Genetic Analysis of Retinopathy in Type 1 Diabetes

Total Page:16

File Type:pdf, Size:1020Kb

Genetic Analysis of Retinopathy in Type 1 Diabetes 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 meta- analysis 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 case- control 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. iv 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.” v List of Abbreviations A1C Glycated hemoglobin ACACB acetyl-CoA carboxylase beta ACE Angiotensin I Converting Enzyme ACN9 ACN9 homolog ACO1 aconitase 1 ACP6 acid phosphatase 6, lysophosphatidic ACR Albumin Creatinine Ratio ADCK4 aarF domain containing kinase 4 AER Albumin Excretion Ratio AFF3 AF4/FMR2 family, member 3 AGE Advanced Glycation End product AGER Advanced Glycosylation End product-specific Receptor AGT angiotensinogen AKR1B1 aldo-keto reductase family 1, member B1 AKR1E2 aldo-keto reductase family 1, member E2 ARHGAP22 Rho GTPase activating protein 22 ARL4C ADP-ribosylation factor-like 4C ASAP2 ArfGAP with SH3 domain, ankyrin repeat and PH domain 2 ASB3 ankyrin repeat and SOCS box containing 3 BBS5 Bardet-Biedl syndrome 5 bFGF basic Fibroblast Growth Factor BMI Body Mass Index BP Blood Pressure BRB Blood-Retina Barrier CACNA1E calcium channel, voltage-dependent, R type, alpha 1E subunit CCBP2 chemokine binding protein 2 CCNE1 cyclin E1 CD300A CD300a molecule CHN2 chimerin 2 CI Confidence Interval CLOGLOG Complementary Log Log COMMD6 COMM domain containing 6 COX7A2 cytochrome c oxidase subunit VIIa polypeptide 2 CPNE4 copine IV CPVL carboxypeptidase, vitellogenic-like CSME Clinically Significant Macular Edema vi CVD Cardiovascular Disease DAG diacylglycerol DBC1 deleted in bladder cancer 1 DBP Diastolic Blood Pressure DCCT Diabetes Complications and Control Trial DDX5 DEAD (Asp-Glu-Ala-Asp) box helicase 5 DM Diabetes Mellitus DME Diabetes Macular Edema DN Diabetic Nephropathy DPP10 dipeptidyl-peptidase 10 DR Diabetic Retinopathy dur Duration of Diabetes DZ Di-Zygotic EDIC Epidemiology of Diabetes Interventions and Complications EFNB2 ephrin B2 EFNB2 ephrin B2 EPO Erythropoietin ESRD End Stage Renal Disease ETDRS Early Treatment Diabetic Retinopathy Study FAM107B family with sequence similarity 107, member B FAM198A family with sequence similarity 198, member A FDR False Discovery Rate FGFR1 fibroblast growth factor receptor 1 FinnDiane Finnish Diabetic Nephropathy Study FSTL5 follistatin-like 5 FTO fat mass and obesity associated GAPDH glyceraldehyde-3-phosphate dehydrogenase GBE1 glucan (1,4-alpha-), branching enzyme 1 GeneDiab Génétique de la Néphropathie Diabétique GFR Glomerular Filteration Rate GH Growth Hormone GJA5 gap junction protein, alpha 5 GoKinD Genetics of Kidney in Diabetes (Study) GUSBP10 glucuronidase, beta pseudogene 10 GWAS Genome-Wide Association Study HAND2 heart and neural crest derivatives expressed transcript 2 HbA1c Glycated hemoglobin HDL High Density Lipoprotein HGF Hepatocyte Growth Factor vii HMGB1 high mobility group box 1 HR Hazard Ratio HS6ST3 heparan sulfate 6-O-sulfotransferase 3 HWE Hardy-Weinberg Equilibrium IBD Identity-By-Descent IBS Identity by State ICAM1 intercellular adhesion molecule 1 ICC Intra-Class Correlation IGF-1 Insulin-like Growth Factor 1 IGSF21 immunoglobin superfamily, member 21 IRMA Intra-Retinal Microvascular Abnormalities IRS2 insulin receptor substrate 2 IRX4 iroquois homeobox 4 ITGA2 integrin, alpha 2 KCNIP4 Kv channel interacting protein 4 KCNN2 potassium intermediate/small conductance calcium-activated channel, subfamily N, member 