DOCSLIB.ORG

Dissecting the Genetics of Inflammatory Bowel Disease

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

Dissecting the genetics of Inflammatory Bowel Disease Heather Elding January 2015 Thesis submitted for the degree of Doctor of Philosophy to Research Department of Genetics, Evolution and Environment University College London (UCL) 1 I, Heather Elding confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. 2 Abstract Inflammatory Bowel Disease (IBD) can be classified into two main subtypes: Crohn’s Disease (CD) and Ulcerative Colitis (UC). The aim of this study is to identify the genetic contribution to the susceptibility to IBD. In the first part of the study, I focused on Crohn’s Disease, the subtype that shows the greatest heritability. Using both pooled and sub-phenotype data, followed by replication, the results reveal substantial genetic heterogeneity and the total number of confirmed CD susceptibility loci was increased from 71 published by others to 200. This was achieved by analyzing the data using a multi- marker approach and high-resolution genetic maps in Linkage Disequilibrium Units. In the second part of the study, I focused on Ulcerative Colitis. The results show that although UC has a lower reported heritability, many loci were also found for Ulcerative Colitis. Some of these overlap with those found for Crohn’s Disease. 3 Acknowledgements I would firstly like to thank my primary Ph.D supervisor Dr. Nikolas Maniatis for providing me with this opportunity and for his expert guidance and significant support throughout my time at UCL. Dr. Nikolas Maniatis’s challenging ideas, creativity, and moral support have greatly helped me in shaping my thoughts as a researcher and for successfully carrying out my PhD research. I would also deeply like to thank my secondary Ph.D supervisor Professor Dallas M. Swallow for her invaluable and exemplary scientific expertise and constant support throughout my Ph.D. Professor Dallas M. Swallow has been, and will be, a great inspiration on both a professional and personal level and I have learnt a lot and made significant progress under her supervision, both as a scientist and as an individual. I would also like to thank Dr. Winston Lau for his patience at always taking time to teach me the novel skills and tools that were crucial for carrying out my Ph.D and for always being there to answer my questions. I would like to thank Dr. Adrien Rieux for providing valuable feedback on my Ph.D Thesis, Dr. Toby Andrew, Dr. Doug Speed and Dr. Kaustubh Adhikari for their opinions on certains aspects of the analysis carried out in this thesis work and Karim Boustani who, as a summer student, has contributed with invaluable work. 4 I would also like to thank my parents Josette and Mario Elding and my sister Davinia Elding for supporting me throughout this journey. I would like to thank my aunt Maria Jordanov for always making sure I always had a plain-sailing stay in London and for her support and my aunt Anna Christie for always being there in time of need. I would sincerely like to show my great appreciation to the Departmental Graduate Tutors Dr. Julia Day, Professor Kevin Fowler and Dr. Lazaros Foukas for their great help and understanding as well as their emotional support during very difficult times and life obstacles that I have encountered during my Ph.D. Last, but definitely not least, I would like to thank all my friends, particularly Arjunan Rajasingam, Leanne Grech, Adrien Rieux, Florent Lassalle, Pascale Gerbault, Anke Liebert, my colleagues and friends at UCL Genetics Institute and all the people in my office in the Darwin Building for making my time at UCL an unforgettable happy time and for always being there for me. 5 Table of Contents Abstract 3 Acknowledgements 4 CHAPTER I. GENERAL INTRODUCTION 10 I. Inflammatory Bowel Disease: the story of two diseases. 10 II. An overview of the immune response and Inflammatory Bowel Disease 16 III. The gut microbiota and inflammatory bowel disease 18 IV. Genetic Studies 20 i. Association Studies 25 ii. Linkage Disequilibrium 27 iii. Crohn’s Disease and Ulcerative Colitis GWASs 32 V. Another approach- Linkage Disequilibrium Unit Maps 35 VI. General Aims of Study 43 CHAPTER II. DISSECTING CHROMOSOME 16: GENETIC AND PHENOTYPIC STRATIFICATION PROVIDES INSIGHT INTO CROHN’S DISEASE. 45 I. Introduction 45 II. Methods 48 i. Subjects and Methods 48 ii. Genetic analysis 49 iii. Genetic and Phenotypic stratification 55 III. Results 57 I. NOD2 and CYLD region 57 II. Genetic Heterogeneity within the NOD2 and CYLD region 65 III. CDH3/CDH1 and IRF8 67 IV. Discussion 75 CHAPTER III. NOVEL GENE REGIONS IDENTIFIED FOR CROHN’S DISEASE. 