-33 signaling may be a key driver of histaminergic itch in mast cell-associated pruritic conditions such as CSU.

STmut: a framework for visualizing somatic alterations in spatial transcriptomics data of cancer.

Spatial transcriptomic technologies, such as the Visium platform, measure gene expression in different regions of tissues. Here, we describe new software, STmut, to visualize somatic point mutations, allelic imbalance, and copy number alterations in Visium data. STmut is tested on fresh-frozen Visium data, formalin-fixed paraffin-embedded (FFPE) Visium data, and tumors with and without matching DNA sequencing data. Copy number is inferred on all conditions, but the chemistry of the FFPE platform does not permit analyses of single nucleotide variants. Taken together, we propose solutions to add the genetic dimension to spatial transcriptomic data and describe the limitations of different datatypes.

Single-Cell and Spatial Transcriptomic Analysis of Human Skin Delineates Intercellular Communication and Pathogenic Cells.

Epidermal homeostasis is governed by a balance between keratinocyte proliferation and differentiation with contributions from cell-cell interactions, but conserved or divergent mechanisms governing this equilibrium across species and how an imbalance contributes to skin disease are largely undefined. To address these questions, human skin single-cell RNA sequencing and spatial transcriptomics data were integrated and compared with mouse skin data. Human skin cell-type annotation was improved using matched spatial transcriptomics data, highlighting the importance of spatial context in cell-type identity, and spatial transcriptomics refined cellular communication inference. In cross-species analyses, we identified a human spinous keratinocyte subpopulation that exhibited proliferative capacity and a heavy metal processing signature, which was absent in mouse and may account for species differences in epidermal thickness. This human subpopulation was expanded in psoriasis and zinc-deficiency dermatitis, attesting to disease relevance and suggesting a paradigm of subpopulation dysfunction as a hallmark of the disease. To assess additional potential subpopulation drivers of skin diseases, we performed cell-of-origin enrichment analysis within genodermatoses, nominating pathogenic cell subpopulations and their communication pathways, which highlighted multiple potential therapeutic targets. This integrated dataset is encompassed in a publicly available web resource to aid mechanistic and translational studies of normal and diseased skin.

The Use of Single-Cell RNA-Sequencing and Spatial Transcriptomics in Understanding the Pathogenesis and Treatment of Skin Diseases.

The development of multiomic profiling tools has rapidly expanded in recent years, along with their use in profiling skin tissues in various contexts, including dermatologic diseases. Among these tools, single-cell RNA-sequencing (scRNA-seq) and spatial transcriptomics (ST) have emerged as widely adopted and powerful assays for elucidating key cellular components and their spatial arrangement within skin disease. In this paper, we review the recent biological insights gained from the use of scRNA-seq and ST and the advantages of combining both for profiling skin diseases, including aberrant wound healing, inflammatory skin diseases, and cancer. We discuss the role of scRNA-seq and ST in improving skin disease treatments and moving toward the goal of achieving precision medicine in dermatology, whereby patients can be optimally matched to treatments that maximize therapeutic response.

Spatially resolved clonal copy number alterations in benign and malignant tissue.

Defining the transition from benign to malignant tissue is fundamental to improving early diagnosis of cancer1. Here we use a systematic approach to study spatial genome integrity in situ and describe previously unidentified clonal relationships. We used spatially resolved transcriptomics2 to infer spatial copy number variations in >120,000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue using an organ-wide approach focused on the prostate. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of capturing the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.

The metabolic adverse effects of antipsychotic use in individuals with intellectual and/or developmental disability: A systematic review and meta-analysis.

