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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. -
SRC Antibody - N-Terminal Region (ARP32476 P050) Data Sheet
SRC antibody - N-terminal region (ARP32476_P050) Data Sheet Product Number ARP32476_P050 Product Name SRC antibody - N-terminal region (ARP32476_P050) Size 50ug Gene Symbol SRC Alias Symbols ASV; SRC1; c-SRC; p60-Src Nucleotide Accession# NM_005417 Protein Size (# AA) 536 amino acids Molecular Weight 60kDa Product Format Lyophilized powder NCBI Gene Id 6714 Host Rabbit Clonality Polyclonal Official Gene Full Name V-src sarcoma (Schmidt-Ruppin A-2) viral oncogene homolog (avian) Gene Family SH2D This is a rabbit polyclonal antibody against SRC. It was validated on Western Blot by Aviva Systems Biology. At Aviva Systems Biology we manufacture rabbit polyclonal antibodies on a large scale (200-1000 Description products/month) of high throughput manner. Our antibodies are peptide based and protein family oriented. We usually provide antibodies covering each member of a whole protein family of your interest. We also use our best efforts to provide you antibodies recognize various epitopes of a target protein. For availability of antibody needed for your experiment, please inquire (). Peptide Sequence Synthetic peptide located within the following region: QTPSKPASADGHRGPSAAFAPAAAEPKLFGGFNSSDTVTSPQRAGPLAGG This gene is highly similar to the v-src gene of Rous sarcoma virus. This proto-oncogene may play a role in the Description of Target regulation of embryonic development and cell growth. SRC protein is a tyrosine-protein kinase whose activity can be inhibited by phosphorylation by c-SRC kinase. Mutations in this gene could be involved in the -
Targeted Genes and Methodology Details for Neuromuscular Genetic Panels
Targeted Genes and Methodology Details for Neuromuscular Genetic Panels Reference transcripts based on build GRCh37 (hg19) interrogated by Neuromuscular Genetic Panels Next-generation sequencing (NGS) and/or Sanger sequencing is performed Motor Neuron Disease Panel to test for the presence of a mutation in these genes. Gene GenBank Accession Number Regions of homology, high GC-rich content, and repetitive sequences may ALS2 NM_020919 not provide accurate sequence. Therefore, all reported alterations detected ANG NM_001145 by NGS are confirmed by an independent reference method based on laboratory developed criteria. However, this does not rule out the possibility CHMP2B NM_014043 of a false-negative result in these regions. ERBB4 NM_005235 Sanger sequencing is used to confirm alterations detected by NGS when FIG4 NM_014845 appropriate.(Unpublished Mayo method) FUS NM_004960 HNRNPA1 NM_031157 OPTN NM_021980 PFN1 NM_005022 SETX NM_015046 SIGMAR1 NM_005866 SOD1 NM_000454 SQSTM1 NM_003900 TARDBP NM_007375 UBQLN2 NM_013444 VAPB NM_004738 VCP NM_007126 ©2018 Mayo Foundation for Medical Education and Research Page 1 of 14 MC4091-83rev1018 Muscular Dystrophy Panel Muscular Dystrophy Panel Gene GenBank Accession Number Gene GenBank Accession Number ACTA1 NM_001100 LMNA NM_170707 ANO5 NM_213599 LPIN1 NM_145693 B3GALNT2 NM_152490 MATR3 NM_199189 B4GAT1 NM_006876 MYH2 NM_017534 BAG3 NM_004281 MYH7 NM_000257 BIN1 NM_139343 MYOT NM_006790 BVES NM_007073 NEB NM_004543 CAPN3 NM_000070 PLEC NM_000445 CAV3 NM_033337 POMGNT1 NM_017739 CAVIN1 NM_012232 POMGNT2 -
Blueprint Genetics ENO3 Single Gene Test
ENO3 single gene test Test code: S00654 Phenotype information Glycogen storage disease Panels that include the ENO3 gene Glycogen Storage Disorder Panel Comprehensive Metabolism Panel Hypoglycemia, Hyperinsulinism and Ketone Metabolism Panel Metabolic Myopathy and Rhabdomyolysis Panel Test Strengths The strengths of this test include: CAP accredited laboratory CLIA-certified personnel performing clinical testing in a CLIA-certified laboratory Powerful sequencing technologies, advanced target enrichment methods and precision bioinformatics pipelines ensure superior analytical performance Careful construction of clinically effective and scientifically justified gene panels Our Nucleus online portal providing transparent and easy access to quality and performance data at the patient level Our publicly available analytic validation demonstrating complete details of test performance ~2,000 non-coding disease causing variants in our clinical grade NGS assay for panels (please see ‘Non-coding disease causing variants covered by this test’) Our rigorous variant classification scheme Our systematic clinical interpretation workflow using proprietary software enabling accurate and traceable processing of NGS data Our comprehensive clinical statements Test Limitations This test does not detect the following: Complex inversions Gene conversions Balanced translocations Mitochondrial DNA variants Repeat expansion disorders unless specifically mentioned Non-coding variants deeper than ±20 base pairs from exon-intron boundary unless otherwise indicated (please see above non-coding variants covered by the test). This test may not reliably detect the following: Low level mosaicism (variant with a minor allele fraction of 14.6% is detected with 90% probability) Stretches of mononucleotide repeats Indels larger than 50bp Single exon deletions or duplications Variants within pseudogene regions/duplicated segments The sensitivity of this test may be reduced if DNA is extracted by a laboratory other than Blueprint Genetics. -
The Role of Z-Disc Proteins in Myopathy and Cardiomyopathy
International Journal of Molecular Sciences Review The Role of Z-disc Proteins in Myopathy and Cardiomyopathy Kirsty Wadmore 1,†, Amar J. Azad 1,† and Katja Gehmlich 1,2,* 1 Institute of Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham B15 2TT, UK; [email protected] (K.W.); [email protected] (A.J.A.) 2 Division of Cardiovascular Medicine, Radcliffe Department of Medicine and British Heart Foundation Centre of Research Excellence Oxford, University of Oxford, Oxford OX3 9DU, UK * Correspondence: [email protected]; Tel.: +44-121-414-8259 † These authors contributed equally. Abstract: The Z-disc acts as a protein-rich structure to tether thin filament in the contractile units, the sarcomeres, of striated muscle cells. Proteins found in the Z-disc are integral for maintaining the architecture of the sarcomere. They also enable it to function as a (bio-mechanical) signalling hub. Numerous proteins interact in the Z-disc to facilitate force transduction and intracellular signalling in both cardiac and skeletal muscle. This review will focus on six key Z-disc proteins: α-actinin 2, filamin C, myopalladin, myotilin, telethonin and Z-disc alternatively spliced PDZ-motif (ZASP), which have all been linked to myopathies and cardiomyopathies. We will summarise pathogenic variants identified in the six genes coding for these proteins and look at their involvement in myopathy and cardiomyopathy. Listing the Minor Allele Frequency (MAF) of these variants in the Genome Aggregation Database (GnomAD) version 3.1 will help to critically re-evaluate pathogenicity based on variant frequency in normal population cohorts. -
Genequery™ Human Skeletal Muscle Contraction And
GeneQuery™ Human Skeletal Muscle Contraction and Muscular Dystrophies qPCR Array Kit (GQH-SKC) Catalog #GK065 Product Description ScienCell's GeneQuery™ Human Skeletal Muscle Contraction and Muscular Dystrophies qPCR Array (GQH-SKC) profiles 88 key genes involved in the contraction of skeletal muscle. There are three major muscle types in the human body: skeletal, cardiac, and smooth. Skeletal muscle is a striated muscle that relaxes and contracts to generate movement and force in the body. Of the three main muscle types, it is the only one under voluntary control. Neuromuscular diseases involving skeletal muscle dysfunction are very diverse and range from myopathies to muscular dystrophies. Below are brief examples of how included genes may be grouped according to their function in skeletal muscle biology: • Myogenesis: MYOD1, MYOG, PAX3, UTRN, MYF6, MDTN • Contractility: MYH2, SLC2A4, LMNA, DYSF, APT2A1 • Sarcomere Assembly : NEB, TRIM63, TTN, CAPN3, ACTA1 • Muscle Atrophy: NOS2, TRIM63, FOXO1, MAPK8, AKT1 • Muscular Dystrophy Development: POMT2, FKRP, ANO5, FRG1, SGCB Note : all gene names follow their official symbols by the Human Genome Organization Gene Nomenclature Committee (HGNC). GeneQuery™ qPCR array kits are qPCR ready in a 96-well plate format, with each well containing one primer set that can specifically recognize and efficiently amplify a target gene's cDNA. The carefully designed primers ensure that: (i) the optimal annealing temperature in qPCR analysis is 65°C (with 2 mM Mg 2+ , and no DMSO); (ii) the primer set recognizes all known transcript variants of target gene, unless otherwise indicated; and (iii) only one gene is amplified. Each primer set has been validated by qPCR with melt curve analysis, and gel electrophoresis. -
Defining Functional Interactions During Biogenesis of Epithelial Junctions
ARTICLE Received 11 Dec 2015 | Accepted 13 Oct 2016 | Published 6 Dec 2016 | Updated 5 Jan 2017 DOI: 10.1038/ncomms13542 OPEN Defining functional interactions during biogenesis of epithelial junctions J.C. Erasmus1,*, S. Bruche1,*,w, L. Pizarro1,2,*, N. Maimari1,3,*, T. Poggioli1,w, C. Tomlinson4,J.Lees5, I. Zalivina1,w, A. Wheeler1,w, A. Alberts6, A. Russo2 & V.M.M. Braga1 In spite of extensive recent progress, a comprehensive understanding of how actin cytoskeleton remodelling supports stable junctions remains to be established. Here we design a platform that integrates actin functions with optimized phenotypic clustering and identify new cytoskeletal proteins, their functional hierarchy and pathways that modulate E-cadherin adhesion. Depletion of EEF1A, an actin bundling protein, increases E-cadherin levels at junctions without a corresponding reinforcement of cell–cell contacts. This unexpected result reflects a more dynamic and mobile junctional actin in EEF1A-depleted cells. A partner for EEF1A in cadherin contact maintenance is the formin DIAPH2, which interacts with EEF1A. In contrast, depletion of either the endocytic regulator TRIP10 or the Rho GTPase activator VAV2 reduces E-cadherin levels at junctions. TRIP10 binds to and requires VAV2 function for its junctional localization. Overall, we present new conceptual insights on junction stabilization, which integrate known and novel pathways with impact for epithelial morphogenesis, homeostasis and diseases. 1 National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK. 2 Computing Department, Imperial College London, London SW7 2AZ, UK. 3 Bioengineering Department, Faculty of Engineering, Imperial College London, London SW7 2AZ, UK. 4 Department of Surgery & Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK. -
Abstracts from the 9Th Biennial Scientific Meeting of The
International Journal of Pediatric Endocrinology 2017, 2017(Suppl 1):15 DOI 10.1186/s13633-017-0054-x MEETING ABSTRACTS Open Access Abstracts from the 9th Biennial Scientific Meeting of the Asia Pacific Paediatric Endocrine Society (APPES) and the 50th Annual Meeting of the Japanese Society for Pediatric Endocrinology (JSPE) Tokyo, Japan. 17-20 November 2016 Published: 28 Dec 2017 PS1 Heritable forms of primary bone fragility in children typically lead to Fat fate and disease - from science to global policy a clinical diagnosis of either osteogenesis imperfecta (OI) or juvenile Peter Gluckman osteoporosis (JO). OI is usually caused by dominant mutations affect- Office of Chief Science Advsor to the Prime Minister ing one of the two genes that code for two collagen type I, but a re- International Journal of Pediatric Endocrinology 2017, 2017(Suppl 1):PS1 cessive form of OI is present in 5-10% of individuals with a clinical diagnosis of OI. Most of the involved genes code for proteins that Attempts to deal with the obesity epidemic based solely on adult be- play a role in the processing of collagen type I protein (BMP1, havioural change have been rather disappointing. Indeed the evidence CREB3L1, CRTAP, LEPRE1, P4HB, PPIB, FKBP10, PLOD2, SERPINF1, that biological, developmental and contextual factors are operating SERPINH1, SEC24D, SPARC, from the earliest stages in development and indeed across generations TMEM38B), or interfere with osteoblast function (SP7, WNT1). Specific is compelling. The marked individual differences in the sensitivity to the phenotypes are caused by mutations in SERPINF1 (recessive OI type obesogenic environment need to be understood at both the individual VI), P4HB (Cole-Carpenter syndrome) and SEC24D (‘Cole-Carpenter and population level. -
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. -
Communication Pathways in Human Nonmuscle Myosin-2C 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Authors: 25 Krishna Chinthalapudia,B,C,1, Sarah M
1 Mechanistic Insights into the Active Site and Allosteric 2 Communication Pathways in Human Nonmuscle Myosin-2C 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Authors: 25 Krishna Chinthalapudia,b,c,1, Sarah M. Heisslera,d,1, Matthias Prellera,e, James R. Sellersd,2, and 26 Dietmar J. Mansteina,b,2 27 28 Author Affiliations 29 aInstitute for Biophysical Chemistry, OE4350 Hannover Medical School, 30625 Hannover, 30 Germany. 31 bDivision for Structural Biochemistry, OE8830, Hannover Medical School, 30625 Hannover, 32 Germany. 33 cCell Adhesion Laboratory, Department of Integrative Structural and Computational Biology, The 34 Scripps Research Institute, Jupiter, Florida 33458, USA. 35 dLaboratory of Molecular Physiology, NHLBI, National Institutes of Health, Bethesda, Maryland 36 20892, USA. 37 eCentre for Structural Systems Biology (CSSB), German Electron Synchrotron (DESY), 22607 38 Hamburg, Germany. 39 1K.C. and S.M.H. contributed equally to this work 40 2To whom correspondence may be addressed: E-mail: [email protected] or 41 [email protected] 42 43 1 44 Abstract 45 Despite a generic, highly conserved motor domain, ATP turnover kinetics and their activation by 46 F-actin vary greatly between myosin-2 isoforms. Here, we present a 2.25 Å crystal pre- 47 powerstroke state (ADPVO4) structure of the human nonmuscle myosin-2C motor domain, one 48 of the slowest myosins characterized. In combination with integrated mutagenesis, ensemble- 49 solution kinetics, and molecular dynamics simulation approaches, the structure reveals an 50 allosteric communication pathway that connects the distal end of the motor domain with the 51 active site. -
KIF1A-Related Autosomal Dominant Spastic Paraplegias (SPG30) in Russian Families G
Rudenskaya et al. BMC Neurology (2020) 20:290 https://doi.org/10.1186/s12883-020-01872-4 RESEARCH ARTICLE Open Access KIF1A-related autosomal dominant spastic paraplegias (SPG30) in Russian families G. E. Rudenskaya1 , V. A. Kadnikova1* , O. P. Ryzhkova1 , L. A. Bessonova1, E. L. Dadali1 , D. S. Guseva1 , T. V. Markova1 , D. N. Khmelkova2 and A. V. Polyakov1 Abstract Background: Spastic paraplegia type 30 (SPG30) caused by KIF1A mutations was first reported in 2011 and was initially considered a very rare autosomal recessive (AR) form. In the last years, thanks to the development of massive parallel sequencing, SPG30 proved to be a rather common autosomal dominant (AD) form of familial or sporadic spastic paraplegia (SPG),, with a wide range of phenotypes: pure and complicated. The aim of our study is to detect AD SPG30 cases and to examine their molecular and clinical characteristics for the first time in the Russian population. Methods: Clinical, genealogical and molecular methods were used. Molecular methods included massive parallel sequencing (MPS) of custom panel ‘spastic paraplegias’ with 62 target genes complemented by familial Sanger sequencing. One case was detected by the whole -exome sequencing. Results: AD SPG30 was detected in 10 unrelated families, making it the 3rd (8.4%) most common SPG form in the cohort of 118 families. No AR SPG30 cases were detected. In total, 9 heterozygous KIF1A mutations were detected, with 4 novel and 5 known mutations. All the mutations were located within KIF1A motor domain. Six cases had pure phenotypes, of which 5 were familial, where 2 familial cases demonstrated incomplete penetrance, early onset and slow relatively benign SPG course. -
Dimerization of Mammalian Kinesin-3 Motors Results in Superprocessive Motion
Dimerization of mammalian kinesin-3 motors results in superprocessive motion Virupakshi Soppinaa,1, Stephen R. Norrisa,b, Aslan S. Dizajia, Matt Kortusa, Sarah Veatchb, Michelle Peckhamc, and Kristen J. Verheya,1 aDepartment of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, MI 48109; bDepartment of Biophysics, University of Michigan, Ann Arbor, MI 48109; and cSchool of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, United Kingdom Edited by J. Richard McIntosh, University of Colorado, Boulder, CO, and approved March 7, 2014 (received for review January 15, 2014) The kinesin-3 family is one of the largest among the kinesin Defects in kinesin-3 transport have been implicated in a wide superfamily and its members play important roles in a wide range variety of neurodegenerative, developmental, and cancer dis- of cellular transport activities, yet the molecular mechanisms of eases (22). However, a mechanistic understanding of this im- kinesin-3 regulation and cargo transport are largely unknown. portant class of cellular transporters is currently limited. We performed a comprehensive analysis of mammalian kinesin-3 To date, mechanistic studies have focused on truncated ver- motors from three different subfamilies (KIF1, KIF13, and KIF16). sions of mammalian KIF1A and its homolog CeUNC-104, and Using Forster resonance energy transfer microscopy in live cells, these studies have yielded contradictory results (23). For exam- we show for the first time to our knowledge that KIF16B motors ple, murine KIF1A has been proposed to function as a monomer undergo cargo-mediated dimerization. The molecular mechanisms that diffuses along the microtubule surface or as a processive dimer.