Effects of Hsa21 Gene Expression on Early Vertebrate
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The Utility of Genetic Risk Scores in Predicting the Onset of Stroke March 2021 6
DOT/FAA/AM-21/24 Office of Aerospace Medicine Washington, DC 20591 The Utility of Genetic Risk Scores in Predicting the Onset of Stroke Diana Judith Monroy Rios, M.D1 and Scott J. Nicholson, Ph.D.2 1. KR 30 # 45-03 University Campus, Building 471, 5th Floor, Office 510 Bogotá D.C. Colombia 2. FAA Civil Aerospace Medical Institute, 6500 S. MacArthur Blvd Rm. 354, Oklahoma City, OK 73125 March 2021 NOTICE This document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The United States Government assumes no liability for the contents thereof. _________________ This publication and all Office of Aerospace Medicine technical reports are available in full-text from the Civil Aerospace Medical Institute’s publications Web site: (www.faa.gov/go/oamtechreports) Technical Report Documentation Page 1. Report No. 2. Government Accession No. 3. Recipient's Catalog No. DOT/FAA/AM-21/24 4. Title and Subtitle 5. Report Date March 2021 The Utility of Genetic Risk Scores in Predicting the Onset of Stroke 6. Performing Organization Code 7. Author(s) 8. Performing Organization Report No. Diana Judith Monroy Rios M.D1, and Scott J. Nicholson, Ph.D.2 9. Performing Organization Name and Address 10. Work Unit No. (TRAIS) 1 KR 30 # 45-03 University Campus, Building 471, 5th Floor, Office 510, Bogotá D.C. Colombia 11. Contract or Grant No. 2 FAA Civil Aerospace Medical Institute, 6500 S. MacArthur Blvd Rm. 354, Oklahoma City, OK 73125 12. Sponsoring Agency name and Address 13. Type of Report and Period Covered Office of Aerospace Medicine Federal Aviation Administration 800 Independence Ave., S.W. -
Identification of Genes Concordantly Expressed with Atoh1 During Inner Ear Development
Original Article doi: 10.5115/acb.2011.44.1.69 pISSN 2093-3665 eISSN 2093-3673 Identification of genes concordantly expressed with Atoh1 during inner ear development Heejei Yoon, Dong Jin Lee, Myoung Hee Kim, Jinwoong Bok Department of Anatomy, Brain Korea 21 Project for Medical Science, College of Medicine, Yonsei University, Seoul, Korea Abstract: The inner ear is composed of a cochlear duct and five vestibular organs in which mechanosensory hair cells play critical roles in receiving and relaying sound and balance signals to the brain. To identify novel genes associated with hair cell differentiation or function, we analyzed an archived gene expression dataset from embryonic mouse inner ear tissues. Since atonal homolog 1a (Atoh1) is a well known factor required for hair cell differentiation, we searched for genes expressed in a similar pattern with Atoh1 during inner ear development. The list from our analysis includes many genes previously reported to be involved in hair cell differentiation such as Myo6, Tecta, Myo7a, Cdh23, Atp6v1b1, and Gfi1. In addition, we identified many other genes that have not been associated with hair cell differentiation, including Tekt2, Spag6, Smpx, Lmod1, Myh7b, Kif9, Ttyh1, Scn11a and Cnga2. We examined expression patterns of some of the newly identified genes using real-time polymerase chain reaction and in situ hybridization. For example, Smpx and Tekt2, which are regulators for cytoskeletal dynamics, were shown specifically expressed in the hair cells, suggesting a possible role in hair cell differentiation or function. Here, by re- analyzing archived genetic profiling data, we identified a list of novel genes possibly involved in hair cell differentiation. -
Stelios Pavlidis3, Matthew Loza3, Fred Baribaud3, Anthony
