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Genetic Analysis of Retinopathy in Type 1 Diabetes

by
Sayed Mohsen Hosseini
A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy

Institute of Medical Science
University of Toronto

© Copyright by S. Mohsen Hosseini 2014

Genetic Analysis of Retinopathy in Type 1 Diabetes

Sayed Mohsen Hosseini Doctor of Philosophy
Institute of Medical Science
University of Toronto

2014

Abstract

Diabetic retinopathy (DR) is a leading cause of blindness worldwide. Several lines of evidence suggest a genetic contribution to the risk of DR; however, no genetic variant has shown convincing association with DR in genome-wide association studies (GWAS).

To identify common polymorphisms associated with DR, meta-GWAS were performed in three type 1 diabetes cohorts of White subjects: Diabetes Complications and Control Trial (DCCT, n=1304), Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR, n=603) and Renin-Angiotensin System Study (RASS, n=239). Severe (SDR) and mild (MDR) retinopathy outcomes were defined based on repeated fundus photographs in each study graded for retinopathy severity on the Early Treatment Diabetic Retinopathy Study (ETDRS) scale. Multivariable models accounted for glycemia (measured by A1C), diabetes duration and other relevant covariates in the association analyses of additive genotypes with SDR and MDR. Fixed-effects metaanalysis was used to combine the results of GWAS performed separately in WESDR,

ii

RASS and subgroups of DCCT, defined by cohort and treatment group. Top association signals were prioritized for replication, based on previous supporting knowledge from the literature, followed by replication in three independent white T1D studies: Genesis-GeneDiab (n=502), Steno (n=936) and FinnDiane (n=2194).

No SNP reached genome-wide significance in survival meta-GWAS for SDR. In a casecontrol meta-GWAS, however, SNPs in DPP10 showed close to genome-wide significant association with SDR. Although, this association could not be replicated in three other studies (P>0.05), the direction of effect remained consistent in all but one of the examined populations. Among the top hits for SDR short of genome-wide significance, SNPs near NLPR3 and AKR1E2 were replicated, after accounting for multiple testing. These signals and other top signals in the meta-GWAS of SDR generally fall in proximity to strong functional candidate genes.

In survival and case-control meta-GWAS for MDR, no SNP reached genome-wide significance. Consistently, our estimation of common additive heritability suggests a stronger genetic component for SDR compared to MDR.

iii

Acknowledgments

First and foremost, I am grateful to all the patients who, despite their pain and suffering, selflessly took the time and effort to participate in long term studies of DCCT/EDIC, WESDR and RASS. You inspire us, teach us and help us be useful. I really hope that the results of my research be a step in the right direction and translate to useful measures to help patients suffering from diabetes in the future.

I am truly grateful to my mentor, Dr. Andrew Paterson, for his unwavering support and great patience over years, giving me the opportunity to start and complete this work. Your direction and understanding have been indispensable.

I am thankful to members of Paterson and Bull lab, past and present, for their assistance and friendships: Daryl Waggott, Charlie “Zhijian” Chen, Enqing Shen. I

would also like to thank everyone from our “Friday meetings” for stimulating

discussions, great insights and support, in particular Drs. Shelley Bull, Andrew Boright, Lei Sun and Angelo Canty. Thanks to Dr. Karen Eny for reviewing introduction of the thesis and providing helpful suggestions. I also thank Dr. Jerald Lawless for his instrumental advice for developing time-to event models.

I am thankful to the members of my advisory committee, Dr. Thomas Hudson and Dr. George Fantus, for their input, guidance and advice during my PhD work.

My doctorate study would not have been possible without graduate scholarships and research assistantships from the Hospital for Sick Children, Vision Science Research Program, Peterborough K.M. Hunter Foundation, University of Toronto and Juvenile Diabetes Research Foundation Canada. Travel awards from Banting and Best Diabetes Centre have certainly enriched my learning experience.

