Cell Type Enrichment Research Articles

Discovery of Novel Drug Candidates for Alzheimer's Disease by Molecular Network Modeling.

To identify the molecular mechanisms and novel therapeutic agents of late-onset Alzheimer’s disease (AD), we performed integrative network analysis using multiple transcriptomic profiles of human brains. With the hypothesis that AD pathology involves the whole cerebrum, we first identified co-expressed modules across multiple cerebral regions of the aging human brain. Among them, two modules (M3 and M8) consisting of 1,429 protein-coding genes were significantly enriched with AD-correlated genes. Differential expression analysis of microarray, bulk RNA-sequencing (RNA-seq) data revealed the dysregulation of M3 and M8 across different cerebral regions in both normal aging and AD. The cell-type enrichment analysis and differential expression analysis at the single-cell resolution indicated the extensive neuronal vulnerability in AD pathogenesis. Transcriptomic-based drug screening from Connectivity Map proposed Gly-His-Lys acetate salt (GHK) as a potential drug candidate that could probably restore the dysregulated genes of the M3 and M8 network. Pretreatment with GHK showed a neuroprotective effect against amyloid-beta-induced injury in differentiated human neuron-like SH-SY5Y cells. Taken together, our findings uncover a dysregulated network disrupted across multiple cerebral regions in AD and propose pretreatment with GHK as a novel neuroprotective strategy against AD.

Analyzing Spatial Transcriptomics Data Using Giotto.

Spatial transcriptomic technologies have been developed rapidly in recent years. The addition of spatial context to expression data holds the potential to revolutionize many fields in biology. However, the lack of computational tools remains a bottleneck that is preventing the broader utilization of these technologies. Recently, we have developed Giotto as a comprehensive, generally applicable, and user-friendly toolbox for spatial transcriptomic data analysis and visualization. Giotto implements a rich set of algorithms to enable robust spatial data analysis. To help users get familiar with the Giotto environment and apply it effectively in analyzing new datasets, we will describe the detailed protocols for applying Giotto without any advanced programming skills. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Getting Giotto set up for use Basic Protocol 2: Pre-processing Basic Protocol 3: Clustering and cell-type identification Basic Protocol 4: Cell-type enrichment and deconvolution analyses Basic Protocol 5: Spatial structure analysis tools Basic Protocol 6: Spatial domain detection by using a hidden Markov random field model Support Protocol 1: Spatial proximity-associated cell-cell interactions Support Protocol 2: Assembly of a registered 3D Giotto object from 2D slices.

Cortical thickness differences are associated with cellular component morphogenesis of astrocytes and excitatory neurons in nonsuicidal self-injuring youth.

Nonsuicidal self-injury (NSSI) generally occurs in youth and probably progresses to suicide. An examination of cortical thickness differences (ΔCT) between NSSI individuals and controls is crucial to investigate potential neurobiological correlates. Notably, ΔCT are influenced by specific genetic factors, and a large proportion of cortical thinning is associated with the expression of genes that overlap in astrocytes and pyramidal cells. However, in NSSI youth, the mechanisms underlying the relations between the genetic and cell type-specific transcriptional signatures to ΔCT are unclear. Here, we studied the genetic association of ΔCT in NSSI youth by performing a partial least-squares regression (PLSR) analysis of gene expression data and 3D-T1 brain images of 45 NSSI youth and 75 controls. We extracted the top-10 Gene Ontology terms for the enrichment results of upregulated PLS component 1 genes related to ΔCT to conduct the cell-type classification and enrichment analysis. Enrichment of cell type-specific genes shows that cellular component morphogenesis of astrocytes and excitatory neurons accounts for the observed NSSI-specific ΔCT. We validated the main results in independent datasets to verify the robustness and specificity. We concluded that the brain ΔCT is associated with cellular component morphogenesis of astrocytes and excitatory neurons in NSSI youth.

Sex-Specific Cell Types and Molecular Pathways Indicate Fibro-Calcific Aortic Valve Stenosis.

