Immune Deficiency in Jacobsen Syndrome: Molecular And
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The Genetical Society of Great Britain
Heredity 59 (1987) 151—160 The Genetical Society of Great Britain THEGENETICAL SOCIETY (Abstracts of papers presented at the TVVO HUNDRED AND FIFTH MEETING of the Society held on Friday, 14th and Saturday, 15th November 1986 at UNIVERSITY COLLEGE, LONDON) 1. Selection of somatic cell D. J. Porteous, P. A. Boyd, N. D. Hastie and hybrids with specific chromosome V. van Heyningen content for mapping the WAGR MAC Clinical and Population Cytogenetics Unit, Western General Hospital, Crewe Road, syndrome Edinburgh EH4 2XU. J. M. Fletcher, H. Morrison, J. A. Fantes, Clonedprobes for a number of available chromo- A. Seawright, S. Christie, D. J. Porteous, some ii assigned genes were used to define the N. D. Hastie and V. van Heyningen extent of deletions associated with the Wilms' MAC Clinical and Population Cytogenetics Unit, tumour, aniridia, genitourinary abnormalities and Western General Hospital, Crewe Road, mental retardation (WAGR) syndrome. Establish- Edinburgh EH4 2XU. ing reliable dosage studies for a number of different probes has proved difficult. We have therefore WAGR(Wilms tumour, aniridia, genitourinary abnormalities and mental retardation) syndrome concentrated on segregating the deleted chromo- is frequently associated with deletions on the short some 11 from a number of patients in somatic cell arm of chromosome 11. The deletions vary in size hybrids and analysing DNA from these to produce but always include part of band lipl3. To home a consistent map of chromosome lip. At the same in on the Wilms tumour and aniridia loci the end time we have determined the deletion breakpoints points of the different deletion breakpoints need at a molecular level and shown that the results are to be defined at the DNA level. -
Screening and Identification of Key Biomarkers in Clear Cell Renal Cell Carcinoma Based on Bioinformatics Analysis
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. Screening and identification of key biomarkers in clear cell renal cell carcinoma based on bioinformatics analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 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. Abstract Clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignancy of the urinary system. The pathogenesis and effective diagnosis of ccRCC have become popular topics for research in the previous decade. In the current study, an integrated bioinformatics analysis was performed to identify core genes associated in ccRCC. An expression dataset (GSE105261) was downloaded from the Gene Expression Omnibus database, and included 26 ccRCC and 9 normal kideny samples. Assessment of the microarray dataset led to the recognition of differentially expressed genes (DEGs), which was subsequently used for pathway and gene ontology (GO) enrichment analysis. -
Hearing Aging Is 14.1±0.4% GWAS-Heritable
medRxiv preprint doi: https://doi.org/10.1101/2021.07.05.21260048; this version posted July 7, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license . Predicting age from hearing test results with machine learning reveals the genetic and environmental factors underlying accelerated auditory aging Alan Le Goallec1,2+, Samuel Diai1+, Théo Vincent1, Chirag J. Patel1* 1Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA 2Department of Systems, Synthetic and Quantitative Biology, Harvard University, Cambridge, MA, 02118, USA +Co-first authors *Corresponding author Contact information: Chirag J Patel [email protected] Abstract With the aging of the world population, age-related hearing loss (presbycusis) and other hearing disorders such as tinnitus become more prevalent, leading to reduced quality of life and social isolation. Unveiling the genetic and environmental factors leading to age-related auditory disorders could suggest lifestyle and therapeutic interventions to slow auditory aging. In the following, we built the first machine learning-based hearing age predictor by training models to predict chronological age from hearing test results (root mean squared error=7.10±0.07 years; R-Squared=31.4±0.8%). We defined hearing age as the prediction outputted by the model on unseen samples, and accelerated auditory aging as the difference between a participant’s hearing age and age. We then performed a genome wide association study [GWAS] and found that accelerated hearing aging is 14.1±0.4% GWAS-heritable. -
