DOCSLIB.ORG

Long-Range Gene Regulation Links Genomic Type 2 Diabetes and Obesity Risk Regions to HHEX, SOX4, and IRX3

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Long-Range Gene Regulation Links Genomic Type 2 Diabetes and Obesity Risk Regions to HHEX, SOX4, and IRX3 Corrections GENETICS MEDICAL SCIENCES Correction for “Long-range gene regulation links genomic type 2 Correction for “Prolonged duration local anesthesia with mini- diabetes and obesity risk regions to HHEX, SOX4,andIRX3,” by mal toxicity,” by Hila Epstein-Barash, Iris Shichor, Albert H. Anja Ragvin, Enrico Moro, David Fredman, Pavla Navratilova, Kwon, Sherwood Hall, Michael W. Lawlor, Robert Langer, and Øyvind Drivenes, Pär G. Engström, M. Eva Alonso, Elisa de la Daniel S. Kohane, which appeared in issue 17, April 28, 2009, of Calle Mustienes, José Luis Gómez Skarmeta, Maria J. Tavares, Proc Natl Acad Sci USA (106:7125–7130; first published April 13, Fernando Casares, Miguel Manzanares, Veronica van Heyningen, 2009; 10.1073/pnas.0900598106). Anders Molven, Pål R. Njølstad, Francesco Argenton, Boris The authors note that on page 7129, left column, fourth full Lenhard, and Thomas S. Becker, which appeared in issue 2, paragraph, sentences 3 through 5, “DSPC:DSPG:cholesterol or January 12, 2010, of Proc Natl Acad Sci USA (107:775–780; first DMPC:DMPG-cholesterol (molar ratio 3:1:2) were dissolved in published December 22, 2009; 10.1073/pnas.0911591107). t-butanol. Dexamethasone was added in some samples before The authors note that, due to a printer’s error, the second lyophilization. The lyophilized cake was hydrated with 250 mM affiliation for Anders Molven should instead appear as “De- ammonium sulfate or, in some groups, with 0.1 mg STX, at 55– partment of Pathology, Haukeland University Hospital, N-5021 60 °C.” should instead appear as “DSPC:DSPG:cholesterol or Bergen, Norway.” The corrected affiliation line appears below. DMPC:DMPG-cholesterol (molar ratio 3:1:2) were dissolved in The online version has been corrected. 9:1 vol/vol chloroform:methanol solution. Dexamethasone was added in some samples. A thin lipid film was obtained by drying aDepartment of Clinical Medicine, University of Bergen, N-5020 Bergen, the lipid mixture in a rotary evaporator at 60 °C. The pressure in Norway; bPediatrics, Haukeland University Hospital, N-5021 Bergen, Norway; cDipartimento di Biologia, Universita’ degli Studi di Padova, I-35121 the evaporator was maintained at 480 torr for 20 minutes and Padua, Italy; dComputational Biology Unit, Bergen Center for Computational then gradually decreased to 20 torr over a period of 30 min. The Science, University of Bergen, N-5008 Bergen, Norway; eSars Centre for lipid film was reconstituted in t-butanol at 55–60 °C and imme- Marine Molecular Biology, University of Bergen, N-5008 Bergen, Norway; diately cooled by immersing in liquid nitrogen. The sample was fFundación Centro Nacional de Investigaciones Cardiovasculares Carlos III, E-28029 Madrid, Spain; gCentro Andaluz de Biología del Desarrollo, Uni- then transferred to a lyophilizer for 24 h. The lyophilized cake versidad Pablo de Olavide, Consejo Superior de Investigaciones Científicas, was hydrated with 250 mM ammonium sulfate or, in some Sevilla 41013, Spain; hMedical Research Council Human Genetics Unit, groups, with 1.0 mg STX, at 55–60 °C.” Western General Hospital, Edinburgh EH4 2XU, United Kingdom; iThe Gade Institute, University of Bergen, N-5020, Bergen, Norway; and jDepartment of www.pnas.org/cgi/doi/10.1073/pnas.1102194108 Pathology, Haukeland University Hospital, N-5021 Bergen, Norway www.pnas.org/cgi/doi/10.1073/pnas.1101890108 BIOCHEMISTRY Correction for “In vitro and in vivo reconstitution of the cadherin– catenin–actin complex from Caenorhabditis elegans,” by Adam V. Kwiatkowski, Stephanie L. Maiden, Sabine Pokutta, Hee-Jung Choi, Jacqueline M. Benjamin, Allison M. Lynch, W. James Nelson, William I. Weis, and Jeff Hardin, which appeared in issue 33, August 17, 2010, of Proc Natl Acad Sci