Whole Exome Sequencing Gene Package Multiple Congenital Anomaly, Version 8.1, 31-1-2020
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Chapter 7: Monogenic Forms of Diabetes
CHAPTER 7 MONOGENIC FORMS OF DIABETES Mark A. Sperling, MD, and Abhimanyu Garg, MD Dr. Mark A. Sperling is Emeritus Professor and Chair, University of Pittsburgh, Department of Pediatrics, Children’s Hospital of Pittsburgh of UPMC, Pittsburgh, PA. Dr. Abhimanyu Garg is Professor of Internal Medicine and Chief of the Division of Nutrition and Metabolic Diseases at University of Texas Southwestern Medical Center, Dallas, TX. SUMMARY Types 1 and 2 diabetes have multiple and complex genetic influences that interact with environmental triggers, such as viral infections or nutritional excesses, to result in their respective phenotypes: young, lean, and insulin-dependence for type 1 diabetes patients or older, overweight, and often manageable by lifestyle interventions and oral medications for type 2 diabetes patients. A small subset of patients, comprising ~2%–3% of all those diagnosed with diabetes, may have characteristics of either type 1 or type 2 diabetes but have single gene defects that interfere with insulin production, secretion, or action, resulting in clinical diabetes. These types of diabetes are known as MODY, originally defined as maturity-onset diabetes of youth, and severe early-onset forms, such as neonatal diabetes mellitus (NDM). Defects in genes involved in adipocyte development, differentiation, and death pathways cause lipodystrophy syndromes, which are also associated with insulin resistance and diabetes. Although these syndromes are considered rare, more awareness of these disorders and increased availability of genetic testing in clinical and research laboratories, as well as growing use of next generation, whole genome, or exome sequencing for clinically challenging phenotypes, are resulting in increased recognition. A correct diagnosis of MODY, NDM, or lipodystrophy syndromes has profound implications for treatment, genetic counseling, and prognosis. -
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SAN TA C RUZ BI OTEC HNOL OG Y, INC . DIP2A (L-16): sc-67555 BACKGROUND APPLICATIONS DIP2A (Disco-interacting protein 2 homolog A), also known as DIP2, is a 1,571 DIP2A (L-16) is recommended for detection of DIP2A of human origin by amino acid nuclear protein. It is one of three human homologs (DIP2A, DIP2B Western Blotting (starting dilution 1:200, dilution range 1:100-1:1000), and DIP2C) of the Drosophila dip2 (disconnected-interacting protein 2) protein. immunoprecipitation [1-2 µg per 100-500 µg of total protein (1 ml of cell In Drosophila , dip2 interacts with disco, a protein required for neuronal con - lysate)], immunofluorescence (starting dilution 1:50, dilution range 1:50- nections in the visual systems of larvae and adults. The closest vertebrate 1:500) and solid phase ELISA (starting dilution 1:30, dilution range 1:30- homologs to disco are the basonuclin genes. In mice, DIP2 homologs show 1:3000). restricted expression to the brain. This suggests that, similar to the function DIP2A (L-16) is also recommended for detection of DIP2A, also designated of Drosphila dip2, vertebrate DIP2 homologs may play a role in the develop - Disco-interacting protein 2 homolog A, in additional species, including ment of the nervous system. Expressed ubiquitously with highest expression canine. in the brain, DIP2A is thought to function in signaling throughout the central nervous system by providing positional clues for axon patterning and pathfind - Suitable for use as control antibody for DIP2A siRNA (h): sc-62212, DIP2A ing . Four isoforms of DIP2A exist due to alternative splicing events. -
Inherited Cerebellar Ataxia in Childhood: a Pattern-Recognition Approach Using Brain MRI
REVIEW ARTICLE Inherited Cerebellar Ataxia in Childhood: A Pattern-Recognition Approach Using Brain MRI L. Vedolin, G. Gonzalez, C.F. Souza, C. Lourenc¸o, and A.J. Barkovich ABSTRACT SUMMARY: Ataxia is the principal symptom of many common neurologic diseases in childhood. Ataxias caused by dysfunction of the cerebellum occur in acute, intermittent, and progressive disorders. Most of the chronic progressive processes are secondary to degen- erative and metabolic diseases. In addition, congenital malformation of the midbrain and hindbrain can also be present, with posterior fossa symptoms related to ataxia. Brain MR imaging is the most accurate imaging technique to investigate these patients, and imaging abnormalities include size, shape, and/or signal of the brain stem and/or cerebellum. Supratentorial and cord lesions are also common. This review will discuss a pattern-recognition approach to inherited cerebellar ataxia in childhood. The purpose is to provide a comprehensive discussion that ultimately could help neuroradiologists better manage this important topic in pediatric neurology. ABBREVIATIONS: AR ϭ autosomal recessive; CAC ϭ cerebellar ataxia in childhood; 4H ϭ hypomyelination with hypogonadotropic hypogonadism and hypodon- tia; JSRD ϭ Joubert syndrome and related disorders; OPHN1 ϭ oligophrenin-1 taxia is an inability to coordinate voluntary muscle move- plastic/paraneoplastic disorders, immune-mediated/demyelinat- Aments that cannot be attributed to weakness or involuntary ing disorders, and drugs/toxins (antiepileptic medications, -
