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Kollerits B, Gruber S, Steinbrenner I, Schwaiger JP, Weissensteiner H, Schönherr S, Forer L, Kotsis F, Schultheiss UT, Meiselbach H, Wanner C, Eckardt KU, Kronenberg F. Correction: Apolipoprotein A-IV concentrations and cancer in a large cohort of chronic kidney disease patients: results from the GCKD study. BMC Cancer 2024; 24:348. [PMID: 38504160 PMCID: PMC10949802 DOI: 10.1186/s12885-024-12128-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/21/2024] Open
Affiliation(s)
- Barbara Kollerits
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstraße 41, 6020, Innsbruck, Austria
| | - Simon Gruber
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstraße 41, 6020, Innsbruck, Austria
| | - Inga Steinbrenner
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Johannes P Schwaiger
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstraße 41, 6020, Innsbruck, Austria
| | - Hansi Weissensteiner
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstraße 41, 6020, Innsbruck, Austria
| | - Sebastian Schönherr
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstraße 41, 6020, Innsbruck, Austria
| | - Lukas Forer
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstraße 41, 6020, Innsbruck, Austria
| | - Fruzsina Kotsis
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Department of Medicine IV - Nephrology and Primary Care, Faculty of Medicine and Medical Center - , University of Freiburg, Freiburg, Germany
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Department of Medicine IV - Nephrology and Primary Care, Faculty of Medicine and Medical Center - , University of Freiburg, Freiburg, Germany
| | - Heike Meiselbach
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- German Chronic Kidney Disease Study, Erlangen, Germany
| | - Christoph Wanner
- Division of Nephrology, Department of Internal Medicine I, University Hospital Würzburg, Würzburg, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- German Chronic Kidney Disease Study, Erlangen, Germany
- Department of Nephrology and Medical Intensive Care, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstraße 41, 6020, Innsbruck, Austria.
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Kollerits B, Gruber S, Steinbrenner I, Schwaiger JP, Weissensteiner H, Schönherr S, Forer L, Kotsis F, Schultheiss UT, Meiselbach H, Wanner C, Eckardt KU, Kronenberg F. Apolipoprotein A-IV concentrations and cancer in a large cohort of chronic kidney disease patients: results from the GCKD study. BMC Cancer 2024; 24:320. [PMID: 38454416 PMCID: PMC10921727 DOI: 10.1186/s12885-024-12053-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 02/26/2024] [Indexed: 03/09/2024] Open
Abstract
BACKGROUND Chronic kidney disease (CKD) is highly connected to inflammation and oxidative stress. Both favour the development of cancer in CKD patients. Serum apolipoprotein A-IV (apoA-IV) concentrations are influenced by kidney function and are an early marker of kidney impairment. Besides others, it has antioxidant and anti-inflammatory properties. Proteomic studies and small case-control studies identified low apoA-IV as a biomarker for various forms of cancer; however, prospective studies are lacking. We therefore investigated whether serum apoA-IV is associated with cancer in the German Chronic Kidney Disease (GCKD) study. METHODS These analyses include 5039 Caucasian patients from the prospective GCKD cohort study followed for 6.5 years. Main inclusion criteria were an eGFR of 30-60 mL/min/1.73m2 or an eGFR > 60 mL/min/1.73m2 in the presence of overt proteinuria. RESULTS Mean apoA-IV concentrations of the entire cohort were 28.9 ± 9.8 mg/dL (median 27.6 mg/dL). 615 patients had a history of cancer before the enrolment into the study. ApoA-IV concentrations above the median were associated with a lower odds for a history of cancer (OR = 0.79, p = 0.02 when adjusted age, sex, smoking, diabetes, BMI, albuminuria, statin intake, and eGFRcreatinine). During follow-up 368 patients developed an incident cancer event and those with apoA-IV above the median had a lower risk (HR = 0.72, 95%CI 0.57-0.90, P = 0.004). Finally, 62 patients died from such an incident cancer event and each 10 mg/dL higher apoA-IV concentrations were associated with a lower risk for fatal cancer (HR = 0.62, 95%CI 0.44-0.88, P = 0.007). CONCLUSIONS Our data indicate an association of high apoA-IV concentrations with reduced frequencies of a history of cancer as well as incident fatal and non-fatal cancer events in a large cohort of patients with CKD.
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Affiliation(s)
- Barbara Kollerits
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstraße 41, Innsbruck, 6020, Austria
| | - Simon Gruber
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstraße 41, Innsbruck, 6020, Austria
| | - Inga Steinbrenner
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Johannes P Schwaiger
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstraße 41, Innsbruck, 6020, Austria
| | - Hansi Weissensteiner
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstraße 41, Innsbruck, 6020, Austria
| | - Sebastian Schönherr
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstraße 41, Innsbruck, 6020, Austria
| | - Lukas Forer
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstraße 41, Innsbruck, 6020, Austria
| | - Fruzsina Kotsis
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Department of Medicine IV - Nephrology and Primary Care, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Department of Medicine IV - Nephrology and Primary Care, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Heike Meiselbach
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- German Chronic Kidney Disease Study, Erlangen, Germany
| | - Christoph Wanner
- Division of Nephrology, Department of Internal Medicine I, University Hospital Würzburg, Würzburg, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- German Chronic Kidney Disease Study, Erlangen, Germany
- Department of Nephrology and Medical Intensive Care, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstraße 41, Innsbruck, 6020, Austria.
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3
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Sterenborg RBTM, Steinbrenner I, Li Y, Bujnis MN, Naito T, Marouli E, Galesloot TE, Babajide O, Andreasen L, Astrup A, Åsvold BO, Bandinelli S, Beekman M, Beilby JP, Bork-Jensen J, Boutin T, Brody JA, Brown SJ, Brumpton B, Campbell PJ, Cappola AR, Ceresini G, Chaker L, Chasman DI, Concas MP, Coutinho de Almeida R, Cross SM, Cucca F, Deary IJ, Kjaergaard AD, Echouffo Tcheugui JB, Ellervik C, Eriksson JG, Ferrucci L, Freudenberg J, Fuchsberger C, Gieger C, Giulianini F, Gögele M, Graham SE, Grarup N, Gunjača I, Hansen T, Harding BN, Harris SE, Haunsø S, Hayward C, Hui J, Ittermann T, Jukema JW, Kajantie E, Kanters JK, Kårhus LL, Kiemeney LALM, Kloppenburg M, Kühnel B, Lahti J, Langenberg C, Lapauw B, Leese G, Li S, Liewald DCM, Linneberg A, Lominchar JVT, Luan J, Martin NG, Matana A, Meima ME, Meitinger T, Meulenbelt I, Mitchell BD, Møllehave LT, Mora S, Naitza S, Nauck M, Netea-Maier RT, Noordam R, Nursyifa C, Okada Y, Onano S, Papadopoulou A, Palmer CNA, Pattaro C, Pedersen O, Peters A, Pietzner M, Polašek O, Pramstaller PP, Psaty BM, Punda A, Ray D, Redmond P, Richards JB, Ridker PM, Russ TC, Ryan KA, Olesen MS, Schultheiss UT, Selvin E, Siddiqui MK, Sidore C, Slagboom PE, Sørensen TIA, Soto-Pedre E, Spector TD, Spedicati B, Srinivasan S, Starr JM, Stott DJ, Tanaka T, Torlak V, Trompet S, Tuhkanen J, Uitterlinden AG, van den Akker EB, van den Eynde T, van der Klauw MM, van Heemst D, Verroken C, Visser WE, Vojinovic D, Völzke H, Waldenberger M, Walsh JP, Wareham NJ, Weiss S, Willer CJ, Wilson SG, Wolffenbuttel BHR, Wouters HJCM, Wright MJ, Yang Q, Zemunik T, Zhou W, Zhu G, Zöllner S, Smit JWA, Peeters RP, Köttgen A, Teumer A, Medici M. Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications. Nat Commun 2024; 15:888. [PMID: 38291025 PMCID: PMC10828500 DOI: 10.1038/s41467-024-44701-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 12/29/2023] [Indexed: 02/01/2024] Open
Abstract
To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases.
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Affiliation(s)
- Rosalie B T M Sterenborg
- Department of Internal Medicine, Division of Endocrinology, Radboud University Medical Center, Nijmegen, The Netherlands
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Inga Steinbrenner
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Yong Li
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | | | - Tatsuhiko Naito
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Eirini Marouli
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
- Digital Environment Research Institute, Queen Mary University of London, London, UK
| | - Tessel E Galesloot
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Oladapo Babajide
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Laura Andreasen
- Laboratory for Molecular Cardiology, Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Arne Astrup
- Department of Obesity and Nutritional Sciences, The Novo Nordisk Foundation, Hellerup, Denmark
| | - Bjørn Olav Åsvold
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Endocrinology, Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | | | - Marian Beekman
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - John P Beilby
- School of Biomedical Sciences, The University of Western Australia, Perth, WA, 6009, Australia
| | - Jette Bork-Jensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Thibaud Boutin
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Suzanne J Brown
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, 6009, Australia
| | - Ben Brumpton
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger, 7600, Norway
| | - Purdey J Campbell
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, 6009, Australia
| | - Anne R Cappola
- Division of Endocrinology, Diabetes, and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
| | - Graziano Ceresini
- Oncological Endocrinology, University of Parma, Parma, Italy
- Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Layal Chaker
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Centre, Rotterdam, The Netherlands
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, USA
- Harvard Medical School, Boston, USA
| | - Maria Pina Concas
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, Italy
| | - Rodrigo Coutinho de Almeida
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Simone M Cross
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Francesco Cucca
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, 09042, Monserrato (CA), Italy
- Università di Sassari, Dipartimento di Scienze Biomediche, V.le San Pietro, 07100, Sassari (SS), Italy
| | - Ian J Deary
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, EH8 9JZ, Edinburgh, United Kingdom
| | - Alisa Devedzic Kjaergaard
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Palle Juul-Jensens Blvd. 11, Entrance A, 8200, Aarhus, Denmark
| | - Justin B Echouffo Tcheugui
- Division of Endocrinology, Diabetes, and Metabolism, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
| | - Christina Ellervik
- Harvard Medical School, Boston, USA
- Faculty of Medical Science, Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Laboratory Medicine, Boston Children's Hospital, Boston, MA, USA
- Department of Clinical Biochemistry, Zealand University Hospital, Køge, Denmark
| | - Johan G Eriksson
- Department of General Practice and Primary health Care, University of Helsinki, Helsinki, Finland
- National University Singapore, Yong Loo Lin School of Medicine, Department of Obstetrics and Gynecology, Singapore, Singapore
| | - Luigi Ferrucci
- Longitudinal Study Section, National Institute on Aging, Baltimore, MD, USA
| | | | - Christian Fuchsberger
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Christian Gieger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Franco Giulianini
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, USA
| | - Martin Gögele
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Sarah E Graham
- Department of Internal Medicine, Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ivana Gunjača
- Department of Medical Biology, University of Split, School of Medicine, Split, Croatia
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Barbara N Harding
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Barcelona Institute for Global Health, Barcelona, Spain
| | - Sarah E Harris
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, EH8 9JZ, Edinburgh, United Kingdom
| | - Stig Haunsø
- Laboratory for Molecular Cardiology, Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Jennie Hui
- Pathwest Laboratory Medicine WA, Nedlands, WA, 6009, Australia
- School of Population and Global Health, The University of Western Australia, Crawley, WA, 6009, Australia
| | - Till Ittermann
- Institute for Community Medicine, University Medicine Greifswald, 17475, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Netherlands Heart Institute, Utrecht, the Netherlands
| | - Eero Kajantie
- Finnish Institute for Health and Welfare, Population Health Unit, Helsinki and Oulu, Oulu, Finland
- Clinical Medicine Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Jørgen K Kanters
- Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
- Center of Physiological Research, University of California San Francisco, San Francisco, USA
| | - Line L Kårhus
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
| | - Lambertus A L M Kiemeney
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Urology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Margreet Kloppenburg
- Departments of Rheumatology and Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Brigitte Kühnel
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Jari Lahti
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
- Computational Medicine, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Bruno Lapauw
