scholarly journals Multitarget Effects of Danqi Pill on Global Gene Expression Changes in Myocardial Ischemia

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Qiyan Wang ◽  
Hui Meng ◽  
Qian Zhang ◽  
Tianjiao Shi ◽  
Xuefeng Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Myocardial Ischemia ◽  
Differentially Expressed Genes ◽  
Sham Group ◽  
Gene Expression Pattern ◽  
Enrichment Analysis ◽  
Global Gene Expression ◽  
Differentially Expressed ◽  
Group Model ◽  
Model Group

Danqi pill (DQP) is a widely prescribed traditional Chinese medicine (TCM) in the treatment of cardiovascular diseases. The objective of this study is to systematically characterize altered gene expression pattern induced by myocardial ischemia (MI) in a rat model and to investigate the effects of DQP on global gene expression. Global mRNA expression was measured. Differentially expressed genes among the sham group, model group, and DQP group were analyzed. The gene ontology enrichment analysis and pathway analysis of differentially expressed genes were carried out. We quantified 10,813 genes. Compared with the sham group, expressions of 339 genes were upregulated and 177 genes were downregulated in the model group. The upregulated genes were enriched in extracellular matrix organization, response to wounding, and defense response pathways. Downregulated genes were enriched in fatty acid metabolism, pyruvate metabolism, PPAR signaling pathways, and so forth. This indicated that energy metabolic disorders occurred in rats with MI. In the DQP group, expressions of genes in the altered pathways were regulated back towards normal levels. DQP reversed expression of 313 of the 516 differentially expressed genes in the model group. This study provides insight into the multitarget mechanism of TCM in the treatment of complex diseases.

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 Analysis of Transcriptional Changes in Different Brassica napus Synthetic Allopolyploids

Genes ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 82
Author(s):  
Yunxiao Wei ◽  
Guoliang Li ◽  
Shujiang Zhang ◽  
Shifan Zhang ◽  
Hui Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Brassica Napus ◽  
Differentially Expressed Genes ◽  
Expression Patterns ◽  
Female Parent ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Transcriptional Changes ◽  
Aa Genome ◽  
High Degree

Allopolyploidy is an evolutionary and mechanistically intriguing process involving the reconciliation of two or more sets of diverged genomes and regulatory interactions, resulting in new phenotypes. In this study, we explored the gene expression patterns of eight F2 synthetic Brassica napus using RNA sequencing. We found that B. napus allopolyploid formation was accompanied by extensive changes in gene expression. A comparison between F2 and the parent shows a certain proportion of differentially expressed genes (DEG) and activation\silent gene, and the two genomes (female parent (AA)\male parent (CC) genomes) showed significant differences in response to whole-genome duplication (WGD); non-additively expressed genes represented a small portion, while Gene Ontology (GO) enrichment analysis showed that it played an important role in responding to WGD. Besides, genome-wide expression level dominance (ELD) was biased toward the AA genome, and the parental expression pattern of most genes showed a high degree of conservation. Moreover, gene expression showed differences among eight individuals and was consistent with the results of a cluster analysis of traits. Furthermore, the differential expression of waxy synthetic pathways and flowering pathway genes could explain the performance of traits. Collectively, gene expression of the newly formed allopolyploid changed dramatically, and this was different among the selfing offspring, which could be a prominent cause of the trait separation. Our data provide novel insights into the relationship between the expression of differentially expressed genes and trait segregation and provide clues into the evolution of allopolyploids.

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 Diagnostic model of combined ceRNA and DNA methylation related genes in esophageal carcinoma

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8831 ◽  
Author(s):  
Xiaojiao Guan ◽  
Yao Yao ◽  
Guangyao Bao ◽  
Yue Wang ◽  
Aimeng Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Esophageal Cancer ◽  
Esophageal Carcinoma ◽  
Differentially Expressed Genes ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Diagnostic Model ◽  
Link Type ◽  
Key Genes