82 I. Introduction 82 II. Methods 83 i. Genetic Analysis 83 ii. Phenotypic Stratification 84 iii. Previously reported and novel significant gene-regions 85 iv. Meta-analysis of shared locations 85 v. Significant gene-regions and Gene Ontology 86 III. Results 87 iv. Identifying the previously reported CD intervals 87 v. Genetic Heterogeneity within the previously reported CD intervals 88 vi. 134 novel gene-regions identified 90 IV. Discussion 94 CHAPTER IV. NOVEL GENE REGIONS IDENTIFIED FOR ULCERATIVE COLITIS. 104 I. Introduction 104 II. Methods 107 i. Subjects 107 ii. Quality Control- WTCCC 2 UC Case-Control Dataset 110 a. Principal Components Analysis 113 b. Relatedness Analysis- Identity-by-Descent and Identity-by-State Analysis 118 c. SNP filtering and individual missingness 119 iii. Quality Control Analysis- NIDDK UC datasets 122 6 iv. Genetic Analysis 138 v. Replications and meta-analysis of shared locations 139 vi. Significant gene-regions identified 140 III. Results 141 i. Identifying the previously reported UC intervals. 141 i. 138 novel gene-regions identified 149 IV. Discussion 160 CHAPTER V. GENERAL DISCUSSION AND FUTURE WORK. 166 i. The story so far. 166 a. Genetic and phenotypic heterogenetiy. 167 b. Interactions and Epistatic effects. 174 ii. Considerations for future work involving the LDU mapping approach 176 iii. Future work- Inflammatory Bowel Disease meta-analysis and beyond. 179 Bibliography 191 Appendix I- Different LD metrics 203 Appendix II- BioMart Analysis from the Crohn’s Disease GWAS described in Chapter III. 205 Appendix III- WTCCC Phase II Ulcerative Colitis Cases, NBS Controls and 1958BC Controls- Quality Control and Data manipulation prior to analysis flowchart. 254 Appendix IV- NIDDK Ulcerative Colitis Cases and Crohn’s Disease Controls- Quality Control and Data manipulation prior to analysis flowchart. 255 Appendix V- BioMart Analysis from the Ulcerative Colitis GWAS described in Chapter IV 256 7 Table of Figures FIGURE 1. THE HUMAN GUT AND STRUCTURE OF THE SMALL-INTESTINAL EPITHELIAL ............................................................................................................................................................. 13 FIGURE 2. INTERACTION OF THE MAJOR IBD-CONTRIBUTORY FACTORS. ........................ 15 FIGURE 3. REPRESENTATION OF THE NOD2 GENE AND THE RELATIVE POSITIONS OF THE THREE COMMON CD-ASSOCIATED NOD2 MUTATIONS (RS2066844- R702W, RS2066845- G9608R AND RS5743293- 3020INSC). ................................................... 23 FIGURE 4. THE RELATIONSHIP BETWEEN LD AND PHYSICAL DISTANCE ........................... 37 FIGURE 5. EXPECTED PAIRWISE ASSOCIATION PER SNP INTERVAL. ................................... 40 FIGURE 6. PARTITIONING THE CHROMOSOME. ...................................................................................... 50 FIGURE 7. LDU MAPPING OF THE ASSOCIATIONS DETECTED IN THE NOD2, CYLD AND COMBINED WINDOWS. ....................................................................................................................... 61 FIGURE 8. LOCALISATION WITHIN THE CDH3/CDH1 REGION. ...................................................... 70 FIGURE 9. LOCALISATION WITHIN THE IRF8 REGION. ........................................................................ 73 FIGURE 10. LOCALISATION WITHIN THE IL1RL1/IL18RAP REGION. ........................................... 90 FIGURE 11. LOCALISATION WITHIN THE ERBB4 REGION. ............................................................... 91 FIGURE 12. PRINCIPAL COMPONENTS ANALYSISN OF WTCCC PHASE II CASE- CONTROL DATASET.......................................................................................................................................114 FIGURE 13. PRINCIPAL COMPONENTS ANALYSIS OF MERGED HAPMAP3 AND WTCCC2 UC CASE-CONTROL DATASETS. ....................................................................................117 FIGURE 14. IDENTITY-BY-DESCENT ANALYSIS OF THE MERGED WTCCC2 UC CASE- CONTROL DATASET BASED ON PAIRWISE KINSHIP COEFFICIENTS. .......................119 FIGURE 15. MULTIDIMENSIONAL SCALING ANALYSIS, BASD ON IBS DISTANCES OF THE MERGED HAPMAP3 AND WTCCC2 UC CASE-CONTROL DATASET. .................121 FIGURE 16. PRINCIPAL COMPONENTS ANALYSIS OF NIDDK IBDO UC CASES GENOTYPED ON THE ILLUMINA HUMANHAP 550V.3 PLATFORM. ................................123 FIGURE 17. PRINCIPAL COMPONENTS ANALYSIS OF NIDDK GRU UC CASES GENOTYPED ON THE ILLUMINA HUMANHAP 550V.3 PLATFORM. ................................124 FIGURE 18. PRINCIPAL COMPONENTS ANALYSIS OF PARKINSON'S DISEASE GWAS CONTROL DATA GENOTYPED ON THE ILLUMINA HUMANHAP 550V.3 PLATFORM. .......................................................................................................................................................................................125 FIGURE 19. PRINCIPAL COMPOENENTS ANALYSIS OF NIDDK
Recommended publications
  • Autophagy: from Basic Science to Clinical Application