- Department of Endocrinology, Ghent University Hospital, C. Heymanslaan 10, 9000, Ghent, Belgium
| | | | - Shuo Li
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - David C M Liewald
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, EH8 9JZ, Edinburgh, United Kingdom
| | - Allan Linneberg
- Center of Physiological Research, University of California San Francisco, San Francisco, USA
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jesus V T Lominchar
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | | | - Antonela Matana
- Department of Medical Biology, University of Split, School of Medicine, Split, Croatia
| | - Marcel E Meima
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Thomas Meitinger
- Institute for Human Genetics, Technical University of Munich, Munich, Germany
| | - Ingrid Meulenbelt
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Braxton D Mitchell
- University of Maryland School of Medicine, Division of Endocrinology, Diabetes and Nutrition, Baltimore, USA
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD, 21201, USA
| | - Line T Møllehave
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
| | - Samia Mora
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, USA
- Harvard Medical School, Boston, USA
| | - Silvia Naitza
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, 09042, Monserrato (CA), Italy
| | - Matthias Nauck
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Romana T Netea-Maier
- Department of Internal Medicine, Division of Endocrinology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Casia Nursyifa
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
- Premium Research Institute for Human Metaverse Medicine (WPI-PRIMe), Osaka University, Suita, Japan
| | - Stefano Onano
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, 09042, Monserrato (CA), Italy
| | - Areti Papadopoulou
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Colin N A Palmer
- Division of Population Health Genomics, School of Medicine, University of Dundee, DD19SY, Dundee, UK
| | - Cristian Pattaro
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Center for Clinical Metabolic Research, Herlev-Gentofte University Hospital, Copenhagen, Denmark
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Maik Pietzner
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
- Computational Medicine, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Ozren Polašek
- Department of Public Health, University of Split, School of Medicine, Split, Croatia
- Algebra University College, Zagreb, Croatia
| | - Peter P Pramstaller
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Departments of Epidemiology and Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Ante Punda
- Department of Nuclear Medicine, University Hospital Split, Split, Croatia
| | - Debashree Ray
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
| | - Paul Redmond
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, EH8 9JZ, Edinburgh, United Kingdom
| | - J Brent Richards
- Lady Davis Institute, Jewish General Hospital, Montreal, Quebec, H3T 1E2, Canada
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, USA
- Harvard Medical School, Boston, USA
| | - Tom C Russ
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, EH8 9JZ, Edinburgh, United Kingdom
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, United Kingdom
| | - Kathleen A Ryan
- University of Maryland School of Medicine, Division of Endocrinology, Diabetes and Nutrition, Baltimore, USA
| | - Morten Salling Olesen
- Laboratory for Molecular Cardiology, Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Department of Medicine IV - Nephrology and Primary Care, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Elizabeth Selvin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
| | - Moneeza K Siddiqui
- Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | - Carlo Sidore
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, 09042, Monserrato (CA), Italy
| | - P Eline Slagboom
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Thorkild I A Sørensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Public Health, Section of Epidemiology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Enrique Soto-Pedre
- Division of Population Health Genomics, School of Medicine, University of Dundee, DD19SY, Dundee, UK
| | - Tim D Spector
- The Department of Twin Research & Genetic Epidemiology, King's College London, St Thomas' Campus, Lambeth Palace Road, London, SE1 7EH, UK
| | - Beatrice Spedicati
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, Italy
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Sundararajan Srinivasan
- Division of Population Health Genomics, School of Medicine, University of Dundee, DD19SY, Dundee, UK
| | - John M Starr
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, United Kingdom
| | - David J Stott
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Toshiko Tanaka
- Longitudinal Study Section, National Institute on Aging, Baltimore, MD, USA
| | - Vesela Torlak
- Department of Nuclear Medicine, University Hospital Split, Split, Croatia
| | - Stella Trompet
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Johanna Tuhkanen
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Erik B van den Akker
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Leiden Computational Biology Center, Leiden University Medical Center, Leiden, The Netherlands
- Department of Pattern Recognition and Bioinformatics, Delft University of Technology, Delft, The Netherlands
| | - Tibbert van den Eynde
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Melanie M van der Klauw
- Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Diana van Heemst
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Charlotte Verroken
- Department of Endocrinology, Ghent University Hospital, C. Heymanslaan 10, 9000, Ghent, Belgium
| | - W Edward Visser
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Dina Vojinovic
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Centre, Rotterdam, The Netherlands
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, 17475, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - John P Walsh
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, 6009, Australia
- Medical School, The University of Western Australia, Crawley, WA, 6009, Australia
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Stefan Weiss
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Cristen J Willer
- Department of Internal Medicine, Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Scott G Wilson
- School of Biomedical Sciences, The University of Western Australia, Perth, WA, 6009, Australia
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, 6009, Australia
- The Department of Twin Research & Genetic Epidemiology, King's College London, St Thomas' Campus, Lambeth Palace Road, London, SE1 7EH, UK
| | - Bruce H R Wolffenbuttel
- Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Hanneke J C M Wouters
- Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
| | - Qiong Yang
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - Tatijana Zemunik
- Department of Medical Biology, University of Split, School of Medicine, Split, Croatia
- Department of Nuclear Medicine, University Hospital Split, Split, Croatia
| | - Wei Zhou
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Gu Zhu
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Sebastian Zöllner
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Johannes W A Smit
- Department of Internal Medicine, Division of Endocrinology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Robin P Peeters
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
- CIBSS - Centre for Integrative Biological Signalling Studies, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, 17475, Greifswald, Germany.
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany.
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Bialystok, Poland.
| | - Marco Medici
- Department of Internal Medicine, Division of Endocrinology, Radboud University Medical Center, Nijmegen, The Netherlands.
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands.
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Ruhe J, Nadal J, Bärthlein B, Meiselbach H, Schultheiss UT, Kotsis F, Stockmann H, Krane V, Sommerer C, Löffler I, Saritas T, Kielstein JT, Sitter T, Schneider MP, Schmid M, Wanner C, Eckardt KU, Wolf G, Busch M. Cardiovascular risk due to diabetes mellitus in patients with chronic kidney disease-prospective data from the German Chronic Kidney Disease cohort. Clin Kidney J 2023; 16:2032-2040. [PMID: 37915914 PMCID: PMC10616496 DOI: 10.1093/ckj/sfad194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Indexed: 11/03/2023] Open
Abstract
Background Diabetes mellitus (DM) and chronic kidney disease (CKD) are well-known cardiovascular and mortality risk factors. To what extent they act in an additive manner and whether the etiology of CKD modifies the risk is uncertain. Methods The multicenter, prospective, observational German Chronic Kidney Disease study comprises 5217 participants (1868 with DM) with a baseline mean estimated glomerular filtration rate of 30-60 mL/min/1.73 m2 and/or proteinuria >0.5 g/day. We categorized patients whose CKD was caused by cardiovascular or metabolic diseases (CKDcvm) with and without DM, as opposed to genuine CKD (CKDgen) with and without DM. Recorded outcomes were first events of non-cardiovascular and cardiovascular death, 4-point major adverse cardiovascular events (4-point MACE) and hospitalization for heart failure (HHF). Results During the 6.5-year follow-up 603 (12%) non-cardiovascular and 209 (4%) cardiovascular deaths, 645 (12%) 4-point MACE, and 398 (8%) HHF were observed, most frequently in patients with DM having CKDcvm. DM increased the risk of non-cardiovascular [hazard ratio (HR) 1.92; 95% confidence interval (CI) 1.59-2.32] and cardiovascular (HR 2.25; 95% CI 1.62-3.12) deaths, 4-point MACE (HR 1.93; 95% CI 1.62-2.31) and HHF (HR 1.87; 95% CI 1.48-2.36). Mortality risks were elevated by DM to a similar extent in CKDcvm and CKDgen, but for HHF in CKDcvm only (HR 2.07; 95% CI 1.55-2.77). In patients with DM, CKDcvm (versus CKDgen) only increased the risk for HHF (HR 1.93; 95% CI 1.15-3.22). Conclusions DM contributes to cardiovascular and mortality excess risk in patients with moderate to severe CKD in both, CKDcvm and CKDgen. Patients with DM and CKDcvm are particularly susceptible to HHF.
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Affiliation(s)
- Johannes Ruhe
- Department of Internal Medicine III, Nephrology, University Hospital Jena – Friedrich Schiller University, Jena, Germany
| | - Jennifer Nadal
- Department of Medical Biometry, Informatics, and Epidemiology, University Hospital Bonn, Bonn, Germany
| | - Barbara Bärthlein
- Medical Centre for Information and Communication Technology, University Hospital Erlangen, Erlangen, Germany
| | - Heike Meiselbach
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
- Departmentof Medicine IV-Nephrology and Primary Care, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Fruzsina Kotsis
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
- Departmentof Medicine IV-Nephrology and Primary Care, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Helena Stockmann
- Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Vera Krane
- Division of Nephrology, Department of Medicine I, University Hospital Würzburg, Würzburg, Germany
| | - Claudia Sommerer
- Nephrology Unit, University Hospital Heidelberg, Heidelberg, Germany
| | - Ivonne Löffler
- Department of Internal Medicine III, Nephrology, University Hospital Jena – Friedrich Schiller University, Jena, Germany
| | - Turgay Saritas
- Division of Nephrology and Clinical Immunology, University Hospital RWTH Aachen, Aachen, Germany
| | - Jan T Kielstein
- Medical Clinic V Nephrology, Rheumatology, Blood Purification – Academic Teaching Hospital Braunschweig, Braunschweig, Germany
| | - Thomas Sitter
- Department of Medicine, Ludwig-Maximilians-University Hospital Munich, Munich, Germany
| | - Markus P Schneider
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Matthias Schmid
- Department of Medical Biometry, Informatics, and Epidemiology, University Hospital Bonn, Bonn, Germany
| | - Christoph Wanner
- Division of Nephrology, Department of Medicine I, University Hospital Würzburg, Würzburg, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
- Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Gunter Wolf
- Department of Internal Medicine III, Nephrology, University Hospital Jena – Friedrich Schiller University, Jena, Germany
| | - Martin Busch
- Department of Internal Medicine III, Nephrology, University Hospital Jena – Friedrich Schiller University, Jena, Germany
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Schumann A, Schultheiss UT, Ferreira CR, Blau N. Clinical and biochemical footprints of inherited metabolic diseases. XIV. Metabolic kidney diseases. Mol Genet Metab 2023; 140:107683. [PMID: 37597335 DOI: 10.1016/j.ymgme.2023.107683] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 08/11/2023] [Accepted: 08/11/2023] [Indexed: 08/21/2023]
Abstract
Kidney disease is a global health burden with high morbidity and mortality. Causes of kidney disease are numerous, extending from common disease groups like diabetes and arterial hypertension to rare conditions including inherited metabolic diseases (IMDs). Given its unique anatomy and function, the kidney is a target organ in about 10% of known IMDs, emphasizing the relevant contribution of IMDs to kidney disease. The pattern of injury affects all segments of the nephron including glomerular disease, proximal and distal tubular damage, kidney cyst formation, built-up of nephrocalcinosis and stones as well as severe malformations. We revised and updated the list of known metabolic etiologies associated with kidney involvement and found 190 relevant IMDs. This represents the 14th of a series of educational articles providing a comprehensive and revised list of metabolic differential diagnoses according to system involvement.