2 KLF12 Kruppel-like factor 12 LD Linkage Disequilibrium LDL Low Density Lipoprotein LINC00426 long intergenic non-protein coding RNA 426 LINC00460 long intergenic non-protein coding RNA 460 LINC00523 long intergenic non-protein coding RNA 523 LINC01118 long intergenic non-protein coding RNA 1118 LMO7 LIM domain 7 LOC643441 uncharacterized LOC643441 LOXHD1 lipoxygenase homology domains 1 LPA lysophosphatidic acid LRP2 low density lipoprotein receptor-related protein 2 LUZP2 leucine zipper protein 2 MA MicroAneurysm MAF Minor Allele Frequency MAGI3 membrane associated guanylate kinase, WW and PDZ domain containing 3 MDR Mild Diabetic Retinopathy MDS Multidimensional Scaling MHC Major Histocompatibiltiy Complex MIR3924 microRNA 3924 MKI67 marker of proliferation Ki-67 MTHFR methylenetetrahydrofolate reductase viii MTUS1 microtubule associated tumor suppressor 1 MVCD MicroVascular Complications of Diabetes MYLIP myosin regulatory light chain interacting protein MYSM1 Myb-like, SWIRM and MPN domains 1 MZ Mono-Zygotic N6AMT2 N-6 adenine-specific DNA methyltransferase 2 NF - κB Nuclear Factor - kappa B NLRP3 NLR family, pyrin domain containing 3 NOS3 nitric oxide synthase 3 NPDR Non-Proliferative Diabetic Retinopathy ODF1 outer dense fiber of sperm tails 1 OR Odds Ratio OR4K17 olfactory receptor, family 4, subfamily K, member 17 PARP2 poly (ADP-ribose) polymerase 2 PC Principal Component PCA Principal Component Analysis PCSK2 proprotein convertase subtilisin/kexin type 2 PDR Proliferative Diabetic Retinopathy PECAM1 platelet/endothelial cell adhesion molecule 1
Recommended publications
  • PARSANA-DISSERTATION-2020.Pdf
    DECIPHERING TRANSCRIPTIONAL PATTERNS OF GENE REGULATION: A COMPUTATIONAL APPROACH by Princy Parsana A dissertation submitted to The Johns Hopkins University in conformity with the requirements for the degree of Doctor of Philosophy Baltimore, Maryland July, 2020 © 2020 Princy Parsana All rights reserved Abstract With rapid advancements in sequencing technology, we now have the ability to sequence the entire human genome, and to quantify expression of tens of thousands of genes from hundreds of individuals. This provides an extraordinary opportunity to learn phenotype relevant genomic patterns that can improve our understanding of molecular and cellular processes underlying a trait. The high dimensional nature of genomic data presents a range of computational and statistical challenges. This dissertation presents a compilation of projects that were driven by the motivation to efficiently capture gene regulatory patterns in the human transcriptome, while addressing statistical and computational challenges that accompany this data. We attempt to address two major difficulties in this domain: a) artifacts and noise in transcriptomic data, andb) limited statistical power. First, we present our work on investigating the effect of artifactual variation in gene expression data and its impact on trans-eQTL discovery. Here we performed an in-depth analysis of diverse pre-recorded covariates and latent confounders to understand their contribution to heterogeneity in gene expression measurements. Next, we discovered 673 trans-eQTLs across 16 human tissues using v6 data from the Genotype Tissue Expression (GTEx) project. Finally, we characterized two trait-associated trans-eQTLs; one in Skeletal Muscle and another in Thyroid. Second, we present a principal component based residualization method to correct gene expression measurements prior to reconstruction of co-expression networks.
