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Frodsham SG, Yu Z, Lyons AM, Agarwal A, Pezzolesi MH, Dong L, Srinivas TR, Ying J, Greene T, Raphael KL, Smith KR, Pezzolesi MG. The Familiality of Rapid Renal Decline in Diabetes. Diabetes 2019; 68:420-429. [PMID: 30425064 PMCID: PMC6341306 DOI: 10.2337/db18-0838] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Accepted: 11/05/2018] [Indexed: 12/15/2022]
Abstract
Sustained and rapid loss of glomerular filtration rate (GFR) is the predominant clinical feature of diabetic kidney disease and a requisite for the development of end-stage renal disease. Although GFR trajectories have been studied in several cohorts with diabetes and without diabetes, whether rapid renal decline clusters in families with diabetes has not been examined. To determine this, we estimated GFR (eGFR) from serum creatinine measurements obtained from 15,612 patients with diabetes at the University of Utah Health Sciences Center and established their renal function trajectories. Patients with rapid renal decline (eGFR slope < -5 mL/min/1.73 m2/year) were then mapped to pedigrees using extensive genealogical records from the Utah Population Database to identify high-risk rapid renal decline pedigrees. We identified 2,127 (13.6%) rapid decliners with a median eGFR slope of -8.0 mL/min/1.73 m2/year and 51 high-risk pedigrees (ranging in size from 1,450 to 24,501 members) with excess clustering of rapid renal decline. Familial analysis showed that rapid renal decline aggregates in these families and is associated with its increased risk among first-degree relatives. Further study of these families is necessary to understand the magnitude of the influence of shared familial factors, including environmental and genetic factors, on rapid renal decline in diabetes.
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Affiliation(s)
- Scott G Frodsham
- Division of Nephrology and Hypertension, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT
| | - Zhe Yu
- Population Science, Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, UT
| | - Ann M Lyons
- Hospital Information Technology Services, Enterprise Data Warehouse, University of Utah Hospital and Clinics, Salt Lake City, UT
| | - Adhish Agarwal
- Division of Nephrology and Hypertension, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT
| | - Melissa H Pezzolesi
- Division of Nephrology and Hypertension, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT
| | - Li Dong
- Division of Nephrology, Intermountain Healthcare, Salt Lake City, UT
| | - Titte R Srinivas
- Division of Nephrology, Intermountain Healthcare, Salt Lake City, UT
| | - Jian Ying
- Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, UT
| | - Tom Greene
- Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, UT
| | - Kalani L Raphael
- Division of Nephrology and Hypertension, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT
- Medicine Section and Research Section, Veterans Affairs Salt Lake City Health Care System, Salt Lake City, UT
| | - Ken R Smith
- Population Science, Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, UT
| | - Marcus G Pezzolesi
- Division of Nephrology and Hypertension, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT
- Diabetes and Metabolism Center, University of Utah School of Medicine, Salt Lake City, UT
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Tziastoudi M, Stefanidis I, Stravodimos K, Zintzaras E. Identification of Chromosomal Regions Linked to Diabetic Nephropathy: A Meta-Analysis of Genome-Wide Linkage Scans. Genet Test Mol Biomarkers 2019; 23:105-117. [DOI: 10.1089/gtmb.2018.0209] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Affiliation(s)
- Maria Tziastoudi
- Department of Biomathematics, Faculty of Medicine, University of Thessaly, Larissa, Greece
| | - Ioannis Stefanidis
- Department of Nephrology, Faculty of Medicine, University of Thessaly, Larissa, Greece
| | - Konstantinos Stravodimos
- 1st University Department of Urology, Laiko General Hospital, National and Kapodistrian Athens University, Athens, Greece
| | - Elias Zintzaras
- Department of Biomathematics, Faculty of Medicine, University of Thessaly, Larissa, Greece
- The Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Tufts University School of Medicine, Boston, Massachusetts
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3
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van Zuydam NR, Ahlqvist E, Sandholm N, Deshmukh H, Rayner NW, Abdalla M, Ladenvall C, Ziemek D, Fauman E, Robertson NR, McKeigue PM, Valo E, Forsblom C, Harjutsalo V, Perna A, Rurali E, Marcovecchio ML, Igo RP, Salem RM, Perico N, Lajer M, Käräjämäki A, Imamura M, Kubo M, Takahashi A, Sim X, Liu J, van Dam RM, Jiang G, Tam CHT, Luk AOY, Lee HM, Lim CKP, Szeto CC, So WY, Chan JCN, Ang SF, Dorajoo R, Wang L, Clara TSH, McKnight AJ, Duffy S, Pezzolesi MG, Marre M, Gyorgy B, Hadjadj S, Hiraki LT, Ahluwalia TS, Almgren P, Schulz CA, Orho-Melander M, Linneberg A, Christensen C, Witte DR, Grarup N, Brandslund I, Melander O, Paterson AD, Tregouet D, Maxwell AP, Lim SC, Ma RCW, Tai ES, Maeda S, Lyssenko V, Tuomi T, Krolewski AS, Rich SS, Hirschhorn JN, Florez JC, Dunger D, Pedersen O, Hansen T, Rossing P, Remuzzi G, Brosnan MJ, Palmer CNA, Groop PH, Colhoun HM, Groop LC, McCarthy MI. A Genome-Wide Association Study of Diabetic Kidney Disease in Subjects With Type 2 Diabetes. Diabetes 2018; 67:1414-1427. [PMID: 29703844 PMCID: PMC6014557 DOI: 10.2337/db17-0914] [Citation(s) in RCA: 114] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2017] [Accepted: 03/30/2018] [Indexed: 01/10/2023]
Abstract
Identification of sequence variants robustly associated with predisposition to diabetic kidney disease (DKD) has the potential to provide insights into the pathophysiological mechanisms responsible. We conducted a genome-wide association study (GWAS) of DKD in type 2 diabetes (T2D) using eight complementary dichotomous and quantitative DKD phenotypes: the principal dichotomous analysis involved 5,717 T2D subjects, 3,345 with DKD. Promising association signals were evaluated in up to 26,827 subjects with T2D (12,710 with DKD). A combined T1D+T2D GWAS was performed using complementary data available for subjects with T1D, which, with replication samples, involved up to 40,340 subjects with diabetes (18,582 with DKD). Analysis of specific DKD phenotypes identified a novel signal near GABRR1 (rs9942471, P = 4.5 × 10-8) associated with microalbuminuria in European T2D case subjects. However, no replication of this signal was observed in Asian subjects with T2D or in the equivalent T1D analysis. There was only limited support, in this substantially enlarged analysis, for association at previously reported DKD signals, except for those at UMOD and PRKAG2, both associated with estimated glomerular filtration rate. We conclude that, despite challenges in addressing phenotypic heterogeneity, access to increased sample sizes will continue to provide more robust inference regarding risk variant discovery for DKD.
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MESH Headings
- Adult
- Aged
- Aged, 80 and over
- Case-Control Studies
- Diabetes Mellitus, Type 2/complications
- Diabetes Mellitus, Type 2/epidemiology
- Diabetes Mellitus, Type 2/genetics
- Diabetic Nephropathies/epidemiology
- Diabetic Nephropathies/genetics
- Female
- Genetic Predisposition to Disease
- Genome-Wide Association Study
- Humans
- Kidney Failure, Chronic/complications
- Kidney Failure, Chronic/epidemiology
- Kidney Failure, Chronic/genetics
- Male
- Middle Aged
- Polymorphism, Single Nucleotide
- Renal Insufficiency, Chronic/complications
- Renal Insufficiency, Chronic/epidemiology
- Renal Insufficiency, Chronic/genetics
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Affiliation(s)
- Natalie R van Zuydam
- Wellcome Centre Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, U.K.
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, U.K
| | - Emma Ahlqvist
- Diabetes and Endocrinology, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Niina Sandholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Abdominal Center Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Diabetes and Obesity Research Program, Research Programs Unit, University of Helsinki, Helsinki, Finland
| | | | - N William Rayner
- Wellcome Centre Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, U.K
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, U.K
- Human Genetics Programme, Wellcome Sanger Institute, University of Cambridge, Cambridge, U.K
| | - Moustafa Abdalla
- Wellcome Centre Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, U.K
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, U.K
- Department of Statistics, University of Oxford, Oxford, U.K
| | - Claes Ladenvall
- Diabetes and Endocrinology, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Daniel Ziemek
- Inflammation and Immunology Research Unit, Pfizer, Berlin, Germany
| | - Eric Fauman
- Computational Target Validation, Pfizer, Cambridge, MA
| | - Neil R Robertson
- Wellcome Centre Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, U.K
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, U.K
| | - Paul M McKeigue
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, U.K
| | - Erkka Valo
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Abdominal Center Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Diabetes and Obesity Research Program, Research Programs Unit, 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
- Diabetes and Obesity Research Program, Research Programs Unit, University of Helsinki, Helsinki, Finland
| | - Valma Harjutsalo
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Abdominal Center Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Diabetes and Obesity Research Program, Research Programs Unit, University of Helsinki, Helsinki, Finland
- Chronic Disease Prevention Unit, National Institute for Health and Welfare, Helsinki, Finland
| | | | - Annalisa Perna
- Clinical Research Center for Rare Diseases "Aldo e Cele Daccò," Istituto di Ricerche Farmacologiche "Mario Negri," Bergamo, Italy
| | - Erica Rurali
- Clinical Research Center for Rare Diseases "Aldo e Cele Daccò," Istituto di Ricerche Farmacologiche "Mario Negri," Bergamo, Italy
| | | | - Robert P Igo
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH
| | - Rany M Salem
- Department of Family Medicine and Public Health, University of California, San Diego, San Diego, CA
| | - Norberto Perico
- Clinical Research Center for Rare Diseases "Aldo e Cele Daccò," Istituto di Ricerche Farmacologiche "Mario Negri," Bergamo, Italy
| | - Maria Lajer
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Annemari Käräjämäki
- Department of Primary Health Care, Vaasa Central Hospital, Vaasa, Finland
- Diabetes Center, Vaasa Health Care Center, Vaasa, Finland
| | - Minako Imamura
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara, Japan
- Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Nishihara, Japan
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Atsushi Takahashi
- Department of Genomic Medicine, National Cerebral and Cardiovascular Center, Suita, Japan
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Jianjun Liu
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
- Division of Human Genetics, Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Guozhi Jiang
- Department of Medicine & Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
| | - Claudia H T Tam
- Department of Medicine & Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
| | - Andrea O Y Luk
- Department of Medicine & Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
| | - Heung Man Lee
- Department of Medicine & Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
- Integrated Bioinformatics Laboratory for Cancer and Metabolic Diseases, The Chinese University of Hong Kong, Hong Kong, China
| | - Cadmon K P Lim
- Department of Medicine & Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
| | - Cheuk Chun Szeto
- Department of Medicine & Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
| | - Wing Yee So
- Department of Medicine & Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
| | - Juliana C N Chan
- Department of Medicine & Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
| | | | - Su Fen Ang
- Clinical Research Unit, Khoo Teck Puat Hospital, National Healthcare Group, Singapore
| | - Rajkumar Dorajoo
- Division of Human Genetics, Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), Singapore
| | - Ling Wang
- Division of Human Genetics, Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), Singapore
| | - Tan Si Hua Clara
- Clinical Research Unit, Khoo Teck Puat Hospital, National Healthcare Group, Singapore
| | | | - Seamus Duffy
- Centre for Public Health, Queen's University Belfast, Belfast, U.K
| | | | - Marcus G Pezzolesi
- Division of Nephrology and Hypertension and Diabetes & Metabolism Research Center, University of Utah Health, Salt Lake City, UT
| | | | - Michel Marre
- Sorbonnes Université, University Pierre and Marie Curie, INSERM UMRS 1166, Institute for Cardiometabolism and Nutrition, Department of Genomics and Pathophysiology of Cardiovascular Diseases, Paris, France
| | - Beata Gyorgy
- Sorbonnes Université, University Pierre and Marie Curie, INSERM UMRS 1166, Institute for Cardiometabolism and Nutrition, Department of Genomics and Pathophysiology of Cardiovascular Diseases, Paris, France
| | - Samy Hadjadj
- Endocrinology-Diabetology, Centre Hospitalier Universitaire de Poitiers, Poitiers, France
- Clinical Investigation Center 1402 and U1082, INSERM, University of Poitiers, Poitiers, France
- Faculté de Médecine et de Pharmacie, University of Poitiers, Poitiers, France
| | - Linda T Hiraki
- Genetics & Genome Biology, The Hospital for Sick Children, Toronto, Canada
| | | | - Tarunveer S Ahluwalia
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Peter Almgren
- Diabetes and Cardiovascular Disease-Genetic Epidemiology, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Christina-Alexandra Schulz
- Diabetes and Cardiovascular Disease-Genetic Epidemiology, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Marju Orho-Melander
- Diabetes and Cardiovascular Disease-Genetic Epidemiology, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Allan Linneberg
- Research Centre for Prevention and Health, Capital Region of Denmark, Glostrup, Denmark
- Department of Clinical Experimental Research, Rigshospitalet, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Cramer Christensen
- Department of Internal Medicine and Endocrinology, Vejle Hospital, Vejle, Denmark
| | - Daniel R Witte
- Department of Public Health, Aarhus University, Aarhus, Denmark
- Danish Diabetes Academy, Odense, Denmark
| | - Niels Grarup
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ivan Brandslund
- Department of Regional Health Research, University of Southern Denmark, Odense, Denmark
- Department of Clinical Biochemistry, Vejle Hospital, Vejle, Denmark
| | - Olle Melander
- Hypertension and Cardiovascular Disease, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Andrew D Paterson
- Genetics & Genome Biology, The Hospital for Sick Children, Toronto, Canada
| | - David Tregouet
- Sorbonnes Université, University Pierre and Marie Curie, INSERM UMRS 1166, Institute for Cardiometabolism and Nutrition, Department of Genomics and Pathophysiology of Cardiovascular Diseases, Paris, France
| | | | - Su Chi Lim
- Diabetes Centre, Clinical Research Unit, Department of Medicine, Khoo Teck Puat Hospital, National Healthcare Group, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Ronald C W Ma
- Department of Medicine & Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
- Integrated Bioinformatics Laboratory for Cancer and Metabolic Diseases, The Chinese University of Hong Kong, Hong Kong, China
| | - E Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Cardiovascular & Metabolic Disorders Program, Duke-National University of Singapore Medical School, Singapore
| | - Shiro Maeda
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara, Japan
- Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Nishihara, Japan
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Valeriya Lyssenko
- Diabetes and Endocrinology, Department of Clinical Sciences, Lund University, Malmö, Sweden
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Norway
| | - Tiinamaija Tuomi
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Diabetes and Obesity Research Program, Research Programs Unit, University of Helsinki, Helsinki, Finland
- Abdominal Center Endocrinology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | | | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA
| | - Joel N Hirschhorn
- Center for Basic and Translational Obesity Research and Division of Endocrinology, Boston Children's Hospital, Boston, MA
- Programs in Medical and Population Genetics and Metabolism, Broad Institute, Cambridge, MA
- Department of Genetics, Harvard Medical School, Boston, MA
| | - Jose C Florez
- Programs in Medical and Population Genetics and Metabolism, Broad Institute, Cambridge, MA
- Diabetes Clinical Research Center, Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - David Dunger
- Department of Paediatrics, University of Cambridge, Cambridge, U.K
- Wellcome Trust-Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, U.K
| | - Oluf Pedersen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Torben Hansen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
| | - Peter Rossing
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Giuseppe Remuzzi
- Clinical Research Center for Rare Diseases "Aldo e Cele Daccò," Istituto di Ricerche Farmacologiche "Mario Negri," Bergamo, Italy
- Unit of Nephrology and Dialysis, Azienda Socio Sanitaria Territoriale Papa Giovanni XXIII, Bergamo, Italy
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | | | - Mary Julia Brosnan
- Cardiovascular, Metabolic and Endocrine Diseases Research Unit, Pfizer, Cambridge, MA
| | - Colin N A Palmer
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, U.K
| | - Per-Henrik Groop
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Abdominal Center Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Diabetes and Obesity Research Program, Research Programs Unit, University of Helsinki, Helsinki, Finland
- Baker IDI Heart and Diabetes Institute, Melbourne, Australia
| | - Helen M Colhoun
- Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, U.K
| | - Leif C Groop
- Diabetes and Endocrinology, Department of Clinical Sciences, Lund University, Malmö, Sweden
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Mark I McCarthy
- Wellcome Centre Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, U.K
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, U.K
- National Institute for Health Research, Oxford Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, U.K
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Lee J, Lee Y, Park B, Won S, Han JS, Heo NJ. Genome-wide association analysis identifies multiple loci associated with kidney disease-related traits in Korean populations. PLoS One 2018; 13:e0194044. [PMID: 29558500 PMCID: PMC5860731 DOI: 10.1371/journal.pone.0194044] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2017] [Accepted: 02/25/2018] [Indexed: 12/19/2022] Open
Abstract
Chronic kidney disease (CKD) is an important social health problem characterized by a decrease in the kidney glomerular filtration rate (GFR). In this study, we analyzed genome-wide association studies for kidney disease-related traits using data from a Korean adult health screening cohort comprising 7,064 participants. Kidney disease-related traits analyzed include blood urea nitrogen (BUN), serum creatinine, estimated GFR, and uric acid levels. We detected two genetic loci (SLC14A2 and an intergenic region) and 8 single nucleotide polymorphisms (SNPs) associated with BUN, 3 genetic loci (BCAS3, C17orf82, ALDH2) and 6 SNPs associated with serum creatinine, 3 genetic loci (BCAS3, C17orf82/TBX2, LRP2) and 7 SNPs associated with GFR, and 14 genetic loci (3 in ABCG2/PKD2, 2 in SLC2A9, 3 in intergenic regions on chromosome 4; OTUB1, NRXN2/SLC22A12, CDC42BPG, RPS6KA4, SLC22A9, and MAP4K2 on chromosome 11) and 84 SNPs associated with uric acid levels. By comparing significant genetic loci associated with serum creatinine levels and GFR, rs9895661 in BCAS3 and rs757608 in C17orf82 were simultaneously associated with both traits. The SNPs rs11710227 in intergenic regions on chromosome 3 showing significant association with BUN is newly discovered. Genetic variations of multiple gene loci are associated with kidney disease-related traits, and differences in associations between kidney disease-related traits and genetic variation are dependent on the population. The meanings of the mutations identified in this study will need to be reaffirmed in other population groups in the future.