Supplementary Data Th2 and non-Th2 molecular phenotypes of asthma using sputum transcriptomics in UBIOPRED Chih-Hsi Scott Kuo1.2, Stelios Pavlidis3, Matthew Loza3, Fred Baribaud3, Anthony Rowe3, Iaonnis Pandis2, Ana Sousa4, Julie Corfield5, Ratko Djukanovic6, Rene 7 7 8 2 1† Lutter , Peter J. Sterk , Charles Auffray , Yike Guo , Ian M. Adcock & Kian Fan 1†* # Chung on behalf of the U-BIOPRED consortium project team 1Airways Disease, National Heart & Lung Institute, Imperial College London, & Biomedical Research Unit, Biomedical Research Unit, Royal Brompton & Harefield NHS Trust, London, United Kingdom; 2Department of Computing & Data Science Institute, Imperial College London, United Kingdom; 3Janssen Research and Development, High Wycombe, Buckinghamshire, United Kingdom; 4Respiratory Therapeutic Unit, GSK, Stockley Park, United Kingdom; 5AstraZeneca R&D Molndal, Sweden and Areteva R&D, Nottingham, United Kingdom; 6Faculty of Medicine, Southampton University, Southampton, United Kingdom; 7Faculty of Medicine, University of Amsterdam, Amsterdam, Netherlands; 8European Institute for Systems Biology and Medicine, CNRS-ENS-UCBL, Université de Lyon, France. †Contributed equally #Consortium project team members are listed under Supplementary 1 Materials *To whom correspondence should be addressed: [email protected] 2 List of the U-BIOPRED Consortium project team members Uruj Hoda & Christos Rossios, Airways Disease, National Heart & Lung Institute, Imperial College London, UK & Biomedical Research Unit, Biomedical Research Unit, Royal -
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. -
Investigation of Copy Number Variations on Chromosome 21 Detected by Comparative Genomic Hybridization
Li et al. Molecular Cytogenetics (2018) 11:42 https://doi.org/10.1186/s13039-018-0391-3 RESEARCH Open Access Investigation of copy number variations on chromosome 21 detected by comparative genomic hybridization (CGH) microarray in patients with congenital anomalies Wenfu Li, Xianfu Wang and Shibo Li* Abstract Background: The clinical features of Down syndrome vary among individuals, with those most common being congenital heart disease, intellectual disability, developmental abnormity and dysmorphic features. Complex combination of Down syndrome phenotype could be produced by partially copy number variations (CNVs) on chromosome 21 as well. By comparing individual with partial CNVs of chromosome 21 with other patients of known CNVs and clinical phenotypes, we hope to provide a better understanding of the genotype-phenotype correlation of chromosome 21. Methods: A total of 2768 pediatric patients sample collected at the Genetics Laboratory at Oklahoma University Health Science Center were screened using CGH Microarray for CNVs on chromosome 21. Results: We report comprehensive clinical and molecular descriptions of six patients with microduplication and seven patients with microdeletion on the long arm of chromosome 21. Patients with microduplication have varied clinical features including developmental delay, microcephaly, facial dysmorphic features, pulmonary stenosis, autism, preauricular skin tag, eye pterygium, speech delay and pain insensitivity. We found that patients with microdeletion presented with developmental delay, microcephaly, intrauterine fetal demise, epilepsia partialis continua, congenital coronary anomaly and seizures. Conclusion: Three patients from our study combine with four patients in public database suggests an association between 21q21.1 microduplication of CXADR gene and patients with developmental delay. One patient with 21q22.13 microdeletion of DYRK1A shows association with microcephaly and scoliosis. -