Esophageal cancer is a common malignant tumor in the world, and the aim of this study was to screen key genes related to the development of esophageal cancer using a variety of bioinformatics analysis tools and analyze their biological functions. The data of esophageal squamous cell carcinoma from the Gene Expression Omnibus (GEO) were selected as the research object, processed and analyzed to screen differentially expressed microRNAs (miRNAs) and differential methylation genes. The competing endogenous RNAs (ceRNAs) interaction network of differentially expressed genes was constructed by bioinformatics tools DAVID, String, and Cytoscape. Biofunctional enrichment analysis was performed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The expression of the screened genes and the survival of the patients were verified. By analyzing GSE59973 and GSE114110, we found three down-regulated and nine up-regulated miRNAs. The gene expression matrix of GSE120356 was calculated by Pearson correlation coefficient, and the 11696 pairs of ceRNA relation were determined. In the ceRNA network, 643 lncRNAs and 147 mRNAs showed methylation difference. Functional enrichment analysis showed that these differentially expressed genes were mainly concentrated in the FoxO signaling pathway and were involved in the corresponding cascade of calcineurin. By analyzing the clinical data in The Cancer Genome Atlas (TCGA) database, it was found that four lncRNAs had an important impact on the survival and prognosis of esophageal carcinoma patients. QRT-PCR was also conducted to identify the expression of the key lncRNAs (RNF217-AS1, HCP5, ZFPM2-AS1 and HCG22) in ESCC samples. The selected key genes can provide theoretical guidance for further research on the molecular mechanism of esophageal carcinoma and the screening of molecular markers.

scholarly journals Diabetes-specific modulation of peripheral blood gene expression signatures in colorectal cancer

2020 ◽  
Vol 20 ◽  
Author(s):  
Zsuzsanna Molnár ◽  
Zsófia Bánlaki ◽  
Anikó Somogyi ◽  
Zoltán Herold ◽  
Magdolna Herold ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Differentially Expressed Genes ◽  
Peripheral Blood ◽  
Expression Patterns ◽  
Enrichment Analysis ◽  
Colorectal Carcinogenesis ◽  
Differentially Expressed ◽  
Blood Leukocytes ◽  
Significant Expression

Background: Type 2 diabetes (T2DM) and colorectal cancer (CRC) are both known to modulate gene expression patterns in peripheral blood leukocytes (PBLs). Objective : As T2DM has been shown to increase the incidence of CRC, we were prompted to check whether diabetes affects mRNA signatures in PBLs isolated from CRC patients. Methods : 22 patients were recruited to the study and classified into four cohorts (healthy controls; T2DM; CRC; CRC and T2DM). Relative expression levels of 573 cell signaling gene transcripts were determined by reverse transcription real-time PCR assays run on low-density OpenArray platforms. Enrichment analysis was performed with the g:GOSt profiling tool to order differentially expressed genes into functional pathways. Results : 49 genes were found to be significantly up- or downregulated in tumorous diabetic individuals as compared to tumor-free diabetic controls, while 11 transcripts were differentially regulated in patients with CRC versus healthy, tumor-free and non-diabetic controls. Importantly, these gene sets were completely distinct, implying that diabetes exerts profound influence on the transcription of signaling genes in CRC. The top 5 genes showing most significant expression differences in both contexts were PCK2, MAPK9, CCND1, HMBS, TLR3 (p≤ 0.0040) and CREBBP, PPIA, NFKBIL1, MDM2 and SELPLG (p0.0121), respectively. Functional analysis revealed that most significantly affected pathways were cytokine, interleukin and PI3K/Akt/mTOR signaling cascades as well as mitotic regulation. Conclusions : We propose that differentially expressed genes listed above might be potential biomarkers of CRC and should be studied further on larger patient groups. Diabetes might promote colorectal carcinogenesis by impairing signaling pathways in PBLs.