USA (107:14591–14596; first published August 5, 2010; 10.1073/pnas.1007349107). The authors note that in the Materials and Methods under the section “Actin Pelleting Assay,” the 10× stock concentration was listed instead of the 1× final working concentration for the po- lymerization and reaction buffers. The correct concentrations are as follows: polymerization buffer (20 mM Imidazole pH 7.0, 100 mM KCl, 2 mM MgCl2, 0.5 mM ATP, 1 mM EGTA) and reaction buffer (20 mM Imidazole pH 7.0, 150 mM NaCl, 2 mM MgCl2, 0.5 mM ATP, 1 mM EGTA, 1 mM DTT). www.pnas.org/cgi/doi/10.1073/pnas.1102189108 4264 | PNAS | March 8, 2011 | vol. 108 | no. 10 www.pnas.org Downloaded by guest on September 26, 2021 Long-range gene regulation links genomic type 2 diabetes and obesity risk regions to HHEX, SOX4, and IRX3 Anja Ragvina,b,1, Enrico Moroc,1, David Fredmand,e,2, Pavla Navratilovae, Øyvind Drivenese, Pär G. Engströmd,e,3, M. Eva Alonsof, Elisa de la Calle Mustienesg, José Luis Gómez Skarmetag, Maria J. Tavaresg, Fernando Casaresg, Miguel Manzanaresf, Veronica van Heyningenh, Anders Molveni,j, Pål R. Njølstada,b, Francesco Argentonc, Boris Lenhardd,e,4, and Thomas S. Beckere,2,5 aDepartment of Clinical Medicine, University of Bergen, N-5020 Bergen, Norway; bPediatrics, Haukeland University Hospital, N-5021 Bergen, Norway; cDipartimento di Biologia, Universita’ degli Studi di Padova, I-35121 Padua, Italy; dComputational Biology Unit, Bergen Center for Computational Science, University of Bergen, N-5008 Bergen, Norway; eSars Centre for Marine Molecular Biology, University of Bergen, N-5008 Bergen, Norway; fFundación Centro Nacional de Investigaciones Cardiovasculares Carlos III, E-28029 Madrid, Spain; gCentro Andaluz de Biología del Desarrollo, Universidad Pablo de Olavide, Consejo Superior de Investigaciones Científicas, Sevilla 41013, Spain; hMedical Research Council Human Genetics Unit, Western General Hospital, Edinburgh EH4 2XU, United Kingdom; iThe Gade Institute, University of Bergen, N-5020, Bergen, Norway; and jDepartment of Pathology, Haukeland University Hospital, N-5021 Bergen, Norway Communicated by Michael S. Levine, University of California, Berkeley, CA, November 10, 2009 (received for review January 15, 2009) Genome-wide association studies identified noncoding SNPs asso- regions, namely the HHEX-IDE, CDKAL1, and FTO LD blocks, ciated with type 2 diabetes and obesity in linkage disequilibrium which harbor SNPs recently demonstrated by genome-wide as- (LD) blocks encompassing HHEX-IDE and introns of CDKAL1 and sociation studies to be significantly associated with risk for T2D FTO [Sladek R, et al. (2007) Nature 445:881–885; Steinthorsdottir and obesity (Table 1). We demonstrate that comparative genomic V, et al. (2007) Nat. Genet 39:770–775; Frayling TM, et al. (2007) analysis of risk regions can quickly confirm or disqualify a can- Science 316:889–894]. We show that these LD blocks contain highly didate disease gene by showing that it is HHEX, SOX4, and IRX3 conserved noncoding elements and overlap with the genomic reg- that likely underlie T2D and obesity in the three loci analyzed in ulatory blocks of the transcription factor genes HHEX, SOX4, and this study. We show that expression patterns driven by HCNEs IRX3. We report that human highly conserved noncoding elements within the risk regions can rapidly be assessed through trans- in LD with the risk SNPs drive expression in endoderm or pancreas in genesis in the zebrafish or in the mouse to identify the organ transgenic mice and zebrafish. Both HHEX and SOX4 have recently system or cell type affected by a common disease. We further been implicated in pancreas development and the regulation of demonstrate by knockdown of the zebrafish orthologue of IRX3, insulin secretion, but IRX3 had no prior association with pancreatic irx3a, that this transcription factor is involved in a conserved function or development. Knockdown of its orthologue in zebra- pathway that specifies pancreatic islet cell identities. fish, irx3a, increased