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Affiliation(s)
- Anke Schumann
- Department of General Paediatrics, Adolescent Medicine and Neonatology, Medical Center-University of Freiburg, Faculty of Medicine, Freiburg, Germany.
| | - Ulla T Schultheiss
- Department of Medicine IV, Nephrology and Primary Care, Faculty of Medicine, and Medical Center, University of Freiburg, Institute of Genetic Epidemiology, Freiburg, Germany.
| | - Carlos R Ferreira
- National Human Genome Research Institute, National Institutes of Health, Bethesda, USA.
| | - Nenad Blau
- Division of Metabolism, University Children's Hospital, Zürich, Switzerland.
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Schneider MP, Schmid M, Nadal J, Krane V, Saritas T, Busch M, Schultheiss UT, Meiselbach H, Friedrich N, Nauck M, Floege J, Kronenberg F, Wanner C, Eckardt KU. Copeptin, Natriuretic Peptides, and Cardiovascular Outcomes in Patients With CKD: The German Chronic Kidney Disease (GCKD) Study. Kidney Med 2023; 5:100725. [PMID: 37915964 PMCID: PMC10616426 DOI: 10.1016/j.xkme.2023.100725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2023] Open
Abstract
Rationale & Objective Copeptin and Midrange pro-atrial natriuretic peptide (MR-pro-ANP) are associated with outcomes independently of N-terminal pro-brain natriuretic peptide (NT-pro-BNP) in patients with heart failure (HF). The value of these markers in patients with chronic kidney disease (CKD) has not been studied. Study Design Prospective cohort study. Setting & Participants A total of 4,417 patients enrolled in the German Chronic Kidney Disease (GCKD) study with an estimated glomerular filtration rate of 30-60 mL/min/1.73m2 or overt proteinuria (urinary albumin-creatinine ratio >300mg/g or equivalent). Exposures Copeptin, MR-pro-ANP, and NT-pro-BNP levels were measured in baseline samples. Outcomes Noncardiovascular death, cardiovascular (CV) death, major adverse CV event (MACE), and hospitalization for HF. Analytical Approach HRs for associations of Copeptin, MR-pro-ANP, and NT-pro-BNP with outcomes were estimated using Cox regression analyses adjusted for established risk factors. Results During a maximum follow-up of 6.5 years, 413 non-CV deaths, 179 CV deaths, 519 MACE, and 388 hospitalizations for HF were observed. In Cox regression analyses adjusted for established risk factors, each one of the 3 markers were associated with all the 4 outcomes, albeit the highest HRs were found for NT-pro-BNP. When models were extended to include all the 3 markers, NT-pro-BNP remained associated with all 4 outcomes. Conversely, from the 2 novel markers, associations remained only for Copeptin with non-CV death (HR, 1.62; 95% CI, 1.04-2.54 for highest vs lowest quintile) and with hospitalizations for HF (HR, 1.73; 95% CI, 1.08-2.75). Limitations Single-point measurements of Copeptin, MR-pro-ANP, and NT-pro-BNP. Conclusions In patients with moderately severe CKD, we confirm NT-pro-BNP to be strongly associated with all outcomes examined. As the main finding, the novel marker Copeptin demonstrated independent associations with non-CV death and hospitalizations for HF, and should therefore be evaluated further for risk assessment in CKD. Plain-Language Summary A blood sample-based biomarker that indicates high cardiovascular risk in a patient with kidney disease would help to guide interventions and has the potential to improve outcomes. In 4,417 patients of the German Chronic Kidney Disease study, we assessed the relationship of Copeptin, pro-atrial natriuretic peptide, and N-terminal pro-brain natriuretic peptide (NT-pro-BNP) with important outcomes over a follow-up period of 6.5 years. NT-pro-BNP was strongly associated with all of the 4 outcomes, including death unrelated to cardiovascular disease, death because of cardiovascular disease, a major cardiovascular event, and hospitalization for heart failure. Copeptin was associated with death unrelated to cardiovascular disease and hospitalization for heart failure. NT-pro-BNP and Copeptin are, therefore, promising candidates for a blood sample-based strategy to identify patients with kidney disease at high cardiovascular risk.
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Affiliation(s)
- Markus P. Schneider
- Department of Nephrology and Hypertension, Universitätsklinikum Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Matthias Schmid
- Department of Medical Biometry, Informatics, and Epidemiology (IMBIE), University Hospital Bonn, Bonn, Germany
| | - Jennifer Nadal
- Department of Medical Biometry, Informatics, and Epidemiology (IMBIE), University Hospital Bonn, Bonn, Germany
| | - Vera Krane
- Department of Medicine 1, Division of Nephrology, University Hospital Würzburg, Würzburg, Germany
| | - Turgay Saritas
- Department of Nephrology and Clinical Immunology, University Hospital RWTH Aachen, Aachen, Germany
| | - Martin Busch
- Department of Internal Medicine III, University Hospital Jena, Friedrich-Schiller Universität, Jena, Germany
| | - Ulla T. Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center and Department of Medicine IV – Nephrology and Primary Care, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Heike Meiselbach
- Department of Nephrology and Hypertension, Universitätsklinikum Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Nele Friedrich
- Institute of Clinical Chemistry and Laboratory Medicine, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, University Medicine, Greifswald, Germany
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, University Medicine, Greifswald, Germany
| | - Jürgen Floege
- Department of Nephrology and Clinical Immunology, University Hospital RWTH Aachen, Aachen, Germany
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Austria
| | - Christoph Wanner
- Department of Medicine 1, Division of Nephrology, University Hospital Würzburg, Würzburg, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, Universitätsklinikum Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
- Department of Nephrology and Medical Intensive Care, Charité – Universitätsmedizin Berlin, Germany
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Sommerer C, Müller-Krebs S, Nadal J, Schultheiss UT, Friedrich N, Nauck M, Schmid M, Nußhag C, Reiser J, Eckardt KU, Zeier M, Hayek SS. Prospective Cohort Study of Soluble Urokinase Plasminogen Activation Receptor and Cardiovascular Events in Patients With CKD. Kidney Int Rep 2023; 8:2265-2275. [PMID: 38025216 PMCID: PMC10658273 DOI: 10.1016/j.ekir.2023.08.038] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 08/28/2023] [Indexed: 12/01/2023] Open
Abstract
Introduction Soluble urokinase plasminogen activation receptor (suPAR) is an immune-derived pathogenic factor for kidney and atherosclerotic disease. Whether the association between suPAR and cardiovascular (CV) outcomes is dependent on the severity of underlying kidney disease is unclear. Methods We measured serum suPAR levels in 4994 participants (mean age 60 years; 60% men; 36% with diabetes mellitus; mean estimated glomerular filtration rate (eGFR) 49 ml/min per 1.73 m2, SD 18) of the German Chronic Kidney Disease (GCKD) cohort and examined its association with all-cause death, CV death, and major CV events (MACE) across the range of eGFR and urine albumin-to-creatinine ratio (UACR). Results The median suPAR level was 1771 pg/ml (interquartile range [IQR] 1447-2254 pg/ml). SuPAR levels were positively and independently correlated with age, eGFR, UACR, and parathyroid hormone levels. There were 573 deaths, including 190 CV deaths and 683 MACE events at a follow-up time of 6.5 years. In multivariable analyses, suPAR levels (log2) were associated with all-cause death (hazard ratio [HR] 1.36, 95% confidence interval [CI] 1.21-1.53), CV death (HR 1.27, 95% CI 1.03-1.57), and MACE (HR 1.13, 95% CI 1.00-1.28), and were not found to differ according to diabetes mellitus status, baseline eGFR, UACR, or parathyroid hormone levels. In mediation analysis, suPAR's direct effect on all-cause death, CV death, and MACE accounted for 77%, 67%, and 60% of the total effect, respectively; whereas the effect mediated through eGFR accounted for 23%, 34%, and 40%, respectively. Conclusion In a large cohort of individuals with chronic kidney disease (CKD), suPAR levels were associated with mortality and CV outcomes independently of indices of kidney function, consistent with its independent role in the pathogenesis of atherosclerosis.
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Affiliation(s)
- Claudia Sommerer
- Department of Nephrology, University Hospital Heidelberg, Renal Center, Heidelberg, Germany
| | - Sandra Müller-Krebs
- Department of Nephrology, University Hospital Heidelberg, Renal Center, Heidelberg, Germany
| | - Jennifer Nadal
- Department of Medical Biometry, Informatics, and Epidemiology (IMBIE), University Hospital Bonn, Bonn, Germany
| | - Ulla T. Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
- Department of Medicine IV, Nephrology and Primary Care, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Nele Friedrich
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, University Medicine, Greifswald, Germany
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, University Medicine, Greifswald, Germany
| | - Matthias Schmid
- Department of Medical Biometry, Informatics, and Epidemiology (IMBIE), University Hospital Bonn, Bonn, Germany
| | - Christian Nußhag
- Department of Nephrology, University Hospital Heidelberg, Renal Center, Heidelberg, Germany
| | - Jochen Reiser
- Department of Medicine, Rush University Medical Center, Chicago, Illinois, USA
| | - Kai-Uwe Eckardt
- Department of Nephrology and Medical Intensive Care, Charité, Universitätsmedizin Berlin, Berlin, Germany
- Department of Nephrology and Hypertension, Universitätsklinikum Erlangen, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Martin Zeier
- Department of Nephrology, University Hospital Heidelberg, Renal Center, Heidelberg, Germany
| | - Salim S. Hayek
- Department of Medicine, Division of Cardiology, University of Michigan, Michigan, USA
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8
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Kotsis F, Bächle H, Altenbuchinger M, Dönitz J, Njipouombe Nsangou YA, Meiselbach H, Kosch R, Salloch S, Bratan T, Zacharias HU, Schultheiss UT. Expectation of clinical decision support systems: a survey study among nephrologist end-users. BMC Med Inform Decis Mak 2023; 23:239. [PMID: 37884906 PMCID: PMC10605935 DOI: 10.1186/s12911-023-02317-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 09/29/2023] [Indexed: 10/28/2023] Open
Abstract
BACKGROUND Chronic kidney disease (CKD), a major public health problem with differing disease etiologies, leads to complications, comorbidities, polypharmacy, and mortality. Monitoring disease progression and personalized treatment efforts are crucial for long-term patient outcomes. Physicians need to integrate different data levels, e.g., clinical parameters, biomarkers, and drug information, with medical knowledge. Clinical decision support systems (CDSS) can tackle these issues and improve patient management. Knowledge about the awareness and implementation of CDSS in Germany within the field of nephrology is scarce. PURPOSE Nephrologists' attitude towards any CDSS and potential CDSS features of interest, like adverse event prediction algorithms, is important for a successful implementation. This survey investigates nephrologists' experiences with and expectations towards a useful CDSS for daily medical routine in the outpatient setting. METHODS The 38-item questionnaire survey was conducted either by telephone or as a do-it-yourself online interview amongst nephrologists across all of Germany. Answers were collected and analysed using the Electronic Data Capture System REDCap, as well as Stata SE 15.1, and Excel. The survey consisted of four modules: experiences with CDSS (M1), expectations towards a helpful CDSS (M2), evaluation of adverse event prediction algorithms (M3), and ethical aspects of CDSS (M4). Descriptive statistical analyses of all questions were conducted. RESULTS The study population comprised 54 physicians, with a response rate of about 80-100% per question. Most participants were aged between 51-60 years (45.1%), 64% were male, and most participants had been working in nephrology out-patient clinics for a median of 10.5 years. Overall, CDSS use was poor (81.2%), often due to lack of knowledge about existing CDSS. Most participants (79%) believed CDSS to be helpful in the management of CKD patients with a high willingness to try out a CDSS. Of all adverse event prediction algorithms, prediction of CKD progression (97.8%) and in-silico simulations of disease progression when changing, e. g., lifestyle or medication (97.7%) were rated most important. The spectrum of answers on ethical aspects of CDSS was diverse. CONCLUSION This survey provides insights into experience with and expectations of out-patient nephrologists on CDSS. Despite the current lack of knowledge on CDSS, the willingness to integrate CDSS into daily patient care, and the need for adverse event prediction algorithms was high.
