Selenium-Binding Protein 1: Its Physiological Function, Dependence on Aryl Hydrocarbon Receptors, and Role in Wasting Syndrome by 2,3,7,8-Tetrachlorodibenzo-P-Dioxin
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Convergent Functional Genomics of Schizophrenia: from Comprehensive Understanding to Genetic Risk Prediction
Molecular Psychiatry (2012) 17, 887 -- 905 & 2012 Macmillan Publishers Limited All rights reserved 1359-4184/12 www.nature.com/mp IMMEDIATE COMMUNICATION Convergent functional genomics of schizophrenia: from comprehensive understanding to genetic risk prediction M Ayalew1,2,9, H Le-Niculescu1,9, DF Levey1, N Jain1, B Changala1, SD Patel1, E Winiger1, A Breier1, A Shekhar1, R Amdur3, D Koller4, JI Nurnberger1, A Corvin5, M Geyer6, MT Tsuang6, D Salomon7, NJ Schork7, AH Fanous3, MC O’Donovan8 and AB Niculescu1,2 We have used a translational convergent functional genomics (CFG) approach to identify and prioritize genes involved in schizophrenia, by gene-level integration of genome-wide association study data with other genetic and gene expression studies in humans and animal models. Using this polyevidence scoring and pathway analyses, we identify top genes (DISC1, TCF4, MBP, MOBP, NCAM1, NRCAM, NDUFV2, RAB18, as well as ADCYAP1, BDNF, CNR1, COMT, DRD2, DTNBP1, GAD1, GRIA1, GRIN2B, HTR2A, NRG1, RELN, SNAP-25, TNIK), brain development, myelination, cell adhesion, glutamate receptor signaling, G-protein-- coupled receptor signaling and cAMP-mediated signaling as key to pathophysiology and as targets for therapeutic intervention. Overall, the data are consistent with a model of disrupted connectivity in schizophrenia, resulting from the effects of neurodevelopmental environmental stress on a background of genetic vulnerability. In addition, we show how the top candidate genes identified by CFG can be used to generate a genetic risk prediction score (GRPS) to aid schizophrenia diagnostics, with predictive ability in independent cohorts. The GRPS also differentiates classic age of onset schizophrenia from early onset and late-onset disease. -
Connecting Myelin-Related and Synaptic Dysfunction In
www.nature.com/scientificreports OPEN Connecting myelin-related and synaptic dysfunction in schizophrenia with SNP-rich Received: 24 October 2016 Accepted: 27 February 2017 gene expression hubs Published: 07 April 2017 Hedi Hegyi Combining genome-wide mapping of SNP-rich regions in schizophrenics and gene expression data in all brain compartments across the human life span revealed that genes with promoters most frequently mutated in schizophrenia are expression hubs interacting with far more genes than the rest of the genome. We summed up the differentially methylated “expression neighbors” of genes that fall into one of 108 distinct schizophrenia-associated loci with high number of SNPs. Surprisingly, the number of expression neighbors of the genes in these loci were 35 times higher for the positively correlating genes (32 times higher for the negatively correlating ones) than for the rest of the ~16000 genes. While the genes in the 108 loci have little known impact in schizophrenia, we identified many more known schizophrenia-related important genes with a high degree of connectedness (e.g. MOBP, SYNGR1 and DGCR6), validating our approach. Both the most connected positive and negative hubs affected synapse-related genes the most, supporting the synaptic origin of schizophrenia. At least half of the top genes in both the correlating and anti-correlating categories are cancer-related, including oncogenes (RRAS and ALDOA), providing further insight into the observed inverse relationship between the two diseases. Gene expression correlation, protein-protein interaction and other high-throughput experiments in the post-genomic era have revealed that genes tend to form complex, scale-free networks where most genes have a few connections with others and a few have a high number of interactions, commonly referred to as “hubs”, estab- lishing them as important central genes in these gene networks1. -