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Affiliation(s)
- Jeonghwan Lee
- Department of Internal Medicine, Hallym University Hangang Sacred Heart Hospital, Seoul, Korea
| | - Young Lee
- Veterans Medical Research Institute, Veterans Health Service Medical Center, Seoul, Korea
| | - Boram Park
- Department of Public Health Science, Seoul National University, Seoul, Korea
| | - Sungho Won
- Department of Public Health Science, Seoul National University, Seoul, Korea
- Interdisciplinary Program of Bioinformatics, Seoul National University, Seoul, Korea
- Institute of Health and Environment, Seoul National University, Seoul, Korea
| | - Jin Suk Han
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea
| | - Nam Ju Heo
- Division of Nephrology, Department of Internal Medicine, Healthcare System Gangnam Center, Seoul National University Hospital, Seoul, Korea
- * E-mail:
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5
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Barrett EJ, Liu Z, Khamaisi M, King GL, Klein R, Klein BEK, Hughes TM, Craft S, Freedman BI, Bowden DW, Vinik AI, Casellini CM. Diabetic Microvascular Disease: An Endocrine Society Scientific Statement. J Clin Endocrinol Metab 2017; 102:4343-4410. [PMID: 29126250 PMCID: PMC5718697 DOI: 10.1210/jc.2017-01922] [Citation(s) in RCA: 287] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2017] [Accepted: 08/29/2017] [Indexed: 01/18/2023]
Abstract
Both type 1 and type 2 diabetes adversely affect the microvasculature in multiple organs. Our understanding of the genesis of this injury and of potential interventions to prevent, limit, or reverse injury/dysfunction is continuously evolving. This statement reviews biochemical/cellular pathways involved in facilitating and abrogating microvascular injury. The statement summarizes the types of injury/dysfunction that occur in the three classical diabetes microvascular target tissues, the eye, the kidney, and the peripheral nervous system; the statement also reviews information on the effects of diabetes and insulin resistance on the microvasculature of skin, brain, adipose tissue, and cardiac and skeletal muscle. Despite extensive and intensive research, it is disappointing that microvascular complications of diabetes continue to compromise the quantity and quality of life for patients with diabetes. Hopefully, by understanding and building on current research findings, we will discover new approaches for prevention and treatment that will be effective for future generations.
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Affiliation(s)
- Eugene J. Barrett
- Division of Endocrinology, Department of Medicine, University of Virginia, Charlottesville, Virginia 22908
| | - Zhenqi Liu
- Division of Endocrinology, Department of Medicine, University of Virginia, Charlottesville, Virginia 22908
| | - Mogher Khamaisi
- Section of Vascular Cell Biology, Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts 02215
| | - George L. King
- Section of Vascular Cell Biology, Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts 02215
| | - Ronald Klein
- Department of Ophthalmology and Visual Sciences, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin 53705
| | - Barbara E. K. Klein
- Department of Ophthalmology and Visual Sciences, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin 53705
| | - Timothy M. Hughes
- Sticht Center for Healthy Aging and Alzheimer’s Prevention, Wake Forest School of Medicine, Winston-Salem, North Carolina 27157
| | - Suzanne Craft
- Sticht Center for Healthy Aging and Alzheimer’s Prevention, Wake Forest School of Medicine, Winston-Salem, North Carolina 27157
| | - Barry I. Freedman
- Divisions of Nephrology and Endocrinology, Department of Internal Medicine, Centers for Diabetes Research, and Center for Human Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina 27157
| | - Donald W. Bowden
- Divisions of Nephrology and Endocrinology, Department of Internal Medicine, Centers for Diabetes Research, and Center for Human Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina 27157
| | - Aaron I. Vinik
- EVMS Strelitz Diabetes Center, Eastern Virginia Medical Center, Norfolk, Virginia 23510
| | - Carolina M. Casellini
- EVMS Strelitz Diabetes Center, Eastern Virginia Medical Center, Norfolk, Virginia 23510
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6
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Piras D, Zoledziewska M, Cucca F, Pani A. Genome-Wide Analysis Studies and Chronic Kidney Disease. KIDNEY DISEASES 2017; 3:106-110. [PMID: 29344505 DOI: 10.1159/000481886] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2017] [Accepted: 10/02/2017] [Indexed: 11/19/2022]
Abstract
In recent years, the very high worldwide prevalence of chronic kidney disease (CKD) has led some authors to talk of an "epidemic." The progression of CKD varies considerably among individuals despite similar aetiologies, optimal blood pressure, and glycaemic control. Over the last decade, through genome-wide association studies (GWAS), more than 50 genetic loci have been identified in association with CKD. Understanding the genetic basis of CKD could provide a better knowledge of the biology of the involved pathways, thus potentially leading to novel tools for the diagnosis, prevention, and therapy of CKD. In this review, we will analyse the role of GWAS in the study of CKD.
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Affiliation(s)
- Doloretta Piras
- Divisione di Nefrologia e Dialisi, Azienda Ospedaliera G. Brotzu, Cagliari, Italy
| | | | - Francesco Cucca
- Istituto di Ricerca Genetica e Biomedica (IRGB-CNR), Cagliari, Italy.,Università degli Studi di Sassari, Sassari, Italy
| | - Antonello Pani
- Divisione di Nefrologia e Dialisi, Azienda Ospedaliera G. Brotzu, Cagliari, Italy
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7
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Zhang R, Zhuang L, Li M, Zhang J, Zhao W, Ge X, Chen Y, Wang F, Wang N, Bao Y, Liu L, Liu Y, Jia W. Arg913Gln of SLC12A3 gene promotes development and progression of end-stage renal disease in Chinese type 2 diabetes mellitus. Mol Cell Biochem 2017; 437:203-210. [PMID: 28744814 DOI: 10.1007/s11010-017-3120-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2017] [Accepted: 07/15/2017] [Indexed: 12/01/2022]
Abstract
Whether the Arg913Gln variation (rs11643718, G/A) of SLC12A3 contributes to diabetic nephropathy (DN) remains controversial. We undertook a case-control study to evaluate the association of the SLC12A3-Arg913Gln variation with the risk of end-stage renal disease (ESRD) in Chinese type 2 diabetes mellitus (T2DM) patients undergoing hemodialysis, and analyzed the genotype-phenotype interaction. Unrelated Chinese T2DM patients (n = 372) with diabetic retinopathy were classified into the non-DN (control) group (n = 151; duration of T2DM >15 years, no signs of renal involvement) and the DN-ESRD group (n = 221; ESRD due to T2DM, receiving hemodialysis). Polymerase chain reaction-direct sequencing was used to genotype the SLC12A3-Arg913Gln variation for all participants. The frequency of the GA+AA genotype in the DN-ESRD group was significantly higher than that of the non-DN group (23.1 vs. 9.9%; adjusted OR 2.2 (95% CI 1.3-4.5), P = 0.019). In the non-DN group, GA+AA carriers had a significantly higher urinary albumin excretion rate (UAER) and diastolic blood pressure compared with GG carriers (both P < 0.05). The SLC12A3-Arg913Gln variation may be associated with increased blood pressure and UAER and, therefore, could be used to predict the development and progression of DN-ESRD in Chinese T2DM patients undergoing hemodialysis.
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Affiliation(s)
- Rong Zhang
- Shanghai Key Laboratory of Diabetes, Department of Endocrinology & Metabolism, Shanghai Diabetes Institute, Shanghai Jiaotong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Langen Zhuang
- Department of Endocrinology, The First Affiliated Hospital of Bengbu Medical College, Bengbu, 233004, Anhui, China
| | - Ming Li
- Shanghai Key Laboratory of Diabetes, Department of Endocrinology & Metabolism, Shanghai Diabetes Institute, Shanghai Jiaotong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Juan Zhang
- Shanghai Key Laboratory of Diabetes, Department of Endocrinology & Metabolism, Shanghai Diabetes Institute, Shanghai Jiaotong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Weijing Zhao
- Shanghai Key Laboratory of Diabetes, Department of Endocrinology & Metabolism, Shanghai Diabetes Institute, Shanghai Jiaotong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Xiaoxu Ge
- Shanghai Key Laboratory of Diabetes, Department of Endocrinology & Metabolism, Shanghai Diabetes Institute, Shanghai Jiaotong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Yating Chen
- Shanghai Key Laboratory of Diabetes, Department of Endocrinology & Metabolism, Shanghai Diabetes Institute, Shanghai Jiaotong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Feng Wang
- Department of Nephrology, Shanghai Diabetes Institute, Shanghai Jiaotong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Niansong Wang
- Department of Nephrology, Shanghai Diabetes Institute, Shanghai Jiaotong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Yuqian Bao
- Shanghai Key Laboratory of Diabetes, Department of Endocrinology & Metabolism, Shanghai Diabetes Institute, Shanghai Jiaotong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Limei Liu
- Shanghai Key Laboratory of Diabetes, Department of Endocrinology & Metabolism, Shanghai Diabetes Institute, Shanghai Jiaotong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China.
| | - Yanjun Liu
- Division of Endocrinology, Metabolism, and Molecular Medicine, Charles R. Drew University of Medicine and Sciences, University of California Los Angeles (UCLA) School of Medicine, Los Angeles, CA, USA
| | - Weiping Jia
- Shanghai Key Laboratory of Diabetes, Department of Endocrinology & Metabolism, Shanghai Diabetes Institute, Shanghai Jiaotong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
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8
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Zhu H, Yu W, Xie Y, Zhang H, Bi Y, Zhu D. Association of Pentraxin 3 Gene Polymorphisms with Susceptibility to Diabetic Nephropathy. Med Sci Monit 2017; 23:428-436. [PMID: 28119515 PMCID: PMC5289099 DOI: 10.12659/msm.902783] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Diabetic nephropathy (DN) is a major microvascular complication of diabetes. Pentraxin 3 (PTX3) is a member of the acute-phase reactants superfamily and altered plasma levels of PTX3 are associated with DN. We performed a case-control study to analyze the relationship between single nucleotide polymorphisms (SNPs) in PTX3 and the risk for DN in patients with type 2 diabetes. MATERIAL AND METHODS The study included 135 DN patients, 155 non-diabetic nephropathy (NDN) patients, and 152 normal controls (NC) (N=442). We genotyped eight PTX3 SNPs (rs2305619, rs2120243, rs1456099, rs7634847, rs1840680, rs2316706, rs2316709, and rs7616177) using the ABI PRISM SNapshot method. RESULTS The genotype frequencies of rs2305619 and rs2120243 differed significantly between the DN and the NDN groups (p=0.017 and p=0.033, respectively). Patients with the GG variant of rs2305619 showed 4.078-fold higher susceptibility to DN than those with the AA variant (OR=4.078, 95% CI=1.370-12.135, p=0.012); patients with the AA variant of rs2120243 had a lower risk of developing DN (OR=0.213, 95% CI=0.055-0.826, p=0.025). Haplotype analysis showed an association between the CAGGG haplotype in block 1 with DN (p=0.0319). CONCLUSIONS Our findings suggested that PTX3 polymorphisms were associated with an increased risk for DN in Chinese patients with type 2 diabetes.
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Affiliation(s)
- Hong Zhu
- Department of Endocrinology, Drum Tower Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China (mainland).,Department of Endocrinology and Metabolism, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China (mainland)
| | - Weihui Yu
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China (mainland)
| | - Yuanyuan Xie
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China (mainland)
| | - Hailing Zhang
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China (mainland)
| | - Yan Bi
- Department of Endocrinology, Drum Tower Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China (mainland)
| | - Dalong Zhu
- Department of Endocrinology, Drum Tower Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China (mainland)
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Lu M, Zhang J, Li M, Ge X, Dai X, Zhao J, Fu M, Wang T, Fang X, Li C, Zhang R, Zhao W, Zheng T, Wang F, Yu M, Lei T, Wang N, Bao Y, Liu L, Liu Y, Jia W. The angiotensin-I converting enzyme gene I/D variation contributes to end-stage renal disease risk in Chinese patients with type 2 diabetes receiving hemodialysis. Mol Cell Biochem 2016; 422:181-188. [PMID: 27633502 DOI: 10.1007/s11010-016-2819-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2016] [Accepted: 09/08/2016] [Indexed: 11/26/2022]
Abstract
Whether the DD genotype of the angiotensin-I converting enzyme (ACE) I/D variation contributes to end-stage renal disease (ESRD) risk in type 2 diabetes mellitus (T2DM) remains controversial. Differences in study design, case and control definition, sample size and ethnicity may contribute to the discrepancies reported in association studies. We performed a case-control study to evaluate the association of the ACE I/D variation with ESRD risk in Chinese patients with T2DM receiving hemodialysis and analyzed the genotype-phenotype interaction. Unrelated Chinese patients (n = 432) were classified into the non-diabetic nephropathy (DN) control group (n = 222, duration of diabetes >10 years, no signs of renal involvement) and the DN-ESRD group (n = 210; ESRD due to T2DM, receiving hemodialysis). Polymerase chain reaction was used to genotype ACE I/D for all 432 subjects. The frequencies of the ID + DD genotypes were higher in the DN-ESRD group than non-DN control group (65.2 vs. 50.9 %; adjusted OR 1.98 (95 % CI, 1.31-3.00; P = 0.001). In the DN-ESRD group, the DD genotypic subgroup had significantly elevated HbA1c and diastolic blood pressure (DBP) compared to the II subgroup (both P < 0.05). The DD genotype of the ACE I/D variation may be associated with more elevated blood pressure and HbA1c, and therefore may predict the development, progression and severity of DN-ESRD in Chinese patients with T2DM undergoing hemodialysis.