48 GLOBAL GENE EXPRESSION PATTERN OF BOS INDICUS AND BOS TAURUS VITRIFIED EMBRYOS

2015 ◽  
Vol 27 (1) ◽  
pp. 117
Author(s):  
R. Cancian ◽  
M. Macelai ◽  
G. Tavares ◽  
R. S. Valente ◽  
E. S. Caixeta ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Pattern ◽  
Cellular Response ◽  
Bos Taurus ◽  
Bos Indicus ◽  
Gene Expression Pattern ◽  
Global Gene Expression ◽  
Differentially Expressed ◽  
Canonical Pathways

The cryopreservation of in vitro-produced (IVP) bovine embryos is one of the most challenging areas of the assisted reproductive biotechnologies. The aim of the present study was to evaluate the global gene expression pattern of Bos indicus (Nellore) and Bos taurus (Simmental) IVP embryos after vitrification. Follicular aspiration was performed on Nellore (n = 14) and Simmental (n = 14) cows, and oocytes (n = 840 and 450; respectively) were submitted to in vitro maturation and in vitro fertilization. Presumptive zygotes were denuded and cultured in SOFaa with 0.5% BSA and 2.5% FCS during 7 days under standard culture conditions. Blastocysts (grade 1 and 2) were vitrified, warmed, and cultured for an additional 12 h under the same conditions. Nellore (n = 8) and Simmental (n = 8) IVP blastocysts considered viable after vitrification, with re-expanded blastocoel, were submitted to total RNA extraction (PicoPure, Arcturus, Applied Biosystems®, Foster Dity, CA, USA), DNAse I treatment (Qiagen®, Valencia, CA, USA), and amplification (RiboAmp, Applied Biosystems®). Fragmented cRNA were obtained through 3′IVT Express Kit (Affymetrix®, Santa Clara, CA, USA) to perform the hybridization using GeneChip Bovine Genome Array (Affymetrix®). Microarray data analysis was performed using the FlexArray 1.6.1.1 software. Genes with at least a 1.5-fold change and a P-value of less than 0.05 were considered differentially expressed. Of the 1278 genes differentially expressed between Bos taurus and Bos indicus vitrified embryos, 1108 were annotated, with 1193 genes up-regulated and 85 genes down-regulated in Bos taurus compared with Bos indicus IVP vitrified embryos. Differentially expressed genes were associated with the functional networks of cell cycle, cellular movement and DNA replication, recombination and repair; RNA post-transcriptional modifications; gene expression, protein synthesis; RNA damage and repair; cellular function and maintenance; and cell death and survival. The top 6 canonical pathways generated by Ingenuity Pathway Analysis® with the differentially expressed genes were ELF2 signalling, oxidative phosphorylation, tricarboxylic acid cycle, protein ubiquitination pathway, mTOR signalling, and IGF-1 signalling. In conclusion, Bos taurus IVP embryos seem to trigger different cellular response mechanisms to the vitrification stress in comparison with Bos indicus IVP embryos. Differential response is mainly represented by different expression profiles of genes regulating important canonical pathways involved in cellular response to stress that could be related with the higher post-cryopreservation survival capacity observed in Bos taurus embryos.Research was supported by FAPESP, CNPq, FAPERGS, and LNBio – National Laboratory of Biosciences/MCT.

Identification of aberrantly methylated differentially expressed genes in melanoma

2020 ◽  
Author(s):  
Wei Han ◽  
Guo-liang Shen
Keyword(s):  
Gene Expression ◽  
Cell Proliferation ◽  
Differentially Expressed Genes ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Regulation Of Transcription ◽  
Biological Processes ◽  
Hub Genes ◽  
Positive Regulation ◽  
Upregulated Genes