OBJECTIVE: Individuals with intellectual and/or developmental disability (IDD) are often prescribed antipsychotics (APs). However, despite their known propensity to cause metabolic adverse effects, including weight gain, diabetes, and increased risk of cardiovascular events, there is currently a limited body of literature describing the metabolic consequences of AP use in this population. METHODS: We searched MEDLINE, EMBASE, PsychINFO, CENTRAL, and CINAHL databases to identify all randomized trials that reported on the metabolic effects of APs in individuals with IDD. Random effects meta-analyses were used to examine weight gain as both a continuous and dichotomous outcome. RESULTS: Eighteen randomized trials met our inclusion criteria with a total of 1376 patients across a variety of IDDs. AP use was associated with significantly greater weight gain compared with placebo (Continuous: mean difference = 1.10 kg, [0.79, 1.40], p < 0.00001, I2  = 54%; Dichotomous: odds ratio = 3.94, [2.15, 7.23], p < 0.00001, I2  = 0). Sub-group analysis revealed no significant effect of AP type. Data regarding the effects of APs on other metabolic outcomes were limited. CONCLUSION: This review (PROSPERO # CRD42021255558) demonstrates that AP use is associated with significant weight gain among patients with IDD. Concerningly, most reported studies were in children and adolescents, which sets up an already vulnerable population for adverse medical sequalae at an early age. There was also a lack of long-term studies in adults with IDD. Further studies are required to better understand how AP use affects metabolic parameters in this group of individuals.

Research Techniques Made Simple: Spatial Transcriptomics.

Transcriptome profiling of tissues and single cells facilitates interrogation of gene expression changes within diverse biological contexts. However, spatial information is often lost during tissue homogenization or dissociation. Recent advances in transcriptome profiling preserve the in situ spatial contexts of RNA molecules and together comprise a group of techniques known as spatial transcriptomics (ST), enabling localization of cell types and their associated gene expression within intact tissues. In this paper, we review ST methods; summarize data analysis approaches, including integration with single-cell transcriptomics data; and discuss their applications in dermatologic research. These tools offer a promising avenue toward improving our understanding of niche patterning and cell‒cell interactions within heterogeneous tissues that encompass skin homeostasis and disease.

Super-resolved spatial transcriptomics by deep data fusion.

Current methods for spatial transcriptomics are limited by low spatial resolution. Here we introduce a method that integrates spatial gene expression data with histological image data from the same tissue section to infer higher-resolution expression maps. Using a deep generative model, our method characterizes the transcriptome of micrometer-scale anatomical features and can predict spatial gene expression from histology images alone.

Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics.

Single-cell RNA sequencing (scRNA-seq) identifies cell subpopulations within tissue but does not capture their spatial distribution nor reveal local networks of intercellular communication acting in situ. A suite of recently developed techniques that localize RNA within tissue, including multiplexed in situ hybridization and in situ sequencing (here defined as high-plex RNA imaging) and spatial barcoding, can help address this issue. However, no method currently provides as complete a scope of the transcriptome as does scRNA-seq, underscoring the need for approaches to integrate single-cell and spatial data. Here, we review efforts to integrate scRNA-seq with spatial transcriptomics, including emerging integrative computational methods, and propose ways to effectively combine current methodologies.

easyCLIP analysis of RNA-protein interactions incorporating absolute quantification.

Quantitative criteria to identify proteins as RNA-binding proteins (RBPs) are presently lacking, as are criteria to define RBP target RNAs. Here, we develop an ultraviolet (UV) cross-linking immunoprecipitation (CLIP)-sequencing method, easyCLIP. easyCLIP provides absolute cross-link rates, as well as increased simplicity, efficiency, and capacity to visualize RNA libraries during sequencing library preparation. Measurement of >200 independent cross-link experiments across >35 proteins identifies an RNA cross-link rate threshold that distinguishes RBPs from non-RBPs and defines target RNAs as those with a complex frequency unlikely for a random protein. We apply easyCLIP to the 33 most recurrent cancer mutations across 28 RBPs, finding increased RNA binding per RBP molecule for KHDRBS2 R168C, A1CF E34K and PCBP1 L100P/Q cancer mutations. Quantitating RBP-RNA interactions can thus nominate proteins as RBPs and define the impact of specific disease-associated RBP mutations on RNA association.

Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell Carcinoma.

To define the cellular composition and architecture of cutaneous squamous cell carcinoma (cSCC), we combined single-cell RNA sequencing with spatial transcriptomics and multiplexed ion beam imaging from a series of human cSCCs and matched normal skin. cSCC exhibited four tumor subpopulations, three recapitulating normal epidermal states, and a tumor-specific keratinocyte (TSK) population unique to cancer, which localized to a fibrovascular niche. Integration of single-cell and spatial data mapped ligand-receptor networks to specific cell types, revealing TSK cells as a hub for intercellular communication. Multiple features of potential immunosuppression were observed, including T regulatory cell (Treg) co-localization with CD8 T cells in compartmentalized tumor stroma. Finally, single-cell characterization of human tumor xenografts and in vivo CRISPR screens identified essential roles for specific tumor subpopulation-enriched gene networks in tumorigenesis. These data define cSCC tumor and stromal cell subpopulations, the spatial niches where they interact, and the communicating gene networks that they engage in cancer.

White matter integrity in schizophrenia and bipolar disorder: Tract- and voxel-based analyses of diffusion data from the Connectom scanner.

BACKGROUND: Diffusion imaging abnormalities have been associated with schizophrenia (SZ) and bipolar disorder (BD), indicating impaired structural connectivity. Newer methods permit the automated reconstruction of major white matter tracts from diffusion-weighted MR images in each individual's native space. Using high-definition diffusion data from SZ and BP subjects, we investigated brain white matter integrity using both an automated tract-based and voxel-based methods. METHODS: Using a protocol matched to the NIH (Young-Adult) Human Connectome Project (and collected on the same customized 'Connectom' scanner), diffusion scans were acquired from 87 total participants (aged 18-30), grouped as SZ (n = 24), BD (n = 33) and healthy controls (n = 30). Fractional anisotropy (FA) of eighteen white matter tracks were analyzed using the TRACULA software. Voxel-wise statistical analyses of diffusion data was carried out using the tract-based spatial statistics (TBSS) software. TRACULA group effects and clinical correlations were investigated using analyses of variance and multiple regression. RESULTS: TRACULA analysis identified a trend towards lower tract FA in SZ patients, most significantly in the left anterior thalamic radiation (ATR; p = .04). TBSS results showed significantly lower FA voxels bilaterally within the cerebellum and unilaterally within the left ATR, posterior thalamic radiation, corticospinal tract, and superior longitudinal fasciculus in SZ patients compared to controls (FDR corrected p < .05). FA in BD patients did not significantly differ from controls using either TRACULA or TBSS. Multiple regression showed FA of the ATR as predicting chronic mania (p = .0005) and the cingulum-angular bundle as predicting recent mania (p = .02) in patients. TBSS showed chronic mania correlating with FA voxels within the left ATR and corpus callosum. CONCLUSIONS: White matter abnormality in SZ varies in severity across different white matter tract regions. Our results indicate that voxel-based analysis of diffusion data is more sensitive than tract-based analysis in identifying such abnormalities. Absence of white matter abnormality in BD may be related to medication effects and age.

Coupled Single-Cell CRISPR Screening and Epigenomic Profiling Reveals Causal Gene Regulatory Networks.

Here, we present Perturb-ATAC, a method that combines multiplexed CRISPR interference or knockout with genome-wide chromatin accessibility profiling in single cells based on the simultaneous detection of CRISPR guide RNAs and open chromatin sites by assay of transposase-accessible chromatin with sequencing (ATAC-seq). We applied Perturb-ATAC to transcription factors (TFs), chromatin-modifying factors, and noncoding RNAs (ncRNAs) in ∼4,300 single cells, encompassing more than 63 genotype-phenotype relationships. Perturb-ATAC in human B lymphocytes uncovered regulators of chromatin accessibility, TF occupancy, and nucleosome positioning and identified a hierarchy of TFs that govern B cell state, variation, and disease-associated cis-regulatory elements. Perturb-ATAC in primary human epidermal cells revealed three sequential modules of cis-elements that specify keratinocyte fate. Combinatorial deletion of all pairs of these TFs uncovered their epistatic relationships and highlighted genomic co-localization as a basis for synergistic interactions. Thus, Perturb-ATAC is a powerful strategy to dissect gene regulatory networks in development and disease.

