scholarly journals Blood Transcriptome Profiling Reveals Diet-Induced Changes in Metabolic Pathway Gene Expression

2021 ◽  
Vol 5 (Supplement_2) ◽  
pp. 938-938
Author(s):  
Jaapna Dhillon ◽  
Jose Godoy-Lugo ◽  
Rudy Ortiz
Keyword(s):  
Gene Expression ◽  
Young Adults ◽  
Signal Transduction Pathway ◽  
Enrichment Analysis ◽  
Immunoglobulin Superfamily ◽  
Pathway Enrichment Analysis ◽  
Sequencing Data ◽  
P Values ◽  
Pathway Gene ◽  
Blood Transcriptome

Abstract Objectives This study explored the effects of diet-induced (almonds vs. crackers) changes on blood transcriptome profiles of young adults. Methods Young adults (age: 18–22 years) were randomly assigned to consume either almonds (2 oz./d, n = 13) or an isocaloric control snack of graham crackers (325 kcal/d, n = 10) daily for 4 weeks. Blood samples were collected at baseline and 4 weeks after intervention. Total leukocyte RNA was extracted and sequenced. Gene expression profiling was carried out using a 3′ Tag-RNA-Seq protocol. Barcoded sequencing libraries were prepared using the QuantSeq FWD kit for multiplexed sequencing. Data were preprocessed, STAR aligned, and count tables generated using the QuantSeq FWD-UMI pipeline. Differential expression (DE) analysis was conducted on the time x diet model using the limma-voom packages in R. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on the DE p-values was conducted using the Wilcoxon rank-sum test in R. P-values were adjusted for false discovery rate correction (FDR). Results Out of 13,018 filtered genes, 69 were differentially expressed (FDR < 0.1). Glutamic-oxaloacetic transaminase 2 (GOT2), diacylglycerol kinase alpha (DGKA), and glutaryl-CoA dehydrogenase (GCDH) genes were upregulated with almond consumption. GOT2 plays a role in amino acid metabolism and the urea and tricarboxylic acid cycles, DGKA is involved in lipid metabolism, and GCDH is involved in lysine degradation and tryptophan metabolism. Cracker consumption resulted in greater upregulation of TGF-beta activated kinase 1 gene (MAP3K7) binding protein 3 (TAB3) gene which is involved in the NF-kappaB signal transduction pathway and a greater downregulation in the immunoglobulin superfamily member 8 (IGSF8) gene. Enrichment analyses indicate gene annotations to 341 KEGG pathways. Thermogeneic and ribosomal pathways were significantly enriched (FDR < 0.1). Pathways related to oxidative phosphorylation, sphingolipid signaling, and tryptophan, propanoate, and starch and sucrose metabolism were also differentially enriched (P < 0.05, FDR < 0.3). Conclusions These findings indicate that diet (almond vs cracker) potentially alters metabolism through changes in gene transcription. The implications of these findings and associations with health and disease outcomes need to be investigated further. Funding Sources NIH

A Method of Pathway Enrichment Analysis Based Gene Expression Variability

2013 ◽  
Vol 40 (12) ◽  
pp. 1256
Author(s):  
XiaoDong JIA ◽  
XiuJie CHEN ◽  
Xin WU ◽  
JianKai XU ◽  
FuJian TAN ◽  
...  
Keyword(s):  
Gene Expression ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Expression Variability ◽  
Pathway Enrichment

scholarly journals AB0005 IDENTIFICATION OF KEY GENES AND PATHWAYS FOR PSORIASIS BASED ON GEO DATABASES BY BIOINFORMATICS ANALYSIS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1037.2-1038
Author(s):  
X. Sun ◽  
S. X. Zhang ◽  
S. Song ◽  
T. Kong ◽  
C. Zheng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signaling Pathways ◽  
Differentially Expressed Genes ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Shanxi Province ◽  
Receptor Interaction ◽  
Term Therapy ◽  
Pathway Enrichment Analysis ◽  
Key Genes