the number of pancreatic ghrelin-producing epsilon cells and decreased the number of insulin-producing β-cells Results and glucagon-producing α-cells, thereby suggesting a direct link of Risk SNPs Identify Regions Regulating HHEX and SOX4. For the pancreatic IRX3 function to both obesity and type 2 diabetes. HHEX-IDE region, the associated SNPs lie in a 295-kb block of LD that includes three genes, HHEX, KIF1 and IDE, encoding a hb9 | hlxb9 | nkx2.2 | pancreatic islet development | pancreatic peptides transcriptional regulator involved in pancreatic development (13), a kinesin interacting factor, and an insulin-degrading enzyme, enome-wide association studies of SNPs are a powerful tool respectively (14). The risk allele has been associated with de- GENETICS Gin the genetic analysis of common diseases. Several studies creased pancreatic β-cell function (15). Throughout vertebrates, have shown significant associations of individual SNPs and hap- HHEX is in conserved synteny with the neighboring EXOC6 gene. lotypes with type 2 diabetes (T2D) (1–5) and obesity (6, 7). With The HHEX conserved synteny block overlaps with a small part of few exceptions, the identified SNPs fall into noncoding regions, the risk allele–containing LD block. This part of the LD block either intronic or intergenic, suggesting a regulatory effect of the contains the SNPs with the highest association scores, as well as the disease-associated haplotypes. Regulatory elements controlling HHEX gene (Fig. 1A and Table 1). In contrast, KIF1 and IDE are developmental expression of transcription factors often coincide located outside the conserved synteny block, strongly suggesting with highly conserved noncoding elements (HCNEs) (8–10). We have recently shown that vertebrate genomes contain functional segments termed genomic regulatory blocks (GRBs), Author contributions: A.R., E.M., D.F., P.N., Ø.D., P.G.E., M.M., A.M., P.R.N., F.A., B.L., and T.S.B. designed research; A.R., E.M., D.F., P.N., Ø.D., P.G.E., M.E.A., E.d.l.C.-M., J.-L.G.-S., M. which are chromosomal domains that control the expression of J.T., F.C., B.L., and T.S.B. performed research; A.R., E.M., D.F., P.R.N., Ø.D., P.E., M.E.A., J.-L.
Load more

Recommended publications
  • Implication of Genetic Variants Near TCF7L2, SLC30A8, HHEX, CDKAL1, CDKN2A/B, IGF2BP2, and FTO in Type 2 Diabetes and Obesity in 6,719 Asians Maggie C.Y
    ORIGINAL ARTICLE Implication of Genetic Variants Near TCF7L2, SLC30A8, HHEX, CDKAL1, CDKN2A/B, IGF2BP2, and FTO in Type 2 Diabetes and Obesity in 6,719 Asians Maggie C.Y. Ng,1 Kyong Soo Park,2 Bermseok Oh,3 Claudia H.T. Tam,1 Young Min Cho,2 Hyoung Doo Shin,4 Vincent K.L. Lam,1 Ronald C.W. Ma,1 Wing Yee So,1 Yoon Shin Cho,3 Hyung-Lae Kim,3 Hong Kyu Lee,2 Juliana C.N. Chan,1,5 and Nam H. Cho6 OBJECTIVE—Recent genome-wide association studies have identified six novel genes for type 2 diabetes and obesity and confirmed TCF7L2 as the major type 2 diabetes gene to date in ype 2 diabetes is a major health problem affect- Europeans. However, the implications of these genes in Asians ing more than 170 million people worldwide. In are unclear. the next 20 years, Asia will be hit hardest, with the diabetic populations in India and China more RESEARCH DESIGN AND METHODS—We studied 13 asso- T than doubling (1). Type 2 diabetes is characterized by the ciated single nucleotide polymorphisms from these genes in presence of insulin resistance and pancreatic ␤-cell dys- 3,041 patients with type 2 diabetes and 3,678 control subjects of Asian ancestry from Hong Kong and Korea. function, resulting from the interaction of genetic and environmental factors. Until recently, few genes identified RESULTS—We confirmed the associations of TCF7L2, through linkage scans or the candidate gene approach SLC30A8, HHEX, CDKAL1, CDKN2A/CDKN2B, IGF2BP2, and have been confirmed to be associated with type 2 diabetes FTO with risk for type 2 diabetes, with odds ratios ranging from (e.g., PPARG, KCNJ11, CAPN10, and TCF7L2).