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On a personal note, I am thankful to my parents, brother and sisters for their consistent faith in me and for their continued love, support and encouragement. You are the reason I keep going on. I am grateful to my friends, especially Afshin, Vahid and Vahideh, who stood by my side in difficult times. Finally, I am thankful to the ones who hurt me; you helped me improve, made me stronger and reminded me that: “Au milieu de l'hiver, j'ai découvert en moi un invincible été.”

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List of Abbreviations

  • A1C
  • Glycated hemoglobin

ACACB ACE ACN9 ACO1 ACP6 acetyl-CoA carboxylase beta Angiotensin I Converting Enzyme ACN9 homolog aconitase 1 acid phosphatase 6, lysophosphatidic

  • Albumin Creatinine Ratio
  • ACR

ADCK4 AER aarF domain containing kinase 4 Albumin Excretion Ratio
AFF3 AGE AGER AGT
AF4/FMR2 family, member 3 Advanced Glycation End product Advanced Glycosylation End product-specific Receptor angiotensinogen
AKR1B1 AKR1E2 ARHGAP22 ARL4C ASAP2 ASB3 aldo-keto reductase family 1, member B1 aldo-keto reductase family 1, member E2 Rho GTPase activating protein 22 ADP-ribosylation factor-like 4C ArfGAP with SH3 domain, ankyrin repeat and PH domain 2 ankyrin repeat and SOCS box containing 3

  • Bardet-Biedl syndrome 5
  • BBS5

bFGF BMI basic Fibroblast Growth Factor Body Mass Index

  • BP
  • Blood Pressure

  • BRB
  • Blood-Retina Barrier

CACNA1E CCBP2 CCNE1 CD300A CHN2 CI calcium channel, voltage-dependent, R type, alpha 1E subunit chemokine binding protein 2 cyclin E1 CD300a molecule chimerin 2 Confidence Interval
CLOGLOG COMMD6 COX7A2 CPNE4 CPVL
Complementary Log Log COMM domain containing 6 cytochrome c oxidase subunit VIIa polypeptide 2 copine IV carboxypeptidase, vitellogenic-like

  • Clinically Significant Macular Edema
  • CSME

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  • CVD
  • Cardiovascular Disease

  • DAG
  • diacylglycerol

DBC1 DBP deleted in bladder cancer 1 Diastolic Blood Pressure
DCCT DDX5 DM
Diabetes Complications and Control Trial DEAD (Asp-Glu-Ala-Asp) box helicase 5 Diabetes Mellitus

  • DME
  • Diabetes Macular Edema

  • DN
  • Diabetic Nephropathy

DPP10 DR dipeptidyl-peptidase 10 Diabetic Retinopathy

  • dur
  • Duration of Diabetes

  • DZ
  • Di-Zygotic

  • EDIC
  • Epidemiology of Diabetes Interventions and Complications

ephrin B2 ephrin B2
EFNB2 EFNB2

  • EPO
  • Erythropoietin

ESRD ETDRS FAM107B FAM198A FDR
End Stage Renal Disease Early Treatment Diabetic Retinopathy Study family with sequence similarity 107, member B family with sequence similarity 198, member A False Discovery Rate
FGFR1 FinnDiane FSTL5 FTO GAPDH GBE1 GeneDiab GFR fibroblast growth factor receptor 1 Finnish Diabetic Nephropathy Study follistatin-like 5 fat mass and obesity associated glyceraldehyde-3-phosphate dehydrogenase glucan (1,4-alpha-), branching enzyme 1 Génétique de la Néphropathie Diabétique Glomerular Filteration Rate

  • Growth Hormone
  • GH

  • GJA5
  • gap junction protein, alpha 5

Genetics of Kidney in Diabetes (Study) glucuronidase, beta pseudogene 10 Genome-Wide Association Study heart and neural crest derivatives expressed transcript 2 Glycated hemoglobin
GoKinD GUSBP10 GWAS HAND2 HbA1c