Background:Psoriasis is an immune-mediated, genetic disease manifesting in the skin or joints or both, and also has a strong genetic predisposition and autoimmune pathogenic traits1. The hallmark of psoriasis is sustained inflammation that leads to uncontrolled keratinocyte proliferation and dysfunctional differentiation. And it’s also a chronic relapsing disease, which often necessitates a long-term therapy2.Objectives:To investigate the molecular mechanisms of psoriasis and find the potential gene targets for diagnosis and treating psoriasis.Methods:Total 334 gene expression data of patients with psoriasis research (GSE13355 GSE14905 and GSE30999) were obtained from the Gene Expression Omnibus database. After data preprocessing and screening of differentially expressed genes (DEGs) by R software. Online toll Metascape3 was used to analyze Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs. Interactions of proteins encoded by DEGs were discovered by Protein-protein interaction network (PPI) using STRING online software. Cytoscape software was utilized to visualize PPI and the degree of each DEGs was obtained by analyzing the topological structure of the PPI network.Results:A total of 611 DEGs were found to be differentially expressed in psoriasis. GO analysis revealed that up-regulated DEGs were mostly associated with defense and response to external stimulus while down-regulated DEGs were mostly associated with metabolism and synthesis of lipids. KEGG enrichment analysis suggested they were mainly enriched in IL-17 signaling, Toll-like receptor signaling and PPAR signaling pathways, Cytokine-cytokine receptor interaction and lipid metabolism. In addition, top 9 key genes (CXCL10, OASL, IFIT1, IFIT3, RSAD2, MX1, OAS1, IFI44 and OAS2) were identified through Cytoscape.Conclusion:DEGs of psoriasis may play an essential role in disease development and may be potential pathogeneses of psoriasis.References:[1]Boehncke WH, Schon MP. Psoriasis. Lancet 2015;386(9997):983-94. doi: 10.1016/S0140-6736(14)61909-7 [published Online First: 2015/05/31].[2]Zhang YJ, Sun YZ, Gao XH, et al. Integrated bioinformatic analysis of differentially expressed genes and signaling pathways in plaque psoriasis. Mol Med Rep 2019;20(1):225-35. doi: 10.3892/mmr.2019.10241 [published Online First: 2019/05/23].[3]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].Acknowledgements:This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).Disclosure of Interests:None declared

scholarly journals Bioinformatics-Based Study to Investigate Potential Differentially Expressed Genes and miRNAs in Hashimoto’s Thyroiditis

2021 ◽  
Author(s):  
Li Guoquan ◽  
Du Junwei ◽  
He Qi ◽  
Fu Xinghao ◽  
Ji Feihong ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Inflammatory Responses ◽  
Expression Profiles ◽  
Treatment Options ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Chronic Lymphocytic Thyroiditis ◽  
Hub Genes

Abstract BackgroundHashimoto's thyroiditis (HT), also known as chronic lymphocytic thyroiditis, is a common autoimmune disease, which mainly occurs in women. The early manifestation was hyperthyroidism, however, hypothyroidism may occur if HT was not controlled for a long time. Numerous studies have shown that multiple factors, including genetic, environmental, and autoimmune factors, were involved in the pathogenesis of the disease, but the exact mechanisms were not yet clear. The aim of this study was to identify differentially expressed genes (DEGs) by comprehensive analysis and to provide specific insights into HT. MethodsTwo gene expression profiles (GSE6339, GSE138198) about HT were downloaded from the Gene Expression Omnibus (GEO) database. The DEGs were assessed between the HT and normal groups using the GEO2R. The DEGs were then sent to the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The hub genes were discovered using Cytoscape and CytoHubba. Finally, NetworkAnalyst was utilized to create the hub genes' targeted microRNAs (miRNAs). ResultsA total of 62 DEGs were discovered, including 60 up-regulated and 2 down-regulated DEGs. The signaling pathways were mainly engaged in cytokine interaction and cytotoxicity, and the DEGs were mostly enriched in immunological and inflammatory responses. IL2RA, CXCL9, IL10RA, CCL3, CCL4, CCL2, STAT1, CD4, CSF1R, and ITGAX were chosen as hub genes based on the results of the protein-protein interaction (PPI) network and CytoHubba. Five miRNAs, including mir-24-3p, mir-223-3p, mir-155-5p, mir-34a-5p, mir-26b-5p, and mir-6499-3p, were suggested as likely important miRNAs in HT. ConclusionsThese hub genes, pathways and miRNAs contribute to a better understanding of the pathophysiology of HT and offer potential treatment options for HT.

scholarly journals Comparative pathway enrichment analysis in gastrointestinal cell lines Caco-2, HT-29, HEPG2, and colon fibroblasts using a custom expression panel for tight-junction and cytoskeletal regulatory genes

