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CADASIL Testing
Lab Management Guidelines V1.0.2020 CADASIL Testing MOL.TS.144.A v1.0.2020 Introduction CADASIL testing is addressed by this guideline. Procedures addressed The inclusion of any procedure code in this table does not imply that the code is under management or requires prior authorization. Refer to the specific Health Plan's procedure code list for management requirements. Procedures addressed by this Procedure codes guideline NOTCH3 Known Familial Mutation 81403 Analysis NOTCH3 Targeted Sequencing 81406 NOTCH3 Deletion/Duplication Analysis 81479 What is CADASIL Definition CADASIL (Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy) is an adult-onset form of cerebrovascular disease. There are no generally accepted clinical diagnostic criteria for CADASIL and symptoms vary among affected individuals. Signs and symptoms Typical signs and symptoms include1,2,3 Transient ischemic attacks and ischemic stroke, occurs at a mean age of 47 years (age range 20-70 years), in most cases without conventional vascular risk factors cognitive disturbance, primarily affecting executive function, may start as early as age 35 years psychiatric or behavioral abnormalities migraine with aura, occurs with a mean age of onset of 30 years (age range 6-48 years), and Less common symptoms include: © 2020 eviCore healthcare. All Rights Reserved. 1 of 7 400 Buckwalter Place Boulevard, Bluffton, SC 29910 (800) 918-8924 www.eviCore.com Lab Management Guidelines V1.0.2020 recurrent seizures with onset in middle age, usually secondary to stroke acute encephalopathy, with a mean age of onset of 42 years Life expectancy for men with CADASIL is reduced by approximately five years and for women by 1 to 2 years.4 Diagnosis Brain Magnetic Resonance Imaging (MRI) findings include T2-signal-abnormalities in the white matter of the temporal pole and T2-signal-abnormalities in the external capsule and corpus callosum.1,2 CADASIL is suspected in an individual with the clinical signs and MRI findings. -
A Reciprocal Effort Towards Better Approaches for Drug Discovery
Acta Pharmacologica Sinica (2013) 34: 765–776 npg © 2013 CPS and SIMM All rights reserved 1671-4083/13 $32.00 www.nature.com/aps Review iPSCs and small molecules: a reciprocal effort towards better approaches for drug discovery Ru ZHANG1, Li-hong ZHANG2, Xin XIE1, 2, * 1Laboratory of Receptor-based Bio-medicine, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China; 2CAS Key Laboratory of Receptor Research, the National Center for Drug Screening, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China The revolutionary induced pluripotent stem cell (iPSC) technology provides a new path for cell replacement therapies and drug screen- ing. Patient-specific iPSCs and subsequent differentiated cells manifesting disease phenotypes will finally position human disease pathology at the core of drug discovery. Cells used to test the toxic effects of drugs can also be generated from normal iPSCs and pro- vide a much more accurate and cost-effective system than many animal models. Here, we highlight the recent progress in iPSC-based cell therapy, disease modeling and drug evaluations. In addition, we discuss the use of small molecule drugs to improve the genera- tion of iPSCs and understand the reprogramming mechanism. It is foreseeable that the interplay between iPSC technology and small molecule compounds will push forward the applications of iPSC-based therapy and screening systems in the real world and eventually revolutionize the methods used to treat diseases. Keywords: induced pluripotent stem cells (iPSCs); disease modeling; drug screening; toxicity evaluation; cell replacement therapy; small molecules; drug development Acta Pharmacologica Sinica (2013) 34: 765–776; doi: 10.1038/aps.2013.21; published online 22 Apr 2013 Introduction his/her own iPSCs[1–3]. -
