Common Differentially Expressed Genes and Pathways Correlating Both Coronary Artery Disease and Atrial Fibrillation
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
How Macrophages Deal with Death
REVIEWS CELL DEATH AND IMMUNITY How macrophages deal with death Greg Lemke Abstract | Tissue macrophages rapidly recognize and engulf apoptotic cells. These events require the display of so- called eat-me signals on the apoptotic cell surface, the most fundamental of which is phosphatidylserine (PtdSer). Externalization of this phospholipid is catalysed by scramblase enzymes, several of which are activated by caspase cleavage. PtdSer is detected both by macrophage receptors that bind to this phospholipid directly and by receptors that bind to a soluble bridging protein that is independently bound to PtdSer. Prominent among the latter receptors are the MER and AXL receptor tyrosine kinases. Eat-me signals also trigger macrophages to engulf virus- infected or metabolically traumatized, but still living, cells, and this ‘murder by phagocytosis’ may be a common phenomenon. Finally , the localized presentation of PtdSer and other eat- me signals on delimited cell surface domains may enable the phagocytic pruning of these ‘locally dead’ domains by macrophages, most notably by microglia of the central nervous system. In long- lived organisms, abundant cell types are often process. Efferocytosis is a remarkably efficient business: short- lived. In the human body, for example, the macrophages can engulf apoptotic cells in less than lifespan of many white blood cells — including neutro- 10 minutes, and it is therefore difficult experimentally to phils, eosinophils and platelets — is less than 2 weeks. detect free apoptotic cells in vivo, even in tissues where For normal healthy humans, a direct consequence of large numbers are generated7. Many of the molecules this turnover is the routine generation of more than that macrophages and other phagocytes use to recognize 100 billion dead cells each and every day of life1,2. -
Supplemental Table S1
Entrez Gene Symbol Gene Name Affymetrix EST Glomchip SAGE Stanford Literature HPA confirmed Gene ID Profiling profiling Profiling Profiling array profiling confirmed 1 2 A2M alpha-2-macroglobulin 0 0 0 1 0 2 10347 ABCA7 ATP-binding cassette, sub-family A (ABC1), member 7 1 0 0 0 0 3 10350 ABCA9 ATP-binding cassette, sub-family A (ABC1), member 9 1 0 0 0 0 4 10057 ABCC5 ATP-binding cassette, sub-family C (CFTR/MRP), member 5 1 0 0 0 0 5 10060 ABCC9 ATP-binding cassette, sub-family C (CFTR/MRP), member 9 1 0 0 0 0 6 79575 ABHD8 abhydrolase domain containing 8 1 0 0 0 0 7 51225 ABI3 ABI gene family, member 3 1 0 1 0 0 8 29 ABR active BCR-related gene 1 0 0 0 0 9 25841 ABTB2 ankyrin repeat and BTB (POZ) domain containing 2 1 0 1 0 0 10 30 ACAA1 acetyl-Coenzyme A acyltransferase 1 (peroxisomal 3-oxoacyl-Coenzyme A thiol 0 1 0 0 0 11 43 ACHE acetylcholinesterase (Yt blood group) 1 0 0 0 0 12 58 ACTA1 actin, alpha 1, skeletal muscle 0 1 0 0 0 13 60 ACTB actin, beta 01000 1 14 71 ACTG1 actin, gamma 1 0 1 0 0 0 15 81 ACTN4 actinin, alpha 4 0 0 1 1 1 10700177 16 10096 ACTR3 ARP3 actin-related protein 3 homolog (yeast) 0 1 0 0 0 17 94 ACVRL1 activin A receptor type II-like 1 1 0 1 0 0 18 8038 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 1 0 0 0 0 19 8751 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 1 0 0 0 0 20 8728 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 1 0 0 0 0 21 81792 ADAMTS12 ADAM metallopeptidase with thrombospondin type 1 motif, 12 1 0 0 0 0 22 9507 ADAMTS4 ADAM metallopeptidase with thrombospondin type 1 -
ANKRD11 Gene Ankyrin Repeat Domain 11