2019 ◽  
Author(s):  
JM Robinson
Keyword(s):  
Gene Expression ◽  
Comparative Analysis ◽  
Tight Junction ◽  
Cell Lines ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Intestinal Epithelial ◽  
Expression Data ◽  
Pathway Enrichment ◽  
Ht 29

AbstractThis brief report details results from a comparative analysis of Nanostring expression data between cell lines HEPG2, Caco-2, HT-29, and colon fibroblasts. Raw and normalized data are available publicly in the NCBI GEO/Bioproject databases. Results identify cell-line specific variations in gene expression relevant to intestinal epithelial function.

scholarly journals Bioinformatic analysis identifies potential biomarkers and therapeutic targets of septic-shock-associated acute kidney injury

Hereditas ◽  
2021 ◽  
Vol 158 (1) ◽  
Author(s):  
Yun Tang ◽  
Xiaobo Yang ◽  
Huaqing Shu ◽  
Yuan Yu ◽  
Shangwen Pan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Septic Shock ◽  
Acute Kidney Injury ◽  
Molecular Mechanisms ◽  
Therapeutic Targets ◽  
Kidney Injury ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Blood Samples ◽  
Potential Biomarkers

Abstract Background Sepsis and septic shock are life-threatening diseases with high mortality rate in intensive care unit (ICU). Acute kidney injury (AKI) is a common complication of sepsis, and its occurrence is a poor prognostic sign to septic patients. We analyzed co-differentially expressed genes (co-DEGs) to explore relationships between septic shock and AKI and reveal potential biomarkers and therapeutic targets of septic-shock-associated AKI (SSAKI). Methods Two gene expression datasets (GSE30718 and GSE57065) were downloaded from the Gene Expression Omnibus (GEO). The GSE57065 dataset included 28 septic shock patients and 25 healthy volunteers and blood samples were collected within 0.5, 24 and 48 h after shock. Specimens of GSE30718 were collected from 26 patients with AKI and 11 control patents. AKI-DEGs and septic-shock-DEGs were identified using the two datasets. Subsequently, Gene Ontology (GO) functional analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction (PPI) network analysis were performed to elucidate molecular mechanisms of DEGs. We also evaluated co-DEGs and corresponding predicted miRNAs involved in septic shock and AKI. Results We identified 62 DEGs in AKI specimens and 888, 870, and 717 DEGs in septic shock blood samples within 0.5, 24 and 48 h, respectively. The hub genes of EGF and OLFM4 may be involved in AKI and QPCT, CKAP4, PRKCQ, PLAC8, PRC1, BCL9L, ATP11B, KLHL2, LDLRAP1, NDUFAF1, IFIT2, CSF1R, HGF, NRN1, GZMB, and STAT4 may be associated with septic shock. Besides, co-DEGs of VMP1, SLPI, PTX3, TIMP1, OLFM4, LCN2, and S100A9 coupled with corresponding predicted miRNAs, especially miR-29b-3p, miR-152-3p, and miR-223-3p may be regarded as promising targets for the diagnosis and treatment of SSAKI in the future. Conclusions Septic shock and AKI are related and VMP1, SLPI, PTX3, TIMP1, OLFM4, LCN2, and S100A9 genes are significantly associated with novel biomarkers involved in the occurrence and development of SSAKI.

Identification of differential gene expression related to epirubicin-induced cardiomyopathy in breast cancer patients

2019 ◽  
Vol 39 (4) ◽  
pp. 393-401 ◽  
Author(s):  
J Peng ◽  
Z Wang ◽  
Y Li ◽  
D Lv ◽  
X Zhao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Patients ◽  
Enrichment Analysis ◽  
Global Gene Expression ◽  
Pathway Enrichment Analysis ◽  
Breast Cancer Patients ◽  
Chlorophyll Metabolism ◽  
Pathway Enrichment ◽  
Before And After

Background: Epirubicin is a potent chemotherapeutic agent for the treatment of breast cancer. However, it may lead to cardiotoxicity and cardiomyopathy, and no reliable biomarker was available for the early prediction of epirubicin-induced cardiomyopathy. Methods: Global gene expression changes of peripheral blood cells were studied using high-throughput RNA sequencing in three pair-matched breast cancer patients (patients who developed symptomatic cardiomyopathy paired with patients who did not) before and after the full session of epirubicin-based chemotherapy. Functional analysis was conducted using gene ontology and pathway enrichment analysis. Results: We identified 13 significantly differentially expressed genes between patients who developed symptomatic epirubicin-induced cardiomyopathy and their paired control who did not. Among them, the upregulated Bcl-associated X protein was related to “apoptosis,” while the downregulated 5′-aminolevulinate synthase 2 (ALAS2) was related to both “glycine, serine, and threonine metabolism” and “porphyrin and chlorophyll metabolism” in pathway enrichment analysis. Conclusions: ALAS2 and the metabolic pathways which were involved may play an important role in the development of epirubicin-induced cardiomyopathy. ALAS2 may be useful as an early biomarker for epirubicin-induced cardiotoxicity detection.