Prioritization of Variants Detected by Next Generation Sequencing According to the Mutation Tolerance and Mutational Architecture of the Corresponding Genes
International Journal of Molecular Sciences Review Prioritization of Variants Detected by Next Generation Sequencing According to the Mutation Tolerance and Mutational Architecture of the Corresponding Genes Iria Roca, Ana Fernández-Marmiesse, Sofía Gouveia, Marta Segovia and María L. Couce * Unit of Diagnosis and Treatment of Congenital Metabolic Diseases, Department of Pediatrics, Hospital Clínico Universitario de Santiago de Compostela, 15706 Santiago de Compostela, Spain; [email protected] (I.R.); [email protected] (A.F.-M.); sofi[email protected] (S.G.); [email protected] (M.S.) * Correspondence: [email protected]; Tel.: +34-981-950-102 Received: 3 April 2018; Accepted: 23 May 2018; Published: 27 May 2018 Abstract: The biggest challenge geneticists face when applying next-generation sequencing technology to the diagnosis of rare diseases is determining which rare variants, from the dozens or hundreds detected, are potentially implicated in the patient’s phenotype. Thus, variant prioritization is an essential step in the process of rare disease diagnosis. In addition to conducting the usual in-silico analyses to predict variant pathogenicity (based on nucleotide/amino-acid conservation and the differences between the physicochemical features of the amino-acid change), three important concepts should be borne in mind. The first is the “mutation tolerance” of the genes in which variants are located. This describes the susceptibility of a given gene to any functional mutation and depends on the strength of purifying selection acting against it. The second is the “mutational architecture” of each gene. This describes the type and location of mutations previously identified in the gene, and their association with different phenotypes or degrees of severity. -
Report of the Expert Committee on the Diagnosis and Classification Of
COMMITTEE REPORT Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus THE EXPERT COMMITTEE ON THE DIAGNOSIS AND CLASSIFICATION OF DIABETES MELLITUS* he current classification and diagno- nosis of diabetes were warranted. The in insulin secretion, insulin action, or sis of diabetes used in the U.S. was Committee met on multiple occasions both. The chronic hyperglycemia of dia- T developed by the National Diabetes and widely circulated a draft report of betes is associated with long-term dam- Data Group (NDDG) and published in their findings and preliminary recom- age, dysfunction, and failure of various 1979 (1). The impetus for the classifica- mendations to the international diabe- organs, especially the eyes, kidneys, tion and diagnosis scheme proposed then tes community. Based on the numerous nerves, heart, and blood vessels. holds true today. That is, comments and suggestions received, in- Several pathogenic processes are in- cluding the opportunity to review unpub- volved in the development of diabetes. the growth of knowledge regarding the eti- lished data in detail, the Committee These range from autoimmune destruc- ology and pathogenesis of diabetes has led discussed and revised numerous drafts of tion of the -cells of the pancreas with many individuals and groups in the diabe- a manuscript that culminated in this pub- consequent insulin deficiency to abnor- tes community to express the need for a lished document. malities that result in resistance to insulin revision of the nomenclature, diagnostic This report is divided into four sec- action. The basis of the abnormalities in criteria, and classification of diabetes. -
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. -
Divergent Genes in Gerbils: Prevalence, Relation to GC-Biased Substitution, and Phenotypic Relevance Yichen Dai, Rodrigo Pracana and Peter W