A Single-Cell Transcriptomic Landscape of Primate Arterial Aging
ARTICLE https://doi.org/10.1038/s41467-020-15997-0 OPEN A single-cell transcriptomic landscape of primate arterial aging Weiqi Zhang 1,2,3,4,5,13, Shu Zhang6,7,13, Pengze Yan3,8,13, Jie Ren7,9,13, Moshi Song3,5,8, Jingyi Li2,3,8, Jinghui Lei4, Huize Pan2,3, Si Wang3,5,8, Xibo Ma3,10, Shuai Ma2,3,8, Hongyu Li2,3, Fei Sun2,3, Haifeng Wan3,5,11, ✉ ✉ ✉ Wei Li 3,5,11, Piu Chan4, Qi Zhou3,5,11, Guang-Hui Liu 2,3,4,5,8 , Fuchou Tang 6,7,9,12 & Jing Qu 3,5,11 Our understanding of how aging affects the cellular and molecular components of the vas- 1234567890():,; culature and contributes to cardiovascular diseases is still limited. Here we report a single-cell transcriptomic survey of aortas and coronary arteries in young and old cynomolgus monkeys. Our data define the molecular signatures of specialized arteries and identify eight markers discriminating aortic and coronary vasculatures. Gene network analyses characterize tran- scriptional landmarks that regulate vascular senility and position FOXO3A, a longevity- associated transcription factor, as a master regulator gene that is downregulated in six subtypes of monkey vascular cells during aging. Targeted inactivation of FOXO3A in human vascular endothelial cells recapitulates the major phenotypic defects observed in aged monkey arteries, verifying FOXO3A loss as a key driver for arterial endothelial aging. Our study provides a critical resource for understanding the principles underlying primate arterial aging and contributes important clues to future treatment of age-associated vascular disorders. 1 CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China. -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like, -
Enzyme DHRS7
Toward the identification of a function of the “orphan” enzyme DHRS7 Inauguraldissertation zur Erlangung der Würde eines Doktors der Philosophie vorgelegt der Philosophisch-Naturwissenschaftlichen Fakultät der Universität Basel von Selene Araya, aus Lugano, Tessin Basel, 2018 Originaldokument gespeichert auf dem Dokumentenserver der Universität Basel edoc.unibas.ch Genehmigt von der Philosophisch-Naturwissenschaftlichen Fakultät auf Antrag von Prof. Dr. Alex Odermatt (Fakultätsverantwortlicher) und Prof. Dr. Michael Arand (Korreferent) Basel, den 26.6.2018 ________________________ Dekan Prof. Dr. Martin Spiess I. List of Abbreviations 3α/βAdiol 3α/β-Androstanediol (5α-Androstane-3α/β,17β-diol) 3α/βHSD 3α/β-hydroxysteroid dehydrogenase 17β-HSD 17β-Hydroxysteroid Dehydrogenase 17αOHProg 17α-Hydroxyprogesterone 20α/βOHProg 20α/β-Hydroxyprogesterone 17α,20α/βdiOHProg 20α/βdihydroxyprogesterone ADT Androgen deprivation therapy ANOVA Analysis of variance AR Androgen Receptor AKR Aldo-Keto Reductase ATCC American Type Culture Collection CAM Cell Adhesion Molecule CYP Cytochrome P450 CBR1 Carbonyl reductase 1 CRPC Castration resistant prostate cancer Ct-value Cycle threshold-value DHRS7 (B/C) Dehydrogenase/Reductase Short Chain Dehydrogenase Family Member 7 (B/C) DHEA Dehydroepiandrosterone DHP Dehydroprogesterone DHT 5α-Dihydrotestosterone DMEM Dulbecco's Modified Eagle's Medium DMSO Dimethyl Sulfoxide DTT Dithiothreitol E1 Estrone E2 Estradiol ECM Extracellular Membrane EDTA Ethylenediaminetetraacetic acid EMT Epithelial-mesenchymal transition ER Endoplasmic Reticulum ERα/β Estrogen Receptor α/β FBS Fetal Bovine Serum 3 FDR False discovery rate FGF Fibroblast growth factor HEPES 4-(2-Hydroxyethyl)-1-Piperazineethanesulfonic Acid HMDB Human Metabolome Database HPLC High Performance Liquid Chromatography HSD Hydroxysteroid Dehydrogenase IC50 Half-Maximal Inhibitory Concentration LNCaP Lymph node carcinoma of the prostate mRNA Messenger Ribonucleic Acid n.d. -