Comparative Gene Expression Analysis of Blood and Brain Provides Concurrent Validation of SELENBP1 Up-Regulation in Schizophrenia
Comparative gene expression analysis of blood and brain provides concurrent validation of SELENBP1 up-regulation in schizophrenia Stephen J. Glatta,b,c,d, Ian P. Everallb,c,e, William S. Kremena,c, Jacques Corbeilf,g, Roman Saˇ ´ sˇikh, Negar Khanlouc,e, Mark Hani, Choong-Chin Liewi, and Ming T. Tsuanga,c,j,k,l aCenter for Behavioral Genomics, Departments of cPsychiatry and gMedicine, hUniversity of California San Diego Cancer Center, and eHIV Neurobehavioral Research Center, University of California at San Diego, La Jolla, CA 92093; dVeterans Medical Research Foundation, San Diego, CA 92161; fDepartment of Anatomy and Physiology, Laval University, Quebec, PQ, Canada G1V 4G2; iChondroGene, Inc., Toronto, ON, Canada M3J 3K4; jDepartments of Epidemiology and Psychiatry, Harvard Institute of Psychiatric Epidemiology and Genetics, Boston, MA 02115; and kVeterans Affairs Healthcare System, San Diego, CA 92161 Communicated by Eric R. Kandel, Columbia University, New York, NY, September 1, 2005 (received for review July 28, 2005) Microarray techniques hold great promise for identifying risk come under study. Because gene expression can reflect both genetic factors for schizophrenia (SZ) but have not yet generated widely and environmental influences, it may be particularly useful for reproducible results due to methodological differences between identifying risk factors for a complex disorder such as SZ, which is studies and the high risk of type I inferential errors. Here we thought to have a multifactorial polygenic etiology in which many established a protocol for conservative analysis and interpretation genes and environmental factors interact. However, the simulta- of gene expression data from the dorsolateral prefrontal cortex of neous consideration of thousands of dependent variables also SZ patients using statistical and bioinformatic methods that limit increases the likelihood of false-positive results (7). -
Decreased Selenium-Binding Protein 1 in Esophageal Adenocarcinoma Results from Posttranscriptional and Epigenetic Regulation and Affects Chemosensitivity
Published OnlineFirst March 23, 2010; DOI: 10.1158/1078-0432.CCR-09-2801 Published Online First on March 23, 2010 as 10.1158/1078-0432.CCR-09-2801 Clinical Human Cancer Biology Cancer Research Decreased Selenium-Binding Protein 1 in Esophageal Adenocarcinoma Results from Posttranscriptional and Epigenetic Regulation and Affects Chemosensitivity Amy L. Silvers1, Lin Lin1, Adam J. Bass3, Guoan Chen1, Zhuwen Wang1, Dafydd G. Thomas2, Jules Lin1, Thomas J. Giordano2, Mark B. Orringer1, David G. Beer1, and Andrew C. Chang1 Abstract Purpose: The chemopreventive effects of selenium have been extensively examined, but its role in cancer development or as a chemotherapeutic agent has only recently been explored. Because selenium- binding protein 1 (SELENBP1, SBP1, hSP56) has been shown to bind selenium covalently and selenium deficiency has been associated with esophageal adenocarcinoma (EAC), we examined its role in EAC development and its potential effect on chemosensitivity in the presence of selenium. Experimental Design: SELENBP1 expression level and copy number variation were determined by oligonucleotide microarrays, real-time reverse transcription-PCR, tissue microarrays, immunoblotting, and single-nucleotide polymorphism arrays. Bisulfite sequencing and sequence analysis of reverse transcription-PCR–amplified products explored epigenetic and posttranscriptional regulation of SELENBP1 expression, respectively. WST-1 cell proliferation assays, senescence-associated β-galactosidase staining, immunoblotting, and flow cytometry were done to evaluate the biological significance of SELENBP1 overexpression in selenium-supplemented EAC cells. Results: SELENBP1 expression decreased significantly in Barrett's esophagus to adenocarcinoma pro- gression. Both epigenetic and posttranscriptional mechanisms seemed to modulate SELENBP1 expres- sion. Stable overexpression of SELENBP1 in methylseleninic acid–supplemented Flo-1 cells resulted in enhanced apoptosis, increased cellular senescence, and enhanced cisplatin cytotoxicity. -