Dai et al. BMC Evolutionary Biology (2020) 20:134 https://doi.org/10.1186/s12862-020-01696-3 RESEARCH ARTICLE Open Access Divergent genes in gerbils: prevalence, relation to GC-biased substitution, and phenotypic relevance Yichen Dai, Rodrigo Pracana and Peter W. H. Holland* Abstract Background: Two gerbil species, sand rat (Psammomys obesus) and Mongolian jird (Meriones unguiculatus), can become obese and show signs of metabolic dysregulation when maintained on standard laboratory diets. The genetic basis of this phenotype is unknown. Recently, genome sequencing has uncovered very unusual regions of high guanine and cytosine (GC) content scattered across the sand rat genome, most likely generated by extreme and localized biased gene conversion. A key pancreatic transcription factor PDX1 is encoded by a gene in the most extreme GC-rich region, is remarkably divergent and exhibits altered biochemical properties. Here, we ask if gerbils have proteins in addition to PDX1 that are aberrantly divergent in amino acid sequence, whether they have also become divergent due to GC-biased nucleotide changes, and whether these proteins could plausibly be connected to metabolic dysfunction exhibited by gerbils. Results: We analyzed ~ 10,000 proteins with 1-to-1 orthologues in human and rodents and identified 50 proteins that accumulated unusually high levels of amino acid change in the sand rat and 41 in Mongolian jird. We show that more than half of the aberrantly divergent proteins are associated with GC biased nucleotide change and many are in previously defined high GC regions. We highlight four aberrantly divergent gerbil proteins, PDX1, INSR, MEDAG and SPP1, that may plausibly be associated with dietary metabolism. -
Genes in Eyecare Geneseyedoc 3 W.M
Genes in Eyecare geneseyedoc 3 W.M. Lyle and T.D. Williams 15 Mar 04 This information has been gathered from several sources; however, the principal source is V. A. McKusick’s Mendelian Inheritance in Man on CD-ROM. Baltimore, Johns Hopkins University Press, 1998. Other sources include McKusick’s, Mendelian Inheritance in Man. Catalogs of Human Genes and Genetic Disorders. Baltimore. Johns Hopkins University Press 1998 (12th edition). http://www.ncbi.nlm.nih.gov/Omim See also S.P.Daiger, L.S. Sullivan, and B.J.F. Rossiter Ret Net http://www.sph.uth.tmc.edu/Retnet disease.htm/. Also E.I. Traboulsi’s, Genetic Diseases of the Eye, New York, Oxford University Press, 1998. And Genetics in Primary Eyecare and Clinical Medicine by M.R. Seashore and R.S.Wappner, Appleton and Lange 1996. M. Ridley’s book Genome published in 2000 by Perennial provides additional information. Ridley estimates that we have 60,000 to 80,000 genes. See also R.M. Henig’s book The Monk in the Garden: The Lost and Found Genius of Gregor Mendel, published by Houghton Mifflin in 2001 which tells about the Father of Genetics. The 3rd edition of F. H. Roy’s book Ocular Syndromes and Systemic Diseases published by Lippincott Williams & Wilkins in 2002 facilitates differential diagnosis. Additional information is provided in D. Pavan-Langston’s Manual of Ocular Diagnosis and Therapy (5th edition) published by Lippincott Williams & Wilkins in 2002. M.A. Foote wrote Basic Human Genetics for Medical Writers in the AMWA Journal 2002;17:7-17. A compilation such as this might suggest that one gene = one disease. -
Lamin A/C Cardiomyopathy: Implications for Treatment
Current Cardiology Reports (2019) 21:160 https://doi.org/10.1007/s11886-019-1224-7 MYOCARDIAL DISEASE (A ABBATE AND G SINAGRA, SECTION EDITORS) Lamin A/C Cardiomyopathy: Implications for Treatment Suet Nee Chen1 & Orfeo Sbaizero1,2 & Matthew R. G. Taylor1 & Luisa Mestroni1 # Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract Purpose of Review The purpose of this review is to provide an update on lamin A/C (LMNA)-related cardiomyopathy and discuss the current recommendations and progress in the management of this disease. LMNA-related cardiomyopathy, an inherited autosomal dominant disease, is one of the most common causes of dilated cardiomyopathy and is characterized by steady progression toward heart failure and high risks of arrhythmias and sudden cardiac death. Recent Findings We discuss recent advances in the understanding of the molecular mechanisms of the disease including altered cell biomechanics, which may represent novel therapeutic targets to advance the current management approach, which relies on standard heart failure recommendations. Future therapeutic approaches include repurposed molecularly directed drugs, siRNA- based gene silencing, and genome editing. Summary LMNA-related cardiomyopathy is the focus of active in vitro and in vivo research, which is expected to generate novel biomarkers and identify new therapeutic targets. LMNA-related cardiomyopathy trials are currently underway. Keywords Lamin A/C gene . Laminopathy . Heart failure . Arrhythmias . Mechanotransduction . P53 . CRISPR–Cas9 therapy Introduction functions, including maintaining nuclear structural integrity, regulating gene expression, mechanosensing, and Mutations in the lamin A/C gene (LMNA)causelaminopathies, mechanotransduction through the lamina-associated proteins a heterogeneous group of inherited disorders including muscu- [6–11]. -
Loss of DIP2C in RKO Cells Stimulates Changes in DNA