    Autophagy: from Basic Science to Clinical Application

    nature publishing group REVIEW See COMMENTARY page XX Autophagy: from basic science to clinical application J Va n L i m b e r g e n 1 , 2 , 3 , C S t e v e n s 4 , E R N i m m o 1 , D C W i l s o n 2 , 3 a n d J S a t s a n g i 1 Autophagy is a cellular pathway involved in protein and organelle degradation, which is likely to represent an innate adaptation to starvation. In times of nutrient deficiency, the cell can self-digest and recycle some nonessential components through nonselective autophagy, thus sustaining minimal growth requirements until a food source becomes available. Over recent years, autophagy has been implicated in an increasing number of clinical scenarios, notably infectious diseases, cancer, neurodegenerative diseases, and autoimmunity. The recent identification of the importance of autophagy genes in the genetic susceptibility to Crohn ’ s disease suggests that a selective autophagic response may play a crucial role in the pathogenesis of common complex immune-mediated diseases. In this review, we discuss the autophagic mechanisms, their molecular regulation, and summarize their clinical relevance. This progress has led to great interest in the therapeutic potential of manipulation of both selective and nonselective autophagy in established disease. INTRODUCTION The ability to adapt to environmental change is essential for sur- Autophagy encompasses several distinct processes involving vival. This is true for the organism as a whole and for individual the delivery of portions of the cytoplasm to the lysosome for cells alike.
  • Effect of Distinct Regulator of G-Protein Signaling 10 Isoforms On