  • HDL
  • High Density Lipoprotein

  • HGF
  • Hepatocyte Growth Factor

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HMGB1 HR high mobility group box 1 Hazard Ratio
HS6ST3 HWE IBD heparan sulfate 6-O-sulfotransferase 3 Hardy-Weinberg Equilibrium Identity-By-Descent

  • IBS
  • Identity by State

ICAM1 ICC intercellular adhesion molecule 1 Intra-Class Correlation
IGF-1 IGSF21 IRMA IRS2
Insulin-like Growth Factor 1 immunoglobin superfamily, member 21 Intra-Retinal Microvascular Abnormalities insulin receptor substrate 2

  • iroquois homeobox 4
  • IRX4

ITGA2 KCNIP4 KCNN2 integrin, alpha 2 Kv channel interacting protein 4 potassium intermediate/small conductance calcium-activated channel, subfamily N, member 2

  • KLF12
  • Kruppel-like factor 12

  • LD
  • Linkage Disequilibrium

  • LDL
  • Low Density Lipoprotein

LINC00426 LINC00460 LINC00523 LINC01118 LMO7 long intergenic non-protein coding RNA 426 long intergenic non-protein coding RNA 460 long intergenic non-protein coding RNA 523 long intergenic non-protein coding RNA 1118 LIM domain 7
LOC643441 LOXHD1 LPA uncharacterized LOC643441 lipoxygenase homology domains 1 lysophosphatidic acid
LRP2 LUZP2 MA low density lipoprotein receptor-related protein 2 leucine zipper protein 2 MicroAneurysm

  • MAF
  • Minor Allele Frequency

MAGI3 MDR membrane associated guanylate kinase, WW and PDZ domain containing 3 Mild Diabetic Retinopathy

  • MDS
  • Multidimensional Scaling

  • MHC
  • Major Histocompatibiltiy Complex

microRNA 3924 marker of proliferation Ki-67
MIR3924 MKI67

  • MTHFR
  • methylenetetrahydrofolate reductase

viii

MTUS1 MVCD MYLIP MYSM1 MZ microtubule associated tumor suppressor 1 MicroVascular Complications of Diabetes myosin regulatory light chain interacting protein Myb-like, SWIRM and MPN domains 1 Mono-Zygotic
N6AMT2 NF - κB NLRP3 NOS3
N-6 adenine-specific DNA methyltransferase 2 Nuclear Factor - kappa B NLR family, pyrin domain containing 3 nitric oxide synthase 3
NPDR ODF1 OR
Non-Proliferative Diabetic Retinopathy outer dense fiber of sperm tails 1 Odds Ratio
OR4K17 PARP2 PC olfactory receptor, family 4, subfamily K, member 17 poly (ADP-ribose) polymerase 2 Principal Component

  • PCA
  • Principal Component Analysis

PCSK2 PDR PECAM1 PH proprotein convertase subtilisin/kexin type 2 Proliferative Diabetic Retinopathy platelet/endothelial cell adhesion molecule 1 Proportional Hazard

  • PKC
  • Protein Kinase C

PLXDC2 PPARG PPP1R12B PTPRS PVT1 plexin domain containing 2 peroxisome proliferator-activated receptor gamma protein phosphatase 1, regulatory subunit 12B protein tyrosine phosphatase, receptor type, S Pvt1 oncogene
RAGE RASS RFWD2 RNF5P1 RNFT2 ROS1 RPPH1 RREB1 SBP receptor for advanced glycation end products Renin Angiotensin System Study ring finger and WD repeat domain 2 ring finger protein 5, E3 ubiquitin protein ligase pseudogene 1 ring finger protein, transmembrane 2 c-ros oncogene 1 , receptor tyrosine kinase ribonuclease P RNA component H1 ras responsive element binding protein 1 Systolic Blood Pressure