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Affiliation(s)
- Ming Lu
- Department of Endocrinology & Metabolism, Putuo Hospital Attached to Shanghai University of Traditional Chinese Medicine, 164 Lanxi Road, Shanghai, 200000, China
| | - Jianzhong Zhang
- Department of Endocrinology, China-Japan Union Hospital of Jilin University, 829 Xinmin Street, Changchun, China
| | - Ming Li
- Department of Endocrinology & Metabolism, Shanghai Diabetes Institute, Shanghai Jiaotong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Xiaoxu Ge
- Department of Endocrinology & Metabolism, Shanghai Diabetes Institute, Shanghai Jiaotong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Xu Dai
- Shanghai Jiaotong University School of Medicine, 227 Chongqing South Road, Shanghai, 200025, China
| | - Jiao Zhao
- Shanghai Jiaotong University School of Medicine, 227 Chongqing South Road, Shanghai, 200025, China
| | - Mingzhou Fu
- Shanghai Jiaotong University School of Medicine, 227 Chongqing South Road, Shanghai, 200025, China
| | - Tao Wang
- Shanghai Jiaotong University School of Medicine, 227 Chongqing South Road, Shanghai, 200025, China
| | - Xiyao Fang
- Shanghai Jiaotong University School of Medicine, 227 Chongqing South Road, Shanghai, 200025, China
| | - Can Li
- Department of Endocrinology & Metabolism, Shanghai Diabetes Institute, Shanghai Jiaotong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Rong Zhang
- Department of Endocrinology & Metabolism, Shanghai Diabetes Institute, Shanghai Jiaotong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Weijing Zhao
- Department of Endocrinology & Metabolism, Shanghai Diabetes Institute, Shanghai Jiaotong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Taishan Zheng
- Department of Endocrinology & Metabolism, Shanghai Diabetes Institute, Shanghai Jiaotong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Feng Wang
- Department of Nephrology, Shanghai Diabetes Institute, Shanghai Jiaotong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Ming Yu
- Department of Endocrinology & Metabolism, Putuo Hospital Attached to Shanghai University of Traditional Chinese Medicine, 164 Lanxi Road, Shanghai, 200000, China
| | - Tao Lei
- Department of Endocrinology & Metabolism, Putuo Hospital Attached to Shanghai University of Traditional Chinese Medicine, 164 Lanxi Road, Shanghai, 200000, China
| | - Niansong Wang
- Department of Nephrology, Shanghai Diabetes Institute, Shanghai Jiaotong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Yuqian Bao
- Department of Endocrinology & Metabolism, Shanghai Diabetes Institute, Shanghai Jiaotong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Limei Liu
- Department of Endocrinology & Metabolism, Shanghai Diabetes Institute, Shanghai Jiaotong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China.
| | - Yanjun Liu
- Division of Endocrinology, Metabolism, and Molecular Medicine, Charles R. Drew University of Medicine and Sciences, University of California Los Angeles (UCLA) School of Medicine, Los Angeles, CA, USA
| | - Weiping Jia
- Department of Endocrinology & Metabolism, Shanghai Diabetes Institute, Shanghai Jiaotong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
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10
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Regele F, Jelencsics K, Shiffman D, Paré G, McQueen MJ, Mann JF, Oberbauer R. Genome-wide studies to identify risk factors for kidney disease with a focus on patients with diabetes. Nephrol Dial Transplant 2015. [DOI: 10.1093/ndt/gfv087] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
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11
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Abstract
The global prevalence of diabetic nephropathy is rising in parallel with the increasing incidence of diabetes in most countries. Unfortunately, up to 40 % of persons diagnosed with diabetes may develop kidney complications. Diabetic nephropathy is associated with substantially increased risks of cardiovascular disease and premature mortality. An inherited susceptibility to diabetic nephropathy exists, and progress is being made unravelling the genetic basis for nephropathy thanks to international research collaborations, shared biological resources and new analytical approaches. Multiple epidemiological studies have highlighted the clinical heterogeneity of nephropathy and the need for better phenotyping to help define important subgroups for analysis and increase the power of genetic studies. Collaborative genome-wide association studies for nephropathy have reported unique genes, highlighted novel biological pathways and suggested new disease mechanisms, but progress towards clinically relevant risk prediction models for diabetic nephropathy has been slow. This review summarises the current status, recent developments and ongoing challenges elucidating the genetics of diabetic nephropathy.
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Affiliation(s)
- Amy Jayne McKnight
- Nephrology Research Group, Centre for Public Health, Queen's University Belfast, c/o Regional Genetics Centre, Level A, Tower Block, Belfast City Hospital, Lisburn Road, Belfast, BT9 7AB, UK,
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12
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Song Q, Zhang Y, Wu Y, Zhou F, Qu Y. Association of erythropoietin gene polymorphisms with retinopathy in a Chinese cohort with type 2 diabetes mellitus. Clin Exp Ophthalmol 2015; 43:544-9. [PMID: 25675872 DOI: 10.1111/ceo.12505] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2014] [Accepted: 01/13/2015] [Indexed: 12/18/2022]
Affiliation(s)
- Qi Song
- Operating Room; Qilu Hospital of Shandong University; Jinan China
| | - Yue Zhang
- Department of Geriatrics; Qilu Hospital of Shandong University; Jinan China
| | - Yongzhong Wu
- State Key Lab of Crystal Materials; Shandong University; Jinan China
| | - Fang Zhou
- Department of Geriatrics; Qilu Hospital of Shandong University; Jinan China
| | - Yi Qu
- Department of Geriatrics; Qilu Hospital of Shandong University; Jinan China
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13
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Abstract
The rising global prevalence of diabetes mellitus is accompanied by an increasing burden of morbidity and mortality that is attributable to the complications of chronic hyperglycaemia. These complications include blindness, renal failure and cardiovascular disease. Current therapeutic options for chronic hyperglycaemia reduce, but do not eradicate, the risk of these complications. Success in defining new preventative and therapeutic strategies hinges on an improved understanding of the molecular processes involved in the development of these complications. This Review explores the role of human genetics in delivering such insights, and describes progress in characterizing the sequence variants that influence individual predisposition to diabetic kidney disease, retinopathy, neuropathy and accelerated cardiovascular disease. Numerous risk variants for microvascular complications of diabetes have been reported, but very few have shown robust replication. Furthermore, only limited evidence exists of a difference in the repertoire of risk variants influencing macrovascular disease between those with and those without diabetes. Here, we outline the challenges associated with the genetic analysis of diabetic complications and highlight ongoing efforts to deliver biological insights that can drive translational benefits.
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14
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Parsa A, Fuchsberger C, Köttgen A, O’Seaghdha CM, Pattaro C, de Andrade M, Chasman DI, Teumer A, Endlich K, Olden M, Chen MH, Tin A, Kim YJ, Taliun D, Li M, Feitosa M, Gorski M, Yang Q, Hundertmark C, Foster MC, Glazer N, Isaacs A, Rao M, Smith AV, O’Connell JR, Struchalin M, Tanaka T, Li G, Hwang SJ, Atkinson EJ, Lohman K, Cornelis MC, Johansson Å, Tönjes A, Dehghan A, Couraki V, Holliday EG, Sorice R, Kutalik Z, Lehtimäki T, Esko T, Deshmukh H, Ulivi S, Chu AY, Murgia F, Trompet S, Imboden M, Kollerits B, Pistis G, Harris TB, Launer LJ, Aspelund T, Eiriksdottir G, Mitchell BD, Boerwinkle E, Schmidt H, Hofer E, Hu F, Demirkan A, Oostra BA, Turner ST, Ding J, Andrews JS, Freedman BI, Giulianini F, Koenig W, Illig T, Döring A, Wichmann HE, Zgaga L, Zemunik T, Boban M, Minelli C, Wheeler HE, Igl W, Zaboli G, Wild SH, Wright AF, Campbell H, Ellinghaus D, Nöthlings U, Jacobs G, Biffar R, Ernst F, Homuth G, Kroemer HK, Nauck M, Stracke S, Völker U, Völzke H, Kovacs P, Stumvoll M, Mägi R, Hofman A, Uitterlinden AG, Rivadeneira F, Aulchenko YS, Polasek O, Hastie N, Vitart V, Helmer C, Wang JJ, Stengel B, Ruggiero D, Bergmann S, Kähönen M, Viikari J, Nikopensius T, Province M, Colhoun H, Doney A, Robino A, Krämer BK, Portas L, Ford I, Buckley BM, Adam M, Thun GA, Paulweber B, Haun M, Sala C, Mitchell P, Ciullo M, Vollenweider P, Raitakari O, Metspalu A, Palmer C, Gasparini P, Pirastu M, Jukema JW, Probst-Hensch NM, Kronenberg F, Toniolo D, Gudnason V, Shuldiner AR, Coresh J, Schmidt R, Ferrucci L, van Duijn CM, Borecki I, Kardia SL, Liu Y, Curhan GC, Rudan I, Gyllensten U, Wilson JF, Franke A, Pramstaller PP, Rettig R, Prokopenko I, Witteman J, Hayward C, Ridker PM, Bochud M, Heid IM, Siscovick DS, Fox CS, Kao WL, Böger CA. Common variants in Mendelian kidney disease genes and their association with renal function. J Am Soc Nephrol 2013; 24:2105-17. [PMID: 24029420 PMCID: PMC3839542 DOI: 10.1681/asn.2012100983] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2012] [Accepted: 07/10/2013] [Indexed: 12/28/2022] Open
Abstract
Many common genetic variants identified by genome-wide association studies for complex traits map to genes previously linked to rare inherited Mendelian disorders. A systematic analysis of common single-nucleotide polymorphisms (SNPs) in genes responsible for Mendelian diseases with kidney phenotypes has not been performed. We thus developed a comprehensive database of genes for Mendelian kidney conditions and evaluated the association between common genetic variants within these genes and kidney function in the general population. Using the Online Mendelian Inheritance in Man database, we identified 731 unique disease entries related to specific renal search terms and confirmed a kidney phenotype in 218 of these entries, corresponding to mutations in 258 genes. We interrogated common SNPs (minor allele frequency >5%) within these genes for association with the estimated GFR in 74,354 European-ancestry participants from the CKDGen Consortium. However, the top four candidate SNPs (rs6433115 at LRP2, rs1050700 at TSC1, rs249942 at PALB2, and rs9827843 at ROBO2) did not achieve significance in a stage 2 meta-analysis performed in 56,246 additional independent individuals, indicating that these common SNPs are not associated with estimated GFR. The effect of less common or rare variants in these genes on kidney function in the general population and disease-specific cohorts requires further research.