BackgroundAortic stenosis (AS) is the most common valve disorder characterized by fibro-calcific remodeling of leaflets. Recent evidence indicated that there is a sex-related difference in AS development and progression. Fibrotic remodeling is peculiar in women’s aortic valves, while men’s leaflets are more calcified. Our study aimed to assess aortic valve fibrosis (AVF) in a severe AS cohort using non-invasive diagnostic tools and determine whether sex-specific pathological pathways and cell types are associated with severe AS.Materials and MethodsWe have included 28 men and 28 women matched for age with severe AS who underwent echocardiography and cardiac contrast-enhanced computed tomography (CT) before intervention. The calcium and fibrosis volumes were assessed and quantified using the ImageJ thresholding method, indexed calcium and fibrosis volume were calculated by dividing the volume by the aortic annular area. For a deeper understanding of molecular mechanisms characterizing AS disorder, differentially expressed genes and functional inferences between women and men’s aortic valves were carried out on a publicly available microarray-based gene expression dataset (GSE102249). Cell types enrichment analysis in stenotic aortic valve tissues was used to reconstruct the sex-specific cellular composition of stenotic aortic valves.ResultsIn agreement with the literature, our CT quantifications showed that women had significantly lower aortic valve calcium content compared to men, while fibrotic tissue composition was significantly higher in women than men. The expression profiles of human stenotic aortic valves confirm sex-dependent processes. Pro-fibrotic processes were prevalent in women, while pro-inflammatory ones, linked to the immune response system, were enhanced in men. Cell-type enrichment analysis showed that mesenchymal cells were over-represented in AS valves of women, whereas signatures for monocytes, macrophages, T and B cells were enriched men ones.ConclusionsOur data provide the basis that the fibro-calcific process of the aortic valve is sex-specific, both at gene expression and cell type level. The quantification of aortic valve fibrosis by CT could make it possible to perform population-based studies and non-invasive assessment of novel therapies to reduce or halt sex-related calcific aortic valve stenosis (CAVS) progression, acting in an optimal window of opportunity early in the course of the disease.

Multi-transcriptomic analysis points to early organelle dysfunction in human astrocytes in Alzheimer's disease

The phenotypic transformation of astrocytes in Alzheimer's disease (AD) is still not well understood. Recent analyses based on single-nucleus RNA sequencing of postmortem Alzheimer's disease (AD) samples are limited by the low number of sequenced astrocytes, small cohort sizes, and low number of differentially expressed genes detected. To optimize the detection of astrocytic genes, we employed a novel strategy consisting of the localization of pre-determined astrocyte and neuronal gene clusters in publicly available whole-brain transcriptomes. Specifically, we used cortical transcriptomes from 766 individuals, including cognitively normal subjects (Controls), and people diagnosed with mild cognitive impairment (MCI) or dementia due to AD. Samples came from three independent cohorts organized by the Mount Sinai Hospital, the Mayo Clinic, and the Religious Order Study/Memory and Aging Project (ROSMAP). Astrocyte- and neuron-specific gene clusters were generated from human brain cell-type specific RNAseq data using hierarchical clustering and cell-type enrichment scoring. Genes from each cluster were manually annotated according to cell-type specific functional Categories. Gene Set Variation Analysis (GSVA) and Principal Component Analysis (PCA) were used to establish changes in these functional categories among clinical cohorts. We highlight three novel findings of the study. First, individuals with the same clinical diagnosis were molecularly heterogeneous. Particularly in the Mayo Clinic and ROSMAP cohorts, over 50% of Controls presented down-regulation of genes encoding synaptic proteins typical of AD, whereas 30% of patients diagnosed with dementia due to AD presented Control-like transcriptomic profiles. Second, down-regulation of neuronal genes related to synaptic proteins coincided, in astrocytes, with up-regulation of genes related to perisynaptic astrocytic processes (PAP) and down-regulation of genes encoding endolysosomal and mitochondrial proteins. Third, down-regulation of astrocytic mitochondrial genes inversely correlated with the disease stages defined by Braak and CERAD scoring. Finally, we interpreted these changes as maladaptive or adaptive from the point of view of astrocyte biology in a model of the phenotypical transformation of astrocytes in AD. The main prediction is that early malfunction of the astrocytic endolysosomal system, associated with progressive mitochondrial dysfunction, contribute to Alzheimer's disease. If this prediction is correct, therapies preventing organelle dysfunction in astrocytes may be beneficial in preclinical and clinical AD.

Characterization of the Cellular Microenvironment and Novel Specific Biomarkers in Pterygia Using RNA Sequencing.

With a worldwide prevalence of ~12%, pterygium is a common degenerative and environmentally triggered ocular surface disorder characterized by wing-shaped growth of conjunctival tissue onto the cornea that can lead to blindness if left untreated. This study characterizes the transcriptional profile and the cellular microenvironment of conjunctival pterygia and identifies novel pterygia-specific biomarkers. Formalin-fixed and paraffin-embedded pterygia as well as healthy conjunctival specimens were analyzed using MACE RNA sequencing (n = 8 each) and immunohistochemistry (pterygia n = 7, control n = 3). According to the bioinformatic cell type enrichment analysis using xCell, the cellular microenvironment of pterygia was characterized by an enrichment of myofibroblasts, T-lymphocytes and various antigen-presenting cells, including dendritic cells and macrophages. Differentially expressed genes that were increased in pterygia compared to control tissue were mainly involved in autophagy (including DCN, TMBIM6), cellular response to stress (including TPT1, DDX5) as well as fibroblast proliferation and epithelial to mesenchymal transition (including CTNNB1, TGFBR1, and FN1). Immunohistochemical analysis confirmed a significantly increased FN1 stromal immunoreactivity in pterygia when compared to control tissue. In addition, a variety of factors involved in apoptosis were significantly downregulated in pterygia, including LCN2, CTSD, and NISCH. Furthermore, 450 pterygia-specific biomarkers were identified by including transcriptional data of different ocular surface pathologies serving as controls (training group), which were then validated using transcriptional data of cultured human pterygium cells. Among the most pterygia-specific factors were transcripts such as AHNAK, RTN4, TPT1, FSTL1, and SPARC. Immunohistochemical validation of SPARC revealed a significantly increased stromal immunoreactivity in pterygia when compared to controls, most notably in vessels and intravascular vessel wall-adherent mononuclear cells. Taken together, the present study provides new insights into the cellular microenvironment and the transcriptional profile of pterygia, identifies new and specific biomarkers and in addition to fibrosis-related genes, uncovers autophagy, stress response and apoptosis modulation as pterygium-associated processes. These findings expand our understanding of the pathophysiology of pterygia, provide new diagnostic tools, and may enable new targeted therapeutic options for this common and sight-threatening ocular surface disease.