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Affiliation(s)
- Fruzsina Kotsis
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Department of Medicine IV - Nephrology and Primary Care, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Helena Bächle
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Michael Altenbuchinger
- Department of Medical Bioinformatics, University Medical Center Göttingen, Göttingen, Germany
| | - Jürgen Dönitz
- Department of Medical Bioinformatics, University Medical Center Göttingen, Göttingen, Germany
- Institute of Computational Biology, Helmholtz Zentrum München, Munich, Germany
| | | | - Heike Meiselbach
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Robin Kosch
- Department of Medical Bioinformatics, University Medical Center Göttingen, Göttingen, Germany
| | - Sabine Salloch
- Institute for Ethics, History and Philosophy of Medicine, Hannover Medical School, Hanover, Germany
| | - Tanja Bratan
- Competence Center Emerging Technologies, Fraunhofer Institute for Systems and Innovation Research ISI, Karlsruhe, Germany
| | - Helena U Zacharias
- Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, Hanover, Germany
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.
- Department of Medicine IV - Nephrology and Primary Care, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.
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9
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Reimer KC, Nadal J, Meiselbach H, Schmid M, Schultheiss UT, Kotsis F, Stockmann H, Friedrich N, Nauck M, Krane V, Eckardt KU, Schneider MP, Kramann R, Floege J, Saritas T. Association of mineral and bone biomarkers with adverse cardiovascular outcomes and mortality in the German Chronic Kidney Disease (GCKD) cohort. Bone Res 2023; 11:52. [PMID: 37857629 PMCID: PMC10587182 DOI: 10.1038/s41413-023-00291-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 09/07/2023] [Indexed: 10/21/2023] Open
Abstract
Mineral and bone disorder (MBD) in chronic kidney disease (CKD) is tightly linked to cardiovascular disease (CVD). In this study, we aimed to compare the prognostic value of nine MBD biomarkers to determine those associated best with adverse cardiovascular (CV) outcomes and mortality. In 5 217 participants of the German CKD (GCKD) study enrolled with an estimated glomerular filtration rate (eGFR) between 30-60 mL·min-1 per 1.73 m2 or overt proteinuria, serum osteoprotegerin (OPG), C-terminal fibroblast growth factor-23 (FGF23), intact parathyroid hormone (iPTH), bone alkaline phosphatase (BAP), cross-linked C-telopeptide of type 1 collagen (CTX1), procollagen 1 intact N-terminal propeptide (P1NP), phosphate, calcium, and 25-OH vitamin D were measured at baseline. Participants with missing values among these parameters (n = 971) were excluded, leaving a total of 4 246 participants for analysis. During a median follow-up of 6.5 years, 387 non-CV deaths, 173 CV deaths, 645 nonfatal major adverse CV events (MACEs) and 368 hospitalizations for congestive heart failure (CHF) were observed. OPG and FGF23 were associated with all outcomes, with the highest hazard ratios (HRs) for OPG. In the final Cox regression model, adjusted for CV risk factors, including kidney function and all other investigated biomarkers, each standard deviation increase in OPG was associated with non-CV death (HR 1.76, 95% CI: 1.35-2.30), CV death (HR 2.18, 95% CI: 1.50-3.16), MACE (HR 1.38, 95% CI: 1.12-1.71) and hospitalization for CHF (HR 2.05, 95% CI: 1.56-2.69). Out of the nine biomarkers examined, stratification based on serum OPG best identified the CKD patients who were at the highest risk for any adverse CV outcome and mortality.
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Affiliation(s)
- Katharina Charlotte Reimer
- Department of Nephrology, Rheumatology, and Clinical Immunology, University Hospital RWTH Aachen, Aachen, Germany
- Institute of Experimental Medicine and Systems Biology, RWTH Aachen University, Aachen, Germany
- Institute for Cell and Tumor Biology, RWTH Aachen University, Aachen, Germany
| | - Jennifer Nadal
- Institute of Medical Biometry, Informatics and Epidemiology, University Hospital of Bonn, Bonn, Germany
| | - Heike Meiselbach
- Department of Nephrology and Hypertension, University of Erlangen-Nürnberg, Erlangen, Germany
| | - Matthias Schmid
- Institute of Medical Biometry, Informatics and Epidemiology, University Hospital of Bonn, Bonn, Germany
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Department of Medicine IV - Nephrology and Primary Care, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Fruzsina Kotsis
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Department of Medicine IV - Nephrology and Primary Care, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Helena Stockmann
- Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Department of Nephrology, University Medical Center Regensburg, Regensburg, Germany
| | - Nele Friedrich
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, University Medicine, Greifswald, Germany
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, University Medicine, Greifswald, Germany
| | - Vera Krane
- Department of Medicine I, Division of Nephrology, University Hospital Würzburg, Würzburg, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, University of Erlangen-Nürnberg, Erlangen, Germany
- Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Markus P Schneider
- Department of Nephrology and Hypertension, University of Erlangen-Nürnberg, Erlangen, Germany
| | - Rafael Kramann
- Department of Nephrology, Rheumatology, and Clinical Immunology, University Hospital RWTH Aachen, Aachen, Germany
- Institute of Experimental Medicine and Systems Biology, RWTH Aachen University, Aachen, Germany
| | - Jürgen Floege
- Department of Nephrology, Rheumatology, and Clinical Immunology, University Hospital RWTH Aachen, Aachen, Germany
| | - Turgay Saritas
- Department of Nephrology, Rheumatology, and Clinical Immunology, University Hospital RWTH Aachen, Aachen, Germany.
- Institute of Experimental Medicine and Systems Biology, RWTH Aachen University, Aachen, Germany.
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Schlosser P, Scherer N, Grundner-Culemann F, Monteiro-Martins S, Haug S, Steinbrenner I, Uluvar B, Wuttke M, Cheng Y, Ekici AB, Gyimesi G, Karoly ED, Kotsis F, Mielke J, Gomez MF, Yu B, Grams ME, Coresh J, Boerwinkle E, Köttgen M, Kronenberg F, Meiselbach H, Mohney RP, Akilesh S, Schmidts M, Hediger MA, Schultheiss UT, Eckardt KU, Oefner PJ, Sekula P, Li Y, Köttgen A. Genetic studies of paired metabolomes reveal enzymatic and transport processes at the interface of plasma and urine. Nat Genet 2023:10.1038/s41588-023-01409-8. [PMID: 37277652 DOI: 10.1038/s41588-023-01409-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 04/26/2023] [Indexed: 06/07/2023]
Abstract
The kidneys operate at the interface of plasma and urine by clearing molecular waste products while retaining valuable solutes. Genetic studies of paired plasma and urine metabolomes may identify underlying processes. We conducted genome-wide studies of 1,916 plasma and urine metabolites and detected 1,299 significant associations. Associations with 40% of implicated metabolites would have been missed by studying plasma alone. We detected urine-specific findings that provide information about metabolite reabsorption in the kidney, such as aquaporin (AQP)-7-mediated glycerol transport, and different metabolomic footprints of kidney-expressed proteins in plasma and urine that are consistent with their localization and function, including the transporters NaDC3 (SLC13A3) and ASBT (SLC10A2). Shared genetic determinants of 7,073 metabolite-disease combinations represent a resource to better understand metabolic diseases and revealed connections of dipeptidase 1 with circulating digestive enzymes and with hypertension. Extending genetic studies of the metabolome beyond plasma yields unique insights into processes at the interface of body compartments.
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Affiliation(s)
- Pascal Schlosser
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
| | - Nora Scherer
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Spemann Graduate School of Biology and Medicine, University of Freiburg, Freiburg, Germany
| | - Franziska Grundner-Culemann
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Sara Monteiro-Martins
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Stefan Haug
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Inga Steinbrenner
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Burulça Uluvar
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Matthias Wuttke
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Yurong Cheng
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Arif B Ekici
- Institute of Human Genetics, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Gergely Gyimesi
- Membrane Transport Discovery Lab, Department of Nephrology and Hypertension and Department of Biomedical Research, University of Bern, Bern, Switzerland
| | | | - Fruzsina Kotsis
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Department of Medicine IV-Nephrology and Primary Care, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Johanna Mielke
- Research and Early Development, Pharmaceuticals Division, Bayer AG, Wuppertal, Germany
| | - Maria F Gomez
- Department of Clinical Sciences in Malmö, Lund University Diabetes Centre, Lund University, Lund, Sweden
| | - Bing Yu
- Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Morgan E Grams
- New York University Grossman School of Medicine, New York, NY, USA
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Eric Boerwinkle
- Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Michael Köttgen
- Department of Medicine IV-Nephrology and Primary Care, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
- Centre for Integrative Biological Signalling Studies (CIBSS), Albert-Ludwigs-University Freiburg, Freiburg, Germany
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Department of Genetics, Medical University of Innsbruck, Innsbruck, Austria
| | - Heike Meiselbach
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | | | - Shreeram Akilesh
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Miriam Schmidts
- Centre for Integrative Biological Signalling Studies (CIBSS), Albert-Ludwigs-University Freiburg, Freiburg, Germany
- Freiburg University Faculty of Medicine, Center for Pediatrics and Adolescent Medicine, University Hospital Freiburg, Freiburg, Germany
| | - Matthias A Hediger
- Membrane Transport Discovery Lab, Department of Nephrology and Hypertension and Department of Biomedical Research, University of Bern, Bern, Switzerland
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Department of Medicine IV-Nephrology and Primary Care, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Peter J Oefner
- Institute of Functional Genomics, University of Regensburg, Regensburg, Germany
| | - Peggy Sekula
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Yong Li
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
- Centre for Integrative Biological Signalling Studies (CIBSS), Albert-Ludwigs-University Freiburg, Freiburg, Germany.
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11
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Cejka V, Störk S, Nadal J, Schmid M, Sommerer C, Sitter T, Meiselbach H, Busch M, Schneider MP, Saritas T, Schultheiss UT, Kotsis F, Wanner C, Eckardt KU, Krane V. Differential prognostic utility of adiposity measures in chronic kidney disease. J Ren Nutr 2023:S1051-2276(23)00066-3. [PMID: 37116626 DOI: 10.1053/j.jrn.2023.04.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 02/12/2023] [Accepted: 04/09/2023] [Indexed: 04/30/2023] Open
Abstract
OBJECTIVE Adipose tissue contributes to adverse outcomes in chronic kidney disease (CKD), but there is uncertainty regarding the prognostic relevance of different adiposity measures. We analyzed the associations of neck circumference (NC), waist circumference (WC), and body mass index (BMI) with clinical outcomes in patients with mild to severe CKD. METHODS The German Chronic Kidney Disease (GCKD) study is a prospective cohort study, which enrolled Caucasian adults with mild to severe CKD, defined as estimated glomerular filtration rate (eGFR): 30-60 mL/min/1.73 m2, or >60 mL/min/1.73 m2 in the presence of overt proteinuria. Associations of NC, WC and BMI with all-cause death, major cardiovascular events (MACE: a composite of non-fatal stroke, non-fatal myocardial infarction, peripheral artery disease intervention, and cardiovascular death), kidney failure (a composite of dialysis or transplantation) were analyzed using multivariable Cox proportional hazards regression models adjusted for confounders and the Akaike information criteria (AIC) were calculated. Models included sex interactions with adiposity measures. RESULTS A total of 4537 participants (59% male) were included in the analysis. During a 6.5-year follow-up, 339 participants died, 510 experienced MACE, and 341 developed kidney failure. In fully adjusted models, NC was associated with all-cause death in women (HR 1.080 per cm; 95% CI 1.009-1.155), but not in men. Irrespective of sex, WC was associated with all-cause death (HR 1.014 per cm; 95% CI 1.005-1.038). NC and WC showed no association with MACE or kidney failure. BMI was not associated with any of the analyzed outcomes. Models of all-cause death including WC offered the best (lowest) AIC. CONCLUSION In Caucasian patients with mild to severe CKD, higher NC (in women) and WC were significantly associated with increased risk of death from any cause, but BMI was not.