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Affiliation(s)
- Afshin Parsa
- Division of Nephrology, University of Maryland School of Medicine, Baltimore, Maryland
| | - Christian Fuchsberger
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Anna Köttgen
- Renal Division, Freiburg University Clinic, Freiburg, Germany
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Conall M. O’Seaghdha
- National Heart, Lung, and Blood Institute's Framingham Heart Study and the Center for Population Studies, Framingham, Massachusetts
- Division of Nephrology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Cristian Pattaro
- Centre for Biomedicine, European Academy of Bozen/Bolzano, Bolzano, Italy
| | - Mariza de Andrade
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota
| | - Daniel I. Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Alexander Teumer
- Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
| | - Karlhans Endlich
- Institute of Anatomy and Cell Biology, University of Greifswald, Greifswald, Germany
| | - Matthias Olden
- Division of Nephrology, Department of Internal Medicine II, University Hospital Regensburg, Regensburg, Germany
- Department of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Ming-Huei Chen
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Adrienne Tin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Young J. Kim
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland
- Genomics Resource Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon, Korea
| | - Daniel Taliun
- Centre for Biomedicine, European Academy of Bozen/Bolzano, Bolzano, Italy
| | - Man Li
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Mary Feitosa
- Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri
| | - Mathias Gorski
- Division of Nephrology, Department of Internal Medicine II, University Hospital Regensburg, Regensburg, Germany
- Department of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, University Hospital Regensburg, Regensburg, Germany
| | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | | | - Meredith C. Foster
- National Heart, Lung, and Blood Institute's Framingham Heart Study and the Center for Population Studies, Framingham, Massachusetts
| | - Nicole Glazer
- Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts
| | - Aaron Isaacs
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Centre for Medical Systems Biology, Rotterdam, The Netherlands
| | - Madhumathi Rao
- Division of Nephrology, Tufts Evidence Practice Center, Tufts University School of Medicine, Tufts Medical Center, Boston, Massachusetts
| | - Albert V. Smith
- Research Institute, Icelandic Heart Association, Kopavogur, Iceland
- University of Iceland, Reykjavik, Iceland
| | - Jeffrey R. O’Connell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland
| | - Maksim Struchalin
- Departments of Epidemiology and Biostatistics and Forensic Molecular Biology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Toshiko Tanaka
- Clinical Research Branch, National Institute of Aging, Baltimore Maryland
| | - Guo Li
- University of Washington, Seattle, Washington
| | - Shih-Jen Hwang
- National Heart, Lung, and Blood Institute's Framingham Heart Study and the Center for Population Studies, Framingham, Massachusetts
| | - Elizabeth J. Atkinson
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota
| | - Kurt Lohman
- Department of Epidemiology and Prevention, Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Marilyn C. Cornelis
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts
| | - Åsa Johansson
- Rudbeck Laboratory, Department of Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Anke Tönjes
- Department of Medicine, University of Leipzig, Leipzig, Germany
- Adiposity Diseases Integrated Research and Treatment Center, University of Leipzig, Leipzig, Germany
| | - Abbas Dehghan
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | | | - Elizabeth G. Holliday
- Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, University of Newcastle, Newcastle, Australia
- Centre for Information-Based Medicine, Hunter Medical Research Institute, Newcastle, Australia
| | - Rossella Sorice
- Adriano-Buzzati Traverso-CNR Institute of Genetics and Biophysics, Naples, Italy
| | - Zoltan Kutalik
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Terho Lehtimäki
- Fimlab Laboratories, Department of Clinical Chemistry, School of Medicine, University of Tampere, Tampere, Finland
| | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Institute of Molecular and Cell Biology, Estonian Biocentre, University of Tartu, Tartu, Estonia
| | - Harshal Deshmukh
- Wellcome Trust Centre for Molecular Medicine, Clinical Research Centre, University of Dundee, Ninewells Hospital, Dundee, United Kingdom
| | - Sheila Ulivi
- IRCCS Burlo Garofolo Institute for Maternal and Child Health, University of Trieste, Trieste, Italy
| | - Audrey Y. Chu
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | | | - Stella Trompet
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Medea Imboden
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Barbara Kollerits
- Division of Genetic Epidemiology, Innsbruck Medical University, Innsbruck, Austria
| | - Giorgio Pistis
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milan, Italy
| | - Tamara B. Harris
- Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, Bethesda, Maryland
| | - Lenore J. Launer
- Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, Bethesda, Maryland
| | - Thor Aspelund
- Research Institute, Icelandic Heart Association, Kopavogur, Iceland
- University of Iceland, Reykjavik, Iceland
| | | | - Braxton D. Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland
| | - Eric Boerwinkle
- Human Genetics Center, University of Texas Health Science Center, Houston, Texas
| | - Helena Schmidt
- Austrian Stroke Prevention Study, Department of Neurology, Institute of Molecular Biology and Biochemistry, Medical University of Graz, Graz, Austria
| | - Edith Hofer
- Austrian Stroke Prevention Study, Clinical Division of Neurogeriatrics, Department of Neurology, University Clinic of Neurology, Medical University of Graz, Graz, Austria
| | - Frank Hu
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts
| | - Ayse Demirkan
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Ben A. Oostra
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Clinical Genetics, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Stephen T. Turner
- Division of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota
| | - Jingzhong Ding
- Division of Geriatrics, Department of Internal Medicine, Wake Forest School of Medicine, Wake Forest University, Winston-Salem, North Carolina
| | - Jeanette S. Andrews
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Wake Forest University, Winston-Salem, North Carolina
| | - Barry I. Freedman
- Division of Nephrology, Department of Internal Medicine, Wake Forest School of Medicine, Wake Forest University, Winston-Salem, North Carolina
| | - Franco Giulianini
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - Wolfgang Koenig
- Department of Internal Medicine II, Ulm University Clinic, University of Ulm, Ulm, Germany
| | - Thomas Illig
- Hanover Unified Biobank, Hanover Medical School, Hanover, Germany
- Research Unit of Molecular Epidemiology, German Research Center for Environmental Health, Neuherberg, Germany
| | - Angela Döring
- Institute of Epidemiology I and II, German Research Center for Environmental Health, Neuherberg, Germany
| | - H.-Erich Wichmann
- Institute of Epidemiology I and II, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Informatics, Biometry, and Epidemiology, Ludwig-Maximilians-University, Munich, Germany
- Grosshadern Clinic, Neuherberg, Germany
| | - Lina Zgaga
- Center for Population Health Sciences, University of Edinburgh Medical School, Edinburgh, Scotland, United Kingdom
| | - Tatijana Zemunik
- Croatian Centre for Global Health, University of Split Medical School, Split, Croatia
| | - Mladen Boban
- Croatian Centre for Global Health, University of Split Medical School, Split, Croatia
| | - Cosetta Minelli
- Centre for Biomedicine, European Academy of Bozen/Bolzano, Bolzano, Italy
| | - Heather E. Wheeler
- Department of Genetics, Stanford University, Stanford, California
- Department of Medicine, University of Chicago, Chicago, Illinois
| | - Wilmar Igl
- Rudbeck Laboratory, Department of Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Ghazal Zaboli
- Rudbeck Laboratory, Department of Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Sarah H. Wild
- Center for Population Health Sciences, University of Edinburgh Medical School, Edinburgh, Scotland, United Kingdom
| | - Alan F. Wright
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, United Kingdom
| | - Harry Campbell
- Center for Population Health Sciences, University of Edinburgh Medical School, Edinburgh, Scotland, United Kingdom
| | - David Ellinghaus
- Institute of Clinical Molecular Biology, Christian-Albrechts University, Kiel, Germany
| | - Ute Nöthlings
- PopGen Biobank, Schleswig-Holstein University Hospital, Kiel, Germany
- Institute for Epidemiology, University of Kiel, Kiel, Germany
- Department of Nutrition and Food Sciences, University of Bonn, Bonn, Germany
| | - Gunnar Jacobs
- PopGen Biobank, Schleswig-Holstein University Hospital, Kiel, Germany
- Institute for Epidemiology, University of Kiel, Kiel, Germany
| | - Reiner Biffar
- Clinic for Prosthodontic Dentistry, Gerostomatology, and Material Science, University of Greifswald, Greifswald, Germany
| | - Florian Ernst
- Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
| | - Heyo K. Kroemer
- Institute of Pharmacology, University of Greifswald, Greifswald, Germany
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University of Greifswald, Greifswald, Germany
| | - Sylvia Stracke
- Clinic for Internal Medicine A, University of Greifswald, Greifswald, Germany
| | - Uwe Völker
- Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
| | - Henry Völzke
- Institute for Community Medicine, University of Greifswald, Greifswald, Germany
| | - Peter Kovacs
- Department of Medicine, University of Leipzig, Leipzig, Germany
| | - Michael Stumvoll
- Department of Medicine, University of Leipzig, Leipzig, Germany
- Adiposity Diseases Integrated Research and Treatment Center, University of Leipzig, Leipzig, Germany
| | - Reedik Mägi
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | | | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Yurii S. Aulchenko
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Ozren Polasek
- Croatian Centre for Global Health, University of Split Medical School, Split, Croatia
| | - Nick Hastie
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, United Kingdom
| | - Veronique Vitart
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, United Kingdom
| | - Catherine Helmer
- INSERM U897, Institute of Public Health, Victor Segalen Bordeaux II University, Bordeaux, France
- Victor Segalen Bordeaux II University, Bordeaux, France
| | - Jie Jin Wang
- Centre for Vision Research, Westmead Millennium Institute, Westmead Hospital, University of Sydney, Sydney, Australia
- Centre for Eye Research Australia, University of Melbourne, East Melbourne, Australia
| | - Bénédicte Stengel
- INSERM UMRS 1018, Villejuif, France
- UMRS 1018, University of Paris-Sud, Paris, France
| | - Daniela Ruggiero
- Adriano-Buzzati Traverso-CNR Institute of Genetics and Biophysics, Naples, Italy
| | - Sven Bergmann
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, School of Medicine, University of Tampere, Tampere, Finland
| | - Jorma Viikari
- Department of Medicine, Turku University Hospital, University of Turku, Turku, Finland
| | - Tiit Nikopensius
- Institute of Molecular and Cell Biology, Estonian Biocentre, University of Tartu, Tartu, Estonia
| | - Michael Province
- Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri
| | - Helen Colhoun
- Wellcome Trust Centre for Molecular Medicine, Clinical Research Centre, University of Dundee, Ninewells Hospital, Dundee, United Kingdom
| | - Alex Doney
- National Health Service Tayside, Wellcome Trust Centre for Molecular Medicine, Clinical Research Centre, Ninewells Hospital, Dundee, United Kingdom
| | - Antonietta Robino
- IRCCS Burlo Garofolo Institute for Maternal and Child Health, University of Trieste, Trieste, Italy
| | - Bernhard K. Krämer
- Fifth Department of Medicine, Mannheim University Medical Centre, Mannheim, Germany
| | - Laura Portas
- CNR Institute of Population Genetics, Sassari, Italy
| | - Ian Ford
- Robertson Centre for Biostatistics, University of Glasgow, Glasgow, United Kingdom
| | - Brendan M. Buckley
- Department of Pharmacology and Therapeutics, University College Cork, Cork, Ireland
| | - Martin Adam
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Gian-Andri Thun
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Bernhard Paulweber
- First Department of Internal Medicine, Paracelsus Medical University, Salzburg, Austria
| | - Margot Haun
- Division of Genetic Epidemiology, Innsbruck Medical University, Innsbruck, Austria
| | - Cinzia Sala
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milan, Italy
| | - Paul Mitchell
- Centre for Vision Research, Westmead Millennium Institute, Westmead Hospital, University of Sydney, Sydney, Australia
| | - Marina Ciullo
- Adriano-Buzzati Traverso-CNR Institute of Genetics and Biophysics, Naples, Italy
| | - Peter Vollenweider
- Department of Internal Medicine, Vaudois University Hospital Center, University of Lausanne, Lausanne, Switzerland
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Institute of Molecular and Cell Biology, Estonian Biocentre, University of Tartu, Tartu, Estonia
| | - Colin Palmer
- Biomedical Research Institute, University of Dundee, Ninewells Hospital and Medical School, Dundee, United Kingdom
| | - Paolo Gasparini
- IRCCS Burlo Garofolo Institute for Maternal and Child Health, University of Trieste, Trieste, Italy
| | - Mario Pirastu
- CNR Institute of Population Genetics, Sassari, Italy
| | - J. Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Interuniversity Cardiology Institute of the Netherlands, Utrecht, The Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden, The Netherlands
- Durrer Center for Cardiogenetic Research, Amsterdam, The Netherlands
| | - Nicole M. Probst-Hensch
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Florian Kronenberg
- Division of Genetic Epidemiology, Innsbruck Medical University, Innsbruck, Austria
| | - Daniela Toniolo
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milan, Italy
- CNR Institute of Molecular Genetics, Pavia, Italy
| | - Vilmundur Gudnason
- Research Institute, Icelandic Heart Association, Kopavogur, Iceland
- University of Iceland, Reykjavik, Iceland
| | - Alan R. Shuldiner
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland
- Geriatric Research and Education Clinical Center, Veterans Affairs Medical Center, Baltimore, Maryland
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Welch Center for Prevention, Epidemiology, and Clinical Research, Baltimore, Maryland
| | - Reinhold Schmidt
- Austrian Stroke Prevention Study, Clinical Division of Neurogeriatrics, Department of Neurology, University Clinic of Neurology, Medical University of Graz, Graz, Austria
| | - Luigi Ferrucci
- Clinical Research Branch, National Institute of Aging, Baltimore Maryland
| | - Cornelia M. van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Centre for Medical Systems Biology, Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Aging, Netherlands Genomics Initiative, Leiden, the Netherlands
| | - Ingrid Borecki
- Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri
| | - Sharon L.R. Kardia
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan
| | - Yongmei Liu
- Department of Epidemiology and Prevention, Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Gary C. Curhan
- Channing Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Igor Rudan
- Center for Population Health Sciences, University of Edinburgh Medical School, Edinburgh, Scotland, United Kingdom
| | - Ulf Gyllensten
- Rudbeck Laboratory, Department of Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - James F. Wilson
- Center for Population Health Sciences, University of Edinburgh Medical School, Edinburgh, Scotland, United Kingdom
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts University, Kiel, Germany
| | | | - Rainer Rettig
- Institute of Physiology, University of Greifswald, Karlsburg, Germany
| | - Inga Prokopenko
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Diabetes, Endocrinology, and Metabolism, University of Oxford, Oxford, United Kingdom
| | - Jacqueline Witteman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, United Kingdom
| | - Paul M. Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Murielle Bochud
- University Institute of Social and Preventive Medicine, Vaudois University Hospital Center, University of Lausanne, Lausanne, Switzerland
| | - Iris M. Heid
- Department of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany; and
| | | | - Caroline S. Fox
- National Heart, Lung, and Blood Institute's Framingham Heart Study and the Center for Population Studies, Framingham, Massachusetts
- Division of Endocrinology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - W. Linda Kao
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Welch Center for Prevention, Epidemiology, and Clinical Research, Baltimore, Maryland
| | - Carsten A. Böger
- Division of Nephrology, Department of Internal Medicine II, University Hospital Regensburg, Regensburg, Germany
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15
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Rao M. Cardiovascular and Kidney Disease Traits—Pleiotropic or Just Polygenic? Am J Kidney Dis 2013; 61:851-4. [DOI: 10.1053/j.ajkd.2013.03.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2013] [Accepted: 03/13/2013] [Indexed: 11/11/2022]
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16
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Pezzolesi MG, Jeong J, Smiles AM, Skupien J, Mychaleckyj JC, Rich SS, Warram JH, Krolewski AS. Family-based association analysis confirms the role of the chromosome 9q21.32 locus in the susceptibility of diabetic nephropathy. PLoS One 2013; 8:e60301. [PMID: 23555951 PMCID: PMC3612041 DOI: 10.1371/journal.pone.0060301] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2012] [Accepted: 02/25/2013] [Indexed: 12/15/2022] Open
Abstract
A genome-wide association scan of type 1 diabetic patients from the GoKinD collections previously identified four novel diabetic nephropathy susceptibility loci that have subsequently been shown to be associated with diabetic nephropathy in unrelated patients with type 2 diabetes. To expand these findings, we examined whether single nucleotide polymorphisms (SNPs) at these susceptibility loci were associated with diabetic nephropathy in patients from the Joslin Study of Genetics of Nephropathy in Type 2 Diabetes Family Collection. Six SNPs across the four loci identified in the GoKinD collections and 7 haplotype tagging SNPs, were genotyped in 66 extended families of European ancestry. Pedigrees from this collection contained an average of 18.5 members, including 2 to 14 members with type 2 diabetes. Among diabetic family members, the 9q21.32 locus approached statistical significance with advanced diabetic nephropathy (P = 0.037 [adjusted P = 0.222]). When we expanded our definition of diabetic nephropathy to include individuals with high microalbuminuria, the strength of this association improved significantly (P = 1.42×10−3 [adjusted P = 0.009]). This same locus also trended toward statistical significance with variation in urinary albumin excretion in family members with type 2 diabetes (P = 0.032 [adjusted P = 0.192]) and in analyses expanded to include all relatives (P = 0.019 [adjusted P = 0.114]). These data increase support that SNPs identified in the GoKinD collections on chromosome 9q21.32 are true diabetic nephropathy susceptibility loci.
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17
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Dörhöfer L, Lammert A, Krane V, Gorski M, Banas B, Wanner C, Krämer BK, Heid IM, Böger CA. Study design of DIACORE (DIAbetes COhoRtE) - a cohort study of patients with diabetes mellitus type 2. BMC MEDICAL GENETICS 2013; 14:25. [PMID: 23409726 PMCID: PMC3577512 DOI: 10.1186/1471-2350-14-25] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 09/29/2012] [Accepted: 01/25/2013] [Indexed: 01/13/2023]
Abstract
Background Diabetes mellitus type 2 (DM2) is highly associated with increased risk for chronic kidney disease (CKD), end stage renal disease (ESRD) and cardiovascular morbidity. Epidemiological and genetic studies generate hypotheses for innovative strategies in DM2 management by unravelling novel mechanisms of diabetes complications, which is essential for future intervention trials. We have thus initiated the DIAbetes COhoRtE study (DIACORE). Methods DIACORE is a prospective cohort study aiming to recruit 6000 patients of self-reported Caucasian ethnicity with prevalent DM2 for at least 10 years of follow-up. Study visits are performed in University-based recruiting clinics in Germany using standard operating procedures. All prevalent DM2 patients in outpatient clinics surrounding the recruiting centers are invited to participate. At baseline and at each 2-year follow-up examination, patients are subjected to a core phenotyping protocol. This includes a standardized online questionnaire and physical examination to determine incident micro- and macrovascular DM2 complications, malignancy and hospitalization, with a primary focus on renal events. Confirmatory outcome information is requested from patient records. Blood samples are obtained for a centrally analyzed standard laboratory panel and for biobanking of aliquots of serum, plasma, urine, mRNA and DNA for future scientific use. A subset of the cohort is subjected to extended phenotyping, e.g. sleep apnea screening, skin autofluorescence measurement, non-mydriatic retinal photography and non-invasive determination of arterial stiffness. Discussion DIACORE will enable the prospective evaluation of factors involved in DM2 complication pathogenesis using high-throughput technologies in biosamples and genetic epidemiological studies.
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Affiliation(s)
- Lena Dörhöfer
- Department of Internal Medicine II, Nephrology, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93042, Regensburg, Germany
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18
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Abu Seman N, Witasp A, Wan Mohamud WN, Anderstam B, Brismar K, Stenvinkel P, Gu HF. Evaluation of the association of plasma pentraxin 3 levels with type 2 diabetes and diabetic nephropathy in a Malay population. J Diabetes Res 2013; 2013:298019. [PMID: 24350299 PMCID: PMC3854091 DOI: 10.1155/2013/298019] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2013] [Revised: 09/25/2013] [Accepted: 09/27/2013] [Indexed: 11/17/2022] Open
Abstract
Recent reports have demonstrated that elevated plasma long pentraxin 3 (PTX3) levels are associated with cardiovascular and chronic kidney diseases. In the current study, we investigated the plasma PTX3 levels in 296 Malay subjects including the subjects with normal glucose tolerance (NGT) and type 2 diabetes (T2DM) patients with or without DN by using an enzyme-linked immune-sorbent assay. Results showed that in males, plasma PTX3 levels in T2DM patients without DN were lower than that in the subjects with NGT (2.78 versus 3.98 ng/mL; P = 0.021). Plasma PTX3 levels in T2DM patients with DN were decreased compared to the patients without DN (1.63 versus 2.78 ng/mL; P = 0.013). In females, however, no significant alteration of plasma PTX3 levels among NGT subjects and T2DM patients with and without DN was detected. Furthermore, an inverse correlation between PTX3 and body mass index was found in male subjects with NGT (P = 0.012; r = -0.390), but not in male T2DM patients, neither in all females. The current study provided the first evidence that decreased plasma PTX3 levels are associated with T2DM and DN in Malay men and also suggested that PTX3 may have different effects in DN and chronic kidney diseases.
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Affiliation(s)
- Norhashimah Abu Seman
- Rolf Luft Research Center for Diabetes and Endocrinology, Department of Molecular Medicine and Surgery, Karolinska University Hospital, Solna, Karolinska Institutet, SE-17176 Stockholm, Sweden
- Cardiovascular, Diabetes and Nutrition Research Centre, Institute for Medical Research, Jalan Pahang, 50588 Kuala Lumpur, Malaysia
- *Norhashimah Abu Seman: and
| | - Anna Witasp
- Center for Molecular Medicine, Karolinska Institutet, SE-17176 Stockholm, Sweden
- Division of Renal Medicine, Department of Clinical Science, Intervention and Technology, Karolinska University Hospital, Huddinge, Karolinska Institutet, SE-14157 Stockholm, Sweden
| | - Wan Nazaimoon Wan Mohamud
- Cardiovascular, Diabetes and Nutrition Research Centre, Institute for Medical Research, Jalan Pahang, 50588 Kuala Lumpur, Malaysia
| | - Björn Anderstam
- Division of Renal Medicine, Department of Clinical Science, Intervention and Technology, Karolinska University Hospital, Huddinge, Karolinska Institutet, SE-14157 Stockholm, Sweden
| | - Kerstin Brismar
- Rolf Luft Research Center for Diabetes and Endocrinology, Department of Molecular Medicine and Surgery, Karolinska University Hospital, Solna, Karolinska Institutet, SE-17176 Stockholm, Sweden
| | - Peter Stenvinkel
- Division of Renal Medicine, Department of Clinical Science, Intervention and Technology, Karolinska University Hospital, Huddinge, Karolinska Institutet, SE-14157 Stockholm, Sweden
| | - Harvest F. Gu
- Rolf Luft Research Center for Diabetes and Endocrinology, Department of Molecular Medicine and Surgery, Karolinska University Hospital, Solna, Karolinska Institutet, SE-17176 Stockholm, Sweden
- *Harvest F. Gu:
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19
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Abstract
For more than 20 years, evidence in favor of a genetic basis for the susceptibility of DN in T2D has provided a foundation for studies aimed at identifying the causal genes responsible for its development. During this period, strategies used to map genes for DN have been driven by our understanding of variation across our genome and the technologies available to interrogate it; as both have evolved, so to have our approaches. The advent of next-generation sequencing technology and increased interest in the search for rare variants has begun to swing the pendulum of these efforts away from population-based studies and back to studies of pedigrees. As the field moves forward, family based approaches should greatly facilitate efforts to identify variants in genes that have a major affect on the risk of DN in T2D. To be successful, the ascertainment and comprehensive study of families with multiple affected members is critical.
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Affiliation(s)
- Marcus G Pezzolesi
- Section on Genetics and Epidemiology, Research Division, Joslin Diabetes Center, Boston, MA 02215, USA.
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20
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Affiliation(s)
- Carsten A Böger
- Department of Internal Medicine II, Nephrology, University Medical Center Regensburg, Regensburg, Germany.
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21
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Schulz A, Kreutz R. Mapping genetic determinants of kidney damage in rat models. Hypertens Res 2012; 35:675-94. [DOI: 10.1038/hr.2012.77] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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22
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El-Bab MF, Shawky N, Al-Sisi A, Akhtar M. Retinopathy and risk factors in diabetic patients from Al-Madinah Al-Munawarah in the Kingdom of Saudi Arabia. Clin Ophthalmol 2012; 6:269-76. [PMID: 22368446 PMCID: PMC3284208 DOI: 10.2147/opth.s27363] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Background Diabetes mellitus is accompanied by chronic and dangerous microvascular changes affecting most body systems, especially the eye, leading to diabetic retinopathy. Diabetic retinopathy without appropriate management is emerging as one of the leading causes of blindness. Therefore, it is necessary to improve the early diagnosis of diabetic retinopathy, reduce the risk of blindness, and identify relevant risk factors. Methods This descriptive study was designed to estimate the prevalence of retinopathy and its staging in diabetic patients attending the diabetes clinic at King Fahd Hospital in Al-Madinah Al-Munawarah, Kingdom of Saudi Arabia, from 2008 to 2010. Patients completed a questionnaire, underwent a full medical assessment carried out by the treating clinicians, and were examined for evidence of diabetic retinopathy using standard ophthalmic outpatient instruments. Results In total, 690 randomly selected diabetic patients of mean age 46.10 ± 11.85 (range 16–88) years were included, comprising 395 men (57.2%) of mean age 46.50 ± 11.31 years and 295 women (42.8%) of mean age 45.55 ± 12.53 years. The mean duration of diabetes mellitus was 11.91 ± 7.92 years in the women and 14.42 ± 8.20 years in the men, and the mean total duration of known diabetes mellitus was 13.35 ± 8.17 years. Glycated hemoglobin was higher in men (8.53% ± 1.81%) than in women (7.73% ± 1.84%), and this difference was statistically significant (P ≤ 0.0001). Of the 690 diabetic patients, 249 (36.1%) had retinopathy. Mild nonproliferative diabetic retinopathy was present in 13.6% of patients, being of moderate grade in 8% and of severe grade in 8.1%. A further 6.4% had proliferative diabetic retinopathy. Conclusion Regular screening to detect diabetic retinopathy is strongly recommended because early detection has the best chance of preventing retinal complications.
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Affiliation(s)
- Mohamed F El-Bab
- Department of Physiology, Faculty of Medicine, Suez Canal University, Ismailia
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23
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Friedman DJ, Pollak MR. Genetics of kidney failure and the evolving story of APOL1. J Clin Invest 2011; 121:3367-74. [PMID: 21881214 DOI: 10.1172/jci46263] [Citation(s) in RCA: 93] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
Chronic kidney disease (CKD) results from a wide array of processes that impair the kidney's ability to perform its major functions. As many as 20 million Americans suffer from CKD and nearly a half million from end-stage renal disease, but there are also examples of centenarians with adequate renal function. Family-based and genome-wide studies suggest that genetic differences substantially influence an individual's lifetime risk for kidney disease. One emerging theme is that evolution of genes related to host defense against pathogens may limit kidney longevity. The identification of these genetic factors will be critical for expanding our understanding of renal development and function as well as for the design of novel therapeutics for kidney disease.
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Affiliation(s)
- David J Friedman
- Nephrology Division, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts 02115, USA.
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24
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Böger CA, Heid IM. Chronic kidney disease: novel insights from genome-wide association studies. Kidney Blood Press Res 2011; 34:225-34. [PMID: 21691125 DOI: 10.1159/000326901] [Citation(s) in RCA: 65] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Chronic kidney disease (CKD) is common, affecting about 10% of the general population, and causing significant morbidity and mortality. Apart from the risk conferred by traditional cardiovascular risk factors, there is a strong genetic component. The method of a genome-wide association study (GWAS) is a powerful hypothesis-free approach to unravel this component by association analyses of CKD with several million genetic variants distributed across the genome. Since the publication of the first GWAS in 2005, this method has led to the discovery of novel loci for numerous human common diseases and phenotypes. Here, we review the recent successes of meta-analyses of GWAS on renal phenotypes. UMOD, SHROOM3, STC1, LASS2, GCKR, ALMS1, TFDP2, DAB2, SLC34A1, VEGFA, PRKAG2, PIP5K1B, ATXN2/SH2B3, DACH1, UBE2Q2, and SLC7A9 were uncovered as loci associated with estimated glomerular filtration rate (eGFR) and CKD, and CUBN as a locus for albuminuria in cross-sectional data of general population studies. However, less than 1.5% of the total variance of eGFR and albuminuria is explained by the identified variants, and the relative risk for CKD is modified by at most 20% per locus. In African Americans, much of the risk for end-stage nondiabetic kidney disease is explained by common variants in the MYH9/APOL1 locus, and in individuals of European descent, variants in HLA-DQA1 and PLA(2)R1 implicate most of the risk for idiopathic membranous nephropathy. In contrast, genetic findings in the analysis of diabetic nephropathy are inconsistent. Uncovering variants explaining more of the genetically determined variability of kidney function is hampered by the multifactorial nature of CKD and different mechanisms involved in progressive CKD stages, and by the challenges in elucidating the role of low-frequency variants. Meta-analyses with larger sample sizes and analyses of longitudinal renal phenotypes using higher-resolution genotyping data are required to uncover novel loci associated with severe renal phenotypes.
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Affiliation(s)
- Carsten A Böger
- Department of Internal Medicine II, University Hospital Regensburg, Regensburg, Germany.
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De Cosmo S, Prudente S, Lamacchia O, Lapice E, Morini E, Di Paola R, Copetti M, Ruggenenti P, Remuzzi G, Vaccaro O, Cignarelli M, Trischitta V. PPARγ2 P12A polymorphism and albuminuria in patients with type 2 diabetes: a meta-analysis of case-control studies. Nephrol Dial Transplant 2011; 26:4011-6. [PMID: 21493814 DOI: 10.1093/ndt/gfr187] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Insulin resistance has a role in diabetic nephropathy. The A12 variant of the PPARγ2 P121A polymorphism has been firmly associated with reduced risk of insulin resistance, while its role on the risk of albuminuria in patients with type 2 diabetes is uncertain. This study investigated whether the PPARγ2 P12A polymorphism modulates the risk of albuminuria in these patients. METHODS We tested the association between the A12 variant and albuminuria in three new case-control studies in diabetic patients from Italy (n = 841, n = 623 and n = 714 patients, respectively) and then performed a meta-analysis of all studies available to date. The nine studies we meta-analysed (six previously published and three presented here) comprised a total of 2376 cases and 4188 controls. RESULTS In none of the three new studies was a significant association observed with odds ratio (OR) [95% confidence intervals (95% CI)] being 1.115, 0.799 and 0.849 (P = 0.603, 0.358 and 0.518, respectively). At meta-analysis, the overall OR (95% CI) for association between A12 and albuminuria was 0.694 (0.528-0.912). A significant heterogeneity of the genetic effect was observed (P = 0.026), which was totally explained by the different method of urine collection and albuminuria definition utilized across the studies. In fact, most of the effect was observed in the four studies determining albumin excretion rate rather than in those using albumin concentration in a single spot (OR, 95% CI: 0.529, 0.397-0.706, P = 0.0000164 and 0.919, 0.733-1.153, P = 0.47, respectively). CONCLUSION The present study shows that the PPARγ2 Ala12 variant is significantly associated with a reduced risk of albuminuria among patients with type 2 diabetes.
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Affiliation(s)
- Salvatore De Cosmo
- Department of Cardiovascular, Endocrine and Metabolic Diseases, IRCCS Casa Sollievo della Sofferenza,San Giovanni Rotondo, Italy.
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An intergenic region on chromosome 13q33.3 is associated with the susceptibility to kidney disease in type 1 and 2 diabetes. Kidney Int 2011; 80:105-11. [PMID: 21412220 DOI: 10.1038/ki.2011.64] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
A genome-wide association scan of the Genetics of Kidneys in Diabetes (GoKinD) collections identified four novel susceptibility loci, located on chromosomes 7p14.3, 9q21.32, 11p15.4, and 13q33.3 associated with type 1 diabetic nephropathy. A recent evaluation of these loci in Japanese patients with type 2 diabetes supported an association at the 13q33.3 locus. To follow up these findings, we determined whether single-nucleotide polymorphisms (SNPs) at these same four loci were associated with diabetic nephropathy in the Joslin Study of Genetics of Nephropathy in Type 2 Diabetes collection. A total of 6 SNPs across these loci were genotyped in 646 normoalbuminuric controls and in 743 nephropathy patients of European ancestry. A significant association was identified at the 13q33.3 locus (rs9521445: P = 4.4 × 10(-3)). At this same locus, rs1411766 was also significantly associated with type 2 diabetic nephropathy (P = 0.03). Meta-analysis of these data with those of the Japanese and GoKinD collections significantly improved the strength of the association (P = 9.7 × 10(-9)). In addition, there was a significant association at the 11p15.4 locus (rs451041: P = 0.02). Thus, associations identified in the GoKinD collections on chromosomes 11p15.4 (near the CARS gene) and 13q33.3 (within an intergenic region between MYO16 and IRS2) are susceptibility loci of kidney disease common to both type 1 and 2 diabetes.
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Santos KG, Crispim D, Canani LH, Ferrugem PT, Gross JL, Roisenberg I. Association of eNOS gene polymorphisms with renal disease in Caucasians with type 2 diabetes. Diabetes Res Clin Pract 2011; 91:353-62. [PMID: 21255858 DOI: 10.1016/j.diabres.2010.12.029] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2010] [Revised: 12/12/2010] [Accepted: 12/21/2010] [Indexed: 11/26/2022]
Abstract
AIM In this study we investigated if the -786T>C, the VNTR intron 4 a/b and the 894G>T (Glu298Asp) polymorphisms in the eNOS gene were associated with renal disease in 617 type 2 diabetic Caucasian-Brazilians. These polymorphisms were also examined in 100 Caucasian healthy blood donors. METHODS Genotyping of eNOS polymorphisms was performed by PCR or PCR-RFLP and haplotype frequencies were estimated using a Bayesian method. Logistic regression analysis was done to test for association of eNOS polymorphisms with susceptibility to renal involvement (microalbuminuria, macroalbuminuria or end-stage renal disease). This analysis was carried out assuming three different genetic models for the minor allele, adjusting for possible effect modifiers. RESULTS Genotype and allele frequencies in patients with renal disease were not significantly different from those of patients with normoalbuminuria and healthy blood donors for all eNOS polymorphisms. Likewise, there were no differences in haplotype frequencies among healthy blood donors and type 2 diabetic patients with or without renal involvement (P>0.05 for all comparisons). CONCLUSION No associations between the -786T>C, the VNTR intron 4 a/b and the 894G>T (Glu298Asp) polymorphisms in the eNOS gene and renal disease were observed in type 2 diabetic Caucasian-Brazilians.
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Affiliation(s)
- Kátia G Santos
- Research Center in Medical Sciences, Universidade Luterana do Brazil, Canoas, Brazil.