Microbiota of the prostate tumor environment investigated by whole-transcriptome profiling

BackgroundWith over 350,000 estimated deaths worldwide in 2018, prostate cancer (PCa) continues to be a major health concern and a significant cause of cancer-associated mortality among men. While cancer in general is considered a disease of the human genome, there is a growing body of evidence suggesting that changes to the healthy microbiota could play a vital role in cancer development, progression, and/or treatment outcome.MethodsUsing a metatranscriptomic approach, we annotated the microbial reads obtained from total RNA sequencing of 106 prostate tissue samples from 94 PCa patients (discovery cohort). We investigated microbial dysbiosis associated with PCa by systematically comparing the microbiomes between benign and malignant tissue samples, between less vs. more-aggressive PCa, and between patients who had biochemical recurrence as opposed to those who did not. We further performed differential gene expression and cell type enrichment analysis to explore the host transcriptomic and cellular responses to selected microbial genera. A public dataset (GSE115414) of total RNA sequencing reads from 24 prostate tissue samples (8 benign and 16 malignant) served as the validation cohort.ResultsWe observed decreased species diversity and significant under-representation of Staphylococcus saprophyticus and Vibrio parahaemolyticus, as well as significant over-abundance of Shewanella in malignant as compared to benign prostate tissue samples in both the discovery (p < 0.01) and validation (p < 0.05) cohorts. In addition, we identified Microbacterium species (p < 0.01) to be significantly over-abundant in pathologically advanced T3 tumors compared to T2 in the discovery cohort. Malignant samples having high vs. low Shewanella counts were associated with downregulated Toll-like receptor signaling pathways and decreased enrichment of dendritic cells. Malignant samples having low vs. high V. parahaemolyticus counts were enriched for olfactory transduction and drug metabolism pathways. Finally, malignant samples were enriched for M1 and M2 macrophages as compared to benign tissue samples.ConclusionsThe results from this exploratory study support the existence of an important biological link between the prostate microbiota and PCa development/progression. Our results highlight Shewanella, V. parahaemolyticus, and Microbacterium sp. as interesting candidates for further investigation of their association with PCa.

P086 Mucosal microbiota modulate host intestinal immune signatures in Inflammatory Bowel Disease

Abstract Background Host intestinal immune gene signatures and microbial dysregulations expose potential mechanisms in the pathogenesis of inflammatory bowel diseases (IBD). Profiling of mucosa-attached microbiota allows the understanding of locally present microbial communities and their immediate impact on the host. This study evaluated interactions between host mucosal gene expression and intestinal mucosa-attached microbiota in IBD. Methods Intestinal mucosal bulk RNA-sequencing data was combined with mucosal 16S rRNA gene sequencing data from 696 intestinal biopsies derived from 337 patients with IBD (181 with Crohn’s disease [CD] and 156 with ulcerative colitis [UC]) and 16 non-IBD controls. Hierarchical all-against-all associations testing (HAllA) was used to assess factors affecting host gene expressions and microbiota. Mucosal cell enrichments were predicted by deconvolution. Linear mixed interaction models were used to investigate host-microbiota interactions, adjusting for age, sex, BMI and batch effects. Variation explanation analysis was performed by Lasso regression. Results In total, 15,934 intestinal genes and 113 microbial taxa were identified and included in subsequent analyses. Host intestinal gene expressions were characterized by tissue- and inflammation-specificity, whereas intraindividual variability of the mucosal microbiota dominated over disease location and inflammation effects. We observed forty associations between the mucosal expression of genes and the abundance of specific microbes independent of dysbiosis (FDR&amp;lt;0.05). Examples include a positive association between aryl hydrocarbon receptor (AHR) and Bifidobacterium, and a negative association between interleukin 18 receptor 1 (IL18R1) and Lachnoclostridium. Furthermore, 112 gene-microbiota interactions changed in patients with microbial dysbiosis compared to non-dysbiosis (FDR&amp;lt;0.05). These interactions were enriched in immune-related and extracellular matrix organization pathways. For example, the IL1R1 gene was positively associated with Collinsella abundance in non-dysbiotic patients, whereas an inverse association was observed in high dysbiosis. Finally, the presence of mucosal microbial taxa explained up to 10% of the variation in cell type enrichment, affecting epithelial cells, macrophages and regulatory T-cells. Conclusion Interactions between host intestinal gene expressions and mucosa-attached microbiota are disrupted in patients with IBD. Furthermore, mucosal microbiota are highly personalized and potentially contribute to intestinal cell type alterations. Our study unravels key immune-mediated molecular pathways and relevant bacteria in intestinal tissue, which may guide drug development and precision medicine in IBD.

