scholarly journals CD16+ monocytes give rise to CD103+RALDH2+TCF4+ dendritic cells with unique transcriptional and immunological features

2018 ◽  
Vol 2 (21) ◽  
pp. 2862-2878 ◽  
Author(s):  
Vanessa Sue Wacleche ◽  
Amélie Cattin ◽  
Jean-Philippe Goulet ◽  
Dominique Gauchat ◽  
Annie Gosselin ◽  
...  
Keyword(s):  
Dendritic Cells ◽  
Meta Analysis ◽  
Transcriptional Profiling ◽  
Enrichment Analysis ◽  
Immature Stage ◽  
Gene Set Enrichment Analysis ◽  
Viral Pathogens ◽  
Genome Wide ◽  
Canonical Pathways

Abstract Classical CD16− vs intermediate/nonclassical CD16+ monocytes differ in their homing potential and biological functions, but whether they differentiate into dendritic cells (DCs) with distinct contributions to immunity against bacterial/viral pathogens remains poorly investigated. Here, we employed a systems biology approach to identify clinically relevant differences between CD16+ and CD16− monocyte-derived DCs (MDDCs). Although both CD16+ and CD16− MDDCs acquire classical immature/mature DC markers in vitro, genome-wide transcriptional profiling revealed unique molecular signatures for CD16+ MDDCs, including adhesion molecules (ITGAE/CD103), transcription factors (TCF7L2/TCF4), and enzymes (ALDH1A2/RALDH2), whereas CD16− MDDCs exhibit a CDH1/E-cadherin+ phenotype. Of note, lipopolysaccharides (LPS) upregulated distinct transcripts in CD16+ (eg, CCL8, SIGLEC1, MIR4439, SCIN, interleukin [IL]-7R, PLTP, tumor necrosis factor [TNF]) and CD16− MDDCs (eg, MMP10, MMP1, TGM2, IL-1A, TNFRSF11A, lysosomal-associated membrane protein 1, MMP8). Also, unique sets of HIV-modulated genes were identified in the 2 subsets. Further gene set enrichment analysis identified canonical pathways that pointed to “inflammation” as the major feature of CD16+ MDDCs at immature stage and on LPS/HIV exposure. Finally, functional validations and meta-analysis comparing the transcriptome of monocyte and MDDC subsets revealed that CD16+ vs CD16− monocytes preserved their superior ability to produce TNF-α and CCL22, as well as other sets of transcripts (eg, TCF4), during differentiation into DC. These results provide evidence that monocyte subsets are transcriptionally imprinted/programmed with specific differentiation fates, with intermediate/nonclassical CD16+ monocytes being precursors for pro-inflammatory CD103+RALDH2+TCF4+ DCs that may play key roles in mucosal immunity homeostasis/pathogenesis. Thus, alterations in the CD16+/CD16− monocyte ratios during pathological conditions may dramatically influence the quality of MDDC-mediated immunity.

scholarly journals Identifying insomnia-related chemicals through integrative analysis of genome-wide association studies and chemical–genes interaction information

SLEEP ◽  
2020 ◽  
Vol 43 (9) ◽  
Author(s):  
Om Prakash Kafle ◽  
Shiqiang Cheng ◽  
Mei Ma ◽  
Ping Li ◽  
Bolun Cheng ◽  
...  
Keyword(s):  
Association Studies ◽  
Meta Analysis ◽  
Enrichment Analysis ◽  
Modern Society ◽  
Environmental Chemicals ◽  
Gene Set Enrichment Analysis ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Study Results

