Genome-Wide Expression Analysis Suggests Hypoxia-Triggered Hyper-Coagulation Leading to Venous Thrombosis at High Altitude

2018 ◽  
Vol 118 (07) ◽  
pp. 1279-1295 ◽  
Author(s):  
Prabhash Jha ◽  
Anita Sahu ◽  
Amit Prabhakar ◽  
Tarun Tyagi ◽  
Tathagata Chatterjee ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Altitude ◽  
Differential Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Bioinformatic Analysis ◽  
Rnase A ◽  
Additional Risk Factor ◽  
Solute Carrier Family ◽  
Solute Carrier

AbstractVenous thromboembolism (VTE), a multi-factorial disease, is the third most common cardiovascular disease. Established genetic and acquired risk factors are responsible for the onset of VTE. High altitude (HA) also poses as an additional risk factor, predisposing individuals to VTE; however, its molecular mechanism remains elusive. This study aimed to identify genes/pathways associated with the pathophysiology of deep vein thrombosis (DVT) at HA. Gene expression profiling of DVT patients, who developed the disease, either at sea level or at HA-DVT locations, resulted in differential expression of 378 and 875 genes, respectively. Gene expression profiles were subjected to bioinformatic analysis, followed by technical and biological validation of selected genes using quantitative reverse transcription-polymerase chain reaction. Both gene ontology and pathway analysis showed enrichment of genes involved in haemostasis and platelet activation in HA-DVT patients with the most relevant pathway being ‘response to hypoxia’. Thus, given the environmental condition the differential expression of hypoxia-responsive genes (angiogenin, ribonuclease, RNase A family, 5; early growth response 1; lamin A; matrix metallopeptidase 14 [membrane-inserted]; neurofibromin 1; PDZ and LIM domain 1; procollagen-lysine 1, 2-oxoglutarate 5-dioxygenase 1; solute carrier family 6 [neurotransmitter transporter, serotonin], member 4; solute carrier family 9 [sodium/hydrogen exchanger], member 1; and TEK tyrosine kinase, endothelial) in HA-DVT could be a determining factor to understand the pathophysiology of DVT at HA.

scholarly journals RankerGUI: A Computational Framework to Compare Differential Gene Expression Profiles Using Rank Based Statistics

2019 ◽  
Vol 20 (23) ◽  
pp. 6098 ◽  
Author(s):  
Amarinder Singh Thind ◽  
Kumar Parijat Tripathi ◽  
Mario Rosario Guarracino
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Differential Gene Expression ◽  
Web Application ◽  
Cellular Response ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Experimental Conditions ◽  
Differential Gene

The comparison of high throughput gene expression datasets obtained from different experimental conditions is a challenging task. It provides an opportunity to explore the cellular response to various biological events such as disease, environmental conditions, and drugs. There is a need for tools that allow the integration and analysis of such data. We developed the “RankerGUI pipeline”, a user-friendly web application for the biological community. It allows users to use various rank based statistical approaches for the comparison of full differential gene expression profiles between the same or different biological states obtained from different sources. The pipeline modules are an integration of various open-source packages, a few of which are modified for extended functionality. The main modules include rank rank hypergeometric overlap, enriched rank rank hypergeometric overlap and distance calculations. Additionally, preprocessing steps such as merging differential expression profiles of multiple independent studies can be added before running the main modules. Output plots show the strength, pattern, and trends among complete differential expression profiles. In this paper, we describe the various modules and functionalities of the developed pipeline. We also present a case study that demonstrates how the pipeline can be used for the comparison of differential expression profiles obtained from multiple platforms’ data of the Gene Expression Omnibus. Using these comparisons, we investigate gene expression patterns in kidney and lung cancers.

scholarly journals Screening of Hub Genes Associated with Lung Adenocarcinoma by Integrated Bioinformatic Analysis

2021 ◽  
Author(s):  
Zimeng Wei ◽  
Min Zhao ◽  
Linnan Zang
Keyword(s):  
Gene Expression ◽  
Lung Adenocarcinoma ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Bioinformatic Analysis ◽  
Analysis Tool ◽  
Hub Genes ◽  
Kegg Analysis ◽  
Ppi Networks