An Alu Element-Based Model of Human Genome Instability George Wyndham Cook, Jr
Louisiana State University LSU Digital Commons LSU Doctoral Dissertations Graduate School 2013 An Alu element-based model of human genome instability George Wyndham Cook, Jr. Louisiana State University and Agricultural and Mechanical College, [email protected] Follow this and additional works at: https://digitalcommons.lsu.edu/gradschool_dissertations Recommended Citation Cook, Jr., George Wyndham, "An Alu element-based model of human genome instability" (2013). LSU Doctoral Dissertations. 2090. https://digitalcommons.lsu.edu/gradschool_dissertations/2090 This Dissertation is brought to you for free and open access by the Graduate School at LSU Digital Commons. It has been accepted for inclusion in LSU Doctoral Dissertations by an authorized graduate school editor of LSU Digital Commons. For more information, please [email protected]. AN ALU ELEMENT-BASED MODEL OF HUMAN GENOME INSTABILITY A Dissertation Submitted to the Graduate Faculty of the Louisiana State University and Agricultural and Mechanical College in partial fulfillment of the requirements for the degree of Doctor of Philosophy in The Department of Biological Sciences by George Wyndham Cook, Jr. B.S., University of Arkansas, 1975 May 2013 TABLE OF CONTENTS LIST OF TABLES ...................................................................................................... iii LIST OF FIGURES .................................................................................................... iv LIST OF ABBREVIATIONS ...................................................................................... -
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. -
The National Economic Burden of Rare Disease Study February 2021
Acknowledgements This study was sponsored by the EveryLife Foundation for Rare Diseases and made possible through the collaborative efforts of the national rare disease community and key stakeholders. The EveryLife Foundation thanks all those who shared their expertise and insights to provide invaluable input to the study including: the Lewin Group, the EveryLife Community Congress membership, the Technical Advisory Group for this study, leadership from the National Center for Advancing Translational Sciences (NCATS) at the National Institutes of Health (NIH), the Undiagnosed Diseases Network (UDN), the Little Hercules Foundation, the Rare Disease Legislative Advocates (RDLA) Advisory Committee, SmithSolve, and our study funders. Most especially, we thank the members of our rare disease patient and caregiver community who participated in this effort and have helped to transform their lived experience into quantifiable data. LEWIN GROUP PROJECT STAFF Grace Yang, MPA, MA, Vice President Inna Cintina, PhD, Senior Consultant Matt Zhou, BS, Research Consultant Daniel Emont, MPH, Research Consultant Janice Lin, BS, Consultant Samuel Kallman, BA, BS, Research Consultant EVERYLIFE FOUNDATION PROJECT STAFF Annie Kennedy, BS, Chief of Policy and Advocacy Julia Jenkins, BA, Executive Director Jamie Sullivan, MPH, Director of Policy TECHNICAL ADVISORY GROUP Annie Kennedy, BS, Chief of Policy & Advocacy, EveryLife Foundation for Rare Diseases Anne Pariser, MD, Director, Office of Rare Diseases Research, National Center for Advancing Translational Sciences (NCATS), National Institutes of Health Elisabeth M. Oehrlein, PhD, MS, Senior Director, Research and Programs, National Health Council Christina Hartman, Senior Director of Advocacy, The Assistance Fund Kathleen Stratton, National Academies of Science, Engineering and Medicine (NASEM) Steve Silvestri, Director, Government Affairs, Neurocrine Biosciences Inc. -