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Affiliation(s)
- Vladimir Cejka
- Department Clinical Research and Epidemiology, Comprehensive Heart Failure Center, University Hospital Würzburg, Würzburg, Germany.
| | - Stefan Störk
- Department Clinical Research and Epidemiology, Comprehensive Heart Failure Center, University Hospital Würzburg, Würzburg, Germany; Department of Medicine I - Cardiology, University Hospital of Würzburg, Würzburg, Germany
| | - Jennifer Nadal
- Institute for Medical Biometry, Informatics and Epidemiology, University Hospital Bonn, Bonn, Germany
| | - Matthias Schmid
- Institute for Medical Biometry, Informatics and Epidemiology, University Hospital Bonn, Bonn, Germany
| | - Claudia Sommerer
- Department of Nephrology, University of Heidelberg, Heidelberg, Germany
| | - Thomas Sitter
- Department of Medicine, Ludwig-Maximilians-University Hospital, Munich, Germany
| | - Heike Meiselbach
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Martin Busch
- Department of Internal Medicine III, University Hospital Jena, Jena, Germany
| | - Markus P Schneider
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Turgay Saritas
- Division of Nephrology and Clinical Immunology, University Hospital RWTH Aachen, Aachen, Germany
| | - Ulla T Schultheiss
- Department of Medicine IV - Nephrology and Primary Care, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany; Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Fruzsina Kotsis
- Department of Medicine IV - Nephrology and Primary Care, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany; Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Christoph Wanner
- Department Clinical Research and Epidemiology, Comprehensive Heart Failure Center, University Hospital Würzburg, Würzburg, Germany; Department of Internal Medicine I - Division of Nephrology, University Hospital of Würzburg, Würzburg, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany; Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Vera Krane
- Department Clinical Research and Epidemiology, Comprehensive Heart Failure Center, University Hospital Würzburg, Würzburg, Germany; Department of Internal Medicine I - Division of Nephrology, University Hospital of Würzburg, Würzburg, Germany
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12
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Gregorich M, Kammer M, Heinzel A, Böger C, Eckardt KU, Heerspink HL, Jung B, Mayer G, Meiselbach H, Schmid M, Schultheiss UT, Heinze G, Oberbauer R. Development and Validation of a Prediction Model for Future Estimated Glomerular Filtration Rate in People With Type 2 Diabetes and Chronic Kidney Disease. JAMA Netw Open 2023; 6:e231870. [PMID: 37017968 PMCID: PMC10077108 DOI: 10.1001/jamanetworkopen.2023.1870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/06/2023] Open
Abstract
Importance Type 2 diabetes increases the risk of progressive diabetic kidney disease, but reliable prediction tools that can be used in clinical practice and aid in patients' understanding of disease progression are currently lacking. Objective To develop and externally validate a model to predict future trajectories in estimated glomerular filtration rate (eGFR) in adults with type 2 diabetes and chronic kidney disease using data from 3 European multinational cohorts. Design, Setting, and Participants This prognostic study used baseline and follow-up information collected between February 2010 and December 2019 from 3 prospective multinational cohort studies: PROVALID (Prospective Cohort Study in Patients with Type 2 Diabetes Mellitus for Validation of Biomarkers), GCKD (German Chronic Kidney Disease), and DIACORE (Diabetes Cohorte). A total of 4637 adult participants (aged 18-75 years) with type 2 diabetes and mildly to moderately impaired kidney function (baseline eGFR of ≥30 mL/min/1.73 m2) were included. Data were analyzed between June 30, 2021, and January 31, 2023. Main Outcomes and Measures Thirteen variables readily available from routine clinical care visits (age, sex, body mass index; smoking status; hemoglobin A1c [mmol/mol and percentage]; hemoglobin, and serum cholesterol levels; mean arterial pressure, urinary albumin-creatinine ratio, and intake of glucose-lowering, blood-pressure lowering, or lipid-lowering medication) were selected as predictors. Repeated eGFR measurements at baseline and follow-up visits were used as the outcome. A linear mixed-effects model for repeated eGFR measurements at study entry up to the last recorded follow-up visit (up to 5 years after baseline) was fit and externally validated. Results Among 4637 adults with type 2 diabetes and chronic kidney disease (mean [SD] age at baseline, 63.5 [9.1] years; 2680 men [57.8%]; all of White race), 3323 participants from the PROVALID and GCKD studies (mean [SD] age at baseline, 63.2 [9.3] years; 1864 men [56.1%]) were included in the model development cohort, and 1314 participants from the DIACORE study (mean [SD] age at baseline, 64.5 [8.3] years; 816 men [62.1%]) were included in the external validation cohort, with a mean (SD) follow-up of 5.0 (0.6) years. Updating the random coefficient estimates with baseline eGFR values yielded improved predictive performance, which was particularly evident in the visual inspection of the calibration curve (calibration slope at 5 years: 1.09; 95% CI, 1.04-1.15). The prediction model had good discrimination in the validation cohort, with the lowest C statistic at 5 years after baseline (0.79; 95% CI, 0.77-0.80). The model also had predictive accuracy, with an R2 ranging from 0.70 (95% CI, 0.63-0.76) at year 1 to 0.58 (95% CI, 0.53-0.63) at year 5. Conclusions and Relevance In this prognostic study, a reliable prediction model was developed and externally validated; the robust model was well calibrated and capable of predicting kidney function decline up to 5 years after baseline. The results and prediction model are publicly available in an accompanying web-based application, which may open the way for improved prediction of individual eGFR trajectories and disease progression.
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Affiliation(s)
- Mariella Gregorich
- Center for Medical Data Science, Section for Clinical Biometrics, Medical University of Vienna, Vienna, Austria
- Division of Nephrology and Dialysis, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria
| | - Michael Kammer
- Center for Medical Data Science, Section for Clinical Biometrics, Medical University of Vienna, Vienna, Austria
- Division of Nephrology and Dialysis, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria
| | - Andreas Heinzel
- Division of Nephrology and Dialysis, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria
| | - Carsten Böger
- Department of Nephrology, University of Regensburg, University Hospital Regensburg, Regensburg, Germany
- Department of Nephrology, Diabetology, and Rheumatology, Traunstein Hospital, Southeast Bavarian Clinics, Traunstein, Germany
- KfH Kidney Center Traunstein, Traunstein, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Medical Intensive Care, Charité University Medicine Berlin, Berlin, Germany
- Department of Nephrology and Hypertension, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Hiddo Lambers Heerspink
- Department of Clinical Pharmacy and Pharmacology, University of Groningen, University Medical Centre Groningen, Groningen, the Netherlands
| | - Bettina Jung
- Department of Nephrology, University of Regensburg, University Hospital Regensburg, Regensburg, Germany
- Department of Nephrology, Diabetology, and Rheumatology, Traunstein Hospital, Southeast Bavarian Clinics, Traunstein, Germany
- KfH Kidney Center Traunstein, Traunstein, Germany
| | - Gert Mayer
- Department of Internal Medicine IV-Nephrology and Hypertension, Medical University Innsbruck, Innsbruck, Austria
| | - Heike Meiselbach
- Department of Nephrology and Hypertension, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Matthias Schmid
- Institute of Medical Biometry, Informatics, and Epidemiology, University Hospital Bonn, Bonn, Germany
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology and Department of Medicine IV-Nephrology and Primary Care, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Georg Heinze
- Center for Medical Data Science, Section for Clinical Biometrics, Medical University of Vienna, Vienna, Austria
| | - Rainer Oberbauer
- Division of Nephrology and Dialysis, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria
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13
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Steinbrenner I, Yu Z, Jin J, Schultheiss UT, Kotsis F, Grams ME, Coresh J, Wuttke M, Kronenberg F, Eckardt KU, Chatterjee N, Sekula P, Köttgen A. A polygenic score for reduced kidney function and adverse outcomes in a cohort with chronic kidney disease. Kidney Int 2023; 103:421-424. [PMID: 36481179 PMCID: PMC9868068 DOI: 10.1016/j.kint.2022.11.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 11/22/2022] [Accepted: 11/23/2022] [Indexed: 12/12/2022]
Affiliation(s)
- Inga Steinbrenner
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Zhi Yu
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Jin Jin
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany; Department of Medicine IV-Nephrology and Primary Care, University of Freiburg, Freiburg, Germany
| | - Fruzsina Kotsis
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany; Department of Medicine IV-Nephrology and Primary Care, University of Freiburg, Freiburg, Germany
| | - Morgan E Grams
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland, USA; Department of Medicine, New York University Grossman School of Medicine, New York, New York, USA
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland, USA; Department of Medicine, New York University Grossman School of Medicine, New York, New York, USA
| | - Matthias Wuttke
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany; Department of Medicine IV-Nephrology and Primary Care, University of Freiburg, Freiburg, Germany
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Kai-Uwe Eckardt
- Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Berlin, Germany; Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Nilanjan Chatterjee
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA; Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Peggy Sekula
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
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14
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Bächle H, Sekula P, Schlosser P, Steinbrenner I, Cheng Y, Kotsis F, Meiselbach H, Stockmann H, Schönherr S, Eckardt KU, Devuyst O, Scherberich J, Köttgen A, Schultheiss UT. Uromodulin and its association with urinary metabolites: the German Chronic Kidney Disease Study. Nephrol Dial Transplant 2023; 38:70-79. [PMID: 35612992 DOI: 10.1093/ndt/gfac187] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND The progression of chronic kidney disease (CKD), a global public health burden, is accompanied by a declining number of functional nephrons. Estimation of remaining nephron mass may improve assessment of CKD progression. Uromodulin has been suggested as a marker of tubular mass. We aimed to identify metabolites associated with uromodulin concentrations in urine and serum to characterize pathophysiologic alterations of metabolic pathways to generate new hypotheses regarding CKD pathophysiology. METHODS We measured urinary and serum uromodulin levels (uUMOD, sUMOD) and 607 urinary metabolites and performed cross-sectional analyses within the German Chronic Kidney Disease study (N = 4628), a prospective observational study. Urinary metabolites significantly associated with uUMOD and sUMOD were used to build weighted metabolite scores for urine (uMS) and serum uromodulin (sMS) and evaluated for time to adverse kidney events over 6.5 years. RESULTS Metabolites cross-sectionally associated with uromodulin included amino acids of the tryptophan metabolism, lipids and nucleotides. Higher levels of the sMS [hazard ratio (HR) = 0.73 (95% confidence interval 0.64; 0.82), P = 7.45e-07] and sUMOD [HR = 0.74 (95% confidence interval 0.63; 0.87), P = 2.32e-04] were associated with a lower risk of adverse kidney events over time, whereas uUMOD and uMS showed the same direction of association but were not significant. CONCLUSIONS We identified urinary metabolites associated with urinary and serum uromodulin. The sUMOD and the sMS were associated with lower risk of adverse kidney events among CKD patients. Higher levels of sUMOD and sMS may reflect a higher number of functional nephrons and therefore a reduced risk of adverse kidney outcomes.