Abstract Study Objectives Insomnia is a common sleep disorder and constitutes a major issue in modern society. We provide new clues for revealing the association between environmental chemicals and insomnia. Methods Three genome-wide association studies (GWAS) summary datasets of insomnia (n = 113,006, n = 1,331,010, and n = 453,379, respectively) were driven from the UK Biobank, 23andMe, and deCODE. The chemical–gene interaction dataset was downloaded from the Comparative Toxicogenomics Database. First, we conducted a meta-analysis of the three datasets of insomnia using the METAL software. Using the result of meta-analysis, transcriptome-wide association studies were performed to calculate the expression association testing statistics of insomnia. Then chemical-related gene set enrichment analysis (GSEA) was used to explore the association between chemicals and insomnia. Results For GWAS meta-analysis dataset of insomnia, we identified 42 chemicals associated with insomnia in brain tissue (p < 0.05) by GSEA. We detected five important chemicals such as pinosylvin (p = 0.0128), bromobenzene (p = 0.0134), clonidine (p = 0.0372), gabapentin (p = 0.0372), and melatonin (p = 0.0404) which are directly associated with insomnia. Conclusion Our study results provide new clues for revealing the roles of environmental chemicals in the development of insomnia.

scholarly journals Cross-Disorder Genomics Data Analysis Elucidates a Shared Genetic Basis Between Major Depression and Osteoarthritis Pain

2021 ◽  
Vol 12 ◽  
Author(s):  
Sophie Barowsky ◽  
Jae-Yoon Jung ◽  
Nicholas Nesbit ◽  
Micah Silberstein ◽  
Maurizio Fava ◽  
...  
Keyword(s):  
Major Depression ◽  
Causal Effect ◽  
Meta Analysis ◽  
Clinical Care ◽  
Genetic Correlations ◽  
Enrichment Analysis ◽  
The Elderly ◽  
Mechanical Stimulus ◽  
Gene Set Enrichment Analysis ◽  
Genome Wide

Osteoarthritis (OA) and major depression (MD) are two debilitating disorders that frequently co-occur and affect millions of the elderly each year. Despite the greater symptom severity, poorer clinical outcomes, and increased mortality of the comorbid conditions, we have a limited understanding of their etiologic relationships. In this study, we conducted the first cross-disorder investigations of OA and MD, using genome-wide association data representing over 247K cases and 475K controls. Along with significant positive genome-wide genetic correlations (rg = 0.299 ± 0.026, p = 9.10 × 10–31), Mendelian randomization (MR) analysis identified a bidirectional causal effect between OA and MD (βOA→MD = 0.09, SE = 0.02, z-score p-value < 1.02 × 10–5; βMD→OA = 0.19, SE = 0.026, p < 2.67 × 10–13), indicating genetic variants affecting OA risk are, in part, shared with those influencing MD risk. Cross-disorder meta-analysis of OA and MD identified 56 genomic risk loci (Pmeta ≤ 5 × 10–8), which show heightened expression of the associated genes in the brain and pituitary. Gene-set enrichment analysis highlighted “mechanosensory behavior” genes (GO:0007638; Pgene_set = 2.45 × 10–8) as potential biological mechanisms that simultaneously increase susceptibility to these mental and physical health conditions. Taken together, these findings show that OA and MD share common genetic risk mechanisms, one of which centers on the neural response to the sensation of mechanical stimulus. Further investigation is warranted to elaborate the etiologic mechanisms of the pleiotropic risk genes, as well as to develop early intervention and integrative clinical care of these serious conditions that disproportionally affect the aging population.

scholarly journals TNF-α Triggers RIP1/FADD/Caspase-8-Mediated Apoptosis of Astrocytes and RIP3/MLKL-Mediated Necroptosis of Neurons Induced by Angiostrongylus cantonensis Infection

2021 ◽  
Author(s):  
Hongli Zhou ◽  
Minyu Zhou ◽  
Yue Hu ◽  
Yanin Limpanon ◽  
Yubin Ma ◽  
...  
Keyword(s):  
Cell Death ◽  
Enrichment Analysis ◽  
Angiostrongylus Cantonensis ◽  
Gene Set Enrichment Analysis ◽  
Caspase 8 ◽  
Cns Injury ◽  
Vitro Assay ◽  
Tnf Α