    Effect of Distinct Regulator of G-Protein Signaling 10 Isoforms On

    EFFECT OF DISTINCT REGULATOR OF G-PROTEIN SIGNALING 10 ISOFORMS ON CYTOKINE PRODUCTION. by BENJAMIN JACKWOOD (Under the Direction of Shelley Hooks) ABSTRACT G-protein coupled receptors (GPCRs) mediate a wide variety of cellular functions related to cell proliferation and survival. Regulators of G-protein Signaling (RGS) proteins that are important negative regulators of both G-proteins and GPCR products. The focus of this thesis involves two human protein variants of RGS10 and their effects on cytokine levels. RGS proteins are GTPase Accelerating Proteins (GAPs) which can facilitate an increased rate of GTP hydrolysis to drive inactivation of GPCR signaling. Based on their ability to regulate GPCRs, RGS proteins are implicated in multiple disease states including cancer and neuro-inflammation. The aim of this study was to define the similarities or differences among RGS10 protein isoforms, and help understand their non-canonical function. Particularly, differences in primary sequence of RGS10 protein variants and their ability to mediate inflammatory cytokines in human embryonic kidney (HEK) cells was investigated. INDEX WORDS: GPCR, RGS10, ISOFORM, TNF-, INFLAMMATION, VARIANTS EFFECT OF DISTINCT REGULATOR OF G-PROTEIN SIGNALING 10 ISOFORMS ON CYTOKINE PRODUCTION. by BENJAMIN JACKWOOD BS, University of North Georgia, 2015 A Thesis Submitted to the Pharmaceutical and Biomedical Sciences department of The University of Georgia in Partial Fulfillment of the Requirements for the Degree. MASTER OF SCIENCE ATHENS, GEORGIA 2017 © 2017 Benjamin Jackwood All Rights Reserved EFFECT OF DISTINCT REGULATOR OF G-PROTEIN RGS10 ISOFORMS ON CYTOKINE PRODUCTION. by BENJAMIN JACKWOOD Major Professor: Shelley B. Hooks Committee: Phillip Greenspan Jason Zastre Electronic Version Approved: Suzanne Barbour Dean of the Graduate School The University of Georgia May 2017 ACKNOWLEDGEMENTS Thanks to my family, friends, and helpful lab mates for all of their support during my time working and studying at the University of Georgia.
  • Gene Expression-Based Recurrence Prediction of Hepatitis B Virus-Related Human Hepatocellular Carcinoma

    Gene Expression-Based Recurrence Prediction of Hepatitis B Virus-Related Human Hepatocellular Carcinoma

    GSK 후원 해외연수지원 기금 연구보고 Gene expression-based recurrence prediction of hepatitis B virus-related human hepatocellular carcinoma Yoon Jun Kim, M.D. Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, Seoul, Korea ABSTRACT Hepatocellular carcinoma (HCC) is one of poor prognostic malignancies because of the high rate of recurrence even after curative resection of tumors. To predict and classify the molecular signatures associated with early recurrence, we profiled the gene expression of 65 HCC samples with hepatitis B infection using genome-scale oligonucleotide microarray. We identified 348 unique gene set well reflecting early recurrence (ER) of HCC, which revealed to be enriched by GTPase signaling related genes, transcription, immune response, cell adhesion and motility related genes. We also generated a signature responding to recurrence time by using Cox proportional hazard model (HR genes). Hierarchical clustering showed that HR genes are more accurate classifier than ER genes. In addition, we applied a meta-analysis to integrate earlier expression data (Iizuka et al, 2003), and obtained 232 genes consistently expressed in both the independent data. This signature was validated in an independent study indicating its robustness for the prediction of HCC recurrence. In conclusion, the gene signatures retrieved from different but complementary methods may provide clues to predict patients with increased risk of developing early recurrence, and to identify novel therapeutic targets for HCC. Key Words: Hepatitis B Virus; Hepatocellular carcinoma; Recurrence; Microarray; Gene Expression Profile Corresponding Author: Yoon Jun Kim, Department of Internal Medicine, Seoul National University Hospital, 28 Yongon-dong, Chongno-gu, Seoul 110-744, Korea.
  • PDF Datasheet