Abstract Background: Skin Cutaneous Melanoma (SKCM) is known as an aggressive malignant cancer, which could be directly derived from melanocytic nevi. However, the molecular mechanisms underlying malignant transformation of melanocytes and melanoma tumor progression still remain unclear. Increasing researches showed significant roles of epigenetic modifications, especially DNA methylation, in melanoma. This study focused on identification and analysis of methylation-regulated differentially expressed genes (MeDEGs) between melanocytic nevus and malignant melanoma in genome-wide profiles. Methods: The gene expression profiling datasets (GSE3189 and GSE114445) and gene methylation profiling datasets (GSE86355 and GSE120878) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) were identified via GEO2R. MeDEGs were obtained by integrating the DEGs and DMGs. Then, functional enrichment analysis of MeDEGs were performed. STRING and Cytoscape were used to describe protein-protein interaction(PPI) network. Furthermore, survival analysis was implemented to select the prognostic hub genes. Finally, we conducted gene set enrichment analysis (GSEA) of hub genes. Results: We identified 237 hypomethylated, upregulated genes and 182 hypermethylated, downregulated genes. Hypomethylation-upregulated genes were enriched in biological processes of the oxidation-reduction process, cell proliferation, cell division, phosphorylation, extracellular matrix disassembly and protein sumoylation. Pathway enrichment showed selenocompound metabolism, small cell lung cancer and lysosome. Hypermethylation-downregulated genes were enriched in biological processes of positive regulation of transcription from RNA polymerase II promoter, cell adhesion, cell proliferation, positive regulation of transcription, DNA-templated and angiogenesis. The most significantly enriched pathways involved the transcriptional misregulation in cancer, circadian rhythm, tight junction, protein digestion and absorption and Hippo signaling pathway. After PPI establishment and survival analysis, seven prognostic hub genes were CKS2, DTL, KIF2C, KPNA2, MYBL2, TPX2 and FBL. Moreover, the most involved hallmarks obtained by GSEA were E2F targets, G2M checkpoint and mitotic spindle. Conclusions: Our study identified potential aberrantly methylated-differentially expressed genes participating in the process of malignant transformation from nevus to melanoma tissues based on comprehensive genomic profiles. Transcription profiles of CKS2, DTL, KIF2C, KPNA2, MYBL2, TPX2 and FBL provided clues of aberrantly methylation-based biomarkers, which might improve the development of precise medicine.

scholarly journals Weighted gene co-expression network analysis to identify key modules and hub genes associated with paucigranulocytic asthma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Min Li ◽  
Wenye Zhu ◽  
Chu Wang ◽  
Yuanyuan Zheng ◽  
Shibo Sun ◽  
...  
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Differentially Expressed Genes ◽  
Immune Status ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Hub Genes

Abstract Background Asthma is a heterogeneous disease that can be divided into four inflammatory phenotypes: eosinophilic asthma (EA), neutrophilic asthma (NA), mixed granulocytic asthma (MGA), and paucigranulocytic asthma (PGA). While research has mainly focused on EA and NA, the understanding of PGA is limited. In this study, we aimed to identify underlying mechanisms and hub genes of PGA. Methods Based on the dataset from Gene Expression Omnibus(GEO), weighted gene coexpression network analysis (WGCNA), differentially expressed genes (DEGs) analysis and protein–protein interaction (PPI) network analysis were conducted to construct a gene network and to identify key gene modules and hub genes. Functional enrichment analyses were performed to investigate the biological process, pathways and immune status of PGA. The hub genes were validated in a separate dataset. Results Compared to non-PGA, PGA had a different gene expression pattern, in which 449 genes were differentially expressed. One gene module significantly associated with PGA was identified. Intersection between the differentially expressed genes (DEGs) and the genes from the module that were most relevant to PGA were mainly enriched in inflammation and immune response regulation. The single sample Gene Set Enrichment Analysis (ssGSEA) suggested a decreased immune infiltration and function in PGA. Finally six hub genes of PGA were identified, including ADCY2, CXCL1, FPRL1, GPR109B, GPR109A and ADCY3, which were validated in a separate dataset of GSE137268. Conclusions Our study characterized distinct gene expression patterns, biological processes and immune status of PGA and identified hub genes, which may improve the understanding of underlying mechanism and provide potential therapeutic targets for PGA.

scholarly journals Identification of Diagnostic Markers for Breast Cancer Based on Differential Gene Expression and Pathway Network

2022 ◽  
Vol 9 ◽  
Author(s):  
Shumei Zhang ◽  
Haoran Jiang ◽  
Bo Gao ◽  
Wen Yang ◽  
Guohua Wang
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Interaction ◽  
Diagnostic Markers ◽  
Differentially Expressed ◽  
Breast Cancer Patients ◽  
Gene Interaction Network