Pre-transplant Transcriptional Signature in Peripheral Blood Mononuclear Cells of Acute Renal Allograft Rejection.

Acute rejection (AR) is closely associated with renal allograft dysfunction. Here, we utilised RNA sequencing (RNA-Seq) and bioinformatic methods to characterise the peripheral blood mononuclear cells (PBMCs) of patients with acute renal allograft rejection. Pretransplant blood samples were collected from 32 kidney allograft donors and 42 corresponding recipients with biopsies classified as T cell-mediated rejection (TCMR, n = 18), antibody-mediated rejection (ABMR, n = 5), and normal/non-specific changes (non-AR, n = 19). The patients with TCMR and ABMR were assigned to the AR group, and the patients with normal/non-specific changes (n = 19) were assigned to the non-AR group. We analysed RNA-Seq data for identifying differentially expressed genes (DEGs), and then gene ontology (GO) analysis, Reactome, and ingenuity pathway analysis (IPA), protein—protein interaction (PPI) network, and cell-type enrichment analysis were utilised for bioinformatics analysis. We identified DEGs in the PBMCs of the non-AR group when compared with the AR, ABMR, and TCMR groups. Pathway and GO analysis showed significant inflammatory responses, complement activation, interleukin-10 (IL-10) signalling pathways, classical antibody-mediated complement activation pathways, etc., which were significantly enriched in the DEGs. PPI analysis showed that IL-10, VEGFA, CXCL8, MMP9, and several histone-related genes were the hub genes with the highest degree scores. Moreover, IPA analysis showed that several proinflammatory pathways were upregulated, whereas antiinflammatory pathways were downregulated. The combination of NFSF14+TANK+ANKRD 33 B +HSPA1B was able to discriminate between AR and non-AR with an AUC of 92.3% (95% CI 82.8–100). Characterisation of PBMCs by RNA-Seq and bioinformatics analysis demonstrated gene signatures and biological pathways associated with AR. Our study may provide the foundation for the discovery of biomarkers and an in-depth understanding of acute renal allograft rejection.

Patient-Oriented Perspective on Chemokine Receptor Expression and Function in Glioma.

Simple SummaryChemokines and their receptors have been pointed out as key actors in a variety of human cancers, playing pivotal roles in multiples processes and pathways. The present study aims at deciphering the functions of several chemokine receptors in gliomas, starting from publicly available patient-derived transcriptomic data with support from the current literature in the field, and sheds light on the clinical relevance of chemokine receptors in targeted therapeutic approaches for glioma patients.Gliomas are severe brain malignancies, with glioblastoma (GBM) being the most aggressive one. Despite continuous efforts for improvement of existing therapies, overall survival remains poor. Over the last years, the implication of chemokines and their receptors in GBM development and progression has become more evident. Recently, large amounts of clinical data have been made available, prompting us to investigate chemokine receptors in GBM from a still-unexplored patient-oriented perspective. This study aims to highlight and discuss the involvement of chemokine receptors—CCR1, CCR5, CCR6, CCR10, CX3CR1, CXCR2, CXCR4, ACKR1, ACKR2, and ACKR3—most abundantly expressed in glioma patients based on the analysis of publicly available clinical datasets. Given the strong intratumoral heterogeneity characterizing gliomas and especially GBM, receptor expression was investigated by glioma molecular groups, by brain region distribution, emphasizing tissue-specific receptor functions, and by cell type enrichment. Our study constitutes a clinically relevant and patient-oriented guide that recapitulates the expression profile and the complex roles of chemokine receptors within the highly diversified glioma landscape. Additionally, it strengthens the importance of patient-derived material for development and precise amelioration of chemokine receptor-targeting therapies.