    PDF Datasheet

    Product Datasheet C9orf85 Overexpression Lysate NBL1-08604 Unit Size: 0.1 mg Store at -80C. Avoid freeze-thaw cycles. Protocols, Publications, Related Products, Reviews, Research Tools and Images at: www.novusbio.com/NBL1-08604 Updated 3/17/2020 v.20.1 Earn rewards for product reviews and publications. Submit a publication at www.novusbio.com/publications Submit a review at www.novusbio.com/reviews/destination/NBL1-08604 Page 1 of 2 v.20.1 Updated 3/17/2020 NBL1-08604 C9orf85 Overexpression Lysate Product Information Unit Size 0.1 mg Concentration The exact concentration of the protein of interest cannot be determined for overexpression lysates. Please contact technical support for more information. Storage Store at -80C. Avoid freeze-thaw cycles. Buffer RIPA buffer Target Molecular Weight 18.1 kDa Product Description Description Transient overexpression lysate of chromosome 9 open reading frame 85 (C9orf85) The lysate was created in HEK293T cells, using Plasmid ID RC208807 and based on accession number NM_182505. The protein contains a C- MYC/DDK Tag. Gene ID 138241 Gene Symbol C9ORF85 Species Human Notes HEK293T cells in 10-cm dishes were transiently transfected with a non-lipid polymer transfection reagent specially designed and manufactured for large volume DNA transfection. Transfected cells were cultured for 48hrs before collection. The cells were lysed in modified RIPA buffer (25mM Tris-HCl pH7.6, 150mM NaCl, 1% NP-40, 1mM EDTA, 1xProteinase inhibitor cocktail mix, 1mM PMSF and 1mM Na3VO4, and then centrifuged to clarify the lysate. Protein concentration was measured by BCA protein assay kit.This product is manufactured by and sold under license from OriGene Technologies and its use is limited solely for research purposes.
  • Deficiency in Class III PI3-Kinase Confers Postnatal Lethality with IBD

    Deficiency in Class III PI3-Kinase Confers Postnatal Lethality with IBD

    ARTICLE DOI: 10.1038/s41467-018-05105-8 OPEN Deficiency in class III PI3-kinase confers postnatal lethality with IBD-like features in zebrafish Shaoyang Zhao1,2,3, Jianhong Xia2,3, Xiuhua Wu2,3, Leilei Zhang2,3, Pengtao Wang2,3, Haiyun Wang2,3, Heying Li2, Xiaoshan Wang 2, Yan Chen 2, Jean Agnetti2, Yinxiong Li 2, Duanqing Pei2,3 & Xiaodong Shu2,3 The class III PI3-kinase (PIK3C3) is an enzyme responsible for the generation of phospha- tidylinositol 3-phosphate (PI3P), a critical component of vesicular membrane. Here, we report 1234567890():,; that PIK3C3 deficiency in zebrafish results in intestinal injury and inflammation. In pik3c3 mutants, gut tube forms but fails to be maintained. Gene expression analysis reveals that barrier-function-related inflammatory bowel disease (IBD) susceptibility genes (e-cadherin, hnf4a, ttc7a) are suppressed, while inflammatory response genes are stimulated in the mutants. Histological analysis shows neutrophil infiltration into mutant intestinal epithelium and the clearance of gut microbiota. Yet, gut microorganisms appear dispensable as mutants cultured under germ-free condition have similar intestinal defects. Mechanistically, we show that PIK3C3 deficiency suppresses the formation of PI3P and disrupts the polarized dis- tribution of cell-junction proteins in intestinal epithelial cells. These results not only reveal a role of PIK3C3 in gut homeostasis, but also provide a zebrafish IBD model. 1 School of Life Sciences, University of Science and Technology of China, 230027 Hefei, Anhui, China. 2 CAS Key Laboratory of Regenerative Biology, Guangzhou Institute of Biomedicine and Health-Guangzhou Medical University Joint School of Biological Sciences, South China Institute for Stem Cell Biology and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, 510530 Guangzhou, China.
  • Xxviiith Belgian Week of Gastroenterology 2016 All Abstracts Belgian Association for the Study of the Liver (BASL)

    Xxviiith Belgian Week of Gastroenterology 2016 All Abstracts Belgian Association for the Study of the Liver (BASL)