    [Show full text]
  • Whole-Genome Microarray Detects Deletions and Loss of Heterozygosity of Chromosome 3 Occurring Exclusively in Metastasizing Uveal Melanoma
    Anatomy and Pathology Whole-Genome Microarray Detects Deletions and Loss of Heterozygosity of Chromosome 3 Occurring Exclusively in Metastasizing Uveal Melanoma Sarah L. Lake,1 Sarah E. Coupland,1 Azzam F. G. Taktak,2 and Bertil E. Damato3 PURPOSE. To detect deletions and loss of heterozygosity of disease is fatal in 92% of patients within 2 years of diagnosis. chromosome 3 in a rare subset of fatal, disomy 3 uveal mela- Clinical and histopathologic risk factors for UM metastasis noma (UM), undetectable by fluorescence in situ hybridization include large basal tumor diameter (LBD), ciliary body involve- (FISH). ment, epithelioid cytomorphology, extracellular matrix peri- ϩ ETHODS odic acid-Schiff-positive (PAS ) loops, and high mitotic M . Multiplex ligation-dependent probe amplification 3,4 5 (MLPA) with the P027 UM assay was performed on formalin- count. Prescher et al. showed that a nonrandom genetic fixed, paraffin-embedded (FFPE) whole tumor sections from 19 change, monosomy 3, correlates strongly with metastatic death, and the correlation has since been confirmed by several disomy 3 metastasizing UMs. Whole-genome microarray analy- 3,6–10 ses using a single-nucleotide polymorphism microarray (aSNP) groups. Consequently, fluorescence in situ hybridization were performed on frozen tissue samples from four fatal dis- (FISH) detection of chromosome 3 using a centromeric probe omy 3 metastasizing UMs and three disomy 3 tumors with Ͼ5 became routine practice for UM prognostication; however, 5% years’ metastasis-free survival. to 20% of disomy 3 UM patients unexpectedly develop metas- tases.11 Attempts have therefore been made to identify the RESULTS. Two metastasizing UMs that had been classified as minimal region(s) of deletion on chromosome 3.12–15 Despite disomy 3 by FISH analysis of a small tumor sample were found these studies, little progress has been made in defining the key on MLPA analysis to show monosomy 3.
    [Show full text]
  • Refinement and Discovery of New Hotspots of Copy-Number Variation
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector ARTICLE Refinement and Discovery of New Hotspots of Copy-Number Variation Associated with Autism Spectrum Disorder Santhosh Girirajan,1,5 Megan Y. Dennis,1,5 Carl Baker,1 Maika Malig,1 Bradley P. Coe,1 Catarina D. Campbell,1 Kenneth Mark,1 Tiffany H. Vu,1 Can Alkan,1 Ze Cheng,1 Leslie G. Biesecker,2 Raphael Bernier,3 and Evan E. Eichler1,4,* Rare copy-number variants (CNVs) have been implicated in autism and intellectual disability. These variants are large and affect many genes but lack clear specificity toward autism as opposed to developmental-delay phenotypes. We exploited the repeat architecture of the genome to target segmental duplication-mediated rearrangement hotspots (n ¼ 120, median size 1.78 Mbp, range 240 kbp to 13 Mbp) and smaller hotspots flanked by repetitive sequence (n ¼ 1,247, median size 79 kbp, range 3–96 kbp) in 2,588 autistic individuals from simplex and multiplex families and in 580 controls. Our analysis identified several recurrent large hotspot events, including association with 1q21 duplications, which are more likely to be identified in individuals with autism than in those with developmental delay (p ¼ 0.01; OR ¼ 2.7). Within larger hotspots, we also identified smaller atypical CNVs that implicated CHD1L and ACACA for the 1q21 and 17q12 deletions, respectively. Our analysis, however, suggested no overall increase in the burden of smaller hotspots in autistic individuals as compared to controls. By focusing on gene-disruptive events, we identified recurrent CNVs, including DPP10, PLCB1, TRPM1, NRXN1, FHIT, and HYDIN, that are enriched in autism.