Cellular proteomic profiling using proximity labeling by TurboID in microglial and neuronal cell lines

AbstractBackgroundDespite advancements in systems‐level analyses to Alzheimer's disease, global proteomic profiling of brain homogenate cannot resolve molecular changes occurring in distinct cell types. Proximity labeling of proteins by the biotin‐ligase TurboID, coupled with mass spectrometry (MS) analyses of biotinylated proteins, can resolve cell‐type specific proteomes from brain without cell type enrichment. Before in‐vivo applications, it is important to identify proteins preferentially labeled by TurboID in mammalian cells, and directly compare biotinylated proteomes with whole cell proteomes. We determined whether TurboID‐labeled proteomes in microglial (BV2) and neuronal (N2A) cell lines are representative of total cellular proteomes under homeostatic and activated conditions.MethodWe generated N2A and BV2 cell lines that stably express TurboID fused to a nuclear export sequence. Cells incubated in 200μM biotin and 1μg/mL lipopolysaccharide (LPS) for 48hrs to mimic inflammatory stress. Western blotting and label‐free quantitation MS identified biotinylated proteins in whole‐cell‐lysates and streptavidin‐enriched preparations.ResultWestern‐blot confirmed robust biotinylation in TurboID N2A and BV2 cell‐lines. LFQ‐MS quantified &gt;3,000 proteins in inputs and &gt;2,400 proteins in biotinylated proteomes from both cell types. In BV2 and N2A inputs, TurboID expression and biotinylation didn't impact the proteome, evidenced by few differentially‐expressed proteins and absence of cellular respiration measures in mitochondrial stress‐tests, comparing TurboID and non‐TurboID cells. Of all the proteins quantified in BV2 and N2A TurboID inputs, ∼50% were also quantified in the biotinylated proteomes in both cell types. Compared to input proteomes of both cell types, the biotinylated proteome was enriched in vesicular, ribosomal, mitochondrial, cytoplasmic and cytoskeletal proteins. The biotinylated proteome successfully differentiated BV2 and N2A cells. LPS stimulation altered levels of 759 proteins in BV2 cells in the input proteome, of which the top increased (e.g. Irg1, Oasl1, Cyb5a) and decreased (e.g. Mrc1, Mgl2, Arg1) proteins showed concordant changes in the biotinylated BV2 proteome.ConclusionOur analyses show that proteomic labeling by TurboID in microglial and neuronal cell lines doesn't disrupt cellular function. The resulting biotinylated proteomes are reasonably representative of the whole‐cell proteome and captures the most robust alterations induced by immune stimuli in microglia. These foundational data will guide future applications of proximity‐labeling for cell‐type‐specific proteomics in‐vivo.

Neuroproteomics of cognitively healthy centenarians in the context of aging and Alzheimer's disease.

Aging is often accompanied by neurodegenerative diseases such as Alzheimer's disease (AD), and their associated neuropathological hallmarks. Few individuals are able to maintain cognitive health until extreme ages, such as cognitively healthy centenarians, despite displaying substantial pathology in their brains. Here we report on a unique and large single-center proteomics study providing insight into proteome changes occurring with AD and aging. We investigate which mechanisms could be involved in maintaining cognitive health at extreme ages in the presence of pathology. We performed quantitative proteomics on middle temporal lobe tissue for a cohort of 61 non-demented and 91 AD individuals across the age-continuum, and 58 centenarians from the 100-plus Study. We performed enrichment analyses for cell-types and GO-terms using multiple approaches (Figure 1). We identified 3,448 proteins, among which proteins associated with AD Braak stage or age. 472 proteins were associated with Braak stages, independent of age. Cell-type enrichment revealed that with increasing Braak stages, the abundance of astrocytic proteins increased while the abundance of neuronal proteins decreased. Among centenarians we identified 13 proteins that that differ in abundance from AD cases with the same Braak stage (IV). These included ubiquitin, cytoskeletal and synaptic proteins. Additionally, we identified 174 age-related proteins in non-demented controls. Of these, 97 were expressed in centenarians at levels different from those predicted for their age. Cell-type enrichment revealed that the abundance of oligodendrocytic proteins decreased with age, whereas the abundance of astrocytic proteins was increased with age and Braak stage. Progressive AD stages are associated with increased abundance of astrocytic- and lower abundance of neuronal proteins, while healthy aging is associated with a lower abundance of oligodendrocytic proteins and higher abundance of astrocytic proteins. In this study we identified proteins in the centenarians that deviate in level from prediction based on age. How these proteins act on cognition needs to be investigated further. Centenarian-specific proteins at Braak stage IV may indicate mechanisms protecting against cognitive decline, whereas the centenarian-specific age-related proteins might indicate processes that prevent adverse brain aging.

A Novel Transcriptomic Classifier for AML Is Highly Associated with Drug Sensitivity