Macropinocytosis Requires Gal-3 in a Subset of Patient-Derived Glioblastoma Stem Cells
ARTICLE https://doi.org/10.1038/s42003-021-02258-z OPEN Macropinocytosis requires Gal-3 in a subset of patient-derived glioblastoma stem cells Laetitia Seguin1,8, Soline Odouard2,8, Francesca Corlazzoli 2,8, Sarah Al Haddad2, Laurine Moindrot2, Marta Calvo Tardón3, Mayra Yebra4, Alexey Koval5, Eliana Marinari2, Viviane Bes3, Alexandre Guérin 6, Mathilde Allard2, Sten Ilmjärv6, Vladimir L. Katanaev 5, Paul R. Walker3, Karl-Heinz Krause6, Valérie Dutoit2, ✉ Jann N. Sarkaria 7, Pierre-Yves Dietrich2 & Érika Cosset 2 Recently, we involved the carbohydrate-binding protein Galectin-3 (Gal-3) as a druggable target for KRAS-mutant-addicted lung and pancreatic cancers. Here, using glioblastoma patient-derived stem cells (GSCs), we identify and characterize a subset of Gal-3high glio- 1234567890():,; blastoma (GBM) tumors mainly within the mesenchymal subtype that are addicted to Gal-3- mediated macropinocytosis. Using both genetic and pharmacologic inhibition of Gal-3, we showed a significant decrease of GSC macropinocytosis activity, cell survival and invasion, in vitro and in vivo. Mechanistically, we demonstrate that Gal-3 binds to RAB10, a member of the RAS superfamily of small GTPases, and β1 integrin, which are both required for macro- pinocytosis activity and cell survival. Finally, by defining a Gal-3/macropinocytosis molecular signature, we could predict sensitivity to this dependency pathway and provide proof-of- principle for innovative therapeutic strategies to exploit this Achilles’ heel for a significant and unique subset of GBM patients. 1 University Côte d’Azur, CNRS UMR7284, INSERM U1081, Institute for Research on Cancer and Aging (IRCAN), Nice, France. 2 Laboratory of Tumor Immunology, Department of Oncology, Center for Translational Research in Onco-Hematology, Swiss Cancer Center Léman (SCCL), Geneva University Hospitals, University of Geneva, Geneva, Switzerland. -
Large Meta-Analysis of Genome-Wide Association Studies
medRxiv preprint doi: https://doi.org/10.1101/2020.10.01.20200659; this version posted October 4, 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. It is made available under a CC-BY-NC-ND 4.0 International license . Large meta-analysis of genome-wide association studies expands knowledge of the genetic etiology of Alzheimer’s disease and highlights potential translational opportunities Céline Bellenguez1,*,#, Fahri Küçükali2,3,4*, Iris Jansen5,6*, Victor Andrade7,8*, Sonia Morenau- Grau9,10,*, Najaf Amin11,12, Benjamin Grenier-Boley1, Anne Boland13, Luca Kleineidam7,8, Peter Holmans14, Pablo Garcia9,10, Rafael Campos Martin7, Adam Naj15,16, Yang Qiong17, Joshua C. Bis18, Vincent Damotte1, Sven Van der Lee5,6,19, Marcos Costa1, Julien Chapuis1, Vilmentas Giedraitis20, María Jesús Bullido10,21, Adolfo López de Munáin10,22, Jordi Pérez- Tur10,23, Pascual Sánchez-Juan10,24, Raquel Sánchez-Valle25, Victoria Álvarez26, Pau Pastor27, Miguel Medina10,28, Jasper Van Dongen2,3,4, Christine Van Broeckhoven2,3,4, Rik Vandenberghe29,30, Sebastiaan Engelborghs31,32, Gael Nicolas33, Florence Pasquier34, Olivier Hanon35, Carole Dufouil36, Claudine Berr37, Stéphanie Debette36, Jean-François Dartigues36, Gianfranco Spalletta38, Benedetta Nacmias39,40, Vincenzo Solfrezzi41, Barbara Borroni42, Lucio Tremolizzo43, Davide Seripa44, Paolo Caffarra45, Antonio Daniele46,47, Daniela Galimberti48,49, Innocenzo Rainero50, Luisa Benussi51, Alesio Squassina52, Patrizia Mecoci53, Lucilla Parnetti54, Carlo Masullo55, Beatrice Arosio56, John Hardy57, Simon Mead58, Kevin Morgan59, Clive Holmes60, Patrick Kehoe61, Bob Woods62, EADB, Charge, ADGC, Jin Sha15,16, Yi Zhao15,63, Chien-Yueh Lee15,63, Pavel P. -