scholarly journals In Silico Discovery of Candidate Drugs against Covid-19

Viruses ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 404 ◽  
Author(s):  
Claudia Cava ◽  
Gloria Bertoli ◽  
Isabella Castiglioni
Keyword(s):  
Gene Expression ◽  
In Silico ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Basic Mechanism ◽  
Cell Receptor ◽  
The Cancer Genome Atlas ◽  
Pathway Enrichment Analysis

Previous studies reported that Angiotensin converting enzyme 2 (ACE2) is the main cell receptor of SARS-CoV and SARS-CoV-2. It plays a key role in the access of the virus into the cell to produce the final infection. In the present study we investigated in silico the basic mechanism of ACE2 in the lung and provided evidences for new potentially effective drugs for Covid-19. Specifically, we used the gene expression profiles from public datasets including The Cancer Genome Atlas, Gene Expression Omnibus and Genotype-Tissue Expression, Gene Ontology and pathway enrichment analysis to investigate the main functions of ACE2-correlated genes. We constructed a protein-protein interaction network containing the genes co-expressed with ACE2. Finally, we focused on the genes in the network that are already associated with known drugs and evaluated their role for a potential treatment of Covid-19. Our results demonstrate that the genes correlated with ACE2 are mainly enriched in the sterol biosynthetic process, Aryldialkylphosphatase activity, adenosylhomocysteinase activity, trialkylsulfonium hydrolase activity, acetate-CoA and CoA ligase activity. We identified a network of 193 genes, 222 interactions and 36 potential drugs that could have a crucial role. Among possible interesting drugs for Covid-19 treatment, we found Nimesulide, Fluticasone Propionate, Thiabendazole, Photofrin, Didanosine and Flutamide.

scholarly journals Host–Viral Interactions Revealed among Shared Transcriptomics Signatures of ARDS and Thrombosis: A Clue into COVID-19 Pathogenesis

TH Open ◽  
2020 ◽  
Vol 04 (04) ◽  
pp. e403-e412
Author(s):  
Aastha Mishra ◽  
Shankar Chanchal ◽  
Mohammad Z. Ashraf
Keyword(s):  
Gene Expression ◽  
Virus Disease ◽  
Meta Analysis ◽  
Random Effect ◽  
Enrichment Analysis ◽  
Coagulation Factors ◽  
Gene Expression Omnibus ◽  
Endothelial Damage ◽  
Pathway Enrichment Analysis ◽  
Hub Genes

AbstractSevere novel corona virus disease 2019 (COVID-19) infection is associated with a considerable activation of coagulation pathways, endothelial damage, and subsequent thrombotic microvascular injuries. These consistent observations may have serious implications for the treatment and management of this highly pathogenic disease. As a consequence, the anticoagulant therapeutic strategies, such as low molecular weight heparin, have shown some encouraging results. Cytokine burst leading to sepsis which is one of the primary reasons for acute respiratory distress syndrome (ARDS) drive that could be worsened with the accumulation of coagulation factors in the lungs of COVID-19 patients. However, the obscurity of this syndrome remains a hurdle in making decisive treatment choices. Therefore, an attempt to characterize shared biological mechanisms between ARDS and thrombosis using comprehensive transcriptomics meta-analysis is made. We conducted an integrated gene expression meta-analysis of two independently publicly available datasets of ARDS and venous thromboembolism (VTE). Datasets GSE76293 and GSE19151 derived from National Centre for Biotechnology Information–Gene Expression Omnibus (NCBI-GEO) database were used for ARDS and VTE, respectively. Integrative meta-analysis of expression data (INMEX) tool preprocessed the datasets and effect size combination with random effect modeling was used for obtaining differentially expressed genes (DEGs). Network construction was done for hub genes and pathway enrichment analysis. Our meta-analysis identified a total of 1,878 significant DEGs among the datasets, which when subjected to enrichment analysis suggested inflammation–coagulation–hypoxemia convolutions in COVID-19 pathogenesis. The top hub genes of our study such as tumor protein 53 (TP53), lysine acetyltransferase 2B (KAT2B), DExH-box helicase 9 (DHX9), REL-associated protein (RELA), RING-box protein 1 (RBX1), and proteasome 20S subunit beta 2 (PSMB2) gave insights into the genes known to be participating in the host–virus interactions that could pave the way to understand the various strategies deployed by the virus to improve its replication and spreading.