Background: Breast cancer is the second largest cancer in the world, the incidence of breast cancer continues to rise worldwide, and women’s health is seriously threatened. Therefore, it is very important to explore the characteristic changes of breast cancer from the gene level, including the screening of differentially expressed genes and the identification of diagnostic markers.Methods: The gene expression profiles of breast cancer were obtained from the TCGA database. The edgeR R software package was used to screen the differentially expressed genes between breast cancer patients and normal samples. The function and pathway enrichment analysis of these genes revealed significant enrichment of functions and pathways. Next, download these pathways from KEGG website, extract the gene interaction relations, construct the KEGG pathway gene interaction network. The potential diagnostic markers of breast cancer were obtained by combining the differentially expressed genes with the key genes in the network. Finally, these markers were used to construct the diagnostic prediction model of breast cancer, and the predictive ability of the model and the diagnostic ability of the markers were verified by internal and external data.Results: 1060 differentially expressed genes were identified between breast cancer patients and normal controls. Enrichment analysis revealed 28 significantly enriched pathways (p < 0.05). They were downloaded from KEGG website, and the gene interaction relations were extracted to construct the gene interaction network of KEGG pathway, which contained 1277 nodes and 7345 edges. The key nodes with a degree greater than 30 were extracted from the network, containing 154 genes. These 154 key genes shared 23 genes with differentially expressed genes, which serve as potential diagnostic markers for breast cancer. The 23 genes were used as features to construct the SVM classification model, and the model had good predictive ability in both the training dataset and the validation dataset (AUC = 0.960 and 0.907, respectively).Conclusion: This study showed that the difference of gene expression level is important for the diagnosis of breast cancer, and identified 23 breast cancer diagnostic markers, which provides valuable information for clinical diagnosis and basic treatment experiments.

The Genetics Analysis of Molecular Pathogenesis for Alzheimer's Disease

2020 ◽  
Vol 83 (5) ◽  
pp. 458-467
Author(s):  
Guanchuan Lin ◽  
Kaiyuan Ji ◽  
Shiyu Li ◽  
Wenli Ma ◽  
Xinghua Pan
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Bioinformatic Analysis ◽  
Brain Regions ◽  
Molecular Pathogenesis ◽  
Differentially Expressed ◽  
Control Group ◽  
Membrane Structures

<b><i>Introduction:</i></b> The molecular pathogenesis of Alzheimer’s disease (AD) is still not clear, and the relationship between gene expression profile for different brain regions has not been studied. <b><i>Objective:</i></b> Bioinformatic analysis at the genetic level has become the best way for the pathogenesis research of AD, which can analyze the abovementioned relationship. <b><i>Methods:</i></b> In this study, the datasets of AD were obtained from the Gene Expression Omnibus (GEO), and Qlucore Omics Explorer (QOE) software was used to screen differentially expressed genes of GSE36980 and GSE9770 and verify gene expression of GSE63060. The Gene Ontology (GO) function enrichment analysis of these selected genes was conducted by Database for Annotation, Visualization, and Integrated Discovery (DAVID), and then the gene/protein interaction network was established by STRING to find the related proteins. R language was used for drafting maps and plots. <b><i>Results:</i></b> There were 20 differentially expressed genes related to AD selected from GSE36980 (<i>p</i> = 6.2e<sup>−6</sup>, <i>q</i> = 2.9422e<sup>−4</sup>) and GSE9770 (<i>p</i> = 3.3e<sup>−4</sup>, <i>q</i> = 0.016606). Their expression levels of the AD group were lower than those in the control group and varied among different brain regions. Cellular morphogenesis and establishment or maintenance of cell polarity were enriched, and <i>LRRTM1</i> and <i>RASAL1</i> were identified by the integration network. Moreover, the analysis of GSE63060 verified the expression level of <i>LRRTM1</i> and <i>RASAL1</i> in Alzheimer’s patients, which was much lower than that in normal people aged &#x3e;65 years. <b><i>Conclusions:</i></b> The pathogenesis of AD at molecular levels may link to cell membrane structures and signal transduction; hence, a list of 20 genes, including <i>LRRTM1</i> and <i>RASAL1,</i>potentially are important for the discovery of treatment target or molecular marker of AD.

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