Introduction: AML is a heterogeneous disease with a wide array of common genetic aberrations. Traditional classification of AML leverages both classical cytogenetics and mutational profiling to stratify patients into four distinct risk groups (ELN). However, tumor gene expression profiles can play an important role in response to therapy, and are potentially useful for unravelling the heterogeneity of AML. In this study, we hypothesized that clinical outcomes and variable responses to therapeutic modalities in AML may be driven by patterns of gene expression, and sought to identify clinically actionable molecular subtypes using the available RNAseq data from the BEAT AML functional genomics study.Methods: Unsupervised machine learning approach based on consensus non-negative matrix factorization (cNMF) was applied to VOOM normalized BEAT-AML RNAseq data from patient samples with ≥50% blasts (N=389) to identify transcriptomic-based molecular subtypes. The subtypes were then compared to the genomic based subtypes for their association with clinical outcome (log-rank test) and ex-vivo drug sensitivity (Kruskal Wallis test). Subtypes were also biologically characterized by gene signature scoring using well curated pathway signatures (GSVA analysis using Hallmark pathways), cell type enrichment (xCell enrichment) and AML differentiation state (scRNAseq signature based on Van Galen et. al). Finally, a random forest classifier was defined based on samples from BEAT AML to predict the NMF subtypes in an independent data set (TCGA AML cohort).Results: Our cNMF based analysis identified six clusters of patients based on the 5,060 (top 10%) most variable genes. These novel subtypes were strongly prognostic (Figure 1A, log rank p=2.79e-08), and were independent of ELN genomic based subtypes (anova p=4.45e-07). Comparison to other genomic based classification is ongoing. The prognostic value of the transcriptomic subtypes was further validated by predicting the subtypes in an independent cohort (TCGA LAML, N=200). We observed a significant association with outcome (Figure 1B, p=0.00013), with clusters 5 and 1 showing markedly better prognosis, similar to BEATAML. These subtypes also displayed unique biological profiles, including significant association with scRNAseq-derived AML differentiation state cell types, Hallmark pathways and cellularity signatures. Notably, clusters 1 and 3 showed a mature phenotype, while clusters 2, 4, and 5 were more progenitor-like (table 1).Importantly, the transcriptomic subtypes were highly predictive of ex-vivo drug sensitivity, with sensitivity to 70 compounds significantly associated with cNMF subtype (Kruskal Wallis p>0.01), compared with 4 in the ELN subtypes.Of the tested molecules, single agent Venetoclax was the most strongly associated with subtype (p=1.7e-13); two subtypes were strongly resistant (median IC50 of 10uM) and four were sensitive, with IC50s in the sub-micromolar range (Table 1). No association was seen between the ELN subtypes and venetoclax sensitivity (p=.35).Conclusions: Unsupervised machine learning-based clustering analysis of transcriptomic data identified six novel subtypes which are similarly prognostic as the ELN genomic based subtype and provide a novel avenue for identifying clinically actionable subsets of AML. [Display omitted] DisclosuresHamidi: Genentech: Current Employment, Current equity holder in publicly-traded company. Bolen: Genentech: Current Employment; F. Hoffmann-La Roche: Current equity holder in publicly-traded company. Lasater: Genentech: Current Employment, Current equity holder in publicly-traded company. Dunshee: Genentech/Roche: Current Employment, Current equity holder in publicly-traded company. Punnoose: Genentech: Current Employment, Current equity holder in publicly-traded company. Dail: Genentech/Roche: Current Employment, Current equity holder in publicly-traded company.

Comprehensive analyses of RNA-seq and genome-wide data point to enrichment of neuronal cell type subsets in neuropsychiatric disorders

Neurological and psychiatric disorders, including substance use disorders, share a range of symptoms, which could be the result of shared genetic background. Many genetic loci have been identified for these disorders using genome-wide association studies, but conclusive evidence about cell types wherein these loci are active is lacking. We aimed to uncover implicated brain cell types in neuropsychiatric traits and to assess consistency in results across RNA datasets and methods. We therefore comprehensively employed cell type enrichment methods by integrating single-cell transcriptomic data from mouse brain regions with an unprecedented dataset of 42 human genome-wide association study results of neuropsychiatric, substance use and behavioral/quantitative brain-related traits (n = 12,544,007 individuals). Single-cell transcriptomic datasets from the Karolinska Institute and 10x Genomics were used. Cell type enrichment was determined using Linkage Disequilibrium Score Regression, Multi-marker Analysis of GenoMic Annotation, and Data-driven Expression Prioritized Integration for Complex Traits. We found the largest degree of consistency across methods for implication of pyramidal cells in schizophrenia and cognitive performance. For other phenotypes, such as bipolar disorder, two methods implicated the same cell types, i.e., medium spiny neurons and pyramidal cells. For autism spectrum disorders and anorexia nervosa, no consistency in implicated cell types was observed across methods. We found no evidence for astrocytes being consistently implicated in neuropsychiatric traits. In conclusion, we provide comprehensive evidence for a subset of neuronal cell types being consistently implicated in several, but not all psychiatric disorders, while non-neuronal cell types seem less implicated.

Identification of VCAN as Hub Gene for Diabetic Kidney Disease Immune Injury Using Integrated Bioinformatics Analysis.