    [Show full text]
  • Page 1 of 76 Diabetes Diabetes Publish Ahead of Print, Published Online September 14, 2020
    Page 1 of 76 Diabetes Peters, Annette; Helmholtz Center Munich German Research Center for Environmental Health, Epidemiology Institute Waldenberger, Melanie; Helmholtz Center Munich German Research Center for Environmental Health, Molecular Epidemiology Diabetes Publish Ahead of Print, published online September 14, 2020 Diabetes Page 2 of 76 Deciphering the Plasma Proteome of Type 2 Diabetes Mohamed A. Elhadad1,2,3 MSc., Christian Jonasson4,5 PhD, Cornelia Huth2,6 PhD, Rory Wilson1,2 MSc, Christian Gieger1,2,6 PhD, Pamela Matias1,2,3 MSc, Harald Grallert1,2,6 PhD, Johannes Graumann7,8 PhD, Valerie Gailus-Durner9 PhD, Wolfgang Rathmann6,10 MD, Christine von Toerne11 PhD, Stefanie M. Hauck11 PhD, Wolfgang Koenig3,12,13 MD, FRCP, FESC, FACC, FAHA, Moritz F. Sinner3,14 MD, MPH, Tudor I Oprea15,16,17 MD, PhD, Karsten Suhre18 PhD, Barbara Thorand2,6 PhD, Kristian Hveem4,5 PhD, Annette Peters2,3,6,19 PhD, Melanie Waldenberger1,2,3 PhD 1. Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. 2. Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany 3. German Research Center for Cardiovascular Disease (DZHK), Partner site Munich Heart Alliance, Germany 4. K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health, NTNU - Norwegian University of Science and Technology, Trondheim, Norway 5. HUNT Research Center, Department of Public Health, NTNU - Norwegian University of Science and Technology, Levanger, Norway 6. German Center for Diabetes Research (DZD), München-Neuherberg, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany 7. Biomolecular Mass Spectrometry, Max Planck Institute for Heart and Lung Research, Ludwigstrasse 43, Bad Nauheim 61231, Germany 8.
    [Show full text]
  • S41598-021-81940-Y.Pdf
    www.nature.com/scientificreports OPEN Understanding the genetic architecture of the metabolically unhealthy normal weight and metabolically healthy obese phenotypes in a Korean population Jae‑Min Park1,2,5, Da‑Hyun Park3,5, Youhyun Song1, Jung Oh Kim3, Ja‑Eun Choi3, Yu‑Jin Kwon4, Seong‑Jin Kim3, Ji‑Won Lee1* & Kyung‑Won Hong3* Understanding the mechanisms underlying the metabolically unhealthy normal weight (MUHNW) and metabolically healthy obese (MHO) phenotypes is important for developing strategies to prevent cardiometabolic diseases. Here, we conducted genome‑wide association studies (GWASs) to identify the MUHNW and MHO genetic indices. The study dataset comprised genome‑wide single‑nucleotide polymorphism genotypes and epidemiological data from 49,915 subjects categorised into four phenotypes—metabolically healthy normal weight (MHNW), MUHNW, MHO, and metabolically unhealthy obese (MUHO). We conducted two GWASs using logistic regression analyses and adjustments for confounding variables (model 1: MHNW versus MUHNW and model 2: MHO versus MUHO). GCKR, ABCB11, CDKAL1, LPL, CDKN2B, NT5C2, APOA5, CETP, and APOC1 were associated with metabolically unhealthy phenotypes among normal weight individuals (model 1). LPL, APOA5, and CETP were associated with metabolically unhealthy phenotypes among obese individuals (model 2). The genes common to both models are related to lipid metabolism (LPL, APOA5, and CETP), and those associated with model 1 are related to insulin or glucose metabolism (GCKR, CDKAL1, and CDKN2B). This study reveals the genetic architecture of the MUHNW and MHO phenotypes in a Korean population‑based cohort. These fndings could help identify individuals at a high metabolic risk in normal weight and obese populations and provide potential novel targets for the management of metabolically unhealthy phenotypes.