A Transcriptome-Wide Approach Reveals the Key Contribution of NFI-A in Promoting Erythroid Differentiation of Human CD34 Þ Progenitors and CML Cells
Letters to the Editor 1220 profiles of acute myeloid/T-lymphoid leukemia with silenced 17 Verhaak RG, Wouters BJ, Erpelinck CA, Abbas S, Beverloo HB, CEBPA and mutations in NOTCH1. Blood 2007; 110: 3706–3714. Lugthart S et al. Prediction of molecular subtypes in acute myeloid 15 Wouters BJ, Lowenberg B, Erpelinck-Verschueren CA, van Putten leukemia based on gene expression profiling. Haematologica WL, Valk PJ, Delwel R. Double CEBPA mutations, but not single 2009; 94: 131–134. CEBPA mutations, define a subgroup of acute myeloid leukemia 18 Swerdlow SH, Campo E, Harris NL, Jaffe ES, Pileri SA, Stein H with a distinctive gene expression profile that is uniquely associated et al. WHO Classification of Tumours of Haematopoietic and with a favorable outcome. Blood 2009; 113: 3088–3091. Lymphoid Tissues. 4th edn IARC: Lyon, France, 2008. 16 Bullinger L, Dohner K, Kranz R, Stirner C, Frohling S, Scholl C 19 Ioannidis JP, Allison DB, Ball CA, Coulibaly I, Cui X, Culhane AC et al. An FLT3 gene-expression signature predicts clinical outcome et al. Repeatability of published microarray gene expression in normal karyotype AML. Blood 2008; 111: 4490–4495. analyses. Nat Genet 2009; 41: 149–155. Supplementary Information accompanies the paper on the Leukemia website (http://www.nature.com/leu) A transcriptome-wide approach reveals the key contribution of NFI-A in promoting erythroid differentiation of human CD34 þ progenitors and CML cells Leukemia (2010) 24, 1220–1223; doi:10.1038/leu.2010.78; NFI-A or a control empty Vector as previously described.2 published online 29 April 2010 Forty-eight hours after transduction, GFP þ cells were sorted using FACSAria instrument (BD Biosciences, San Jose`, CA, USA), subjected to total RNA extraction and hybridized on Agilent whole human genome oligo microarray (No. -
Blood Biomarkers for Memory: Toward Early Detection of Risk for Alzheimer Disease, Pharmacogenomics, and Repurposed Drugs
Molecular Psychiatry (2020) 25:1651–1672 https://doi.org/10.1038/s41380-019-0602-2 IMMEDIATE COMMUNICATION Blood biomarkers for memory: toward early detection of risk for Alzheimer disease, pharmacogenomics, and repurposed drugs 1,2,3 1 1 1,3,4 1 1 1 3 A. B. Niculescu ● H. Le-Niculescu ● K. Roseberry ● S. Wang ● J. Hart ● A. Kaur ● H. Robertson ● T. Jones ● 3 3,5 5 2 1 1,4 4 A. Strasburger ● A. Williams ● S. M. Kurian ● B. Lamb ● A. Shekhar ● D. K. Lahiri ● A. J. Saykin Received: 25 March 2019 / Revised: 25 September 2019 / Accepted: 11 November 2019 / Published online: 2 December 2019 © The Author(s) 2019. This article is published with open access Abstract Short-term memory dysfunction is a key early feature of Alzheimer’s disease (AD). Psychiatric patients may be at higher risk for memory dysfunction and subsequent AD due to the negative effects of stress and depression on the brain. We carried out longitudinal within-subject studies in male and female psychiatric patients to discover blood gene expression biomarkers that track short term memory as measured by the retention measure in the Hopkins Verbal Learning Test. These biomarkers were subsequently prioritized with a convergent functional genomics approach using previous evidence in the field implicating them in AD. The top candidate biomarkers were then tested in an independent cohort for ability to predict state short-term memory, 1234567890();,: 1234567890();,: and trait future positive neuropsychological testing for cognitive impairment. The best overall evidence was for a series of new, as well as some previously known genes, which are now newly shown to have functional evidence in humans as blood biomarkers: RAB7A, NPC2, TGFB1, GAP43, ARSB, PER1, GUSB, and MAPT. -