Tract-based analysis of white matter integrity in psychotic and nonpsychotic bipolar disorder.

BACKGROUND: At least 50% of individuals with bipolar disorder (BD) present with psychosis during their lifetime. Psychotic symptoms have sometimes been linked to specific genetic and phenotypic markers. This study aims to explore potential differences between bipolar disorder subtypes by measuring white matter integrity of the brain and relationships with clinical measures. METHODS: Diffusion tensor imaging and clinical measures were acquired from 102 participants, grouped as psychotic bipolar disorder (PBD) (n=48), non-psychotic bipolar disorder (NBD) (n=24), and healthy controls (n=30). We utilized a powerful, automated tool (TRACULA: Tracts Constrained by Underlying Anatomy) to analyze the fractional anisotropy (FA) and mean diffusivity (MD) of 18 white matter tracts. RESULTS: Decreased FA in numerous tracts was observed in bipolar disorder groups compared to healthy controls: bilateral cingulum-cingulate gyrus bundles, corticospinal tracts, and superior longitudinal fasciculi as well as the right hemisphere cingulum-angular bundle. Only left uncinate fasciculus FA differed between PBD and NPBD groups. We found no group differences in MD. Positive symptoms correlated with FA in the superior (inversely) and inferior (directly) longitudinal fasciculi. Negative symptoms directly correlated with mean FA of the corticospinal tract and cingulum-angular bundle. LIMITATIONS: Neurotropic, mood-stabilizing medication prescribed for individuals with BD may interact with measures of white matter integrity in our BD participants. CONCLUSION: Our results indicate decreased white matter coherence in BD. Minimal differences in white matter FA between PBD and NPBD participants suggest related underlying neurobiology.

Functional Connectivity of Cognitive Brain Networks in Schizophrenia during a Working Memory Task.

Task-based connectivity studies facilitate the understanding of how the brain functions during cognition, which is commonly impaired in schizophrenia (SZ). Our aim was to investigate functional connectivity during a working memory task in SZ. We hypothesized that the task-negative (default mode) network and the cognitive control (frontoparietal) network would show dysconnectivity. Twenty-five SZ patient and 31 healthy control scans were collected using the customized 3T Siemens Skyra MRI scanner, previously used to collect data for the Human Connectome Project. Blood oxygen level dependent signal during the 0-back and 2-back conditions were extracted within a network-based parcelation scheme. Average functional connectivity was assessed within five brain networks: frontoparietal (FPN), default mode (DMN), cingulo-opercular (CON), dorsal attention (DAN), and ventral attention network; as well as between the DMN or FPN and other networks. For within-FPN connectivity, there was a significant interaction between n-back condition and group (p = 0.015), with decreased connectivity at 0-back in SZ subjects compared to controls. FPN-to-DMN connectivity also showed a significant condition × group effect (p = 0.003), with decreased connectivity at 0-back in SZ. Across groups, connectivity within the CON and DAN were increased during the 2-back condition, while DMN connectivity with either CON or DAN were decreased during the 2-back condition. Our findings support the role of the FPN, CON, and DAN in working memory and indicate that the pattern of FPN functional connectivity differs between SZ patients and control subjects during the course of a working memory task.

Molecular Profiling in Cutaneous Melanoma.