PLATFORM ABSTRACTS Abstract Abstract Numbers Numbers Tuesday, November 6 41
American Society of Human Genetics 62nd Annual Meeting November 6–10, 2012 San Francisco, California PLATFORM ABSTRACTS Abstract Abstract Numbers Numbers Tuesday, November 6 41. Genes Underlying Neurological Disease Room 134 #196–#204 2. 4:30–6:30pm: Plenary Abstract 42. Cancer Genetics III: Common Presentations Hall D #1–#6 Variants Ballroom 104 #205–#213 43. Genetics of Craniofacial and Wednesday, November 7 Musculoskeletal Disorders Room 124 #214–#222 10:30am–12:45 pm: Concurrent Platform Session A (11–19): 44. Tools for Phenotype Analysis Room 132 #223–#231 11. Genetics of Autism Spectrum 45. Therapy of Genetic Disorders Room 130 #232–#240 Disorders Hall D #7–#15 46. Pharmacogenetics: From Discovery 12. New Methods for Big Data Ballroom 103 #16–#24 to Implementation Room 123 #241–#249 13. Cancer Genetics I: Rare Variants Room 135 #25–#33 14. Quantitation and Measurement of Friday, November 9 Regulatory Oversight by the Cell Room 134 #34–#42 8:00am–10:15am: Concurrent Platform Session D (47–55): 15. New Loci for Obesity, Diabetes, and 47. Structural and Regulatory Genomic Related Traits Ballroom 104 #43–#51 Variation Hall D #250–#258 16. Neuromuscular Disease and 48. Neuropsychiatric Disorders Ballroom 103 #259–#267 Deafness Room 124 #52–#60 49. Common Variants, Rare Variants, 17. Chromosomes and Disease Room 132 #61–#69 and Everything in-Between Room 135 #268–#276 18. Prenatal and Perinatal Genetics Room 130 #70–#78 50. Population Genetics Genome-Wide Room 134 #277–#285 19. Vascular and Congenital Heart 51. Endless Forms Most Beautiful: Disease Room 123 #79–#87 Variant Discovery in Genomic Data Ballroom 104 #286–#294 52. -
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. -
Serum Cell-Free DNA Methylation of OPCML and HOXD9 As a Biomarker That May Aid in Differential Diagnosis Between Cholangiocarcin
Wasenang et al. Clinical Epigenetics (2019) 11:39 https://doi.org/10.1186/s13148-019-0634-0 RESEARCH Open Access Serum cell-free DNA methylation of OPCML and HOXD9 as a biomarker that may aid in differential diagnosis between cholangiocarcinoma and other biliary diseases Wiphawan Wasenang1,2, Ponlatham Chaiyarit3, Siriporn Proungvitaya1,4 and Temduang Limpaiboon1,4* Abstract Background: Cholangiocarcinoma (CCA) is a fatal cancer of the bile duct epithelial cell lining. The misdiagnosis of CCA and other biliary diseases may occur due to the similarity of clinical manifestations and blood tests resulting in inappropriate or delayed treatment. Thus, an accurate and less-invasive method for differentiating CCA from other biliary diseases is inevitable. Methods: We quantified methylation of OPCML, HOXA9,andHOXD9 in serum cell-free DNA (cfDNA) of CCA patients and other biliary diseases using methylation-sensitive high-resolution melting (MS-HRM). Their potency as differential biomarkers between CCA and other biliary diseases was also evaluated by using receiver operating characteristic (ROC) curves. Results: The significant difference of methylation levels of OPCML and HOXD9 was observed in serum cfDNA of CCA compared to other biliary diseases. Assessment of serum cfDNA methylation of OPCML and HOXD9 as differential biomarkers of CCA and other biliary diseases showed the area under curve (AUC) of 0.850 (0.759–0.941) for OPCML which sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were 80.00%, 90.00%, 88.88%, 81.81%, and 85.00%, respectively. The AUC of HOXD9 was 0.789 (0.686–0.892) with sensitivity, specificity, PPV, NPV, and accuracy of 67.50%, 90.00%, 87.09%, 73.46%, and 78.75%, respectively. -
Sema4 Noninvasive Prenatal Select