Abstract Background Lung adenocarcinoma (LUAD) is the main histological subtype of lung cancer. However, the molecular mechanism underlying LUAD is not yet clearly defined, but elucidating this process in detail would be of great significance for clinical diagnosis and treatment. Methods Gene expression profiles were retrieved from Gene Expression Omnibus database (GEO), and the common differentially expressed genes (DEGs) were identified by online GEO2R analysis tool. Subsequently, the enrichment analysis of function and signaling pathways of DEGs in LUAD were performed by gene ontology (GO) and The Kyoto Encyclopedia of Genes and Genomics (KEGG) analysis. The protein-protein interaction (PPI) networks of the DEGs were established through the Search Tool for the Retrieval of Interacting Genes (STRING) database and hub genes were screened by plug-in CytoHubba in Cytoscape. Afterwards, we detected the expression of hub genes in LUAD and other cancers via GEPIA, Oncomine and HPA databases. Finally, Kaplan-Meier plotter were performed to analyze the prognosis efficacy of hub genes. Results 74 up-regulated and 238 down-regulated DEGs were identified. As for the up-regulated DEGs, KEGG analysis results revealed they were mainly enrolled in protein digestion and absorption. However, the down-regulated DEGs were primarily enriched in cell adhesion molecules. Subsequently, 9 hub genes: KIAA0101, CDCA7, TOP2A, CDC20, ASPM, TPX2, CENPF, UBE2T and ECT2, were identified and showed higher expression in both LUAD and other cancers. Finally, all these hub genes were found significantly related to the prognosis of LUAD (p < 0.05). Conclusions Our results screened out the hub genes and pathways that were related to the development and prognosis of LUAD, which could provide new insight for the future molecularly targeted therapy and prognosis evaluation of LUAD.

scholarly journals A classifier driven approach to find biomarkers for affective disorders from transcription profiles in blood

2016 ◽  
Vol 1 (1) ◽  
pp. 34 ◽  
Author(s):  
Wiktor Mazin ◽  
Joseph A Tamm ◽  
Irina A Antonijevic ◽  
Aicha Abdourahman ◽  
Munish Das ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Affective Disorders ◽  
Expression Profiles ◽  
Quantitative Polymerase Chain Reaction ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Expression Levels ◽  
Control Subjects ◽  
Transcription Profiles

Gene expression profiles in blood are increasingly being used to identify biomarkers for different affective disorders. We have selected a set of 29 genes to generate expression profiles for healthy control subjects as well as for patients diagnosed with acute post-traumatic stress disorder (PTSD) and with borderline personality disorder (BPD). Measurements were performed by quantitative polymerase chain reaction (qPCR). Using the actual data in an anonym-ous form we constructed a series of artificial data sets with known gene expression profiles. These sets were used to test 14 classification algorithms and feature selection methods for their ability to identify the correct expression patterns. Application of the three most effective algorithms to the actual expression data showed that control subjects can be dis-tinguished from BPD patients based on differential expression levels of the gene transcripts Gi2, GR and MAPK14, targets that may have links to stress related diseases. Controls can also be distinguished from acute PTSD patients by differential expression levels of the transcripts for ERK2 and RGS2 that are known to be associated with mood disord-ers and social anxiety. We conclude that it is possible to identify informative transcription profiles in blood samples from individuals with affective disorders.

The Hypoxic Response and Altered Gene Expression in Patients with Sickle Cell Disease

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 3245-3245
Author(s):  
Victor R. Gordeuk ◽  
Xu Zhang ◽  
Wei Zhang ◽  
Shwu-Fan Ma ◽  
Galina Miasniakova ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Solute Carrier Family ◽  
Cell Disease ◽  
Hypoxic Response ◽  
Tetratricopeptide Repeats ◽  
Altered Gene Expression ◽  
Solute Carrier ◽  
Altered Gene ◽  
Gene Expression Alterations

Abstract Abstract 3245 Sickle cell disease (SCD) and Chuvash polycythemia (CP) are both monogenic hematologic disorders, the first resulting in hemolytic anemia and the second in polycythemia related to an upregulated hypoxic response at normoxia. Specifically, homozygosity for the VHLR200W mutation leads to increased levels of the transcription factors hypoxia inducible factor (HIF)-1 and HIF-2 at normoxia and altered transcription of many genes. Much attention in the pathophysiology of SCD has focused on the adverse effects of chronic inflammation, enhanced cellular adhesion pathways and hemolytic rate. However, the chronic anemia of SCD is associated with an upregulation of the hypoxic response as evidenced by high erythropoietin concentrations. In this prospective study, we compared gene expression alterations in peripheral blood mononuclear cells in SCD and CP. Our pre-specified hypothesis was that we could identify hypoxia-mediated gene expression alterations in SCD through a comparison with altered gene expression in CP and reveal molecular pathways that are potentially shared by these two conditions. We prospectively compared gene expression profiles in two independent cohorts, an SCD cohort comprised of 22 SCD patients and 19 African American controls and a CP cohort comprised of 8 VHLR200W homozygotes and 17 Chuvash controls with wildtype VHL. Because iron deficiency can influence the hypoxic response, we excluded iron-deficient subjects from each cohort. We used the identical Affymetrix exon array platform for both cohorts. Differential gene expression was highly correlated between the two conditions, with Spearman correlation ρ = 0.75 between their expression profiles across 16,642 genes, suggesting that 56% of expression variation triggered by beta hemoglobin mutation in SCD may be explained by hypoxic transcriptional responses. A small portion of differential genes were highly induced in both conditions. Among 54 genes up-regulated >1.5-fold in SCD patients, 24 (44%) overlapped with the 31 genes up-regulated >1.5-fold in VHLR200W homozygotes. The genes highly induced in both conditions included FAM46C (family with sequence similarity 46 member C), SELENBP1 (selenium binding protein 1), IL1B (interleukin 1, beta), MOP-1, SNCA (synuclein, alpha), GMPR (guanosine monophosphate reductase), BPGM (2,3-bisphosphoglycerate mutase), SLC25A37 (solute carrier family 25 member 37), CA1 (carbonic anhydrase I), DCAF12 (DDB1 and CUL4 associated factor 12), EPB42 (erythrocyte membrane protein band 4.2), AHSP (alpha hemoglobin stabilizing protein), SLC4A1 (solute carrier family 4 member 1), HBB (hemoglobin, beta), HBD (hemoglobin, delta), CSDA (cold shock domain protein A), FECH (ferrochelatase), BCL2L1 (BCL2-like 1), OSBP2 (oxysterol binding protein 2), APOBEC3A (apolipoprotein B mRNA editing enzyme catalytic polypeptide-like 3A), IFIT1 (interferon-induced protein with tetratricopeptide repeats 1), IFIT3 (interferon-induced protein with tetratricopeptide repeats 3), IFI44L (interferon-induced protein 44-like), and IFI27 (interferon, alpha-inducible protein 27). Three genes were down-regulated >1.5-fold in SCD patients. One of these, GIMAP7 (GTPase, IMAP family member 7), was among the 11 genes down-regulated >1.5-fold in VHLR200Whomozygotes. These results suggest that there is a broad upregulation of the hypoxic response in SCD and that the hypoxic response may underlie or interact with an important proportion of the clinical and pathophysiologic manifestations of SCD. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Differential immune gene expression associated with contemporary range expansion in two invasive rodents in Senegal