Supplementary Data
SUPPLEMENTARY DATA A cyclin D1-dependent transcriptional program predicts clinical outcome in mantle cell lymphoma Santiago Demajo et al. 1 SUPPLEMENTARY DATA INDEX Supplementary Methods p. 3 Supplementary References p. 8 Supplementary Tables (S1 to S5) p. 9 Supplementary Figures (S1 to S15) p. 17 2 SUPPLEMENTARY METHODS Western blot, immunoprecipitation, and qRT-PCR Western blot (WB) analysis was performed as previously described (1), using cyclin D1 (Santa Cruz Biotechnology, sc-753, RRID:AB_2070433) and tubulin (Sigma-Aldrich, T5168, RRID:AB_477579) antibodies. Co-immunoprecipitation assays were performed as described before (2), using cyclin D1 antibody (Santa Cruz Biotechnology, sc-8396, RRID:AB_627344) or control IgG (Santa Cruz Biotechnology, sc-2025, RRID:AB_737182) followed by protein G- magnetic beads (Invitrogen) incubation and elution with Glycine 100mM pH=2.5. Co-IP experiments were performed within five weeks after cell thawing. Cyclin D1 (Santa Cruz Biotechnology, sc-753), E2F4 (Bethyl, A302-134A, RRID:AB_1720353), FOXM1 (Santa Cruz Biotechnology, sc-502, RRID:AB_631523), and CBP (Santa Cruz Biotechnology, sc-7300, RRID:AB_626817) antibodies were used for WB detection. In figure 1A and supplementary figure S2A, the same blot was probed with cyclin D1 and tubulin antibodies by cutting the membrane. In figure 2H, cyclin D1 and CBP blots correspond to the same membrane while E2F4 and FOXM1 blots correspond to an independent membrane. Image acquisition was performed with ImageQuant LAS 4000 mini (GE Healthcare). Image processing and quantification were performed with Multi Gauge software (Fujifilm). For qRT-PCR analysis, cDNA was generated from 1 µg RNA with qScript cDNA Synthesis kit (Quantabio). qRT–PCR reaction was performed using SYBR green (Roche). -
Meta-Analysis of Genetic Association with Diagnosed Alzheimer's Disease Identifies Novel Risk Loci and Implicates Abeta, Tau, Immunity and Lipid Processing
bioRxiv preprint doi: https://doi.org/10.1101/294629; this version posted April 4, 2018. 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-NC-ND 4.0 International license. Meta-analysis of genetic association with diagnosed Alzheimer's disease identifies novel risk loci and implicates Abeta, Tau, immunity and lipid processing Kunkle BW+*1, Grenier-Boley B+2,3,4, Sims R5, Bis JC6, Naj AC7, Boland A8, Vronskaya M5, van der Lee SJ9, Amlie- Wolf A10, Bellenguez C2,3,4, Frizatti A5, Chouraki V2,11, Martin ER1,12, Sleegers K13,14, Badarinarayan N5, Jakobsdottir J15, Hamilton-Nelson KL1, Aloso R8, Raybould R5, Chen Y10, Kuzma AB10, Hiltunen M17,18, Morgan T5, Ahmad S9, Vardarajan BN19-21, Epelbaum J22, Hoffmann P23,24,25, Boada M26, Beecham GW1,12, Garnier JG8, Harold D27, Fitzpatrick AL28,29, Valladares O10, Moutet ML8, Gerrish A5, Smith AV30,31, Qu L10, Bacq D8, Denning N5, Jian X32, Zhao Y10, Zompo MD33, Fox NC34, Grove ML23, Choi SH16, Mateo I35, Hughes JT36, Adams HH9, Malamon J10, Garcia FS36, Patel Y37, Brody JA6, Dombroski B10, Naranjo MCD36, Daniilidou M38, Eiriksdottir G15, Mukherjee S39, Wallon D40,41, Uphill J42, Aspelund T15,43, Cantwell LB10, Garzia F8, Galimberti D44, Hofer E45,46, Butkiewics M47, Fin B8, Scarpini E44, Sarnowski C16, Bush W47, Meslage S8, Kornhuber J48, White CC49, Song Y47, Barber RC50, Engelborghs S51,52, Pichler S53, Voijnovic D9, Adams PM54, Vandenberghe