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Affiliation(s)
- Helena Bächle
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Peggy Sekula
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Pascal Schlosser
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Inga Steinbrenner
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Yurong Cheng
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Fruzsina Kotsis
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany.,Department of Medicine IV-Nephrology and Primary Care, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Heike Meiselbach
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Helena Stockmann
- Department of Nephrology and Medical Intensive Care, Charité, University-Medicine, Berlin, Germany
| | - Sebastian Schönherr
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.,Department of Nephrology and Medical Intensive Care, Charité, University-Medicine, Berlin, Germany
| | - Olivier Devuyst
- Institute of Physiology, University of Zurich, Zurich, Switzerland
| | - Jürgen Scherberich
- Klinikum München-Harlaching, Nephrology & Clinical Immunology, Teaching Hospital of the Ludwig-Maximilians-University München, Munich, Germany
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany.,Department of Medicine IV-Nephrology and Primary Care, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
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15
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Neri L, Lonati C, Titapiccolo JI, Nadal J, Meiselbach H, Schmid M, Baerthlein B, Tschulena U, Schneider MP, Schultheiss UT, Barbieri C, Moore C, Steppan S, Eckardt KU, Stuard S, Bellocchio F. The Cardiovascular Literature-Based Risk Algorithm (CALIBRA): Predicting Cardiovascular Events in Patients With Non-Dialysis Dependent Chronic Kidney Disease. Front Nephrol 2022; 2:922251. [PMID: 37675027 PMCID: PMC10479593 DOI: 10.3389/fneph.2022.922251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Accepted: 05/20/2022] [Indexed: 09/08/2023]
Abstract
Background and Objectives Cardiovascular (CV) disease is the main cause of morbidity and mortality in patients suffering from chronic kidney disease (CKD). Although it is widely recognized that CV risk assessment represents an essential prerequisite for clinical management, existing prognostic models appear not to be entirely adequate for CKD patients. We derived a literature-based, naïve-bayes model predicting the yearly risk of CV hospitalizations among patients suffering from CKD, referred as the CArdiovascular, LIterature-Based, Risk Algorithm (CALIBRA). Methods CALIBRA incorporates 31 variables including traditional and CKD-specific risk factors. It was validated in two independent CKD populations: the FMC NephroCare cohort (European Clinical Database, EuCliD®) and the German Chronic Kidney Disease (GCKD) study prospective cohort. CALIBRA performance was evaluated by c-statistics and calibration charts. In addition, CALIBRA discrimination was compared with that of three validated tools currently used for CV prediction in CKD, namely the Framingham Heart Study (FHS) risk score, the atherosclerotic cardiovascular disease risk score (ASCVD), and the Individual Data Analysis of Antihypertensive Intervention Trials (INDANA) calculator. Superiority was defined as a ΔAUC>0.05. Results CALIBRA showed good discrimination in both the EuCliD® medical registry (AUC 0.79, 95%CI 0.76-0.81) and the GCKD cohort (AUC 0.73, 95%CI 0.70-0.76). CALIBRA demonstrated improved accuracy compared to the benchmark models in EuCliD® (FHS: ΔAUC=-0.22, p<0.001; ASCVD: ΔAUC=-0.17, p<0.001; INDANA: ΔAUC=-0.14, p<0.001) and GCKD (FHS: ΔAUC=-0.16, p<0.001; ASCVD: ΔAUC=-0.12, p<0.001; INDANA: ΔAUC=-0.04, p<0.001) populations. Accuracy of the CALIBRA score was stable also for patients showing missing variables. Conclusion CALIBRA provides accurate and robust stratification of CKD patients according to CV risk and allows score calculations with improved accuracy compared to established CV risk scores also in real-world clinical cohorts with considerable missingness rates. Our results support the generalizability of CALIBRA across different CKD populations and clinical settings.
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Affiliation(s)
- Luca Neri
- Clinical and Data Intelligence Systems-Advanced Analytics, Fresenius Medical Care Deutschland GmbH, Vaiano Cremasco, Italy
| | - Caterina Lonati
- Center for Preclinical Research, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Jasmine Ion Titapiccolo
- Clinical and Data Intelligence Systems-Advanced Analytics, Fresenius Medical Care Deutschland GmbH, Vaiano Cremasco, Italy
| | - Jennifer Nadal
- Department of Medical Biometry, Informatics, and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Heike Meiselbach
- Department of Nephrology and Hypertension, Universitätsklinikum Erlangen, Friedrich-Alexander Universität Erlangen-Nürnber, Erlangen, Germany
| | - Matthias Schmid
- Department of Medical Biometry, Informatics, and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Barbara Baerthlein
- Medical Centre for Information and Communication Technology (MIK), University Hospital Erlangen, Erlangen, Germany
| | | | - Markus P. Schneider
- Department of Nephrology and Hypertension, Universitätsklinikum Erlangen, Friedrich-Alexander Universität Erlangen-Nürnber, Erlangen, Germany
| | - Ulla T. Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Department of Medicine IV – Nephrology and Primary Care, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Carlo Barbieri
- Fresenius Medical Care, Deutschland GmbH, Bad Homburg, Germany
| | - Christoph Moore
- Fresenius Medical Care, Deutschland GmbH, Bad Homburg, Germany
| | - Sonia Steppan
- Fresenius Medical Care, Deutschland GmbH, Bad Homburg, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, Universitätsklinikum Erlangen, Friedrich-Alexander Universität Erlangen-Nürnber, Erlangen, Germany
- Department of Nephrology and Medical Intensive Care, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Stefano Stuard
- Fresenius Medical Care, Deutschland GmbH, Bad Homburg, Germany
| | - Francesco Bellocchio
- Clinical and Data Intelligence Systems-Advanced Analytics, Fresenius Medical Care Deutschland GmbH, Vaiano Cremasco, Italy
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16
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Li Y, Cheng Y, Consolato F, Schiano G, Chong MR, Pietzner M, Nguyen NQH, Scherer N, Biggs ML, Kleber ME, Haug S, Göçmen B, Pigeyre M, Sekula P, Steinbrenner I, Schlosser P, Joseph CB, Brody JA, Grams ME, Hayward C, Schultheiss UT, Krämer BK, Kronenberg F, Peters A, Seissler J, Steubl D, Then C, Wuttke M, März W, Eckardt KU, Gieger C, Boerwinkle E, Psaty BM, Coresh J, Oefner PJ, Pare G, Langenberg C, Scherberich JE, Yu B, Akilesh S, Devuyst O, Rampoldi L, Köttgen A. Genome-wide studies reveal factors associated with circulating uromodulin and its relationships to complex diseases. JCI Insight 2022; 7:e157035. [PMID: 35446786 PMCID: PMC9220927 DOI: 10.1172/jci.insight.157035] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 04/07/2022] [Indexed: 11/28/2022] Open
Abstract
Uromodulin (UMOD) is a major risk gene for monogenic and complex forms of kidney disease. The encoded kidney-specific protein uromodulin is highly abundant in urine and related to chronic kidney disease, hypertension, and pathogen defense. To gain insights into potential systemic roles, we performed genome-wide screens of circulating uromodulin using complementary antibody-based and aptamer-based assays. We detected 3 and 10 distinct significant loci, respectively. Integration of antibody-based results at the UMOD locus with functional genomics data (RNA-Seq, ATAC-Seq, Hi-C) of primary human kidney tissue highlighted an upstream variant with differential accessibility and transcription in uromodulin-synthesizing kidney cells as underlying the observed cis effect. Shared association patterns with complex traits, including chronic kidney disease and blood pressure, placed the PRKAG2 locus in the same pathway as UMOD. Experimental validation of the third antibody-based locus, B4GALNT2, showed that the p.Cys466Arg variant of the encoded N-acetylgalactosaminyltransferase had a loss-of-function effect leading to higher serum uromodulin levels. Aptamer-based results pointed to enzymes writing glycan marks present on uromodulin and to their receptors in the circulation, suggesting that this assay permits investigating uromodulin's complex glycosylation rather than its quantitative levels. Overall, our study provides insights into circulating uromodulin and its emerging functions.
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Affiliation(s)
- Yong Li
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, and
| | - Yurong Cheng
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, and
- Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Francesco Consolato
- Molecular Genetics of Renal Disorders group, Division of Genetics and Cell Biology, IRCCS Ospedale San Raffaele, Milan, Italy
| | | | - Michael R. Chong
- Population Health Research Institute and Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences, Hamilton, Ontario, Canada
- Department of Biochemistry and Biomedical Sciences and
- Department of Pathology and Molecular Medicine, Faculty of Health Science, McMaster University, Hamilton, Ontario, Canada
| | - Maik Pietzner
- Medical Research Council (MRC) Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
- Computational Medicine, Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Ngoc Quynh H. Nguyen
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Nora Scherer
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, and
- Spemann Graduate School of Biology and Medicine, University of Freiburg, Freiburg, Germany
| | - Mary L. Biggs
- Cardiovascular Health Research Unit, Department of Medicine, and
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Marcus E. Kleber
- SYNLAB MVZ Humangenetik Mannheim GmbH, Mannheim, Germany
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Stefan Haug
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, and
| | - Burulça Göçmen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, and
| | - Marie Pigeyre
- Population Health Research Institute and Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences, Hamilton, Ontario, Canada
- Department of Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Peggy Sekula
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, and
| | - Inga Steinbrenner
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, and
| | - Pascal Schlosser
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, and
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Christina B. Joseph
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | | | - Morgan E. Grams
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Division of Nephrology, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Ulla T. Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, and
- Department of Medicine IV: Nephrology and Primary Care, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Bernhard K. Krämer
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, Ludwig-Maximilians-Universität (LMU), Munich, Germany
| | - Jochen Seissler
- Medical Clinic and Policlinic IV, Hospital of the University of Munich, LMU Munich, Munich, Germany
| | - Dominik Steubl
- Division of Nephrology, Tufts Medical Center, Boston, Massachusetts, USA
- Department of Nephrology, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
- Boehringer Ingelheim International GmbH, Ingelheim, Germany
| | - Cornelia Then
- Medical Clinic and Policlinic IV, Hospital of the University of Munich, LMU Munich, Munich, Germany
| | - Matthias Wuttke
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, and
- Department of Medicine IV: Nephrology and Primary Care, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Winfried März
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
- SYNLAB Academy, SYNLAB Holding Deutschland GmbH, Augsburg and Mannheim, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Medical Intensive Care, Charité – Universitätsmedizin Berlin, Berlin, Germany
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Christian Gieger
- Institute of Epidemiology, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Partner Munich, Neuherberg, Germany
| | - Eric Boerwinkle
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, and
- Department of Epidemiology and
- Department of Health Systems and Population Health, School of Public Health, University of Washington, Seattle, Washington, USA
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Peter J. Oefner
- Institute of Functional Genomics, University of Regensburg, Regensburg, Germany
| | - Guillaume Pare
- Population Health Research Institute and Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, Faculty of Health Science, McMaster University, Hamilton, Ontario, Canada
| | - Claudia Langenberg
- Medical Research Council (MRC) Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
- Computational Medicine, Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany
| | | | - Bing Yu
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Shreeram Akilesh
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA
| | - Olivier Devuyst
- Institute of Physiology, University of Zurich, Zurich, Switzerland
| | - Luca Rampoldi
- Molecular Genetics of Renal Disorders group, Division of Genetics and Cell Biology, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, and
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Centre for Integrative Biological Signalling Studies (CIBSS), University of Freiburg, Freiburg, Germany
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17
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Steinbrenner I, Sekula P, Kotsis F, von Cube M, Cheng Y, Nadal J, Schmid M, Schneider MP, Krane V, Nauck M, Eckardt KU, Schultheiss UT. Association of osteopontin with kidney function and kidney failure in chronic kidney disease patients: the GCKD study. Nephrol Dial Transplant 2022; 38:1430-1438. [PMID: 35524694 DOI: 10.1093/ndt/gfac173] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Osteopontin (OPN), synthesized in the thick ascending limb of Henle's loop and in the distal tubule, is involved in the pathogenesis of kidney fibrosis, a hallmark of kidney failure (KF). In a cohort of chronic kidney disease (CKD) patients, we evaluated OPN's association with kidney markers and KF. METHODS OPN was measured from baseline serum samples of German Chronic Kidney Disease study participants. Cross-sectional regression models for estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (UACR) as well as Cox regression models for all-cause mortality and KF were evaluated to estimate the OPN effect. Additionally, predictive ability, of OPN and time-dependent population-attributable fraction were evaluated. RESULTS Over a median follow-up of 6.5 years, 471 KF events and 629 deaths occurred among 4,950 CKD patients. One-unit higher log(OPN) was associated with 5.5 mL/min/1.73m2 lower eGFR (95%CI: [-6.4,-4.6]) and 1% change in OPN with 0.7% higher UACR (estimated effect 0.7, 95%CI: [0.6,0.8]). Moreover, higher OPN levels were associated with a higher risk of KF (hazard ratio [HR] 1.4, 95%CI: [1.2,1.7]) and all-cause mortality (HR 1.5, 95%CI: [1.3,1.8]). After 6 years, 31% of the KF events could be attributed to higher OPN levels (95%CI: [3%,56%]). CONCLUSIONS In this study, higher OPN levels were associated with kidney function markers worsening, and a higher risk for adverse outcomes. A larger proportion of KF could be attributed to higher OPN levels warranting further research on OPN with regards to its role in CKD progression and possible treatment options.