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Nathalie Charbonnel ◽  
Maxime Galan ◽  
Caroline Tatard ◽  
Anne Loiseau ◽  
Christophe Diagne ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
House Mouse ◽  
Expression Profiles ◽  
Rattus Rattus ◽  
Gene Expression Profiles ◽  
Invasion Success ◽  
Immune Gene ◽  
Mus Musculus Domesticus ◽  
Black Rat

Abstract Biological invasions are major anthropogenic changes associated with threats to biodiversity and health. However, what determines the successful establishment and spread of introduced populations remains unclear. Here, we explore several hypotheses linking invasion success and immune phenotype traits, including those based on the evolution of increased competitive ability concept. We compared gene expression profiles between anciently and recently established populations of two major invading species, the house mouse Mus musculus domesticus and the black rat Rattus rattus, in Senegal (West Africa). Transcriptome analyses identified differential expression between anciently and recently established populations for 364 mouse genes and 83 rat genes. All immune-related genes displaying differential expression along the mouse invasion route were overexpressed at three of the four recently invaded sites studied. Complement activation pathway genes were overrepresented among these genes. By contrast, no particular immunological process was found to be overrepresented among the differentially expressed genes of black rat. Changes in transcriptome profiles were thus observed along invasion routes, but with different specific patterns between the two invasive species. These changes may be driven by increases in infection risks at sites recently invaded by the house mouse, and by stochastic events associated with colonization history for the black rat. These results constitute a first step toward the identification of immune eco-evolutionary processes potentially involved in the invasion success of these two rodent species.

scholarly journals Transcriptional Profiling of Leucocyte Count Variation from Porcine Peripheral Blood Reveals Differential Gene Expression

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Adeyinka Abiola Adetula ◽  
Xiangdong Liu ◽  
Thuy Nhien Tran Thi ◽  
Ali Akbar Bhuiyan ◽  
Xiaoyong Du ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
Differential Expression ◽  
Leucocyte Count ◽  
Expression Profiles ◽  
Transcriptional Profiling ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Poly I:C ◽  
Biological Processes

Leucocytes have tremendous health-check importance related to the individual antiviral capacity of pigs and other mammals. However, the molecular mechanism of the immune response of blood leucocytes in pigs is not completely known. This study investigated the leucocyte-count variation before and after poly I:C stimulation in a Duroc–Erhualian F2 population. Pigs with increased and decreased differences in leucocyte counts were coded as increased responder (IR) and decreased responder (DR), respectively. Then, we used microarray technology to compare the gene-expression profiles of both groups of pigs. Transcriptomic analysis identified 129 differentially expressed genes (DEGs) in IR pigs and 136 DEGs in DR pigs. Forty-one common DEGs showed that both groups had similar expression patterns of immune responses. These results illustrated a differential expression in both groups. Furthermore, qPCR experiment was performed to verify the differential-expression profile. Functional annotation of the DEGs indicated that both IR and DR pigs were similar in several biological processes, including innate immune response, and also exhibited distinct differences in biological processes, molecular function, and pathways. These results provided insights into the mechanism underlying the antiviral capacity of pigs.Trial registration numberis CAS Registry Number24939-03-5.

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