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. -
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. -
Cadasil Pathogenesis, Clinical and Radiological Findings and Treatment
View and review Arq Neuropsiquiatr 2010;68(2):287-299 Cadasil Pathogenesis, clinical and radiological findings and treatment Charles André ABSTRACT Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is the most common genetic cause of ischemic strokes and a most important model for the study of subcortical vascular dementia. This unrelentlessly progressive disease affects many hundreds of families all over the world but is not well studied in Brazil. This manuscript reviews pathogenetic, clinical, radiological and therapeutic features of CADASIL. The causal mutations are now very well known, but the same can not be said about its intimate pathogenetic mechanisms. The variable clinical presentation should lead physicians to actively pursue the diagnosis in many settings and to more thouroughly investigate family history in first degree relatives. A rational approach to genetic testing is however needed. Treatment of CADASIL is still largely empiric. High- quality therapeutic studies involving medications and cognitive interventions are strongly needed in CADASIL. Key words: CADASIL, etiology, genetics, diagnosis, therapeutics. CADASIL: patogênese, achados clínicos e radiológicos e tratamento RESUMO CADASIL é a causa genética mais freqüente de infartos cerebrais e constitui modelo importante de estudo de demências vasculares subcorticais. De natureza inexoravelmente progressiva, afeta milhares de pessoas em todo o mundo. Sua importância é pouco reconhecida entre nós, o que nos levou à presente revisão dos principais aspectos patogenéticos, clínicos, neuroradiológicos e terapêuticos da doença. As mutações causais são hoje bem conhecidas, mas os mecanismos patogenéticos íntimos ainda permanecem misteriosos. A apresentação clínica variável deve fazer com que os médicos considerem o diagnóstico em vários contextos clínicos e investiguem de forma mais extensa que o usual a história familial deparentes de primeiro grau. -
Megalencephaly and Macrocephaly
277 Megalencephaly and Macrocephaly KellenD.Winden,MD,PhD1 Christopher J. Yuskaitis, MD, PhD1 Annapurna Poduri, MD, MPH2 1 Department of Neurology, Boston Children’s Hospital, Boston, Address for correspondence Annapurna Poduri, Epilepsy Genetics Massachusetts Program, Division of Epilepsy and Clinical Electrophysiology, 2 Epilepsy Genetics Program, Division of Epilepsy and Clinical Department of Neurology, Fegan 9, Boston Children’s Hospital, 300 Electrophysiology, Department of Neurology, Boston Children’s Longwood Avenue, Boston, MA 02115 Hospital, Boston, Massachusetts (e-mail: [email protected]). Semin Neurol 2015;35:277–287. Abstract Megalencephaly is a developmental disorder characterized by brain overgrowth secondary to increased size and/or numbers of neurons and glia. These disorders can be divided into metabolic and developmental categories based on their molecular etiologies. Metabolic megalencephalies are mostly caused by genetic defects in cellular metabolism, whereas developmental megalencephalies have recently been shown to be caused by alterations in signaling pathways that regulate neuronal replication, growth, and migration. These disorders often lead to epilepsy, developmental disabilities, and Keywords behavioral problems; specific disorders have associations with overgrowth or abnor- ► megalencephaly malities in other tissues. The molecular underpinnings of many of these disorders are ► hemimegalencephaly now understood, providing insight into how dysregulation of critical pathways leads to ► -
UC San Francisco Electronic Theses and Dissertations
UCSF UC San Francisco Electronic Theses and Dissertations Title Chemical genetic approaches to study protein kinase signaling pathways Permalink https://escholarship.org/uc/item/0sn1j4nk Author Hertz, Nicholas T. Publication Date 2013 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California Copyright 2013 by Nicholas T. Hertz ii Acknowledgements I would like to thank Kevan for his support, insight, encouragement and enthusiasm for science. I would also like to thank Al for all of his support and encouragement. My parents were instrumental in me getting to this point and I want to thank them for their continued support and my wife Janel for everything. Part of this thesis is a reproduction of material previously published, and contains contributions from collaborators listed therein. Chapter 1 is reproduced in part with permission from: Hertz, N.T., Wang, B.T., Allen, J.J., Zhang, C., Dar, A.C., Burlingame, A.L., and Shokat, K.M., Chemical genetic approach for kinase-substrate mapping by covalent capture of thiophosphopeptides and analysis by mass spectrometry, Current Protocols in Chemical Biology. 2010, February; 2:(15-36). Chapter 2 is reproduced in part with permission from: Ultanir, S.K.*, Hertz, N.T.*, Li, G., Ge1, W.P., Burlingame, A.L., Pleasure, S.J., Shokat, K.M., Jan, L.Y., and Jan, Y., Chemical genetic identification of NDR1/2 kinase substrates AAK1 and Rabin8 uncovers their roles in controlling dendrite arborization and synapse maturation. Neuron. 2012, March 22; 73:1127-42. Chapter 3 is reproduced in part with permission from: Hengeveld, R.C.C.*, Hertz, N.T.*, Vromans, M.J.M., Zhang, C., Burlingame, A.L., Shokat, K.M., Lens, S.M.A., Development of a chemical genetic approach for human Aurora B kinase identifies novel substrates of the chromosomal passenger complex. -
Cardiomyopathy Precision Panel Overview Indications
Cardiomyopathy Precision Panel Overview Cardiomyopathies are a group of conditions with a strong genetic background that structurally hinder the heart to pump out blood to the rest of the body due to weakness in the heart muscles. These diseases affect individuals of all ages and can lead to heart failure and sudden cardiac death. If there is a family history of cardiomyopathy it is strongly recommended to undergo genetic testing to be aware of the family risk, personal risk, and treatment options. Most types of cardiomyopathies are inherited in a dominant manner, which means that one altered copy of the gene is enough for the disease to present in an individual. The symptoms of cardiomyopathy are variable, and these diseases can present in different ways. There are 5 types of cardiomyopathies, the most common being hypertrophic cardiomyopathy: 1. Hypertrophic cardiomyopathy (HCM) 2. Dilated cardiomyopathy (DCM) 3. Restrictive cardiomyopathy (RCM) 4. Arrhythmogenic Right Ventricular Cardiomyopathy (ARVC) 5. Isolated Left Ventricular Non-Compaction Cardiomyopathy (LVNC). The Igenomix Cardiomyopathy Precision Panel serves as a diagnostic and tool ultimately leading to a better management and prognosis of the disease. It provides a comprehensive analysis of the genes involved in this disease using next-generation sequencing (NGS) to fully understand the spectrum of relevant genes. Indications The Igenomix Cardiomyopathy Precision Panel is indicated in those cases where there is a clinical suspicion of cardiomyopathy with or without the following manifestations: - Shortness of breath - Fatigue - Arrythmia (abnormal heart rhythm) - Family history of arrhythmia - Abnormal scans - Ventricular tachycardia - Ventricular fibrillation - Chest Pain - Dizziness - Sudden cardiac death in the family 1 Clinical Utility The clinical utility of this panel is: - The genetic and molecular diagnosis for an accurate clinical diagnosis of a patient with personal or family history of cardiomyopathy, channelopathy or sudden cardiac death. -