ANKRD11 gene ankyrin repeat domain 11 Normal Function The ANKRD11 gene provides instructions for making a protein called ankyrin repeat domain 11 (ANKRD11). As its name suggests, this protein contains multiple regions called ankyrin domains; proteins with these domains help other proteins interact with each other. The ANKRD11 protein interacts with certain proteins called histone deacetylases, which are important for controlling gene activity. Through these interactions, ANKRD11 affects when genes are turned on and off. For example, ANKRD11 brings together histone deacetylases and other proteins called p160 coactivators. This association regulates the ability of p160 coactivators to turn on gene activity. ANKRD11 may also enhance the activity of a protein called p53, which controls the growth and division (proliferation) and the self-destruction (apoptosis) of cells. The ANKRD11 protein is found in nerve cells (neurons) in the brain. During embryonic development, ANKRD11 helps regulate the proliferation of these cells and development of the brain. Researchers speculate that the protein may also be involved in the ability of neurons to change and adapt over time (plasticity), which is important for learning and memory. ANKRD11 may function in other cells in the body and appears to be involved in normal bone development. Health Conditions Related to Genetic Changes KBG syndrome Several ANKRD11 gene mutations have been found to cause KBG syndrome, a condition characterized by large upper front teeth and other unusual facial features, skeletal abnormalities, and intellectual disability. Most of these mutations lead to an abnormally short ANKRD11 protein, which likely has little or no function. Reduction of this protein's function is thought to underlie the signs and symptoms of the condition. -
ZNF226 Is Over-Expressed in Brain Metastatic Breast Cancer-PDF 111920
1 ZNF226 is over-expressed in brain metastatic breast cancer. 2 Shahan Mamoor East Islip, NY USA1 3 [email protected] 4 5 Metastasis to the brain is a clinical problem in patients with breast cancer1-3. We mined published 6 microarray data4,5 to compare primary and metastatic tumor transcriptomes to discover genes associated with brain metastasis in patients with metastatic breast cancer. We found that the zinc finger protein 226, 7 encoded by ZNF226 was among the genes whose expression was most different in the brain metastases of patients with brain metastatic breast cancer as compared to primary tumors of the breast. ZNF226 may be 8 relevant to processes underlying metastasis of primary tumor-derived cancer cells to the brain in humans 9 with metastatic breast cancer. 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Keywords: breast cancer, brain metastases, central nervous system metastases, ZNF226, systems biology 26 of breast cancer, targeted therapeutics in breast cancer. 27 28 PAGE 1 1 One report described a 34% incidence of central nervous system metastases in trastuzumab- treated patients with breast cancer2. This alarmingly high frequency of CNS metastasis events demands 2 an enhanced understanding of the transcriptional makeup of brain metastatic tissues to support identification of therapeutic targets, whether they are treatment related or not. We performed a global 3 comparative analysis of primary and metastatic tumors in patients with brain metastatic breast cancer4,5. 4 We discovered significant differential and increased expression of ZNF226 in brain metastatic tissues of patients with metastatic breast cancer. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
Protein Identities in Evs Isolated from U87-MG GBM Cells As Determined by NG LC-MS/MS
Protein identities in EVs isolated from U87-MG GBM cells as determined by NG LC-MS/MS. No. Accession Description Σ Coverage Σ# Proteins Σ# Unique Peptides Σ# Peptides Σ# PSMs # AAs MW [kDa] calc. pI 1 A8MS94 Putative golgin subfamily A member 2-like protein 5 OS=Homo sapiens PE=5 SV=2 - [GG2L5_HUMAN] 100 1 1 7 88 110 12,03704523 5,681152344 2 P60660 Myosin light polypeptide 6 OS=Homo sapiens GN=MYL6 PE=1 SV=2 - [MYL6_HUMAN] 100 3 5 17 173 151 16,91913397 4,652832031 3 Q6ZYL4 General transcription factor IIH subunit 5 OS=Homo sapiens GN=GTF2H5 PE=1 SV=1 - [TF2H5_HUMAN] 98,59 1 1 4 13 71 8,048185945 4,652832031 4 P60709 Actin, cytoplasmic 1 OS=Homo sapiens GN=ACTB PE=1 SV=1 - [ACTB_HUMAN] 97,6 5 5 35 917 375 41,70973209 5,478027344 5 P13489 Ribonuclease inhibitor OS=Homo sapiens GN=RNH1 PE=1 SV=2 - [RINI_HUMAN] 96,75 1 12 37 173 461 49,94108966 4,817871094 6 P09382 Galectin-1 OS=Homo sapiens GN=LGALS1 PE=1 SV=2 - [LEG1_HUMAN] 96,3 1 7 14 283 135 14,70620005 5,503417969 7 P60174 Triosephosphate isomerase OS=Homo sapiens GN=TPI1 PE=1 SV=3 - [TPIS_HUMAN] 95,1 3 16 25 375 286 30,77169764 5,922363281 8 P04406 Glyceraldehyde-3-phosphate dehydrogenase OS=Homo sapiens GN=GAPDH PE=1 SV=3 - [G3P_HUMAN] 94,63 2 13 31 509 335 36,03039959 8,455566406 9 Q15185 Prostaglandin E synthase 3 OS=Homo sapiens GN=PTGES3 PE=1 SV=1 - [TEBP_HUMAN] 93,13 1 5 12 74 160 18,68541938 4,538574219 10 P09417 Dihydropteridine reductase OS=Homo sapiens GN=QDPR PE=1 SV=2 - [DHPR_HUMAN] 93,03 1 1 17 69 244 25,77302971 7,371582031 11 P01911 HLA class II histocompatibility antigen, -