  • SDR
  • Severe Diabetic Retinopathy

SDR9C7 SELP short chain dehydrogenase/reductase family 9C, member 7 selectin P

  • SERPINE1
  • serpin peptidase inhibitor, clade E, member 1

ix

SFDR SH3BP4 SIT1 SLC14A2 SLC26A1 SNP SOCS SOD2 SPTLC3 STMND1 SUV39H2 T1D
Stratified False Discovery Rate SH3-domain binding protein 4 signaling threshold regulating transmembrane adaptor 1 solute carrier family 14 (urea transporter), member 2 solute carrier family 26 (anion exchanger), member 1 Single Nucleotide Polymorphism cytokine inducible SH2-containing protein SuperOxide Dismutase 2, mitochondrial serine palmitoyltransferase, long chain base subunit 3 stathmin domain containing 1 suppressor of variegation 3-9 homolog 2 Type 1 Diabetes

  • T2D
  • Type 2 Diabetes

  • TAC1
  • tachykinin, precursor 1

  • TAS
  • trait associated SNP

TBC1D4 TBCD
TBC1 domain family, member 4 tubulin folding cofactor D
TENM4 TLR4 teneurin transmembrane protein 4 toll-like receptor 4
TMEM30A TTC5 UCHL3 USP2-AS1 UTR transmembrane protein 30A tetratricopeptide repeat domain 5 ubiquitin carboxyl-terminal esterase L3 USP2 antisense RNA 1 untranslated region

  • VB
  • Venous Beading

VEGF / VEGFA Vascular Endothelial Growth Factor

  • VTDR
  • Vision-Threatening Diabetic Retinopathy

Wisconsin Epidemiologic Study of Diabetic Retinopathy zinc finger, MIZ-type containing 1 zinc finger protein 696
WESDR ZMIZ1 ZNF696

  • ZNF750
  • zinc finger protein 750

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Table of Contents

Acknowledgments ......................................................................................................................... iv List of Abbreviations...................................................................................................................... vi Table of Contents...........................................................................................................................xi List of Tables............................................................................................................................... xvii List of Figures............................................................................................................................... xxi List of Appendices ..................................................................................................................... xxiii 1. INTRODUCTION ....................................................................................................................1
1.1 Clinical Features of Diabetic Retinopathy.....................................................................2
1.1.1 Natural history of DR...........................................................................................2 1.1.2 Assessment ............................................................................................................3 1.1.3 Prevention and treatment....................................................................................6
1.2 Epidemiology of Diabetic Retinopathy in Type 1 Diabetes .......................................8
1.2.1 Health care impact................................................................................................8 1.2.2 Prevalence of diabetic retinopathy...................................................................10 1.2.3 Incidence of diabetic retinopathy.....................................................................11 1.2.4 Risk factors for diabetic retinopathy................................................................13 1.2.5 Relationship between diabetic retinopathy and nephropathy.....................20
1.3 Genetics of Diabetic Retinopathy .................................................................................22
1.3.1 Evidence for a genetic contribution to DR ......................................................22 1.3.2 Linkage studies of diabetic retinopathy ..........................................................30 1.3.3 Candidate gene association studies of diabetic retinopathy ........................33

xi

1.3.4 Genome-wide association studies of diabetic retinopathy...........................36
1.4 Pathogenesis of Diabetic Retinopathy .........................................................................43
1.4.1 Blood-retinal barrier impairment .....................................................................43 1.4.2 Impaired autoregulation of retinal blood flow...............................................44 1.4.3 Sorbitol accumulation ........................................................................................44 1.4.4 Advanced glycation end products (AGEs) .....................................................46 1.4.5 Protein Kinase C activation...............................................................................47 1.4.6 Retinal microthrombosis....................................................................................48 1.4.7 Angiogenic Factors.............................................................................................48
1.5 Summary..........................................................................................................................49
2. RESEARCH AIMS..................................................................................................................50
2.1 General Aim.....................................................................................................................51 2.2 Specific Objectives ..........................................................................................................51
3. METHODS ..............................................................................................................................53
3.1 Study Populations and Measurement of Phenotypes ...............................................54
3.1.1 The Diabetes Control and Complications Trial - Epidemiology of
Diabetes Interventions and Complications (DCCT/EDIC)...........................54