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Affiliation(s)
- Inga Steinbrenner
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Peggy Sekula
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Fruzsina Kotsis
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Department of Medicine IV - Nephrology and Primary Care, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Maja von Cube
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Yurong Cheng
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Jennifer Nadal
- Department of Medical Biometry, Informatics and Epidemiology, Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Matthias Schmid
- Department of Medical Biometry, Informatics and Epidemiology, Faculty of Medicine, University of Bonn, Bonn, Germany
- Department of Nephrology and Medical Intensive Care, Charité, Universitätsmedizin Berlin, Berlin, Germany
| | - Markus P Schneider
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Vera Krane
- Department of Internal Medicine I, Division of Nephrology, University Hospital Würzburg, Würzburg, Germany
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- Department of Nephrology and Medical Intensive Care, Charité, Universitätsmedizin Berlin, Berlin, Germany
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Department of Medicine IV - Nephrology and Primary Care, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
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Schultheiss UT, Bächle H, Altenbuchinger M, Meiselbach H, Kosch R, Salloch S, Bratan T, Zacharias HU, Kotsis F. MO474: Expectation and Acceptance of a Clinical Decision Support Software by Nephrologist End-Users: The Ckdnapp Survey. Nephrol Dial Transplant 2022. [DOI: 10.1093/ndt/gfac071.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
BACKGROUND AND AIMS
Chronic kidney disease (CKD) is a major public health problem. CKD constitutes a complex disease due to differing underlying disease etiologies in each patient, which can in turn lead to many complications, comorbidities and polypharmacy. Monitoring disease progression and personalized treatment efforts are crucial for optimal long-term patient outcomes. In order to achieve this, physicians need to integrate different levels of data, e.g. clinical/demographic parameters, biomarkers and drug information, with medical knowledge. Clinical decision support systems (CDSS) can tackle these issues and improve patient management. ‘CKDNapp’ (CKD Nephrologist App), a CDSS application for nephrologists, based on mathematical models using machine-learning techniques, is currently being developed (https://ckdn.app). CKDNapp is intended to become a tool for daily clinical use. The nephrologists’ attitude towards any CDSS and CKDNapp in particular is of prime importance for its successful implementation into the daily medical routine. This survey investigates nephrologists’ experiences with CDSS in general and their expectations towards a reliable and useful application supporting their daily medical routine.
METHOD
CKDNapp survey is ongoing and has been conducted by telephone or as a do-it-yourself online interview in the form of a 38-item questionnaire. The answers of nephrologists from all regions across Germany were collected and analyzed using the Electronic Data Capture System, RedCap [1]. CKDNapp survey is divided into four modules: (1) experiences with CDSS, (2) expectations of a helpful CDSS, (3) evaluation of the planned contents of CKDNapp and (4) ethical aspects of CDSS (in collaboration with the BMBF-funded DESIREE project; https://www.desiree-forschung.de/desiree/index.php). All questions were based on a literature search for questionnaire items on CDSS [2, 3]. Response formats include the Likert scale or multiple choice. Descriptive statistical analyses of all questions were calculated.
RESULTS
In total, 44 participants took the survey, and completeness of answers ranged from 85% to 100%. Participants were aged 51–60 years old, male (64%) and had been working in nephrology outpatient clinics for a median of 12 years. Nephrologists treated a median of 35 patients/day. A total of 85% of participants reported never or rarely use a CDSS in patient care. The most frequently given reason for this was a lack of knowledge about CDSS. Nevertheless, 79% of participants believed CDSS to be helpful in the management of patients with CKD and 71% would be willing to use a CDSS given the chance to do so. When rating the importance of planned CKDNapp features, prediction of CKD progression (97%, Figure 1) and in-silico simulations of disease progression when changing, e.g. lifestyle or medication (97%) were most important, followed by the need for integration of available CKD guidelines (95%), prediction of acute kidney injury (95%), prediction of mortality risk (80%), and easy access to patient information (76%). The spectrum of answers to ethical aspects of CDSS (utility of CDSS for experienced versus inexperienced nephrologists, aspects of machine learning Fig. 2, discrimination of minority groups, etc.) was diverse.
CONCLUSION
This survey provides insights into experience with and expectations of outpatient nephrologists on CDSS in general and CKDNapp in particular. Despite the current lack of knowledge on CDSS, the willingness to integrate CDSS into daily patient care and the evaluation of planned CKDNapp features was high.
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Affiliation(s)
- Ulla T Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center – University of Freiburg , Freiburg , Germany
- Department of Medicine IV – Nephrology and Primary Care, Faculty of Medicine and Medical Center – University of Freiburg , Germany
| | - Helena Bächle
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center – University of Freiburg , Freiburg , Germany
| | - Michael Altenbuchinger
- Department of Medical Bioinformatics, University Medical Center Göttingen (UMG) , Göttingen , Germany
| | - Heike Meiselbach
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg , Erlangen , Germany
| | - Robin Kosch
- Department of Medical Bioinformatics, University Medical Center Göttingen (UMG) , Göttingen , Germany
| | - Sabine Salloch
- Institute for Ethics, History and Philosophy of Medicine, Hanover Medical School , Hanover , Germany
| | - Tanja Bratan
- Fraunhofer Institute for Systems and Innovation Research ISI , Karlsruhe , Germany
| | - Helena U Zacharias
- Department of Internal Medicine I, University Medical Center Schleswig-Holstein, Campus Kiel , Kiel , Germany
- Institute of Clinical Molecular Biology, Kiel University and University Medical Center Schleswig-Holstein, Campus Kiel , Kiel , Germany
| | - Fruzsina Kotsis
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center – University of Freiburg , Freiburg , Germany
- Department of Medicine IV – Nephrology and Primary Care, Faculty of Medicine and Medical Center – University of Freiburg , Germany
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Schwaiger JP, Kollerits B, Steinbrenner I, Weissensteiner H, Schönherr S, Forer L, Kotsis F, Lamina C, Schneider MP, Schultheiss UT, Wanner C, Köttgen A, Eckardt KU, Kronenberg F. Apolipoprotein A-IV concentrations and clinical outcomes in a large chronic kidney disease cohort: Results from the GCKD study. J Intern Med 2022; 291:622-636. [PMID: 34914850 PMCID: PMC9305919 DOI: 10.1111/joim.13437] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
BACKGROUND Chronic kidney disease (CKD) represents a chronic proinflammatory state and is associated with very high cardiovascular risk. Apolipoprotein A-IV (apoA-IV) has antiatherogenic, antioxidative, anti-inflammatory and antithrombotic properties and levels increase significantly during the course of CKD. OBJECTIVES We aimed to investigate the association between apoA-IV and all-cause mortality and cardiovascular outcomes in the German Chronic Kidney Disease study. METHODS This was a prospective cohort study including 5141 Caucasian patients with available apoA-IV measurements and CKD. The majority of the patients had an estimated glomerular filtration rate (eGFR) of 30-60 ml/min/1.73m2 or an eGFR >60 ml/min/1.73m2 in the presence of overt proteinuria. Median follow-up was 6.5 years. The association of apoA-IV with comorbidities at baseline and endpoints during follow-up was modelled adjusting for major confounders. RESULTS Mean apoA-IV concentrations of the entire cohort were 28.9 ± 9.8 mg/dl. Patients in the highest apoA-IV quartile had the lowest high-sensitivity C-reactive protein values despite the highest prevalence of diabetes, albuminuria and the lowest eGFR. Each 10 mg/dl higher apoA-IV translated into lower odds of prevalent cardiovascular disease (1289 cases, odds ratio = 0.80, 95% confidence interval [CI] 0.72-0.86, p = 0.0000003). During follow-up, each 10 mg/dl higher apoA-IV was significantly associated with a lower risk for all-cause mortality (600 cases, hazard ratio [HR] = 0.81, 95% CI 0.73-0.89, p = 0.00004), incident major adverse cardiovascular events (506 cases, HR = 0.88, 95% CI 0.79-0.99, p = 0.03) and death or hospitalizations due to heart failure (346 cases, HR = 0.84, 95% CI 0.73-0.96, p = 0.01). CONCLUSIONS These data support a link between elevated apoA-IV concentrations and reduced inflammation in moderate CKD. ApoA-IV appears to be an independent risk marker for reduced all-cause mortality, cardiovascular events and heart failure in a large cohort of patients with CKD.
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Affiliation(s)
- Johannes P Schwaiger
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria.,Department of Internal Medicine, Landeskrankenhaus Hall i.T., Hall in Tirol, Austria
| | - Barbara Kollerits
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Inga Steinbrenner
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Hansi Weissensteiner
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Sebastian Schönherr
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Lukas Forer
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Fruzsina Kotsis
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.,Department of Medicine IV - Nephrology and Primary Care, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Claudia Lamina
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Markus P Schneider
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.,Department of Medicine IV - Nephrology and Primary Care, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Christoph Wanner
- Division of Nephrology, Department of Internal Medicine I, University Hospital Würzburg, Würzburg, Germany
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.,Department of Nephrology and Medical Intensive Care, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
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- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
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20
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Cheng Y, Li Y, Scherer N, Grundner-Culemann F, Lehtimäki T, Mishra BH, Raitakari OT, Nauck M, Eckardt KU, Sekula P, Schultheiss UT. Genetics of osteopontin in patients with chronic kidney disease: The German Chronic Kidney Disease study. PLoS Genet 2022; 18:e1010139. [PMID: 35385482 PMCID: PMC9015153 DOI: 10.1371/journal.pgen.1010139] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 04/18/2022] [Accepted: 03/09/2022] [Indexed: 11/18/2022] Open
Abstract
Osteopontin (OPN), encoded by SPP1, is a phosphorylated glycoprotein predominantly synthesized in kidney tissue. Increased OPN mRNA and protein expression correlates with proteinuria, reduced creatinine clearance, and kidney fibrosis in animal models of kidney disease. But its genetic underpinnings are incompletely understood. We therefore conducted a genome-wide association study (GWAS) of OPN in a European chronic kidney disease (CKD) population. Using data from participants of the German Chronic Kidney Disease (GCKD) study (N = 4,897), a GWAS (minor allele frequency [MAF]≥1%) and aggregated variant testing (AVT, MAF<1%) of ELISA-quantified serum OPN, adjusted for age, sex, estimated glomerular filtration rate (eGFR), and urinary albumin-to-creatinine ratio (UACR) was conducted. In the project, GCKD participants had a mean age of 60 years (SD 12), median eGFR of 46 mL/min/1.73m2 (p25: 37, p75: 57) and median UACR of 50 mg/g (p25: 9, p75: 383). GWAS revealed 3 loci (p<5.0E-08), two of which replicated in the population-based Young Finns Study (YFS) cohort (p<1.67E-03): rs10011284, upstream of SPP1 encoding the OPN protein and related to OPN production, and rs4253311, mapping into KLKB1 encoding prekallikrein (PK), which is processed to kallikrein (KAL) implicated through the kinin-kallikrein system (KKS) in blood pressure control, inflammation, blood coagulation, cancer, and cardiovascular disease. The SPP1 gene was also identified by AVT (p = 2.5E-8), comprising 7 splice-site and missense variants. Among others, downstream analyses revealed colocalization of the OPN association signal at SPP1 with expression in pancreas tissue, and at KLKB1 with various plasma proteins in trans, and with phenotypes (bone disorder, deep venous thrombosis) in human tissue. In summary, this GWAS of OPN levels revealed two replicated associations. The KLKB1 locus connects the function of OPN with PK, suggestive of possible further post-translation processing of OPN. Further studies are needed to elucidate the complex role of OPN within human (patho)physiology.