Download The
PROBING THE INTERACTION OF ASPERGILLUS FUMIGATUS CONIDIA AND HUMAN AIRWAY EPITHELIAL CELLS BY TRANSCRIPTIONAL PROFILING IN BOTH SPECIES by POL GOMEZ B.Sc., The University of British Columbia, 2002 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES (Experimental Medicine) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) January 2010 © Pol Gomez, 2010 ABSTRACT The cells of the airway epithelium play critical roles in host defense to inhaled irritants, and in asthma pathogenesis. These cells are constantly exposed to environmental factors, including the conidia of the ubiquitous mould Aspergillus fumigatus, which are small enough to reach the alveoli. A. fumigatus is associated with a spectrum of diseases ranging from asthma and allergic bronchopulmonary aspergillosis to aspergilloma and invasive aspergillosis. Airway epithelial cells have been shown to internalize A. fumigatus conidia in vitro, but the implications of this process for pathogenesis remain unclear. We have developed a cell culture model for this interaction using the human bronchial epithelium cell line 16HBE and a transgenic A. fumigatus strain expressing green fluorescent protein (GFP). Immunofluorescent staining and nystatin protection assays indicated that cells internalized upwards of 50% of bound conidia. Using fluorescence-activated cell sorting (FACS), cells directly interacting with conidia and cells not associated with any conidia were sorted into separate samples, with an overall accuracy of 75%. Genome-wide transcriptional profiling using microarrays revealed significant responses of 16HBE cells and conidia to each other. Significant changes in gene expression were identified between cells and conidia incubated alone versus together, as well as between GFP positive and negative sorted cells. -
Complement Component 4 Genes Contribute Sex-Specific Vulnerability in Diverse Illnesses
bioRxiv preprint doi: https://doi.org/10.1101/761718; this version posted September 9, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. Complement component 4 genes contribute sex-specific vulnerability in diverse illnesses Nolan Kamitaki1,2, Aswin Sekar1,2, Robert E. Handsaker1,2, Heather de Rivera1,2, Katherine Tooley1,2, David L. Morris3, Kimberly E. Taylor4, Christopher W. Whelan1,2, Philip Tombleson3, Loes M. Olde Loohuis5,6, Schizophrenia Working Group of the Psychiatric Genomics Consortium7, Michael Boehnke8, Robert P. Kimberly9, Kenneth M. Kaufman10, John B. Harley10, Carl D. Langefeld11, Christine E. Seidman1,12,13, Michele T. Pato14, Carlos N. Pato14, Roel A. Ophoff5,6, Robert R. Graham15, Lindsey A. Criswell4, Timothy J. Vyse3, Steven A. McCarroll1,2 1 Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA 2 Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA 3 Department of Medical and Molecular Genetics, King’s College London, London WC2R 2LS, UK 4 Rosalind Russell / Ephraim P Engleman Rheumatology Research Center, Division of Rheumatology, UCSF School of Medicine, San Francisco, California 94143, USA 5 Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, California 90095, USA 6 Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, California 90095, USA 7 A full list of collaborators is in Supplementary Information. -
Investigation of Candidate Genes and Mechanisms Underlying Obesity