3.1.2 The Wisconsin Epidemiologic Study of Diabetic Retinopathy
(WESDR) ..............................................................................................................56

3.1.3 Renin Angiotensin System Study (RASS) .......................................................57 3.1.4 Grading of retinopathy severity .......................................................................59 3.1.5 Calculating weighted mean A1C......................................................................60
3.2 Genotyping and Quality Control .................................................................................60
3.2.1 Sample quality.....................................................................................................61

xii

3.2.2 Marker quality.....................................................................................................65
3.3 Genotype Imputation.....................................................................................................66 3.4 Phenotype Modeling......................................................................................................67 3.5 Genome-Wide Association Testing..............................................................................68 3.6 Meta-analysis...................................................................................................................69 3.7 Prioritizing SNPs from GWAS for Replication ..........................................................69 3.8 Replication .......................................................................................................................73
3.8.1 The Finnish Diabetic Nephropathy (FinnDiane) Study................................73 3.8.2 The Steno Clinic Study.......................................................................................74 3.8.3 GeneDiab / Genesis Studies ..............................................................................74
4. RESULTS: META-GWAS OF SEVERE DIABETIC RETINOPATHY............................75
4.1 Characteristics of Study Populations...........................................................................76 4.2 Definition of Severe Diabetic Retinopathy Phenotype..............................................78
4.2.1 Defining time to SDR outcome .........................................................................80
4.3 Association of Baseline Risk Factors With Time-to SDR in DCCT/EDIC...............81 4.4 Development of Time to Event Models for SDR........................................................82 4.5 Identification of Loci Associated with Time-to SDR .................................................84
4.5.1 GWAS of time-to SDR in separate cohorts......................................................84 4.5.2 Meta-GWAS of time-to SDR..............................................................................89
4.6 Case – Control Association Meta-Analysis of SDR....................................................93
4.6.1 Regression models for SDR...............................................................................93 4.6.2 Case-control GWAS of SDR separately by study...........................................94 4.6.3 Case-control meta-GWAS of SDR ....................................................................96

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  • Supplemental Information

    Supplemental Information

    Supplemental information Dissection of the genomic structure of the miR-183/96/182 gene. Previously, we showed that the miR-183/96/182 cluster is an intergenic miRNA cluster, located in a ~60-kb interval between the genes encoding nuclear respiratory factor-1 (Nrf1) and ubiquitin-conjugating enzyme E2H (Ube2h) on mouse chr6qA3.3 (1). To start to uncover the genomic structure of the miR- 183/96/182 gene, we first studied genomic features around miR-183/96/182 in the UCSC genome browser (http://genome.UCSC.edu/), and identified two CpG islands 3.4-6.5 kb 5’ of pre-miR-183, the most 5’ miRNA of the cluster (Fig. 1A; Fig. S1 and Seq. S1). A cDNA clone, AK044220, located at 3.2-4.6 kb 5’ to pre-miR-183, encompasses the second CpG island (Fig. 1A; Fig. S1). We hypothesized that this cDNA clone was derived from 5’ exon(s) of the primary transcript of the miR-183/96/182 gene, as CpG islands are often associated with promoters (2). Supporting this hypothesis, multiple expressed sequences detected by gene-trap clones, including clone D016D06 (3, 4), were co-localized with the cDNA clone AK044220 (Fig. 1A; Fig. S1). Clone D016D06, deposited by the German GeneTrap Consortium (GGTC) (http://tikus.gsf.de) (3, 4), was derived from insertion of a retroviral construct, rFlpROSAβgeo in 129S2 ES cells (Fig. 1A and C). The rFlpROSAβgeo construct carries a promoterless reporter gene, the β−geo cassette - an in-frame fusion of the β-galactosidase and neomycin resistance (Neor) gene (5), with a splicing acceptor (SA) immediately upstream, and a polyA signal downstream of the β−geo cassette (Fig.
  • A Mouse Model of Heritable Cerebrovascular Disease