    [Show full text]
  • A Novel Computational Algorithm for Predicting Immune Cell Types Using Single-Cell RNA Sequencing Data
    A novel computational algorithm for predicting immune cell types using single-cell RNA sequencing data By Shuo Jia A hesis submitted to the Faculty of Graduate Studies of The University of Manitoba n partial fulfillment of the requirements of the degree of MASTER OF SCIENCE Department of Biochemistry and Medical Genetics University of Manitoba Winnipeg, Manitoba, Canada Copyright © 2020 by Shuo Jia Abstract Background: Cells from our immune system detect and kill pathogens to protect our body against many diseases. However, current methods for determining cell types have some major limitations, such as being time-consuming and with low throughput rate, etc. These problems stack up and hinder the deep exploration of cellular heterogeneity. Immune cells that are associated with cancer tissues play a critical role in revealing the stages of tumor development. Identifying the immune composition within tumor microenvironments in a timely manner will be helpful to improve clinical prognosis and therapeutic management for cancer. Single-cell RNA sequencing (scRNA-seq), an RNA sequencing (RNA-seq) technique that focuses on a single cell level, has provided us with the ability to conduct cell type classification. Although unsupervised clustering approaches are the major methods for analyzing scRNA-seq datasets, their results vary among studies with different input parameters and sizes. However, in supervised machine learning methods, information loss and low prediction accuracy are the key limitations. Methods and Results: Genes in the human genome align to chromosomes in a particular order. Hence, we hypothesize incorporating this information into our model will potentially improve the cell type classification performance. In order to utilize gene positional information, we introduce chromosome-based neural network, namely ChrNet, a novel chromosome-specific re-trainable supervised learning method based on a one-dimensional 1 convolutional neural network (1D-CNN).
    [Show full text]
  • 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.
    [Show full text]
  • 4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
    Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4).
    [Show full text]
  • Missense Variant in LOXHD1 Is Associated with Canine Nonsyndromic Hearing Loss
    Missense Variant in LOXHD1 is Associated With Canine Nonsyndromic Hearing Loss Marjo K Hytönen University of Helsinki: Helsingin Yliopisto Julia E Niskanen University of Helsinki: Helsingin Yliopisto Meharji Arumilli University of Helsinki: Helsingin Yliopisto Casey A Knox Wisdom Health Jonas Donner Genoscoper Laboratories Hannes Lohi ( hannes.lohi@helsinki. ) Helsingin Yliopisto Laaketieteellinen tiedekunta https://orcid.org/0000-0003-1087-5532 Research Article Keywords: dog, hearing, hearing loss, deafness, Rottweiler, stereocilia, PLAT Posted Date: March 16th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-288479/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/16 Abstract Hearing loss is a common sensory decit both in humans and dogs. In canines the genetic basis is largely unknown, as genetic variants have only been identied for a syndromic form of hearing impairment. We observed a congenital or early-onset sensorineural hearing loss in a Rottweiler litter. Assuming an autosomal recessive inheritance, we used a combined approach of homozygosity mapping and genome sequencing to dissect the genetic background of the disorder. We identied a fully segregating missense variant in LOXHD1, a gene that is known to be essential for cochlear hair cell function and associated with nonsyndromic hearing loss in humans and mice. The canine LOXHD1 variant was specic to the Rottweiler breed in our study cohorts of pure-bred dogs. However, it also was present in mixed-breed dogs, of which the majority showed Rottweiler ancestry. Low allele frequencies in these populations, 2.6 % and 0.04 %, respectively, indicate a rare variant.
    [Show full text]
  • 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.
    [Show full text]
  • 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.
    [Show full text]
  • 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.
    [Show full text]
  • 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.
    [Show full text]
  • 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.
    [Show full text]