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Mooyaart AL, Valk EJJ, van Es LA, Bruijn JA, de Heer E, Freedman BI, Dekkers OM, Baelde HJ. Genetic associations in diabetic nephropathy: a meta-analysis. Diabetologia 2011; 54:544-53. [PMID: 21127830 PMCID: PMC3034040 DOI: 10.1007/s00125-010-1996-1] [Citation(s) in RCA: 170] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2010] [Accepted: 10/26/2010] [Indexed: 12/13/2022]
Abstract
AIMS/HYPOTHESIS This meta-analysis assessed the pooled effect of each genetic variant reproducibly associated with diabetic nephropathy. METHODS PubMed, EMBASE and Web of Science were searched for articles assessing the association between genes and diabetic nephropathy. All genetic variants statistically associated with diabetic nephropathy in an initial study, then independently reproduced in at least one additional study, were selected. Subsequently, all studies assessing these variants were included. The association between these variants and diabetic nephropathy (defined as macroalbuminuria/proteinuria or end-stage renal disease [ESRD]) was calculated at the allele level and the main measure of effect was a pooled odds ratio. Pre-specified subgroup analyses were performed, stratifying for type 1/type 2 diabetes mellitus, proteinuria/ESRD and ethnic group. RESULTS The literature search yielded 3,455 citations, of which 671 were genetic association studies investigating diabetic nephropathy. We identified 34 replicated genetic variants. Of these, 21 remained significantly associated with diabetic nephropathy in a random-effects meta-analysis. These variants were in or near the following genes: ACE, AKR1B1 (two variants), APOC1, APOE, EPO, NOS3 (two variants), HSPG2, VEGFA, FRMD3 (two variants), CARS (two variants), UNC13B, CPVL and CHN2, and GREM1, plus four variants not near genes. The odds ratios of associated genetic variants ranged from 0.48 to 1.70. Additional variants were detected in subgroup analyses: ELMO1 (Asians), CCR5 (Asians) and CNDP1 (type 2 diabetes). CONCLUSIONS/INTERPRETATION This meta-analysis found 24 genetic variants associated with diabetic nephropathy. The relative contribution and relevance of the identified genes in the pathogenesis of diabetic nephropathy should be the focus of future studies.
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Affiliation(s)
- A L Mooyaart
- Department of Pathology, Bldg.1, L1-Q, Leiden University Medical Center, PO Box 9600, 2300 RC, Leiden, the Netherlands.
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Hanson RL, Millis MP, Young NJ, Kobes S, Nelson RG, Knowler WC, DiStefano JK. ELMO1 variants and susceptibility to diabetic nephropathy in American Indians. Mol Genet Metab 2010; 101:383-90. [PMID: 20826100 PMCID: PMC6542634 DOI: 10.1016/j.ymgme.2010.08.014] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2010] [Revised: 08/12/2010] [Accepted: 08/12/2010] [Indexed: 11/27/2022]
Abstract
Variants in the engulfment and cell motility 1 gene, ELMO1, have previously been associated with kidney disease attributed to type 2 diabetes. The Pima Indians of Arizona have high rates of diabetic nephropathy, which is strongly dependent on genetic determinants; thus, we sought to investigate the role of ELMO1 polymorphisms in mediating susceptibility to this disease in this population. Genotype distributions were compared among 141 individuals with nephropathy and 416 individuals without heavy proteinuria in a family study of 257 sibships, and 107 cases with diabetic ESRD and 108 controls with long duration diabetes and no nephropathy. We sequenced 17.4 kb of ELMO1 and identified 19 variants. We genotyped 12 markers, excluding those in 100% genotypic concordance with other variants or with a minor allele frequency <0.05, plus 21 additional markers showing association with ESRD in earlier studies. In the family study, the strongest evidence for association was with rs1345365 (odds ratio [OR]=2.42 per copy of A allele [1.35-4.32]; P=0.001) and rs10951509 (OR=2.42 per copy of A allele [1.31-4.48]; P=0.002), both of which are located in intron 13 and are in strong pairwise linkage disequilibrium (r(2)=0.97). These associations were in the opposite direction from those observed in African Americans, which suggests that the relationship between diabetic kidney disease and ELMO1 variation may involve as yet undiscovered functional variants or complex interactions with other biological variables.
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Affiliation(s)
- Robert L. Hanson
- Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 1550 East Indian School Road, Phoenix, AZ 85014
| | - Meredith P. Millis
- Translational Genomics Research Institute, Diabetes, Cardiovascular and Metabolic Diseases Division, 445 North Fifth Street, Phoenix, AZ 85004
| | - Naomi J. Young
- Translational Genomics Research Institute, Diabetes, Cardiovascular and Metabolic Diseases Division, 445 North Fifth Street, Phoenix, AZ 85004
| | - Sayuko Kobes
- Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 1550 East Indian School Road, Phoenix, AZ 85014
| | - Robert G. Nelson
- Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 1550 East Indian School Road, Phoenix, AZ 85014
| | - William C. Knowler
- Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 1550 East Indian School Road, Phoenix, AZ 85014
| | - Johanna K. DiStefano
- Translational Genomics Research Institute, Diabetes, Cardiovascular and Metabolic Diseases Division, 445 North Fifth Street, Phoenix, AZ 85004
- Corresponding author: Johanna K. DiStefano, Ph.D., Translational Genomics Research Institute, 445 North Fifth Street, Phoenix, AZ 85004, Tel: 602.343.8812, FAX: 602.343.8844,
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Ned RM, Yesupriya A, Imperatore G, Smelser DT, Moonesinghe R, Chang MH, Dowling NF. Inflammation gene variants and susceptibility to albuminuria in the U.S. population: analysis in the Third National Health and Nutrition Examination Survey (NHANES III), 1991-1994. BMC MEDICAL GENETICS 2010; 11:155. [PMID: 21054877 PMCID: PMC2991302 DOI: 10.1186/1471-2350-11-155] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 04/15/2010] [Accepted: 11/05/2010] [Indexed: 11/17/2022]
Abstract
BACKGROUND Albuminuria, a common marker of kidney damage, serves as an important predictive factor for the progression of kidney disease and for the development of cardiovascular disease. While the underlying etiology is unclear, chronic, low-grade inflammation is a suspected key factor. Genetic variants within genes involved in inflammatory processes may, therefore, contribute to the development of albuminuria. METHODS We evaluated 60 polymorphisms within 27 inflammatory response genes in participants from the second phase (1991-1994) of the Third National Health and Nutrition Examination Survey (NHANES III), a population-based and nationally representative survey of the United States. Albuminuria was evaluated as logarithm-transformed albumin-to-creatinine ratio (ACR), as ACR ≥ 30 mg/g, and as ACR above sex-specific thresholds. Multivariable linear regression and haplotype trend analyses were conducted to test for genetic associations in 5321 participants aged 20 years or older. Differences in allele and genotype distributions among non-Hispanic whites, non-Hispanic blacks, and Mexican Americans were tested in additive and codominant genetic models. RESULTS Variants in several genes were found to be marginally associated (uncorrected P value < 0.05) with log(ACR) in at least one race/ethnic group, but none remained significant in crude or fully-adjusted models when correcting for the false-discovery rate (FDR). In analyses of sex-specific albuminuria, IL1B (rs1143623) among Mexican Americans remained significantly associated with increased odds, while IL1B (rs1143623), CRP (rs1800947) and NOS3 (rs2070744) were significantly associated with ACR ≥ 30 mg/g in this population (additive models, FDR-P < 0.05). In contrast, no variants were found to be associated with albuminuria among non-Hispanic blacks after adjustment for multiple testing. The only variant among non-Hispanic whites significantly associated with any outcome was TNF rs1800750, which failed the test for Hardy-Weinberg proportions in this population. Haplotypes within MBL2, CRP, ADRB2, IL4R, NOS3, and VDR were significantly associated (FDR-P < 0.05) with log(ACR) or albuminuria in at least one race/ethnic group. CONCLUSIONS Our findings suggest a small role for genetic variation within inflammation-related genes to the susceptibility to albuminuria. Additional studies are needed to further assess whether genetic variation in these, and untested, inflammation genes alter the susceptibility to kidney damage.
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Affiliation(s)
- Renée M Ned
- Office of Public Health Genomics, Office of Surveillance, Epidemiology, and Laboratory Services, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Ajay Yesupriya
- Office of Public Health Genomics, Office of Surveillance, Epidemiology, and Laboratory Services, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Giuseppina Imperatore
- Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Diane T Smelser
- Office of Public Health Genomics, Office of Surveillance, Epidemiology, and Laboratory Services, Centers for Disease Control and Prevention, Atlanta, GA, USA
- American Society of Human Genetics Fellow, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Ramal Moonesinghe
- Office of Minority Health and Health Disparities, Office of the Director, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Man-huei Chang
- Office of Public Health Genomics, Office of Surveillance, Epidemiology, and Laboratory Services, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Nicole F Dowling
- Office of Public Health Genomics, Office of Surveillance, Epidemiology, and Laboratory Services, Centers for Disease Control and Prevention, Atlanta, GA, USA
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Carpena MP, Rados DV, Sortica DA, Souza BMD, Reis AF, Canani LH, Crispim D. Genetics of diabetic nephropathy. ACTA ACUST UNITED AC 2010; 54:253-61. [PMID: 20520954 DOI: 10.1590/s0004-27302010000300002] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2009] [Accepted: 02/26/2010] [Indexed: 01/08/2023]
Abstract
The increasing prevalence of diabetes mellitus has led to a growing number of chronic complications including diabetic nephropathy (DN). In addition to its high prevalence, DN is associated with high morbidity and mortality especially due to cardiovascular diseases. It is well established that genetic factors play a role in the pathogenesis of DN and genetically susceptible individuals can develop it after being exposed to environmental factors. DN is probably a complex, polygenic disease. Two main strategies have been used to identify genes associated to DN: analysis of candidate genes, and more recently genome-wide scan. Great efforts have been made to identify these main genes, but results are still inconsistent with different genes associated to a small effect in specific populations. The identification of the main genes would allow the detection of those individuals at high risk for DN and better understanding of its pathophysiology as well.
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Rao M, Peter I, Trikalinos TA. A lesson from the Zuni Indians: heritability in perspective. Am J Kidney Dis 2010; 56:251-4. [PMID: 20659625 DOI: 10.1053/j.ajkd.2010.05.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2010] [Accepted: 05/14/2010] [Indexed: 11/11/2022]
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MacCluer JW, Scavini M, Shah VO, Cole SA, Laston SL, Voruganti VS, Paine SS, Eaton AJ, Comuzzie AG, Tentori F, Pathak DR, Bobelu A, Bobelu J, Ghahate D, Waikaniwa M, Zager PG. Heritability of measures of kidney disease among Zuni Indians: the Zuni Kidney Project. Am J Kidney Dis 2010; 56:289-302. [PMID: 20646805 DOI: 10.1053/j.ajkd.2010.03.012] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2009] [Accepted: 03/03/2010] [Indexed: 01/29/2023]
Abstract
BACKGROUND The long-term goal of the GKDZI (Genetics of Kidney Disease in Zuni Indians) Study is to identify genes, environmental factors, and genetic-environmental interactions that modulate susceptibility to renal disease and intermediate phenotypes. STUDY DESIGN A community-based participatory research approach was used to recruit family members of individuals with kidney disease. SETTING & PARTICIPANTS The study was conducted in the Zuni Indians, a small endogamous tribe located in rural New Mexico. We recruited members of extended families, ascertained through a proband with kidney disease and at least 1 sibling with kidney disease. 821 participants were recruited, comprising 7,702 relative pairs. PREDICTOR OUTCOMES & MEASUREMENTS: Urine albumin-creatinine ratio (UACR) and hematuria were determined in 3 urine samples and expressed as a true ratio. Glomerular filtration rate (GFR) was estimated using the Modification of Diet in Renal Disease (MDRD) Study equation modified for American Indians. Probands were considered to have kidney disease if UACR was >or=0.2 in 2 or more of 3 spot urine samples or estimated GFR was decreased according to the CRIC (Chronic Renal Insufficiency Cohort) Study criteria. RESULTS Kidney disease was identified in 192 participants (23.4%). There were significant heritabilities for estimated GFR, UACR, serum creatinine, serum urea nitrogen, and uric acid and a variety of phenotypes related to obesity, diabetes, and cardiovascular disease. There were significant genetic correlations of some kidney-related phenotypes with these other phenotypes. LIMITATIONS Limitations include absence of renal biopsy, possible misclassification bias, lack of direct GFR measurements, and failure to include all possible environmental interactions. CONCLUSIONS Many phenotypes related to kidney disease showed significant heritabilities in Zuni Indians, and there were significant genetic correlations with phenotypes related to obesity, diabetes, and cardiovascular disease. The study design serves as a paradigm for the conduct of research in relatively isolated, endogamous, underserved populations.
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Affiliation(s)
- Jean W MacCluer
- Southwest Foundation for Biomedical Research, San Antonio, TX, USA
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Pezzolesi MG, Katavetin P, Kure M, Poznik GD, Skupien J, Mychaleckyj JC, Rich SS, Warram JH, Krolewski AS. Confirmation of genetic associations at ELMO1 in the GoKinD collection supports its role as a susceptibility gene in diabetic nephropathy. Diabetes 2009; 58:2698-702. [PMID: 19651817 PMCID: PMC2768169 DOI: 10.2337/db09-0641] [Citation(s) in RCA: 81] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
OBJECTIVE To examine the association between single nucleotide polymorphisms (SNPs) in the engulfment and cell motility 1 (ELMO1) gene, a locus previously shown to be associated with diabetic nephropathy in two ethnically distinct type 2 diabetic populations, and the risk of nephropathy in type 1 diabetes. RESEARCH DESIGN AND METHODS Genotypic data from a genome-wide association scan (GWAS) of the Genetics of Kidneys in Diabetes (GoKinD) study collection were analyzed for associations across the ELMO1 locus. In total, genetic associations were assessed using 118 SNPs and 1,705 individuals of European ancestry with type 1 diabetes (885 normoalbuminuric control subjects and 820 advanced diabetic nephropathy case subjects). RESULTS The strongest associations in ELMO1 occurred at rs11769038 (odds ratio [OR] 1.24; P = 1.7 x 10(-3)) and rs1882080 (OR 1.23; P = 3.2 x 10(-3)) located in intron 16. Two additional SNPs, located in introns 18 and 20, respectively, were also associated with diabetic nephropathy. No evidence of association for variants previously reported in type 2 diabetes was observed in our collection. CONCLUSIONS Using GWAS data from the GoKinD collection, we comprehensively examined evidence of association across the ELMO1 locus. Our investigation marks the third report of associations in ELMO1 with diabetic nephropathy, further establishing its role in the susceptibility of this disease. There is evidence of allelic heterogeneity, contributed by the diverse genetic backgrounds of the different ethnic groups examined. Further investigation of SNPs at this locus is necessary to fully understand the commonality of these associations and the mechanism(s) underlying their role in diabetic nephropathy.
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Affiliation(s)
- Marcus G. Pezzolesi
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Pisut Katavetin
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Masahiko Kure
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - G. David Poznik
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Jan Skupien
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Josyf C. Mychaleckyj
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, Virginia
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, Virginia
| | - James H. Warram
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Andrzej S. Krolewski
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Corresponding author: Andrzej S. Krolewski,
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Zelmanovitz T, Gerchman F, Balthazar APS, Thomazelli FCS, Matos JD, Canani LH. Diabetic nephropathy. Diabetol Metab Syndr 2009; 1:10. [PMID: 19825147 PMCID: PMC2761852 DOI: 10.1186/1758-5996-1-10] [Citation(s) in RCA: 88] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2009] [Accepted: 09/21/2009] [Indexed: 12/21/2022] Open
Abstract
Diabetic nephropathy is the leading cause of chronic renal disease and a major cause of cardiovascular mortality. Diabetic nephropathy has been categorized into stages: microalbuminuria and macroalbuminuria. The cut-off values of micro- and macroalbuminuria are arbitrary and their values have been questioned. Subjects in the upper-normal range of albuminuria seem to be at high risk of progression to micro- or macroalbuminuria and they also had a higher blood pressure than normoalbuminuric subjects in the lower normoalbuminuria range. Diabetic nephropathy screening is made by measuring albumin in spot urine. If abnormal, it should be confirmed in two out three samples collected in a three to six-months interval. Additionally, it is recommended that glomerular filtration rate be routinely estimated for appropriate screening of nephropathy, because some patients present a decreased glomerular filtration rate when urine albumin values are in the normal range. The two main risk factors for diabetic nephropathy are hyperglycemia and arterial hypertension, but the genetic susceptibility in both type 1 and type 2 diabetes is of great importance. Other risk factors are smoking, dyslipidemia, proteinuria, glomerular hyperfiltration and dietary factors. Nephropathy is pathologically characterized in individuals with type 1 diabetes by thickening of glomerular and tubular basal membranes, with progressive mesangial expansion (diffuse or nodular) leading to progressive reduction of glomerular filtration surface. Concurrent interstitial morphological alterations and hyalinization of afferent and efferent glomerular arterioles also occur. Podocytes abnormalities also appear to be involved in the glomerulosclerosis process. In patients with type 2 diabetes, renal lesions are heterogeneous and more complex than in individuals with type 1 diabetes. Treatment of diabetic nephropathy is based on a multiple risk factor approach, and the goal is retarding the development or progression of the disease and to decrease the subject's increased risk of cardiovascular disease. Achieving the best metabolic control, treating hypertension (<130/80 mmHg) and dyslipidemia (LDL cholesterol <100 mg/dl), using drugs that block the renin-angiotensin-aldosterone system, are effective strategies for preventing the development of microalbuminuria, delaying the progression to more advanced stages of nephropathy and reducing cardiovascular mortality in patients with diabetes.
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Affiliation(s)
- Themis Zelmanovitz
- Endocrine Division, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Universidade Federal do Rio Grande do Sul, Brazil
| | - Fernando Gerchman
- Endocrine Division, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | | | | | | | - Luís H Canani
- Endocrine Division, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Universidade Federal do Rio Grande do Sul, Brazil
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Nobrega MA, Solberg Woods LC, Fleming S, Jacob HJ. Distinct genetic regulation of progression of diabetes and renal disease in the Goto-Kakizaki rat. Physiol Genomics 2009; 39:38-46. [PMID: 19584172 DOI: 10.1152/physiolgenomics.90389.2008] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Goto-Kakizaki (GK) rats develop early-onset type 2 diabetes (T2D) symptoms, with signs of diabetic nephropathy becoming apparent with aging. To determine whether T2D and renal disease share similar genetic architecture, we ran a quantitative trait locus (QTL) analysis in the F2 progeny of a GK x Brown Norway (BN) rat cross. Further, to determine whether genetic components change over time, we ran the QTL analysis on phenotypes collected longitudinally, at 3, 6, 9 and 12 mo, from the same animals. We confirmed three chromosomal regions that are linked to early diabetes phenotypes (chromosomes 1, 5, and 10) and a single region involved in the late progression of the disorder (chromosome 4). A single region was identified for the onset of the renal phenotype proteinuria (chromosome 5). This region overlaps the diabetic QTL, although it is not certain whether similar genes are involved in both phenotypes. A second QTL linked to the progression of the renal phenotype was found on chromosome 7. Linkage for triglyceride and cholesterol levels were also identified (chromosomes 7 and 8, respectively). These results demonstrate that, in general, different genetic components control diabetic and renal phenotypes in a diabetic nephropathy model. Furthermore, these results demonstrate that, over time, different genetic components are involved in progression of disease from those that were involved in disease onset. This observation would suggest that clinical studies collecting participants over a wide age distribution may be diluting genetic effects and reducing power to detect true effects.
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Affiliation(s)
- Marcelo A Nobrega
- Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin 53266, USA.
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Almeida JC, Mello VD, Canani LH, Gross JL, Azevedo MJ. Papel dos lipídeos da dieta na nefropatia diabética. ACTA ACUST UNITED AC 2009; 53:634-45. [DOI: 10.1590/s0004-27302009000500016] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2008] [Accepted: 11/19/2008] [Indexed: 11/22/2022]
Abstract
O objetivo do presente manuscrito foi revisar o possível papel dos lipídeos dietéticos na nefropatia diabética (ND), considerando as alterações do perfil lipídico associadas e a interação entre aspectos dietéticos e genéticos. Os lipídeos dietéticos podem ter um papel importante no desenvolvimento e na progressão da ND. A composição das gorduras da dieta tem sido associada com a ND, particularmente à microalbuminúria e às anormalidades lipídicas e de função endotelial. Entretanto, ainda não está comprovado o benefício da modificação da ingestão de gorduras em pacientes com ND, em especial sobre desfechos definitivos, como incidência e progressão da ND, insuficiência renal e morte. Além disso, a resposta do perfil lipídico à ingestão de gorduras pode ser influenciada por fatores genéticos. A identificação de polimorfismos genéticos específicos associados a essa interação poderá permitir a individualização de estratégias nutricionais na ND.
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Pezzolesi MG, Poznik GD, Mychaleckyj JC, Paterson AD, Barati MT, Klein JB, Ng DP, Placha G, Canani LH, Bochenski J, Waggott D, Merchant ML, Krolewski B, Mirea L, Wanic K, Katavetin P, Kure M, Wolkow P, Dunn JS, Smiles A, Walker WH, Boright AP, Bull SB, Doria A, Rogus JJ, Rich SS, Warram JH, Krolewski AS. Genome-wide association scan for diabetic nephropathy susceptibility genes in type 1 diabetes. Diabetes 2009; 58:1403-10. [PMID: 19252134 PMCID: PMC2682673 DOI: 10.2337/db08-1514] [Citation(s) in RCA: 234] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
OBJECTIVE Despite extensive evidence for genetic susceptibility to diabetic nephropathy, the identification of susceptibility genes and their variants has had limited success. To search for genes that contribute to diabetic nephropathy, a genome-wide association scan was implemented on the Genetics of Kidneys in Diabetes collection. RESEARCH DESIGN AND METHODS We genotyped approximately 360,000 single nucleotide polymorphisms (SNPs) in 820 case subjects (284 with proteinuria and 536 with end-stage renal disease) and 885 control subjects with type 1 diabetes. Confirmation of implicated SNPs was sought in 1,304 participants of the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) study, a long-term, prospective investigation of the development of diabetes-associated complications. RESULTS A total of 13 SNPs located in four genomic loci were associated with diabetic nephropathy with P < 1 x 10(-5). The strongest association was at the FRMD3 (4.1 protein ezrin, radixin, moesin [FERM] domain containing 3) locus (odds ratio [OR] = 1.45, P = 5.0 x 10(-7)). A strong association was also identified at the CARS (cysteinyl-tRNA synthetase) locus (OR = 1.36, P = 3.1 x 10(-6)). Associations between both loci and time to onset of diabetic nephropathy were supported in the DCCT/EDIC study (hazard ratio [HR] = 1.33, P = 0.02, and HR = 1.32, P = 0.01, respectively). We demonstratedexpression of both FRMD3 and CARS in human kidney. CONCLUSIONS We identified genetic associations for susceptibility to diabetic nephropathy at two novel candidate loci near the FRMD3 and CARS genes. Their identification implicates previously unsuspected pathways in the pathogenesis of this important late complication of type 1 diabetes.
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Affiliation(s)
- Marcus G. Pezzolesi
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - G. David Poznik
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Josyf C. Mychaleckyj
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, Virginia
| | - Andrew D. Paterson
- Program in Genetics and Genome Biology, Hospital for Sick Children, University of Toronto, Toronto, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | | | - Jon B. Klein
- Kidney Disease Program, University of Louisville, Louisville, Kentucky
| | - Daniel P.K. Ng
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Department of Community, Occupational and Family Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Grzegorz Placha
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Department of Hypertension, Medical University of Warsaw, Warsaw, Poland
| | - Luis H. Canani
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Department of Endocrinology, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Jacek Bochenski
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Daryl Waggott
- Samuel Lunenfeld Research Institute of Mount Sinai Hospital, Prosserman Centre for Health Research, Toronto, Canada
| | | | - Bozena Krolewski
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Lucia Mirea
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
- Samuel Lunenfeld Research Institute of Mount Sinai Hospital, Prosserman Centre for Health Research, Toronto, Canada
| | - Krzysztof Wanic
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Pisut Katavetin
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Masahiko Kure
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Pawel Wolkow
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Department of Pharmacology, Jagiellonian University, School of Medicine, Krakow, Poland
| | - Jonathon S. Dunn
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Adam Smiles
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - William H. Walker
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Andrew P. Boright
- Department of Medicine, University Health Network, University of Toronto, Toronto, Canada
| | - Shelley B. Bull
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
- Samuel Lunenfeld Research Institute of Mount Sinai Hospital, Prosserman Centre for Health Research, Toronto, Canada
| | | | - Alessandro Doria
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - John J. Rogus
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, Virginia
| | - James H. Warram
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Andrzej S. Krolewski
- Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Corresponding author: Andrzej S. Krolewski,
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Ng DPK, Fukushima M, Tai BC, Koh D, Leong H, Imura H, Lim XL. Reduced GFR and albuminuria in Chinese type 2 diabetes mellitus patients are both independently associated with activation of the TNF-alpha system. Diabetologia 2008; 51:2318-24. [PMID: 18839132 DOI: 10.1007/s00125-008-1162-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/02/2008] [Accepted: 08/05/2008] [Indexed: 11/30/2022]
Abstract
AIMS/HYPOTHESIS The involvement of chronic inflammation in albuminuria and renal function was investigated in a cross-sectional study of 320 type 2 diabetic Chinese patients from the Singapore Diabetes Cohort Study. METHODS Plasma levels of TNF-alpha and its two cellular receptors and of IL-6 and C-reactive protein (CRP) were measured. A composite TNF-alpha score was extracted using principal component analysis. Multiple linear regression analysis was implemented to evaluate the relationship between log( e ) (ln) albumin:creatinine ratio (ACR) and estimated GFR (eGFR) with the inflammatory variables and other clinical covariates. A Bonferroni correction was applied based on the total number of variables entered into regression analyses. RESULTS ln ACR was significantly associated with TNF-alpha score independently of eGFR even after a Bonferroni correction. TNF-alpha score was also significantly associated with eGFR independently of ln ACR even after correction for multiple testing. These findings were similar when the individual molecules of the TNF-alpha system were analysed separately instead of using the composite TNF-alpha score. No association was observed for IL-6 and CRP with either renal trait. Diabetes duration was a significant predictor for ln ACR but not eGFR. Conversely, age was significantly associated with eGFR but not ln ACR. CONCLUSIONS/INTERPRETATION Activation of the TNF-alpha system may potentially exert independent effects on ln ACR and eGFR in type 2 diabetes. Because of the study design, one may also consider the possibility that changes in these renal traits may conversely be responsible for such an inflammatory response.
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Affiliation(s)
- D P K Ng
- Department of Community, Occupational and Family Medicine, Yong Loo Lin School of Medicine, National University of Singapore, 16 Medical Drive MD3, Singapore, 117597, Singapore.
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De Cosmo S, Minenna A, Zhang YY, Thompson R, Thompson R, Miscio G, Vedovato M, Rauseo A, Saller A, Mastroianno S, Pellegrini F, Trevisan R, Fioretto P, Doria A, Trischitta V. Association of the Q121 variant of ENPP1 gene with decreased kidney function among patients with type 2 diabetes. Am J Kidney Dis 2008; 53:273-80. [PMID: 18950909 DOI: 10.1053/j.ajkd.2008.07.040] [Citation(s) in RCA: 15] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2008] [Accepted: 07/29/2008] [Indexed: 12/20/2022]
Abstract
BACKGROUND Insulin resistance has a role in diabetic kidney complications. The K121Q (lysine to glutamine substitution at amino acid 121, encoded by single-nucleotide polymorphism rs1044498) variant of the ectonucleotide pyrophosphatase/phosphodiesterase gene (ENPP1) has been associated with insulin resistance and related vascular complications in patients with type 2 diabetes (T2D) in many, although not all, studies. This study investigated whether the ENPP1 Q121 variant modulates the risk of decreased glomerular filtration rate (GFR) in patients with T2D. STUDY DESIGN Cross-sectional study. SETTING & PARTICIPANTS 2 diabetes units from Italy (in Gargano and Padua) and 1 from the United States (Boston, MA) recruited a total of 1,392 patients with T2D. PREDICTOR The ENPP1 Q121 variant. MEASUREMENTS Estimated GFR from serum creatinine, urinary albumin excretion, blood pressure, hemoglobin A(1c), triglycerides, total cholesterol, and high-density lipoprotein cholesterol. OUTCOMES Decreased GFRs (ie, estimated GFR <60 mL/min/1.73 m(2)). RESULTS In the Gargano and Boston populations, according to the dominant model of inheritance, Q121 carriers (ie, individual with either KQ or QQ alleles) had an increased risk of decreased GFR: odds ratios (ORs) of 1.69 (95% confidence interval [CI], 1.1 to 2.6) and 1.50 (95% CI, 1.0 to 2.2), respectively. In the Padua set, the association was in the same direction, but did not reach formal statistical significance (OR, 1.77; 95% CI, 0.7 to 4.5). When the 3 studies were pooled, Q121 carriers showed an increased risk of decreased GFR (OR, 1.58; 95% CI, 1.2 to 2.1; P = 0.002). Also, pooled mean differences in absolute GFRs were different across genotype groups, with Q121 carriers showing lower GFRs compared with KK individuals (P = 0.04). LIMITATIONS P values not approaching a genome-wide level of significance. CONCLUSIONS Our data suggest that patients with T2D carrying the ENPP1 Q121 variant are at increased risk of decreased GFR.
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Affiliation(s)
- Salvatore De Cosmo
- Unit of Endocrinology, Scientific Institute Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy.
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Promoter polymorphism of the erythropoietin gene in severe diabetic eye and kidney complications. Proc Natl Acad Sci U S A 2008; 105:6998-7003. [PMID: 18458324 DOI: 10.1073/pnas.0800454105] [Citation(s) in RCA: 153] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Significant morbidity and mortality among patients with diabetes mellitus result largely from a greatly increased incidence of microvascular complications. Proliferative diabetic retinopathy (PDR) and end stage renal disease (ESRD) are two of the most common and severe microvascular complications of diabetes. A high concordance exists in the development of PDR and ESRD in diabetic patients, as well as strong familial aggregation of these complications, suggesting a common underlying genetic mechanism. However, the precise gene(s) and genetic variant(s) involved remain largely unknown. Erythropoietin (EPO) is a potent angiogenic factor observed in the diabetic human and mouse eye. By a combination of case-control association and functional studies, we demonstrate that the T allele of SNP rs1617640 in the promoter of the EPO gene is significantly associated with PDR and ESRD in three European-American cohorts [Utah: P = 1.91 x 10(-3); Genetics of Kidneys in Diabetes (GoKinD) Study: P = 2.66 x 10(-8); and Boston: P = 2.1 x 10(-2)]. The EPO concentration in human vitreous body was 7.5-fold higher in normal subjects with the TT risk genotype than in those with the GG genotype. Computational analysis suggests that the risk allele (T) of rs1617640 creates a matrix match with the EVI1/MEL1 or AP1 binding site, accounting for an observed 25-fold enhancement of luciferase reporter expression as compared with the G allele. These results suggest that rs1617640 in the EPO promoter is significantly associated with PDR and ESRD. This study identifies a disease risk-associated gene and potential pathway mediating severe diabetic microvascular complications.