Chromatin Conformation Links Distal Target Genes to CKD Loci
BASIC RESEARCH www.jasn.org Chromatin Conformation Links Distal Target Genes to CKD Loci Maarten M. Brandt,1 Claartje A. Meddens,2,3 Laura Louzao-Martinez,4 Noortje A.M. van den Dungen,5,6 Nico R. Lansu,2,3,6 Edward E.S. Nieuwenhuis,2 Dirk J. Duncker,1 Marianne C. Verhaar,4 Jaap A. Joles,4 Michal Mokry,2,3,6 and Caroline Cheng1,4 1Experimental Cardiology, Department of Cardiology, Thoraxcenter Erasmus University Medical Center, Rotterdam, The Netherlands; and 2Department of Pediatrics, Wilhelmina Children’s Hospital, 3Regenerative Medicine Center Utrecht, Department of Pediatrics, 4Department of Nephrology and Hypertension, Division of Internal Medicine and Dermatology, 5Department of Cardiology, Division Heart and Lungs, and 6Epigenomics Facility, Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands ABSTRACT Genome-wide association studies (GWASs) have identified many genetic risk factors for CKD. However, linking common variants to genes that are causal for CKD etiology remains challenging. By adapting self-transcribing active regulatory region sequencing, we evaluated the effect of genetic variation on DNA regulatory elements (DREs). Variants in linkage with the CKD-associated single-nucleotide polymorphism rs11959928 were shown to affect DRE function, illustrating that genes regulated by DREs colocalizing with CKD-associated variation can be dysregulated and therefore, considered as CKD candidate genes. To identify target genes of these DREs, we used circular chro- mosome conformation capture (4C) sequencing on glomerular endothelial cells and renal tubular epithelial cells. Our 4C analyses revealed interactions of CKD-associated susceptibility regions with the transcriptional start sites of 304 target genes. Overlap with multiple databases confirmed that many of these target genes are involved in kidney homeostasis. -
Content Based Search in Gene Expression Databases and a Meta-Analysis of Host Responses to Infection
Content Based Search in Gene Expression Databases and a Meta-analysis of Host Responses to Infection A Thesis Submitted to the Faculty of Drexel University by Francis X. Bell in partial fulfillment of the requirements for the degree of Doctor of Philosophy November 2015 c Copyright 2015 Francis X. Bell. All Rights Reserved. ii Acknowledgments I would like to acknowledge and thank my advisor, Dr. Ahmet Sacan. Without his advice, support, and patience I would not have been able to accomplish all that I have. I would also like to thank my committee members and the Biomed Faculty that have guided me. I would like to give a special thanks for the members of the bioinformatics lab, in particular the members of the Sacan lab: Rehman Qureshi, Daisy Heng Yang, April Chunyu Zhao, and Yiqian Zhou. Thank you for creating a pleasant and friendly environment in the lab. I give the members of my family my sincerest gratitude for all that they have done for me. I cannot begin to repay my parents for their sacrifices. I am eternally grateful for everything they have done. The support of my sisters and their encouragement gave me the strength to persevere to the end. iii Table of Contents LIST OF TABLES.......................................................................... vii LIST OF FIGURES ........................................................................ xiv ABSTRACT ................................................................................ xvii 1. A BRIEF INTRODUCTION TO GENE EXPRESSION............................. 1 1.1 Central Dogma of Molecular Biology........................................... 1 1.1.1 Basic Transfers .......................................................... 1 1.1.2 Uncommon Transfers ................................................... 3 1.2 Gene Expression ................................................................. 4 1.2.1 Estimating Gene Expression ............................................ 4 1.2.2 DNA Microarrays ...................................................... -