Larsson et al. BMC Cancer (2017) 17:487 DOI 10.1186/s12885-017-3472-5 RESEARCH ARTICLE Open Access Loss of DIP2C in RKO cells stimulates changes in DNA methylation and epithelial- mesenchymal transition Chatarina Larsson1, Muhammad Akhtar Ali1,2, Tatjana Pandzic1, Anders M. Lindroth3, Liqun He1,4 and Tobias Sjöblom1* Abstract Background: The disco-interacting protein 2 homolog C (DIP2C) gene is an uncharacterized gene found mutated in a subset of breast and lung cancers. To understand the role of DIP2C in tumour development we studied the gene in human cancer cells. Methods: We engineered human DIP2C knockout cells by genome editing in cancer cells. The growth properties of the engineered cells were characterised and transcriptome and methylation analyses were carried out to identify pathways deregulated by inactivation of DIP2C. Effects on cell death pathways and epithelial-mesenchymal transition traits were studied based on the results from expression profiling. Results: Knockout of DIP2C in RKO cells resulted in cell enlargement and growth retardation. Expression profiling revealed 780 genes for which the expression level was affected by the loss of DIP2C, including the tumour-suppressor encoding CDKN2A gene, the epithelial-mesenchymal transition (EMT) regulator-encoding ZEB1,andCD44 and CD24 that encode breast cancer stem cell markers. Analysis of DNA methylation showed more than 30,000 sites affected by differential methylation, the majority of which were hypomethylated following loss of DIP2C. Changes in DNA methylation at promoter regions were strongly correlated to changes in gene expression, and genes involved with EMT and cell death were enriched among the differentially regulated genes. -
Ophthalmology
Ophthalmology Information for health professionals MEDICAL GENETIC TESTING FOR OPHTHALMOLOGY Recent technologies, in particularly Next Generation Sequencing (NGS), allows fast, accurate and valuable diagnostic tests. For Ophthalmology, CGC Genetics has an extensive list of medical genetic tests with clinical integration of results by our Medical Geneticists. 1. EXOME SEQUENCING: Exome Sequencing is a very efficient strategy to study most exons of a patient’s genome, unraveling mutations associated with specific disorders or phenotypes. With this diagnostic strategy, patients can be studied with a significantly reduced turnaround time and cost. CGC Genetics has available 2 options for Exome Sequencing: • Whole Exome Sequencing (WES), which analyzes the entire exome (about 20 000 genes); • Disease Exome by CGC Genetics, which analyzes about 6 000 clinically-relevant genes. Any of these can be performed in the index case or in a Trio. 2. NGS PANELS For NGS panels, several genes associated with the same phenotype are simultaneously sequenced. These panels provide increased diagnostic capability with a significantly reduced turnaround time and cost. CGC Genetics has several NGS panels for Ophthalmology that are constantly updated (www.cgcgenetics.com). Any gene studied in exome or NGS panel can also be individually sequenced and analyzed for deletion/duplication events. 3. EXPERTISE IN MEDICAL GENETICS CGC Genetics has Medical Geneticists specialized in genetic counseling for ophthalmological diseases who may advice in choosing the most appropriate -
Neuropathology Category Code List
Neuropathology Page 1 of 27 Neuropathology Major Category Code Headings Revised 10/2018 1 General neuroanatomy, pathology, and staining 65000 2 Developmental neuropathology, NOS 65400 3 Epilepsy 66230 4 Vascular disorders 66300 5 Trauma 66600 6 Infectious/inflammatory disease 66750 7 Demyelinating diseases 67200 8 Complications of systemic disorders 67300 9 Aging and neurodegenerative diseases 68000 10 Prion diseases 68400 11 Neoplasms 68500 12 Skeletal Muscle 69500 13 Peripheral Nerve 69800 14 Ophthalmic pathology 69910 Neuropathology Page 2 of 27 Neuropathology 1 General neuroanatomy, pathology, and staining 65000 A Neuroanatomy, NOS 65010 1 Neocortex 65011 2 White matter 65012 3 Entorhinal cortex/hippocampus 65013 4 Deep (basal) nuclei 65014 5 Brain stem 65015 6 Cerebellum 65016 7 Spinal cord 65017 8 Pituitary 65018 9 Pineal 65019 10 Tracts 65020 11 Vascular supply 65021 12 Notochord 65022 B Cell types 65030 1 Neurons 65031 2 Astrocytes 65032 3 Oligodendroglia 65033 4 Ependyma 65034 5 Microglia and mononuclear cells 65035 6 Choroid plexus 65036 7 Meninges 65037 8 Blood vessels 65038 C Cerebrospinal fluid 65045 D Pathologic responses in neurons and axons 65050 1 Axonal degeneration/spheroid/reaction 65051 2 Central chromatolysis 65052 3 Tract degeneration 65053 4 Swollen/ballooned neurons 65054 5 Trans-synaptic neuronal degeneration 65055 6 Olivary hypertrophy 65056 7 Acute ischemic (hypoxic) cell change 65057 8 Apoptosis 65058 9 Protein aggregation 65059 10 Protein degradation/ubiquitin pathway 65060 E Neuronal nuclear inclusions 65100