AbstractAngiostrongylus cantonensis (AC) can cause severe eosinophilic meningitis or encephalitis in non-permissive hosts accompanied by apoptosis and necroptosis of brain cells. However, the explicit underlying molecular basis of apoptosis and necroptosis upon AC infection has not yet been elucidated. To determine the specific pathways of apoptosis and necroptosis upon AC infection, gene set enrichment analysis (GSEA) and protein–protein interaction (PPI) analysis for gene expression microarray (accession number: GSE159486) of mouse brain infected by AC revealed that TNF-α likely played a central role in the apoptosis and necroptosis in the context of AC infection, which was further confirmed via an in vivo rescue assay after treating with TNF-α inhibitor. The signalling axes involved in apoptosis and necroptosis were investigated via immunoprecipitation and immunoblotting. Immunofluorescence was used to identify the specific cells that underwent apoptosis or necroptosis. The results showed that TNF-α induced apoptosis of astrocytes through the RIP1/FADD/Caspase-8 axis and induced necroptosis of neurons by the RIP3/MLKL signalling pathway. In addition, in vitro assay revealed that TNF-α secretion by microglia increased upon LSA stimulation and caused necroptosis of neurons. The present study provided the first evidence that TNF-α was secreted by microglia stimulated by AC infection, which caused cell death via parallel pathways of astrocyte apoptosis (mediated by the RIP1/FADD/caspase-8 axis) and neuron necroptosis (driven by the RIP3/MLKL complex). Our research comprehensively elucidated the mechanism of cell death after AC infection and provided new insight into targeting TNF-α signalling as a therapeutic strategy for CNS injury.

scholarly journals Gene set enrichment analysis for genome-wide DNA methylation data

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jovana Maksimovic ◽  
Alicia Oshlack ◽  
Belinda Phipson
Keyword(s):  
Dna Methylation ◽  
Enrichment Analysis ◽  
R Package ◽  
Gene Set Enrichment Analysis ◽  
Methylation Array ◽  
Gene Set ◽  
Genome Wide ◽  
Genome Methylation ◽  
Unbiased Gene ◽  
Gene Set Testing

AbstractDNA methylation is one of the most commonly studied epigenetic marks, due to its role in disease and development. Illumina methylation arrays have been extensively used to measure methylation across the human genome. Methylation array analysis has primarily focused on preprocessing, normalization, and identification of differentially methylated CpGs and regions. GOmeth and GOregion are new methods for performing unbiased gene set testing following differential methylation analysis. Benchmarking analyses demonstrate GOmeth outperforms other approaches, and GOregion is the first method for gene set testing of differentially methylated regions. Both methods are publicly available in the missMethyl Bioconductor R package.

Transmembrane p24 Trafficking Protein 2 Regulates Inflammation Through the TLR4/NF-κB Signaling Pathway in Lung Adenocarcinoma

2021 ◽  
Author(s):  
Longhua Feng ◽  
Pengjiang Cheng ◽  
Zhengyun Feng ◽  
Xiaoyu Zhang
Keyword(s):  
Lung Adenocarcinoma ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Inflammatory Factors ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
New Strategy

Abstract Background: To investigate the role of transmembrane p24 trafficking protein 2 (TMED2) in lung adenocarcinoma (LUAD) and determine whether TMED2 knockdown could inhibit LUAD in vitro and in vivo.Methods: TIMER2.0, Kaplan-Meier plotter, gene set enrichment analysis (GSEA), Target Gene, and pan-cancer systems were used to predict the potential function of TMED2. Western blotting and immunohistochemistry were performed to analyze TMED2 expression in different tissues or cell lines. The proliferation, development, and apoptosis of LUAD were observed using a lentivirus-mediated TMED2 knockdown. Bioinformatics and western blot analysis of TMED2 against inflammation via the TLR4/NF-κB signaling pathway were conducted. Results: TMED2 expression in LUAD tumor tissues was higher than that in normal tissues and positively correlated with poor survival in lung cancer and negatively correlated with apoptosis in LUAD. The expression of TMED2 was higher in tumors or HCC827 cells. TMED2 knockdown inhibited LUAD development in vitro and in vivo and increased the levels of inflammatory factors via the TLR4/NF-κB signaling pathway. TMED2 was correlated with TME, immune score, TME-associated immune cells, their target markers, and some mechanisms and pathways, as determined using the TIMER2.0, GO, and KEGG assays.Conclusions: TMED2 may regulate inflammation in LUAD through the TLR4/NF-κB signaling pathway, and enhance the proliferation, development, and prognosis of LUAD by regulating inflammation, which provide a new strategy for treating LUAD by regulating inflammation.

scholarly journals Key pathways involved in prostate cancer based on gene set enrichment analysis and meta analysis

2011 ◽  
Vol 10 (4) ◽  
pp. 3856-3887 ◽  
Author(s):  
Q.Y. Ning ◽  
J.Z. Wu ◽  
N. Zang ◽  
J. Liang ◽  
Y.L. Hu ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Meta Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Key Pathways

scholarly journals Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions

2018 ◽  
Author(s):  
David M. Howard ◽  
Mark J. Adams ◽  
Toni-Kim Clarke ◽  
Jonathan D. Hafferty ◽  
Jude Gibson ◽  
...  
Keyword(s):  
Multiple Testing ◽  
Drug Repositioning ◽  
Association Studies ◽  
Meta Analysis ◽  
Enrichment Analysis ◽  
Brain Regions ◽  
Genome Wide Association Studies ◽  
Multiple Testing Correction ◽  
Synaptic Structure ◽  
Genome Wide

AbstractMajor depression is a debilitating psychiatric illness that is typically associated with low mood, anhedonia and a range of comorbidities. Depression has a heritable component that has remained difficult to elucidate with current sample sizes due to the polygenic nature of the disorder. To maximise sample size, we meta-analysed data on 807,553 individuals (246,363 cases and 561,190 controls) from the three largest genome-wide association studies of depression. We identified 102 independent variants, 269 genes, and 15 gene-sets associated with depression, including both genes and gene-pathways associated with synaptic structure and neurotransmission. Further evidence of the importance of prefrontal brain regions in depression was provided by an enrichment analysis. In an independent replication sample of 1,306,354 individuals (414,055 cases and 892,299 controls), 87 of the 102 associated variants were significant following multiple testing correction. Based on the putative genes associated with depression this work also highlights several potential drug repositioning opportunities. These findings advance our understanding of the complex genetic architecture of depression and provide several future avenues for understanding aetiology and developing new treatment approaches.

scholarly journals Benchmarking substrate-based kinase activity inference using phosphoproteomic data

2016 ◽  
Author(s):  
Claudia Hernandez-Armenta ◽  
David Ochoa ◽  
Emanuel Gonçalves ◽  
Julio Saez-Rodriguez ◽  
Pedro Beltrao
Keyword(s):  
Kinase Activity ◽  
Multiple Linear Regression Model ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Target Sequence ◽  
Sequence Specificity ◽  
Gold Standard Dataset ◽  
Kolmogorov Smirnov

AbstractMotivationPhosphoproteomic experiments are increasingly used to study the changes in signalling occurring across different conditions. It has been proposed that changes in phosphorylation of kinase target sites can be used to infer when a kinase activity is under regulation. However, these approaches have not yet been benchmarked due to a lack of appropriate benchmarking strategies.ResultsWe curated public phosphoproteomic experiments to identify a gold standard dataset containing a total of 184 kinase-condition pairs where regulation is expected to occur. A list of kinase substrates was compiled and used to estimate changes in kinase activities using the following methods: Z-test, Kolmogorov Smirnov test, Wilcoxon rank sum test, gene set enrichment analysis (GSEA), and a multiple linear regression model (MLR). We also tested weighted variants of the Z-test, and GSEA that include information on kinase sequence specificity as proxy for affinity. Finally, we tested how the number of known substrates and the type of evidence (in vivo, in vitro or in silico) supporting these influence the predictions.ConclusionsMost models performed well with the Z-test and the GSEA performing best as determined by the area under the ROc curve (Mean AUC=0.722). Weighting kinase targets by the kinase target sequence preference improves the results only marginally. However, the number of known substrates and the evidence supporting the interactions has a strong effect on the predictions.

scholarly journals A novel mouse model expressing human forms for complement receptors CR1 and CR2