scholarly journals Revealing Biological Pathways Implicated in Lung Cancer from TCGA Gene Expression Data Using Gene Set Enrichment Analysis

2014 ◽  
Vol 13s1 ◽  
pp. CIN.S13882 ◽  
Author(s):  
Binghuang Cai ◽  
Xia Jiang
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Gene Expression Data ◽  
Lung Squamous Cell Carcinoma ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Expression Data ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Pathway Gene

Analyzing biological system abnormalities in cancer patients based on measures of biological entities, such as gene expression levels, is an important and challenging problem. This paper applies existing methods, Gene Set Enrichment Analysis and Signaling Pathway Impact Analysis, to pathway abnormality analysis in lung cancer using microarray gene expression data. Gene expression data from studies of Lung Squamous Cell Carcinoma (LUSC) in The Cancer Genome Atlas project, and pathway gene set data from the Kyoto Encyclopedia of Genes and Genomes were used to analyze the relationship between pathways and phenotypes. Results, in the form of pathway rankings, indicate that some pathways may behave abnormally in LUSC. For example, both the cell cycle and viral carcinogenesis pathways ranked very high in LUSC. Furthermore, some pathways that are known to be associated with cancer, such as the p53 and the PI3K-Akt signal transduction pathways, were found to rank high in LUSC. Other pathways, such as bladder cancer and thyroid cancer pathways, were also ranked high in LUSC.

Immune-related gene expression deficit of leukemia stem cells (LSC) in AML.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 7011-7011
Author(s):  
Kamal Chamoun ◽  
Christopher Brent Benton ◽  
Ahmed AlRawi ◽  
Rodrigo Jacamo ◽  
Patrick Williams ◽  
...  
Keyword(s):  
Gene Expression ◽  
Antigen Presentation ◽  
Mhc Class Ii ◽  
Antigen Processing ◽  
Differentially Expressed Gene ◽  
Enrichment Analysis ◽  
Class Ii ◽  
Differentially Expressed ◽  
Pathway Gene ◽  
Presentation Pathway

7011 Background: AML LSC are believed to be responsible for residual and resistant leukemic disease leading to relapse. Understanding differences between bulk AML and the LSC subpopulation may allow the identification of novel LSC targets, especially for the most adverse risk AML where few patients are cured. Targeting LSC may be needed to eradicate AML, and immune-based therapies provide an approach for eliminating LSC. The transcriptional landscape of immune-related genes in LSC is not well understood. Methods: Samples were collected at diagnosis from 12 patients with high-risk AML prior to therapy. Bulk (CD45-dim blasts) and LSC (Lin-CD34+CD38-CD123+) AML marrow cells were FACS-sorted and analyzed using whole genome RNA-sequencing. Transcriptomes were analyzed using AltAnalyze software to identify differentially expressed genes in bulk AML cells and in AML LSC populations. These genes were further assessed by gene enrichment analysis using data from Gene Ontology (GO) and the Cancer Genome Atlas Project (CGAP). Results: Sixty-eight genes were identified with greater than 3-fold differential expression between bulk AML and LSC. GO enrichment analysis demonstrated more than 10-fold enrichment of genes involved in the molecular functions, biologic processes, and cell components related to the antigen presentation pathway, with the comparative down-regulation occurring in LSC. Among the top differentially expressed gene clusters, both the MHC class II and interferon-gamma signaling/response pathway gene expression was blunted in LSC. Additional expression analysis revealed that 42% of a CGAP-curated list of 201 antigen-processing and -presentation genes had significantly decreased expression in the LSC subpopulation compared to bulk AML. Conclusions: LSC from primary AML patient samples are characterized by reduction in expression of MHC class II receptor and antigen presentation genes compared to bulk AML. These results suggest that impairment in the presentation and/or processing of tumor associated antigens by MHC class II on LSC, along with tonic sponging of immune response cells and diversion away from LSC by bulk AML, may contribute to LSC evasion of immune surveillance and response.

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