Prashanth et al. BMC Endocrine Disorders (2021) 21:80 https://doi.org/10.1186/s12902-021-00718-5 RESEARCH ARTICLE Open Access Investigation of candidate genes and mechanisms underlying obesity associated type 2 diabetes mellitus using bioinformatics analysis and screening of small drug molecules G. Prashanth1 , Basavaraj Vastrad2 , Anandkumar Tengli3 , Chanabasayya Vastrad4* and Iranna Kotturshetti5 Abstract Background: Obesity associated type 2 diabetes mellitus is a metabolic disorder ; however, the etiology of obesity associated type 2 diabetes mellitus remains largely unknown. There is an urgent need to further broaden the understanding of the molecular mechanism associated in obesity associated type 2 diabetes mellitus. Methods: To screen the differentially expressed genes (DEGs) that might play essential roles in obesity associated type 2 diabetes mellitus, the publicly available expression profiling by high throughput sequencing data (GSE143319) was downloaded and screened for DEGs. Then, Gene Ontology (GO) and REACTOME pathway enrichment analysis were performed. The protein - protein interaction network, miRNA - target genes regulatory network and TF-target gene regulatory network were constructed and analyzed for identification of hub and target genes. The hub genes were validated by receiver operating characteristic (ROC) curve analysis and RT- PCR analysis. Finally, a molecular docking study was performed on over expressed proteins to predict the target small drug molecules. Results: A total of 820 DEGs were identified between -
Supp Table 1.Pdf
Upregulated genes in Hdac8 null cranial neural crest cells fold change Gene Symbol Gene Title 134.39 Stmn4 stathmin-like 4 46.05 Lhx1 LIM homeobox protein 1 31.45 Lect2 leukocyte cell-derived chemotaxin 2 31.09 Zfp108 zinc finger protein 108 27.74 0710007G10Rik RIKEN cDNA 0710007G10 gene 26.31 1700019O17Rik RIKEN cDNA 1700019O17 gene 25.72 Cyb561 Cytochrome b-561 25.35 Tsc22d1 TSC22 domain family, member 1 25.27 4921513I08Rik RIKEN cDNA 4921513I08 gene 24.58 Ofa oncofetal antigen 24.47 B230112I24Rik RIKEN cDNA B230112I24 gene 23.86 Uty ubiquitously transcribed tetratricopeptide repeat gene, Y chromosome 22.84 D8Ertd268e DNA segment, Chr 8, ERATO Doi 268, expressed 19.78 Dag1 Dystroglycan 1 19.74 Pkn1 protein kinase N1 18.64 Cts8 cathepsin 8 18.23 1500012D20Rik RIKEN cDNA 1500012D20 gene 18.09 Slc43a2 solute carrier family 43, member 2 17.17 Pcm1 Pericentriolar material 1 17.17 Prg2 proteoglycan 2, bone marrow 17.11 LOC671579 hypothetical protein LOC671579 17.11 Slco1a5 solute carrier organic anion transporter family, member 1a5 17.02 Fbxl7 F-box and leucine-rich repeat protein 7 17.02 Kcns2 K+ voltage-gated channel, subfamily S, 2 16.93 AW493845 Expressed sequence AW493845 16.12 1600014K23Rik RIKEN cDNA 1600014K23 gene 15.71 Cst8 cystatin 8 (cystatin-related epididymal spermatogenic) 15.68 4922502D21Rik RIKEN cDNA 4922502D21 gene 15.32 2810011L19Rik RIKEN cDNA 2810011L19 gene 15.08 Btbd9 BTB (POZ) domain containing 9 14.77 Hoxa11os homeo box A11, opposite strand transcript 14.74 Obp1a odorant binding protein Ia 14.72 ORF28 open reading -
Longitudinal Peripheral Blood Transcriptional Analysis of COVID-19 Patients
medRxiv preprint doi: https://doi.org/10.1101/2020.05.05.20091355; this version posted May 8, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. 1 Longitudinal peripheral blood transcriptional analysis of COVID-19 patients 2 captures disease progression and reveals potential biomarkers 3 Qihong Yan1,5,†, Pingchao Li1,†, Xianmiao Ye1,†, Xiaohan Huang1,5,†, Xiaoneng Mo2, 4 Qian Wang1, Yudi Zhang1, Kun Luo1, Zhaoming Chen1, Jia Luo1, Xuefeng Niu3, Ying 5 Feng3, Tianxing Ji3, Bo Feng3, Jinlin Wang2, Feng Li2, Fuchun Zhang2, Fang Li2, 6 Jianhua Wang1, Liqiang Feng1, Zhilong Chen4,*, Chunliang Lei2,*, Linbing Qu1,*, Ling 7 Chen1,2,3,4,* 8 1Guangzhou Regenerative Medicine and Health-Guangdong Laboratory 9 (GRMH-GDL), Guangdong Laboratory of Computational Biomedicine, Guangzhou 10 Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 11 China 12 2Guangzhou Institute of Infectious Disease, Guangzhou Eighth People’s Hospital, 13 Guangzhou Medical University, Guangzhou, China 14 3State Key Laboratory of Respiratory Disease, National Clinical Research Center for 15 Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated 16 Hospital of Guangzhou Medical University, Guangzhou, China 17 4School of Medicine, Huaqiao University, Xiamen, China 18 5University of Chinese Academy of Science, Beijing, China 19 †These authors contributed equally to this work. 20 *To whom correspondence should be addressed: Ling Chen ([email protected]), 21 Linbing Qu ([email protected]), Chunliang Lei ([email protected]), Zhilong 22 Chen ([email protected]) NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase