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Gustafson D, DiStefano PV, Wang XF, Wu R, Ghaffari S, Ching C, Rathnakumar K, Alibhai F, Syonov M, Fitzpatrick J, Boudreau E, Lau C, Galant N, Husain M, Li RK, Lee WL, Parekh RS, Monnier PP, Fish JE. Circulating small extracellular vesicles mediate vascular hyperpermeability in diabetes. Diabetologia 2024; 67:1138-1154. [PMID: 38489029 PMCID: PMC11058313 DOI: 10.1007/s00125-024-06120-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 01/30/2024] [Indexed: 03/17/2024]
Abstract
AIMS/HYPOTHESIS A hallmark chronic complication of type 2 diabetes mellitus is vascular hyperpermeability, which encompasses dysfunction of the cerebrovascular endothelium and the subsequent development of associated cognitive impairment. The present study tested the hypothesis that during type 2 diabetes circulating small extracellular vesicles (sEVs) exhibit phenotypic changes that facilitate pathogenic disruption of the vascular barrier. METHODS sEVs isolated from the plasma of a mouse model of type 2 diabetes and from diabetic human individuals were characterised for their ability to disrupt the endothelial cell (EC) barrier. The contents of sEVs and their effect on recipient ECs were assessed by proteomics and identified pathways were functionally interrogated with small molecule inhibitors. RESULTS Using intravital imaging, we found that diabetic mice (Leprdb/db) displayed hyperpermeability of the cerebrovasculature. Enhanced vascular leakiness was recapitulated following i.v. injection of sEVs from diabetic mice into non-diabetic recipient mice. Characterisation of circulating sEV populations from the plasma of diabetic mice and humans demonstrated increased quantity and size of sEVs compared with those isolated from non-diabetic counterparts. Functional experiments revealed that sEVs from diabetic mice or humans induced the rapid and sustained disruption of the EC barrier through enhanced paracellular and transcellular leak but did not induce inflammation. Subsequent sEV proteome and recipient EC phospho-proteome analysis suggested that extracellular vesicles (sEVs) from diabetic mice and humans modulate the MAPK/MAPK kinase (MEK) and Rho-associated protein kinase (ROCK) pathways, cell-cell junctions and actin dynamics. This was confirmed experimentally. Treatment of sEVs with proteinase K or pre-treatment of recipient cells with MEK or ROCK inhibitors reduced the hyperpermeability-inducing effects of circulating sEVs in the diabetic state. CONCLUSIONS/INTERPRETATION Diabetes is associated with marked increases in the concentration and size of circulating sEVs. The modulation of sEV-associated proteins under diabetic conditions can induce vascular leak through activation of the MEK/ROCK pathway. These data identify a new paradigm by which diabetes can induce hyperpermeability and dysfunction of the cerebrovasculature and may implicate sEVs in the pathogenesis of cognitive decline during type 2 diabetes.
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Affiliation(s)
- Dakota Gustafson
- Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Peter V DiStefano
- Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
| | - Xue Fan Wang
- Division of Fundamental Neurobiology, Toronto Western Research Institute, University Health Network, Toronto, ON, Canada
| | - Ruilin Wu
- Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Siavash Ghaffari
- Keenan Research Centre for Biomedical Science, St Michael's Hospital, Toronto, ON, Canada
| | - Crizza Ching
- Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | | | - Faisal Alibhai
- Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
| | - Michal Syonov
- Keenan Research Centre for Biomedical Science, St Michael's Hospital, Toronto, ON, Canada
| | - Jessica Fitzpatrick
- Department of Medicine and Pediatrics, Women's College Hospital, Hospital for Sick Children and University of Toronto, Toronto, ON, Canada
| | - Emilie Boudreau
- Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
| | - Cori Lau
- Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Natalie Galant
- Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
| | - Mansoor Husain
- Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Ren-Ke Li
- Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
| | - Warren L Lee
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
- Keenan Research Centre for Biomedical Science, St Michael's Hospital, Toronto, ON, Canada
- Department of Biochemistry, University of Toronto, Toronto, ON, Canada
| | - Rulan S Parekh
- Department of Medicine and Pediatrics, Women's College Hospital, Hospital for Sick Children and University of Toronto, Toronto, ON, Canada
| | - Philippe P Monnier
- Division of Fundamental Neurobiology, Toronto Western Research Institute, University Health Network, Toronto, ON, Canada
- Donald K. Johnson Eye Institute, Krembil Research Institute, University Health Network, Toronto, ON, Canada
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Jason E Fish
- Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada.
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada.
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada.
- Peter Munk Cardiac Centre, University Health Network, Toronto, ON, Canada.
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Looker HC, Chang DC, Baier LJ, Hanson RL, Nelson RG. Diagnostic criteria and etiopathogenesis of type 2 diabetes and its complications: Lessons from the Pima Indians. Presse Med 2023; 52:104176. [PMID: 37783422 PMCID: PMC10805453 DOI: 10.1016/j.lpm.2023.104176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 03/28/2023] [Accepted: 07/19/2023] [Indexed: 10/04/2023] Open
Abstract
The Phoenix Epidemiology and Clinical Research Branch of the National Institute of Diabetes and Digestive and Kidney Diseases has conducted prospective studies of diabetes and its complications in the Pima Indians living in Arizona, USA for over 50 years. In this review we highlight areas in which these studies provided vital insights into the criteria used to diagnose type 2 diabetes, the pathophysiologic changes that accompany the development of type 2 diabetes, and the course and determinants of diabetes complications-focusing specifically on diabetic kidney disease. We include data from our longitudinal population-based study of diabetes and its complications, studies on the role of insulin resistance and insulin secretion in the pathophysiology of type 2 diabetes, and in-depth studies of diabetic kidney disease that include measures of glomerular function and research kidney biopsies. We also focus on the emerging health threat posed by youth-onset type 2 diabetes, which was first seen in the Pima Indians in the 1960s and is becoming an increasing issue worldwide.
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Affiliation(s)
- Helen C Looker
- Chronic Kidney Disease Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - Douglas C Chang
- Obesity and Diabetes Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - Leslie J Baier
- Diabetes Molecular Genetics Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - Robert L Hanson
- Diabetes Genetic Epidemiology Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - Robert G Nelson
- Chronic Kidney Disease Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA.
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3
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Fernández-Rhodes L, Graff M, Buchanan VL, Justice AE, Highland HM, Guo X, Zhu W, Chen HH, Young KL, Adhikari K, Palmer ND, Below JE, Bradfield J, Pereira AC, Glover L, Kim D, Lilly AG, Shrestha P, Thomas AG, Zhang X, Chen M, Chiang CW, Pulit S, Horimoto A, Krieger JE, Guindo-Martínez M, Preuss M, Schumann C, Smit RA, Torres-Mejía G, Acuña-Alonzo V, Bedoya G, Bortolini MC, Canizales-Quinteros S, Gallo C, González-José R, Poletti G, Rothhammer F, Hakonarson H, Igo R, Adler SG, Iyengar SK, Nicholas SB, Gogarten SM, Isasi CR, Papnicolaou G, Stilp AM, Qi Q, Kho M, Smith JA, Langefeld CD, Wagenknecht L, Mckean-Cowdin R, Gao XR, Nousome D, Conti DV, Feng Y, Allison MA, Arzumanyan Z, Buchanan TA, Ida Chen YD, Genter PM, Goodarzi MO, Hai Y, Hsueh W, Ipp E, Kandeel FR, Lam K, Li X, Nadler JL, Raffel LJ, Roll K, Sandow K, Tan J, Taylor KD, Xiang AH, Yao J, Audirac-Chalifour A, de Jesus Peralta Romero J, Hartwig F, Horta B, Blangero J, Curran JE, Duggirala R, Lehman DE, Puppala S, Fejerman L, John EM, Aguilar-Salinas C, Burtt NP, Florez JC, García-Ortíz H, González-Villalpando C, Mercader J, Orozco L, Tusié-Luna T, Blanco E, Gahagan S, Cox NJ, Hanis C, Butte NF, Cole SA, Comuzzie AG, Voruganti VS, Rohde R, Wang Y, Sofer T, Ziv E, Grant SF, Ruiz-Linares A, Rotter JI, Haiman CA, Parra EJ, Cruz M, Loos RJ, North KE. Ancestral diversity improves discovery and fine-mapping of genetic loci for anthropometric traits-The Hispanic/Latino Anthropometry Consortium. HGG ADVANCES 2022; 3:100099. [PMID: 35399580 PMCID: PMC8990175 DOI: 10.1016/j.xhgg.2022.100099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Accepted: 03/06/2022] [Indexed: 02/05/2023] Open
Abstract
Hispanic/Latinos have been underrepresented in genome-wide association studies (GWAS) for anthropometric traits despite their notable anthropometric variability, ancestry proportions, and high burden of growth stunting and overweight/obesity. To address this knowledge gap, we analyzed densely imputed genetic data in a sample of Hispanic/Latino adults to identify and fine-map genetic variants associated with body mass index (BMI), height, and BMI-adjusted waist-to-hip ratio (WHRadjBMI). We conducted a GWAS of 18 studies/consortia as part of the Hispanic/Latino Anthropometry (HISLA) Consortium (stage 1, n = 59,771) and generalized our findings in 9 additional studies (stage 2, n = 10,538). We conducted a trans-ancestral GWAS with summary statistics from HISLA stage 1 and existing consortia of European and African ancestries. In our HISLA stage 1 + 2 analyses, we discovered one BMI locus, as well as two BMI signals and another height signal each within established anthropometric loci. In our trans-ancestral meta-analysis, we discovered three BMI loci, one height locus, and one WHRadjBMI locus. We also identified 3 secondary signals for BMI, 28 for height, and 2 for WHRadjBMI in established loci. We show that 336 known BMI, 1,177 known height, and 143 known WHRadjBMI (combined) SNPs demonstrated suggestive transferability (nominal significance and effect estimate directional consistency) in Hispanic/Latino adults. Of these, 36 BMI, 124 height, and 11 WHRadjBMI SNPs were significant after trait-specific Bonferroni correction. Trans-ancestral meta-analysis of the three ancestries showed a small-to-moderate impact of uncorrected population stratification on the resulting effect size estimates. Our findings demonstrate that future studies may also benefit from leveraging diverse ancestries and differences in linkage disequilibrium patterns to discover novel loci and additional signals with less residual population stratification.
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Affiliation(s)
- Lindsay Fernández-Rhodes
- Department of Biobehavioral Health, Pennsylvania State University, 219 Biobehavioral Health Building, University Park, PA 16802, USA
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Victoria L. Buchanan
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Anne E. Justice
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Biomedical and Translational Informatics, Geisinger Health System, Danville, PA 17822, USA
| | - Heather M. Highland
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Wanying Zhu
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Hung-Hsin Chen
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Kristin L. Young
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Kaustubh Adhikari
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, MK7 6AA Milton Keynes, UK
| | - Nicholette D. Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC 27101, USA
| | - Jennifer E. Below
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Jonathan Bradfield
- Center for Applied Genomics, Division of Human Genetics, Department of Pediatrics, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Alexandre C. Pereira
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of São Paulo, São Paulo 05508-220, Brazil
| | - LáShauntá Glover
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Daeeun Kim
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Adam G. Lilly
- Department of Sociology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Poojan Shrestha
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Division of Pediatric and Public Health, Adams School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Alvin G. Thomas
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Xinruo Zhang
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Minhui Chen
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Charleston W.K. Chiang
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90007, USA
| | - Sara Pulit
- Vertex Pharmaceuticals, W2 6BD Oxford, UK
| | - Andrea Horimoto
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of São Paulo, São Paulo 05508-220, Brazil
| | - Jose E. Krieger
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of São Paulo, São Paulo 05508-220, Brazil
| | - Marta Guindo-Martínez
- The Charles Bronfman Institutes for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- The Novo Nordisk Center for Basic Metabolic Research, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Michael Preuss
- The Charles Bronfman Institutes for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Claudia Schumann
- Hasso Plattner Institute, University of Potsdam, Digital Health Center, 14482 Potsdam, Germany
| | - Roelof A.J. Smit
- The Charles Bronfman Institutes for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Gabriela Torres-Mejía
- Department of Research in Cardiovascular Diseases, Diabetes Mellitus, and Cancer, Population Health Research Center, National Institute of Public Health, Cuernavaca, Morelos 62100, Mexico
| | | | - Gabriel Bedoya
- Molecular Genetics Investigation Group, University of Antioquia, Medellín 1226, Colombia
| | - Maria-Cátira Bortolini
- Department of Genetics, Federal University of Rio Grande do Sul, Porto Alegre 90040-060, Brazil
| | - Samuel Canizales-Quinteros
- Population Genomics Applied to Health Unit, The National Institute of Genomic Medicine and the Faculty of Chemistry at the National Autonomous University of Mexico, Mexico City 04510, Mexico
| | - Carla Gallo
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 15102, Peru
| | - Rolando González-José
- Patagonian Institute of the Social and Human Sciences, Patagonian National Center, Puerto Madryn U9120, Argentina
| | - Giovanni Poletti
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 15102, Peru
| | | | - Hakon Hakonarson
- Center for Applied Genomics, Division of Human Genetics, Department of Pediatrics, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Robert Igo
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Sharon G. Adler
- Division of Nephrology and Hypertension, Harbor-University of California Los Angeles Medical Center, Torrance, CA 90502, USA
| | - Sudha K. Iyengar
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Susanne B. Nicholas
- Department of Medicine, David Geffen School of Medicine at University of California, Los Angeles, CA 90095, USA
| | | | - Carmen R. Isasi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | | | - Adrienne M. Stilp
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Minjung Kho
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Carl D. Langefeld
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC 27101, USA
| | - Lynne Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC 27101, USA
| | - Roberta Mckean-Cowdin
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA
| | - Xiaoyi Raymond Gao
- Department of Ophthalmology and Visual Sciences, Department of Biomedical Informatics, Division of Human Genetics, The Ohio State University, Columbus, OH 43210, USA
| | - Darryl Nousome
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA
| | - David V. Conti
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Ye Feng
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA
| | - Matthew A. Allison
- Department of Family Medicine, University of California, San Diego, CA 92161, USA
| | - Zorayr Arzumanyan
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Thomas A. Buchanan
- Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Pauline M. Genter
- Department of Medicine, Division of Endocrinology, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Mark O. Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Yang Hai
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Willa Hsueh
- Department of Internal Medicine, The Ohio State University Wexner Medical Center, Columbus, OH 43210, USA
| | - Eli Ipp
- Department of Medicine, David Geffen School of Medicine at University of California, Los Angeles, CA 90095, USA
- Department of Medicine, Division of Endocrinology, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Fouad R. Kandeel
- Department of Translational Research & Cellular Therapeutics, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Kelvin Lam
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Xiaohui Li
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Jerry L. Nadler
- Department of Pharmacology at New York Medical College School of Medicine, Valhalla, NY 10595, USA
| | - Leslie J. Raffel
- Division of Genetic and Genomic Medicine, Department of Pediatrics, University of California, Irvine, CA 92697, USA
| | - Kathryn Roll
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Kevin Sandow
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Jingyi Tan
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Kent D. Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Anny H. Xiang
- Research and Evaluation Branch, Kaiser Permanente of Southern California, Pasadena, CA 91101, USA
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Astride Audirac-Chalifour
- Medical Research Unit in Biochemistry, Specialty Hospital, National Medical Center of the Twenty-First Century, Mexican Institute of Social Security, Mexico City 06725, Mexico
| | - Jose de Jesus Peralta Romero
- Medical Research Unit in Biochemistry, Specialty Hospital, National Medical Center of the Twenty-First Century, Mexican Institute of Social Security, Mexico City 06725, Mexico
| | - Fernando Hartwig
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas 96010-610, Brazil
| | - Bernando Horta
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas 96010-610, Brazil
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville and Edinburg, TX 78520 and 78539, USA
| | - Joanne E. Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville and Edinburg, TX 78520 and 78539, USA
| | - Ravindranath Duggirala
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville and Edinburg, TX 78520 and 78539, USA
| | - Donna E. Lehman
- Department of Medicine, School of Medicine, University of Texas Health San Antonio, San Antonio, TX 78229, USA
| | - Sobha Puppala
- Department of Internal Medicine, Section of Molecular Medicine, Wake Forest School of Medicine, Winston-Salem, NC 27109, USA
| | - Laura Fejerman
- Department of Public Health Sciences, School of Medicine, and the Comprehensive Cancer Center, University of California Davis, Davis, CA 95616, USA
| | - Esther M. John
- Departments of Epidemiology & Population Health and Medicine-Oncology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Carlos Aguilar-Salinas
- Division of Nutrition, Salvador Zubirán National Institute of Health Sciences and Nutrition, Mexico City 14080, Mexico
| | - Noël P. Burtt
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Jose C. Florez
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Humberto García-Ortíz
- Laboratory of Immunogenomics and Metabolic Diseases, National Institute of Genomic Medicine, Mexico City 14610, Mexico
| | - Clicerio González-Villalpando
- Center for Diabetes Studies, Research Unit for Diabetes and Cardiovascular Risk, Center for Population Health Studies, National Institute of Public Health, Mexico City 14080, Mexico
| | - Josep Mercader
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Lorena Orozco
- Laboratory of Immunogenomics and Metabolic Diseases, National Institute of Genomic Medicine, Mexico City 14610, Mexico
| | - Teresa Tusié-Luna
- Molecular Biology and Medical Genomics Unity, Institute of Biomedical Research, The National Autonomous University of Mexico and the Salvador Zubirán National Institute of Health Sciences and Nutrition, Mexico City 14080, Mexico
| | - Estela Blanco
- Center for Community Health, Division of Academic General Pediatrics, University of California at San Diego, San Diego, CA 92093, USA
| | - Sheila Gahagan
- Center for Community Health, Division of Academic General Pediatrics, University of California at San Diego, San Diego, CA 92093, USA
| | - Nancy J. Cox
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Craig Hanis
- University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Nancy F. Butte
- United States Department of Agriculture, Agricultural Research Service, The Children’s Nutrition Research Center, and the Department Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Shelley A. Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX 78227, USA
| | | | - V. Saroja Voruganti
- Department of Nutrition and Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC 28081, USA
| | - Rebecca Rohde
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Yujie Wang
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Tamar Sofer
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Elad Ziv
- Division of General Internal Medicine, Department of Medicine, Helen Diller Family Comprehensive Cancer Center, Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94115, USA
| | - Struan F.A. Grant
- Center for Applied Genomics, Division of Human Genetics, Department of Pediatrics, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Andres Ruiz-Linares
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Shanghai 200438, China
- Department of Genetics, Evolution and Environment, and Genetics Institute of the University College London, London WC1E 6BT, UK
- Laboratory of Biocultural Anthropology, Law, Ethics, and Health, Aix-Marseille University, Marseille 13385, France
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Christopher A. Haiman
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Esteban J. Parra
- Department of Anthropology, University of Toronto- Mississauga, Mississauga, ON L5L 1C6, Canada
| | - Miguel Cruz
- Medical Research Unit in Biochemistry, Specialty Hospital, National Medical Center of the Twenty-First Century, Mexican Institute of Social Security, Mexico City 06725, Mexico
| | - Ruth J.F. Loos
- The Charles Bronfman Institutes for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Kari E. North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
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4
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Adeshara KA, Bangar N, Diwan AG, Tupe RS. Plasma glycation adducts and various RAGE isoforms are intricately associated with oxidative stress and inflammatory markers in type 2 diabetes patients with vascular complications. Diabetes Metab Syndr 2022; 16:102441. [PMID: 35247657 DOI: 10.1016/j.dsx.2022.102441] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 02/19/2022] [Accepted: 02/21/2022] [Indexed: 10/19/2022]
Abstract
BACKGROUND The secondary vascular complications in diabetes mellitus (DM) are contributed by acute as well as inflammatory responses which get activated due to interaction between glycation adducts and respective receptors. AIM The present work was performed to understand the relationship between Advanced glycation end products (AGEs)-receptor for advanced glycation end products (RAGE) interaction with oxidative stress and inflammation in vascular complications. METHODS For the present work we recruited 103 controls, 200 patients with type 2 DM, and 200 patients with Diabetic complications. Different Plasma glycation adducts (fructosamine, carbonyls, AGEs, β-amyloid content, free amino groups, and free thiol groups); RAGE isoforms, level of antioxidant such as glutathione, catalase activity, nitric oxide level, total antioxidant capacity, and superoxide dismutase activity, as well as oxidative markers, and expression of Nε-carboxymethyl-lysine (CML), different isoforms of RAGE, NF-κB, and inflammatory markers were analyzed. RESULTS Glycation adducts were higher in DM patients and more elevated in nephropathy patients where free amino groups and thiol groups lowered as compared to controls. sRAGE levels and expression were increased mainly in nephropathy. CML expression was higher in nephropathy patients. The antioxidant profile indicates a reduced level of different antioxidants while increased lipid peroxidation and intracellular ROS generation in DM and much higher in nephropathy patients. Expression of membrane RAGE, NF-κB, and inflammatory markers showed a remarkably increased level in DM patients with nephropathy. CONCLUSION This work provides the first evidence of four different RAGE isoforms in diabetes and in complications. The glycation via the activation of RAGE, oxidative stress, and resultant inflammation plays a crucial role in the development of diabetic complications.
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Affiliation(s)
- Krishna A Adeshara
- Biochemical Sciences Division, Rajiv Gandhi Institute of IT and Biotechnology, Bharati Vidyapeeth (Deemed to be University), Pune, Maharashtra State, India; Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland; Abdominal Center, Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Nilima Bangar
- Symbiosis School of Biological Sciences (SSBS), Symbiosis International (Deemed University) (SIU), Lavale, Pune, Maharashtra State, India; Biochemical Sciences Division, Rajiv Gandhi Institute of IT and Biotechnology, Bharati Vidyapeeth (Deemed to be University), Pune, Maharashtra State, India
| | - Arundhati G Diwan
- Department of Medicine, Bharati Vidyapeeth's Medical College and Bharati Hospital, Bharati Vidyapeeth (Deemed to be University), Pune, Maharashtra State, India
| | - Rashmi S Tupe
- Symbiosis School of Biological Sciences (SSBS), Symbiosis International (Deemed University) (SIU), Lavale, Pune, Maharashtra State, India; Biochemical Sciences Division, Rajiv Gandhi Institute of IT and Biotechnology, Bharati Vidyapeeth (Deemed to be University), Pune, Maharashtra State, India.
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5
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Chen Y, Liang KY, Tong P, Beaty TH, Barnes KC, Linda Kao WH. A pseudolikelihood approach for assessing genetic association in case-control studies with unmeasured population structure. Stat Methods Med Res 2020; 29:3153-3165. [PMID: 32393154 DOI: 10.1177/0962280220921212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The case-control study design is one of the main tools for detecting associations between genetic markers and diseases. It is well known that population substructure can lead to spurious association between disease status and a genetic marker if the prevalence of disease and the marker allele frequency vary across subpopulations. In this paper, we propose a novel statistical method to estimate the association in case-control studies with unmeasured population substructure. The proposed method takes two steps. First, the information on genomic markers and disease status is used to infer the population substructure; second, the association between the disease and the test marker adjusting for the population substructure is modeled and estimated parametrically through polytomous logistic regression. The performance of the proposed method, relative to the existing methods, on bias, coverage probability and computational time, is assessed through simulations. The method is applied to an end-stage renal disease study in African Americans population.
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Affiliation(s)
- Yong Chen
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, USA
| | | | - Pan Tong
- Department of Bioinformatics & Computational Biology, University of Texas, Houston, USA
| | - Terri H Beaty
- Department of Epidemiology, Johns Hopkins University, Baltimore, USA
| | - Kathleen C Barnes
- University of Colorado Denver - Anschutz Medical Campus, Aurora, USA
| | - W H Linda Kao
- Department of Epidemiology, Johns Hopkins University, Baltimore, USA
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6
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Hanson RL, Safabakhsh S, Curtis JM, Hsueh WC, Jones LI, Aflague TF, Duenas Sarmiento J, Kumar S, Blackburn NB, Curran JE, Mahkee D, Baier LJ, Knowler WC, Nelson RG. Association of CREBRF variants with obesity and diabetes in Pacific Islanders from Guam and Saipan. Diabetologia 2019; 62:1647-1652. [PMID: 31280340 PMCID: PMC6721609 DOI: 10.1007/s00125-019-4932-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2019] [Accepted: 05/10/2019] [Indexed: 12/27/2022]
Abstract
AIMS/HYPOTHESIS Variants in CREBRF (rs12513649 and rs373863828) have been strongly associated with increased BMI and decreased risk of type 2 diabetes in Polynesian populations; the A allele at rs373863828 is common in Polynesians but rare in most other global populations. The aim of the present study was to assess the association of CREBRF variants with obesity and diabetes in Pacific Islander (largely Marianas and Micronesian) populations from Guam and Saipan. METHODS CREBRF rs12513649 and rs373863828 were genotyped in 2022 participants in a community-based cross-sectional study designed to identify determinants of diabetes and end-stage renal disease (ESRD). Associations were analysed with adjustment for age, sex, ESRD and the first four genetic principal components from a genome-wide association study (to account for population stratification); a genomic control procedure was used to account for residual stratification. RESULTS The G allele at rs12513649 had an overall frequency of 7.7%, which varied from 2.2% to 20.7% across different Marianas and Micronesian populations; overall frequency of the A allele at rs373863828 was 4.2% (range: 1.1-5.4%). The G allele at rs12513649 was associated with higher BMI (β = 1.55 kg/m2 per copy; p = 0.0026) as was the A allele at rs373863828 (β = 1.48 kg/m2, p = 0.033). The same alleles were associated with lower risk of diabetes (OR per copy: 0.63 [p = 0.0063] and 0.49 [p = 0.0022], respectively). Meta-analyses combining the current results with previous results in Polynesians showed a strong association between the A allele at rs373863828 and BMI (β = 1.38 kg/m2; p = 2.5 × 10-29) and diabetes (OR 0.65, p = 1.5 × 10-13). CONCLUSIONS/INTERPRETATION These results confirm the associations of CREBRF variants with higher BMI and lower risk of diabetes and, importantly, they suggest that these variants contribute to the risk of obesity and diabetes in Oceanic populations.
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Affiliation(s)
- Robert L Hanson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, 1550 E. Indian School Road, Phoenix, AZ, 85014, USA.
| | - Saied Safabakhsh
- Micronesian Institute for Disease Prevention and Research, Sinajana, Guam
| | - Jeffrey M Curtis
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, 1550 E. Indian School Road, Phoenix, AZ, 85014, USA
| | - Wen-Chi Hsueh
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, 1550 E. Indian School Road, Phoenix, AZ, 85014, USA
| | - Lois I Jones
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, 1550 E. Indian School Road, Phoenix, AZ, 85014, USA
| | - Tanisha F Aflague
- Micronesian Institute for Disease Prevention and Research, Sinajana, Guam
| | | | - Satish Kumar
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
- Department of Human Genetics, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Nicholas B Blackburn
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
- Department of Human Genetics, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Joanne E Curran
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
- Department of Human Genetics, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Darin Mahkee
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, 1550 E. Indian School Road, Phoenix, AZ, 85014, USA
| | - Leslie J Baier
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, 1550 E. Indian School Road, Phoenix, AZ, 85014, USA
| | - William C Knowler
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, 1550 E. Indian School Road, Phoenix, AZ, 85014, USA
| | - Robert G Nelson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, 1550 E. Indian School Road, Phoenix, AZ, 85014, USA
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7
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Kruzel-Davila E, Divers J, Russell GB, Kra-Oz Z, Cohen MS, Langefeld CD, Ma L, Lyles DS, Hicks PJ, Skorecki KL, Freedman BI. JC Viruria Is Associated With Reduced Risk of Diabetic Kidney Disease. J Clin Endocrinol Metab 2019; 104:2286-2294. [PMID: 30715336 PMCID: PMC6489692 DOI: 10.1210/jc.2018-02482] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Accepted: 01/25/2019] [Indexed: 11/19/2022]
Abstract
PURPOSE African Americans who shed JC polyomavirus (JCV) in their urine have reduced rates of nondiabetic chronic kidney disease (CKD). We assessed the associations between urinary JCV and urine BK polyomavirus (BKV) with CKD in African Americans with diabetes mellitus. METHODS African Americans with diabetic kidney disease (DKD) and controls lacking nephropathy from the Family Investigation of Nephropathy and Diabetes Consortium (FIND) and African American-Diabetes Heart Study (AA-DHS) had urine tested for JCV and BKV using quantitative PCR. Of the 335 individuals tested, 148 had DKD and 187 were controls. RESULTS JCV viruria was detected more often in the controls than in the patients with DKD (FIND: 46.6% vs 32.2%; OR, 0.52; 95% CI, 0.29 to 0.93; P = 0.03; AA-DHS: 30.4% vs 26.2%; OR, 0.63; 95% CI, 0.27 to 1.48; P = 0.29). A joint analysis adjusted for age, sex, and study revealed that JC viruria was inversely associated with DKD (OR, 0.56; 95% CI, 0.35 to 0.91; P = 0.02). Statistically significant relationships between BKV and DKD were not observed. MAIN CONCLUSIONS The results from the present study extend the inverse association between urine JCV and nondiabetic nephropathy in African Americans to DKD. These results imply that common pathways likely involving the innate immune system mediate coincident chronic kidney injury and restriction of JCV replication. Future studies are needed to explore causative pathways and characterize whether the absence of JC viruria can serve as a biomarker for DKD in the African American population.
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Affiliation(s)
- Etty Kruzel-Davila
- Department of Nephrology, Rambam Health Care Campus and Rappaport Faculty of Medicine and Research Institute, Technion-Israel Institute of Technology, Haifa, Israel
| | - Jasmin Divers
- Division of Public Health Sciences, Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Gregory B Russell
- Division of Public Health Sciences, Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Zipi Kra-Oz
- Virology Laboratory, Rambam Health Care Campus, Haifa, Israel
| | | | - Carl D Langefeld
- Division of Public Health Sciences, Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Lijun Ma
- Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Douglas S Lyles
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Pamela J Hicks
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Karl L Skorecki
- Department of Nephrology, Rambam Health Care Campus and Rappaport Faculty of Medicine and Research Institute, Technion-Israel Institute of Technology, Haifa, Israel
- Azrieli Faculty of Medicine, Bar-Ilan University, Tzefat, Israel
- Correspondence and Reprint Requests: Karl. L. Skorecki, MD, Azrieli Faculty of Medicine, Bar-Ilan University, Henrietta Szold, 8, PO Box 1589, Galilee 1311502, Israel. E-mail: ; or Barry I. Freedman, MD, Section on Nephrology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, North Carolina 27157-1053. E-mail:
| | - Barry I Freedman
- Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Correspondence and Reprint Requests: Karl. L. Skorecki, MD, Azrieli Faculty of Medicine, Bar-Ilan University, Henrietta Szold, 8, PO Box 1589, Galilee 1311502, Israel. E-mail: ; or Barry I. Freedman, MD, Section on Nephrology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, North Carolina 27157-1053. E-mail:
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8
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Sherman LD, Fawole T. "The More I Do, the Better I'll Be": The Treatment Preferences of Type 2 Diabetes Among African American Men. Am J Mens Health 2018; 12:779-787. [PMID: 27256886 PMCID: PMC6131424 DOI: 10.1177/1557988316642274] [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] [Indexed: 11/16/2022] Open
Abstract
To gain better insight to the preferred methods of managing and treating type 2 diabetes among African American men (AA men). Participants ( n = 19) were AA men aged 35 to 69 years, who were diagnosed with type 2 diabetes. Participants were recruited via community outreach efforts, including barbershops and churches located in predominantly African American communities in Southeast United States. On consent, individual interviews were conducted, audio recorded, and subsequently transcribed. Transcripts were analyzed using a phenomenological approach, and focused on identifying common themes among the descriptions of AA men's experiences specific to type 2 diabetes. Participants' statements indicated three main commonalities regarding treatment preferences which were medication, dietary changes, and increase in exercise. Some participants from the study stated that they preferred taking oral medication primarily out of convenience, lack of pain, and how well the medicine makes them feel. Others stated educating themselves and having a consistent relationship with the diabetes physician has assisted them the most. Other participants shared preferences of being dedicated to proper diet and exercise without any medication (pill or injection), as well as maintaining the mental motivation needed to sustain management. Some participants preferred to not take an oral pill, while some did not mind taking pills at all. For some of the participants, it appears that it is easier for them to manage their diabetes by prescription medication than by lifestyle changes such as diet and exercise. Future studies are needed to investigate how social support system also assists these men in managing their diabetes.
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9
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Daehn IS. Glomerular Endothelial Cell Stress and Cross-Talk With Podocytes in Early [corrected] Diabetic Kidney Disease. Front Med (Lausanne) 2018; 5:76. [PMID: 29629372 PMCID: PMC5876248 DOI: 10.3389/fmed.2018.00076] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2017] [Accepted: 03/07/2018] [Indexed: 12/11/2022] Open
Abstract
Diabetic kidney disease (DKD) is one of the major causes of morbidity and mortality in diabetic patients and also the leading single cause of end-stage renal disease in the United States. A large proportion of diabetic patients develop DKD and others don't, even with comparable blood glucose levels, indicating a significant genetic component of disease susceptibility. The glomerulus is the primary site of diabetic injury in the kidney, glomerular hypertrophy and podocyte depletion are glomerular hallmarks of progressive DKD, and the degree of podocyte loss correlates with severity of the disease. We know that chronic hyperglycemia contributes to both microvascular and macrovascular complications, as well as podocyte injury. We are beginning to understand the role of glomerular endothelial injury, as well as the involvement of reactive oxygen species and mitochondrial stress, which play a direct role in DKD and in other diabetic complications. There is, however, a gap in our knowledge that links genetic susceptibility to early molecular mechanisms and proteinuria in DKD. Emerging research that explores glomerular cell's specific responses to diabetes and cell cross-talk will provide mechanistic clues that underlie DKD and provide novel avenues for therapeutic intervention.
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Affiliation(s)
- Ilse Sofia Daehn
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, The Charles Bronfman Institute for Personalized Medicine, New York City, NY, United States
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10
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Bansal S, Friedrichs WE, Velagapudi C, Feliers D, Khazim K, Horn D, Cornell JE, Werner SL, Fanti P. Spleen contributes significantly to increased circulating levels of fibroblast growth factor 23 in response to lipopolysaccharide-induced inflammation. Nephrol Dial Transplant 2018; 32:960-968. [PMID: 27836924 DOI: 10.1093/ndt/gfw376] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2016] [Accepted: 09/20/2016] [Indexed: 12/19/2022] Open
Abstract
Background Circulating levels of fibroblast growth factor 23 (FGF23) increase progressively and correlate with systemic inflammation in chronic kidney disease (CKD). The aim of this study was to identify and characterize the causal relationship between FGF23 and inflammation in CKD. Methods Circulating FGF23 and inflammatory cytokines were correlated in healthy subjects and patients with varying levels of CKD. In addition, FGF23 expression in blood and solid organs was measured in normal mice that were exposed acutely (one time) or chronically (2-week) to low-dose lipopolysaccharide (LPS); chronic exposure being either sustained (subcutaneous pellets), intermittent (daily injections) or combined sustained plus acute (subcutaneous pellets plus acute injection on the day of sacrifice). Blood was analyzed for both terminal (cFGF23) and intact (iFGF23) FGF23 levels. Solid tissues were investigated with immunohistochemistry, enzyme-linked immunosorbent assay and reverse transcription polymerase chain reaction. Results FGF23 levels correlated significantly with neutrophil gelatinase-associated lipocalin ( r = 0.72, P < 0.001), C-reactive protein ( r = 0.38, P < 0.001), tumor necrosis factor-α ( r = 0.32, P = 0.001) and interleukin-6 ( r = 0.48, P < 0.001). Acute LPS administration increased tissue FGF23 mRNA and plasma levels of cFGF23 but not iFGF23. Neither chronic sustained nor chronic pulsatile LPS increased the tissue or circulating levels of FGF23. However, acute on chronic LPS raised tissue FGF23 mRNA and both circulating cFG23 and iFGF23. Interestingly, the spleen was the major source of FGF23. Conclusion Acute on chronic exposure to LPS stimulates FGF23 production in a normal mouse model of inflammation. We provide the first evidence that the spleen, under these conditions, contributes substantially to elevated circulating FGF23 levels.
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Affiliation(s)
- Shweta Bansal
- Division of Nephrology, Department of Medicine, University of Texas Health Sciences Center at San Antonio, San Antonio, TX 78229, USA.,Renal Section, South Texas Veterans Healthcare System, San Antonio, TX, USA
| | - William E Friedrichs
- Division of Nephrology, Department of Medicine, University of Texas Health Sciences Center at San Antonio, San Antonio, TX 78229, USA
| | - Chakradhar Velagapudi
- Division of Nephrology, Department of Medicine, University of Texas Health Sciences Center at San Antonio, San Antonio, TX 78229, USA.,Renal Section, South Texas Veterans Healthcare System, San Antonio, TX, USA
| | - Denis Feliers
- Division of Nephrology, Department of Medicine, University of Texas Health Sciences Center at San Antonio, San Antonio, TX 78229, USA
| | - Khaled Khazim
- Faculty of Medicine, Galilee Medical Center, Bar-Ilan University, Safed, Israel
| | - Diane Horn
- Department of Pathology, University of Texas Health Sciences Center at San Antonio and South Texas Veterans Healthcare System, San Antonio, TX, USA
| | - John E Cornell
- Department of Epidemiology & Biostatistics, University of Texas Health Sciences Center at San Antonio, San Antonio, TX, USA
| | - Sherry L Werner
- Department of Pathology, University of Texas Health Sciences Center at San Antonio and South Texas Veterans Healthcare System, San Antonio, TX, USA
| | - Paolo Fanti
- Division of Nephrology, Department of Medicine, University of Texas Health Sciences Center at San Antonio, San Antonio, TX 78229, USA
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11
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Debnath S, Velagapudi C, Redus L, Thameem F, Kasinath B, Hura CE, Lorenzo C, Abboud HE, O'Connor JC. Tryptophan Metabolism in Patients With Chronic Kidney Disease Secondary to Type 2 Diabetes: Relationship to Inflammatory Markers. Int J Tryptophan Res 2017; 10:1178646917694600. [PMID: 28469469 PMCID: PMC5398653 DOI: 10.1177/1178646917694600] [Citation(s) in RCA: 86] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2016] [Accepted: 01/26/2017] [Indexed: 12/21/2022] Open
Abstract
Objective: Type 2 diabetes (T2D) is the primary case of chronic kidney disease (CKD). Inflammation is associated with metabolic dysregulation in patients with T2D and CKD. Tryptophan (TRP) metabolism may have relevance to the CKD outcomes and associated symptoms. We investigated the relationships of TRP metabolism with inflammatory markers in patients with T2D and CKD. Methods: Data were collected from a well-characterized cohort of type 2 diabetic individuals with all stages of CKD, including patients on hemodialysis. Key TRP metabolites (kynurenine [KYN], kynurenic acid [KYNA], and quinolinic acid [QA]), proinflammatory cytokines (tumor necrosis factor-α [TNF-α] and interleukin-6 [IL-6]), and C-reactive protein were measured in plasma. The KYN/TRP ratio was utilized as a surrogate marker for indoleamine 2,3-dioxygenase 1 (IDO1) enzyme activity. Results: There was a significant inverse association between circulating TRP level and stages of CKD (P < 0.0001). Downstream bioactive TRP metabolites KYN, KYNA, and QA were positively and robustly correlated with the severity of kidney disease (P < 0.0001). In multiple linear regression, neither TNF-α nor IL-6 was independently related to KYN/TRP ratio after adjusting for estimated glomerular filtration rate (eGFR). Only TNF-α was independently related to KYN after taking into account the effect of eGFR. Conclusions: Chronic kidney disease secondary to T2D may be associated with accumulation of toxic TRP metabolites due to both inflammation and impaired kidney function. Future longitudinal studies to determine whether the accumulation of KYN directly contributes to CKD progression and associated symptoms in patients with T2D are warranted.
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Affiliation(s)
- Subrata Debnath
- Division of Nephrology, Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Chakradhar Velagapudi
- Division of Nephrology, Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Laney Redus
- Department of Pharmacology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Farook Thameem
- Division of Nephrology, Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Balakuntalam Kasinath
- Division of Nephrology, Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Claudia E Hura
- Division of Nephrology, Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Carlos Lorenzo
- Division of Rheumatology and Clinical Immunology, Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Hanna E Abboud
- Division of Nephrology, Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Jason C O'Connor
- Department of Pharmacology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.,South Texas Veterans Health Care System, San Antonio, TX, USA
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12
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Parsa A, Kanetsky PA, Xiao R, Gupta J, Mitra N, Limou S, Xie D, Xu H, Anderson AH, Ojo A, Kusek JW, Lora CM, Hamm LL, He J, Sandholm N, Jeff J, Raj DE, Böger CA, Bottinger E, Salimi S, Parekh RS, Adler SG, Langefeld CD, Bowden DW, Groop PH, Forsblom C, Freedman BI, Lipkowitz M, Fox CS, Winkler CA, Feldman HI. Genome-Wide Association of CKD Progression: The Chronic Renal Insufficiency Cohort Study. J Am Soc Nephrol 2017; 28:923-934. [PMID: 27729571 PMCID: PMC5328149 DOI: 10.1681/asn.2015101152] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2015] [Accepted: 08/25/2016] [Indexed: 11/03/2022] Open
Abstract
The rate of decline of renal function varies significantly among individuals with CKD. To understand better the contribution of genetics to CKD progression, we performed a genome-wide association study among participants in the Chronic Renal Insufficiency Cohort Study. Our outcome of interest was CKD progression measured as change in eGFR over time among 1331 blacks and 1476 whites with CKD. We stratified all analyses by race and subsequently, diabetes status. Single-nucleotide polymorphisms (SNPs) that surpassed a significance threshold of P<1×10-6 for association with eGFR slope were selected as candidates for follow-up and secondarily tested for association with proteinuria and time to ESRD. We identified 12 such SNPs among black patients and six such SNPs among white patients. We were able to conduct follow-up analyses of three candidate SNPs in similar (replication) cohorts and eight candidate SNPs in phenotype-related (validation) cohorts. Among blacks without diabetes, rs653747 in LINC00923 replicated in the African American Study of Kidney Disease and Hypertension cohort (discovery P=5.42×10-7; replication P=0.039; combined P=7.42×10-9). This SNP also associated with ESRD (hazard ratio, 2.0 (95% confidence interval, 1.5 to 2.7); P=4.90×10-6). Similarly, rs931891 in LINC00923 associated with eGFR decline (P=1.44×10-4) in white patients without diabetes. In summary, SNPs in LINC00923, an RNA gene expressed in the kidney, significantly associated with CKD progression in individuals with nondiabetic CKD. However, the lack of equivalent cohorts hampered replication for most discovery loci. Further replication of our findings in comparable study populations is warranted.
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Affiliation(s)
- Afshin Parsa
- Division of Nephrology and
- Department of Medicine, Baltimore Veterans Affairs Medical Center, Baltimore, Maryland
| | - Peter A Kanetsky
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida
| | - Rui Xiao
- Department of Biostatistics and Epidemiology and
| | - Jayanta Gupta
- Department of Health Sciences, College of Health Professions and Social Work, Florida Gulf Coast University, Fort Myers, FL
| | | | - Sophie Limou
- Molecular Genetic Epidemiology Section, Basic Research Laboratory, Center for Cancer Research, National Cancer Institute and Basic Science Program, Leidos Biomedical Research, Inc., Frederick National Laboratory, Frederick, Maryland
| | - Dawei Xie
- Department of Biostatistics and Epidemiology and
| | | | - Amanda Hyre Anderson
- Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Akinlolu Ojo
- Division of Nephrology, University of Michigan, Ann Arbor, Michigan
| | - John W Kusek
- Division of Kidney, Urologic and Hematologic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland
| | - Claudia M Lora
- Department of Medicine, Division of Nephrology, University of Illinois at Chicago, Chicago, Illinois
| | - L Lee Hamm
- Department of Medicine, Section of Nephrology, Tulane University, New Orleans, Louisiana
| | - Jiang He
- Department of Medicine, Section of Nephrology, Tulane University, New Orleans, Louisiana
| | - Niina Sandholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Abdominal Center Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland
| | - Janina Jeff
- Department of Medicine, The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine Mount Sinai, New York, New York
| | - Dominic E Raj
- Department of Medicine, The George Washington University School of Medicine, Washington, DC
| | - Carsten A Böger
- Department of Nephrology, University Hospital Regensburg, Regensburg, Germany
| | - Erwin Bottinger
- Department of Medicine, The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine Mount Sinai, New York, New York
| | - Shabnam Salimi
- Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland
| | - Rulan S Parekh
- Division of Nephrology, Department of Pediatrics and Medicine, Hospital for Sick Children, University Health Network and the University of Toronto, Toronto, Ontario, Canada
| | - Sharon G Adler
- Department of Medicine, Division of Nephrology and Hypertension, Harbor-University of California, Los Angeles Medical Center, Los Angeles, California
| | | | | | - Per-Henrik Groop
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Abdominal Center Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland
| | - Carol Forsblom
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Abdominal Center Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland
| | - Barry I Freedman
- Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Michael Lipkowitz
- Department of Medicine, Georgetown University Medical Center, Washington, DC; and
| | - Caroline S Fox
- Division of Intramural Research, National Heart, Lung and Blood Institute's Framingham Heart Study, National Heart, Lung and Blood Institute, Framingham, Massachusetts
| | | | - Harold I Feldman
- Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, Pennsylvania
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13
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Dieter BP, McPherson SM, Afkarian M, de Boer IH, Mehrotra R, Short R, Barbosa-Leiker C, Alicic RZ, Meek RL, Tuttle KR. Serum amyloid a and risk of death and end-stage renal disease in diabetic kidney disease. J Diabetes Complications 2016; 30:1467-1472. [PMID: 27522272 PMCID: PMC5435122 DOI: 10.1016/j.jdiacomp.2016.07.018] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2016] [Revised: 07/20/2016] [Accepted: 07/20/2016] [Indexed: 01/09/2023]
Abstract
AIMS To determine if serum levels of serum amyloid A (SAA) predict death and end-stage renal disease in a cohort of people with diabetic kidney disease. METHODS In a longitudinal cohort study of 135 participants with type 2 diabetes and diabetic kidney disease, serum samples were assayed for SAA. Censored time-to-event analyses in Cox-proportional hazard models were utilized to assess SAA as a predictor of the primary outcome of death and end-stage renal disease. RESULTS Participants were 73% Mexican-American (99/135) and 55% men (75/135), with a mean±SD age of 57±7.5years. At baseline, participants had hemoglobin A1c of 8.6±2.3%, systolic blood pressure of 153±27mm Hg, body mass index of 31±9kg/m2, median urine-albumin-to-creatinine ratio of 1861mg/g (interquartile range 720-3912mg/g), and estimated glomerular filtration rate of 55.7±22.3ml/min/1.73m2. Over a median duration of follow-up of 3.5years, 44% (60/135) of participants experienced a primary outcome event. The hazards ratio for the primary outcome was 3.03 (95% CI 1.43-6.40, p=0.003) in the highest (>1.0 μg/ml) compared to the lowest (<0.55 μg/ml) SAA tertile in a model adjusted for urine-albumin-to-creatinine ratio, estimated glomerular filtration rate, age, sex, and race/ethnicity. Addition of SAA as a covariate improved the model C-statistic (Δ c=0.017). CONCLUSIONS In a longitudinal cohort study of participants with type 2 diabetes and DKD, higher levels of serum SAA predicted higher risk of death and ESRD. SAA is a promising targetable biomarker for DKD.
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Affiliation(s)
- Brad P Dieter
- Providence Medical Research Center, Providence Health Care.
| | - Sterling M McPherson
- Providence Medical Research Center, Providence Health Care; Washington State University
| | - Maryam Afkarian
- University of Washington; Nephrology Division, Kidney Research Institute
| | - Ian H de Boer
- Washington State University Elson S. Floyd College of Medicine; University of Washington; Nephrology Division, Kidney Research Institute
| | | | - Robert Short
- Washington State University Elson S. Floyd College of Medicine
| | | | - Radica Z Alicic
- Providence Medical Research Center, Providence Health Care; University of Washington
| | - Rick L Meek
- Providence Medical Research Center, Providence Health Care
| | - Katherine R Tuttle
- Providence Medical Research Center, Providence Health Care; University of Washington; Nephrology Division, Kidney Research Institute
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14
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Blangero J, Teslovich TM, Sim X, Almeida MA, Jun G, Dyer TD, Johnson M, Peralta JM, Manning A, Wood AR, Fuchsberger C, Kent JW, Aguilar DA, Below JE, Farook VS, Arya R, Fowler S, Blackwell TW, Puppala S, Kumar S, Glahn DC, Moses EK, Curran JE, Thameem F, Jenkinson CP, DeFronzo RA, Lehman DM, Hanis C, Abecasis G, Boehnke M, Göring H, Duggirala R, Almasy L. Omics-squared: human genomic, transcriptomic and phenotypic data for genetic analysis workshop 19. BMC Proc 2016; 10:71-77. [PMID: 27980614 PMCID: PMC5133484 DOI: 10.1186/s12919-016-0008-y] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Background The Genetic Analysis Workshops (GAW) are a forum for development, testing, and comparison of statistical genetic methods and software. Each contribution to the workshop includes an application to a specified data set. Here we describe the data distributed for GAW19, which focused on analysis of human genomic and transcriptomic data. Methods GAW19 data were donated by the T2D-GENES Consortium and the San Antonio Family Heart Study and included whole genome and exome sequences for odd-numbered autosomes, measures of gene expression, systolic and diastolic blood pressures, and related covariates in two Mexican American samples. These two samples were a collection of 20 large families with whole genome sequence and transcriptomic data and a set of 1943 unrelated individuals with exome sequence. For each sample, simulated phenotypes were constructed based on the real sequence data. ‘Functional’ genes and variants for the simulations were chosen based on observed correlations between gene expression and blood pressure. The simulations focused primarily on additive genetic models but also included a genotype-by-medication interaction. A total of 245 genes were designated as ‘functional’ in the simulations with a few genes of large effect and most genes explaining < 1 % of the trait variation. An additional phenotype, Q1, was simulated to be correlated among related individuals, based on theoretical or empirical kinship matrices, but was not associated with any sequence variants. Two hundred replicates of the phenotypes were simulated. The GAW19 data are an expansion of the data used at GAW18, which included the family-based whole genome sequence, blood pressure, and simulated phenotypes, but not the gene expression data or the set of 1943 unrelated individuals with exome sequence.
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Affiliation(s)
- John Blangero
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - Tanya M Teslovich
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109 USA
| | - Xueling Sim
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109 USA
| | - Marcio A Almeida
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - Goo Jun
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109 USA ; Department of Epidemiology, Human Genetics and Environmenal Sciences, University of Texas Health Science Center at Houston, Houston, TX 77030 USA
| | - Thomas D Dyer
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - Matthew Johnson
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - Juan M Peralta
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - Alisa Manning
- Department of Genetics, Massachusetts General Hospital, Boston, MA 02114 USA
| | - Andrew R Wood
- Genetics of Complex Traits, Peninsula College of Medicine and Dentistry, University of Exeter, Exeter, UK
| | - Christian Fuchsberger
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109 USA
| | - Jack W Kent
- Department of Genetics, Texas Biomedical Research Institute, 7620 NW Loop 410, San Antonio, TX 78227 USA
| | - David A Aguilar
- Cardiovascular Division, Baylor College of Medicine, Houston, TX 77030 USA
| | - Jennifer E Below
- Department of Epidemiology, Human Genetics and Environmenal Sciences, University of Texas Health Science Center at Houston, Houston, TX 77030 USA
| | - Vidya S Farook
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - Rector Arya
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - Sharon Fowler
- Division of Clinical Epidemiology, Department of Medicine, University of San Antonio Health Science Center at San Antonio, San Antonio, TX 78229 USA
| | - Tom W Blackwell
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109 USA
| | - Sobha Puppala
- Department of Genetics, Texas Biomedical Research Institute, 7620 NW Loop 410, San Antonio, TX 78227 USA
| | - Satish Kumar
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - David C Glahn
- Department of Psychiatry, Yale University, New Haven, CT 06106 USA
| | - Eric K Moses
- Centre for Genetic Origins of Health and Disease, University of Western Australia, Crawley, Australia
| | - Joanne E Curran
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - Farook Thameem
- Department of Biochemistry, Faculty of Medicine, Kuwait University, Safat, Kuwait City, 13110 Kuwait
| | - Christopher P Jenkinson
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - Ralph A DeFronzo
- Texas Diabetes Institute, University of San Antonio Health Science Center at San Antonio, San Antonio, TX 78229 USA
| | - Donna M Lehman
- Division of Clinical Epidemiology, Department of Medicine, University of San Antonio Health Science Center at San Antonio, San Antonio, TX 78229 USA
| | - Craig Hanis
- Department of Epidemiology, Human Genetics and Environmenal Sciences, University of Texas Health Science Center at Houston, Houston, TX 77030 USA
| | - Goncalo Abecasis
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109 USA
| | - Michael Boehnke
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109 USA
| | - Harald Göring
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - Ravindranath Duggirala
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - Laura Almasy
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA ; Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104 USA
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15
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Tayo BO, Tong L, Cooper RS. Association of polymorphisms in the aldosterone-regulated sodium reabsorption pathway with blood pressure among Hispanics. BMC Proc 2016; 10:343-348. [PMID: 27980660 PMCID: PMC5133472 DOI: 10.1186/s12919-016-0054-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Whereas genome-wide association study (GWAS) has proven to be an important tool for discovery of variants influencing many human diseases and traits, unfortunately its performance has not been much of all-around success for some complex conditions, for example, hypertension. Because some of the existing effective pharmacotherapeutic agents act by targeting known biological pathways, pathway-based analytical approaches could lead to more success in discovery of disease-associated variants. The objective of the present study was to identify functional variants associated with blood pressure in the aldosterone-regulated sodium reabsorption pathway using the simulated and real blood pressure phenotypes provided for Genetic Analysis Workshop 19. METHODS The present analysis included 1942 samples with exome sequencing data and for whom blood pressure phenotypes were available. Because only odd-numbered autosomes were available, we restricted analysis to 127 quality-controlled single-nucleotide polymorphisms from the aldosterone-regulated sodium reabsorption pathway. We performed pathway-based association analysis using appropriate regression models for single variant, haplotype and epistasis association analyses. To account for multiple comparisons, statistical significance was empirically derived by permutation procedure and Bonferroni correction. RESULTS The topmost pathway-based association signals were observed in PRKCA gene for diastolic blood pressure (DBP), systolic blood pressure (SBP), and mean arterial pressure (MAP) in both real and simulated data. The associations remained significant (P <0.05) after multiple testing corrections for the number of genes. Similarly, the pathway-based 2-locus epistasis analysis indicated significant interactions between INSR and PRKCG for SBP and MAP; INS and PIK3R2 for DBP; PIK3CD and ATP1B2 for hypertension in the real data set. We also observed significant within-gene interactions in INSR for SBP, DBP, and hypertension in the simulated data set. CONCLUSION The findings from this study show that pathway-based analytical approach targeting known biological pathways can be useful in identification of disease-associated variants that are otherwise undetectable by GWAS. The approach takes advantage of the assumption of nonindependence of variants within and across pathway genes which leads to reduced penalty of multiple testing and thus less-stringent statistical significance threshold.
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Affiliation(s)
- Bamidele O. Tayo
- Department of Public Health Sciences, Stritch School of Medicine, Loyola University Chicago, Maywood, IL 60153 USA
| | - Liping Tong
- Department of Public Health Sciences, Stritch School of Medicine, Loyola University Chicago, Maywood, IL 60153 USA
| | - Richard S. Cooper
- Department of Public Health Sciences, Stritch School of Medicine, Loyola University Chicago, Maywood, IL 60153 USA
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16
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Sas KM, Kayampilly P, Byun J, Nair V, Hinder LM, Hur J, Zhang H, Lin C, Qi NR, Michailidis G, Groop PH, Nelson RG, Darshi M, Sharma K, Schelling JR, Sedor JR, Pop-Busui R, Weinberg JM, Soleimanpour SA, Abcouwer SF, Gardner TW, Burant CF, Feldman EL, Kretzler M, Brosius FC, Pennathur S. Tissue-specific metabolic reprogramming drives nutrient flux in diabetic complications. JCI Insight 2016; 1:e86976. [PMID: 27699244 PMCID: PMC5033761 DOI: 10.1172/jci.insight.86976] [Citation(s) in RCA: 173] [Impact Index Per Article: 21.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2016] [Accepted: 08/16/2016] [Indexed: 12/15/2022] Open
Abstract
Diabetes is associated with altered cellular metabolism, but how altered metabolism contributes to the development of diabetic complications is unknown. We used the BKS db/db diabetic mouse model to investigate changes in carbohydrate and lipid metabolism in kidney cortex, peripheral nerve, and retina. A systems approach using transcriptomics, metabolomics, and metabolic flux analysis identified tissue-specific differences, with increased glucose and fatty acid metabolism in the kidney, a moderate increase in the retina, and a decrease in the nerve. In the kidney, increased metabolism was associated with enhanced protein acetylation and mitochondrial dysfunction. To confirm these findings in human disease, we analyzed diabetic kidney transcriptomic data and urinary metabolites from a cohort of Southwestern American Indians. The urinary findings were replicated in 2 independent patient cohorts, the Finnish Diabetic Nephropathy and the Family Investigation of Nephropathy and Diabetes studies. Increased concentrations of TCA cycle metabolites in urine, but not in plasma, predicted progression of diabetic kidney disease, and there was an enrichment of pathways involved in glycolysis and fatty acid and amino acid metabolism. Our findings highlight tissue-specific changes in metabolism in complication-prone tissues in diabetes and suggest that urinary TCA cycle intermediates are potential prognostic biomarkers of diabetic kidney disease progression.
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Affiliation(s)
| | | | | | - Viji Nair
- Department of Internal Medicine
- Department of Computational Medicine and Bioinformatics
| | - Lucy M. Hinder
- Department of Neurology, University of Michigan, Ann Arbor, Michigan, USA
| | - Junguk Hur
- Department of Biomedical Sciences, University of North Dakota School of Medicine and Health Sciences, Grand Forks, North Dakota, USA
| | | | | | | | - George Michailidis
- Department of Statistics, University of Michigan, Ann Arbor, Michigan, USA
| | - Per-Henrik Groop
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Abdominal Center Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Baker IDI Heart and Diabetes Institute, Melbourne, Australia
| | - Robert G. Nelson
- Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona, USA
| | - Manjula Darshi
- Institute of Metabolomic Medicine and Center for Renal Translational Medicine, Department of Medicine, University of California San Diego, and Veterans Administration San Diego Healthcare System, La Jolla, California, USA
| | - Kumar Sharma
- Institute of Metabolomic Medicine and Center for Renal Translational Medicine, Department of Medicine, University of California San Diego, and Veterans Administration San Diego Healthcare System, La Jolla, California, USA
| | | | - John R. Sedor
- Department of Medicine
- Department of Physiology and Biophysics, Case Western Reserve University, Cleveland, Ohio, USA
| | | | | | | | | | | | - Charles F. Burant
- Department of Internal Medicine
- Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Eva L. Feldman
- Department of Neurology, University of Michigan, Ann Arbor, Michigan, USA
| | - Matthias Kretzler
- Department of Internal Medicine
- Department of Computational Medicine and Bioinformatics
| | - Frank C. Brosius
- Department of Internal Medicine
- Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, Michigan, USA
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17
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Williams RC, Elston RC, Kumar P, Knowler WC, Abboud HE, Adler S, Bowden DW, Divers J, Freedman BI, Igo RP, Ipp E, Iyengar SK, Kimmel PL, Klag MJ, Kohn O, Langefeld CD, Leehey DJ, Nelson RG, Nicholas SB, Pahl MV, Parekh RS, Rotter JI, Schelling JR, Sedor JR, Shah VO, Smith MW, Taylor KD, Thameem F, Thornley-Brown D, Winkler CA, Guo X, Zager P, Hanson RL. Selecting SNPs informative for African, American Indian and European Ancestry: application to the Family Investigation of Nephropathy and Diabetes (FIND). BMC Genomics 2016; 17:325. [PMID: 27142425 PMCID: PMC4855449 DOI: 10.1186/s12864-016-2654-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2015] [Accepted: 04/22/2016] [Indexed: 01/06/2023] Open
Abstract
Background The presence of population structure in a sample may confound the search for important genetic loci associated with disease. Our four samples in the Family Investigation of Nephropathy and Diabetes (FIND), European Americans, Mexican Americans, African Americans, and American Indians are part of a genome- wide association study in which population structure might be particularly important. We therefore decided to study in detail one component of this, individual genetic ancestry (IGA). From SNPs present on the Affymetrix 6.0 Human SNP array, we identified 3 sets of ancestry informative markers (AIMs), each maximized for the information in one the three contrasts among ancestral populations: Europeans (HAPMAP, CEU), Africans (HAPMAP, YRI and LWK), and Native Americans (full heritage Pima Indians). We estimate IGA and present an algorithm for their standard errors, compare IGA to principal components, emphasize the importance of balancing information in the ancestry informative markers (AIMs), and test the association of IGA with diabetic nephropathy in the combined sample. Results A fixed parental allele maximum likelihood algorithm was applied to the FIND to estimate IGA in four samples: 869 American Indians; 1385 African Americans; 1451 Mexican Americans; and 826 European Americans. When the information in the AIMs is unbalanced, the estimates are incorrect with large error. Individual genetic admixture is highly correlated with principle components for capturing population structure. It takes ~700 SNPs to reduce the average standard error of individual admixture below 0.01. When the samples are combined, the resulting population structure creates associations between IGA and diabetic nephropathy. Conclusions The identified set of AIMs, which include American Indian parental allele frequencies, may be particularly useful for estimating genetic admixture in populations from the Americas. Failure to balance information in maximum likelihood, poly-ancestry models creates biased estimates of individual admixture with large error. This also occurs when estimating IGA using the Bayesian clustering method as implemented in the program STRUCTURE. Odds ratios for the associations of IGA with disease are consistent with what is known about the incidence and prevalence of diabetic nephropathy in these populations. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2654-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Robert C Williams
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ, 85014, USA.
| | - Robert C Elston
- Genetic Analysis and Data Coordinating Center, Case Western Reserve University, Cleveland, OH, 44104, USA
| | - Pankaj Kumar
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ, 85014, USA
| | - William C Knowler
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ, 85014, USA
| | - Hanna E Abboud
- Division of Nephrology, The University of Texas Health Science Center, San Antonio, TX, 78229, USA
| | - Sharon Adler
- Department of Nephrology, Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Donald W Bowden
- Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA
| | - Jasmin Divers
- Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA
| | | | - Robert P Igo
- Genetic Analysis and Data Coordinating Center, Case Western Reserve University, Cleveland, OH, 44104, USA
| | - Eli Ipp
- Department of Nephrology, Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Sudha K Iyengar
- Genetic Analysis and Data Coordinating Center, Case Western Reserve University, Cleveland, OH, 44104, USA
| | - Paul L Kimmel
- National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, 20892, USA
| | - Michael J Klag
- Welch Center for Prevention, Epidemiology, and Clinical Research, Baltimore, MD, 21205, USA
| | - Orly Kohn
- The University of Chicago Medical Center, Chicago, IL, 60637, USA
| | | | - David J Leehey
- Loyola University Medical Center, Chicago, IL, 60153, USA
| | - Robert G Nelson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ, 85014, USA
| | - Susanne B Nicholas
- Divisions of Nephrology and Endocrinology, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - Madeleine V Pahl
- Division of Nephrology and Hypertension, Department of Medicine, UC Irvine School of Medicine, University of California, Orange, 92868, CA, USA
| | - Rulan S Parekh
- Hospital for Sick Children, University Health Network and the University of Toronto, Ontario, M5G1X8, Canada
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Jeffrey R Schelling
- Departments of Medicine and Physiology and Biophysics, Case Western Reserve University, Cleveland, OH, 44104, USA
| | - John R Sedor
- Departments of Medicine and Physiology and Biophysics, Case Western Reserve University, Cleveland, OH, 44104, USA
| | - Vallabh O Shah
- The University of New Mexico, Albuquerque, NM, 87131, USA
| | - Michael W Smith
- National Human Genome Research Institute, NIH, Bethesda, MD, 20892, USA
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Farook Thameem
- Division of Nephrology, The University of Texas Health Science Center, San Antonio, TX, 78229, USA.,Department of Biochemistry, Faculty of Medicine, Kuwait University, Kuwait City, Kuwait
| | | | - Cheryl A Winkler
- Center for Cancer Research, National Cancer Institute, NIH, Leidos Biomedical, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Phillip Zager
- The University of New Mexico, Albuquerque, NM, 87131, USA
| | - Robert L Hanson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ, 85014, USA
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18
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Shah AP, Shen JI, Wang Y, Tong L, Pak Y, Andalibi A, LaPage JA, Adler SG. Effects of Minocycline on Urine Albumin, Interleukin-6, and Osteoprotegerin in Patients with Diabetic Nephropathy: A Randomized Controlled Pilot Trial. PLoS One 2016; 11:e0152357. [PMID: 27019421 PMCID: PMC4809491 DOI: 10.1371/journal.pone.0152357] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2015] [Accepted: 03/11/2016] [Indexed: 01/19/2023] Open
Abstract
Background We tested minocycline as an anti-proteinuric adjunct to renin-angiotensin-aldosterone system inhibitors (RAASi) in diabetic nephropathy (DN) and measured urinary biomarkers to evaluate minocycline’s biological effects. Methods Design: Prospective, single center, randomized, placebo-controlled, intention-to-treat pilot trial. Inclusion. Type 2 diabetes/DN; Baseline creatinine clearance > 30 mL/min; proteinuria ≥ 1.0 g/day; Age ≥30 years; BP <150/95 mm Hg; intolerant of/at maximum RAASi dose. Protocol. 3-wk screening; Baseline randomization; Urine and blood measures at months 1, 2, 4, and Month 6 study completion. Urine interleukin-6 (IL-6) and osteoprotegerin were measured in a subset. Primary outcome. Natural log of urine protein/creatinine (ln U P:Cr) ratio at Month 6 vs Baseline. Results 30 patients completed the study. The 15% decline in U P: Cr in minocycline patients (6 month P:Cr ÷ Baseline P:Cr, 0.85 vs. 0.92) was not significant (p = 0.27). Creatinine clearance did not differ in the 2 groups. Urine IL-6:Cr (p = 0.03) and osteoprotegerin/Cr (p = 0.046) decrements were significant. Minocycline modified the relationship between urine IL-6 and proteinuria, suggesting a protective biological effect. Conclusions Although the decline in U P:Cr in minocycline patients was not statistically significant, the significant differences in urine IL-6 and osteoprotegerin suggest that minocycline may confer cytoprotection in patients with DN, providing a rationale for further study. Trial Registration Clinicaltrials.gov NCT01779089
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Affiliation(s)
- Anuja P. Shah
- Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, 1124 West Carson Street, Torrance, CA, 90509, United States of America
| | - Jenny I. Shen
- Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, 1124 West Carson Street, Torrance, CA, 90509, United States of America
| | - Ying Wang
- Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, 1124 West Carson Street, Torrance, CA, 90509, United States of America
| | - Lili Tong
- Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, 1124 West Carson Street, Torrance, CA, 90509, United States of America
| | - Youngju Pak
- Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, 1124 West Carson Street, Torrance, CA, 90509, United States of America
| | - Ali Andalibi
- Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, 1124 West Carson Street, Torrance, CA, 90509, United States of America
| | - Janine A. LaPage
- Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, 1124 West Carson Street, Torrance, CA, 90509, United States of America
| | - Sharon G. Adler
- Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, 1124 West Carson Street, Torrance, CA, 90509, United States of America
- * E-mail:
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19
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Schick UM, Jain D, Hodonsky CJ, Morrison JV, Davis JP, Brown L, Sofer T, Conomos MP, Schurmann C, McHugh CP, Nelson SC, Vadlamudi S, Stilp A, Plantinga A, Baier L, Bien SA, Gogarten SM, Laurie CA, Taylor KD, Liu Y, Auer PL, Franceschini N, Szpiro A, Rice K, Kerr KF, Rotter JI, Hanson RL, Papanicolaou G, Rich SS, Loos RJF, Browning BL, Browning SR, Weir BS, Laurie CC, Mohlke KL, North KE, Thornton TA, Reiner AP. Genome-wide Association Study of Platelet Count Identifies Ancestry-Specific Loci in Hispanic/Latino Americans. Am J Hum Genet 2016; 98:229-42. [PMID: 26805783 PMCID: PMC4746331 DOI: 10.1016/j.ajhg.2015.12.003] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2015] [Accepted: 12/07/2015] [Indexed: 12/23/2022] Open
Abstract
Platelets play an essential role in hemostasis and thrombosis. We performed a genome-wide association study of platelet count in 12,491 participants of the Hispanic Community Health Study/Study of Latinos by using a mixed-model method that accounts for admixture and family relationships. We discovered and replicated associations with five genes (ACTN1, ETV7, GABBR1-MOG, MEF2C, and ZBTB9-BAK1). Our strongest association was with Amerindian-specific variant rs117672662 (p value = 1.16 × 10(-28)) in ACTN1, a gene implicated in congenital macrothrombocytopenia. rs117672662 exhibited allelic differences in transcriptional activity and protein binding in hematopoietic cells. Our results underscore the value of diverse populations to extend insights into the allelic architecture of complex traits.
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Affiliation(s)
- Ursula M Schick
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98195, USA; Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Deepti Jain
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Chani J Hodonsky
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Jean V Morrison
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - James P Davis
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Lisa Brown
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Tamar Sofer
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Matthew P Conomos
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Claudia Schurmann
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Caitlin P McHugh
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Sarah C Nelson
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | | | - Adrienne Stilp
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Anna Plantinga
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Leslie Baier
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Disease, NIH, 445 North 5(th) Street, Phoenix, AZ 85004, USA
| | - Stephanie A Bien
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98195, USA
| | | | - Cecelia A Laurie
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA 90502, USA; Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Yongmei Liu
- School of Medicine, Wake Forest University, Winston-Salem, NC 27157, USA
| | - Paul L Auer
- Joseph J. Zilber School of Public Health, University of Wisconsin Milwaukee, Milwaukee, WI 53201, USA
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Adam Szpiro
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Ken Rice
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Kathleen F Kerr
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Robert L Hanson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Disease, NIH, 445 North 5(th) Street, Phoenix, AZ 85004, USA
| | - George Papanicolaou
- Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, NIH, Bethesda, MD 20892, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA; Division of Endocrinology, Department of Medicine, University of Virginia, Charlottesville, VA 22908, USA
| | - Ruth J F Loos
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Brian L Browning
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Sharon R Browning
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Bruce S Weir
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Cathy C Laurie
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Timothy A Thornton
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Alex P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98195, USA.
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20
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Traurig M, Hanson RL, Marinelarena A, Kobes S, Piaggi P, Cole S, Curran JE, Blangero J, Göring H, Kumar S, Nelson RG, Howard BV, Knowler WC, Baier LJ, Bogardus C. Analysis of SLC16A11 Variants in 12,811 American Indians: Genotype-Obesity Interaction for Type 2 Diabetes and an Association With RNASEK Expression. Diabetes 2016; 65:510-9. [PMID: 26487785 PMCID: PMC4747458 DOI: 10.2337/db15-0571] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2015] [Accepted: 10/11/2015] [Indexed: 01/31/2023]
Abstract
Genetic variants in SLC16A11 were recently reported to be associated with type 2 diabetes in Mexican and other Latin American populations. The diabetes risk haplotype had a frequency of 50% in Native Americans from Mexico but was rare in Europeans and Africans. In the current study, we analyzed SLC16A11 in 12,811 North American Indians and found that the diabetes risk haplotype, tagged by the rs75493593 A allele, was nominally associated with type 2 diabetes (P = 0.001, odds ratio 1.11). However, there was a strong interaction with BMI (P = 5.1 × 10(-7)) such that the diabetes association was stronger in leaner individuals. rs75493593 was also strongly associated with BMI in individuals with type 2 diabetes (P = 3.4 × 10(-15)) but not in individuals without diabetes (P = 0.77). Longitudinal analyses suggest that this is due, in part, to an association of the A allele with greater weight loss following diabetes onset (P = 0.02). Analyses of global gene expression data from adipose tissue, skeletal muscle, and whole blood provide evidence that rs75493593 is associated with expression of the nearby RNASEK gene, suggesting that RNASEK expression may mediate the effect of genotype on diabetes.
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Affiliation(s)
- Michael Traurig
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ
| | - Robert L Hanson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ
| | - Alejandra Marinelarena
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ
| | - Sayuko Kobes
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ
| | - Paolo Piaggi
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ
| | - Shelley Cole
- Texas Biomedical Research Institute, San Antonio, TX
| | - Joanne E Curran
- South Texas Diabetes and Obesity Institute, The University of Texas Rio Grande Valley School of Medicine, Brownsville, TX
| | - John Blangero
- South Texas Diabetes and Obesity Institute, The University of Texas Rio Grande Valley School of Medicine, Brownsville, TX
| | - Harald Göring
- South Texas Diabetes and Obesity Institute, The University of Texas Rio Grande Valley School of Medicine, Brownsville, TX
| | - Satish Kumar
- South Texas Diabetes and Obesity Institute, The University of Texas Rio Grande Valley School of Medicine, Brownsville, TX
| | - Robert G Nelson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ
| | - Barbara V Howard
- MedStar Health Research Institute, Hyattsville, MD Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC
| | - William C Knowler
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ
| | - Leslie J Baier
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ
| | - Clifton Bogardus
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ
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21
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Davoudi S, Sobrin L. Novel Genetic Actors of Diabetes-Associated Microvascular Complications: Retinopathy, Kidney Disease and Neuropathy. Rev Diabet Stud 2016; 12:243-59. [PMID: 26859656 DOI: 10.1900/rds.2015.12.243] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
Both type 1 and type 2 diabetes mellitus can lead to the common microvascular complications of diabetic retinopathy, kidney disease, and neuropathy. Diabetic patients do not universally develop these complications. Long duration of diabetes and poor glycemic control explain a lot of the variability in the development of microvascular complications, but not all. Genetic factors account for some of the remaining variability because of the heritability and familial clustering of these complications. There have been a large number of investigations, including linkage studies, candidate gene studies, and genome-wide association studies, all of which have sought to identify the specific variants that increase susceptibility. For retinopathy, several genome-wide association studies have been performed in small or midsize samples, but no reproducible loci across the studies have been identified. For diabetic kidney disease, genome-wide association studies in larger samples have been performed, and loci for this complication are beginning to emerge. However, validation of the existing discoveries, and further novel discoveries in larger samples is ongoing. The amount of genetic research into diabetic neuropathy has been very limited, and much is dedicated to the understanding of genetic risk factors only. Collaborations that pool samples and aim to detect phenotype classifications more precisely are promising avenues for a better explanation of the genetics of diabetic microvascular complications.
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Affiliation(s)
- Samaneh Davoudi
- Massachusetts Eye and Ear Infirmary, Harvard Medical School, 243 Charles Street, Boston, MA 02114, USA
| | - Lucia Sobrin
- Massachusetts Eye and Ear Infirmary, Harvard Medical School, 243 Charles Street, Boston, MA 02114, USA
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22
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Hawkins GA, Friedman DJ, Lu L, McWilliams DR, Chou JW, Sajuthi S, Divers J, Parekh R, Li M, Genovese G, Pollak MR, Hicks PJ, Bowden DW, Ma L, Freedman BI, Langefeld CD. Re-Sequencing of the APOL1-APOL4 and MYH9 Gene Regions in African Americans Does Not Identify Additional Risks for CKD Progression. Am J Nephrol 2015; 42:99-106. [PMID: 26343748 PMCID: PMC4589514 DOI: 10.1159/000439448] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2015] [Accepted: 08/11/2015] [Indexed: 12/31/2022]
Abstract
BACKGROUND In African Americans (AAs), APOL1 G1 and G2 nephropathy risk variants are associated with non-diabetic end-stage kidney disease (ESKD) in an autosomal recessive pattern. Additional risk and protective genetic variants may be present near the APOL1 loci, since earlier age ESKD is observed in some AAs with one APOL1 renal-risk variant, and because the adjacent gene MYH9 is associated with nephropathy in populations lacking G1 and G2 variants. METHODS Re-sequencing was performed across a ∼275 kb region encompassing the APOL1-APOL4 and MYH9 genes in 154 AA cases with non-diabetic ESKD and 38 controls without nephropathy who were heterozygous for a single APOL1 G1 or G2 risk variant. RESULTS Sequencing identified 3,246 non-coding single nucleotide polymorphisms (SNPs), 55 coding SNPs, and 246 insertion/deletions. No new coding variations were identified. Eleven variants, including a rare APOL3 Gln58Ter null variant (rs11089781), were genotyped in a replication panel of 1,571 AA ESKD cases and 1,334 controls. After adjusting for APOL1 G1 and G2 risk effects, these variations were not significantly associated with ESKD. In subjects with <2 APOL1 G1 and/or G2 alleles (849 cases; 1,139 controls), the APOL3 null variant was nominally associated with ESKD (recessive model, OR 1.81; p = 0.026); however, analysis in 807 AA cases and 634 controls from the Family Investigation of Nephropathy and Diabetes did not replicate this association. CONCLUSION Additional common variants in the APOL1-APOL4-MYH9 region do not contribute significantly to ESKD risk beyond the APOL1 G1 and G2 alleles.
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Affiliation(s)
- Gregory A. Hawkins
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC
| | - David J. Friedman
- Department of Internal Medicine, Division of Nephrology, Beth Israel Deaconess Medical Center, Boston MA
| | - Lingyi Lu
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - David R. McWilliams
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Jeff W. Chou
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Satria Sajuthi
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Jasmin Divers
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Rulan Parekh
- Nephrology, Hospital for Sick Children, Toronto, CA
| | - Man Li
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | | | - Martin R. Pollak
- Department of Internal Medicine, Division of Nephrology, Beth Israel Deaconess Medical Center, Boston MA
| | - Pamela J. Hicks
- Department of Biochemistry and Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC
| | - Donald W. Bowden
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC
- Department of Biochemistry and Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC
| | - Lijun Ma
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC
- Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC
| | - Barry I. Freedman
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC
- Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC
| | - Carl D. Langefeld
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC
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23
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Iyengar SK, Sedor JR, Freedman BI, Kao WHL, Kretzler M, Keller BJ, Abboud HE, Adler SG, Best LG, Bowden DW, Burlock A, Chen YDI, Cole SA, Comeau ME, Curtis JM, Divers J, Drechsler C, Duggirala R, Elston RC, Guo X, Huang H, Hoffmann MM, Howard BV, Ipp E, Kimmel PL, Klag MJ, Knowler WC, Kohn OF, Leak TS, Leehey DJ, Li M, Malhotra A, März W, Nair V, Nelson RG, Nicholas SB, O’Brien SJ, Pahl MV, Parekh RS, Pezzolesi MG, Rasooly RS, Rotimi CN, Rotter JI, Schelling JR, Seldin MF, Shah VO, Smiles AM, Smith MW, Taylor KD, Thameem F, Thornley-Brown DP, Truitt BJ, Wanner C, Weil EJ, Winkler CA, Zager PG, Igo RP, Hanson RL, Langefeld CD. Genome-Wide Association and Trans-ethnic Meta-Analysis for Advanced Diabetic Kidney Disease: Family Investigation of Nephropathy and Diabetes (FIND). PLoS Genet 2015; 11:e1005352. [PMID: 26305897 PMCID: PMC4549309 DOI: 10.1371/journal.pgen.1005352] [Citation(s) in RCA: 96] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2014] [Accepted: 06/10/2015] [Indexed: 11/28/2022] Open
Abstract
Diabetic kidney disease (DKD) is the most common etiology of chronic kidney disease (CKD) in the industrialized world and accounts for much of the excess mortality in patients with diabetes mellitus. Approximately 45% of U.S. patients with incident end-stage kidney disease (ESKD) have DKD. Independent of glycemic control, DKD aggregates in families and has higher incidence rates in African, Mexican, and American Indian ancestral groups relative to European populations. The Family Investigation of Nephropathy and Diabetes (FIND) performed a genome-wide association study (GWAS) contrasting 6,197 unrelated individuals with advanced DKD with healthy and diabetic individuals lacking nephropathy of European American, African American, Mexican American, or American Indian ancestry. A large-scale replication and trans-ethnic meta-analysis included 7,539 additional European American, African American and American Indian DKD cases and non-nephropathy controls. Within ethnic group meta-analysis of discovery GWAS and replication set results identified genome-wide significant evidence for association between DKD and rs12523822 on chromosome 6q25.2 in American Indians (P = 5.74x10-9). The strongest signal of association in the trans-ethnic meta-analysis was with a SNP in strong linkage disequilibrium with rs12523822 (rs955333; P = 1.31x10-8), with directionally consistent results across ethnic groups. These 6q25.2 SNPs are located between the SCAF8 and CNKSR3 genes, a region with DKD relevant changes in gene expression and an eQTL with IPCEF1, a gene co-translated with CNKSR3. Several other SNPs demonstrated suggestive evidence of association with DKD, within and across populations. These data identify a novel DKD susceptibility locus with consistent directions of effect across diverse ancestral groups and provide insight into the genetic architecture of DKD. Type 2 diabetes is the most common cause of severe kidney disease worldwide and diabetic kidney disease (DKD) associates with premature death. Individuals of non-European ancestry have the highest burden of type 2 DKD; hence understanding the causes of DKD remains critical to reducing health disparities. Family studies demonstrate that genes regulate the onset and progression of DKD; however, identifying these genes has proven to be challenging. The Family Investigation of Diabetes and Nephropathy consortium (FIND) recruited a large multi-ethnic collection of individuals with type 2 diabetes with and without kidney disease in order to detect genes associated with DKD. FIND discovered and replicated a DKD-associated genetic locus on human chromosome 6q25.2 (rs955333) between the SCAF8 and CNKSR genes. Findings were supported by significantly different expression of genes in this region from kidney tissue of subjects with, versus without DKD. The present findings identify a novel kidney disease susceptibility locus in individuals with type 2 diabetes which is consistent across subjects of differing ancestries. In addition, FIND results provide a rich catalogue of genetic variation in DKD patients for future research on the genetic architecture regulating this common and devastating disease.
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Affiliation(s)
- Sudha K. Iyengar
- Department of Epidemiology & Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
- * E-mail: (SKI); (JRS); (BIF)
| | - John R. Sedor
- Departments of Medicine, Case Western Reserve University, Cleveland, Ohio, United States of America
- Departments of Physiology and Biophysics, Case Western Reserve University, Cleveland, Ohio, United States of America
- * E-mail: (SKI); (JRS); (BIF)
| | - Barry I. Freedman
- Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- * E-mail: (SKI); (JRS); (BIF)
| | - W. H. Linda Kao
- Department of Epidemiology and Medicine, John Hopkins University, Baltimore, Maryland, United States of America
| | - Matthias Kretzler
- Department of Internal Medicine/Nephrology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Benjamin J. Keller
- Department of Internal Medicine/Nephrology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Hanna E. Abboud
- Department of Medicine/Nephrology, The University of Texas Health Science Center, San Antonio, Texas, United States of America
| | - Sharon G. Adler
- Department of Medicine, Division of Nephrology and Hypertension, Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Lyle G. Best
- Missouri Breaks Industries Research, Timber Lake, South Dakota, United States of America
| | - Donald W. Bowden
- Department of Biochemistry, Center for Human Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Allison Burlock
- Department of Internal Medicine/Nephrology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Shelley A. Cole
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Mary E. Comeau
- Center for Public Health Genomics and Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, United States of America
| | - Jeffrey M. Curtis
- National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona, United States of America
| | - Jasmin Divers
- Center for Public Health Genomics and Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, United States of America
| | - Christiane Drechsler
- University Hospital Würzburg, Renal Division and Comprehensive Heart Failure Center, Würzburg, Germany
| | - Ravi Duggirala
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Robert C. Elston
- Department of Epidemiology & Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Huateng Huang
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, United States of America
| | | | - Barbara V. Howard
- MedStar Health Research Institute, Hyattsville, Maryland, United States of America
| | - Eli Ipp
- Department of Medicine, Section of Diabetes and Metabolism, Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Paul L. Kimmel
- Division of Kidney, Urologic, and Hematologic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland, United States of America
| | - Michael J. Klag
- Johns Hopkins Bloomberg School of Public Health, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - William C. Knowler
- National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona, United States of America
| | - Orly F. Kohn
- Department of Medicine, University of Chicago Medicine, Chicago, Illinois, United States of America
| | - Tennille S. Leak
- Department of Internal Medicine/Nephrology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - David J. Leehey
- Department of Medicine, Loyola School of Medicine, Maywood, Illinois, United States of America
| | - Man Li
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Alka Malhotra
- National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona, United States of America
| | - Winfried März
- Heidelberg University and Synlab Academy, University of Graz, Graz, Austria
| | - Viji Nair
- Department of Internal Medicine/Nephrology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Robert G. Nelson
- National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona, United States of America
| | - Susanne B. Nicholas
- Department of Medicine, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Stephen J. O’Brien
- Theodosius Dobzhansky Center for Genome Bioinformatics, St. Petersburg, Russia, and Oceanographic Center, Nova Southeastern University, Ft. Lauderdale, Florida, United States of America
| | - Madeleine V. Pahl
- Department of Medicine, University of California, Irvine, Irvine, California, United States of America
| | - Rulan S. Parekh
- Departments of Paediatrics and Medicine, Hospital for Sick Children, University Health Network and the University of Toronto, Toronto, Ontario, Canada
| | - Marcus G. Pezzolesi
- Department of Medicine, Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Rebekah S. Rasooly
- National Institute of Diabetes and Digestive Disease, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Charles N. Rotimi
- Center for Research on Genomics and Global Health, Bethesda, Maryland, United States of America
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Jeffrey R. Schelling
- Departments of Medicine, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Michael F. Seldin
- Department of Biochemistry and Molecular Medicine, UC Davis School of Medicine, Davis, California, United States of America
| | - Vallabh O. Shah
- Department of Biochemistry & Molecular Biology, University of New Mexico, Albuquerque, New Mexico, United States of America
| | - Adam M. Smiles
- Joslin Diabetes Center, Section on Genetics and Epidemiology, Boston, Massachusetts, United States of America
| | - Michael W. Smith
- National Human Genome Research Institute, Rockville, Maryland, United States of America
| | - Kent D. Taylor
- The Institute for Translational Genomics and Population Sciences, Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Farook Thameem
- Department of Medicine, The University of Texas Health Science Center, San Antonio, Texas, United States of America
| | | | - Barbara J. Truitt
- Department of Epidemiology & Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Christoph Wanner
- Department of Medicine, Division of Nephrology, University Hospital Würzburg, Würzburg, Germany
| | - E. Jennifer Weil
- National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona, United States of America
| | - Cheryl A. Winkler
- Center for Cancer Research, National Cancer Institute, Frederick, Maryland, United States of America
| | - Philip G. Zager
- Department of Internal Medicine, University of New Mexico, Albuquerque, New Mexico, United States of America
| | - Robert P. Igo
- Department of Epidemiology & Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Robert L. Hanson
- National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona, United States of America
| | - Carl D. Langefeld
- The Institute for Translational Genomics and Population Sciences, Harbor-UCLA Medical Center, Torrance, California, United States of America
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Alkayyali S, Lyssenko V. Genetics of diabetes complications. Mamm Genome 2014; 25:384-400. [PMID: 25169573 DOI: 10.1007/s00335-014-9543-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2014] [Accepted: 08/13/2014] [Indexed: 12/11/2022]
Abstract
Chronic hyperglycemia and duration of diabetes are the major risk factors associated with development of micro- and macrovascular complications of diabetes. Although it is believed that hyperglycemia induces damage to the particular cell subtypes, e.g., mesangial cells in the renal glomerulus, capillary endothelial cells in the retina, and neurons and Schwann cells in peripheral nerves, the exact mechanisms underlying these damaging defects are not yet well understood. Clustering of micro- and macrovascular complications in families of patients with diabetes suggests a strong genetic susceptibility. However, until now only a handful number of genetic variants were reported to be associated with either nephropathy (ACE, ELMO1, FRMD3, and AKR1B1) or retinopathy (VEGF, AKR1B1, and EPO), and only a few studies were carried out for genetic susceptibility to cardiovascular diseases (ADIPOQ, GLUL) in patients with diabetes. It is, therefore, obvious that the accumulation of more data from larger studies and better phenotypically characterized cohorts is needed to facilitate genetic discoveries and unravel novel insights into the pathogenesis of diabetic complications.
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Affiliation(s)
- Sami Alkayyali
- Department of Clinical Sciences, Diabetes and Endocrinology, CRC, Lund University, Lund, Sweden,
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25
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Thameem F, Igo RP, Freedman BI, Langefeld C, Hanson RL, Schelling JR, Elston RC, Duggirala R, Nicholas SB, Goddard KAB, Divers J, Guo X, Ipp E, Kimmel PL, Meoni LA, Shah VO, Smith MW, Winkler CA, Zager PG, Knowler WC, Nelson RG, Pahl MV, Parekh RS, Kao WHL, Rasooly RS, Adler SG, Abboud HE, Iyengar SK, Sedor JR. A genome-wide search for linkage of estimated glomerular filtration rate (eGFR) in the Family Investigation of Nephropathy and Diabetes (FIND). PLoS One 2013; 8:e81888. [PMID: 24358131 PMCID: PMC3866106 DOI: 10.1371/journal.pone.0081888] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2013] [Accepted: 10/27/2013] [Indexed: 12/22/2022] Open
Abstract
Objective Estimated glomerular filtration rate (eGFR), a measure of kidney function, is heritable, suggesting that genes influence renal function. Genes that influence eGFR have been identified through genome-wide association studies. However, family-based linkage approaches may identify loci that explain a larger proportion of the heritability. This study used genome-wide linkage and association scans to identify quantitative trait loci (QTL) that influence eGFR. Methods Genome-wide linkage and sparse association scans of eGFR were performed in families ascertained by probands with advanced diabetic nephropathy (DN) from the multi-ethnic Family Investigation of Nephropathy and Diabetes (FIND) study. This study included 954 African Americans (AA), 781 American Indians (AI), 614 European Americans (EA) and 1,611 Mexican Americans (MA). A total of 3,960 FIND participants were genotyped for 6,000 single nucleotide polymorphisms (SNPs) using the Illumina Linkage IVb panel. GFR was estimated by the Modification of Diet in Renal Disease (MDRD) formula. Results The non-parametric linkage analysis, accounting for the effects of diabetes duration and BMI, identified the strongest evidence for linkage of eGFR on chromosome 20q11 (log of the odds [LOD] = 3.34; P = 4.4×10−5) in MA and chromosome 15q12 (LOD = 2.84; P = 1.5×10−4) in EA. In all subjects, the strongest linkage signal for eGFR was detected on chromosome 10p12 (P = 5.5×10−4) at 44 cM near marker rs1339048. A subsequent association scan in both ancestry-specific groups and the entire population identified several SNPs significantly associated with eGFR across the genome. Conclusion The present study describes the localization of QTL influencing eGFR on 20q11 in MA, 15q21 in EA and 10p12 in the combined ethnic groups participating in the FIND study. Identification of causal genes/variants influencing eGFR, within these linkage and association loci, will open new avenues for functional analyses and development of novel diagnostic markers for DN.
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Affiliation(s)
- Farook Thameem
- Department of Medicine, The University of Texas Health Science Center, San Antonio, Texas, United States of America
| | - Robert P. Igo
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Barry I. Freedman
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Carl Langefeld
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Robert L. Hanson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona, United States of America
| | - Jeffrey R. Schelling
- Department of Medicine, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Robert C. Elston
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Ravindranath Duggirala
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Susanne B. Nicholas
- Department of Medicine, University of California, Los Angeles, California, United States of America
| | - Katrina A. B. Goddard
- Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon, United States of America
| | - Jasmin Divers
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Xiuqing Guo
- Department of Pediatrics, Harbor-University of California Los Angeles Medical Center, Torrance, California, United States of America
| | - Eli Ipp
- Department of Medicine, Harbor-University of California Los Angeles Medical Center, Torrance, California, United States of America
| | - Paul L. Kimmel
- National Institute of Diabetes, Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Lucy A. Meoni
- Department of Epidemiology and Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Vallabh O. Shah
- University of New Mexico, Albuquerque, New Mexico, United States of America
| | - Michael W. Smith
- National Human Genome Research Institute, NIH, Bethesda, Maryland, United States of America
| | - Cheryl A. Winkler
- Center for Cancer Research, National Cancer Institute, NIH, Frederick, Maryland, United States of America
| | - Philip G. Zager
- University of New Mexico, Albuquerque, New Mexico, United States of America
| | - William C. Knowler
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona, United States of America
| | - Robert G. Nelson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona, United States of America
| | - Madeline V. Pahl
- Department of Medicine, University of California, Irvine, California, United States of America
| | - Rulan S. Parekh
- Department of Epidemiology and Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America
- Department of Pediatrics, University of Toronto, Toronto, Canada
| | - W. H. Linda Kao
- Department of Epidemiology and Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Rebekah S. Rasooly
- National Institute of Diabetes, Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Sharon G. Adler
- Department of Medicine, Harbor-University of California Los Angeles Medical Center, Torrance, California, United States of America
| | - Hanna E. Abboud
- Department of Medicine, The University of Texas Health Science Center, San Antonio, Texas, United States of America
| | - Sudha K. Iyengar
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
- * E-mail:
| | - John R. Sedor
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
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Estus JL, Fardo DW. Combining genetic association study designs: a GWAS case study. Front Genet 2013; 4:186. [PMID: 24098305 PMCID: PMC3784826 DOI: 10.3389/fgene.2013.00186] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2013] [Accepted: 09/03/2013] [Indexed: 01/06/2023] Open
Abstract
Genome-wide association studies (GWAS) explore the relationship between genome variability and disease susceptibility with either population- or family-based data. Here, we have evaluated the utility of combining population- and family-based statistical association tests and have proposed a method for reducing the burden of multiple testing. Unrelated singleton and parent-offspring trio cases and controls from the Genetics of Kidneys in Diabetes (GoKinD) study were analyzed for genetic association with diabetic nephropathy (DN) in type 1 diabetics (T1D). The Cochran-Armitage test for trend and the family-based association test were employed using either unrelated cases and controls or trios, respectively. In addition to combining single nucleotide polymorphism (SNP) p-values across these tests via Fisher's method, we employed a novel screening approach to rank SNPs based on conditional power for more efficient testing. Using either the population-based or family-based subset alone predictably limited resolution to detect DN SNPs. For 384,197 SNPs passing quality control (QC), none achieved strict genome-wide significance (1.4 × 10−7) using 1171 singletons (577/594 cases/controls) or 1738 pooled singletons and offspring probands (841/897). Similarly, none of the 352,004 SNPs passing QC in 567 family trios (264/303 case/control proband trios) reached genome-wide significance. Testing the top 10 SNPs ranked using aggregated conditional power resulted in two SNPs reaching genome-wide significance, rs11645147 on chromosome 16 (p = 1.74 × 10−4 < 0.05/10 = 0.005) and rs7866522 on chromosome 9 (p = 0.0033). Efficient usage of mixed designs incorporating both unrelated and family-based data may help to uncover associations otherwise difficult to detect in the presence of massive multiple testing corrections. Capitalizing on the strengths of both types while using screening approaches may be useful especially in light of large-scale, next-generation sequencing and rare variant studies.
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Affiliation(s)
- Janice L Estus
- Department of Biostatistics, University of Kentucky Lexington, KY, USA
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27
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Susceptibility gene search for nephropathy and related traits in Mexican-Americans. Mol Biol Rep 2013; 40:5769-79. [PMID: 24057238 DOI: 10.1007/s11033-013-2680-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2013] [Accepted: 09/14/2013] [Indexed: 02/06/2023]
Abstract
The rising global epidemic of diabetic nephropathy (DN) will likely lead to increase in the prevalence of cardiovascular morbidity and mortality posing a serious burden for public health care. Despite greater understanding of the etiology of diabetes and the development of novel treatment strategies to control blood glucose levels, the prevalence and incidence rate of DN is increasing especially in minority populations including Mexican-Americans. Mexican-Americans with type 2 diabetes (T2DM) are three times more likely to develop microalbuminuria, and four times more likely to develop clinical proteinuria compared to non-Hispanic whites. Furthermore, Mexican-Americans have a sixfold increased risk of developing renal failure secondary to T2DM compared to Caucasians. Prevention and better treatment of DN should be a high priority for both health-care organizations and society at large. Pathogenesis of DN is multi-factorial. Familial clustering of DN-related traits in MAs show that DN and related traits are heritable and that genes play a susceptibility role. While, there has been some progress in identifying genes which when mutated influence an individual's risk, major gene(s) responsible for DN are yet to be identified. Knowledge of the genetic causes of DN is essential for elucidation of its mechanisms, and for adequate classification, prognosis, and treatment. Self-identification and collaboration among researchers with suitable genomic and clinical data for meta-analyses in Mexican-Americans is critical for progress in replicating/identifying DN risk genes in this population. This paper reviews the approaches and recent efforts made to identify genetic variants contributing to risk for DN and related phenotypes in the Mexican-American population.
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Sandholm N, McKnight AJ, Salem RM, Brennan EP, Forsblom C, Harjutsalo V, Mäkinen VP, McKay GJ, Sadlier DM, Williams WW, Martin F, Panduru NM, Tarnow L, Tuomilehto J, Tryggvason K, Zerbini G, Comeau ME, Langefeld CD, Godson C, Hirschhorn JN, Maxwell AP, Florez JC, Groop PH. Chromosome 2q31.1 associates with ESRD in women with type 1 diabetes. J Am Soc Nephrol 2013; 24:1537-43. [PMID: 24029427 DOI: 10.1681/asn.2012111122] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
Abstract
Sex and genetic variation influence the risk of developing diabetic nephropathy and ESRD in patients with type 1 diabetes. We performed a genome-wide association study in a cohort of 3652 patients from the Finnish Diabetic Nephropathy (FinnDiane) Study with type 1 diabetes to determine whether sex-specific genetic risk factors for ESRD exist. A common variant, rs4972593 on chromosome 2q31.1, was associated with ESRD in women (P<5×10(-8)) but not in men (P=0.77). This association was replicated in the meta-analysis of three independent type 1 diabetes cohorts (P=0.02) and remained significant for women (P<5×10(-8); odds ratio, 1.81 [95% confidence interval, 1.47 to 2.24]) upon combined meta-analysis of the discovery and replication cohorts. rs4972593 is located between the genes that code for the Sp3 transcription factor, which interacts directly with estrogen receptor α and regulates the expression of genes linked to glomerular function and the pathogenesis of nephropathy, and the CDCA7 transcription factor, which regulates cell proliferation. Further examination revealed potential transcription factor-binding sites within rs4972593 and predicted eight estrogen-responsive elements within 5 kb of this locus. Moreover, we found sex-specific differences in the glomerular expression levels of SP3 (P=0.004). Overall, these results suggest that rs4972593 is a sex-specific genetic variant associated with ESRD in patients with type 1 diabetes and may underlie the sex-specific protection against ESRD.
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Affiliation(s)
- Niina Sandholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
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Gangaputra S, Lovato JF, Hubbard L, Davis MD, Esser BA, Ambrosius WT, Chew EY, Greven C, Perdue LH, Wong WT, Condren A, Wilkinson CP, Agrón E, Adler S, Danis RP. Comparison of standardized clinical classification with fundus photograph grading for the assessment of diabetic retinopathy and diabetic macular edema severity. Retina 2013; 33:1393-9. [PMID: 23615341 PMCID: PMC3706017 DOI: 10.1097/iae.0b013e318286c952] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
PURPOSE To compare evaluation by clinical examination with image grading at a reading center for the classification of diabetic retinopathy and diabetic macular edema. METHODS Action to Control Cardiovascular Risk in Diabetes (ACCORD) and Family Investigations of Nephropathy in Diabetes (FIND) had similar methods of clinical and fundus photograph evaluation. For analysis purposes, the photographic grading scales were condensed to correspond to the clinical scales, and agreement between clinicians and reading center classification were compared. RESULTS Six thousand nine hundred and two eyes of ACCORD participants and 3,638 eyes of FIND participants were analyzed for agreement (percent, kappa) on diabetic retinopathy on a 5-level scale. Exact agreement between clinicians and reading center on diabetic retinopathy severity category was 69% in ACCORD and 74% in FIND (kappa 0.42 and 0.65). Sensitivities of the clinical grading to identify the presence of mild nonproliferative retinopathy or worse were 0.53 in ACCORD and 0.84 in FIND. Specificities were 0.97 and 0.96, respectively. Diabetic macular edema agreement in 6,649 eyes of ACCORD participants and 3,366 eyes of FIND participants was similar (kappa 0.35 and 0.41). Sensitivities of the clinical grading to identify diabetic macular edema were 0.44 and 0.53 and specificities were 0.99 and 0.94, respectively. CONCLUSION The results support the use of clinical information for defining broad severity categories but not for documenting small-to-moderate changes in diabetic retinopathy over time.
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Affiliation(s)
- Sapna Gangaputra
- Fundus Photograph Reading Center, Department of Ophthalmology and Visual Sciences, University of Wisconsin-Madison, WI 53717, USA
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Change in ankle-brachial index over time and mortality in diabetics with proteinuria. Clin Nephrol 2012; 78:335-45. [PMID: 22784559 PMCID: PMC4407335 DOI: 10.5414/cn107463] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/18/2012] [Indexed: 11/18/2022] Open
Abstract
Peripheral arterial disease is common in diabetic chronic kidney disease (CKD) and is characterized either by abnormally low or high ankle-brachial index (ABI). Whether low or high ABI carries similar prognostic value is unknown. The association of baseline ABI with all-cause mortality over 40 ± 21 months (mean ± SD) was ascertained in 167 proteinuric diabetics (age 57 ± 7 years; median urine protein-creatinine, 2.5 mg/mg). Association of change in ABI with all-cause mortality was determined in 75 subjects with normal ABI (0.9 - 1.3) at baseline. Among 167 participants, 41% had an abnormal ABI: < 0.9, 18%; and > 1.3 or non-compressible arteries, 23%. Only individuals with low ABI had a significantly higher risk for all-cause mortality (hazards ratio (95% confidence interval), HR: 2.23 (1.07, 4.65)). In subjects with normal ABI at baseline with follow-up measurement (n = 75), vascular disease worsened in 39% over 23 ± 6 months: 17% had either a decrease in ABI by ≥ 0.1 or a final ABI < 0.9, and 21% had a final ABI > 1.3 or noncompressible arteries. Only individuals who had a decrease in ABI over time had a significantly higher risk for death (adjusted HR, 7.41 (1.63, 33.65)). Peripheral arterial disease is not uncommon and progresses rapidly in individuals with diabetes and proteinuria. Low or declining ABI is a strong predictor of all-cause mortality. Routine measurement of ABI is a simple bed-side procedure that may permit easy risk-stratification in diabetic CKD patients.
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Abstract
Diabetic nephropathy (DN) is a devastating complication of type 1 and type 2 diabetes and leads to increased morbidity and premature mortality. Susceptibility to DN has an inherent genetic basis as evidenced by familial aggregation and ethnic-specific prevalence rates. Progress in identifying the underlying genetic architecture has been arduous with the realization that a single locus of large effect does not exist, unlike in predisposition to non-diabetic nephropathy in individuals with African ancestry. Numerous risk variants have been identified, each with a nominal effect, and they collectively contribute to disease. These results have identified loci targeting novel pathways for disease susceptibility. With continued technological advances and development of new analytic methods, additional genetic variants and mechanisms (e.g., epigenetic variation) will be identified and help to elucidate the pathogenesis of DN. These advances will lead to early detection and development of novel therapeutic strategies to decrease the incidence of disease.
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Affiliation(s)
- Nicholette D. Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston Salem, NC USA
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston Salem, NC USA
| | - Barry I. Freedman
- Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston Salem, NC USA
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Komorowsky CV, Brosius FC, Pennathur S, Kretzler M. Perspectives on systems biology applications in diabetic kidney disease. J Cardiovasc Transl Res 2012; 5:491-508. [PMID: 22733404 PMCID: PMC3422674 DOI: 10.1007/s12265-012-9382-7] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2012] [Accepted: 05/22/2012] [Indexed: 12/18/2022]
Abstract
Diabetic kidney disease (DKD) is a microvascular complication of type 1 and 2 diabetes with a devastating impact on individuals with the disease, their families, and society as a whole. DKD is the single most frequent cause of incident chronic kidney disease cases and accounts for over 40% of the population with end-stage renal disease. Contributing factors for the high prevalence are the increase in obesity and subsequent diabetes combined with an improved long-term survival with diabetes. Environment and genetic variations contribute to DKD susceptibility and progressive loss of kidney function. How the molecular mechanisms of genetic and environmental exposures interact during DKD initiation and progression is the focus of ongoing research efforts. The development of standardized, unbiased high-throughput profiling technologies of human DKD samples opens new avenues in capturing the multiple layers of DKD pathobiology. These techniques routinely interrogate analytes on a genome-wide scale generating comprehensive DKD-associated fingerprints. Linking the molecular fingerprints to deep clinical phenotypes may ultimately elucidate the intricate molecular interplay in a disease stage and subtype-specific manner. This insight will form the basis for accurate prognosis and facilitate targeted therapeutic interventions. In this review, we present ongoing efforts from large-scale data integration translating "-omics" research efforts into improved and individualized health care in DKD.
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Affiliation(s)
- Claudiu V. Komorowsky
- Department of Internal Medicine, Division of Nephrology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Frank C. Brosius
- Department of Internal Medicine, Division of Nephrology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Subramaniam Pennathur
- Department of Internal Medicine, Division of Nephrology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Matthias Kretzler
- Department of Internal Medicine, Division of Nephrology, University of Michigan Medical School, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
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Abstract
The incidence of diabetic nephropathy (DN) is growing rapidly worldwide as a consequence of the rising prevalence of Type 2 diabetes mellitus (T2DM). Among U.S. ethnic groups, Mexican Americans have a disproportionately high incidence and prevalence of DN and associated end-stage renal disease (ESRD). In communities bordering Mexico, as many as 90% of Mexican American patients with ESRD also suffer from T2DM compared to only 50% of non-Hispanic Whites (NHW). Both socio-economic factors and genetic predisposition appear to have a strong influence on this association. In addition, certain pathogenetic and clinical features of T2DM and DN are different in Mexican Americans compared to NHW, raising questions as to whether the diagnostic and treatment strategies that are standard practice in the NHW patient population may not be applicable in Mexican Americans. This article reviews the epidemiology of DN in Mexican Americans, describes the pathophysiology and associated risk factors, and identifies gaps in our knowledge and understanding that needs to be addressed by future investigations.
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Hsieh CH, Pei D, Hung YJ, Hsiao FC. Association between retinoid-X receptor-gamma genetic polymorphisms and diabetic retinopathy. GENETICS AND MOLECULAR RESEARCH 2011; 10:3545-51. [PMID: 22180072 DOI: 10.4238/2011.december.5.4] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Retinoid-X receptor (RXR) is one of the members of the nuclear hormone receptor superfamily. It forms heterodimers with many nuclear receptors, such as the peroxisome proliferative-activated receptor, which has been proposed to be involved in diabetic complications, including retinopathy. A recent study revealed that RXR-alpha has antioxidant properties and is associated with diabetic retinopathy. We found that the RXR-gamma gene is involved in the pathogenesis of diabetic nephropathy. We also hypothesized that the RXR-gamma gene has a role in the development of diabetic retinopathy. We examined 213 diabetic patients, who were divided into retinopathy or no retinopathy groups. Nine selected single nucleotide polymorphisms (SNPs) in the RXR-gamma gene were evaluated. The diabetic retinopathy group had longer diabetes duration, higher body mass indexes, and higher systolic blood pressure, as well as higher concentrations of fasting plasma glucose, blood urine nitrogen, and creatine. One SNP--rs3818569 of the RXR-gamma gene was found to be associated with increased risk for diabetic retinopathy in both allele and genotype frequencies (P = 0.0023 and 0.0057, respectively). Analysis with multivariate logistic regression revealed that the dominant RXR-gamma GG genotype is a risk factors for the development of diabetic retinopathy (odds ratio = 2.388; 95% confidence interval = 1.17-4.875). We conclude that the RXR-gamma rs3818569 SNP is associated with diabetic retinopathy development in the Taiwanese population.
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Affiliation(s)
- C-H Hsieh
- Department of Internal Medicine, Division of Endocrinology and Metabolism, National Defense Medical Center, Tri-Service General Hospital, Taipei, Taiwan.
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Igo RP, Iyengar SK, Nicholas SB, Goddard KAB, Langefeld CD, Hanson RL, Duggirala R, Divers J, Abboud H, Adler SG, Arar NH, Horvath A, Elston RC, Bowden DW, Guo X, Ipp E, Kao WHL, Kimmel PL, Knowler WC, Meoni LA, Molineros J, Nelson RG, Pahl MV, Parekh RS, Rasooly RS, Schelling JR, Shah VO, Smith MW, Winkler CA, Zager PG, Sedor JR, Freedman BI. Genomewide linkage scan for diabetic renal failure and albuminuria: the FIND study. Am J Nephrol 2011; 33:381-9. [PMID: 21454968 DOI: 10.1159/000326763] [Citation(s) in RCA: 49] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2011] [Accepted: 02/23/2011] [Indexed: 01/06/2023]
Abstract
BACKGROUND Diabetic nephropathy (DN) is a leading cause of mortality and morbidity in patients with type 1 and type 2 diabetes. The multicenter FIND consortium aims to identify genes for DN and its associated quantitative traits, e.g. the urine albumin:creatinine ratio (ACR). Herein, the results of whole-genome linkage analysis and a sparse association scan for ACR and a dichotomous DN phenotype are reported in diabetic individuals. METHODS A genomewide scan comprising more than 5,500 autosomal single nucleotide polymorphism markers (average spacing of 0.6 cM) was performed on 1,235 nuclear and extended pedigrees (3,972 diabetic participants) ascertained for DN from African-American (AA), American-Indian (AI), European-American (EA) and Mexican-American (MA) populations. RESULTS Strong evidence for linkage to DN was detected on chromosome 6p (p = 8.0 × 10(-5), LOD = 3.09) in EA families as well as suggestive evidence for linkage to chromosome 7p in AI families. Regions on chromosomes 3p in AA, 7q in EA, 16q in AA and 22q in MA displayed suggestive evidence of linkage for urine ACR. The linkage peak on chromosome 22q overlaps the MYH9/APOL1 gene region, previously implicated in AA diabetic and nondiabetic nephropathies. CONCLUSION These results strengthen the evidence for previously identified genomic regions and implicate several novel loci potentially involved in the pathogenesis of DN.
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Affiliation(s)
- Robert P Igo
- Genetic Analysis and Data Coordinating Center, Cleveland, Ohio, USA
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McDonough CW, Palmer ND, Hicks PJ, Roh BH, An SS, Cooke JN, Hester JM, Wing MR, Bostrom MA, Rudock ME, Lewis JP, Talbert ME, Blevins RA, Lu L, Ng MCY, Sale MM, Divers J, Langefeld CD, Freedman BI, Bowden DW. A genome-wide association study for diabetic nephropathy genes in African Americans. Kidney Int 2010; 79:563-72. [PMID: 21150874 DOI: 10.1038/ki.2010.467] [Citation(s) in RCA: 125] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
A genome-wide association study was performed using the Affymetrix 6.0 chip to identify genes associated with diabetic nephropathy in African Americans. Association analysis was performed adjusting for admixture in 965 type 2 diabetic African American patients with end-stage renal disease (ESRD) and in 1029 African Americans without type 2 diabetes or kidney disease as controls. The top 724 single nucleotide polymorphisms (SNPs) with evidence of association to diabetic nephropathy were then genotyped in a replication sample of an additional 709 type 2 diabetes-ESRD patients and 690 controls. SNPs with evidence of association in both the original and replication studies were tested in additional African American cohorts consisting of 1246 patients with type 2 diabetes without kidney disease and 1216 with non-diabetic ESRD to differentiate candidate loci for type 2 diabetes-ESRD, type 2 diabetes, and/or all-cause ESRD. Twenty-five SNPs were significantly associated with type 2 diabetes-ESRD in the genome-wide association and initial replication. Although genome-wide significance with type 2 diabetes was not found for any of these 25 SNPs, several genes, including RPS12, LIMK2, and SFI1 are strong candidates for diabetic nephropathy. A combined analysis of all 2890 patients with ESRD showed significant association SNPs in LIMK2 and SFI1 suggesting that they also contribute to all-cause ESRD. Thus, our results suggest that multiple loci underlie susceptibility to kidney disease in African Americans with type 2 diabetes and some may also contribute to all-cause ESRD.
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Affiliation(s)
- Caitrin W McDonough
- Program in Molecular Medicine and Translational Science, Wake Forest University School of Medicine, Winston-Salem, North Carolina 27157, USA
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Arar N, Seo J, Lee S, Abboud HE, Copeland LA, Noel P, Parchman M. Preferences regarding genetic research results: comparing veterans and nonveterans responses. Public Health Genomics 2010; 13:431-9. [PMID: 20829581 DOI: 10.1159/000317099] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2009] [Accepted: 06/16/2010] [Indexed: 02/03/2023] Open
Abstract
OBJECTIVE Communicating genetic research results to participants presents ethical challenges. Our objectives were to examine participants' preferences in receiving future genetic research results and to compare preferences reported by veteran and nonveterans participants. METHODS Secondary analysis was performed on data collected in 2000-2004 from 1,575 consent forms signed by Mexican-American participants enrolled in 2 genetic family studies (GFS) in San Antonio: The Family Investigation of Nephropathy and Diabetes (FIND) and the Extended FIND (EFIND). The consent forms for these studies contained multiple-choice questions to examine participants' preferences about receiving their (1) clinical lab results and (2) future genetic research results. The FIND and EFIND databases had information on subjects' demographic characteristics and some selected clinical variables. We identified veterans using the Veterans Health Administration's (VHA's) centralized data repository. We compared veterans' and nonveterans' preferences using Student's t test for continuous variables and χ² test for discrete variables. A logistic regression analyzed subjects' preference for receiving their research results, controlling for other socio-demographic and clinical variables. RESULTS The sample included 275 (18%) veterans and 1,247 (82%) nonveterans. Our results indicated a strong desire among the majority of participants 1,445 (95%) in getting their clinical lab research results. Likewise, 93% expressed interest in being informed about their future genetic results. There was no significant difference in veterans' and nonveterans' preference to disclosure of the research results (χ² test; p > 0.05). Regression analysis showed no significant relationship (p = 0.449) between the outcome (receiving research results) and veterans' responses after controlling for demographics and educational levels. CONCLUSION Participants believed they would prefer receiving their genetic research results. Veterans are similar to nonveterans in their preferences. Offering genetic research results to participants should be based on well defined and structured plans to enhance interpretation of genetic data.
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Affiliation(s)
- N Arar
- Division of Nephrology, Department of Medicine, University of Texas Health Science Center at San Antonio, Audie L. Murphy Memorial Veterans Hospital, San Antonio, TX 78229-3900, USA.
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Chiu YW, Adler S, Budoff M, Takasu J, Ashai J, Mehrotra R. Prevalence and prognostic significance of renal artery calcification in patients with diabetes and proteinuria. Clin J Am Soc Nephrol 2010; 5:2093-100. [PMID: 20705966 DOI: 10.2215/cjn.03730410] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
BACKGROUND AND OBJECTIVES Vascular calcification is common and severe in chronic kidney disease. Because the consequences of calcification may differ by vascular beds, we sought to test the hypothesis that patients who have diabetes with proteinuria and have significant renal artery calcification (RAC) have a higher risk for progression to ESRD. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS Using electron-beam computed tomography, RAC was computed as the sum of Agatston scores at each of the two renal ostia and renal arteries. Time-to-event analysis was conducted to compare the risk in individuals with or without significant RAC (total score >10). RESULTS Of 172 patients with type 2 diabetes and overt proteinuria studied (estimated GFR 56 ± 25 ml/min per 1.73 m(2)), significant RAC was present in 31%. In 33 ± 21 months, 41 progressed to ESRD and 65 reached a composite outcome (ESRD or death). Serum phosphorus was a significant predictor of progression to ESRD but was replaced by the significant RAC in multivariate models that included the latter. Individuals with significant RAC had a higher risk for reaching the composite outcome. In contrast, there was no association between coronary artery calcification scores and progression to ESRD. CONCLUSIONS Significant RAC was an independent predictor of progression to ESRD as well as reaching the composite outcome. Understanding the pathogenesis of RAC would allow determination of whether this risk is potentially modifiable.
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Affiliation(s)
- Yi-Wen Chiu
- Department of Medicine, Los Angeles Biomedical Research Institute, Torrance, California, USA
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Drawz PE, Sedor JR. Translating associations between common kidney diseases and genetic variation into the clinic. Semin Nephrol 2010; 30:195-202. [PMID: 20347648 DOI: 10.1016/j.semnephrol.2010.01.010] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Studies of the genetics of common diseases have revealed multiple risk alleles associated with end-stage renal disease, albuminuria, serum creatinine, diabetes, coronary heart disease, and increased triglyceride levels. These associations have prompted further basic science research, which has led to the discovery of novel pathways and a better understanding of the pathophysiology of common diseases. Currently, the ability to translate these discoveries into clinical practice is limited by the small effect size of these risk alleles and a lack of studies showing meaningful impact of genetic variation on risk assessment and clinical outcomes. Advances in genetic testing will continue to yield highly significant associations but translation into clinical practice will require effective collaboration between physicians and basic and social scientists. Rigorous clinical trials eventually will reveal which combination of genetic tests improves risk stratification and identifies individuals most likely to benefit from specific prevention strategies and therapies.
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Affiliation(s)
- Paul E Drawz
- Division of Nephrology and Hypertension, Case Western Reserve University, Cleveland, OH, USA
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Adler S, Pahl M, Abboud H, Nicholas S, Ipp E, Seldin M. Mexican-American admixture mapping analyses for diabetic nephropathy in type 2 diabetes mellitus. Semin Nephrol 2010; 30:141-9. [PMID: 20347643 DOI: 10.1016/j.semnephrol.2010.01.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Diabetic nephropathy is a classic complex trait, whose development in a given individual reflects contributions from multiple genes and whose expression is modulated by environmental factors. Numerous genetic strategies have been used to identify common disease risk loci and genes, including candidate gene analyses, linkage analysis, transmission disequilibrium testing (a family based association test to identify linkage between a genetic marker and a biological trait or disease), and admixture mapping (also referred to as mapping by admixture linkage disequilibrium). Choosing the best genetic strategy to identify susceptibility genes in a disease is dependent on knowing whether the disorder is monogenic (the result of one gene), oligogenic (the result of a few genes), or polygenic (the result of many genes). The likelihood of finding risk loci for a disease with a putative genetic contribution is in part owing to the disease recurrence risk ratio (the risk of expressing the disease phenotype in siblings of the proband divided by the risk observed in the general population), the genotypic risk ratio (the risk of expressing the phenotype if the gene is present divided by the risk if the gene is not present), the number of susceptibility genes, how the susceptibility genes interact, how much of the disease risk is contributed by environmental factors, and the disease penetrance (the likelihood that the phenotype will be expressed if the gene is present).
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Affiliation(s)
- Sharon Adler
- Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA 90502, USA.
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Chiu YW, Adler SG, Budoff MJ, Takasu J, Ashai J, Mehrotra R. Coronary artery calcification and mortality in diabetic patients with proteinuria. Kidney Int 2010; 77:1107-14. [DOI: 10.1038/ki.2010.70] [Citation(s) in RCA: 71] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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Kim S, Abboud HE, Pahl MV, Tayek J, Snyder S, Tamkin J, Alcorn H, Ipp E, Nast CC, Elston RC, Iyengar SK, Adler SG. Examination of association with candidate genes for diabetic nephropathy in a Mexican American population. Clin J Am Soc Nephrol 2010; 5:1072-8. [PMID: 20299368 PMCID: PMC2879299 DOI: 10.2215/cjn.06550909] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2009] [Accepted: 02/10/2010] [Indexed: 12/18/2022]
Abstract
BACKGROUND AND OBJECTIVES Diabetic nephropathy (DN) is a multifactorial complication characterized by persistent proteinuria in susceptible individuals with type 1 and type 2 diabetes. Disease burden in people of Mexican-American descent is particularly high, but there are only a few studies that characterize genes for DN in this ethnic group. Two genes, carnosine dipeptidase 1 (CNDP1) and engulfment and cell motility 1 (ELMO1) previously showed association with DN in other ethnic groups. CNDP1 and ELMO1 were examined along with eight other genes that are less well characterized for DN in a new study of Mexican-Americans. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS The target sample was patients of Mexican-American ancestry collected from three centers: 455 patients with DN and 437 controls with long-term diabetes but no incident nephropathy. Forty-two, 227, and 401 single nucleotide polymorphisms (SNPs) in CNDP1, ELMO1, and the other eight genes, respectively, were examined. RESULTS No region in CNDP1 or ELMO1 showed significant P values. Of the other eight candidate genes, an association of DN with a SNP pair, rs2146098 and rs6659783, was found in hemicentin 1 (HMCN1) (unadjusted P = 6.1 x 10(-5)). Association with a rare haplotype in this region was subsequently identified. CONCLUSIONS The associations in CNDP1 or ELMO1 were not replicable; however, an association of DN with HMCN1 was found. Additional work at this and other loci will enable refinement of the genetic hypotheses regarding DN in the Mexican-American population to find therapies for this debilitating disease.
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Affiliation(s)
- Sulgi Kim
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio
| | | | - Madeleine V. Pahl
- Division of Nephrology and Hypertension, University of California–Irvine, Irvine, California
| | - John Tayek
- Los Angeles Biomedical Research Institute at Harbor–UCLA Medical Center, Torrance, California
| | - Susan Snyder
- Los Angeles Biomedical Research Institute at Harbor–UCLA Medical Center, Torrance, California
| | - James Tamkin
- Providence Medical Institute, Torrance, California; and
| | - Harry Alcorn
- DaVita Clinical Research, Minneapolis, Minnesota
| | - Eli Ipp
- Los Angeles Biomedical Research Institute at Harbor–UCLA Medical Center, Torrance, California
| | - Cynthia C. Nast
- Los Angeles Biomedical Research Institute at Harbor–UCLA Medical Center, Torrance, California
| | - Robert C. Elston
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio
| | - Sudha K. Iyengar
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio
| | - Sharon G. Adler
- Los Angeles Biomedical Research Institute at Harbor–UCLA Medical Center, Torrance, California
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Freedman BI, Hicks PJ, Bostrom MA, Comeau ME, Divers J, Bleyer AJ, Kopp JB, Winkler CA, Nelson GW, Langefeld CD, Bowden DW. Non-muscle myosin heavy chain 9 gene MYH9 associations in African Americans with clinically diagnosed type 2 diabetes mellitus-associated ESRD. Nephrol Dial Transplant 2009; 24:3366-71. [PMID: 19567477 PMCID: PMC2910323 DOI: 10.1093/ndt/gfp316] [Citation(s) in RCA: 81] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2009] [Accepted: 06/04/2009] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND Although MYH9 is strongly associated with biopsy-proven idiopathic and HIV-associated focal segmental glomerulosclerosis (FSGS) and clinically diagnosed 'hypertension-associated' end-stage renal disease (ESRD) in African Americans, its role in type 2 diabetes mellitus (T2DM)-associated ESRD is unclear. METHODS To assess whether MYH9 was associated with T2DM-ESRD, 751 African Americans with T2DM-ESRD, 227 with T2DM lacking nephropathy and 925 non-diabetic non-nephropathy controls were genotyped for 14 MYH9 SNPs. Association analyses used SNPGWA and Dandelion. RESULTS Comparing T2DM-ESRD cases with non-diabetic controls, single SNP associations were detected with 8 of 14 SNPs, gender- and admixture-adjusted P-values 0.047-0.005 [recessive model, odds ratio (OR) range 1.30-1.55]. The previously associated MYH9 E1 and L1 haplotypes were associated with T2DM-ESRD (E1: OR 1.27, 95% CI 1.04-1.56, P = 0.021 recessive and L1: OR 1.43, 95% CI 1.09-1.87, P = 0.009 dominant). Contrasting the 751 T2DM-ESRD cases with 227 T2DM non-nephropathy controls revealed that E1 haplotype SNPs rs4821480, rs2032487 and rs4821481 were associated with kidney failure (OR 1.38-1.40 recessive, all P < 0.048). Among E1 and L1 risk homozygotes, respectively, mean (SD) diabetes duration prior to renal replacement therapy was 16.6 (9.7) and 16.4 (10.0) years, and 65% had diabetic retinopathy. CONCLUSIONS Genetic dissection of T2DM-associated ESRD reveals that MYH9 underlies a portion of this clinically diagnosed disorder in African Americans. It is likely that a subset of African Americans with T2DM and coincident nephropathy have primary MYH9-related kidney disease (e.g. FSGS or global glomerulosclerosis), although renal biopsy studies need to be performed.
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Affiliation(s)
- Barry I Freedman
- 1Internal Medicine/Nephrology, 2Biochemistry, 3Biostatistical Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
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Malhotra A, Igo RP, Thameem F, Kao WL, Abboud HE, Adler SG, Arar NH, Bowden DW, Duggirala R, Freedman BI, Goddard KA, Ipp E, Iyengar SK, Kimmel PL, Knowler WC, Kohn O, Leehey D, Meoni LA, Nelson RG, Nicholas SB, Parekh RS, Rich SS, Chen YDI, Saad MF, Scavini M, Schelling JR, Sedor JR, Shah VO, Taylor KD, Thornley-Brown D, Zager PG, Horvath A, Hanson RL. Genome-wide linkage scans for type 2 diabetes mellitus in four ethnically diverse populations-significant evidence for linkage on chromosome 4q in African Americans: the Family Investigation of Nephropathy and Diabetes Research Group. Diabetes Metab Res Rev 2009; 25:740-7. [PMID: 19795399 PMCID: PMC2783577 DOI: 10.1002/dmrr.1031] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
BACKGROUND Previous studies have shown that in addition to environmental influences, type 2 diabetes mellitus (T2DM) has a strong genetic component. The goal of the current study is to identify regions of linkage for T2DM in ethnically diverse populations. METHODS Phenotypic and genotypic data were obtained from African American (AA; total number of individuals [N] = 1004), American Indian (AI; N = 883), European American (EA; N = 537), and Mexican American (MA; N = 1634) individuals from the Family Investigation of Nephropathy and Diabetes. Non-parametric linkage analysis, using an average of 4404 SNPs, was performed in relative pairs affected with T2DM in each ethnic group. In addition, family-based tests were performed to detect association with T2DM. RESULTS Statistically significant evidence for linkage was observed on chromosome 4q21.1 (LOD = 3.13; genome-wide p = 0.04) in AA. In addition, a total of 11 regions showed suggestive evidence for linkage (estimated at LOD > 1.71), with the highest LOD scores on chromosomes 12q21.31 (LOD = 2.02) and 22q12.3 (LOD = 2.38) in AA, 2p11.1 (LOD = 2.23) in AI, 6p12.3 (LOD = 2.77) in EA, and 13q21.1 (LOD = . 2.24) in MA. While no region overlapped across all ethnic groups, at least five loci showing LOD > 1.71 have been identified in previously published studies. CONCLUSIONS The results from this study provide evidence for the presence of genes affecting T2DM on chromosomes 4q, 12q, and 22q in AA; 6p in EA; 2p in AI; and 13q in MA. The strong evidence for linkage on chromosome 4q in AA provides important information given the paucity of diabetes genetic studies in this population.
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Affiliation(s)
- Alka Malhotra
- National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona
| | | | - Farook Thameem
- University of Texas Health Science Center at San Antonio, San Antonio, Texas
| | | | - Hanna E. Abboud
- University of Texas Health Science Center at San Antonio, San Antonio, Texas
| | - Sharon G. Adler
- Harbor-University of California Los Angeles Medical Center, Torrance, California
| | - Nedal H. Arar
- University of Texas Health Science Center at San Antonio, San Antonio, Texas
| | | | | | | | | | - Eli Ipp
- Harbor-University of California Los Angeles Medical Center, Torrance, California
| | | | - Paul L. Kimmel
- National Institute of Diabetes and Digestive and Kidney Diseases Program Office, Bethesda, Maryland
| | - William C. Knowler
- National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona
| | - Orly Kohn
- University of Chicago, Chicago, Illinois
| | | | | | - Robert G. Nelson
- National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona
| | | | | | | | - Yii-Der I. Chen
- University of California Los Angeles, Los Angeles, California
| | | | - Marina Scavini
- University of New Mexico, Albuquerque, New Mexico
- San Raffaele Scientific Institute, Milan (Italy)
| | | | | | | | - Kent D. Taylor
- University of California Los Angeles, Los Angeles, California
| | | | | | | | - Robert L. Hanson
- National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona
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Brosius FC, Alpers CE, Bottinger EP, Breyer MD, Coffman TM, Gurley SB, Harris RC, Kakoki M, Kretzler M, Leiter EH, Levi M, McIndoe RA, Sharma K, Smithies O, Susztak K, Takahashi N, Takahashi T. Mouse models of diabetic nephropathy. J Am Soc Nephrol 2009; 20:2503-12. [PMID: 19729434 DOI: 10.1681/asn.2009070721] [Citation(s) in RCA: 438] [Impact Index Per Article: 29.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open
Abstract
Diabetic nephropathy is a major cause of ESRD worldwide. Despite its prevalence, a lack of reliable animal models that mimic human disease has delayed the identification of specific factors that cause or predict diabetic nephropathy. The Animal Models of Diabetic Complications Consortium (AMDCC) was created in 2001 by the National Institutes of Health to develop and characterize models of diabetic nephropathy and other complications. This interim report and our online supplement detail the progress made toward that goal, specifically in the development and testing of murine models. Updates are provided on validation criteria for early and advanced diabetic nephropathy, phenotyping methods, the effect of background strain on nephropathy, current best models of diabetic nephropathy, negative models, and views of future directions. AMDCC investigators and other investigators in the field have yet to validate a complete murine model of human diabetic kidney disease. Nonetheless, the critical analysis of existing murine models substantially enhances our understanding of this disease process.
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Affiliation(s)
- Frank C Brosius
- University of Michigan,1150 W. Medical Center Drive, Ann Arbor, MI 48109-0680, USA.
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Arar NH, Freedman BI, Adler SG, Iyengar SK, Chew EY, Davis MD, Satko SG, Bowden DW, Duggirala R, Elston RC, Guo X, Hanson RL, Igo RP, Ipp E, Kimmel PL, Knowler WC, Molineros J, Nelson RG, Pahl MV, Quade SRE, Rasooly RS, Rotter JI, Saad MF, Scavini M, Schelling JR, Sedor JR, Shah VO, Zager PG, Abboud HE. Heritability of the severity of diabetic retinopathy: the FIND-Eye study. Invest Ophthalmol Vis Sci 2008; 49:3839-45. [PMID: 18765632 DOI: 10.1167/iovs.07-1633] [Citation(s) in RCA: 121] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
PURPOSE Diabetic retinopathy (DR) and diabetic nephropathy (DN) are serious microvascular complications of diabetes mellitus. Correlations between severity of DR and DN and computed heritability estimates for DR were determined in a large, multiethnic sample of diabetic families. The hypothesis was that (1) the severity of DR correlates with the presence and severity of nephropathy in individuals with diabetes mellitus, and (2) the severity of DR is under significant familial influence in members of multiplex diabetic families. METHODS The Family Investigation of Nephropathy and Diabetes (FIND) was designed to evaluate the genetic basis of DN in American Indians, European Americans, African Americans, and Mexican Americans. FIND enrolled probands with advanced DN, along with their diabetic siblings who were concordant and discordant for nephropathy. These diabetic family members were invited to participate in the FIND-Eye study to determine whether inherited factors underlie susceptibility to DR and its severity. FIND-Eye participants underwent eye examinations and had fundus photographs taken. The severity of DR was graded by using the Early Treatment Diabetic Retinopathy Study Classification (ETDRS). Sib-sib correlations were calculated with the SAGE 5.0 program FCOR, to estimate heritability of retinopathy severity. RESULTS This report summarizes the results for the first 2368 diabetic subjects from 767 families enrolled in FIND-Eye; nearly 50% were Mexican American, the largest single ethnicity within FIND. The overall prevalence of DR was high; 33.4% had proliferative DR; 7.5%, 22.8%, and 9.5% had severe, moderate, and mild nonproliferative DR, respectively; 26.6% had no DR. The severity of DR was significantly associated with severity of DN, both by phenotypic category and by increasing serum creatinine concentration (chi(2) = 658.14, df = 20; P < 0.0001). The sib-sib correlation for DR severity was 0.1358 in the total sample and 0.1224 when limited to the Mexican-American sample. Broad sense heritabilities for DR were 27% overall and 24% in Mexican-American families. The polygenic heritability of liability for proliferative DR approximated 25% in this FIND-Eye sample. CONCLUSIONS These data confirm that the severity of DR parallels the presence and severity of nephropathy in individuals with diabetes mellitus. The severity of DR in members of multiplex diabetic families appears to have a significant familial connection.
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Affiliation(s)
- Nedal H Arar
- Family Investigation of Nephropathy and Diabetes (FIND) Genetic Analysis and Data Coordinating Center, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, USA
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Kao WHL, Klag MJ, Meoni LA, Reich D, Berthier-Schaad Y, Li M, Coresh J, Patterson N, Tandon A, Powe NR, Fink NE, Sadler JH, Weir MR, Abboud HE, Adler SG, Divers J, Iyengar SK, Freedman BI, Kimmel PL, Knowler WC, Kohn OF, Kramp K, Leehey DJ, Nicholas SB, Pahl MV, Schelling JR, Sedor JR, Thornley-Brown D, Winkler CA, Smith MW, Parekh RS. MYH9 is associated with nondiabetic end-stage renal disease in African Americans. Nat Genet 2008; 40:1185-92. [PMID: 18794854 DOI: 10.1038/ng.232] [Citation(s) in RCA: 488] [Impact Index Per Article: 30.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2008] [Accepted: 07/21/2008] [Indexed: 12/20/2022]
Abstract
As end-stage renal disease (ESRD) has a four times higher incidence in African Americans compared to European Americans, we hypothesized that susceptibility alleles for ESRD have a higher frequency in the West African than the European gene pool. We carried out a genome-wide admixture scan in 1,372 ESRD cases and 806 controls and found a highly significant association between excess African ancestry and nondiabetic ESRD (lod score = 5.70) but not diabetic ESRD (lod = 0.47) on chromosome 22q12. Each copy of the European ancestral allele conferred a relative risk of 0.50 (95% CI = 0.39-0.63) compared to African ancestry. Multiple common SNPs (allele frequencies ranging from 0.2 to 0.6) in the gene encoding nonmuscle myosin heavy chain type II isoform A (MYH9) were associated with two to four times greater risk of nondiabetic ESRD and accounted for a large proportion of the excess risk of ESRD observed in African compared to European Americans.
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Affiliation(s)
- W H Linda Kao
- Department of Epidemiology, School of Medicine and Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland 21287, USA.
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Ng DPK, Tai BC, Lim XL. Is the presence of retinopathy of practical value in defining cases of diabetic nephropathy in genetic association studies? The experience with the ACE insertion/deletion polymorphism in 53 studies comprising 17,791 subjects. Diabetes 2008; 57:2541-6. [PMID: 18523141 PMCID: PMC2518508 DOI: 10.2337/db08-0581] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2008] [Accepted: 05/28/2008] [Indexed: 11/13/2022]
Abstract
OBJECTIVE A key consideration when setting up genetic studies is the case definition. For diabetic nephropathy, the case definition is typically based on the presence of albuminuria. However, it has been long debated whether diabetic nephropathy cases defined in this way may have a high prevalence of nondiabetic kidney disease, especially if diabetic retinopathy is absent. RESEARCH DESIGN AND METHODS We performed a meta-analysis of 53 studies comprising 17,791 subjects investigating the angiotensin-I converting enzyme insertion/deletion polymorphism, taking into account the requirement for diabetic retinopathy in the case definition and assuming a random-effects model. RESULTS No publication bias was observed. The overall pooled odds ratio (OR) for all 53 studies was 0.78 (95% CI 0.70-0.87; P < 0.001), which indicated a significant protection against diabetic nephropathy for genotype II compared with carriage of the D-allele. The pooled OR for the 11 studies (n = 3,413) requiring diabetic retinopathy in the case definition was 0.68 (0.53-0.86; P = 0.002), and this was not significantly different from the pooled OR of 0.81 (0.71-0.92; P = 0.001) obtained from the 42 remaining studies (n = 14,378) (P = 0.198). This lack of any significant effect of diabetic retinopathy was reiterated in subgroup analyses based on the type of diabetes present. CONCLUSIONS Stipulating the presence of diabetic retinopathy in the case definition of diabetic nephropathy did not appear to confer tangible benefits when detecting genetic associations. Besides reducing sample sizes, this stipulation makes the interpretation of genetic associations more difficult due to the potential confounding presence of diabetic retinopathy.
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Affiliation(s)
- Daniel P K Ng
- Department of Community, Occupational and Family Medicine, National University of Singapore, Singapore.
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Freedman BI, Bowden DW, Rich SS, Xu J, Wagenknecht LE, Ziegler J, Hicks PJ, Langefeld CD. Genome-wide linkage scans for renal function and albuminuria in Type 2 diabetes mellitus: the Diabetes Heart Study. Diabet Med 2008; 25:268-76. [PMID: 18307454 DOI: 10.1111/j.1464-5491.2007.02361.x] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
AIMS/HYPOTHESIS Glomerular filtration rate (GFR), end-stage renal disease and albuminuria are highly heritable. We performed a genome-wide linkage scan in 416 Diabetes Heart Study (DHS) families to detect loci that contributed to renal function and albuminuria. MATERIALS AND METHODS A total of 1067 individuals (900 with Type 2 diabetes mellitus) from 348 European American and 68 African American DHS families had measures of urine albumin : creatinine ratio (ACR), serum creatinine concentration and Modification of Diet in Renal Disease estimated GFR (eGFR). Variance components quantitative trait linkage analysis (using SOLAR) was computed. RESULTS Participants had mean +/- sd age 61.4 +/- 9.4 years; diabetes duration 10.5 +/- 7.4 years; eGFR 1.15 +/- 0.32 ml/sec; and urine ACR 15.8 +/- 67.2 mmol/l (median 1.4). In all families, significant evidence for linkage of GFR was observed on chromosome 2p16 (log of the odds; LOD = 4.31 at 72.0 cM, ATA47C04P/D2S1352) and 1p36 (LOD = 3.81 at 45.0 cM, D1S3669/D1S3720), with suggestive evidence on 7q21 (LOD = 2.42 at 99.0 cM, D7S820/D7S821) and 13q13 (LOD = 2.28 at 28.0 cM, D13S1493/D13S894). The evidence for linkage to ACR was far weaker, on 13q21-q22 (LOD = 1.84 at 50 cM, D13S1807/D13S800), 3p24-p23 (LOD = 1.81 at 58 cM, D3S3038/D3S2432) and 10p11 (LOD = 1.78 at 71.0 cM, D10S1208/D10S1221). CONCLUSIONS/INTERPRETATIONS The eGFR linkage peaks on 2p16, 7q21 and 13q13 closely overlap with nephropathy peaks identified in family studies enriched for severe kidney disease. These diabetes-enriched families provide an opportunity to map genes regulating renal function, potentially leading to the identification of genes producing nephropathy susceptibility in subjects with Type 2 diabetes.
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Affiliation(s)
- B I Freedman
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC 27157-1053, USA.
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Abstract
PURPOSE OF REVIEW To discuss mouse models of diabetic nephropathy and their use in discovering genetic risk factors predisposing to diabetic nephropathy. RECENT FINDINGS Despite occurring in only 10-40% of diabetic patients, diabetic nephropathy is the largest single cause of end stage renal disease in the USA. Accumulated evidence points to critical genetic factors that predispose a subset of diabetic patients to nephropathy. Defining the genes that confer risk for nephropathy in human populations has proven challenging. The use of robust genetic reagents available in the laboratory mouse provides a complementary approach to defining genes that predispose to diabetic nephropathy in mice and humans. These findings support the existence of dominant mutations predisposing to diabetic nephropathy in mice as well as substantiating an important role for eNOS in forestalling the development of diabetic nephropathy. SUMMARY When studied for a sufficient duration of diabetic hyperglycemia, some strains of mice exhibit changes similar to those of human diabetic nephropathy. The unique genetic reagents in mice should help accelerate the identification of genes predisposing to diabetic nephropathy.
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