Spatial Maps of Prostate Cancer Transcriptomes Reveal an Unexplored Landscape of Heterogeneity
ARTICLE DOI: 10.1038/s41467-018-04724-5 OPEN Spatial maps of prostate cancer transcriptomes reveal an unexplored landscape of heterogeneity Emelie Berglund1, Jonas Maaskola1, Niklas Schultz2, Stefanie Friedrich3, Maja Marklund1, Joseph Bergenstråhle1, Firas Tarish2, Anna Tanoglidi4, Sanja Vickovic 1, Ludvig Larsson1, Fredrik Salmeń1, Christoph Ogris3, Karolina Wallenborg2, Jens Lagergren5, Patrik Ståhl1, Erik Sonnhammer3, Thomas Helleday2 & Joakim Lundeberg 1 1234567890():,; Intra-tumor heterogeneity is one of the biggest challenges in cancer treatment today. Here we investigate tissue-wide gene expression heterogeneity throughout a multifocal prostate cancer using the spatial transcriptomics (ST) technology. Utilizing a novel approach for deconvolution, we analyze the transcriptomes of nearly 6750 tissue regions and extract distinct expression profiles for the different tissue components, such as stroma, normal and PIN glands, immune cells and cancer. We distinguish healthy and diseased areas and thereby provide insight into gene expression changes during the progression of prostate cancer. Compared to pathologist annotations, we delineate the extent of cancer foci more accurately, interestingly without link to histological changes. We identify gene expression gradients in stroma adjacent to tumor regions that allow for re-stratification of the tumor micro- environment. The establishment of these profiles is the first step towards an unbiased view of prostate cancer and can serve as a dictionary for future studies. 1 Department of Gene Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health, Royal Institute of Technology (KTH), Science for Life Laboratory, Tomtebodavägen 23, Solna 17165, Sweden. 2 Department of Oncology-Pathology, Karolinska Institutet (KI), Science for Life Laboratory, Tomtebodavägen 23, Solna 17165, Sweden. 3 Department of Biochemistry and Biophysics, Stockholm University, Science for Life Laboratory, Tomtebodavägen 23, Solna 17165, Sweden. -
UNIVERSITY of CALIFORNIA, SAN DIEGO Measuring
UNIVERSITY OF CALIFORNIA, SAN DIEGO Measuring and Correlating Blood and Brain Gene Expression Levels: Assays, Inbred Mouse Strain Comparisons, and Applications to Human Disease Assessment A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Biomedical Sciences by Mary Elizabeth Winn Committee in charge: Professor Nicholas J Schork, Chair Professor Gene Yeo, Co-Chair Professor Eric Courchesne Professor Ron Kuczenski Professor Sanford Shattil 2011 Copyright Mary Elizabeth Winn, 2011 All rights reserved. 2 The dissertation of Mary Elizabeth Winn is approved, and it is acceptable in quality and form for publication on microfilm and electronically: Co-Chair Chair University of California, San Diego 2011 iii DEDICATION To my parents, Dennis E. Winn II and Ann M. Winn, to my siblings, Jessica A. Winn and Stephen J. Winn, and to all who have supported me throughout this journey. iv TABLE OF CONTENTS Signature Page iii Dedication iv Table of Contents v List of Figures viii List of Tables x Acknowledgements xiii Vita xvi Abstract of Dissertation xix Chapter 1 Introduction and Background 1 INTRODUCTION 2 Translational Genomics, Genome-wide Expression Analysis, and Biomarker Discovery 2 Neuropsychiatric Diseases, Tissue Accessibility and Blood-based Gene Expression 4 Mouse Models of Human Disease 5 Microarray Gene Expression Profiling and Globin Reduction 7 Finding and Accessible Surrogate Tissue for Neural Tissue 9 Genetic Background Effect Analysis 11 SPECIFIC AIMS 12 ENUMERATION OF CHAPTERS -
Differential Gene Expression in the Peripheral Zone Compared to the Transition Zone of the Human Prostate Gland
Prostate Cancer and Prostatic Diseases (2008) 11, 173–180 & 2008 Nature Publishing Group All rights reserved 1365-7852/08 $30.00 www.nature.com/pcan ORIGINAL ARTICLE Differential gene expression in the peripheral zone compared to the transition zone of the human prostate gland EE Noel1,4, N Ragavan2,3,4, MJ Walsh2, SY James1, SS Matanhelia3, CM Nicholson3, Y-J Lu1 and FL Martin2 1Medical Oncology Centre, Institute of Cancer, Barts and London School of Medicine and Dentistry Queen Mary, University of London, London, UK; 2Biomedical Sciences Unit, Department of Biological Sciences, Lancaster University, Lancaster, UK and 3Lancashire Teaching Hospitals NHS Trust, Preston, UK Gene expression profiles may lend insight into whether prostate adenocarcinoma (CaP) predominantly occurs in the peripheral zone (PZ) compared to the transition zone (TZ). From human prostates, tissue sets consisting of PZ and TZ were isolated to investigate whether there is a differential level of gene expression between these two regions of this gland. Gene expression profiling using Affymetrix Human Genome U133 plus 2.0 arrays coupled with quantitative real- time reverse transcriptase-PCR was employed. Genes associated with neurogenesis, signal transduction, embryo implantation and cell adhesion were found to be expressed at a higher level in the PZ. Those overexpressed in the TZ were associated with neurogenesis development, signal transduction, cell motility and development. Whether such differential gene expression profiles may identify molecular mechanisms responsible -
Dynamic Gene Expressions of Peripheral Blood Mononuclear Cells
Wu et al. Critical Care (2014) 18:508 DOI 10.1186/s13054-014-0508-y RESEARCH Open Access Dynamic gene expressions of peripheral blood mononuclear cells in patients with acute exacerbation of chronic obstructive pulmonary disease: a preliminary study Xiaodan Wu1†, Xiaoru Sun2†, Chengshui Chen2*, Chunxue Bai3 and Xiangdong Wang2,3* Abstract Introduction: Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is a serious event that is responsible for the progress of the disease, increases in medical costs and high mortality. Methods: Theaimofthepresentstudywastoidentify AECOPD-specific biomarkers by evaluating the dynamic gene ex- pression profiling of peripheral blood mononuclear cells (PBMCs) from patients with AECOPD on days 1, 3 and 10 after hospital admission and to compare the derived data with data from healthy controls or patients with stable COPD. Results: We found that 14 genes were co–differentially upregulated and 2 downregulated greater than 10-fold in patients with COPD or AECOPD compared with the healthy individuals. Eight co–differentially upregulated genes and six down- regulated genes were identified as a panel of AECOPD-specific genes. Downregulation of TCF7 in PBMCs was found to be associated with the severity of COPD. Dynamic changes of Aminolevulinate-delta-synthase 2 and carbonic anhydrase I had similar patterns of Digital Evaluation Score System scores and may serve as potential genes of interest during the course of AECOPD. Conclusion: Thus, our findings indicate a panel of altered gene expression patterns in PBMCs that can be used as AECOPD-specific dynamic biomarkers to monitor the course of AECOPD. Introduction along with a progressive decline in lung function; Chronic obstructive pulmonary disease (COPD) is an AECOPD becomes more frequent and severe when the inflammation-based syndrome characterized by progres- severity of disease increases [4,5].