Background: Diabetic kidney disease (DKD) is a leading cause of chronic kidney disease in China. Tubular injury contributes to the progression of DKD. Our study was conducted to explore the differential gene expression profiles between kidneys from patients with DKD and kidney living donors (LDs).Methods: In total, seven DKD and eighteen LD gene expression profiles from the GSE104954 dataset were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were analyzed in R with the limma package. DEGs were uploaded to the g:Profiler online database to explore the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Ingenuity pathway analysis (IPA) was carried out using online IPA software. Weighted gene co-expression network analysis (WGCNA) was performed using the WGCNA R package. By integrating DEGs and genes from the top 1 phenotype-gene associated module, we determined the hub gene. We next tested the hub gene, VCAN, in the GSE30122 dataset. We also validated the versican levels in human kidney tissues, explored immune cell type enrichment using an online database xCell, and investigated the correlation between cell types and VCAN expression.Results: A total of 563 DEGs was identified. A large number of pathways were involved in the immune response process according to the results of GO, KEGG, and IPA. Using WGCNA, we selected the lightcyan module in which genes showed the strongest correlation with the phenotype and smallest P-value. We also identified VCAN as a hub gene by integrating DEG analysis and WGCNA. Versican expression was upregulated in human diabetic kidney tissue. Moreover, versican was speculated to play a role in immune injury according to the enrichment of functions and signaling pathways. VCAN transcript levels correlate with the assembly of immune cells in the kidney.Conclusion: Immune processes played an essential role in DKD tubulointerstitium injury. The hub gene VCAN contributed to this process.

A systems-level analysis highlights microglial activation as a modifying factor in common epilepsies.

The causes of distinct patterns of reduced cortical thickness in the common human epilepsies, detectable on neuroimaging and with important clinical consequences, are unknown. We investigated the underlying mechanisms of cortical thinning using a systems-level analysis. Imaging-based cortical structural maps from a large-scale epilepsy neuroimaging study were overlaid with highly spatially resolved human brain gene expression data from the Allen Human Brain Atlas. Cell-type deconvolution, differential expression analysis and cell-type enrichment analyses were used to identify differences in cell-type distribution. These differences were followed up in post-mortem brain tissue from humans with epilepsy using Iba1 immunolabelling. Furthermore, to investigate a causal effect in cortical thinning, cell-type-specific depletion was used in a murine model of acquired epilepsy. We identified elevated fractions of microglia and endothelial cells in regions of reduced cortical thickness. Differentially expressed genes showed enrichment for microglial markers and, in particular, activated microglial states. Analysis of post-mortem brain tissue from humans with epilepsy confirmed excess activated microglia. In the murine model, transient depletion of activated microglia during the early phase of the disease development prevented cortical thinning and neuronal cell loss in the temporal cortex. Although the development of chronic seizures was unaffected, the epileptic mice with early depletion of activated microglia did not develop deficits in a non-spatial memory test seen in epileptic mice not depleted of microglia. These convergent data strongly implicate activated microglia in cortical thinning, representing a new dimension for concern and disease modification in the epilepsies, potentially distinct from seizure control.

Rheumatoid arthritis, systemic lupus erythematosus and primary Sjögren’s syndrome shared megakaryocyte expansion in peripheral blood

ObjectivesRheumatoid arthritis (RA), systemic lupus erythematosus (SLE) and primary Sjögren’s syndrome (pSS) share many clinical manifestations and serological features. The aim of this study was to identify the common transcriptional...

Genome-wide association study followed by trans-ancestry meta-analysis identify 17 new risk loci for schizophrenia

BackgroundOver 200 schizophrenia risk loci have been identified by genome-wide association studies (GWASs). However, the majority of risk loci were identified in populations of European ancestry (EUR), potentially missing important biological insights. It is important to perform 5 GWASs in non-European populations.MethodsTo identify novel schizophrenia risk loci, we conducted a GWAS in Han Chinese population (3493 cases and 4709 controls). We then performed a large-scale meta-analysis (a total of 143,438 subjects) through combining our results with previous GWASs conducted in EAS and EUR. In addition, we also carried out comprehensive post-GWAS analysis, including heritability partitioning, enrichment of schizophrenia associations in tissues and cell types, trancscriptome-wide association study (TWAS), expression quantitative trait loci (eQTL) and differential expression analysis.ResultsWe identified two new schizophrenia risk loci, including associations in SHISA9 (rs7192086, P = 4.92 × 10-08) and PES1 (rs57016637, P = 2.33 × 10−11) in Han Chinese population. A fixed-effect meta-analysis (a total of 143,438 subjects) with summary statistics from EAS and EUR identifies 15 novel genome-wide significant risk loci. Heritability partitioning with linkage disequilibrium score regression (LDSC) reveals a significant enrichment of schizophrenia heritability in conserved genomic regions, promoters, and enhancers. Tissue and cell-type enrichment analyses show that schizophrenia associations are significantly enriched in human brain tissues and several types of neurons, including cerebellum neurons, telencephalon inhibitory, and excitatory neurons. Polygenic risk score profiling reveals that GWAS summary statistics from trans-ancestry meta-analysis (EAS + EUR) improves prediction performance in predicting the case/control status of our sample. Finally, transcriptome-wide association study (TWAS) identifies risk genes whose cis-regulated expression change may have a role in schizophrenia.ConclusionsOur study identifies 17 novel schizophrenia risk loci and highlights the importance and necessity of conducting genetic study in different populations. These findings not only provide new insights into genetic etiology of schizophrenia, but also facilitate to delineate the pathophysiology of schizophrenia and develop new therapeutic targets.