    [Show full text]
  • Linkage and Association Analysis of Obesity Traits Reveals Novel Loci and Interactions with Dietary N-3 Fatty Acids in an Alaska Native (Yup’Ik) Population
    METABOLISM CLINICAL AND EXPERIMENTAL XX (2015) XXX– XXX Available online at www.sciencedirect.com Metabolism www.metabolismjournal.com Linkage and association analysis of obesity traits reveals novel loci and interactions with dietary n-3 fatty acids in an Alaska Native (Yup’ik) population Laura Kelly Vaughan a, Howard W. Wiener b, Stella Aslibekyan b, David B. Allison c, Peter J. Havel d, Kimber L. Stanhope d, Diane M. O’Brien e, Scarlett E. Hopkins e, Dominick J. Lemas f, Bert B. Boyer e,⁎, Hemant K. Tiwari c a Department of Biology, King University, 1350 King College Rd, Bristol, TN 37620, USA b Department of Epidemiology, University of Alabama at Birmingham, 1665 University Blvd, Birmingham, AL 35294, USA c Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, 1665 University Blvd, Birmingham, AL 35294, USA d Departments of Nutrition and Molecular Biosciences, University of California at Davis, 1 Shields Ave, Davis, CA 95616, USA e USACenter for Alaska Native Health Research, Institute of Arctic Biology, 311 Irving I Building, University of Alaska Fairbanks, Fairbanks, AK 99775, USA f Department of Pediatrics, Section of Neonatology, University of Colorado Anschutz Medical Campus, 13123 East 16th Ave, Aurora, CO 80045, USA ARTICLE INFO ABSTRACT Article history: Objective. To identify novel genetic markers of obesity-related traits and to identify gene- Received 16 June 2014 diet interactions with n-3 polyunsaturated fatty acid (n-3 PUFA) intake in Yup’ik people. Accepted 28 February 2015 Material and methods. We measured body composition, plasma adipokines and ghrelin in 982 participants enrolled in the Center for Alaska Native Health Research (CANHR) Study.
    [Show full text]
  • Genome-Wide Association Analysis of Pancreatic Beta-Cell Glucose
    The Journal of Clinical Endocrinology & Metabolism, 2021, Vol. 106, No. 1, 80–90 doi:10.1210/clinem/dgaa653 Clinical Research Article Clinical Research Article Genome-Wide Association Analysis of Pancreatic Beta-Cell Glucose Sensitivity Downloaded from https://academic.oup.com/jcem/article/106/1/80/5908126 by guest on 30 September 2021 Harshal A. Deshmukh,1,* Anne Lundager Madsen,2,* Ana Viñuela,3 Christian Theil Have,2 Niels Grarup,2 Andrea Tura,4 Anubha Mahajan,5,6 Alison J. Heggie,1 Robert W. Koivula,6,7 Federico De Masi,8 Konstantinos K. Tsirigos,8 Allan Linneberg,9,10 Thomas Drivsholm,9,11 Oluf Pedersen,2 Thorkild I. A. Sørensen,12,13 Arne Astrup,14 Anette A. P. Gjesing,2 Imre Pavo,15 Andrew R. Wood,16 Hartmut Ruetten,17 Angus G. Jones,18 Anitra D. M. Koopman,19 Henna Cederberg,20 Femke Rutters,19 Martin Ridderstrale,21 Markku Laakso,22 Mark I. McCarthy,23 Tim M. Frayling,16 Ele Ferrannini,24 Paul W. Franks,6,7,25,26 Ewan R. Pearson,27 Andrea Mari,4 Torben Hansen,2 and Mark Walker1 1Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE2 4HH UK; 2Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, DK-2100 Copenhagen, Denmark; 3Department of Genetic Medicine and Development, University of Geneva Medical School, 1211, Geneva; 4Institute of Neuroscience, National Research Council, Corso Stati Uniti 4, 35127 Padua, Italy; 5Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7BN, UK,6 Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7LE, UK; 7Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Skåne University Hospital Malmö, Lund University, 205 02 Malmö, Sweden; 8Integrative Systems Biology Group, Department of Health Technology, Technical University of Denmark (DTU), Kemitorvet, Building 208, 2800 Kgs.
    [Show full text]
  • Genome-Wide Analysis of Histone Modifications in Human Pancreatic Islets
    Downloaded from genome.cshlp.org on September 26, 2021 - Published by Cold Spring Harbor Laboratory Press Research Genome-wide analysis of histone modifications in human pancreatic islets Reena Bhandare,1,2,4 Jonathan Schug,1,2,4 John Le Lay,1,2 Alan Fox,1,2 Olga Smirnova,1,2 Chengyang Liu,2,3 Ali Naji,2,3 and Klaus H. Kaestner1,2,5 1Department of Genetics, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania 19104, USA; 2Institute for Diabetes, Obesity, and Metabolism, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania 19104, USA; 3Department of Surgery, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania 19104, USA The global diabetes epidemic poses a major challenge. Epigenetic events contribute to the etiology of diabetes; however, the lack of epigenomic analysis has limited the elucidation of the mechanistic basis for this link. To determine the epi- genetic architecture of human pancreatic islets we mapped the genome-wide locations of four histone marks: three as- sociated with gene activation—H3K4me1, H3K4me2, and H3K4me3—and one associated with gene repression, H3K27me3. Interestingly, the promoters of the highly transcribed insulin and glucagon genes are occupied only sparsely by H3K4me2 and H3K4me3. Globally, we identified important relationships between promoter structure, histone modification, and gene expression. We demonstrated co-occurrences of histone modifications including bivalent marks in mature islets. Furthermore, we found a set of promoters that is differentially modified between islets and other cell types. We also use our histone marks to determine which of the known diabetes-associated single-nucleotide polymorphisms are likely to be part of regulatory elements.
    [Show full text]
  • UC San Francisco Previously Published Works
    UCSF UC San Francisco Previously Published Works Title FitSNPs: highly differentially expressed genes are more likely to have variants associated with disease. Permalink https://escholarship.org/uc/item/91k8p2km Journal Genome biology, 9(12) ISSN 1474-7596 Authors Chen, Rong Morgan, Alex A Dudley, Joel et al. Publication Date 2008 DOI 10.1186/gb-2008-9-12-r170 Peer reviewed eScholarship.org Powered by the California Digital Library University of California Open Access Research2008ChenetVolume al. 9, Issue 12, Article R170 FitSNPs: highly differentially expressed genes are more likely to have variants associated with disease Rong Chen*†‡, Alex A Morgan*†‡, Joel Dudley*†‡, Tarangini Deshpande§, Li Li†, Keiichi Kodama*†‡, Annie P Chiang*†‡ and Atul J Butte*†‡ Addresses: *Stanford Center for Biomedical Informatics Research, 251 Cmpus Drive, Stanford, CA 94305, USA. †Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA. ‡Lucile Packard Children's Hospital, 725 Welch Road, Palo Alto, CA 94304, USA. §NuMedii Inc., Menlo Park, CA 94025, USA. Correspondence: Atul J Butte. Email: [email protected] Published: 5 December 2008 Received: 17 June 2008 Revised: 26 September 2008 Genome Biology 2008, 9:R170 (doi:10.1186/gb-2008-9-12-r170) Accepted: 5 December 2008 The electronic version of this article is the complete one and can be found online at http://genomebiology.com/2008/9/12/R170 © 2008 Chen et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
    [Show full text]
  • Correlation Between CDKAL1 Rs10946398c>A Single Nucleotide
    Open Life Sci. 2017; 12: 501–509 Research Article Yunyi Liang, Yi Shu, Haizhao Luo, Riqiu Chen, Zhifu Zeng* Correlation between CDKAL1 rs10946398C>A single nucleotide polymorphism and type 2 diabetes mellitus susceptibility: A meta-analysis https://doi.org/10.1515/biol-2017-0059 showed people with AA or CA genotype had decreased Received September 19, 2017; accepted October 17, 2017 risk of developing T2DM compared to CC genotype (OR=0.83, P<0.05); For a homozygous genetic model (CC Abstract: Objective The purpose of this meta- vs AA), the OR was calculated through random effect analysis was to assess the correlation between CDKAL1 model for statistical heterogeneity among the included rs10946398C>A single nucleotide polymorphism (SNP) 13 studies. The combined OR was 1.33 which indicated and type 2 diabetes mellitus (T2DM) susceptibility by people with CC genotype had increased risk of developing pooling the open published studies. Method Electronic T2DM. Conclusion According to the present results, searching of PubMed, EMBASE, Medline, Cochrane, CDKAL1 rs10946398C>A single nucleotide polymorphism China Biology Medicine disc (CBM) and China National had correlation with the susceptibility of type 2 diabetes Knowledge Infrastructure (CNKI) databases were mellitus. performed by two reviewers independently to collect the open published studies related to CDKAL1 rs10946398C>A Keywords: type 2 diabetes mellitus; CDKAL1 gene; single nucleotide polymorphism and T2DM susceptibility. susceptibility; polymorphism; meta-analysis. The association between CDKAL1 rs10946398C>A single nucleotide polymorphism and T2DM susceptibility was expressed by odds ratio (OR) and the corresponding 95% confidence interval (95%CI). Results Thirteen studies with a total of 13,966 T2DM and 14,274 controls were 1 Introduction finally included for analysis in this meta-analysis.