    A Mouse Model of Heritable Cerebrovascular Disease

    A Mouse Model of Heritable Cerebrovascular Disease Thomas J. Sproule1, John G. Sled2, Jill Wentzell1, Bing Wang1, R. Mark Henkelman2, Derry C. Roopenian1, Robert W. Burgess1* 1 The Jackson Laboratory, Bar Harbor, Maine, United States of America, 2 Hospital for Sick Children, University of Toronto, Toronto, Canada Abstract The study of animal models of heritable cerebrovascular diseases can improve our understanding of disease mechanisms, identify candidate genes for related human disorders, and provide experimental models for preclinical trials. Here we describe a spontaneous mouse mutation that results in reproducible, adult-onset, progressive, focal ischemia in the brain. The pathology is not the result of hemorrhage, embolism, or an anatomical abnormality in the cerebral vasculature. The mutation maps as a single site recessive locus to mouse Chromosome 9 at 105 Mb, a region of shared synteny with human chromosome 3q22. The genetic interval, defined by recombination mapping, contains seven protein-coding genes and one processed transcript, none of which are changed in their expression level, splicing, or sequence in affected mice. Targeted resequencing of the entire interval did not reveal any provocative changes; thus, the causative molecular lesion has not been identified. Citation: Sproule TJ, Sled JG, Wentzell J, Wang B, Henkelman RM, et al. (2010) A Mouse Model of Heritable Cerebrovascular Disease. PLoS ONE 5(12): e15327. doi:10.1371/journal.pone.0015327 Editor: Takeo Yoshikawa, RIKEN Brain Science Institute, Japan Received September 8, 2010; Accepted November 8, 2010; Published December 31, 2010 Copyright: ß 2010 Sproule et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
  • Signaling Pathway Activities Improve Prognosis for Breast Cancer Yunlong Jiao1,2,3,4, Marta R

    Signaling Pathway Activities Improve Prognosis for Breast Cancer Yunlong Jiao1,2,3,4, Marta R

    bioRxiv preprint doi: https://doi.org/10.1101/132357; this version posted April 29, 2017. 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 4.0 International license. Signaling Pathway Activities Improve Prognosis for Breast Cancer Yunlong Jiao1,2,3,4, Marta R. Hidalgo5, Cankut Çubuk6, Alicia Amadoz5, José Carbonell- Caballero5, Jean-Philippe Vert1,2,3,4, and Joaquín Dopazo6,7,8,* 1MINES ParisTech, PSL Research University, Centre for Computational Biology, 77300 Fontainebleau, France; 2Institut Curie, 75248 Paris Cedex, Franc; 3INSERM, U900, 75248 Paris Cedex, France; 4Ecole Normale Supérieure, Department of Mathematics and their Applications, 75005 Paris, France; 5 Computational Genomics Department, Centro de Investigación Príncipe Felipe (CIPF), 46012 Valencia, Spain; 6Clinical Bioinformatics Research Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, 41013, Sevilla, Spain; 7Functional Genomics Node (INB), FPS, Hospital Virgen del Rocío, 41013 Sevilla, Spain; 8 Bioinformatics in Rare Diseases (BiER), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), FPS, Hospital Virgen del Rocío, 41013, Sevilla, Spain *To whom correspondence should be addressed. Abstract With the advent of high-throughput technologies for genome-wide expression profiling, a large number of methods have been proposed to discover gene-based signatures as biomarkers to guide cancer prognosis. However, it is often difficult to interpret the list of genes in a prognostic signature regarding the underlying biological processes responsible for disease progression or therapeutic response. A particularly interesting alternative to gene-based biomarkers is mechanistic biomarkers, derived from signaling pathway activities, which are known to play a key role in cancer progression and thus provide more informative insights into cellular functions involved in cancer mechanism.
  • Stranded DNA and Sensitizes Human Kidney Renal Clear Cell Carcinoma