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Arar NH, Voruganti VS, Nath SD, Thameem F, Bauer R, Cole SA, Blangero J, MacCluer JW, Comuzzie AG, Abboud HE. A genome-wide search for linkage to chronic kidney disease in a community-based sample: the SAFHS. Nephrol Dial Transplant 2008; 23:3184-91. [PMID: 18443212 DOI: 10.1093/ndt/gfn215] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Chronic kidney disease (CKD) phenotypes such as albuminuria measured by urinary albumin creatinine ratio (ACR), elevated serum creatinine (SrCr) and/or decreased creatinine clearance (CrCl) and glomerular filtration rate (eGFR) are major risk factors for renal and cardiovascular diseases. Epidemiological studies have reported that CKD phenotypes cluster in families suggesting a genetic predisposition. However, studies reporting chromosomal regions influencing CKD are very limited. Therefore, the purpose of this study is to identify susceptible chromosomal regions for CKD phenotypes in Mexican American families enrolled in the San Antonio Family Heart Study (SAFHS). METHODS We used the variance components decomposition approach (implemented in the software package SOLAR) to perform linkage analysis on 848 participants from 26 families. A total of 417 microsatellite markers were genotyped at an average interval of 10 cM spanning 22 autosomal chromosomes. RESULTS All phenotypes were measured by standard procedures. Mean +/- SD values of ACR, SrCr, CrCl and eGFR were 0.06 +/- 0.38, 0.85 +/- 0.72 mg/dl, 129.85 +/- 50.37 ml/min and 99.18 +/- 25.69 ml/min/1.73 m(2) body surface area, respectively. All four CKD phenotypes exhibited significant heritabilities (P < 0.0001). A genome-wide scan showed linkage on chromosome 2p25 for SrCr, CrCl and eGFR. Significant linkage was also detected on chromosome 9q21 for eGFR [logarithm of the odds (LOD) score = 3.87, P = 0.00005] and SrCr (LOD score = 2.6, P = 0.00026). ACR revealed suggestive evidence for linkage to a region on chromosome 20q12 (LOD score = 2.93, P = 0.00020). CONCLUSION Findings indicate that chromosomal regions 2p25, 9q21 and 20q12 may have functional relevance to CKD phenotypes in Mexican Americans.
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Affiliation(s)
- Nedal H Arar
- Department of Medicine/Nephrology, University of Texas Health Science Center, South Texas Veterans Health Care System, 7400 Merton Minter Blvd, San Antonio, TX 78229-4404, USA.
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Navarro-González JF, Mora-Fernández C. The role of inflammatory cytokines in diabetic nephropathy. J Am Soc Nephrol 2008; 19:433-42. [PMID: 18256353 DOI: 10.1681/asn.2007091048] [Citation(s) in RCA: 637] [Impact Index Per Article: 39.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Cytokines act as pleiotropic polypeptides regulating inflammatory and immune responses through actions on cells. They provide important signals in the pathophysiology of a range of diseases, including diabetes mellitus. Chronic low-grade inflammation and activation of the innate immune system are closely involved in the pathogenesis of diabetes and its microvascular complications. Inflammatory cytokines, mainly IL-1, IL-6, and IL-18, as well as TNF-alpha, are involved in the development and progression of diabetic nephropathy. In this context, cytokine genetics is of special interest to combinatorial polymorphisms among cytokine genes, their functional variations, and general susceptibility to diabetic nephropathy. Finally, the recognition of these molecules as significant pathogenic mediators in diabetic nephropathy leaves open the possibility of new potential therapeutic targets.
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Affiliation(s)
- Juan F Navarro-González
- Servicio de Nefrología, Hospital Universitario Nuestra Señora de Candelaria, Carretera del Rosario, 145, 38010 Santa Cruz de Tenerife, Spain.
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Sauerhöfer S, Yuan G, Braun GS, Deinzer M, Neumaier M, Gretz N, Floege J, Kriz W, van der Woude F, Moeller MJ. L-carnosine, a substrate of carnosinase-1, influences glucose metabolism. Diabetes 2007; 56:2425-32. [PMID: 17601992 DOI: 10.2337/db07-0177] [Citation(s) in RCA: 121] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
OBJECTIVE Carnosinase 1 (CN1) is a secreted dipeptidase that hydrolyzes L-carnosine. Recently, we have identified an allelic variant of human CN1 (hCN1) that results in increased enzyme activity and is associated with susceptibility for diabetic nephropathy in human diabetic patients. We therefore hypothesized that L-carnosine in the serum represents a critical protective factor in diabetic patients. RESEARCH DESIGN AND METHODS L-carnosine serum levels were manipulated in db/db mice, a model of type 2 diabetes. In a transgenic approach, hCN1 cDNA was expressed under the control of a liver-specific promoter in db/db mice, mimicking the expression pattern of hCN1 in humans. RESULTS Fasting plasma glucose as well as A1C levels rose significantly earlier and remained higher in transgenic animals throughout life. Body weights were reduced as a result of significant glucosuria. In an opposite approach, nontransgenic db/db mice were supplemented with L-carnosine. In these latter mice, diabetes manifested significantly later and milder. In agreement with the above data, serum fasting insulin levels were low in the transgenic mice and elevated by L-carnosine feeding. Insulin resistance and insulin secretion were not significantly affected by L-carnosine serum levels. Instead, a significant correlation of L-carnosine levels with beta-cell mass was observed. CONCLUSIONS hCN1-dependent susceptibility to diabetic nephropathy may at least in part be mediated by altered glucose metabolism in type 2 diabetic patients.
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Affiliation(s)
- Sibylle Sauerhöfer
- Institute for Anatomy and Cell Biology 1, University of Heidelberg, Heidelberg, Germany
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Iyengar SK, Abboud HE, Goddard KAB, Saad MF, Adler SG, Arar NH, Bowden DW, Duggirala R, Elston RC, Hanson RL, Ipp E, Kao WHL, Kimmel PL, Klag MJ, Knowler WC, Meoni LA, Nelson RG, Nicholas SB, Pahl MV, Parekh RS, Quade SRE, Rich SS, Rotter JI, Scavini M, Schelling JR, Sedor JR, Sehgal AR, Shah VO, Smith MW, Taylor KD, Winkler CA, Zager PG, Freedman BI. Genome-wide scans for diabetic nephropathy and albuminuria in multiethnic populations: the family investigation of nephropathy and diabetes (FIND). Diabetes 2007; 56:1577-85. [PMID: 17363742 DOI: 10.2337/db06-1154] [Citation(s) in RCA: 123] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
The Family Investigation of Nephropathy and Diabetes (FIND) was initiated to map genes underlying susceptibility to diabetic nephropathy. A total of 11 centers participated under a single collection protocol to recruit large numbers of diabetic sibling pairs concordant and discordant for diabetic nephropathy. We report the findings from the first-phase genetic analyses in 1,227 participants from 378 pedigrees of European-American, African-American, Mexican-American, and American Indian descent recruited from eight centers. Model-free linkage analyses, using a dichotomous definition for diabetic nephropathy in 397 sibling pairs, as well as the quantitative trait urinary albumin-to-creatinine ratio (ACR), were performed using the Haseman-Elston linkage test on 404 microsatellite markers. The strongest evidence of linkage to the diabetic nephropathy trait was on chromosomes 7q21.3, 10p15.3, 14q23.1, and 18q22.3. In ACR (883 diabetic sibling pairs), the strongest linkage signals were on chromosomes 2q14.1, 7q21.1, and 15q26.3. These results confirm regions of linkage to diabetic nephropathy on chromosomes 7q, 10p, and 18q from prior reports, making it important that genes underlying these peaks be evaluated for their contribution to nephropathy susceptibility. Large family collections consisting of multiple members with diabetes and advanced nephropathy are likely to accelerate the identification of genes causing diabetic nephropathy, a life-threatening complication of diabetes.
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Affiliation(s)
- Sudha K Iyengar
- FIND-Genetic Analysis and Data Coordinating Center, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio 44106-7281, USA.
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Barzilay JI, Cutler JA, Davis BR. Antihypertensive medications and risk of diabetes mellitus. Curr Opin Nephrol Hypertens 2007; 16:256-60. [PMID: 17420670 DOI: 10.1097/mnh.0b013e328057dea2] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
PURPOSE OF REVIEW Over the past decade post-hoc analyses of clinical trials and observational studies have tended to show that participants treated with thiazide diuretics are at greater risk for newly diagnosed diabetes mellitus than those treated with other medication classes. We review the results of several recent studies on the impact of thiazide-related hyperglycemia and diabetes mellitus on cardiovascular disease outcomes. We also examine the impact of the glucose-sparing effects of angiotensin-converting enzyme inhibitors and angiotensin receptor blockers on preventing cardiovascular disease. RECENT FINDINGS No consistent or conclusive evidence has been found that hyperglycemia or diabetes mellitus in association with thiazide diuretic use is associated with increased cardiovascular disease outcomes. This benign outcome may be a consequence of the fact that only a segment of such diuretic-associated cases is induced by the usual etiologic mechanisms that are associated with classic 'diabetes mellitus'. Likewise, no evidence has been found that the glucose-lowering effect of angiotensin-converting enzyme inhibitors is associated with decreased cardiovascular disease risk. SUMMARY We conclude that thiazide diuretics are safe to use, even in hypertensive individuals at risk for incident glucose disorders. The use of angiotensin-converting enzyme inhibitors for protection against glucose disorders and subsequent cardiovascular disease remains to be determined.
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Affiliation(s)
- Joshua I Barzilay
- Kaiser Permanente of Georgia and the Division of Endocrinology, Emory University School of Medicine, Atlanta, Georgia, USA.
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Chen G, Adeyemo AA, Zhou J, Chen Y, Doumatey A, Lashley K, Huang H, Amoah A, Agyenim-Boateng K, Eghan BA, Okafor G, Acheampong J, Oli J, Fasanmade O, Johnson T, Rotimi C. A genome-wide search for linkage to renal function phenotypes in West Africans with type 2 diabetes. Am J Kidney Dis 2007; 49:394-400. [PMID: 17336700 DOI: 10.1053/j.ajkd.2006.12.011] [Citation(s) in RCA: 43] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2006] [Accepted: 12/11/2006] [Indexed: 11/11/2022]
Abstract
BACKGROUND Reduced renal function often is a major consequence of diabetes and hypertension. Although several indices of renal function (eg, creatinine clearance) are clearly heritable and show linkage to several genomic regions, the specific underlying genetic determinants are still being sought. The purpose of this study is to conduct a genome-wide search for regions linked to 3 renal function phenotypes, serum creatinine, creatinine clearance, and glomerular filtration rate (GFR), in persons with type 2 diabetes. METHODS A genome-wide panel of 372 autosomal short tandem repeat markers at an average spacing of 9 centimorgan were typed in 691 patients with type 2 diabetes (321 sib pairs and 36 half-sib pairs) in an affected sib pair study in West Africa. Linkage analysis was conducted with the 3 phenotypes by using a multipoint variance components linkage method. RESULTS Creatinine clearance showed higher logarithm of odds (LOD) score than the other 2 phenotypes. Linkage to creatinine clearance was observed on chromosomes 16 (marker D16S539, LOD score of 3.56, empirical P = 0.0001), 17 (D17S1298, LOD score of 2.08, empirical P = 0.0018), and 7 (D7S1818, LOD score of 1.84, nominal P = 0.00181, empirical P = 0.0022). Maximum LOD scores for serum creatinine were observed on chromosomes 10 (D10S1432, LOD score of 2.53, empirical P = 0.0001) and 3 (D3S2418, LOD score of 2.21, empirical P = 0.0003) and for GFR on chromosomes 6 (D6S1040, LOD score of 2.08, empirical P = 0.0001) and 8 (D8S256, LOD score of 1.80, empirical P = 0.0001). Several of these results are replications of significant findings from other genome scans. CONCLUSION A genome-wide scan for serum creatinine, creatinine clearance, and GFR in a West African sample showed linkage regions that may harbor genes influencing variation in these phenotypes. Potential candidate genes in these regions that have been implicated in diabetic nephropathy and/or renal damage in models of hypertension include CYBA (or P22PHOX) (16q24), NOX1 (10q22), and NOX3 (6q25.1-q26).
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Affiliation(s)
- Guanjie Chen
- National Human Genome Center at Howard University, College of Medicine, Washington, DC 20059, USA.
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Placha G, Poznik GD, Dunn J, Smiles A, Krolewski B, Glew T, Puppala S, Schneider J, Rogus JJ, Rich SS, Duggirala R, Warram JH, Krolewski AS. A genome-wide linkage scan for genes controlling variation in renal function estimated by serum cystatin C levels in extended families with type 2 diabetes. Diabetes 2006; 55:3358-65. [PMID: 17130480 DOI: 10.2337/db06-0781] [Citation(s) in RCA: 59] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
We performed a variance components linkage analysis of renal function, measured as glomerular filtration rate (GFR), in 63 extended families with multiple members with type 2 diabetes. GFR was estimated from serum concentrations of cystatin C and creatinine in 406 diabetic and 428 nondiabetic relatives. Results for cystatin C were summarized because they are superior to creatinine results. GFR aggregates in families with significant heritability (h(2)) in diabetic (h(2) = 0.45, P < 1 x 10(-5)) and nondiabetic (h(2) = 0.36, P < 1 x 10(-3)) relatives. Genetic correlation (r(G) = 0.35) between the GFR of diabetic and nondiabetic relatives was less than one (P = 0.01), suggesting that genes controlling GFR variation in these groups are different. Linkage results supported this interpretation. In diabetic relatives, linkage was strong on chromosome 2q (logarithm of odds [LOD] = 4.1) and suggestive on 10q (LOD = 3.1) and 18p (LOD = 2.2). In nondiabetic relatives, linkage was suggestive on 3q (LOD = 2.2) and 11p (LOD = 2.1). When diabetic and nondiabetic relatives were combined, strong evidence for linkage was found only on 7p (LOD = 4.0). In conclusion, partially distinct sets of genes control GFR variation in relatives with and without diabetes on chromosome 2q, possibly on 10q and 18p in the former, and on 7p in both. None of these genes overlaps with genes controlling variation in urinary albumin excretion.
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MESH Headings
- Adult
- Age of Onset
- Aged
- Chromosome Mapping
- Chromosomes, Human, Pair 10
- Chromosomes, Human, Pair 18
- Chromosomes, Human, Pair 2
- Chromosomes, Human, Pair 7
- Cystatin C
- Cystatins/blood
- Cystatins/genetics
- DNA/genetics
- DNA/isolation & purification
- Diabetes Mellitus, Type 2/blood
- Diabetes Mellitus, Type 2/genetics
- Diabetes Mellitus, Type 2/physiopathology
- Family
- Genetic Variation
- Genome, Human
- Genotype
- Glomerular Filtration Rate
- Humans
- Kidney Function Tests
- Middle Aged
- Reference Values
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Affiliation(s)
- Grzegorz Placha
- Section on Genetics and Epidemiology, Joslin Diabetes Center, One Joslin Place, Boston, MA 02215, USA
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