    XXVIIIth Belgian Week of Gastroenterology 2016 All Abstracts Belgian Association for the Study of the Liver (BASL) A01 Light-to-moderate alcohol intake increases the risk of hepatocellular carcinoma in patients with HCV-related compensated cirrhosis: a prospective study H. VANDENBULCKE (1), C. MORENO (2), I. COLLE (3), J. KNEBEL (4), S. FRANCQUE (5), T. SERSTÉ (6), C. GEORGE (7), C. DE GALOCSY (8), W. LALEMAN (9), J. DELWAIDE (10), H. ORLENT (11), L. LASSER (12), E. TRÉPO (2), H. VAN VLIERBERGHE (3), P. MICHIELSEN (5), M. VAN GOSSUM (6), M. DE VOS (1), A. MAROT (13), C. DOERIG (13), M. ADLER (2), J. HENRION (1), P. DELTENRE (13) / [1] Hôpital de Jolimont, Haine-Saint-Paul, Belgium, Departement of Gastroenterology and Hepatology, [2] Erasme Hospital, Brussels, Belgium, Department of Gastroenterology, Hepatopancreatology and Digestive Oncology, [3] Ghent University, Ghent, Belgium, Departement of Gastroenterology and Hepatology, [4] Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland, Division of Radiology, [5] Antwerp University Hospital, Edegem, Belgium, Departement of Gastroenterology and Hepatology, [6] CHU Saint-Pierre, Brussels, Belgium, Departement of Gastroenterology and Hepatology, [7] AZ Groeninge, Kortrijk, Belgium, Departement of Gastroenterology and Hepatology, [8] Hôp. Iris Sud Bracops, Bruxelles, Belgium, Departement of Gastroenterology and Hepatology, [9] KU, Leuven, Belgium, Departement of Gastroenterology and Hepatology, [10] CHU Liege, Liège, Belgium, Departement of Gastroenterology and Hepatology, [11] AZ St. Jan Brugge AV, Brugge, Belgium, Departement of Gastroenterology and Hepatology, [12] CHU Brugmann, , Belgium, Departement of Gastroenterology and Hepatology, [13] Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland, Division of Gastroenterology and Hepatology Introduction: Whether light-to-moderate alcohol intake increases the risk of complications in patients with HCV-related cirrhosis remains unclear.
  • Supplemental Material

    Supplemental Material

    Supplemental Table B ARGs in alphabetical order Symbol Title 3 months 6 months 9 months 12 months 23 months ANOVA Direction Category 38597 septin 2 1557 ± 44 1555 ± 44 1579 ± 56 1655 ± 26 1691 ± 31 0.05219 up Intermediate 0610031j06rik kidney predominant protein NCU-G1 491 ± 6 504 ± 14 503 ± 11 527 ± 13 534 ± 12 0.04747 up Early Adult 1G5 vesicle-associated calmodulin-binding protein 662 ± 23 675 ± 17 629 ± 16 617 ± 20 583 ± 26 0.03129 down Intermediate A2m alpha-2-macroglobulin 262 ± 7 272 ± 8 244 ± 6 290 ± 7 353 ± 16 0.00000 up Midlife Aadat aminoadipate aminotransferase (synonym Kat2) 180 ± 5 201 ± 12 223 ± 7 244 ± 14 275 ± 7 0.00000 up Early Adult Abca2 ATP-binding cassette, sub-family A (ABC1), member 2 958 ± 28 1052 ± 58 1086 ± 36 1071 ± 44 1141 ± 41 0.05371 up Early Adult Abcb1a ATP-binding cassette, sub-family B (MDR/TAP), member 1A 136 ± 8 147 ± 6 147 ± 13 155 ± 9 185 ± 13 0.01272 up Midlife Acadl acetyl-Coenzyme A dehydrogenase, long-chain 423 ± 7 456 ± 11 478 ± 14 486 ± 13 512 ± 11 0.00003 up Early Adult Acadvl acyl-Coenzyme A dehydrogenase, very long chain 426 ± 14 414 ± 10 404 ± 13 411 ± 15 461 ± 10 0.01017 up Late Accn1 amiloride-sensitive cation channel 1, neuronal (degenerin) 242 ± 10 250 ± 9 237 ± 11 247 ± 14 212 ± 8 0.04972 down Late Actb actin, beta 12965 ± 310 13382 ± 170 13145 ± 273 13739 ± 303 14187 ± 269 0.01195 up Midlife Acvrinp1 activin receptor interacting protein 1 304 ± 18 285 ± 21 274 ± 13 297 ± 21 341 ± 14 0.03610 up Late Adk adenosine kinase 1828 ± 43 1920 ± 38 1922 ± 22 2048 ± 30 1949 ± 44 0.00797 up Early
  • Gene PMID WBS Locus ABR 26603386 AASDH 26603386