    [Show full text]
  • Supplementary Tables 1-6 Supplementary Table 1
    Novel pleiotropic risk loci for melanoma and nevus density implicate multiple biological pathways Supplementary Tables 1-6 Supplementary Table 1. Meta-analysis heterogeneity and meta-regression results for nevus association using the R metafor package. The meta- regression included mean age in the study, mean absolute latitude and nevus measurement method as moderators. In the meta-regression, I2 is the estimated percentage of sampling variance due to heterogeneity between studies, R2 the percentage explained by the moderator variables, and H2 the percentage unexplained residual heterogeneity. QM P is the P-value from the test for the contribution of moderators, and QE P, the P-value for the test for residual heterogeneity. Random Effects (REML) meta-analysis Meta-regression (covariates: mean age, latitude, nevus measure) SNP Gene/Interval 2 2 2 Z P Het P H R I QE P QM P rs72704658 SETDB1 -1.783 7.46E-02 0.696 1.029 0.000 2.774 0.307 0.978 rs2695237 PARP1 -2.902 3.71E-03 0.525 1.000 95.683 0.022 0.251 0.871 rs4670813 CYP1B1 -5.001 5.70E-07 0.585 1.231 0.000 18.763 0.402 0.778 rs55875066 HDAC4 3.887 1.02E-04 0.203 1.928 0.000 48.135 0.082 0.916 rs12696304 TERC -4.536 5.73E-06 0.719 1.147 0.000 12.795 0.493 0.839 rs251464 PPARGC1B -3.833 1.26E-04 0.083 2.058 0.000 51.417 0.039 0.833 rs12203592 IRF4 1.216 2.24E-01 3.35E-51 3.245 79.689 69.187 0.013 7.02E-6 rs1636744 TCONS_l2_00025686 3.061 2.21E-03 0.684 1.000 0.000 0.000 0.625 0.550 rs600951 DOCK8 2.590 9.59E-03 5.86E-04 2.775 1.573 63.965 0.009 0.327 rs869329 MTAP 5.490 4.01E-08 1.72E-05
    [Show full text]
  • Common Variants in TCF7L2 and CDKAL1 Genes and Risk of Type 2 Diabetes Mellitus in Egyptians
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Journal of Genetic Engineering and Biotechnology (2016) 14, 247–251 HOSTED BY Academy of Scientific Research & Technology and National Research Center, Egypt Journal of Genetic Engineering and Biotechnology www.elsevier.com/locate/jgeb ORIGINAL ARTICLE Common variants in TCF7L2 and CDKAL1 genes and risk of type 2 diabetes mellitus in Egyptians Dalia El-Lebedy *, Ingy Ashmawy Department of Clinical and Chemical Pathology, Medical Research Division, National Research Centre, Cairo, Egypt Received 17 July 2016; revised 21 September 2016; accepted 17 October 2016 Available online 5 November 2016 KEYWORDS Abstract In this work we studied association of common variants in transcription factor 7-like 2 Type 2 diabetes mellitus; (TCF7L2) and cyclin-dependent kinase 5 regulatory subunit-associated protein 1-like 1 (CDKAL1) TCF7L2; genes with type 2 diabetes mellitus (T2DM) in Egyptians. CDKAL1; Subjects and methods: This is a case–control study; 180 T2DM patients and 210 control subjects Polymorphism were genotyped for TCF7L2 rs7903146 and rs12255372 and CDKAL1 rs7756992 single nucleotide polymorphisms (SNPs) by TaqMan method on real time polymerase chain reaction system (real time-PCR). Results: TCF7L2 rs12255372 and rs7903146 associated with T2DM (p = 0.0001 and 0.003; respectively). The rs12255372 variant T allele associated with 2-fold increased risk for T2DM and TT genotype carriers were at 3.58-folds higher risk to develop T2DM than wild genotype (GG) carriers. Meanwhile, rs7903146 variant T allele associated with 1.6-fold increased risk for T2DM and TT genotype carriers were at 2.3-folds higher risk than wild genotype (CC) carriers.
    [Show full text]
  • Implication of CDKAL1 Single-Nucleotide Polymorphism Rs 9465871 in Obese and Non-Obese Egyptian Children
    ORIGINAL ARTICLE Implication of CDKAL1 single-nucleotide polymorphism rs 9465871 in obese and non-obese Egyptian children Nagwa Abdallah Ismail, MD 1, ShadiaRagab, MD 2, Soha M. Abd El Dayem, MD 1, Abeer M Nour Eldin Abd El Baky, MD 1, Mona Hamed, MD 2, Solaf Ahmed Kamel, MD 2, Dalia Adel Abd El Halim, MD 2 1Pediatric Department, Medical Division, National Research Centre, Cairo, Egypt, 2Clinical & Chemical Pathology Department, Medical Division, National Research Centre, Cairo Egypt done by Genome-wide association studies (GWAS). 3, 4 In ABSTRACT Africa, the underlying genetic background remains Introduction:CDKAL1 single-nucleotide polymorphism rs unknown. There has been recent progress in describing the 9465871variant is a risk locus for Type 2 Diabetes genetic variations of obesity among populations within (T2DM).The study evaluated the associations of CDKAL1- Africa. This effort needs to be supported by GWAS studies. 5 rs9465871 with glycosylated hemoglobin A1C Level (HbA1c), fasting insulin level, insulin resistance and metabolic Obesity is the most common finding in children with type 2 syndrome among obese and non- obese Egyptian children. diabetes. 6 The genetic activities during childhood may have a role for the later development of type 2 diabetes. Type 2 Materials and Methods: The study included 43 obese diabetes occurs when the body cannot efficiently use the children and 40 normal weight children. Anthropometric insulin that is produced because the cells have become body measurements, bio-specimen and biochemistry resistant. Over time, insulin resistance can lead to assays were done. Genotyping of rs9465871 (CDKAL1) was prediabetes and type 2 diabetes because the beta cells fail to conducted.
    [Show full text]
  • Association of CDKAL1 Genetic Polymorphism with Glycosylated
    abetes & Di M f e o t a l b a o Jiang et al., J Diabetes Metab 2011, 2:9 n l r i s u m o DOI: 10.4172/2155-6156.1000166 J Journal of Diabetes and Metabolism ISSN: 2155-6156 Research Article Open Access Association of CDKAL1 Genetic Polymorphism with Glycosylated Hemoglobin A1c Level among Non-Diabetic Chinese Adults Jun-yi Jiang1, Hua Qiu2, Gen-ming Zhao1, Yi Zhou2, Miao Mo1, Le Shu1, Lu-xi Yang1, Si-yu Yu2, Qing-wu Jiang1, Xiao-nan Ruan2* and Wang- hong Xu1* 1Department of Epidemiology, School of Public Health; Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, 138 Yi Xue Yuan Road, Shanghai, 200032, People’s Republic of China 2Pudong New Area Centers for Disease Control and Prevention, 3039 Zhang Yang Road, Shanghai 200136, People’s Republic of China Abstract Objectives: Multiple single nucleotide polymorphisms (SNPs) have been identified as risk loci for type 2 diabetes (T2DM). This study was conducted to increase our understanding of the mechanisms through which three novel risk variants affect the risk of T2DM. Methods: 918 Chinese volunteers from Pudong New Area of Shanghai, China, were recruited in Oct-Dec, 2006. Collection of demographic and lifestyle characteristics, body measurements, bio-specimen collection and biochemistry assays were performed during the period. Genotyping of rs290487 at transcription factor 7-like 2 (TCF7L2), rs9465871 at cyclin-dependent kinase 5 regulatory subunit associated protein 1-like 1(CDKAL1) and rs1359790 at chromosome 13q31.1 were conducted using Taqman approach. Results: Genotypes of TCF7L2-rs290487, CDKAL1-rs9465871 and rs1359790 at 13q31.1 were not associated with metabolic syndrome or its components.
    [Show full text]