2019 ◽  
Author(s):  
Harriet M. Jackson ◽  
Kate E. Foley ◽  
Rita O’Rourke ◽  
Timothy M. Stearns ◽  
Dina Fathalla ◽  
...  
Keyword(s):  
Mouse Model ◽  
Lupus Erythematosus ◽  
Transcriptional Profiling ◽  
Enrichment Analysis ◽  
Cell Number ◽  
Gene Set Enrichment Analysis ◽  
Human Populations ◽  
Complement Cascade ◽  
Complement Receptors ◽  
Human Complement

AbstractThe complement cascade is increasingly implicated in development of a variety of diseases with strong immune contributions such as Alzheimer’s disease and Systemic Lupus Erythematosus. Mouse models have been used to determine function of central components of the complement cascade such as C1q and C3. However, species differences in their gene structures mean that mice do not adequately replicate human complement regulators, including CR1 and CR2. Genetic variation in CR1 and CR2 have been implicated in modifying disease states but the mechanisms are not known. To decipher the roles of human CR1 and CR2 in health and disease, we engineered C57BL/6J (B6) mice to replace endogenous murine Cr2 with human complement receptors, CR1 and CR2 (B6.CR2CR1). CR1 has an array of allotypes in human populations and using traditional recombination methods (Flp-frt and Cre-loxP) two of the most common alleles (referred to as CR1long and CR1short) are replicated within this mouse model, along with a CR1 knockout allele (CR1KO). Transcriptional profiling of spleens and brains identifies genes and pathways differentially expressed between mice homozygous for either CR1long, CR1short or CR1KO. Gene set enrichment analysis predicts hematopoietic cell number and cell infiltration are modulated by CR1long, but not CR1short or CR1KO. Therefore, this mouse model provides a novel tool for determining the relationship between human-relevant CR1 alleles and disease.Summary StatementWe present the creation and validation of a novel mouse model that expresses human forms of complement cascade regulators CR1 and CR2.

scholarly journals Norepinephrine exposure restrains endometrial decidualization in early pregnancy

2021 ◽  
Author(s):  
Jiju Wang ◽  
Yuhui Tang ◽  
Songcun Wang ◽  
Liyuan Cui ◽  
Da-Jin Li ◽  
...  
Keyword(s):  
Stromal Cells ◽  
Adrenergic Receptor ◽  
Enrichment Analysis ◽  
Normal Pregnancy ◽  
Receptor Expression ◽  
Gene Set Enrichment Analysis ◽  
Endometrial Stromal Cells ◽  
Significant Enrichment

Previous studies have focused on the role of norepinephrine on arrhythmias, generalized anxiety disorder, and cancer. This study aimed to investigate the effect of norepinephrine on endometrial decidualization. Artificial decidualization and norepinephrine-treated mice were established in vivo. In vitro, human endometrial stromal cells were treated with MPA and cAMP to induce decidualization. Decidual markers and important signaling molecules during decidualization were detected using quantitative real-time polymerase chain reaction and Western blot. RNA sequencing was performed to determine related signaling pathways. Exposure of excess norepinephrine significantly restricted the induced expression of decidualized markers Dtprp, BMP2, WNT4, and Hand2 in mice. In vitro, 10 µM norepinephrine markedly downregulated the expressions of prolactin, IGFBP1, and PLZF, which are the specifical markers of decidual stromal cells during decidualization. The gene set enrichment analysis showed that a significant enrichment in neuroactive ligand–receptor interactions of norepinephrine treatment group. The α1b-adrenergic receptor expression was upregulated by norepinephrine. Interestingly, norepinephrine did not inhibit the expression of IGFBP1 in endometrial stromal cells after silencing α1b-adrenergic receptor, while significantly suppressed the induced decidualization with overexpression of α1b-adrenergic receptor. When α1b-adrenergic receptor was activated, endometrial p-PKC was significantly increased under post-treatment with norepinephrine in vivo and in vitro. In addition, norepinephrine treatment inhibited embryo and fetal development using a normal pregnancy model. Therefore, norepinephrine exposure inhibited endometrial decidualization through the activation of the PKC signaling pathway by upregulating α1b-adrenergic receptor. Our study could explain some female reproductive problems due to stress and provide some novel strategies for this disorder.

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