Molecular profiling of malignant tumors is gaining increasing interest in oncology. In recent years, several molecular techniques have been studied in melanoma, with the goal to improve upon the diagnostic and prognostic abilities of currently available clinical and histopathologic parameters. Reliable tests performed early in the diagnosis and management of melanoma could lead to decreased morbidity and mortality by selecting appropriate patients for more-aggressive therapy and sparing those for whom it is not indicated. This article reviews the molecular diagnostic and prognostic techniques currently available for melanoma and evaluates their potential role in clinical practice.

Trends in Outcome and Hospitalization Cost among Adult Patients with Acute Ischemic Stroke in the United States.

INTRODUCTION: New treatments for acute ischemic stroke (AIS) have been introduced and are expected to improve patients' overall outcomes. We assessed the impact of new therapeutic strategies on outcome and cost of hospitalization among adult patients with AIS in the United States. METHODS: Patients with AIS admitted in the United States in 1993-1994 and 2006-2007 were listed using the Nationwide Inpatient Survey database. We determined the rates of occurrence, hospitalization outcomes, and mean hospital charges for all patients. We further analyzed these variables in the ventilated and nonventilated patients. RESULTS: We identified 386,043 patients with AIS admitted in the United States in 1993-1994 and 749,766 patients in 2006-2007. The length of hospitalization was significantly higher in 1993-1994 compared with 2006-2007: 6.9 ± 4.2 days versus 4.66 ± 3 days, respectively. In-hospital mortality rate was 8.9% in 1993-1994 and 5.6% in 2006-2007 (P < 0.0001). There was a significant increase in mean hospital charges in 2006-2007 compared with 1993-1994 ($21,916 ± $14,117 versus $9,646 ± $5,727). The length of hospitalization was significantly shorter in 2006-2007 in nonventilated patients. There was a significant increase in mean hospital charges in 2006-2007 compared with 1993-1994 in both ventilated ($81,528 ± $64,526 versus $25,143 ± $17,172, P<0.0001) and nonventilated patients ($21,085 ± $13,042 versus $10,000 ± $6,300, P<0.0001). The mortality rate was significantly lower in 2006-2007 in both subgroups: 46.5% versus 59.8% in ventilated patients and 4.2% versus 8.2% in nonventilated patients (P < 0.0001). CONCLUSION: Our study suggests that new therapeutic strategies have improved outcomes and increased cost of hospitalization among adult patients with AIS in the United States over a period of 13 years. The hospitalization cost was significantly higher in the ventilated and nonventilated patients in 2006-2007, which may reflect the impact of new therapeutic strategies, the availability of more intensive care units and stroke centers, and the lower mortality rate in this time period.

Therapy-induced tumour secretomes promote resistance and tumour progression.

Drug resistance invariably limits the clinical efficacy of targeted therapy with kinase inhibitors against cancer. Here we show that targeted therapy with BRAF, ALK or EGFR kinase inhibitors induces a complex network of secreted signals in drug-stressed human and mouse melanoma and human lung adenocarcinoma cells. This therapy-induced secretome stimulates the outgrowth, dissemination and metastasis of drug-resistant cancer cell clones and supports the survival of drug-sensitive cancer cells, contributing to incomplete tumour regression. The tumour-promoting secretome of melanoma cells treated with the kinase inhibitor vemurafenib is driven by downregulation of the transcription factor FRA1. In situ transcriptome analysis of drug-resistant melanoma cells responding to the regressing tumour microenvironment revealed hyperactivation of several signalling pathways, most prominently the AKT pathway. Dual inhibition of RAF and the PI(3)K/AKT/mTOR intracellular signalling pathways blunted the outgrowth of the drug-resistant cell population in BRAF mutant human melanoma, suggesting this combination therapy as a strategy against tumour relapse. Thus, therapeutic inhibition of oncogenic drivers induces vast secretome changes in drug-sensitive cancer cells, paradoxically establishing a tumour microenvironment that supports the expansion of drug-resistant clones, but is susceptible to combination therapy.