    Stranded DNA and Sensitizes Human Kidney Renal Clear Cell Carcinoma

    RESEARCH ARTICLE Exosome component 1 cleaves single- stranded DNA and sensitizes human kidney renal clear cell carcinoma cells to poly(ADP-ribose) polymerase inhibitor Qiaoling Liu1†, Qi Xiao1†, Zhen Sun1†, Bo Wang2†, Lina Wang1, Na Wang1, Kai Wang1, Chengli Song1*, Qingkai Yang1* 1Institute of Cancer Stem Cell, DaLian Medical University, Dalian, China; 2Department of General Surgery, Second Affiliated Hospital, DaLian Medical University, Dalian, China Abstract Targeting DNA repair pathway offers an important therapeutic strategy for Homo sapiens (human) cancers. However, the failure of DNA repair inhibitors to markedly benefit patients necessitates the development of new strategies. Here, we show that exosome component 1 (EXOSC1) promotes DNA damages and sensitizes human kidney renal clear cell carcinoma (KIRC) cells to DNA repair inhibitor. Considering that endogenous source of mutation (ESM) constantly assaults genomic DNA and likely sensitizes human cancer cells to the inhibitor, we first analyzed the statistical relationship between the expression of individual genes and the mutations for KIRC. Among the candidates, EXOSC1 most notably promoted DNA damages and subsequent mutations via preferentially cleaving C site(s) in single-stranded DNA. Consistently, EXOSC1 was more *For correspondence: significantly correlated with C>A transversions in coding strands than these in template strands in [email protected] human KIRC. Notably, KIRC patients with high EXOSC1 showed a poor prognosis, and EXOSC1 (CS); sensitized human cancer cells to poly(ADP-ribose) polymerase inhibitors. These results show that [email protected] (QY) EXOSC1 acts as an ESM in KIRC, and targeting EXOSC1 might be a potential therapeutic strategy. †These authors contributed equally to this work Competing interests: The Introduction authors declare that no DNA damages and subsequent mutations are central to development, progression, and treatment competing interests exist.
  • Aneuploidy: Using Genetic Instability to Preserve a Haploid Genome?

    Aneuploidy: Using Genetic Instability to Preserve a Haploid Genome?

    Health Science Campus FINAL APPROVAL OF DISSERTATION Doctor of Philosophy in Biomedical Science (Cancer Biology) Aneuploidy: Using genetic instability to preserve a haploid genome? Submitted by: Ramona Ramdath In partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biomedical Science Examination Committee Signature/Date Major Advisor: David Allison, M.D., Ph.D. Academic James Trempe, Ph.D. Advisory Committee: David Giovanucci, Ph.D. Randall Ruch, Ph.D. Ronald Mellgren, Ph.D. Senior Associate Dean College of Graduate Studies Michael S. Bisesi, Ph.D. Date of Defense: April 10, 2009 Aneuploidy: Using genetic instability to preserve a haploid genome? Ramona Ramdath University of Toledo, Health Science Campus 2009 Dedication I dedicate this dissertation to my grandfather who died of lung cancer two years ago, but who always instilled in us the value and importance of education. And to my mom and sister, both of whom have been pillars of support and stimulating conversations. To my sister, Rehanna, especially- I hope this inspires you to achieve all that you want to in life, academically and otherwise. ii Acknowledgements As we go through these academic journeys, there are so many along the way that make an impact not only on our work, but on our lives as well, and I would like to say a heartfelt thank you to all of those people: My Committee members- Dr. James Trempe, Dr. David Giovanucchi, Dr. Ronald Mellgren and Dr. Randall Ruch for their guidance, suggestions, support and confidence in me. My major advisor- Dr. David Allison, for his constructive criticism and positive reinforcement.