Immune cell analyses of the tumor microenvironment in prostate cancer highlight infiltrating regulatory T cells and macrophages as adverse prognostic factors.

Improved risk stratification is needed for patients with localized prostate cancer. This study characterized and assessed the prognostic potential of distinct immune cell infiltration patterns in the prostate tumor microenvironment. Using tissue microarrays, multiplex immunohistochemistry/immunofluorescence, and automated digital pathology, we analyzed radical prostatectomy specimens from two large patient cohorts (training: n = 470; validation: n = 333) to determine infiltration levels of seven immune cell types in malignant versus benign prostate tissue: CD3+ CD8- FoxP3- T helper cells, CD3+ CD8+ FoxP3- cytotoxic T cells (CTLs), CD3+ CD8- FoxP3+ regulatory T cells (Tregs ), CD20+ B cells, CD68+ CD163- M1 macrophages, CD68+ CD163+ M2 macrophages, and tryptase+ mast cells. Results were further validated by cell type enrichment analyses of bulk tumor RNAseq data from a third independent patient cohort (n = 99). Prognostic potential was assessed by Kaplan-Meier and uni-/multi-variate Cox regression analyses. Clinical endpoint was biochemical recurrence. All seven immune cell types were enriched in prostate cancer versus benign stroma, while there was selective enrichment for B cells, Tregs , M1 and M2 macrophages, and depletion of mast cells and CTLs in prostate cancer epithelium. In all three cohorts, high levels of infiltrating Tregs , M1, and M2 macrophages in stroma and/or epithelium were associated with biochemical recurrence (p < 0.05; log-rank test). After adjustment for routine clinical variables, Tregs and M2 macrophages remained significant adverse predictors of biochemical recurrence (p < 0.05; multivariate Cox regression). Our comprehensive analyses of immune cell infiltration patterns in the prostate tumor microenvironment highlight infiltrating Tregs , M1, and M2 macrophages as adverse predictors of prostate cancer outcome. © 2021 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Single-Cell Transcriptome Analysis of Embryonic Erythro-Myeloid Progenitor Cells Reveals Lineage Heterogeneity

The paradigm that multipotential hematopoietic stem cells (HSC) differentiate through a hierarchical series of increasingly specified progenitors has recently been challenged by single cell transcriptome analyses, which suggest greater heterogeneity in progenitor populations and hierarchy than previously thought. These studies are complicated by the wide variety of hematopoietic progenitors at different stages of maturation concurrently present in the adult bone marrow. In the early mammalian embryo, unique hematopoietic progenitors arise prior to, and independently of, HSC. These include erythro-myeloid progenitors (EMP) that arise from hemogenic endothelium in the yolk sac and migrate to the fetal liver to jump-start definitive hematopoiesis before HSC emerge. In vitro, EMP can generate definitive erythroid, megakaryocyte and myeloid cells, although not B-cells, and include at least some single cells with both erythroid and myeloid potential (McGrath et al. 2015 Cell Rep. 11:1892). We have previously shown that day 9.5 (E9.5) murine EMP have a unique and uniform (kit+CD41+CD16/32+) immunophenotype in the yolk sac and circulation, which is maintained as they colonize the E10.5 liver. We performed single-cell transcriptome analysis of this apparently poised, embryonic-specific multi-potential hematopoietic progenitor population, asking whether it contains an underlying heterogeneity or intrinsic lineage hierarchy. High quality data, as assessed by transcriptomic complexity, read depth, and alignment distributions, were generated for 133 single-cell EMP (scEMP) derived from E9.5 mouse embryos. Use both of supervised and of semi-supervised analytical approaches uncovered transcriptome heterogeneity that allowed clustering of scEMP by expression patterns. Based on expression of known lineage-directing transcription factors and cell type enrichment analysis, clusters of cells were identified that could be annotated as multipotential hematopoietic, megakaryocyte/erythroid, myeloid, and a more specific macrophage lineage potential. A novel binary reduction data integration and transformation methods was developed and utilized to further refine and characterize single-cell classifications by facilitating cross platform comparisons with single cell RNA-seq data obtained from EMP progeny in E11.5 liver and with published gene expression datasets derived from adult hematopoietic progenitors and fetal macrophage populations. Predictions of lineage potential based on our analytical approaches were tested by sorting cells based on immunophenotypic markers differentially expressed in specific clusters and analyzing their potential using single cell colony-forming assays. These functional studies support the concept that immunophenotypically homogeneous EMP contain subpopulations of multipotential progenitors differentiating into erythro-megakaryocyte, myeloid, and macrophage-specific lineage fates. DisclosuresNo relevant conflicts of interest to declare.