Prevalence and Incidence of Rare Diseases: Bibliographic Data
Number 1 | January 2019 Prevalence and incidence of rare diseases: Bibliographic data Prevalence, incidence or number of published cases listed by diseases (in alphabetical order) www.orpha.net www.orphadata.org If a range of national data is available, the average is Methodology calculated to estimate the worldwide or European prevalence or incidence. When a range of data sources is available, the most Orphanet carries out a systematic survey of literature in recent data source that meets a certain number of quality order to estimate the prevalence and incidence of rare criteria is favoured (registries, meta-analyses, diseases. This study aims to collect new data regarding population-based studies, large cohorts studies). point prevalence, birth prevalence and incidence, and to update already published data according to new For congenital diseases, the prevalence is estimated, so scientific studies or other available data. that: Prevalence = birth prevalence x (patient life This data is presented in the following reports published expectancy/general population life expectancy). biannually: When only incidence data is documented, the prevalence is estimated when possible, so that : • Prevalence, incidence or number of published cases listed by diseases (in alphabetical order); Prevalence = incidence x disease mean duration. • Diseases listed by decreasing prevalence, incidence When neither prevalence nor incidence data is available, or number of published cases; which is the case for very rare diseases, the number of cases or families documented in the medical literature is Data collection provided. A number of different sources are used : Limitations of the study • Registries (RARECARE, EUROCAT, etc) ; The prevalence and incidence data presented in this report are only estimations and cannot be considered to • National/international health institutes and agencies be absolutely correct. -
1714 Gene Comprehensive Cancer Panel Enriched for Clinically Actionable Genes with Additional Biologically Relevant Genes 400-500X Average Coverage on Tumor
xO GENE PANEL 1714 gene comprehensive cancer panel enriched for clinically actionable genes with additional biologically relevant genes 400-500x average coverage on tumor Genes A-C Genes D-F Genes G-I Genes J-L AATK ATAD2B BTG1 CDH7 CREM DACH1 EPHA1 FES G6PC3 HGF IL18RAP JADE1 LMO1 ABCA1 ATF1 BTG2 CDK1 CRHR1 DACH2 EPHA2 FEV G6PD HIF1A IL1R1 JAK1 LMO2 ABCB1 ATM BTG3 CDK10 CRK DAXX EPHA3 FGF1 GAB1 HIF1AN IL1R2 JAK2 LMO7 ABCB11 ATR BTK CDK11A CRKL DBH EPHA4 FGF10 GAB2 HIST1H1E IL1RAP JAK3 LMTK2 ABCB4 ATRX BTRC CDK11B CRLF2 DCC EPHA5 FGF11 GABPA HIST1H3B IL20RA JARID2 LMTK3 ABCC1 AURKA BUB1 CDK12 CRTC1 DCUN1D1 EPHA6 FGF12 GALNT12 HIST1H4E IL20RB JAZF1 LPHN2 ABCC2 AURKB BUB1B CDK13 CRTC2 DCUN1D2 EPHA7 FGF13 GATA1 HLA-A IL21R JMJD1C LPHN3 ABCG1 AURKC BUB3 CDK14 CRTC3 DDB2 EPHA8 FGF14 GATA2 HLA-B IL22RA1 JMJD4 LPP ABCG2 AXIN1 C11orf30 CDK15 CSF1 DDIT3 EPHB1 FGF16 GATA3 HLF IL22RA2 JMJD6 LRP1B ABI1 AXIN2 CACNA1C CDK16 CSF1R DDR1 EPHB2 FGF17 GATA5 HLTF IL23R JMJD7 LRP5 ABL1 AXL CACNA1S CDK17 CSF2RA DDR2 EPHB3 FGF18 GATA6 HMGA1 IL2RA JMJD8 LRP6 ABL2 B2M CACNB2 CDK18 CSF2RB DDX3X EPHB4 FGF19 GDNF HMGA2 IL2RB JUN LRRK2 ACE BABAM1 CADM2 CDK19 CSF3R DDX5 EPHB6 FGF2 GFI1 HMGCR IL2RG JUNB LSM1 ACSL6 BACH1 CALR CDK2 CSK DDX6 EPOR FGF20 GFI1B HNF1A IL3 JUND LTK ACTA2 BACH2 CAMTA1 CDK20 CSNK1D DEK ERBB2 FGF21 GFRA4 HNF1B IL3RA JUP LYL1 ACTC1 BAG4 CAPRIN2 CDK3 CSNK1E DHFR ERBB3 FGF22 GGCX HNRNPA3 IL4R KAT2A LYN ACVR1 BAI3 CARD10 CDK4 CTCF DHH ERBB4 FGF23 GHR HOXA10 IL5RA KAT2B LZTR1 ACVR1B BAP1 CARD11 CDK5 CTCFL DIAPH1 ERCC1 FGF3 GID4 HOXA11 IL6R KAT5 ACVR2A -
Whole Exome Sequencing Gene Package Intellectual Disability, Version 9.1, 31-1-2020
Whole Exome Sequencing Gene package Intellectual disability, version 9.1, 31-1-2020 Technical information DNA was enriched using Agilent SureSelect DNA + SureSelect OneSeq 300kb CNV Backbone + Human All Exon V7 capture and paired-end sequenced on the Illumina platform (outsourced). The aim is to obtain 10 Giga base pairs per exome with a mapped fraction of 0.99. The average coverage of the exome is ~50x. Duplicate and non-unique reads are excluded. Data are demultiplexed with bcl2fastq Conversion Software from Illumina. Reads are mapped to the genome using the BWA-MEM algorithm (reference: http://bio-bwa.sourceforge.net/). Variant detection is performed by the Genome Analysis Toolkit HaplotypeCaller (reference: http://www.broadinstitute.org/gatk/). The detected variants are filtered and annotated with Cartagenia software and classified with Alamut Visual. It is not excluded that pathogenic mutations are being missed using this technology. At this moment, there is not enough information about the sensitivity of this technique with respect to the detection of deletions and duplications of more than 5 nucleotides and of somatic mosaic mutations (all types of sequence changes). HGNC approved Phenotype description including OMIM phenotype ID(s) OMIM median depth % covered % covered % covered gene symbol gene ID >10x >20x >30x A2ML1 {Otitis media, susceptibility to}, 166760 610627 66 100 100 96 AARS1 Charcot-Marie-Tooth disease, axonal, type 2N, 613287 601065 63 100 97 90 Epileptic encephalopathy, early infantile, 29, 616339 AASS Hyperlysinemia, -
Insurance and Advance Pay Test Requisition
Insurance and Advance Pay Test Requisition (2021) For Specimen Collection Service, Please Fax this Test Requisition to 1.610.271.6085 Client Services is available Monday through Friday from 8:30 AM to 9:00 PM EST at 1.800.394.4493, option 2 Patient Information Patient Name Patient ID# (if available) Date of Birth Sex designated at birth: 9 Male 9 Female Street address City, State, Zip Mobile phone #1 Other Phone #2 Patient email Language spoken if other than English Test and Specimen Information Consult test list for test code and name Test Code: Test Name: Test Code: Test Name: 9 Check if more than 2 tests are ordered. Additional tests should be checked off within the test list ICD-10 Codes (required for billing insurance): Clinical diagnosis: Age at Initial Presentation: Ancestral Background (check all that apply): 9 African 9 Asian: East 9 Asian: Southeast 9 Central/South American 9 Hispanic 9 Native American 9 Ashkenazi Jewish 9 Asian: Indian 9 Caribbean 9 European 9 Middle Eastern 9 Pacific Islander Other: Indications for genetic testing (please check one): 9 Diagnostic (symptomatic) 9 Predictive (asymptomatic) 9 Prenatal* 9 Carrier 9 Family testing/single site Relationship to Proband: If performed at Athena, provide relative’s accession # . If performed at another lab, a copy of the relative’s report is required. Please attach detailed medical records and family history information Specimen Type: Date sample obtained: __________ /__________ /__________ 9 Whole Blood 9 Serum 9 CSF 9 Muscle 9 CVS: Cultured 9 Amniotic Fluid: Cultured 9 Saliva (Not available for all tests) 9 DNA** - tissue source: Concentration ug/ml Was DNA extracted at a CLIA-certified laboratory or a laboratory meeting equivalent requirements (as determined by CAP and/or CMS)? 9 Yes 9 No 9 Other*: If not collected same day as shipped, how was sample stored? 9 Room temp 9 Refrigerated 9 Frozen (-20) 9 Frozen (-80) History of blood transfusion? 9 Yes 9 No Most recent transfusion: __________ /__________ /__________ *Please contact us at 1.800.394.4493, option 2 prior to sending specimens.