    Gene PMID WBS Locus ABR 26603386 AASDH 26603386

    Supplementary material J Med Genet Gene PMID WBS Locus ABR 26603386 AASDH 26603386 ABCA1 21304579 ABCA13 26603386 ABCA3 25501393 ABCA7 25501393 ABCC1 25501393 ABCC3 25501393 ABCG1 25501393 ABHD10 21304579 ABHD11 25501393 yes ABHD2 25501393 ABHD5 21304579 ABLIM1 21304579;26603386 ACOT12 25501393 ACSF2,CHAD 26603386 ACSL4 21304579 ACSM3 26603386 ACTA2 25501393 ACTN1 26603386 ACTN3 26603386;25501393;25501393 ACTN4 21304579 ACTR1B 21304579 ACVR2A 21304579 ACY3 19897463 ACYP1 21304579 ADA 25501393 ADAM12 21304579 ADAM19 25501393 ADAM32 26603386 ADAMTS1 25501393 ADAMTS10 25501393 ADAMTS12 26603386 ADAMTS17 26603386 ADAMTS6 21304579 ADAMTS7 25501393 ADAMTSL1 21304579 ADAMTSL4 25501393 ADAMTSL5 25501393 ADCY3 25501393 ADK 21304579 ADRBK2 25501393 AEBP1 25501393 AES 25501393 AFAP1,LOC84740 26603386 AFAP1L2 26603386 AFG3L1 21304579 AGAP1 26603386 AGAP9 21304579 Codina-Sola M, et al. J Med Genet 2019; 56:801–808. doi: 10.1136/jmedgenet-2019-106080 Supplementary material J Med Genet AGBL5 21304579 AGPAT3 19897463;25501393 AGRN 25501393 AGXT2L2 25501393 AHCY 25501393 AHDC1 26603386 AHNAK 26603386 AHRR 26603386 AIDA 25501393 AIFM2 21304579 AIG1 21304579 AIP 21304579 AK5 21304579 AKAP1 25501393 AKAP6 21304579 AKNA 21304579 AKR1E2 26603386 AKR7A2 21304579 AKR7A3 26603386 AKR7L 26603386 AKT3 21304579 ALDH18A1 25501393;25501393 ALDH1A3 21304579 ALDH1B1 21304579 ALDH6A1 21304579 ALDOC 21304579 ALG10B 26603386 ALG13 21304579 ALKBH7 25501393 ALPK2 21304579 AMPH 21304579 ANG 21304579 ANGPTL2,RALGPS1 26603386 ANGPTL6 26603386 ANK2 21304579 ANKMY1 26603386 ANKMY2
  • Dual Proteome-Scale Networks Reveal Cell-Specific Remodeling of the Human Interactome

    Dual Proteome-Scale Networks Reveal Cell-Specific Remodeling of the Human Interactome

    bioRxiv preprint doi: https://doi.org/10.1101/2020.01.19.905109; this version posted January 19, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Dual Proteome-scale Networks Reveal Cell-specific Remodeling of the Human Interactome Edward L. Huttlin1*, Raphael J. Bruckner1,3, Jose Navarrete-Perea1, Joe R. Cannon1,4, Kurt Baltier1,5, Fana Gebreab1, Melanie P. Gygi1, Alexandra Thornock1, Gabriela Zarraga1,6, Stanley Tam1,7, John Szpyt1, Alexandra Panov1, Hannah Parzen1,8, Sipei Fu1, Arvene Golbazi1, Eila Maenpaa1, Keegan Stricker1, Sanjukta Guha Thakurta1, Ramin Rad1, Joshua Pan2, David P. Nusinow1, Joao A. Paulo1, Devin K. Schweppe1, Laura Pontano Vaites1, J. Wade Harper1*, Steven P. Gygi1*# 1Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA. 2Broad Institute, Cambridge, MA, 02142, USA. 3Present address: ICCB-Longwood Screening Facility, Harvard Medical School, Boston, MA, 02115, USA. 4Present address: Merck, West Point, PA, 19486, USA. 5Present address: IQ Proteomics, Cambridge, MA, 02139, USA. 6Present address: Vor Biopharma, Cambridge, MA, 02142, USA. 7Present address: Rubius Therapeutics, Cambridge, MA, 02139, USA. 8Present address: RPS North America, South Kingstown, RI, 02879, USA. *Correspondence: [email protected] (E.L.H.), [email protected] (J.W.H.), [email protected] (S.P.G.) #Lead Contact: [email protected] bioRxiv preprint doi: https://doi.org/10.1101/2020.01.19.905109; this version posted January 19, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder.
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus

    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.
  • PROTEOMIC ANALYSIS of HUMAN URINARY EXOSOMES. Patricia

    PROTEOMIC ANALYSIS of HUMAN URINARY EXOSOMES. Patricia

    ABSTRACT Title of Document: PROTEOMIC ANALYSIS OF HUMAN URINARY EXOSOMES. Patricia Amalia Gonzales Mancilla, Ph.D., 2009 Directed By: Associate Professor Nam Sun Wang, Department of Chemical and Biomolecular Engineering Exosomes originate as the internal vesicles of multivesicular bodies (MVBs) in cells. These small vesicles (40-100 nm) have been shown to be secreted by most cell types throughout the body. In the kidney, urinary exosomes are released to the urine by fusion of the outer membrane of the MVBs with the apical plasma membrane of renal tubular epithelia. Exosomes contain apical membrane and cytosolic proteins and can be isolated using differential centrifugation. The analysis of urinary exosomes provides a non- invasive means of acquiring information about the physiological or pathophysiological state of renal cells. The overall objective of this research was to develop methods and knowledge infrastructure for urinary proteomics. We proposed to conduct a proteomic analysis of human urinary exosomes. The first objective was to profile the proteome of human urinary exosomes using liquid chromatography-tandem spectrometry (LC- MS/MS) and specialized software for identification of peptide sequences from fragmentation spectra. We unambiguously identified 1132 proteins. In addition, the phosphoproteome of human urinary exosomes was profiled using the neutral loss scanning acquisition mode of LC-MS/MS. The phosphoproteomic profiling identified 19 phosphorylation sites corresponding to 14 phosphoproteins. The second objective was to analyze urinary exosomes samples isolated from patients with genetic mutations. Polyclonal antibodies were generated to recognize epitopes on the gene products of these genetic mutations, NKCC2 and MRP4. The potential usefulness of urinary exosome analysis was demonstrated using the well-defined renal tubulopathy, Bartter syndrome type I and using the single nucleotide polymorphism in the ABCC4 gene.
  • Transcriptional Control of Tissue-Resident Memory T Cell Generation

    Transcriptional Control of Tissue-Resident Memory T Cell Generation

    Transcriptional control of tissue-resident memory T cell generation Filip Cvetkovski Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2019 © 2019 Filip Cvetkovski All rights reserved ABSTRACT Transcriptional control of tissue-resident memory T cell generation Filip Cvetkovski Tissue-resident memory T cells (TRM) are a non-circulating subset of memory that are maintained at sites of pathogen entry and mediate optimal protection against reinfection. Lung TRM can be generated in response to respiratory infection or vaccination, however, the molecular pathways involved in CD4+TRM establishment have not been defined. Here, we performed transcriptional profiling of influenza-specific lung CD4+TRM following influenza infection to identify pathways implicated in CD4+TRM generation and homeostasis. Lung CD4+TRM displayed a unique transcriptional profile distinct from spleen memory, including up-regulation of a gene network induced by the transcription factor IRF4, a known regulator of effector T cell differentiation. In addition, the gene expression profile of lung CD4+TRM was enriched in gene sets previously described in tissue-resident regulatory T cells. Up-regulation of immunomodulatory molecules such as CTLA-4, PD-1, and ICOS, suggested a potential regulatory role for CD4+TRM in tissues. Using loss-of-function genetic experiments in mice, we demonstrate that IRF4 is required for the generation of lung-localized pathogen-specific effector CD4+T cells during acute influenza infection. Influenza-specific IRF4−/− T cells failed to fully express CD44, and maintained high levels of CD62L compared to wild type, suggesting a defect in complete differentiation into lung-tropic effector T cells.