Sema4 Noninvasive Prenatal Select Noninvasive prenatal testing with targeted genome counting 2 Autosomal trisomies 5 Trisomy 21 (Down syndrome) 6 Trisomy 18 (Edwards syndrome) 7 Trisomy 13 (Patau syndrome) 8 Trisomy 16 9 Trisomy 22 9 Trisomy 15 10 Sex chromosome aneuploidies 12 Monosomy X (Turner syndrome) 13 XXX (Trisomy X) 14 XXY (Klinefelter syndrome) 14 XYY 15 Microdeletions 17 22q11.2 deletion 18 1p36 deletion 20 4p16 deletion (Wolf-Hirschhorn syndrome) 20 5p15 deletion (Cri-du-chat syndrome) 22 15q11.2-q13 deletion (Angelman syndrome) 22 15q11.2-q13 deletion (Prader-Willi syndrome) 24 11q23 deletion (Jacobsen Syndrome) 25 8q24 deletion (Langer-Giedion syndrome) 26 Turnaround time 27 Specimen and shipping requirements 27 2 Noninvasive prenatal testing with targeted genome counting Sema4’s Noninvasive Prenatal Testing (NIPT)- Targeted Genome Counting analyzes genetic information of cell-free DNA (cfDNA) through a simple maternal blood draw to determine the risk for common aneuploidies, sex chromosomal abnormalities, and microdeletions, in addition to fetal gender, as early as nine weeks gestation. The test uses paired-end next-generation sequencing technology to provide higher depth across targeted regions. It also uses a laboratory-specific statistical model to help reduce false positive and false negative rates. The test can be offered to all women with singleton, twins and triplet pregnancies, including egg donor. The conditions offered are shown in below tables. For multiple gestation pregnancies, screening of three conditions -
RD-Action Matchmaker – Summary of Disease Expertise Recorded Under
Summary of disease expertise recorded via RD-ACTION Matchmaker under each Thematic Grouping and EURORDIS Members’ Thematic Grouping Thematic Reported expertise of those completing the EURORDIS Member perspectives on Grouping matchmaker under each heading Grouping RD Thematically Rare Bone Achondroplasia/Hypochondroplasia Achondroplasia Amelia skeletal dysplasia’s including Achondroplasia/Growth hormone cleidocranial dysostosis, arthrogryposis deficiency/MPS/Turner Brachydactyly chondrodysplasia punctate Fibrous dysplasia of bone Collagenopathy and oncologic disease such as Fibrodysplasia ossificans progressive Li-Fraumeni syndrome Osteogenesis imperfecta Congenital hand and fore-foot conditions Sterno Costo Clavicular Hyperostosis Disorders of Sex Development Duchenne Muscular Dystrophy Ehlers –Danlos syndrome Fibrodysplasia Ossificans Progressiva Growth disorders Hypoparathyroidism Hypophosphatemic rickets & Nutritional Rickets Hypophosphatasia Jeune’s syndrome Limb reduction defects Madelung disease Metabolic Osteoporosis Multiple Hereditary Exostoses Osteogenesis imperfecta Osteoporosis Paediatric Osteoporosis Paget’s disease Phocomelia Pseudohypoparathyroidism Radial dysplasia Skeletal dysplasia Thanatophoric dwarfism Ulna dysplasia Rare Cancer and Adrenocortical tumours Acute monoblastic leukaemia Tumours Carcinoid tumours Brain tumour Craniopharyngioma Colon cancer, familial nonpolyposis Embryonal tumours of CNS Craniopharyngioma Ependymoma Desmoid disease Epithelial thymic tumours in -
Análise Integrativa De Perfis Transcricionais De Pacientes Com
UNIVERSIDADE DE SÃO PAULO FACULDADE DE MEDICINA DE RIBEIRÃO PRETO PROGRAMA DE PÓS-GRADUAÇÃO EM GENÉTICA ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas Ribeirão Preto – 2012 ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas Tese apresentada à Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo para obtenção do título de Doutor em Ciências. Área de Concentração: Genética Orientador: Prof. Dr. Eduardo Antonio Donadi Co-orientador: Prof. Dr. Geraldo A. S. Passos Ribeirão Preto – 2012 AUTORIZO A REPRODUÇÃO E DIVULGAÇÃO TOTAL OU PARCIAL DESTE TRABALHO, POR QUALQUER MEIO CONVENCIONAL OU ELETRÔNICO, PARA FINS DE ESTUDO E PESQUISA, DESDE QUE CITADA A FONTE. FICHA CATALOGRÁFICA Evangelista, Adriane Feijó Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas. Ribeirão Preto, 2012 192p. Tese de Doutorado apresentada à Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo. Área de Concentração: Genética. Orientador: Donadi, Eduardo Antonio Co-orientador: Passos, Geraldo A. 1. Expressão gênica – microarrays 2. Análise bioinformática por module maps 3. Diabetes mellitus tipo 1 4. Diabetes mellitus tipo 2 5. Diabetes mellitus gestacional FOLHA DE APROVAÇÃO ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas.