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Pulli K, Saarimäki-Vire J, Ahonen P, Liu X, Ibrahim H, Chandra V, Santambrogio A, Wang Y, Vaaralahti K, Iivonen AP, Känsäkoski J, Tommiska J, Kemkem Y, Varjosalo M, Vuoristo S, Andoniadou CL, Otonkoski T, Raivio T. A splice site variant in MADD affects hormone expression in pancreatic β cells and pituitary gonadotropes. JCI Insight 2024; 9:e167598. [PMID: 38775154 PMCID: PMC11141940 DOI: 10.1172/jci.insight.167598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 04/12/2024] [Indexed: 06/02/2024] Open
Abstract
MAPK activating death domain (MADD) is a multifunctional protein regulating small GTPases RAB3 and RAB27, MAPK signaling, and cell survival. Polymorphisms in the MADD locus are associated with glycemic traits, but patients with biallelic variants in MADD manifest a complex syndrome affecting nervous, endocrine, exocrine, and hematological systems. We identified a homozygous splice site variant in MADD in 2 siblings with developmental delay, diabetes, congenital hypogonadotropic hypogonadism, and growth hormone deficiency. This variant led to skipping of exon 30 and in-frame deletion of 36 amino acids. To elucidate how this mutation causes pleiotropic endocrine phenotypes, we generated relevant cellular models with deletion of MADD exon 30 (dex30). We observed reduced numbers of β cells, decreased insulin content, and increased proinsulin-to-insulin ratio in dex30 human embryonic stem cell-derived pancreatic islets. Concordantly, dex30 led to decreased insulin expression in human β cell line EndoC-βH1. Furthermore, dex30 resulted in decreased luteinizing hormone expression in mouse pituitary gonadotrope cell line LβT2 but did not affect ontogeny of stem cell-derived GnRH neurons. Protein-protein interactions of wild-type and dex30 MADD revealed changes affecting multiple signaling pathways, while the GDP/GTP exchange activity of dex30 MADD remained intact. Our results suggest MADD-specific processes regulate hormone expression in pancreatic β cells and pituitary gonadotropes.
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Affiliation(s)
- Kristiina Pulli
- Stem Cells and Metabolism Research Program (STEMM), Research Programs Unit, Faculty of Medicine, and
| | - Jonna Saarimäki-Vire
- Stem Cells and Metabolism Research Program (STEMM), Research Programs Unit, Faculty of Medicine, and
| | - Pekka Ahonen
- Stem Cells and Metabolism Research Program (STEMM), Research Programs Unit, Faculty of Medicine, and
| | - Xiaonan Liu
- Institute of Biotechnology, Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Hazem Ibrahim
- Stem Cells and Metabolism Research Program (STEMM), Research Programs Unit, Faculty of Medicine, and
| | - Vikash Chandra
- Stem Cells and Metabolism Research Program (STEMM), Research Programs Unit, Faculty of Medicine, and
| | - Alice Santambrogio
- Centre for Craniofacial and Regenerative Biology, King’s College London, London, United Kingdom
- Department of Medicine III, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Yafei Wang
- Stem Cells and Metabolism Research Program (STEMM), Research Programs Unit, Faculty of Medicine, and
| | - Kirsi Vaaralahti
- Stem Cells and Metabolism Research Program (STEMM), Research Programs Unit, Faculty of Medicine, and
| | - Anna-Pauliina Iivonen
- Stem Cells and Metabolism Research Program (STEMM), Research Programs Unit, Faculty of Medicine, and
| | - Johanna Känsäkoski
- Stem Cells and Metabolism Research Program (STEMM), Research Programs Unit, Faculty of Medicine, and
- Department of Physiology, Faculty of Medicine
| | - Johanna Tommiska
- Stem Cells and Metabolism Research Program (STEMM), Research Programs Unit, Faculty of Medicine, and
- Department of Physiology, Faculty of Medicine
| | - Yasmine Kemkem
- Centre for Craniofacial and Regenerative Biology, King’s College London, London, United Kingdom
| | - Markku Varjosalo
- Institute of Biotechnology, Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Sanna Vuoristo
- Stem Cells and Metabolism Research Program (STEMM), Research Programs Unit, Faculty of Medicine, and
- Department of Obstetrics and Gynecology; and
- HiLIFE, University of Helsinki, Helsinki, Finland
| | - Cynthia L. Andoniadou
- Centre for Craniofacial and Regenerative Biology, King’s College London, London, United Kingdom
- Department of Medicine III, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Timo Otonkoski
- Stem Cells and Metabolism Research Program (STEMM), Research Programs Unit, Faculty of Medicine, and
- New Children’s Hospital, Helsinki University Hospital, Pediatric Research Center, Helsinki, Finland
| | - Taneli Raivio
- Stem Cells and Metabolism Research Program (STEMM), Research Programs Unit, Faculty of Medicine, and
- Department of Physiology, Faculty of Medicine
- New Children’s Hospital, Helsinki University Hospital, Pediatric Research Center, Helsinki, Finland
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2
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Di Pietro P, Abate AC, Prete V, Damato A, Venturini E, Rusciano MR, Izzo C, Visco V, Ciccarelli M, Vecchione C, Carrizzo A. C2CD4B Evokes Oxidative Stress and Vascular Dysfunction via a PI3K/Akt/PKCα-Signaling Pathway. Antioxidants (Basel) 2024; 13:101. [PMID: 38247525 PMCID: PMC10812653 DOI: 10.3390/antiox13010101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 01/11/2024] [Accepted: 01/12/2024] [Indexed: 01/23/2024] Open
Abstract
High glucose-induced endothelial dysfunction is an important pathological feature of diabetic vasculopathy. While genome-wide studies have identified an association between type 2 diabetes mellitus (T2DM) and increased expression of a C2 calcium-dependent domain containing 4B (C2CD4B), no study has yet explored the possible direct effect of C2CD4B on vascular function. Vascular reactivity studies were conducted using a pressure myograph, and nitric oxide and oxidative stress were assessed through difluorofluorescein diacetate and dihydroethidium, respectively. We demonstrate that high glucose upregulated both mRNA and protein expression of C2CD4B in mice mesenteric arteries in a time-dependent manner. Notably, the inhibition of C2CD4B expression by genetic knockdown efficiently prevented hyperglycemia-induced oxidative stress, endothelial dysfunction, and loss of nitric oxide (NO) bioavailability. Recombinant C2CD4B evoked endothelial dysfunction of mice mesenteric arteries, an effect associated with increased reactive oxygen species (ROS) and decreased NO production. In isolated human umbilical vein endothelial cells (HUVECs), C2CD4B increased phosphorylation of endothelial nitric oxide synthase (eNOS) at the inhibitory site Thr495 and reduced eNOS dimerization. Pharmacological inhibitors of phosphoinositide 3-kinase (PI3K), Akt, and PKCα effectively attenuated oxidative stress, NO reduction, impairment of endothelial function, and eNOS uncoupling induced by C2CD4B. These data demonstrate, for the first time, that C2CD4B exerts a direct effect on vascular endothelium via a phosphoinositide 3-kinase (PI3K)/Akt/PKCα-signaling pathway, providing a new perspective on C2CD4B as a promising therapeutic target for the prevention of oxidative stress in diabetes-induced endothelial dysfunction.
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Affiliation(s)
- Paola Di Pietro
- Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana”, University of Salerno, 84081 Baronissi, Italy; (P.D.P.); (A.C.A.); (V.P.); (M.R.R.); (C.I.); (V.V.); (M.C.); (C.V.)
| | - Angela Carmelita Abate
- Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana”, University of Salerno, 84081 Baronissi, Italy; (P.D.P.); (A.C.A.); (V.P.); (M.R.R.); (C.I.); (V.V.); (M.C.); (C.V.)
| | - Valeria Prete
- Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana”, University of Salerno, 84081 Baronissi, Italy; (P.D.P.); (A.C.A.); (V.P.); (M.R.R.); (C.I.); (V.V.); (M.C.); (C.V.)
| | - Antonio Damato
- Vascular Physiopathology Unit, IRCCS Neuromed, 86077 Pozzilli, Italy; (A.D.); (E.V.)
| | - Eleonora Venturini
- Vascular Physiopathology Unit, IRCCS Neuromed, 86077 Pozzilli, Italy; (A.D.); (E.V.)
| | - Maria Rosaria Rusciano
- Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana”, University of Salerno, 84081 Baronissi, Italy; (P.D.P.); (A.C.A.); (V.P.); (M.R.R.); (C.I.); (V.V.); (M.C.); (C.V.)
| | - Carmine Izzo
- Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana”, University of Salerno, 84081 Baronissi, Italy; (P.D.P.); (A.C.A.); (V.P.); (M.R.R.); (C.I.); (V.V.); (M.C.); (C.V.)
| | - Valeria Visco
- Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana”, University of Salerno, 84081 Baronissi, Italy; (P.D.P.); (A.C.A.); (V.P.); (M.R.R.); (C.I.); (V.V.); (M.C.); (C.V.)
| | - Michele Ciccarelli
- Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana”, University of Salerno, 84081 Baronissi, Italy; (P.D.P.); (A.C.A.); (V.P.); (M.R.R.); (C.I.); (V.V.); (M.C.); (C.V.)
| | - Carmine Vecchione
- Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana”, University of Salerno, 84081 Baronissi, Italy; (P.D.P.); (A.C.A.); (V.P.); (M.R.R.); (C.I.); (V.V.); (M.C.); (C.V.)
- Vascular Physiopathology Unit, IRCCS Neuromed, 86077 Pozzilli, Italy; (A.D.); (E.V.)
| | - Albino Carrizzo
- Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana”, University of Salerno, 84081 Baronissi, Italy; (P.D.P.); (A.C.A.); (V.P.); (M.R.R.); (C.I.); (V.V.); (M.C.); (C.V.)
- Vascular Physiopathology Unit, IRCCS Neuromed, 86077 Pozzilli, Italy; (A.D.); (E.V.)
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3
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Lagou V, Jiang L, Ulrich A, Zudina L, González KSG, Balkhiyarova Z, Faggian A, Maina JG, Chen S, Todorov PV, Sharapov S, David A, Marullo L, Mägi R, Rujan RM, Ahlqvist E, Thorleifsson G, Gao Η, Εvangelou Ε, Benyamin B, Scott RA, Isaacs A, Zhao JH, Willems SM, Johnson T, Gieger C, Grallert H, Meisinger C, Müller-Nurasyid M, Strawbridge RJ, Goel A, Rybin D, Albrecht E, Jackson AU, Stringham HM, Corrêa IR, Farber-Eger E, Steinthorsdottir V, Uitterlinden AG, Munroe PB, Brown MJ, Schmidberger J, Holmen O, Thorand B, Hveem K, Wilsgaard T, Mohlke KL, Wang Z, Shmeliov A, den Hoed M, Loos RJF, Kratzer W, Haenle M, Koenig W, Boehm BO, Tan TM, Tomas A, Salem V, Barroso I, Tuomilehto J, Boehnke M, Florez JC, Hamsten A, Watkins H, Njølstad I, Wichmann HE, Caulfield MJ, Khaw KT, van Duijn CM, Hofman A, Wareham NJ, Langenberg C, Whitfield JB, Martin NG, Montgomery G, Scapoli C, Tzoulaki I, Elliott P, Thorsteinsdottir U, Stefansson K, Brittain EL, McCarthy MI, Froguel P, Sexton PM, Wootten D, Groop L, Dupuis J, Meigs JB, Deganutti G, Demirkan A, Pers TH, Reynolds CA, Aulchenko YS, Kaakinen MA, Jones B, Prokopenko I. GWAS of random glucose in 476,326 individuals provide insights into diabetes pathophysiology, complications and treatment stratification. Nat Genet 2023; 55:1448-1461. [PMID: 37679419 PMCID: PMC10484788 DOI: 10.1038/s41588-023-01462-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Accepted: 06/27/2023] [Indexed: 09/09/2023]
Abstract
Conventional measurements of fasting and postprandial blood glucose levels investigated in genome-wide association studies (GWAS) cannot capture the effects of DNA variability on 'around the clock' glucoregulatory processes. Here we show that GWAS meta-analysis of glucose measurements under nonstandardized conditions (random glucose (RG)) in 476,326 individuals of diverse ancestries and without diabetes enables locus discovery and innovative pathophysiological observations. We discovered 120 RG loci represented by 150 distinct signals, including 13 with sex-dimorphic effects, two cross-ancestry and seven rare frequency signals. Of these, 44 loci are new for glycemic traits. Regulatory, glycosylation and metagenomic annotations highlight ileum and colon tissues, indicating an underappreciated role of the gastrointestinal tract in controlling blood glucose. Functional follow-up and molecular dynamics simulations of lower frequency coding variants in glucagon-like peptide-1 receptor (GLP1R), a type 2 diabetes treatment target, reveal that optimal selection of GLP-1R agonist therapy will benefit from tailored genetic stratification. We also provide evidence from Mendelian randomization that lung function is modulated by blood glucose and that pulmonary dysfunction is a diabetes complication. Our investigation yields new insights into the biology of glucose regulation, diabetes complications and pathways for treatment stratification.
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Affiliation(s)
- Vasiliki Lagou
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Human Genetics, Wellcome Sanger Institute, Hinxton, UK
- VIB-KU Leuven Center for Brain and Disease Research, Leuven, Belgium
| | - Longda Jiang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Anna Ulrich
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Guildford, UK
| | - Liudmila Zudina
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Guildford, UK
| | - Karla Sofia Gutiérrez González
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Department of Molecular Diagnostics, Clinical Laboratory, Clinica Biblica Hospital, San José, Costa Rica
| | - Zhanna Balkhiyarova
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Guildford, UK
- People-Centred Artificial Intelligence Institute, University of Surrey, Guildford, UK
| | - Alessia Faggian
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Guildford, UK
- Laboratory for Artificial Biology, Department of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy
| | - Jared G Maina
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Guildford, UK
- UMR 8199-EGID, Institut Pasteur de Lille, CNRS, University of Lille, Lille, France
| | - Shiqian Chen
- Section of Endocrinology and Investigative Medicine, Imperial College London, London, UK
| | - Petar V Todorov
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Sodbo Sharapov
- Laboratory of Glycogenomics, Institute of Cytology and Genetics SD RAS, Novosibirsk, Russia
- MSU Institute for Artificial Intelligence, Lomonosov Moscow State University, Moscow, Russia
| | - Alessia David
- Centre for Bioinformatics and System Biology, Department of Life Sciences, Imperial College London, London, UK
| | - Letizia Marullo
- Department of Evolutionary Biology, Genetic Section, University of Ferrara, Ferrara, Italy
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Roxana-Maria Rujan
- Centre for Sports, Exercise and Life Sciences, Coventry University, Conventry, UK
| | - Emma Ahlqvist
- Lund University Diabetes Centre, Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | | | - Ηe Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Εvangelos Εvangelou
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | - Beben Benyamin
- Australian Centre for Precision Health, University of South Australia, Adelaide, South Australia, Australia
- Allied Health and Human Performance, University of South Australia, Adelaide, South Australia, Australia
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
| | - Robert A Scott
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Aaron Isaacs
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- CARIM School for Cardiovascular Diseases and Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, the Netherlands
- Department of Physiology, Maastricht University, Maastricht, the Netherlands
| | - Jing Hua Zhao
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Sara M Willems
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Toby Johnson
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Christa Meisinger
- Epidemiology, Faculty of Medicine, University of Augsburg, Augsburg, Germany
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- IBE, Faculty of Medicine, LMU Munich, Munich, Germany
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
- Department of Medicine I, University Hospital Grosshadern, Ludwig-Maximilians-University, Munich, Germany
| | - Rona J Strawbridge
- Cardiovascular Medicine Unit, Department of Medicine, Solna, Karolinska Institutet, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska University Hospital Solna, Stockholm, Sweden
- School of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Anuj Goel
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Denis Rybin
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Eva Albrecht
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Anne U Jackson
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Heather M Stringham
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | | | - Eric Farber-Eger
- Vanderbilt Institute for Clinical and Translational Research and Vanderbilt Translational and Clinical Cardiovascular Research Center, Nashville, TN, USA
| | | | - André G Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Patricia B Munroe
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Morris J Brown
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Julian Schmidberger
- Department of Internal Medicine I, Ulm University Medical Centre, Ulm, Germany
| | - Oddgeir Holmen
- Department of Public Health and General Practice, Norwegian University of Science and Technology, Trondheim, Norway
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Kristian Hveem
- K G Jebsen Centre for Genetic Epdiemiology, Department of Public Health and General Practice, Norwegian University of Science and Technology, Trondheim, Norway
| | - Tom Wilsgaard
- Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway
- Department of Clinical Medicine, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Zhe Wang
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Aleksey Shmeliov
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Guildford, UK
| | - Marcel den Hoed
- The Beijer Laboratory and Department of Immunology, Genetics and Pathology, Uppsala University and SciLifeLab, Uppsala, Sweden
| | - Ruth J F Loos
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Wolfgang Kratzer
- Department of Internal Medicine I, Ulm University Medical Centre, Ulm, Germany
| | - Mark Haenle
- Department of Internal Medicine I, Ulm University Medical Centre, Ulm, Germany
| | - Wolfgang Koenig
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
| | - Bernhard O Boehm
- Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore and Department of Endocrinology, Tan Tock Seng Hospital, Singapore City, Singapore
| | - Tricia M Tan
- Section of Endocrinology and Investigative Medicine, Imperial College London, London, UK
| | - Alejandra Tomas
- Section of Cell Biology and Functional Genomics, Imperial College London, London, UK
| | - Victoria Salem
- Department of Bioengineering, Imperial College London, South Kensington Campus, London, UK
| | - Inês Barroso
- Exeter Centre of Excellence for Diabetes Research (EXCEED), University of Exeter Medical School, Exeter, UK
| | - Jaakko Tuomilehto
- Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Diabetes Research Unit, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Jose C Florez
- Center for Genomic Medicine and Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Anders Hamsten
- Cardiovascular Medicine Unit, Department of Medicine, Solna, Karolinska Institutet, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska University Hospital Solna, Stockholm, Sweden
| | - Hugh Watkins
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Inger Njølstad
- Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway
- Department of Clinical Medicine, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway
| | - H-Erich Wichmann
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Mark J Caulfield
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Kay-Tee Khaw
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Centre for Medical Systems Biology, Leiden, the Netherlands
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Netherlands Consortium for Healthy Ageing, the Hague, the Netherlands
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Computational Medicine, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - John B Whitfield
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Grant Montgomery
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Institute for Molecular Bioscience, The University of Queensland, St Lucia, Queensland, Australia
| | - Chiara Scapoli
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | - Ioanna Tzoulaki
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC Centre for Environment and Health, Imperial College London, London, UK
- National Institute for Health Research Imperial College London Biomedical Research Centre, Imperial College London, London, UK
| | - Unnur Thorsteinsdottir
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavík, Iceland
| | - Kari Stefansson
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavík, Iceland
| | - Evan L Brittain
- Vanderbilt University Medical Center and the Vanderbilt Translational and Clinical Cardiovascular Research Center, Nashville, TN, USA
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
- Genentech, South San Francisco, CA, USA
| | - Philippe Froguel
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- UMR 8199-EGID, Institut Pasteur de Lille, CNRS, University of Lille, Lille, France
| | - Patrick M Sexton
- Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia
- ARC Centre for Cryo-Electron Microscopy of Membrane Proteins, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia
| | - Denise Wootten
- Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia
- ARC Centre for Cryo-Electron Microscopy of Membrane Proteins, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia
| | - Leif Groop
- Lund University Diabetes Centre, Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
- Finnish Institute for Molecular Medicine (FIMM), Helsinki University, Helsinki, Finland
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada
| | - James B Meigs
- Programs in Metabolism and Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Giuseppe Deganutti
- Centre for Sports, Exercise and Life Sciences, Coventry University, Conventry, UK
| | - Ayse Demirkan
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Guildford, UK
- People-Centred Artificial Intelligence Institute, University of Surrey, Guildford, UK
- Department of Genetics, University Medical Center Groningen, Groningen, the Netherlands
| | - Tune H Pers
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Christopher A Reynolds
- Centre for Sports, Exercise and Life Sciences, Coventry University, Conventry, UK
- School of Life Sciences, University of Essex, Colchester, UK
| | - Yurii S Aulchenko
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Laboratory of Glycogenomics, Institute of Cytology and Genetics SD RAS, Novosibirsk, Russia
- MSU Institute for Artificial Intelligence, Lomonosov Moscow State University, Moscow, Russia
| | - Marika A Kaakinen
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Guildford, UK.
- People-Centred Artificial Intelligence Institute, University of Surrey, Guildford, UK.
| | - Ben Jones
- Section of Endocrinology and Investigative Medicine, Imperial College London, London, UK.
| | - Inga Prokopenko
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Guildford, UK.
- People-Centred Artificial Intelligence Institute, University of Surrey, Guildford, UK.
- UMR 8199-EGID, Institut Pasteur de Lille, CNRS, University of Lille, Lille, France.
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4
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Xie Q, Zhang Z, Chen Z, Sun J, Li M, Wang Q, Pan Y. Integration of Selection Signatures and Protein Interactions Reveals NR6A1, PAPPA2, and PIK3C2B as the Promising Candidate Genes Underlying the Characteristics of Licha Black Pig. BIOLOGY 2023; 12:biology12040500. [PMID: 37106701 PMCID: PMC10135650 DOI: 10.3390/biology12040500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 03/23/2023] [Accepted: 03/23/2023] [Indexed: 03/29/2023]
Abstract
Licha black (LI) pig has the specific characteristics of larger body length and appropriate fat deposition among Chinese indigenous pigs. Body length is one of the external traits that affect production performance, and fat deposition influences meat quality. However, the genetic characteristics of LI pigs have not yet been systematically uncovered. Here, the genomic information from 891 individuals of LI pigs, commercial pigs, and other Chinese indigenous pigs was used to analyze the breed characteristics of the LI pig with runs of homozygosity, haplotype, and FST selection signatures. The results showed the growth traits-related genes (i.e., NR6A1 and PAPPA2) and the fatness traits-related gene (i.e., PIK3C2B) were the promising candidate genes that closely related to the characteristics of LI pigs. In addition, the protein–protein interaction network revealed the potential interactions between the promising candidate genes and the FASN gene. The RNA expression data from FarmGTEx indicated that the RNA expression levels of NR6A1, PAPPA2, PIK3C2B, and FASN were highly correlated in the ileum. This study provides valuable molecular insights into the mechanisms that affect pig body length and fat deposition, which can be used in the further breeding process to improve meat quality and commercial profitability.
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Rottner AK, Ye Y, Navarro-Guerrero E, Rajesh V, Pollner A, Bevacqua RJ, Yang J, Spigelman AF, Baronio R, Bautista A, Thomsen SK, Lyon J, Nawaz S, Smith N, Wesolowska-Andersen A, Fox JEM, Sun H, Kim SK, Ebner D, MacDonald PE, Gloyn AL. A genome-wide CRISPR screen identifies CALCOCO2 as a regulator of beta cell function influencing type 2 diabetes risk. Nat Genet 2023; 55:54-65. [PMID: 36543916 PMCID: PMC9839450 DOI: 10.1038/s41588-022-01261-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 10/26/2022] [Indexed: 12/24/2022]
Abstract
Identification of the genes and processes mediating genetic association signals for complex diseases represents a major challenge. As many of the genetic signals for type 2 diabetes (T2D) exert their effects through pancreatic islet-cell dysfunction, we performed a genome-wide pooled CRISPR loss-of-function screen in a human pancreatic beta cell line. We assessed the regulation of insulin content as a disease-relevant readout of beta cell function and identified 580 genes influencing this phenotype. Integration with genetic and genomic data provided experimental support for 20 candidate T2D effector transcripts including the autophagy receptor CALCOCO2. Loss of CALCOCO2 was associated with distorted mitochondria, less proinsulin-containing immature granules and accumulation of autophagosomes upon inhibition of late-stage autophagy. Carriers of T2D-associated variants at the CALCOCO2 locus further displayed altered insulin secretion. Our study highlights how cellular screens can augment existing multi-omic efforts to support mechanistic understanding and provide evidence for causal effects at genome-wide association studies loci.
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Affiliation(s)
- Antje K Rottner
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Yingying Ye
- Department of Pediatrics, Division of Endocrinology, Stanford School of Medicine, Stanford University, Stanford, CA, USA
| | - Elena Navarro-Guerrero
- Target Discovery Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Varsha Rajesh
- Department of Pediatrics, Division of Endocrinology, Stanford School of Medicine, Stanford University, Stanford, CA, USA
| | - Alina Pollner
- Department of Pediatrics, Division of Endocrinology, Stanford School of Medicine, Stanford University, Stanford, CA, USA
| | - Romina J Bevacqua
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Diabetes Research Centre, Stanford School of Medicine, Stanford University, Stanford, CA, USA
| | - Jing Yang
- Department of Pediatrics, Division of Endocrinology, Stanford School of Medicine, Stanford University, Stanford, CA, USA
| | - Aliya F Spigelman
- Department of Pharmacology and Alberta Diabetes Institute, University of Alberta, Edmonton, Alberta, Canada
| | - Roberta Baronio
- Target Discovery Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Austin Bautista
- Department of Pharmacology and Alberta Diabetes Institute, University of Alberta, Edmonton, Alberta, Canada
| | - Soren K Thomsen
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - James Lyon
- Department of Pharmacology and Alberta Diabetes Institute, University of Alberta, Edmonton, Alberta, Canada
| | - Sameena Nawaz
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Nancy Smith
- Department of Pharmacology and Alberta Diabetes Institute, University of Alberta, Edmonton, Alberta, Canada
| | | | - Jocelyn E Manning Fox
- Department of Pharmacology and Alberta Diabetes Institute, University of Alberta, Edmonton, Alberta, Canada
| | - Han Sun
- Department of Pediatrics, Division of Endocrinology, Stanford School of Medicine, Stanford University, Stanford, CA, USA
| | - Seung K Kim
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Diabetes Research Centre, Stanford School of Medicine, Stanford University, Stanford, CA, USA
| | - Daniel Ebner
- Department of Pediatrics, Division of Endocrinology, Stanford School of Medicine, Stanford University, Stanford, CA, USA
| | - Patrick E MacDonald
- Department of Pharmacology and Alberta Diabetes Institute, University of Alberta, Edmonton, Alberta, Canada
| | - Anna L Gloyn
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
- Department of Pediatrics, Division of Endocrinology, Stanford School of Medicine, Stanford University, Stanford, CA, USA.
- Stanford Diabetes Research Centre, Stanford School of Medicine, Stanford University, Stanford, CA, USA.
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK.
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
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6
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Dafoe TJ, Dos Santos T, Spigelman AF, Lyon J, Smith N, Bautista A, MacDonald PE, Manning Fox JE. Impacts of the COVID-19 pandemic on a human research islet program. Islets 2022; 14:101-113. [PMID: 35285768 PMCID: PMC8928860 DOI: 10.1080/19382014.2022.2047571] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 02/23/2022] [Accepted: 02/24/2022] [Indexed: 11/23/2022] Open
Abstract
Designated a pandemic in March 2020, the spread of severe acute respiratory syndrome virus 2 (SARS-CoV2), the virus responsible for coronavirus disease 2019 (COVID-19), led to new guidelines and restrictions being implemented for individuals, businesses, and societies in efforts to limit the impacts of COVID-19 on personal health and healthcare systems. Here we report the impacts of the COVID-19 pandemic on pancreas processing and islet isolation/distribution outcomes at the Alberta Diabetes Institute IsletCore, a facility specializing in the processing and distribution of human pancreatic islets for research. While the number of organs processed was significantly reduced, organ quality and the function of cellular outputs were minimally impacted during the pandemic when compared to an equivalent period immediately prior. Despite the maintained quality of isolated islets, feedback from recipient groups was more negative. Our findings suggest this is likely due to disrupted distribution which led to increased transit times to recipient labs, particularly those overseas. Thus, to improve overall outcomes in a climate of limited research islet supply, prioritization of tissue recipients based on likely tissue transit times may be needed.
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Affiliation(s)
- Tina J. Dafoe
- Alberta Diabetes Institute IsletCore and Department of Pharmacology, University of Alberta, Edmonton, Alberta, Canada
| | - Theodore Dos Santos
- Alberta Diabetes Institute IsletCore and Department of Pharmacology, University of Alberta, Edmonton, Alberta, Canada
| | - Aliya F. Spigelman
- Alberta Diabetes Institute IsletCore and Department of Pharmacology, University of Alberta, Edmonton, Alberta, Canada
| | - James Lyon
- Alberta Diabetes Institute IsletCore and Department of Pharmacology, University of Alberta, Edmonton, Alberta, Canada
| | - Nancy Smith
- Alberta Diabetes Institute IsletCore and Department of Pharmacology, University of Alberta, Edmonton, Alberta, Canada
| | - Austin Bautista
- Alberta Diabetes Institute IsletCore and Department of Pharmacology, University of Alberta, Edmonton, Alberta, Canada
| | - Patrick E. MacDonald
- Alberta Diabetes Institute IsletCore and Department of Pharmacology, University of Alberta, Edmonton, Alberta, Canada
| | - Jocelyn E. Manning Fox
- Alberta Diabetes Institute IsletCore and Department of Pharmacology, University of Alberta, Edmonton, Alberta, Canada
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7
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Michałowska J, Miller-Kasprzak E, Seraszek-Jaros A, Mostowska A, Bogdański P. The Link between Three Single Nucleotide Variants of the GIPR Gene and Metabolic Health. Genes (Basel) 2022; 13:genes13091534. [PMID: 36140702 PMCID: PMC9498707 DOI: 10.3390/genes13091534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 08/22/2022] [Accepted: 08/24/2022] [Indexed: 11/26/2022] Open
Abstract
Single nucleotide variants (SNVs) of the GIPR gene have been associated with BMI and type 2 diabetes (T2D), suggesting the role of the variation in this gene in metabolic health. To increase our understanding of this relationship, we investigated the association of three GIPR SNVs, rs11672660, rs2334255 and rs10423928, with anthropometric measurements, selected metabolic parameters, and the risk of excessive body mass and metabolic syndrome (MS) in the Polish population. Normal-weight subjects (n = 340, control group) and subjects with excessive body mass (n = 600, study group) participated in this study. For all participants, anthropometric measurements and metabolic parameters were collected, and genotyping was performed using the high-resolution melting curve analysis. We did not find a significant association between rs11672660, rs2334255 and rs10423928 variants with the risk of being overweight. Differences in metabolic and anthropometric parameters were found for investigated subgroups. An association between rs11672660 and rs10423928 with MS was identified. Heterozygous CT genotype of rs11672660 and AT genotype of rs10423928 were significantly more frequent in the group with MS (OR = 1.38, 95%CI: 1.03–1.85; p = 0.0304 and OR = 1.4, 95%CI: 1.05–1.87; p = 0.0222, respectively). Moreover, TT genotype of rs10423928 was less frequent in the MS group (OR = 0.72, 95%CI: 0.54–0.95; p = 0.0221).
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Affiliation(s)
- Joanna Michałowska
- Department of Treatment of Obesity, Metabolic Disorders and Clinical Dietetics, Poznan University of Medical Sciences, 61-701 Poznan, Poland
- Correspondence:
| | - Ewa Miller-Kasprzak
- Department of Treatment of Obesity, Metabolic Disorders and Clinical Dietetics, Poznan University of Medical Sciences, 61-701 Poznan, Poland
| | - Agnieszka Seraszek-Jaros
- Department of Bioinformatics and Computational Biology, Poznan University of Medical Sciences, 61-701 Poznan, Poland
| | - Adrianna Mostowska
- Department of Biochemistry and Molecular Biology, Poznan University of Medical Sciences, 61-701 Poznan, Poland
| | - Paweł Bogdański
- Department of Treatment of Obesity, Metabolic Disorders and Clinical Dietetics, Poznan University of Medical Sciences, 61-701 Poznan, Poland
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Laakso M, Fernandes Silva L. Genetics of Type 2 Diabetes: Past, Present, and Future. Nutrients 2022; 14:nu14153201. [PMID: 35956377 PMCID: PMC9370092 DOI: 10.3390/nu14153201] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 07/30/2022] [Accepted: 08/03/2022] [Indexed: 02/01/2023] Open
Abstract
Diabetes has reached epidemic proportions worldwide. Currently, approximately 537 million adults (20–79 years) have diabetes, and the total number of people with diabetes is continuously increasing. Diabetes includes several subtypes. About 80% of all cases of diabetes are type 2 diabetes (T2D). T2D is a polygenic disease with an inheritance ranging from 30 to 70%. Genetic and environment/lifestyle factors, especially obesity and sedentary lifestyle, increase the risk of T2D. In this review, we discuss how studies on the genetics of diabetes started, how they expanded when genome-wide association studies and exome and whole-genome sequencing became available, and the current challenges in genetic studies of diabetes. T2D is heterogeneous with respect to clinical presentation, disease course, and response to treatment, and has several subgroups which differ in pathophysiology and risk of micro- and macrovascular complications. Currently, genetic studies of T2D focus on these subgroups to find the best diagnoses and treatments for these patients according to the principles of precision medicine.
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Affiliation(s)
- Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, 70210 Kuopio, Finland
- Department of Medicine, Kuopio University Hospital, 70210 Kuopio, Finland
- Correspondence: ; Tel.: +358-40-672-3338
| | - Lilian Fernandes Silva
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, 70210 Kuopio, Finland
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9
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Verma M, Loh NY, Sabaratnam R, Vasan SK, van Dam AD, Todorčević M, Neville MJ, Toledo E, Karpe F, Christodoulides C. TCF7L2 plays a complex role in human adipose progenitor biology, which might contribute to genetic susceptibility to type 2 diabetes. Metabolism 2022; 133:155240. [PMID: 35697299 DOI: 10.1016/j.metabol.2022.155240] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 05/31/2022] [Accepted: 06/04/2022] [Indexed: 11/20/2022]
Abstract
INTRODUCTION Non-coding genetic variation at TCF7L2 is the strongest genetic determinant of type 2 diabetes (T2D) risk in humans. TCF7L2 encodes a transcription factor mediating the nuclear effects of WNT signaling in adipose tissue (AT). In vivo studies in transgenic mice have highlighted important roles for TCF7L2 in adipose tissue biology and systemic metabolism. OBJECTIVE To map the expression of TCF7L2 in human AT, examine its role in human adipose cell biology in vitro, and investigate the effects of the fine-mapped T2D-risk allele at rs7903146 on AT morphology and TCF7L2 expression. METHODS Ex vivo gene expression studies of TCF7L2 in whole and fractionated human AT. In vitro TCF7L2 gain- and/or loss-of-function studies in primary and immortalized human adipose progenitor cells (APCs) and mature adipocytes (mADs). AT phenotyping of rs7903146 T2D-risk variant carriers and matched controls. RESULTS Adipose progenitors (APs) exhibited the highest TCF7L2 mRNA abundance compared to mature adipocytes and adipose-derived endothelial cells. Obesity was associated with reduced TCF7L2 transcript levels in whole subcutaneous abdominal AT but paradoxically increased expression in APs. In functional studies, TCF7L2 knockdown (KD) in abdominal APs led to dose-dependent activation of WNT/β-catenin signaling, impaired proliferation and dose-dependent effects on adipogenesis. Whilst partial KD enhanced adipocyte differentiation, near-total KD impaired lipid accumulation and adipogenic gene expression. Over-expression of TCF7L2 accelerated adipogenesis. In contrast, TCF7L2-KD in gluteal APs dose-dependently enhanced lipid accumulation. Transcriptome-wide profiling revealed that TCF7L2 might modulate multiple aspects of AP biology including extracellular matrix secretion, immune signaling and apoptosis. The T2D-risk allele at rs7903146 was associated with reduced AP TCF7L2 expression and enhanced AT insulin sensitivity. CONCLUSIONS TCF7L2 plays a complex role in AP biology and has both dose- and depot-dependent effects on adipogenesis. In addition to regulating pancreatic insulin secretion, genetic variation at TCF7L2 might also influence T2D risk by modulating AP function.
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Affiliation(s)
- Manu Verma
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 7LE, UK
| | - Nellie Y Loh
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 7LE, UK
| | - Rugivan Sabaratnam
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 7LE, UK; Steno Diabetes Center Odense, Odense University Hospital, DK-5000 Odense, Denmark; Department of Clinical Research, University of Southern Denmark, DK-5000 Odense, Denmark
| | - Senthil K Vasan
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 7LE, UK
| | - Andrea D van Dam
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 7LE, UK
| | - Marijana Todorčević
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 7LE, UK
| | - Matthew J Neville
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 7LE, UK
| | - Enrique Toledo
- Department of Computational Biology, Novo Nordisk Research Centre Oxford, UK
| | - Fredrik Karpe
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 7LE, UK; NIHR Oxford Biomedical Research Centre, OUH Foundation Trust, Oxford OX3 7LE, UK
| | - Constantinos Christodoulides
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 7LE, UK; NIHR Oxford Biomedical Research Centre, OUH Foundation Trust, Oxford OX3 7LE, UK.
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10
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Kaminska J, Soczewka P, Rzepnikowska W, Zoladek T. Yeast as a Model to Find New Drugs and Drug Targets for VPS13-Dependent Neurodegenerative Diseases. Int J Mol Sci 2022; 23:ijms23095106. [PMID: 35563497 PMCID: PMC9104724 DOI: 10.3390/ijms23095106] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 04/28/2022] [Accepted: 04/30/2022] [Indexed: 12/10/2022] Open
Abstract
Mutations in human VPS13A-D genes result in rare neurological diseases, including chorea-acanthocytosis. The pathogenesis of these diseases is poorly understood, and no effective treatment is available. As VPS13 genes are evolutionarily conserved, the effects of the pathogenic mutations could be studied in model organisms, including yeast, where one VPS13 gene is present. In this review, we summarize advancements obtained using yeast. In recent studies, vps13Δ and vps13-I2749 yeast mutants, which are models of chorea-acanthocytosis, were used to screen for multicopy and chemical suppressors. Two of the suppressors, a fragment of the MYO3 and RCN2 genes, act by downregulating calcineurin activity. In addition, vps13Δ suppression was achieved by using calcineurin inhibitors. The other group of multicopy suppressors were genes: FET4, encoding iron transporter, and CTR1, CTR3 and CCC2, encoding copper transporters. Mechanisms of their suppression rely on causing an increase in the intracellular iron content. Moreover, among the identified chemical suppressors were copper ionophores, which require a functional iron uptake system for activity, and flavonoids, which bind iron. These findings point at areas for further investigation in a higher eukaryotic model of VPS13-related diseases and to new therapeutic targets: calcium signalling and copper and iron homeostasis. Furthermore, the identified drugs are interesting candidates for drug repurposing for these diseases.
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Affiliation(s)
- Joanna Kaminska
- Institute of Biochemistry and Biophysics Polish Academy of Sciences, 02-106 Warsaw, Poland; (J.K.); (P.S.)
| | - Piotr Soczewka
- Institute of Biochemistry and Biophysics Polish Academy of Sciences, 02-106 Warsaw, Poland; (J.K.); (P.S.)
| | - Weronika Rzepnikowska
- Neuromuscular Unit, Mossakowski Medical Research Institute, Polish Academy of Sciences, 02-106 Warsaw, Poland;
| | - Teresa Zoladek
- Institute of Biochemistry and Biophysics Polish Academy of Sciences, 02-106 Warsaw, Poland; (J.K.); (P.S.)
- Correspondence:
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11
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Wesolowska-Andersen A, Brorsson CA, Bizzotto R, Mari A, Tura A, Koivula R, Mahajan A, Vinuela A, Tajes JF, Sharma S, Haid M, Prehn C, Artati A, Hong MG, Musholt PB, Kurbasic A, De Masi F, Tsirigos K, Pedersen HK, Gudmundsdottir V, Thomas CE, Banasik K, Jennison C, Jones A, Kennedy G, Bell J, Thomas L, Frost G, Thomsen H, Allin K, Hansen TH, Vestergaard H, Hansen T, Rutters F, Elders P, t’Hart L, Bonnefond A, Canouil M, Brage S, Kokkola T, Heggie A, McEvoy D, Hattersley A, McDonald T, Teare H, Ridderstrale M, Walker M, Forgie I, Giordano GN, Froguel P, Pavo I, Ruetten H, Pedersen O, Dermitzakis E, Franks PW, Schwenk JM, Adamski J, Pearson E, McCarthy MI, Brunak S. Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study. Cell Rep Med 2022; 3:100477. [PMID: 35106505 PMCID: PMC8784706 DOI: 10.1016/j.xcrm.2021.100477] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 06/21/2021] [Accepted: 11/23/2021] [Indexed: 12/11/2022]
Abstract
The presentation and underlying pathophysiology of type 2 diabetes (T2D) is complex and heterogeneous. Recent studies attempted to stratify T2D into distinct subgroups using data-driven approaches, but their clinical utility may be limited if categorical representations of complex phenotypes are suboptimal. We apply a soft-clustering (archetype) method to characterize newly diagnosed T2D based on 32 clinical variables. We assign quantitative clustering scores for individuals and investigate the associations with glycemic deterioration, genetic risk scores, circulating omics biomarkers, and phenotypic stability over 36 months. Four archetype profiles represent dysfunction patterns across combinations of T2D etiological processes and correlate with multiple circulating biomarkers. One archetype associated with obesity, insulin resistance, dyslipidemia, and impaired β cell glucose sensitivity corresponds with the fastest disease progression and highest demand for anti-diabetic treatment. We demonstrate that clinical heterogeneity in T2D can be mapped to heterogeneity in individual etiological processes, providing a potential route to personalized treatments.
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Affiliation(s)
| | - Caroline A. Brorsson
- Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Andrea Mari
- C.N.R. Institute of Neuroscience, Padova, Italy
| | - Andrea Tura
- C.N.R. Institute of Neuroscience, Padova, Italy
| | - Robert Koivula
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Ana Vinuela
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | | | - Sapna Sharma
- Research Unit Molecular Endocrinology And Metabolism, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Mark Haid
- Research Unit Molecular Endocrinology And Metabolism, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Cornelia Prehn
- Research Unit Molecular Endocrinology And Metabolism, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Anna Artati
- Research Unit Molecular Endocrinology And Metabolism, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Mun-Gwan Hong
- Affinity Proteomics, Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden
| | - Petra B. Musholt
- R&D Global Development, Translational Medicine & Clinical Pharmacology (TMCP), Sanofi-Aventis Deutschland GmbH, Frankfurt, Germany
| | - Azra Kurbasic
- University of Lund, Clinical Sciences, Malmö, Sweden
| | - Federico De Masi
- Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Kostas Tsirigos
- Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Helle Krogh Pedersen
- Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Valborg Gudmundsdottir
- Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Cecilia Engel Thomas
- Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Karina Banasik
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Angus Jones
- University of Exeter Medical School, Exeter, UK
| | - Gwen Kennedy
- The Immunoassay Biomarker Core Laboratory, Shool of Medicine, University of Dundee, Dundee, UK
| | - Jimmy Bell
- Research Centre for Optimal Health, Deparment of Life Sciences, University of Westminster, London, UK
| | - Louise Thomas
- Research Centre for Optimal Health, Deparment of Life Sciences, University of Westminster, London, UK
| | - Gary Frost
- Section for Nutrition Research, Faculty of Medicine, Hammersmith Campus, Imperial College London, London, UK
| | - Henrik Thomsen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Kristine Allin
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tue Haldor Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Henrik Vestergaard
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Femke Rutters
- Department of Epidemiology and Biostatistics, Amsterdam Public Health Research Institute, Amsterdam UMC-location VUmc, Amsterdam, the Netherlands
| | - Petra Elders
- Department of General Practice, Amsterdam UMC-location VUmc, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Leen t’Hart
- Department of Epidemiology and Biostatistics, Amsterdam Public Health Research Institute, Amsterdam UMC-location VUmc, Amsterdam, the Netherlands
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands
| | - Amelie Bonnefond
- INSERM UMR 1283, CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, Lille University Hospital, Lille, France
| | - Mickaël Canouil
- INSERM UMR 1283, CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, Lille University Hospital, Lille, France
| | - Soren Brage
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Tarja Kokkola
- Department of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Alison Heggie
- Institute of Cellular Medicine, Newcastle University, Newcastle, UK
| | - Donna McEvoy
- Diabetes Research Network, Royal Victoria Infirmary, Newcastle, UK
| | | | | | - Harriet Teare
- Centre for Health, Law and Emerging Technologies (HeLEX), Faculty of Law, University of Oxford, Oxford, UK
| | | | - Mark Walker
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle, UK
| | | | - Giuseppe N. Giordano
- R&D Global Development, Translational Medicine & Clinical Pharmacology (TMCP), Sanofi-Aventis Deutschland GmbH, Frankfurt, Germany
| | - Philippe Froguel
- INSERM UMR 1283, CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, Lille University Hospital, Lille, France
| | - Imre Pavo
- Eli Lilly Regional Operations GmbH, Vienna, Austria
| | - Hartmut Ruetten
- R&D Global Development, Translational Medicine & Clinical Pharmacology (TMCP), Sanofi-Aventis Deutschland GmbH, Frankfurt, Germany
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Emmanouil Dermitzakis
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | | | - Jochen M. Schwenk
- Affinity Proteomics, Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden
| | - Jerzy Adamski
- Research Unit Molecular Endocrinology And Metabolism, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Lehrstuhl für Experimentelle Genetik, Technische Universität München, Freising-Weihenstephan, Germany
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore
| | | | - Mark I. McCarthy
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK
| | - Søren Brunak
- Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - IMI DIRECT Consortium
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- C.N.R. Institute of Neuroscience, Padova, Italy
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
- Research Unit Molecular Endocrinology And Metabolism, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Affinity Proteomics, Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden
- R&D Global Development, Translational Medicine & Clinical Pharmacology (TMCP), Sanofi-Aventis Deutschland GmbH, Frankfurt, Germany
- University of Lund, Clinical Sciences, Malmö, Sweden
- Department of Mathematical Sciences, University of Bath, Bath, UK
- University of Exeter Medical School, Exeter, UK
- The Immunoassay Biomarker Core Laboratory, Shool of Medicine, University of Dundee, Dundee, UK
- Research Centre for Optimal Health, Deparment of Life Sciences, University of Westminster, London, UK
- Section for Nutrition Research, Faculty of Medicine, Hammersmith Campus, Imperial College London, London, UK
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Epidemiology and Biostatistics, Amsterdam Public Health Research Institute, Amsterdam UMC-location VUmc, Amsterdam, the Netherlands
- Department of General Practice, Amsterdam UMC-location VUmc, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands
- INSERM UMR 1283, CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, Lille University Hospital, Lille, France
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Department of Medicine, University of Eastern Finland, Kuopio, Finland
- Institute of Cellular Medicine, Newcastle University, Newcastle, UK
- Diabetes Research Network, Royal Victoria Infirmary, Newcastle, UK
- Centre for Health, Law and Emerging Technologies (HeLEX), Faculty of Law, University of Oxford, Oxford, UK
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle, UK
- University of Dundee, Dundee, UK
- Eli Lilly Regional Operations GmbH, Vienna, Austria
- Lehrstuhl für Experimentelle Genetik, Technische Universität München, Freising-Weihenstephan, Germany
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK
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12
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Nikolaev G, Robeva R, Konakchieva R. Membrane Melatonin Receptors Activated Cell Signaling in Physiology and Disease. Int J Mol Sci 2021; 23:ijms23010471. [PMID: 35008896 PMCID: PMC8745360 DOI: 10.3390/ijms23010471] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 12/28/2021] [Accepted: 12/29/2021] [Indexed: 02/07/2023] Open
Abstract
The pineal hormone melatonin has attracted great scientific interest since its discovery in 1958. Despite the enormous number of basic and clinical studies the exact role of melatonin in respect to human physiology remains elusive. In humans, two high-affinity receptors for melatonin, MT1 and MT2, belonging to the family of G protein-coupled receptors (GPCRs) have been cloned and identified. The two receptor types activate Gi proteins and MT2 couples additionally to Gq proteins to modulate intracellular events. The individual effects of MT1 and MT2 receptor activation in a variety of cells are complemented by their ability to form homo- and heterodimers, the functional relevance of which is yet to be confirmed. Recently, several melatonin receptor genetic polymorphisms were discovered and implicated in pathology-for instance in type 2 diabetes, autoimmune disease, and cancer. The circadian patterns of melatonin secretion, its pleiotropic effects depending on cell type and condition, and the already demonstrated cross-talks of melatonin receptors with other signal transduction pathways further contribute to the perplexity of research on the role of the pineal hormone in humans. In this review we try to summarize the current knowledge on the membrane melatonin receptor activated cell signaling in physiology and pathology and their relevance to certain disease conditions including cancer.
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Affiliation(s)
- Georgi Nikolaev
- Faculty of Biology, Sofia University “St. Kliment Ohridski”, 1504 Sofia, Bulgaria;
- Correspondence:
| | - Ralitsa Robeva
- Department of Endocrinology, Faculty of Medicine, Medical University, 1431 Sofia, Bulgaria;
| | - Rossitza Konakchieva
- Faculty of Biology, Sofia University “St. Kliment Ohridski”, 1504 Sofia, Bulgaria;
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13
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Prasad RB, Kristensen K, Katsarou A, Shaat N. Association of single nucleotide polymorphisms with insulin secretion, insulin sensitivity, and diabetes in women with a history of gestational diabetes mellitus. BMC Med Genomics 2021; 14:274. [PMID: 34801028 PMCID: PMC8606068 DOI: 10.1186/s12920-021-01123-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 11/10/2021] [Indexed: 12/23/2022] Open
Abstract
Background This study investigated whether single nucleotide polymorphisms (SNPs) reported by previous genome-wide association studies (GWAS) to be associated with impaired insulin secretion, insulin resistance, and/or type 2 diabetes are associated with disposition index, the homeostasis model assessment of insulin resistance (HOMA-IR), and/or development of diabetes following a pregnancy complicated by gestational diabetes mellitus (GDM). Methods Seventy-two SNPs were genotyped in 374 women with previous GDM from Southern Sweden. An oral glucose tolerance test was performed 1–2 years postpartum, although data on the diagnosis of diabetes were accessible up to 5 years postpartum. HOMA-IR and disposition index were used to measure insulin resistance and secretion, respectively. Results The risk A-allele in the rs11708067 polymorphism of the adenylate cyclase 5 gene (ADCY5) was associated with decreased disposition index (beta = − 0.90, SE 0.38, p = 0.019). This polymorphism was an expression quantitative trait loci (eQTL) in islets for both ADCY5 and its antisense transcript. The risk C-allele in the rs2943641 polymorphism, near the insulin receptor substrate 1 gene (IRS1), showed a trend towards association with increased HOMA-IR (beta = 0.36, SE 0.18, p = 0.050), and the T-allele of the rs4607103 polymorphism, near the ADAM metallopeptidase with thrombospondin type 1 motif 9 gene (ADAMTS9), was associated with postpartum diabetes (OR = 2.12, SE 0.22, p = 0.00055). The genetic risk score (GRS) of the top four SNPs tested for association with the disposition index using equal weights was associated with the disposition index (beta = − 0.31, SE = 0.29, p = 0.00096). In addition, the GRS of the four SNPs studied for association with HOMA-IR using equal weights showed an association with HOMA-IR (beta = 1.13, SE = 0.48, p = 9.72874e−11). All analyses were adjusted for age, body mass index, and ethnicity. Conclusions This study demonstrated the genetic susceptibility of women with a history of GDM to impaired insulin secretion and sensitivity and, ultimately, to diabetes development.
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Affiliation(s)
- Rashmi B Prasad
- Genomics, Diabetes and Endocrinology, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Karl Kristensen
- Genomics, Diabetes and Endocrinology, Department of Clinical Sciences, Lund University, Malmö, Sweden.,Department of Obstetrics and Gynaecology, Skåne University Hospital, Malmö, Sweden
| | - Anastasia Katsarou
- Genomics, Diabetes and Endocrinology, Department of Clinical Sciences, Lund University, Malmö, Sweden.,Department of Endocrinology, Skåne University Hospital, 205 02, Malmö, Sweden
| | - Nael Shaat
- Genomics, Diabetes and Endocrinology, Department of Clinical Sciences, Lund University, Malmö, Sweden. .,Department of Endocrinology, Skåne University Hospital, 205 02, Malmö, Sweden.
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14
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Abbasi F, Lamendola C, Harris CS, Harris V, Tsai MS, Tripathi P, Abbas F, Reaven G, Reaven P, Snyder MP, Kim SH, Knowles JW. Statins Are Associated With Increased Insulin Resistance and Secretion. Arterioscler Thromb Vasc Biol 2021; 41:2786-2797. [PMID: 34433298 PMCID: PMC8551023 DOI: 10.1161/atvbaha.121.316159] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 08/09/2021] [Indexed: 11/16/2022]
Abstract
Objective Statin treatment reduces the risk of atherosclerotic cardiovascular disease but is associated with a modest increased risk of type 2 diabetes, especially in those with insulin resistance or prediabetes. Our objective was to determine the physiological mechanism for the increased type 2 diabetes risk. Approach and Results We conducted an open-label clinical trial of atorvastatin 40 mg daily in adults without known atherosclerotic cardiovascular disease or type 2 diabetes at baseline. The co-primary outcomes were changes at 10 weeks versus baseline in insulin resistance as assessed by steady-state plasma glucose during the insulin suppression test and insulin secretion as assessed by insulin secretion rate area under the curve (ISRAUC) during the graded-glucose infusion test. Secondary outcomes included glucose and insulin, both fasting and during oral glucose tolerance test. Of 75 participants who enrolled, 71 completed the study (median age 61 years, 37% women, 65% non-Hispanic White, median body mass index, 27.8 kg/m2). Atorvastatin reduced LDL (low-density lipoprotein)-cholesterol (median decrease 53%, P<0.001) but did not change body weight. Compared with baseline, atorvastatin increased insulin resistance (steady-state plasma glucose) by a median of 8% (P=0.01) and insulin secretion (ISRAUC) by a median of 9% (P<0.001). There were small increases in oral glucose tolerance test glucoseAUC (median increase, 0.05%; P=0.03) and fasting insulin (median increase, 7%; P=0.01). Conclusions In individuals without type 2 diabetes, high-intensity atorvastatin for 10 weeks increases insulin resistance and insulin secretion. Over time, the risk of new-onset diabetes with statin use may increase in individuals who become more insulin resistant but are unable to maintain compensatory increases in insulin secretion.
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Affiliation(s)
- Fahim Abbasi
- Division of Cardiovascular Medicine, Stanford University, Stanford, California, USA
- Cardiovascular Institute, Stanford University, Stanford, California, USA
- Department of Medicine, Stanford University, Stanford, California, USA
- Stanford Diabetes Research Center, Stanford University, Stanford, California, USA
| | - Cindy Lamendola
- Division of Cardiovascular Medicine, Stanford University, Stanford, California, USA
- Cardiovascular Institute, Stanford University, Stanford, California, USA
- Department of Medicine, Stanford University, Stanford, California, USA
| | - Chelsea S. Harris
- Division of Cardiovascular Medicine, Stanford University, Stanford, California, USA
- Cardiovascular Institute, Stanford University, Stanford, California, USA
- Department of Medicine, Stanford University, Stanford, California, USA
| | - Vander Harris
- Division of Cardiovascular Medicine, Stanford University, Stanford, California, USA
- Cardiovascular Institute, Stanford University, Stanford, California, USA
- Department of Medicine, Stanford University, Stanford, California, USA
| | - Ming-Shian Tsai
- Cardiovascular Institute, Stanford University, Stanford, California, USA
- Department of Genetics, Stanford University, Stanford, California, USA
- Stanford Diabetes Research Center, Stanford University, Stanford, California, USA
| | - Pragya Tripathi
- Division of Cardiovascular Medicine, Stanford University, Stanford, California, USA
- Cardiovascular Institute, Stanford University, Stanford, California, USA
| | - Fakhar Abbas
- Division of Cardiovascular Medicine, Stanford University, Stanford, California, USA
- Cardiovascular Institute, Stanford University, Stanford, California, USA
- Department of Medicine, Stanford University, Stanford, California, USA
| | - Gerald Reaven
- Division of Cardiovascular Medicine, Stanford University, Stanford, California, USA
- Cardiovascular Institute, Stanford University, Stanford, California, USA
- Department of Medicine, Stanford University, Stanford, California, USA
| | - Peter Reaven
- University of Arizona and Phoenix VA Health Care System, Phoenix, Arizona, USA
| | - Michael P. Snyder
- Cardiovascular Institute, Stanford University, Stanford, California, USA
- Department of Genetics, Stanford University, Stanford, California, USA
- Stanford Diabetes Research Center, Stanford University, Stanford, California, USA
| | - Sun H. Kim
- Department of Medicine, Stanford University, Stanford, California, USA
- Stanford Diabetes Research Center, Stanford University, Stanford, California, USA
- Division of Endocrinology, Gerontology and Metabolism, Stanford University, Stanford, California, USA
| | - Joshua W. Knowles
- Division of Cardiovascular Medicine, Stanford University, Stanford, California, USA
- Cardiovascular Institute, Stanford University, Stanford, California, USA
- Department of Medicine, Stanford University, Stanford, California, USA
- Stanford Diabetes Research Center, Stanford University, Stanford, California, USA
- Stanford Prevention Research Center, Stanford University, Stanford, California, USA
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Ghosh S, Mahalanobish S, Sil PC. Diabetes: discovery of insulin, genetic, epigenetic and viral infection mediated regulation. THE NUCLEUS : AN INTERNATIONAL JOURNAL OF CYTOLOGY AND ALLIED TOPICS 2021; 65:283-297. [PMID: 34629548 PMCID: PMC8491600 DOI: 10.1007/s13237-021-00376-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 09/23/2021] [Indexed: 01/11/2023]
Abstract
Diabetes mellitus, commonly referred to as diabetes, is a combination of many metabolic diseases. Insulin deficiency in our body is the main cause of diabetes. Insulin is one of the most well studied proteins, yet the genesis of its discovery was not getting much attention so far. Nevertheless, the history of the discovery of insulin is an exemplary of solving observational and scientific riddles, drudgery, patience and even professional turmoil. It is an inspiration for all medical personnel and scientists who are practising in the field of molecular medicine. Additionally, the genetic and epigenetic regulation of different types of diabetes needs to be addressed because of the widespread nature of the disease. Diabetes not only involves genetic predisposition but environmental factors, lifestyle etc. can be the major contributor for its inception. Nonetheless, viral infections at an early age are also found to trigger the onset of type I diabetes. In this review article, the history of the discovery of insulin is detailed along with the justification for the genetic and epigenetic regulatory mechanisms of diabetes and explained how viral infections can also trigger the onset of diabetes.
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Affiliation(s)
- Sumit Ghosh
- Division of Molecular Medicine, Bose Institute, P-1/12, CIT Scheme VII M, Kolkata, West Bengal 700054 India
| | - Sushweta Mahalanobish
- Division of Molecular Medicine, Bose Institute, P-1/12, CIT Scheme VII M, Kolkata, West Bengal 700054 India
| | - Parames C. Sil
- Division of Molecular Medicine, Bose Institute, P-1/12, CIT Scheme VII M, Kolkata, West Bengal 700054 India
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Kim DS, Gloyn AL, Knowles JW. Genetics of Type 2 Diabetes: Opportunities for Precision Medicine: JACC Focus Seminar. J Am Coll Cardiol 2021; 78:496-512. [PMID: 34325839 PMCID: PMC8328195 DOI: 10.1016/j.jacc.2021.03.346] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 03/14/2021] [Accepted: 03/16/2021] [Indexed: 12/30/2022]
Abstract
Type 2 diabetes (T2D) is highly prevalent and is a strong contributor for cardiovascular disease. However, there is significant heterogeneity in disease pathogenesis and the risk of complications. Enormous progress has been made in our ability to catalog genetic variation associated with T2D risk and variation in disease-relevant quantitative traits. These discoveries hold the potential to shed light on tractable targets and pathways for safe and effective therapeutic development, but the promise of precision medicine has been slow to be realized. Recent studies have identified subgroups of individuals with differential risk for intermediate phenotypes (eg, lipid levels, fasting insulin, body mass index) that contribute to T2D risk, helping to account for the observed clinical heterogeneity. These "partitioned genetic risk scores" not only have the potential to identify patients at greatest risk of cardiovascular disease and rapid disease progression, but also could aid patient stratification bridging the gap toward precision medicine for T2D.
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Affiliation(s)
- Daniel Seung Kim
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Anna L Gloyn
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA; Stanford Diabetes Research Center, Stanford University, Stanford, California, USA
| | - Joshua W Knowles
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, California, USA; Stanford Diabetes Research Center, Stanford University, Stanford, California, USA; Stanford Cardiovascular Institute, Stanford University, Stanford, California, USA.
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Impact of Amerind ancestry and FADS genetic variation on omega-3 deficiency and cardiometabolic traits in Hispanic populations. Commun Biol 2021; 4:918. [PMID: 34321601 PMCID: PMC8319323 DOI: 10.1038/s42003-021-02431-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Accepted: 06/22/2021] [Indexed: 12/31/2022] Open
Abstract
Long chain polyunsaturated fatty acids (LC-PUFAs) have critical signaling roles that regulate dyslipidemia and inflammation. Genetic variation in the FADS gene cluster accounts for a large portion of interindividual differences in circulating and tissue levels of LC-PUFAs, with the genotypes most strongly predictive of low LC-PUFA levels at strikingly higher frequencies in Amerind ancestry populations. In this study, we examined relationships between genetic ancestry and FADS variation in 1102 Hispanic American participants from the Multi-Ethnic Study of Atherosclerosis. We demonstrate strong negative associations between Amerind genetic ancestry and LC-PUFA levels. The FADS rs174537 single nucleotide polymorphism (SNP) accounted for much of the AI ancestry effect on LC-PUFAs, especially for low levels of n-3 LC-PUFAs. Rs174537 was also strongly associated with several metabolic, inflammatory and anthropomorphic traits including circulating triglycerides (TGs) and E-selectin in MESA Hispanics. Our study demonstrates that Amerind ancestry provides a useful and readily available tool to identify individuals most likely to have FADS-related n-3 LC-PUFA deficiencies and associated cardiovascular risk.
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18
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Chung RH, Chiu YF, Wang WC, Hwu CM, Hung YJ, Lee IT, Chuang LM, Quertermous T, Rotter JI, Chen YDI, Chang IS, Hsiung CA. Multi-omics analysis identifies CpGs near G6PC2 mediating the effects of genetic variants on fasting glucose. Diabetologia 2021; 64:1613-1625. [PMID: 33842983 DOI: 10.1007/s00125-021-05449-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Accepted: 02/08/2021] [Indexed: 10/21/2022]
Abstract
AIMS/HYPOTHESIS An elevated fasting glucose level in non-diabetic individuals is a key predictor of type 2 diabetes. Genome-wide association studies (GWAS) have identified hundreds of SNPs for fasting glucose but most of their functional roles in influencing the trait are unclear. This study aimed to identify the mediation effects of DNA methylation between SNPs identified as significant from GWAS and fasting glucose using Mendelian randomisation (MR) analyses. METHODS We first performed GWAS analyses for three cohorts (Taiwan Biobank with 18,122 individuals, the Healthy Aging Longitudinal Study in Taiwan with 1989 individuals and the Stanford Asia-Pacific Program for Hypertension and Insulin Resistance with 416 individuals) with individuals of Han Chinese ancestry in Taiwan, followed by a meta-analysis for combining the three GWAS analysis results to identify significant and independent SNPs for fasting glucose. We determined whether these SNPs were methylation quantitative trait loci (meQTLs) by testing their associations with DNA methylation levels at nearby CpG sites using a subsample of 1775 individuals from the Taiwan Biobank. The MR analysis was performed to identify DNA methylation with causal effects on fasting glucose using meQTLs as instrumental variables based on the 1775 individuals. We also used a two-sample MR strategy to perform replication analysis for CpG sites with significant MR effects based on literature data. RESULTS Our meta-analysis identified 18 significant (p < 5 × 10-8) and independent SNPs for fasting glucose. Interestingly, all 18 SNPs were meQTLs. The MR analysis identified seven CpGs near the G6PC2 gene that mediated the effects of a significant SNP (rs2232326) in the gene on fasting glucose. The MR effects for two CpGs were replicated using summary data based on the European population, using an exonic SNP rs2232328 in G6PC2 as the instrument. CONCLUSIONS/INTERPRETATION Our analysis results suggest that rs2232326 and rs2232328 in G6PC2 may affect DNA methylation at CpGs near the gene and that the methylation may have downstream effects on fasting glucose. Therefore, SNPs in G6PC2 and CpGs near G6PC2 may reside along the pathway that influences fasting glucose levels. This is the first study to report CpGs near G6PC2, an important gene for regulating insulin secretion, mediating the effects of GWAS-significant SNPs on fasting glucose.
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Affiliation(s)
- Ren-Hua Chung
- Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan.
| | - Yen-Feng Chiu
- Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan
| | - Wen-Chang Wang
- The Ph.D. Program for Translational Medicine, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
| | - Chii-Min Hwu
- Section of Endocrinology and Metabolism, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
- School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Yi-Jen Hung
- Division of Endocrine and Metabolism, Tri-Service General Hospital, Taipei, Taiwan
- Institute of Preventive Medicine, National Defense Medical Center, Taipei, Taiwan
| | - I-Te Lee
- School of Medicine, National Yang-Ming University, Taipei, Taiwan
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
- School of Medicine, Chung Shan Medical University, Taichung, Taiwan
| | - Lee-Ming Chuang
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
- Institutes of Molecular Medicine, Collage of Medicine, National Taiwan University, Taipei, Taiwan
| | - Thomas Quertermous
- Division of Cardiovascular Medicine and Stanford Cardiovascular Institute, Falk Cardiovascular Research Center, Stanford University, Stanford, CA, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, the Lundquist Institute, Harbor-UCLA Medical Center, Torrance, CA, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Yii-Der I Chen
- Institute for Translational Genomics and Population Sciences, the Lundquist Institute, Harbor-UCLA Medical Center, Torrance, CA, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - I-Shou Chang
- National Institute of Cancer Research, National Health Research Institutes, Zhunan, Taiwan
| | - Chao A Hsiung
- Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan.
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Eksi YE, Sanlioglu AD, Akkaya B, Ozturk BE, Sanlioglu S. Genome engineering and disease modeling via programmable nucleases for insulin gene therapy: Promises of CRISPR/Cas9 technology. World J Stem Cells 2021; 13:485-502. [PMID: 34249224 PMCID: PMC8246254 DOI: 10.4252/wjsc.v13.i6.485] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 04/02/2021] [Accepted: 06/16/2021] [Indexed: 02/06/2023] Open
Abstract
Targeted genome editing is a continually evolving technology employing programmable nucleases to specifically change, insert, or remove a genomic sequence of interest. These advanced molecular tools include meganucleases, zinc finger nucleases, transcription activator-like effector nucleases and RNA-guided engineered nucleases (RGENs), which create double-strand breaks at specific target sites in the genome, and repair DNA either by homologous recombination in the presence of donor DNA or via the error-prone non-homologous end-joining mechanism. A recently discovered group of RGENs known as CRISPR/Cas9 gene-editing systems allowed precise genome manipulation revealing a causal association between disease genotype and phenotype, without the need for the reengineering of the specific enzyme when targeting different sequences. CRISPR/Cas9 has been successfully employed as an ex vivo gene-editing tool in embryonic stem cells and patient-derived stem cells to understand pancreatic beta-cell development and function. RNA-guided nucleases also open the way for the generation of novel animal models for diabetes and allow testing the efficiency of various therapeutic approaches in diabetes, as summarized and exemplified in this manuscript.
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Affiliation(s)
- Yunus E Eksi
- Department of Gene and Cell Therapy, Akdeniz University Faculty of Medicine, Antalya 07058, Turkey
| | - Ahter D Sanlioglu
- Department of Gene and Cell Therapy, Akdeniz University Faculty of Medicine, Antalya 07058, Turkey
| | - Bahar Akkaya
- Department of Gene and Cell Therapy, Akdeniz University Faculty of Medicine, Antalya 07058, Turkey
| | - Bilge Esin Ozturk
- Department of Ophthalmology, University of Pittsburgh, Pittsburgh, PA 15213, United States
| | - Salih Sanlioglu
- Department of Gene and Cell Therapy, Akdeniz University Faculty of Medicine, Antalya 07058, Turkey
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20
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Zhang Z, Xu L, Xu X. The role of transcription factor 7-like 2 in metabolic disorders. Obes Rev 2021; 22:e13166. [PMID: 33615650 DOI: 10.1111/obr.13166] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 10/08/2020] [Accepted: 10/08/2020] [Indexed: 12/13/2022]
Abstract
Transcription factor 7-like 2 (TCF7L2), a member of the T cell factor/lymphoid enhancer factor family, generally forms a complex with β-catenin to regulate the downstream target genes as an effector of the canonical Wnt signalling pathway. TCF7L2 plays a vital role in various biological processes and functions in many organs and tissues, including the liver, islet and adipose tissues. Further, TCF7L2 down-regulates hepatic gluconeogenesis and promotes lipid accumulation. In islets, TCF7L2 not only affects the insulin secretion of the β-cells but also has an impact on other cells. In addition, TCF7L2 influences adipogenesis in adipose tissues. Thus, an out-of-control TCF7L2 expression can result in metabolic disorders. The TCF7L2 gene is composed of 17 exons, generating 13 different transcripts, and has many single-nucleotide polymorphisms (SNPs). The discovery that these SNPs have an impact on the risk of type 2 diabetes (T2D) has attracted thorough investigations in the study of TCF7L2. Apart from T2D, TCF7L2 SNPs are also associated with type 1, posttransplant and other types of diabetes. Furthermore, TCF7L2 variants affect the progression of other disorders, such as obesity, cancers, metabolic syndrome and heart diseases. Finally, the interaction between TCF7L2 variants and diet also needs to be investigated.
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Affiliation(s)
- Zhensheng Zhang
- Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China.,Department of Hepatobiliary and Pancreatic Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.,NHC Key Laboratory of Combined Multi-organ Transplantation, Hangzhou, China.,Zhejiang University School of Medicine, Hangzhou, China
| | - Li Xu
- Department of Hepatobiliary and Pancreatic Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.,Zhejiang University Cancer Center, Hangzhou, China.,NHC Key Laboratory of Combined Multi-organ Transplantation, Hangzhou, China.,Zhejiang University School of Medicine, Hangzhou, China
| | - Xiao Xu
- Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China.,Department of Hepatobiliary and Pancreatic Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.,Zhejiang University Cancer Center, Hangzhou, China
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21
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Ouyang Y, Qiu G, zhao X, Su B, Feng D, Lv W, Xuan Q, Wang L, Yu D, Wang Q, Lin X, Wu T, Xu G. Metabolome-Genome-Wide Association Study (mGWAS) Reveals Novel Metabolites Associated with Future Type 2 Diabetes Risk and Susceptibility Loci in a Case-Control Study in a Chinese Prospective Cohort. GLOBAL CHALLENGES (HOBOKEN, NJ) 2021; 5:2000088. [PMID: 33854788 PMCID: PMC8025395 DOI: 10.1002/gch2.202000088] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 01/20/2021] [Indexed: 05/03/2023]
Abstract
In a Chinese prospective cohort, 500 patients with new-onset type 2 diabetes (T2D) within 4.61 years and 500 matched healthy participants are selected as case and control groups, and randomized into discovery and validation sets to discover the metabolite changes before T2D onset and the related diabetogenic loci. A serum metabolomics analysis reveals that 81 metabolites changed significantly before T2D onset. Based on binary logistic regression, eight metabolites are defined as a biomarker panel for T2D prediction. Pipecolinic acid, carnitine C14:0, epinephrine and phosphatidylethanolamine 34:2 are first found associated with future T2D. The addition of the biomarker panel to the clinical markers (BMI, triglycerides, and fasting glucose) significantly improves the predictive ability in the discovery and validation sets, respectively. By associating metabolomics with genomics, a significant correlation (p < 5.0 × 10-8) between eicosatetraenoic acid and the FADS1 (rs174559) gene is observed, and suggestive correlations (p < 5.0 × 10-6) between pipecolinic acid and CHRM3 (rs535514), and leucine/isoleucine and WWOX (rs72487966) are discovered. Elevated leucine/isoleucine levels increased the risk of T2D. In conclusion, multiple metabolic dysregulations are observed to occur before T2D onset, and the new biomarker panel can help to predict T2D risk.
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Affiliation(s)
- Yang Ouyang
- CAS Key Laboratory of Separation Science for Analytical ChemistryDalian Institute of Chemical PhysicsChinese Academy of Sciences457 Zhongshan RoadDalian116023China
- University of Chinese Academy of SciencesBeijing100049China
| | - Gaokun Qiu
- MOE Key Lab of Environment and HealthSchool of Public HealthTongji Medical CollegeHuazhong University of Science & TechnologyWuhanHubei430030China
| | - Xinjie zhao
- CAS Key Laboratory of Separation Science for Analytical ChemistryDalian Institute of Chemical PhysicsChinese Academy of Sciences457 Zhongshan RoadDalian116023China
| | - Benzhe Su
- School of Computer Science & TechnologyDalian University of TechnologyDalian116024China
| | - Disheng Feng
- CAS Key Laboratory of Separation Science for Analytical ChemistryDalian Institute of Chemical PhysicsChinese Academy of Sciences457 Zhongshan RoadDalian116023China
- University of Chinese Academy of SciencesBeijing100049China
| | - Wangjie Lv
- CAS Key Laboratory of Separation Science for Analytical ChemistryDalian Institute of Chemical PhysicsChinese Academy of Sciences457 Zhongshan RoadDalian116023China
- University of Chinese Academy of SciencesBeijing100049China
| | - Qiuhui Xuan
- CAS Key Laboratory of Separation Science for Analytical ChemistryDalian Institute of Chemical PhysicsChinese Academy of Sciences457 Zhongshan RoadDalian116023China
- University of Chinese Academy of SciencesBeijing100049China
| | - Lichao Wang
- CAS Key Laboratory of Separation Science for Analytical ChemistryDalian Institute of Chemical PhysicsChinese Academy of Sciences457 Zhongshan RoadDalian116023China
- University of Chinese Academy of SciencesBeijing100049China
| | - Di Yu
- CAS Key Laboratory of Separation Science for Analytical ChemistryDalian Institute of Chemical PhysicsChinese Academy of Sciences457 Zhongshan RoadDalian116023China
- University of Chinese Academy of SciencesBeijing100049China
| | - Qingqing Wang
- CAS Key Laboratory of Separation Science for Analytical ChemistryDalian Institute of Chemical PhysicsChinese Academy of Sciences457 Zhongshan RoadDalian116023China
- University of Chinese Academy of SciencesBeijing100049China
| | - Xiaohui Lin
- School of Computer Science & TechnologyDalian University of TechnologyDalian116024China
| | - Tangchun Wu
- MOE Key Lab of Environment and HealthSchool of Public HealthTongji Medical CollegeHuazhong University of Science & TechnologyWuhanHubei430030China
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical ChemistryDalian Institute of Chemical PhysicsChinese Academy of Sciences457 Zhongshan RoadDalian116023China
- University of Chinese Academy of SciencesBeijing100049China
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22
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Barragán-Álvarez CP, Padilla-Camberos E, Díaz NF, Cota-Coronado A, Hernández-Jiménez C, Bravo-Reyna CC, Díaz-Martínez NE. Loss of Znt8 function in diabetes mellitus: risk or benefit? Mol Cell Biochem 2021; 476:2703-2718. [PMID: 33666829 DOI: 10.1007/s11010-021-04114-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Accepted: 02/18/2021] [Indexed: 12/13/2022]
Abstract
The zinc transporter 8 (ZnT8) plays an essential role in zinc homeostasis inside pancreatic β cells, its function is related to the stabilization of insulin hexameric form. Genome-wide association studies (GWAS) have established a positive and negative relationship of ZnT8 variants with type 2 diabetes mellitus (T2DM), exposing a dual and controversial role. The first hypotheses about its role in T2DM indicated a higher risk of developing T2DM for loss of function; nevertheless, recent GWAS of ZnT8 loss-of-function mutations in humans have shown protection against T2DM. With regard to the ZnT8 role in T2DM, most studies have focused on rodent models and common high-risk variants; however, considerable differences between human and rodent models have been found and the new approaches have included lower-frequency variants as a tool to clarify gene functions, allowing a better understanding of the disease and offering possible therapeutic targets. Therefore, this review will discuss the physiological effects of the ZnT8 variants associated with a major and lower risk of T2DM, emphasizing the low- and rare-frequency variants.
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Affiliation(s)
- Carla P Barragán-Álvarez
- Biotecnología Médica y Farmacéutica, Centro de Investigación y Asistencia en Tecnología y Diseño del Estado de Jalisco, Guadalajara, Mexico
| | - Eduardo Padilla-Camberos
- Biotecnología Médica y Farmacéutica, Centro de Investigación y Asistencia en Tecnología y Diseño del Estado de Jalisco, Guadalajara, Mexico
| | - Nestor F Díaz
- Departamento de Fisiología y Desarrollo Celular, Instituto Nacional de Perinatología, Mexico City, Mexico
| | - Agustín Cota-Coronado
- Biotecnología Médica y Farmacéutica, Centro de Investigación y Asistencia en Tecnología y Diseño del Estado de Jalisco, Guadalajara, Mexico
| | - Claudia Hernández-Jiménez
- Departamento de Cirugía Experimental, Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Mexico City, Mexico
| | - Carlos C Bravo-Reyna
- Departamento de Cirugía Experimental, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Nestor E Díaz-Martínez
- Biotecnología Médica y Farmacéutica, Centro de Investigación y Asistencia en Tecnología y Diseño del Estado de Jalisco, Guadalajara, Mexico.
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23
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Incretin Hormones in Obesity and Related Cardiometabolic Disorders: The Clinical Perspective. Nutrients 2021; 13:nu13020351. [PMID: 33503878 PMCID: PMC7910956 DOI: 10.3390/nu13020351] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 01/21/2021] [Accepted: 01/22/2021] [Indexed: 02/06/2023] Open
Abstract
The prevalence of obesity continues to grow rapidly worldwide, posing many public health challenges of the 21st century. Obese subjects are at major risk for serious diet-related noncommunicable diseases, including type 2 diabetes mellitus, cardiovascular disease, and non-alcoholic fatty liver disease. Understanding the mechanisms underlying obesity pathogenesis is needed for the development of effective treatment strategies. Dysregulation of incretin secretion and actions has been observed in obesity and related metabolic disorders; therefore, incretin-based therapies have been developed to provide new therapeutic options. Incretin mimetics present glucose-lowering properties, together with a reduction of appetite and food intake, resulting in weight loss. In this review, we describe the physiology of two known incretins—glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1), and their role in obesity and related cardiometabolic disorders. We also focus on the available and incoming incretin-based medications that can be used in the treatment of the above-mentioned conditions.
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24
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Sayed S, Nabi AHMN. Diabetes and Genetics: A Relationship Between Genetic Risk Alleles, Clinical Phenotypes and Therapeutic Approaches. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1307:457-498. [PMID: 32314317 DOI: 10.1007/5584_2020_518] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Unveiling human genome through successful completion of Human Genome Project and International HapMap Projects with the advent of state of art technologies has shed light on diseases associated genetic determinants. Identification of mutational landscapes such as copy number variation, single nucleotide polymorphisms or variants in different genes and loci have revealed not only genetic risk factors responsible for diseases but also region(s) playing protective roles. Diabetes is a global health concern with two major types - type 1 diabetes (T1D) and type 2 diabetes (T2D). Great progress in understanding the underlying genetic predisposition to T1D and T2D have been made by candidate gene studies, genetic linkage studies, genome wide association studies with substantial number of samples. Genetic information has importance in predicting clinical outcomes. In this review, we focus on recent advancement regarding candidate gene(s) associated with these two traits along with their clinical parameters as well as therapeutic approaches perceived. Understanding genetic architecture of these disease traits relating clinical phenotypes would certainly facilitate population stratification in diagnosing and treating T1D/T2D considering the doses and toxicity of specific drugs.
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Affiliation(s)
- Shomoita Sayed
- Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, Bangladesh
| | - A H M Nurun Nabi
- Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, Bangladesh.
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25
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Powe CE, Udler MS, Hsu S, Allard C, Kuang A, Manning AK, Perron P, Bouchard L, Lowe WL, Scholtens D, Florez JC, Hivert MF. Genetic Loci and Physiologic Pathways Involved in Gestational Diabetes Mellitus Implicated Through Clustering. Diabetes 2021; 70:268-281. [PMID: 33051273 PMCID: PMC7876560 DOI: 10.2337/db20-0772] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2020] [Accepted: 10/08/2020] [Indexed: 12/17/2022]
Abstract
Hundreds of common genetic variants acting through distinguishable physiologic pathways influence the risk of type 2 diabetes (T2D). It is unknown to what extent the physiology underlying gestational diabetes mellitus (GDM) is distinct from that underlying T2D. In this study of >5,000 pregnant women from three cohorts, we aimed to identify physiologically related groups of maternal variants associated with GDM using two complementary approaches that were based on Bayesian nonnegative matrix factorization (bNMF) clustering. First, we tested five bNMF clusters of maternal T2D-associated variants grouped on the basis of physiology outside of pregnancy for association with GDM. We found that cluster polygenic scores representing genetic determinants of reduced β-cell function and abnormal hepatic lipid metabolism were associated with GDM; these clusters were not associated with infant birth weight. Second, we derived bNMF clusters of maternal variants on the basis of pregnancy physiology and tested these clusters for association with GDM. We identified a cluster that was strongly associated with GDM as well as associated with higher infant birth weight. The effect size for this cluster's association with GDM appeared greater than that for T2D. Our findings imply that the genetic and physiologic pathways that lead to GDM differ, at least in part, from those that lead to T2D.
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Affiliation(s)
- Camille E Powe
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA
- Broad Institute, Cambridge, MA
- Harvard Medical School, Boston, MA
| | - Miriam S Udler
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA
- Broad Institute, Cambridge, MA
- Harvard Medical School, Boston, MA
| | - Sarah Hsu
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA
- Broad Institute, Cambridge, MA
| | - Catherine Allard
- Centre de Recherche du Centre Hospitalier, Université de Sherbrooke, Sherbrooke, Quebec, Canada
| | - Alan Kuang
- Division of Biostatistics, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Alisa K Manning
- Broad Institute, Cambridge, MA
- Harvard Medical School, Boston, MA
- Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA
| | - Patrice Perron
- Department of Medicine, Université de Sherbrooke, Quebec, Canada
| | - Luigi Bouchard
- Centre de Recherche du Centre Hospitalier, Université de Sherbrooke, Sherbrooke, Quebec, Canada
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, Quebec, Canada
- Department of Medical Biology, CIUSSS Saguenay-Lac-Saint-Jean-Hôpital Universitaire de Chicoutimi, Saguenay, Quebec, Canada
| | - William L Lowe
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Denise Scholtens
- Division of Biostatistics, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Jose C Florez
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA
- Broad Institute, Cambridge, MA
- Harvard Medical School, Boston, MA
| | - Marie-France Hivert
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA
- Harvard Medical School, Boston, MA
- Department of Medicine, Université de Sherbrooke, Quebec, Canada
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA
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26
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Song C, Ding C, Yuan F, Feng G, Ma Y, Liu A. Ten SNPs May Affect Type 2 Diabetes Risk in Interaction with Prenatal Exposure to Chinese Famine. Nutrients 2020; 12:E3880. [PMID: 33353041 PMCID: PMC7766924 DOI: 10.3390/nu12123880] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 12/03/2020] [Accepted: 12/14/2020] [Indexed: 12/01/2022] Open
Abstract
Increasing studies have demonstrated that gene and famine may interact on type 2 diabetes risk. The data derived from the cross-sectional 2010-2012 China National Nutrition and Health Survey (CNNHS) was examined to explore whether gene and famine interacted to influence type 2 diabetes risk. In total, 2216 subjects were involved. The subjects born in 1960 and 1961 were selected as the famine-exposed group, whereas subjects born in 1963 were selected as the unexposed group. A Mass Array system was used to detect the genotypes of 50 related single-nucleotide polymorphisms (SNPs). Interactions were found between prenatal exposure to famine and ten SNPs (rs10401969, rs10886471, rs10946398, rs1470579, rs2796441, rs340874, rs3794991, rs5015480, rs7961581, and rs9470794) on type 2 diabetes risk after adjustments. The stratified results showed that famine exposure exacerbated the effect of CILP2-rs10401969 to fasting serum insulin (FINS), GRK5-rs10886471 to fasting plasma glucose (FPG) and FINS, IGF2BP2-rs1470579 to FINS, TLE1-rs2796441 to impaired fasting glucose (IFG), PROX1-rs340874 to impaired glucose tolerance (IGT), GATAD2A-rs3794991 to FINS, TSPAN8/LGR5-rs7961581 to FPG, and ZFAND3-rs9470794 to IGT and FINS. Famine exposure weakened the effect of CDKAL1-rs10946398 to type 2 diabetes. Famine exposure weakened the effect of HHEX-rs5015480 to IFG, but exacerbated the effect of HHEX-rs5015480 to FINS. The present study suggests that ten SNPs may affect type 2 diabetes risk in interaction with prenatal exposure to Chinese famine.
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Affiliation(s)
| | | | | | | | | | - Ailing Liu
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China; (C.S.); (C.D.); (F.Y.); (G.F.); (Y.M.)
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27
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Hook SC, Chadt A, Heesom KJ, Kishida S, Al-Hasani H, Tavaré JM, Thomas EC. TBC1D1 interacting proteins, VPS13A and VPS13C, regulate GLUT4 homeostasis in C2C12 myotubes. Sci Rep 2020; 10:17953. [PMID: 33087848 PMCID: PMC7578007 DOI: 10.1038/s41598-020-74661-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Accepted: 09/07/2020] [Indexed: 01/01/2023] Open
Abstract
Proteins involved in the spaciotemporal regulation of GLUT4 trafficking represent potential therapeutic targets for the treatment of insulin resistance and type 2 diabetes. A key regulator of insulin- and exercise-stimulated glucose uptake and GLUT4 trafficking is TBC1D1. This study aimed to identify proteins that regulate GLUT4 trafficking and homeostasis via TBC1D1. Using an unbiased quantitative proteomics approach, we identified proteins that interact with TBC1D1 in C2C12 myotubes including VPS13A and VPS13C, the Rab binding proteins EHBP1L1 and MICAL1, and the calcium pump SERCA1. These proteins associate with TBC1D1 via its phosphotyrosine binding (PTB) domains and their interactions with TBC1D1 were unaffected by AMPK activation, distinguishing them from the AMPK regulated interaction between TBC1D1 and AMPKα1 complexes. Depletion of VPS13A or VPS13C caused a post-transcriptional increase in cellular GLUT4 protein and enhanced cell surface GLUT4 levels in response to AMPK activation. The phenomenon was specific to GLUT4 because other recycling proteins were unaffected. Our results provide further support for a role of the TBC1D1 PTB domains as a scaffold for a range of Rab regulators, and also the VPS13 family of proteins which have been previously linked to fasting glycaemic traits and insulin resistance in genome wide association studies.
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Affiliation(s)
- Sharon C Hook
- School of Biochemistry, Biomedical Sciences Building, University of Bristol, University Walk, Bristol, BS8 1TD, UK
| | - Alexandra Chadt
- Institute of Clinical Biochemistry and Pathobiochemistry, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Medical Faculty, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Kate J Heesom
- School of Biochemistry, Biomedical Sciences Building, University of Bristol, University Walk, Bristol, BS8 1TD, UK
| | - Shosei Kishida
- Department of Biochemistry and Genetics, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan
| | - Hadi Al-Hasani
- Institute of Clinical Biochemistry and Pathobiochemistry, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Medical Faculty, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Jeremy M Tavaré
- School of Biochemistry, Biomedical Sciences Building, University of Bristol, University Walk, Bristol, BS8 1TD, UK
| | - Elaine C Thomas
- School of Biochemistry, Biomedical Sciences Building, University of Bristol, University Walk, Bristol, BS8 1TD, UK.
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28
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Halama A, Suleiman NN, Kulinski M, Bettahi I, Hassoun S, Alkasem M, Abdalhakam I, Iskandarani A, Samra TA, Atkin SL, Suhre K, Abou-Samra AB. The metabolic footprint of compromised insulin sensitivity under fasting and hyperinsulinemic-euglycemic clamp conditions in an Arab population. Sci Rep 2020; 10:17164. [PMID: 33051490 PMCID: PMC7555540 DOI: 10.1038/s41598-020-73723-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Accepted: 09/15/2020] [Indexed: 11/29/2022] Open
Abstract
Metabolic pathways that are corrupted at early stages of insulin resistance (IR) remain elusive. This study investigates changes in body metabolism in clinically healthy and otherwise asymptomatic subjects that may become apparent already under compromised insulin sensitivity (IS) and prior to IR. 47 clinically healthy Arab male subjects with a broad range of IS, determined by hyperinsulinemic-euglycemic clamp (HIEC), were investigated. Untargeted metabolomics and complex lipidomics were conducted on serum samples collected under fasting and HIEC conditions. Linear models were used to identify associations between metabolites concentrations and IS levels. Among 1896 identified metabolites, 551 showed significant differences between fasting and HIEC, reflecting the metabolic switch in energy utilization. At fasting, 336 metabolites, predominantly di- and tri-acylglycerols, showed significant differences between subjects with low and high levels of IS. Changes in amino acid, carbohydrate and fatty acid metabolism in response to insulin were impaired in subjects with low IS. Association of altered mannose and amino acids with IS was also replicated in an independent cohort of T2D patients. We identified metabolic phenotypes that characterize clinically healthy Arab subjects with low levels of IS at their fasting state. Our study is providing further insights into the metabolic pathways that precede IR.
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Affiliation(s)
- Anna Halama
- Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Doha, Qatar.
| | - Noor N Suleiman
- Department of Internal Medicine, Qatar Metabolic Institute, Hamad Medical Corporation, Doha, Qatar
| | - Michal Kulinski
- Translational Research Institute, Academic Health System, Hamad Medical Corporation, Doha, Qatar
| | - Ilham Bettahi
- Department of Internal Medicine, Qatar Metabolic Institute, Hamad Medical Corporation, Doha, Qatar.,Translational Research Institute, Academic Health System, Hamad Medical Corporation, Doha, Qatar
| | - Shaimaa Hassoun
- Department of Internal Medicine, Qatar Metabolic Institute, Hamad Medical Corporation, Doha, Qatar
| | - Meis Alkasem
- Department of Internal Medicine, Qatar Metabolic Institute, Hamad Medical Corporation, Doha, Qatar.,Translational Research Institute, Academic Health System, Hamad Medical Corporation, Doha, Qatar
| | - Ibrahem Abdalhakam
- Department of Internal Medicine, Qatar Metabolic Institute, Hamad Medical Corporation, Doha, Qatar
| | - Ahmad Iskandarani
- Department of Internal Medicine, Qatar Metabolic Institute, Hamad Medical Corporation, Doha, Qatar.,Translational Research Institute, Academic Health System, Hamad Medical Corporation, Doha, Qatar
| | - Tareq A Samra
- Department of Internal Medicine, Qatar Metabolic Institute, Hamad Medical Corporation, Doha, Qatar.,Translational Research Institute, Academic Health System, Hamad Medical Corporation, Doha, Qatar
| | - Stephen L Atkin
- Weill Cornell Medicine-Qatar, Doha, Qatar.,Royal College of Surgeons in Ireland, Busaiteen, Bahrain
| | - Karsten Suhre
- Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Doha, Qatar.
| | - Abdul Badi Abou-Samra
- Department of Internal Medicine, Qatar Metabolic Institute, Hamad Medical Corporation, Doha, Qatar. .,Weill Cornell Medicine-Qatar, Doha, Qatar.
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29
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Abstract
The term phenotype is so commonly used that we often assume that we each mean the same thing. The general definition, the set of observable characteristics of an individual resulting from the interaction of their genotype with the environment, is often left to the eye of the beholder. Whether applied to the multiple levels of biological phenomena or the intact human being, our ability to characterize, classify, and analyze phenotype has been limited by measurement deficits, computing limitations, and a culture that avoids the generalizable. With the advent of modern technology, there is the potential for a revolution in phenotyping, which incorporates old and new in structured ways to dramatically advance basic understanding of biology and behavior and to lead to major improvements in clinical care and public health. This revolution in how we think about phenotypes will require a radical change in the scale at which biomedicine operates with significant changes in the unit of action, which will have far-reaching implications for how care, translation, and discovery are implemented.
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Affiliation(s)
- Calum A MacRae
- From the One Brave Idea (C.A.M., R.M.C.).,Cardiovascular Medicine Division and Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (C.A.M.)
| | - Robert M Califf
- From the One Brave Idea (C.A.M., R.M.C.).,Verily Life Sciences (R.M.C.).,Google Health, South San Francisco and Mountain View, CA (R.M.C.)
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30
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Goodarzi MO, Palmer ND, Cui J, Guo X, Chen YDI, Taylor KD, Raffel LJ, Wagenknecht LE, Buchanan TA, Hsueh WA, Rotter JI. Classification of Type 2 Diabetes Genetic Variants and a Novel Genetic Risk Score Association With Insulin Clearance. J Clin Endocrinol Metab 2020; 105:dgz198. [PMID: 31714576 PMCID: PMC7059988 DOI: 10.1210/clinem/dgz198] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Accepted: 11/11/2019] [Indexed: 12/16/2022]
Abstract
CONTEXT Genome-wide association studies have identified more than 450 single nucleotide polymorphisms (SNPs) for type 2 diabetes (T2D). OBJECTIVE To facilitate use of these SNPs in future genetic risk score (GRS)-based analyses, we aimed to classify the SNPs based on physiology. We also sought to validate GRS associations with insulin-related traits in deeply phenotyped Mexican Americans. DESIGN, SETTING, AND PARTICIPANTS A total of 457 T2D SNPs from the literature were assigned physiologic function based on association studies and cluster analyses. All SNPs (All-GRS), beta-cell (BC-GRS), insulin resistance (IR-GRS), lipodystrophy (Lipo-GRS), and body mass index plus lipids (B + L-GRS) were evaluated for association with diabetes and indices of insulin secretion (from oral glucose tolerance test), insulin sensitivity and insulin clearance (from euglycemic clamp), and adiposity and lipid markers in 1587 Mexican Americans. RESULTS Of the 457 SNPs, 52 were classified as BC, 30 as IR, 12 as Lipo, 12 as B + L, whereas physiologic function of 351 was undefined. All-GRS was strongly associated with T2D. Among nondiabetic Mexican Americans, BC-GRS was associated with reduced insulinogenic index, IR-GRS was associated with reduced insulin sensitivity, and Lipo-GRS was associated with reduced adiposity. B + L-GRS was associated with increased insulin clearance. The latter did not replicate in an independent cohort wherein insulin clearance was assessed by a different method. CONCLUSIONS Supporting their utility, BC-GRS, IR-GRS, and Lipo-GRS, based on SNPs discovered largely in Europeans, exhibited expected associations in Mexican Americans. The novel association of B + L-GRS with insulin clearance suggests that impaired ability to reduce insulin clearance in compensation for IR may play a role in the pathogenesis of T2D. Whether this applies to other ethnic groups remains to be determined.
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Affiliation(s)
- Mark O Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, US
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, US
| | - Jinrui Cui
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, US
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, California, US
| | - Yii-Der I Chen
- Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, California, US
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, California, US
| | - Leslie J Raffel
- Division of Genetic and Genomic Medicine, Department of Pediatrics, University of California, Irvine, US
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, US
| | - Thomas A Buchanan
- Department of Physiology and Biophysics and Department of Medicine, Keck School of Medicine of USC, Los Angeles, California, US
| | - Willa A Hsueh
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Wexner Medical Center, The Ohio State University, Columbus, US
| | - Jerome I Rotter
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, US
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Sangwung P, Petersen KF, Shulman GI, Knowles JW. Mitochondrial Dysfunction, Insulin Resistance, and Potential Genetic Implications. Endocrinology 2020; 161:bqaa017. [PMID: 32060542 PMCID: PMC7341556 DOI: 10.1210/endocr/bqaa017] [Citation(s) in RCA: 100] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Revised: 01/30/2020] [Accepted: 02/13/2020] [Indexed: 02/06/2023]
Abstract
Insulin resistance (IR) is fundamental to the development of type 2 diabetes (T2D) and is present in most prediabetic (preDM) individuals. Insulin resistance has both heritable and environmental determinants centered on energy storage and metabolism. Recent insights from human genetic studies, coupled with comprehensive in vivo and ex vivo metabolic studies in humans and rodents, have highlighted the critical role of reduced mitochondrial function as a predisposing condition for ectopic lipid deposition and IR. These studies support the hypothesis that reduced mitochondrial function, particularly in insulin-responsive tissues such as skeletal muscle, white adipose tissue, and the liver, is inextricably linked to tissue and whole body IR through the effects on cellular energy balance. Here we discuss these findings as well as address potential mechanisms that serve as the nexus between mitochondrial malfunction and IR.
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Affiliation(s)
- Panjamaporn Sangwung
- Stanford Division of Cardiovascular Medicine and Cardiovascular Institute, Stanford University, Stanford, California
- Stanford Diabetes Research Center, Stanford University, Stanford, California
| | - Kitt Falk Petersen
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
- Department of Cellular & Molecular Physiology, Yale School of Medicine, New Haven, Connecticut
- Yale Diabetes Research Center, Yale School of Medicine, New Haven, Connecticut
| | - Gerald I Shulman
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
- Department of Cellular & Molecular Physiology, Yale School of Medicine, New Haven, Connecticut
- Yale Diabetes Research Center, Yale School of Medicine, New Haven, Connecticut
| | - Joshua W Knowles
- Stanford Division of Cardiovascular Medicine and Cardiovascular Institute, Stanford University, Stanford, California
- Stanford Diabetes Research Center, Stanford University, Stanford, California
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Krentz NAJ, Gloyn AL. Insights into pancreatic islet cell dysfunction from type 2 diabetes mellitus genetics. Nat Rev Endocrinol 2020; 16:202-212. [PMID: 32099086 DOI: 10.1038/s41574-020-0325-0] [Citation(s) in RCA: 77] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/17/2020] [Indexed: 12/30/2022]
Abstract
Type 2 diabetes mellitus (T2DM) is an increasingly prevalent multifactorial disease that has both genetic and environmental risk factors, resulting in impaired glucose homeostasis. Genome-wide association studies (GWAS) have identified over 400 genetic signals that are associated with altered risk of T2DM. Human physiology and epigenomic data support a central role for the pancreatic islet in the pathogenesis of T2DM. This Review focuses on the promises and challenges of moving from genetic associations to molecular mechanisms and highlights efforts to identify the causal variant and effector transcripts at T2DM GWAS susceptibility loci. In addition, we examine current human models that are used to study both β-cell development and function, including EndoC-β cell lines and human induced pluripotent stem cell-derived β-like cells. We use examples of four T2DM susceptibility loci (CDKAL1, MTNR1B, SLC30A8 and PAM) to emphasize how a holistic approach involving genetics, physiology, and cellular and developmental biology can disentangle disease mechanisms at T2DM GWAS signals.
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Affiliation(s)
- Nicole A J Krentz
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
| | - Anna L Gloyn
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
- NIHR Oxford Biomedical Research Centre, Churchill Hospital, Oxford, UK.
- Stanford Diabetes Research Centre, Stanford University, Stanford, CA, USA.
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Elman I, Howard M, Borodovsky JT, Mysels D, Rott D, Borsook D, Albanese M. Metabolic and Addiction Indices in Patients on Opioid Agonist Medication-Assisted Treatment: A Comparison of Buprenorphine and Methadone. Sci Rep 2020; 10:5617. [PMID: 32221389 PMCID: PMC7101411 DOI: 10.1038/s41598-020-62556-0] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Accepted: 03/03/2020] [Indexed: 12/18/2022] Open
Abstract
Metabolic hormones stabilize brain reward and motivational circuits, whereas excessive opioid consumption counteracts this effect and may impair metabolic function. Here we addressed the role of metabolic processes in the course of the agonist medication-assisted treatment for opioid use disorder (OUD) with buprenorphine or methadone. Plasma lipids, hemoglobin A1C, body composition, the oral glucose tolerance test (oGTT) and the Sweet Taste Test (STT) were measured in buprenorphine- (n = 26) or methadone (n = 32)- treated subjects with OUD. On the whole, the subjects in both groups were overweight or obese and insulin resistant; they displayed similar oGTT and STT performance. As compared to methadone-treated subjects, those on buprenorphine had significantly lower rates of metabolic syndrome (MetS) along with better values of the high-density lipoproteins (HDL). Subjects with- vs. without MetS tended to have greater addiction severity. Correlative analyses revealed that more buprenorphine exposure duration was associated with better HDL and opioid craving values. In contrast, more methadone exposure duration was associated with worse triglycerides-, HDL-, blood pressure-, fasting glucose- and hemoglobin A1C values. Buprenorphine appears to produce beneficial HDL- and craving effects and, contrary to methadone, its role in the metabolic derangements is not obvious. Our data call for further research aimed at understanding the distinctive features of buprenorphine metabolic effects vis-à-vis those of methadone and their potential role in these drugs' unique therapeutic profiles.
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Affiliation(s)
- Igor Elman
- Center for Pain and the Brain, Department of Anesthesia, Critical Care and Pain Medicine, Boston Children's Hospital, Boston, MA, USA.
| | - Margaret Howard
- Rhode Island Department of Behavioral Healthcare, Cranston, RI, USA
| | - Jacob T Borodovsky
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - David Mysels
- Department of Psychiatry, Alpert Medical School of Brown University, Providence, RI, USA
| | - David Rott
- Department of Cardiology, Sheba Medical Center, Sackler School of Medicine, Tel Aviv, Israel
| | - David Borsook
- Center for Pain and the Brain, Department of Anesthesia, Critical Care and Pain Medicine, Boston Children's Hospital, Massachusetts General Hospital and McLean Hospital, Harvard Medical School, Boston, MA, USA
| | - Mark Albanese
- Cambridge Health Alliance, Harvard Medical School, Cambridge, MA, USA
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Mattis KK, Gloyn AL. From Genetic Association to Molecular Mechanisms for Islet-cell Dysfunction in Type 2 Diabetes. J Mol Biol 2020; 432:1551-1578. [PMID: 31945378 DOI: 10.1016/j.jmb.2019.12.045] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Revised: 12/15/2019] [Accepted: 12/17/2019] [Indexed: 12/30/2022]
Abstract
Genome-wide association studies (GWAS) have identified over 400 signals robustly associated with risk for type 2 diabetes (T2D). At the vast majority of these loci, the lead single nucleotide polymorphisms (SNPs) reside in noncoding regions of the genome, which hampers biological inference and translation of genetic discoveries into disease mechanisms. The study of these T2D risk variants in normoglycemic individuals has revealed that a significant proportion are exerting their disease risk through islet-cell dysfunction. The central role of the islet is also demonstrated by numerous studies, which have shown an enrichment of these signals in islet-specific epigenomic annotations. In recent years the emergence of authentic human beta-cell lines, and advances in genome-editing technologies coupled with improved protocols differentiating human pluripotent stem cells into beta-like cells has opened up new opportunities for T2D disease modeling. Here we review the current understanding on the genetic basis of T2D focusing on approaches, which have facilitated the identification of causal variants and their effector transcripts in human islets. We will present examples of functional studies based on animal and conventional cellular systems and highlight the potential of novel stem cell-based T2D disease models.
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Affiliation(s)
- Katia K Mattis
- Oxford Centre for Diabetes Endocrinology & Metabolism, University of Oxford, UK
| | - Anna L Gloyn
- Oxford Centre for Diabetes Endocrinology & Metabolism, University of Oxford, UK; Wellcome Trust Centre for Human Genetics, University of Oxford, UK; National Institute of Health Research, Biomedical Research Centre, Churchill Hospital, Headington, Oxford, UK.
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35
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Barbosa-Yañez RL, Markova M, Dambeck U, Honsek C, Machann J, Schüler R, Kabisch S, Pfeiffer AFH. Predictive effect of GIPR SNP rs10423928 on glucose metabolism liver fat and adiposity in prediabetic and diabetic subjects. Peptides 2020; 125:170237. [PMID: 31874232 DOI: 10.1016/j.peptides.2019.170237] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2019] [Revised: 12/15/2019] [Accepted: 12/18/2019] [Indexed: 11/22/2022]
Abstract
The gastric inhibitory polypeptide receptor (GIPR) regulates postprandial metabolism. In this context GIPR SNP rs10423928 seems toplay an important role in modulating glucose metabolism and insulinsensitivity. However, evidence regarding thisparticular SNP is still vague. In this study, we collected baseline data from four different dietaryintervention studies. We genotyped 424 subjects with prediabetes and 73with diabetes for GIPR SNP rs10423928 and examined its impact on glucosemetabolism, insulin sensitivity and body fat accumulation. We extended previous data by showing that carriers of the A allele withprediabetes displayed increased fasting glucose (p = 0.015). Unexpectedly,A allele carriers showed lower glucose levels 2 h (p = 0.021) after anoral glucose challenge compared to T/T homozygous individuals. A allelecarriers also showed significantly higher insulin sensitivity (p < 0.001)(assessed by Cederholm Index), indicating an enhanced ß-cell response. This study points to a potential protective role for rs10423928 inglucose metabolism and insulin sensitivity in subjects with prediabetes.Further studies are necessary to confirm these results.
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Affiliation(s)
- Renate Luzía Barbosa-Yañez
- Department of Clinical Nutrition, German Institute of Human Nutrition, Potsdam-Rehbruecke, 14558, Nuthetal, Germany; German Center for Diabetes Research (Deutsches Zentrum für Diabetesforschung e.V.), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany; Department of Endocrinology, Diabetes and Nutrition, Campus Benjamin Franklin, Charité University Medicine, Hindenburgdamm 30, 12203, Berlin, Germany.
| | - Mariya Markova
- Department of Clinical Nutrition, German Institute of Human Nutrition, Potsdam-Rehbruecke, 14558, Nuthetal, Germany; German Center for Diabetes Research (Deutsches Zentrum für Diabetesforschung e.V.), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
| | - Ulrike Dambeck
- Department of Clinical Nutrition, German Institute of Human Nutrition, Potsdam-Rehbruecke, 14558, Nuthetal, Germany; German Center for Diabetes Research (Deutsches Zentrum für Diabetesforschung e.V.), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany; Department of Endocrinology, Diabetes and Nutrition, Campus Benjamin Franklin, Charité University Medicine, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Caroline Honsek
- Department of Clinical Nutrition, German Institute of Human Nutrition, Potsdam-Rehbruecke, 14558, Nuthetal, Germany; German Center for Diabetes Research (Deutsches Zentrum für Diabetesforschung e.V.), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany; Department of Endocrinology, Diabetes and Nutrition, Campus Benjamin Franklin, Charité University Medicine, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Jürgen Machann
- German Center for Diabetes Research (Deutsches Zentrum für Diabetesforschung e.V.), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany; Institute of Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, 72076, Tübingen, Germany; Section on Experimental Radiology, Department of Diagnostic and Interventional Radiology, University Hospital Tübingen, 72076, Tübingen, Germany
| | - Rita Schüler
- Department of Clinical Nutrition, German Institute of Human Nutrition, Potsdam-Rehbruecke, 14558, Nuthetal, Germany; German Center for Diabetes Research (Deutsches Zentrum für Diabetesforschung e.V.), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
| | - Stefan Kabisch
- Department of Clinical Nutrition, German Institute of Human Nutrition, Potsdam-Rehbruecke, 14558, Nuthetal, Germany; German Center for Diabetes Research (Deutsches Zentrum für Diabetesforschung e.V.), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany; Department of Endocrinology, Diabetes and Nutrition, Campus Benjamin Franklin, Charité University Medicine, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Andreas F H Pfeiffer
- Department of Clinical Nutrition, German Institute of Human Nutrition, Potsdam-Rehbruecke, 14558, Nuthetal, Germany; German Center for Diabetes Research (Deutsches Zentrum für Diabetesforschung e.V.), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany; Department of Endocrinology, Diabetes and Nutrition, Campus Benjamin Franklin, Charité University Medicine, Hindenburgdamm 30, 12203, Berlin, Germany
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Jang HB, Go MJ, Park SI, Lee HJ, Cho SB. Chronic heavy alcohol consumption influences the association between genetic variants of GCK or INSR and the development of diabetes in men: A 12-year follow-up study. Sci Rep 2019; 9:20029. [PMID: 31882596 PMCID: PMC6934767 DOI: 10.1038/s41598-019-56011-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Accepted: 12/03/2019] [Indexed: 12/17/2022] Open
Abstract
Chronic heavy alcohol consumption is a risk factor for diabetes, which is characterized by impaired β-cell function and insulin resistance. We aimed to determine whether the longitudinal associations between genetic variants of glucokinase (GCK) and insulin receptor (INSR) and the risk of developing diabetes were influenced by chronic heavy alcohol consumption. Data were obtained from the Korean Genome and Epidemiology Study. To identify candidate variants, 1,520 subjects (726 non-drinkers and 794 heavy drinkers) were included in the baseline cross-sectional study. After excluding patients with diabetes at baseline and those with insufficient data on diabetes incidence, prospective analyses were conducted in 773 subjects (353 non-drinkers and 420 heavy drinkers). In the baseline cross-sectional study, one SNP (rs758989) in GCK and four SNPs (rs7245757, rs1035942, rs1035940, and rs2042901) in INSR were selected as candidate SNPs that interact with alcohol to affect prediabetes and diabetes. We identified that these GCK and INSR polymorphisms are affected by chronic heavy alcohol consumption and have an effect on the incidence of diabetes. The incidence of diabetes was increased in chronic heavy alcohol drinkers carrying the C allele of GCK compared with never-drinkers with the C allele (HR, 2.15; 95% CI 1.30-3.57), and was increased in chronic heavy alcohol drinkers who were not carrying the INSR haplotype (-/-) compared with never-drinkers carrying the AACT haplotype (HR, 1.98; 95% CI 1.24-3.18). Moreover, we observed that the aggravating effects on the late insulin secretion (I/G120 and I/G AUC 60-120) in individuals who were chronic heavy drinkers with C allele of GCK. In the INSR haplotype, chronic heavy drinkers not carrying AACT were associated with lower disposition index. These results potentially suggest that chronic heavy alcohol consumption induce β-cell dysfunction partially mediated by decreased GCK expression or decline of insulin sensitivity via inhibition of INSR, thereby contributing to the development of diabetes.
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Affiliation(s)
- Han Byul Jang
- Center for Biomedical Science, Korea National Institute of Health, Cheongju, Chungcheongbuk-do, Republic of Korea
| | - Min Jin Go
- Center for Genome Science, Korea National Institute of Health, Cheongju, Chungcheongbuk-do, Republic of Korea
| | - Sang Ick Park
- Center for Biomedical Science, Korea National Institute of Health, Cheongju, Chungcheongbuk-do, Republic of Korea
| | - Hye-Ja Lee
- Center for Biomedical Science, Korea National Institute of Health, Cheongju, Chungcheongbuk-do, Republic of Korea.
| | - Seong Beom Cho
- Center for Genome Science, Korea National Institute of Health, Cheongju, Chungcheongbuk-do, Republic of Korea.
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Lytrivi M, Castell AL, Poitout V, Cnop M. Recent Insights Into Mechanisms of β-Cell Lipo- and Glucolipotoxicity in Type 2 Diabetes. J Mol Biol 2019; 432:1514-1534. [PMID: 31628942 DOI: 10.1016/j.jmb.2019.09.016] [Citation(s) in RCA: 219] [Impact Index Per Article: 43.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2019] [Revised: 09/15/2019] [Accepted: 09/16/2019] [Indexed: 12/24/2022]
Abstract
The deleterious effects of chronically elevated free fatty acid (FFA) levels on glucose homeostasis are referred to as lipotoxicity, and the concurrent exposure to high glucose may cause synergistic glucolipotoxicity. Lipo- and glucolipotoxicity have been studied for over 25 years. Here, we review the current evidence supporting the role of pancreatic β-cell lipo- and glucolipotoxicity in type 2 diabetes (T2D), including lipid-based interventions in humans, prospective epidemiological studies, and human genetic findings. In addition to total FFA quantity, the quality of FFAs (saturation and chain length) is a key determinant of lipotoxicity. We discuss in vitro and in vivo experimental models to investigate lipo- and glucolipotoxicity in β-cells and describe experimental pitfalls. Lipo- and glucolipotoxicity adversely affect many steps of the insulin production and secretion process. The molecular mechanisms underpinning lipo- and glucolipotoxic β-cell dysfunction and death comprise endoplasmic reticulum stress, oxidative stress and mitochondrial dysfunction, impaired autophagy, and inflammation. Crosstalk between these stress pathways exists at multiple levels and may aggravate β-cell lipo- and glucolipotoxicity. Lipo- and glucolipotoxicity are therapeutic targets as several drugs impact the underlying stress responses in β-cells, potentially contributing to their glucose-lowering effects in T2D.
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Affiliation(s)
- Maria Lytrivi
- ULB Center for Diabetes Research, Medical Faculty, Université Libre de Bruxelles, Brussels, Belgium; Division of Endocrinology, Erasmus Hospital, Université Libre de Bruxelles, Brussels, Belgium
| | - Anne-Laure Castell
- CRCHUM, Montréal, QC, Canada; Department of Medicine, Université de Montréal, Montréal, QC, Canada
| | - Vincent Poitout
- CRCHUM, Montréal, QC, Canada; Department of Medicine, Université de Montréal, Montréal, QC, Canada.
| | - Miriam Cnop
- ULB Center for Diabetes Research, Medical Faculty, Université Libre de Bruxelles, Brussels, Belgium; Division of Endocrinology, Erasmus Hospital, Université Libre de Bruxelles, Brussels, Belgium.
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Hall E, Jönsson J, Ofori JK, Volkov P, Perfilyev A, Dekker Nitert M, Eliasson L, Ling C, Bacos K. Glucolipotoxicity Alters Insulin Secretion via Epigenetic Changes in Human Islets. Diabetes 2019; 68:1965-1974. [PMID: 31420409 DOI: 10.2337/db18-0900] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Accepted: 07/24/2019] [Indexed: 11/13/2022]
Abstract
Type 2 diabetes (T2D) is characterized by insufficient insulin secretion and elevated glucose levels, often in combination with high levels of circulating fatty acids. Long-term exposure to high levels of glucose or fatty acids impair insulin secretion in pancreatic islets, which could partly be due to epigenetic alterations. We studied the effects of high concentrations of glucose and palmitate combined for 48 h (glucolipotoxicity) on the transcriptome, the epigenome, and cell function in human islets. Glucolipotoxicity impaired insulin secretion, increased apoptosis, and significantly (false discovery rate <5%) altered the expression of 1,855 genes, including 35 genes previously implicated in T2D by genome-wide association studies (e.g., TCF7L2 and CDKN2B). Additionally, metabolic pathways were enriched for downregulated genes. Of the differentially expressed genes, 1,469 also exhibited altered DNA methylation (e.g., CDK1, FICD, TPX2, and TYMS). A luciferase assay showed that increased methylation of CDK1 directly reduces its transcription in pancreatic β-cells, supporting the idea that DNA methylation underlies altered expression after glucolipotoxicity. Follow-up experiments in clonal β-cells showed that knockdown of FICD and TPX2 alters insulin secretion. Together, our novel data demonstrate that glucolipotoxicity changes the epigenome in human islets, thereby altering gene expression and possibly exacerbating the secretory defect in T2D.
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Affiliation(s)
- Elin Hall
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden
| | - Josefine Jönsson
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden
| | - Jones K Ofori
- Islet Cell Exocytosis Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden
| | - Petr Volkov
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden
| | - Alexander Perfilyev
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden
| | - Marloes Dekker Nitert
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden
| | - Lena Eliasson
- Islet Cell Exocytosis Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden
| | - Charlotte Ling
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden
| | - Karl Bacos
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden
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Raygor V, Abbasi F, Lazzeroni LC, Kim S, Ingelsson E, Reaven GM, Knowles JW. Impact of race/ethnicity on insulin resistance and hypertriglyceridaemia. Diab Vasc Dis Res 2019; 16:153-159. [PMID: 31014093 PMCID: PMC6713231 DOI: 10.1177/1479164118813890] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Abstract
OBJECTIVE Insulin sensitivity affects plasma triglyceride concentration and both differ by race/ethnicity. The purpose of this study was to provide a comprehensive assessment of the variation in insulin sensitivity and its relationship to hypertriglyceridaemia between five race/ethnic groups. RESEARCH DESIGN AND METHODS In this cross-sectional study, clinical data for 1025 healthy non-Hispanic White, Hispanic White, East Asian, South Asian and African American individuals were analysed. Insulin-mediated glucose disposal (a direct measure of peripheral insulin sensitivity) was measured using the modified insulin suppression test. Statistical analysis was performed using analysis of co-variance. RESULTS Of the study participants, 63% were non-Hispanic White, 9% were Hispanic White, 11% were East Asian, 11% were South Asian and 6% were African American. Overall, non-Hispanic Whites and African Americans displayed greater insulin sensitivity than East Asians and South Asians. Triglyceride concentration was positively associated with insulin resistance in all groups, including African Americans. Nevertheless, for any given level of insulin sensitivity, African Americans had the lowest triglyceride concentrations. CONCLUSION Insulin sensitivity, as assessed by a direct measure of insulin-mediated glucose disposal, and its relationship to triglyceride concentration vary across five race/ethnic groups. Understanding these relationships is crucial for accurate cardiovascular risk stratification and prevention.
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Affiliation(s)
- Viraj Raygor
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Fahim Abbasi
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Laura C Lazzeroni
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | - Sun Kim
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Diabetes Research Center, Stanford University School of Medicine, Stanford, CA, USA
| | - Erik Ingelsson
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Diabetes Research Center, Stanford University School of Medicine, Stanford, CA, USA
- Cardiovascular Medicine, Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Gerald M Reaven
- Diabetes Research Center, Stanford University School of Medicine, Stanford, CA, USA
- Cardiovascular Medicine, Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Joshua W Knowles
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Diabetes Research Center, Stanford University School of Medicine, Stanford, CA, USA
- Cardiovascular Medicine, Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
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40
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Lamantia V, Bissonnette S, Provost V, Devaux M, Cyr Y, Daneault C, Rosiers CD, Faraj M. The Association of Polyunsaturated Fatty Acid δ-5-Desaturase Activity with Risk Factors for Type 2 Diabetes Is Dependent on Plasma ApoB-Lipoproteins in Overweight and Obese Adults. J Nutr 2019; 149:57-67. [PMID: 30535058 PMCID: PMC6351138 DOI: 10.1093/jn/nxy238] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2018] [Accepted: 08/24/2018] [Indexed: 01/05/2023] Open
Abstract
Background δ-5 and δ-6 desaturases (D5D and D6D) catalyze the endogenous conversion of n-3 (ω-3) and n-6 (ω-6) polyunsaturated fatty acids (PUFAs). Their activities are negatively and positively associated with type 2 diabetes (T2D), respectively, by unclear mechanisms. Elevated plasma apoB-lipoproteins (measured as plasma apoB), which can be reduced by n-3 PUFA intake, promote T2D risk factors. Objective The aim of this study was to test the hypothesis that the association of D5D and D6D activities with T2D risk factors is dependent on plasma apoB. Methods This is a pooled analysis of 2 populations recruited for 2 different metabolic studies. It is a post hoc analysis of baseline data of these subjects [n = 98; 60% women (postmenopausal); mean ± SD body mass index (in kg/m2): 32.8 ± 4.7; mean ± SD age: 57.6 ± 6.3 y]. Glucose-induced insulin secretion (GIIS) and insulin sensitivity (IS) were measured using Botnia clamps. Plasma clearance of a high-fat meal (600 kcal/m2, 66% fat) and white adipose tissue (WAT) function (storage of 3H-triolein-labeled substrate) were assessed in a subpopulation (n = 47). Desaturase activities were estimated from plasma phospholipid fatty acids. Associations were examined using Pearson and partial correlations. Results While both desaturase activities were positively associated with percentage of eicosapentaenoic acid, only D5D was negatively associated with plasma apoB (r = -0.30, P = 0.003). Association of D5D activity with second-phase GIIS (r = -0.23, P = 0.029), IS (r = 0.33, P = 0.015, in women) and 6-h area-under-the-curve (AUC6h) of plasma chylomicrons (apoB48, r = -0.47, P = 0.020, in women) was independent of age and adiposity, but was eliminated after adjustment for plasma apoB. D6D activity was associated in the opposite direction with GIIS (r = 0.24, P = 0.049), IS (r = -0.36, P = 0.004) and AUC6h chylomicrons (r = 0.52, P = 0.004), independent of plasma apoB. Both desaturases were associated with plasma interleukin-1-receptor antagonist (D5D: r = -0.45, P < 0.001 in women; D6D: r = -0.33, P = 0.007) and WAT function (trend for D5D: r = 0.30, P = 0.05; D6D: r = 0.39, P = 0.027) independent of any adjustment. Conclusions Association of D5D activity with IS, lower GIIS, and plasma chylomicron clearance is dependent on plasma apoB in overweight and obese adults.
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Affiliation(s)
- Valérie Lamantia
- Faculty of Medicine, Université de Montréal, Montréal, Québec,Institut de Recherches Cliniques de Montréal (IRCM), Montréal, Québec
| | - Simon Bissonnette
- Faculty of Medicine, Université de Montréal, Montréal, Québec,Institut de Recherches Cliniques de Montréal (IRCM), Montréal, Québec
| | - Viviane Provost
- Faculty of Medicine, Université de Montréal, Montréal, Québec,Institut de Recherches Cliniques de Montréal (IRCM), Montréal, Québec
| | - Marie Devaux
- Faculty of Medicine, Université de Montréal, Montréal, Québec,Institut de Recherches Cliniques de Montréal (IRCM), Montréal, Québec
| | - Yannick Cyr
- Faculty of Medicine, Université de Montréal, Montréal, Québec,Institut de Recherches Cliniques de Montréal (IRCM), Montréal, Québec
| | | | - Christine Des Rosiers
- Faculty of Medicine, Université de Montréal, Montréal, Québec,Institut de Cardiologie de Montréal (ICM), Montréal, Québec
| | - May Faraj
- Faculty of Medicine, Université de Montréal, Montréal, Québec,Institut de Recherches Cliniques de Montréal (IRCM), Montréal, Québec,Montreal Diabetes Research Center (MDRC), Montréal, Québec,Address correspondence to MF (e-mail: )
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Wu X, Guan T, Liu DJ, León Novelo LG, Bandyopadhyay D. ADAPTIVE-WEIGHT BURDEN TEST FOR ASSOCIATIONS BETWEEN QUANTITATIVE TRAITS AND GENOTYPE DATA WITH COMPLEX CORRELATIONS. Ann Appl Stat 2018; 12:1558-1582. [PMID: 30214655 DOI: 10.1214/17-aoas1121] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
High-throughput sequencing has often been used to screen samples from pedigrees or with population structure, producing genotype data with complex correlations rendered from both familial relation and linkage disequilibrium. With such data, it is critical to account for these genotypic correlations when assessing the contribution of variants by gene or pathway. Recognizing the limitations of existing association testing methods, we propose Adaptive-weight Burden Test (ABT), a retrospective, mixed-model test for genetic association of quantitative traits on genotype data with complex correlations. This method makes full use of genotypic correlations across both samples and variants, and adopts "data-driven" weights to improve power. We derive the ABT statistic and its explicit distribution under the null hypothesis, and demonstrate through simulation studies that it is generally more powerful than the fixed-weight burden test and family-based SKAT in various scenarios, controlling for the type I error rate. Further investigation reveals the connection of ABT with kernel tests, as well as the adaptability of its weights to the direction of genetic effects. The application of ABT is illustrated by a whole genome analysis of genes with common and rare variants associated with fasting glucose from the NHLBI "Grand Opportunity" Exome Sequencing Project.
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Affiliation(s)
- Xiaowei Wu
- Department of Statistics, Virginia Tech, 250 Drillfield Drive, MC0439, Blacksburg, VA 24061, USA
| | - Ting Guan
- Department of Statistics, Virginia Tech, 250 Drillfield Drive, MC0439, Blacksburg, VA 24061, USA
| | - Dajiang J Liu
- Department of Public Health Sciences, Hershey Institute of Personalized Medicine, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
| | - Luis G León Novelo
- Department of Biostatistics, School of Public Health, University of Texas Health Science Center, Houston, TX 77030, USA
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Dziewulska A, Dobosz AM, Dobrzyn A. High-Throughput Approaches onto Uncover (Epi)Genomic Architecture of Type 2 Diabetes. Genes (Basel) 2018; 9:E374. [PMID: 30050001 PMCID: PMC6115814 DOI: 10.3390/genes9080374] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2018] [Revised: 07/20/2018] [Accepted: 07/23/2018] [Indexed: 12/20/2022] Open
Abstract
Type 2 diabetes (T2D) is a complex disorder that is caused by a combination of genetic, epigenetic, and environmental factors. High-throughput approaches have opened a new avenue toward a better understanding of the molecular bases of T2D. A genome-wide association studies (GWASs) identified a group of the most common susceptibility genes for T2D (i.e., TCF7L2, PPARG, KCNJ1, HNF1A, PTPN1, and CDKAL1) and illuminated novel disease-causing pathways. Next-generation sequencing (NGS)-based techniques have shed light on rare-coding genetic variants that account for an appreciable fraction of T2D heritability (KCNQ1 and ADRA2A) and population risk of T2D (SLC16A11, TPCN2, PAM, and CCND2). Moreover, single-cell sequencing of human pancreatic islets identified gene signatures that are exclusive to α-cells (GCG, IRX2, and IGFBP2) and β-cells (INS, ADCYAP1, INS-IGF2, and MAFA). Ongoing epigenome-wide association studies (EWASs) have progressively defined links between epigenetic markers and the transcriptional activity of T2D target genes. Differentially methylated regions were found in TCF7L2, THADA, KCNQ1, TXNIP, SOCS3, SREBF1, and KLF14 loci that are related to T2D. Additionally, chromatin state maps in pancreatic islets were provided and several non-coding RNAs (ncRNA) that are key to T2D pathogenesis were identified (i.e., miR-375). The present review summarizes major progress that has been made in mapping the (epi)genomic landscape of T2D within the last few years.
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Affiliation(s)
- Anna Dziewulska
- Laboratory of Cell Signaling and Metabolic Disorders, Nencki Institute of Experimental Biology of Polish Academy of Sciences, 02-093 Warsaw, Poland.
| | - Aneta M Dobosz
- Laboratory of Cell Signaling and Metabolic Disorders, Nencki Institute of Experimental Biology of Polish Academy of Sciences, 02-093 Warsaw, Poland.
| | - Agnieszka Dobrzyn
- Laboratory of Cell Signaling and Metabolic Disorders, Nencki Institute of Experimental Biology of Polish Academy of Sciences, 02-093 Warsaw, Poland.
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Adams JD, Vella A. What Can Diabetes-Associated Genetic Variation in TCF7L2 Teach Us About the Pathogenesis of Type 2 Diabetes? Metab Syndr Relat Disord 2018; 16:383-389. [PMID: 29993315 DOI: 10.1089/met.2018.0024] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Type 2 diabetes mellitus (T2DM) is a polygenic metabolic disorder characterized by hyperglycemia occurring as a result of impaired insulin secretion and/or insulin resistance. Among the various genetic factors associated with T2DM, a common genetic variant within the transcription factor 7-like 2 locus (TCF7L2) confers the greatest genetic risk for development of the disease. However, the mechanism(s) by which TCF7L2 predisposes to diabetes remain uncertain. Here we review the current literature pertaining to the potential mechanisms by which TCF7L2 confers risk of T2DM, using genetic variation as a probe to understand the pathogenesis of the disease.
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Affiliation(s)
- J D Adams
- Endocrine Research Unit, Department of Endocrinology, Diabetes and Nutrition, Mayo Clinic College of Medicine , Rochester, Minnesota
| | - Adrian Vella
- Endocrine Research Unit, Department of Endocrinology, Diabetes and Nutrition, Mayo Clinic College of Medicine , Rochester, Minnesota
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Mansouri V, Javanmard SH, Mahdavi M, Tajedini MH. Association of Polymorphism in Fatty Acid Desaturase Gene with the Risk of Type 2 Diabetes in Iranian Population. Adv Biomed Res 2018; 7:98. [PMID: 30050886 PMCID: PMC6036782 DOI: 10.4103/abr.abr_131_17] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
Background: The type 2 diabetes is one of the most common autoimmune diseases. Due to a key role in the metabolism of unsaturated fatty acids such as arachidonic acid, one of the most important precursors of immunity mediators, fatty acid desaturase (FADS) genes could have an important impact in the development of type 2 diabetes. Materials and Methods: This study aimed to determine the relationship between polymorphisms rs174537 in FADS1 gene and rs174575 in FADS2 gene with type 2 diabetes in Iranian population. After extracting genomic DNA, the locations of mutations and allele types were identified with high-resolution melting (HRM)-polymerase chain reaction method. Then, association between these mutations with metabolic syndrome, dyslipidemia, and type 2 diabetes was investigated using χ2 correlation coefficients for variables and logistic regression. Results: The results showed that among 50 diabetic participants, 68% of patients have the mutant allele for rs174537 in FADS1 gene. This rate is 26% for rs174575 in FADS2 gene. Based on the results, it seems that participants having rs174537 mutant allele are more prone to become diabetic but it has a beneficial effect on total and low-density lipoprotein cholesterol and participants having rs174575 mutant are less prone to become diabetic, and also, it leads to higher triglycerides and body mass index (obesity). Conclusions: Detecting FADS1 and FADS2, gene polymorphisms using HRM can be an anticipating tool for making decision on initiating lifestyle modifications to prevent type 2 diabetes.
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Affiliation(s)
- Vahid Mansouri
- Department of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | | | - Manijeh Mahdavi
- Pediatric Inherited Diseases Research Center, Research Institute for Primordial Prevention of Noncommunicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran
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Langenberg C, Lotta LA. Genomic insights into the causes of type 2 diabetes. Lancet 2018; 391:2463-2474. [PMID: 29916387 DOI: 10.1016/s0140-6736(18)31132-2] [Citation(s) in RCA: 103] [Impact Index Per Article: 17.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2018] [Revised: 04/30/2018] [Accepted: 05/15/2018] [Indexed: 01/05/2023]
Abstract
Genome-wide association studies have implicated around 250 genomic regions in predisposition to type 2 diabetes, with evidence for causal variants and genes emerging for several of these regions. Understanding of the underlying mechanisms, including the interplay between β-cell failure, insulin sensitivity, appetite regulation, and adipose storage has been facilitated by the integration of multidimensional data for diabetes-related intermediate phenotypes, detailed genomic annotations, functional experiments, and now multiomic molecular features. Studies in diverse ethnic groups and examples from population isolates have shown the value and need for a broad genomic approach to this global disease. Transethnic discovery efforts and large-scale biobanks in diverse populations and ancestries could help to address some of the Eurocentric bias. Despite rapid progress in the discovery of the highly polygenic architecture of type 2 diabetes, dominated by common alleles with small, cumulative effects on disease risk, these insights have been of little clinical use in terms of disease prediction or prevention, and have made only small contributions to subtype classification or stratified approaches to treatment. Successful development of academia-industry partnerships for exome or genome sequencing in large biobanks could help to deliver economies of scale, with implications for the future of genomics-focused research.
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Affiliation(s)
| | - Luca A Lotta
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
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46
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Jung S. Implications of publicly available genomic data resources in searching for therapeutic targets of obesity and type 2 diabetes. Exp Mol Med 2018; 50:1-13. [PMID: 29674722 PMCID: PMC5938056 DOI: 10.1038/s12276-018-0066-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2017] [Accepted: 01/28/2018] [Indexed: 12/29/2022] Open
Abstract
Obesity and type 2 diabetes (T2D) are two major conditions that are related to metabolic disorders and affect a large population. Although there have been significant efforts to identify their therapeutic targets, few benefits have come from comprehensive molecular profiling. This limited availability of comprehensive molecular profiling of obesity and T2D may be due to multiple challenges, as these conditions involve multiple organs and collecting tissue samples from subjects is more difficult in obesity and T2D than in other diseases, where surgical treatments are popular choices. While there is no repository of comprehensive molecular profiling data for obesity and T2D, multiple existing data resources can be utilized to cover various aspects of these conditions. This review presents studies with available genomic data resources for obesity and T2D and discusses genome-wide association studies (GWAS), a knockout (KO)-based phenotyping study, and gene expression profiles. These studies, based on their assessed coverage and characteristics, can provide insights into how such data can be utilized to identify therapeutic targets for obesity and T2D.
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Affiliation(s)
- Sungwon Jung
- Department of Genome Medicine and Science, Gachon University School of Medicine, Incheon, Republic of Korea. .,Gachon Institute of Genome Medicine and Science, Gachon University Gil Medical Center, Incheon, Republic of Korea.
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Quinault A, Leloup C, Denwood G, Spiegelhalter C, Rodriguez M, Lefebvre P, Messaddeq N, Zhang Q, Dacquet C, Pénicaud L, Collins SC. Modulation of large dense core vesicle insulin content mediates rhythmic hormone release from pancreatic beta cells over the 24h cycle. PLoS One 2018; 13:e0193882. [PMID: 29543849 PMCID: PMC5854349 DOI: 10.1371/journal.pone.0193882] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Accepted: 02/20/2018] [Indexed: 11/19/2022] Open
Abstract
The rhythmic nature of insulin secretion over the 24h cycle in pancreatic islets has been mostly investigated using transcriptomics studies showing that modulation of insulin secretion over this cycle is achieved via distal stages of insulin secretion. We set out to measure β-cell exocytosis using in depth cell physiology techniques at several time points. In agreement with the activity and feeding pattern of nocturnal rodents, we find that C57/Bl6J islets in culture for 24h exhibit higher insulin secretion during the corresponding dark phase than in the light phase (Zeitgeber Time ZT20 and ZT8, respectively, in vivo). Glucose-induced insulin secretion is increased by 21% despite normal intracellular Ca2+ transients and depolarization-evoked exocytosis, as measured by whole-cell capacitance measurements. This paradox is explained by a 1.37-fold increase in beta cell insulin content. Ultramorphological analyses show that vesicle size and density are unaltered, demonstrating that intravesicular insulin content per granule is modulated over the 24h cycle. Proinsulin levels did not change between ZT8 and ZT20. Islet glucagon content was inversely proportional to insulin content indicating that this unique feature is likely to support a physiological role. Microarray data identified the differential expression of 301 transcripts, of which 26 are miRNAs and 54 are known genes (including C2cd4b, a gene previously involved in insulin processing, and clock genes such as Bmal1 and Rev-erbα). Mouse β-cell secretion over the full course of the 24h cycle may rely on several distinct cellular functions but late night increase in insulin secretion depends solely on granule insulin content.
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Affiliation(s)
- Aurore Quinault
- CSGA, AgroSup Dijon, Centre National de la Recherche Scientifique, Institut National de la Recherche Agronomique, Université de Bourgogne Franche-Comté, 9E Boulevard Jeanne d'Arc, Dijon, France
| | - Corinne Leloup
- CSGA, AgroSup Dijon, Centre National de la Recherche Scientifique, Institut National de la Recherche Agronomique, Université de Bourgogne Franche-Comté, 9E Boulevard Jeanne d'Arc, Dijon, France
| | - Geoffrey Denwood
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, University of Oxford, Headington, Oxford, United Kingdom
| | | | - Marianne Rodriguez
- Metabolism Discovery Research Pole of Therapeutical innovation Institut de Recherche Servier, 11 rue des Moulineaux Suresnes, France
| | - Philippe Lefebvre
- European Genomic Institute for Diabetes and UMR 1011 Inserm Université Nord de France-Institut Pasteur de Lille, Boulevard du Professeur Leclerc, Lille, France
| | | | - Quan Zhang
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, University of Oxford, Headington, Oxford, United Kingdom
| | - Catherine Dacquet
- Biotechnology and Biomarker Research, Institut de Recherche Servier, 125 Chemin de Ronde, Croissy sur Seine, France
| | - Luc Pénicaud
- CSGA, AgroSup Dijon, Centre National de la Recherche Scientifique, Institut National de la Recherche Agronomique, Université de Bourgogne Franche-Comté, 9E Boulevard Jeanne d'Arc, Dijon, France
| | - Stephan C. Collins
- CSGA, AgroSup Dijon, Centre National de la Recherche Scientifique, Institut National de la Recherche Agronomique, Université de Bourgogne Franche-Comté, 9E Boulevard Jeanne d'Arc, Dijon, France
- IGBMC, 1 Rue Laurent Fries, Illkirch-Graffenstaden, France
- * E-mail:
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Xu M, Hu H, Deng D, Chen M, Xu Z, Wang Y. Prediabetes is associated with genetic variations in the gene encoding the Kir6.2 subunit of the pancreatic ATP-sensitive potassium channel (KCNJ11): A case-control study in a Han Chinese youth population. J Diabetes 2018; 10:121-129. [PMID: 28449408 DOI: 10.1111/1753-0407.12565] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2016] [Revised: 04/06/2017] [Accepted: 04/24/2017] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND The E23K variant of the potassium voltage-gated channel subfamily J member 11 (KCNJ11) gene has been reported to be associated with type 2 diabetes (T2D) in many populations. However, little is known about the role of E23K in the development of prediabetes in Chinese youth. METHODS To investigate the role of E23K in the development of prediabetes, 279 subjects with prediabetes and 240 normal controls (mean [± SD] age 18.1 ± 3.2 and 17.8 ± 4.3 years, respectively) were recruited to the study. Height, weight, and hip and waist circumferences were measured by trained physicians. Genotyping of KCNJ11 polymorphisms and clinical laboratory tests to determine cholesterol, triglyceride (TG), blood glucose, and insulin levels were performed. RESULTS The carrier rate of K23 allele-containing genotypes was higher for prediabetic than control subjects (P = 0.005). Logistic regression analyses revealed that higher body mass index percentiles (P = 0.013), lower insulin levels at 30 min during an oral glucose tolerance test (P = 0.001), a higher ratio of total cholesterol: high-density lipoprotein cholesterol (P = 0.001), and a K allele-containing genotype (P = 0.019) are independent risk factors for prediabetes in Chinese Han youth. Furthermore, K23 allele-containing genotypes were associated with impaired indices of insulin secretion and β-cell function in female youth with prediabetes. These effects were not seen in male youth with prediabetes. CONCLUSIONS The results confirm that the common E23K polymorphism of KCNJ11 carries a higher susceptibility to the development of prediabetes in the Chinese Han population. The results suggest that E23K may have a greater effect on the development of T2D in female Chinese youth.
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Affiliation(s)
- Min Xu
- Department of Endocrinology, The First Hospital of An Hui Medical University, Hefei, China
| | - Honglin Hu
- Department of Endocrinology, The First Hospital of An Hui Medical University, Hefei, China
| | - Datong Deng
- Department of Endocrinology, The First Hospital of An Hui Medical University, Hefei, China
| | - Mingwei Chen
- Department of Endocrinology, The First Hospital of An Hui Medical University, Hefei, China
| | - Zhenshan Xu
- AnHui AnKe Biotechnology Group, Hefei, China
| | - Youmin Wang
- Department of Endocrinology, The First Hospital of An Hui Medical University, Hefei, China
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Manukumar HM, Shiva Kumar J, Chandrasekhar B, Raghava S, Umesha S. Evidences for diabetes and insulin mimetic activity of medicinal plants: Present status and future prospects. Crit Rev Food Sci Nutr 2018; 57:2712-2729. [PMID: 26857927 DOI: 10.1080/10408398.2016.1143446] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Diabetes mellitus (DM) is a considerable systemic metabolic disorder to exhibit various metabolic and cardiovascular disorders, mainly hyperglycemia. The global projected estimate of diabetes in 2030 will be about 439 million adults, out of which 300 million expected are of type-2 diabetes mellitus (T2DM). The present knowledge revealed responsible factors, occurrence and mechanism of these factors involved in the DM diseases. Hence, the aim of this review is to address and summarize the causes, plant resources, importance, present status and future programmes for diabetes control. The present review answers the contemporary present questions raised in the scientific field on DM. Two major problems are explained in detail about the autoimmune attack or dysfunction of β-cell and insulin resistance involved for Type 1 and Type 2 DM, respectively. Though there are various approaches to reduce the ill effects of diabetes and its secondary complications, many preferred herbal formulations due to lesser side effects and low cost. For this reason still it is getting increased attention in searching antidiabetic medicinal plants for hot research and to develop targeted medicine. Recurrence of islet autoimmunity lesson from pancreatic islet cell transplantation to cure T1D was outlined. With these highlights, the review summarizes the current knowledge on diabetes occurrence, factors (environmental and genetics), and types (I, II, gestation, and secondary DM), antidiabetic plants, sources for insulin mimetic plant principle compounds and their target mechanism with current and future trusted research areas for controlling of DM.
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Affiliation(s)
- H M Manukumar
- a Department of Studies in Biotechnology , University of Mysore , Manasagangotri, Mysore , Karnataka , India
| | - J Shiva Kumar
- a Department of Studies in Biotechnology , University of Mysore , Manasagangotri, Mysore , Karnataka , India
| | - B Chandrasekhar
- a Department of Studies in Biotechnology , University of Mysore , Manasagangotri, Mysore , Karnataka , India
| | - Sri Raghava
- a Department of Studies in Biotechnology , University of Mysore , Manasagangotri, Mysore , Karnataka , India
| | - S Umesha
- a Department of Studies in Biotechnology , University of Mysore , Manasagangotri, Mysore , Karnataka , India
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50
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Abstract
This chapter reviews both statistical and physiologic issues related to the pathophysiologic effects of genetic variation in the context of type 2 diabetes. The goal is to review current methodologies used to analyze disease-related quantitative traits for those who do not have extensive quantitative and physiologic background, as an attempt to bridge that gap. We leverage mathematical modeling to illustrate the strengths and weaknesses of different approaches and attempt to reinforce with real data analysis. Topics reviewed include phenotype selection, phenotype specificity, multiple variant analysis via the genetic risk score, and consideration of multiple disease-related phenotypes. Type 2 diabetes is used as the example, not only because of the extensive existing knowledge at the genetic, physiologic, clinical, and epidemiologic levels, but also because type 2 diabetes has been at the forefront of complex disease genetics, with many examples to draw from.
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Affiliation(s)
- Richard M Watanabe
- Departments of Preventive Medicine and Physiology & Biophysics, Keck School of Medicine of USC, 2250 Alcazar Street, CSC-204, Los Angeles, CA, 90089-9073, USA.
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