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Affiliation(s)
- Yurong Cheng
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center—University of Freiburg, Freiburg, Germany
- Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Yong Li
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center—University of Freiburg, Freiburg, Germany
| | - Nora Scherer
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center—University of Freiburg, Freiburg, Germany
- Spemann Graduate School of Biology and Medicine (SGBM), University of Freiburg, Freiburg, Germany
| | - Franziska Grundner-Culemann
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center—University of Freiburg, Freiburg, Germany
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Binisha H. Mishra
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Olli T. Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku Finland
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- Department of Nephrology and Medical Intensive Care, Charité, University-Medicine, Berlin, Germany
| | - Peggy Sekula
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center—University of Freiburg, Freiburg, Germany
| | - Ulla T. Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center—University of Freiburg, Freiburg, Germany
- Department of Medicine IV, Nephrology and Primary Care, Faculty of Medicine and Medical Center—University of Freiburg, Freiburg, Germany
- * E-mail:
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21
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Pammer LM, Lamina C, Schultheiss UT, Kotsis F, Kollerits B, Stockmann H, Lipovsek J, Meiselbach H, Busch M, Eckardt KU, Kronenberg F. Association of the metabolic syndrome with mortality and major adverse cardiac events: A large chronic kidney disease cohort. J Intern Med 2021; 290:1219-1232. [PMID: 34342064 DOI: 10.1111/joim.13355] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND Metabolic syndrome with its key components insulin resistance, central obesity, dyslipidaemia, and hypertension is associated with a high risk for cardiovascular events and all-cause mortality in the general population. However, evidence that these findings apply to patients with chronic kidney disease (CKD) with moderately reduced estimated glomerular filtration rate and/or albuminuria is limited. OBJECTIVES We aimed to investigate the association between metabolic syndrome and its components with all-cause mortality and cardiovascular outcomes in CKD patients. METHODS Prospective observation of a cohort of 5110 CKD patients from the German Chronic Kidney Disease study with 3284 (64.3%) of them having a metabolic syndrome at baseline. RESULTS During the follow-up of 6.5 years, 605 patients died and 650 patients experienced major cardiovascular events. After extended data adjustment, patients with a metabolic syndrome had a higher risk for all-cause mortality (hazard ratio [HR] = 1.26, 95% confidence interval [CI]: 1.04-1.54) and cardiovascular events (HR = 1.48, 95% CI: 1.22-1.79). The risk increased steadily with a growing number of metabolic syndrome components (increased waist circumference, glucose, triglycerides, hypertension and decreased HDL cholesterol): HR per component = 1.09 (95% CI: 1.02-1.17) for all-cause mortality and 1.23 (95% CI: 1.15-1.32) for cardiovascular events. This resulted in hazard ratios between 1.50 and 2.50 in the case when four or five components are present. An analysis of individual components of metabolic syndrome showed that the glucose component led to the highest increase in risk for all-cause mortality (HR = 1.68, 95% CI: 1.38-2.03) and cardiovascular events (HR = 1.81, 95% CI: 1.51-2.18), followed by the HDL cholesterol and triglyceride components. CONCLUSIONS We observed a high prevalence of metabolic syndrome among patients with moderate CKD. Metabolic syndrome increases the risk for all-cause mortality and cardiovascular events. The glucose and lipid components seem to be the main drivers for the association with outcomes.
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Affiliation(s)
- Lorenz M Pammer
- Department of Genetics and Pharmacology, Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Claudia Lamina
- Department of Genetics and Pharmacology, Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Ulla T Schultheiss
- Faculty of Medicine and Medical Center, Institute of Genetic Epidemiology, University of Freiburg, Freiburg, Germany.,Department of Medicine IV-Nephrology and Primary Care, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Fruzsina Kotsis
- Faculty of Medicine and Medical Center, Institute of Genetic Epidemiology, University of Freiburg, Freiburg, Germany.,Department of Medicine IV-Nephrology and Primary Care, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Barbara Kollerits
- Department of Genetics and Pharmacology, Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Helena Stockmann
- Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Jan Lipovsek
- Faculty of Medicine and Medical Center, Institute of Genetic Epidemiology, University of Freiburg, Freiburg, Germany
| | - Heike Meiselbach
- Department of Nephrology and Hypertension, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Martin Busch
- Department of Internal Medicine III, Friedrich Schiller University Jena, Jena, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Berlin, Germany.,Department of Nephrology and Hypertension, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Florian Kronenberg
- Department of Genetics and Pharmacology, Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
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- Department of Genetics and Pharmacology, Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
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22
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Bellocchio F, Lonati C, Ion Titapiccolo J, Nadal J, Meiselbach H, Schmid M, Baerthlein B, Tschulena U, Schneider M, Schultheiss UT, Barbieri C, Moore C, Steppan S, Eckardt KU, Stuard S, Neri L. Validation of a Novel Predictive Algorithm for Kidney Failure in Patients Suffering from Chronic Kidney Disease: The Prognostic Reasoning System for Chronic Kidney Disease (PROGRES-CKD). Int J Environ Res Public Health 2021; 18:12649. [PMID: 34886378 PMCID: PMC8656741 DOI: 10.3390/ijerph182312649] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 11/21/2021] [Accepted: 11/25/2021] [Indexed: 12/04/2022]
Abstract
Current equation-based risk stratification algorithms for kidney failure (KF) may have limited applicability in real world settings, where missing information may impede their computation for a large share of patients, hampering one from taking full advantage of the wealth of information collected in electronic health records. To overcome such limitations, we trained and validated the Prognostic Reasoning System for Chronic Kidney Disease (PROGRES-CKD), a novel algorithm predicting end-stage kidney disease (ESKD). PROGRES-CKD is a naïve Bayes classifier predicting ESKD onset within 6 and 24 months in adult, stage 3-to-5 CKD patients. PROGRES-CKD trained on 17,775 CKD patients treated in the Fresenius Medical Care (FMC) NephroCare network. The algorithm was validated in a second independent FMC cohort (n = 6760) and in the German Chronic Kidney Disease (GCKD) study cohort (n = 4058). We contrasted PROGRES-CKD accuracy against the performance of the Kidney Failure Risk Equation (KFRE). Discrimination accuracy in the validation cohorts was excellent for both short-term (stage 4-5 CKD, FMC: AUC = 0.90, 95%CI 0.88-0.91; GCKD: AUC = 0.91, 95% CI 0.86-0.97) and long-term (stage 3-5 CKD, FMC: AUC = 0.85, 95%CI 0.83-0.88; GCKD: AUC = 0.85, 95%CI 0.83-0.88) forecasting horizons. The performance of PROGRES-CKD was non-inferior to KFRE for the 24-month horizon and proved more accurate for the 6-month horizon forecast in both validation cohorts. In the real world setting captured in the FMC validation cohort, PROGRES-CKD was computable for all patients, whereas KFRE could be computed for complete cases only (i.e., 30% and 16% of the cohort in 6- and 24-month horizons). PROGRES-CKD accurately predicts KF onset among CKD patients. Contrary to equation-based scores, PROGRES-CKD extends to patients with incomplete data and allows explicit assessment of prediction robustness in case of missing values. PROGRES-CKD may efficiently assist physicians' prognostic reasoning in real-life applications.
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Affiliation(s)
- Francesco Bellocchio
- Clinical & Data Intelligence Systems-Advanced Analytics, Fresenius Medical Care Deutschland GmbH, 26020 Vaiano Cremasco, Italy; (J.I.T.); (L.N.)
| | - Caterina Lonati
- Center for Preclinical Research, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy;
| | - Jasmine Ion Titapiccolo
- Clinical & Data Intelligence Systems-Advanced Analytics, Fresenius Medical Care Deutschland GmbH, 26020 Vaiano Cremasco, Italy; (J.I.T.); (L.N.)
| | - Jennifer Nadal
- Department of Medical Biometry, Informatics, and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, 53113 Bonn, Germany; (J.N.); (M.S.); (M.S.)
| | - Heike Meiselbach
- Department of Nephrology and Hypertension, Friedrich-Alexander University of Erlangen-Nürnberg, 91054 Erlangen, Germany; (H.M.); (K.-U.E.)
| | - Matthias Schmid
- Department of Medical Biometry, Informatics, and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, 53113 Bonn, Germany; (J.N.); (M.S.); (M.S.)
| | - Barbara Baerthlein
- Medical Centre for Information and Communication Technology (MIK), University Hospital Erlangen, 91054 Erlangen, Germany;
| | - Ulrich Tschulena
- Fresenius Medical Care, Deutschland GmbH, 61352 Bad Homburg, Germany; (U.T.); (C.B.); (C.M.); (S.S.); (S.S.)
| | - Markus Schneider
- Department of Medical Biometry, Informatics, and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, 53113 Bonn, Germany; (J.N.); (M.S.); (M.S.)
| | - Ulla T. Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, 79085 Freiburg, Germany;
- Department of Medicine IV–Nephrology and Primary Care, Faculty of Medicine and Medical Center, University of Freiburg, 79085 Freiburg, Germany
| | - Carlo Barbieri
- Fresenius Medical Care, Deutschland GmbH, 61352 Bad Homburg, Germany; (U.T.); (C.B.); (C.M.); (S.S.); (S.S.)
| | - Christoph Moore
- Fresenius Medical Care, Deutschland GmbH, 61352 Bad Homburg, Germany; (U.T.); (C.B.); (C.M.); (S.S.); (S.S.)
| | - Sonja Steppan
- Fresenius Medical Care, Deutschland GmbH, 61352 Bad Homburg, Germany; (U.T.); (C.B.); (C.M.); (S.S.); (S.S.)
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, Friedrich-Alexander University of Erlangen-Nürnberg, 91054 Erlangen, Germany; (H.M.); (K.-U.E.)
- Department of Nephrology and Medical Intensive Care, Charité Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Stefano Stuard
- Fresenius Medical Care, Deutschland GmbH, 61352 Bad Homburg, Germany; (U.T.); (C.B.); (C.M.); (S.S.); (S.S.)
| | - Luca Neri
- Clinical & Data Intelligence Systems-Advanced Analytics, Fresenius Medical Care Deutschland GmbH, 26020 Vaiano Cremasco, Italy; (J.I.T.); (L.N.)
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23
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Kotsis F, Schultheiss UT, Wuttke M, Schlosser P, Mielke J, Becker MS, Oefner PJ, Karoly ED, Mohney RP, Eckardt KU, Sekula P, Köttgen A. Self-Reported Medication Use and Urinary Drug Metabolites in the German Chronic Kidney Disease (GCKD) Study. J Am Soc Nephrol 2021; 32:2315-2329. [PMID: 34140400 PMCID: PMC8729827 DOI: 10.1681/asn.2021010063] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Accepted: 05/31/2021] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Polypharmacy is common among patients with CKD, but little is known about the urinary excretion of many drugs and their metabolites among patients with CKD. METHODS To evaluate self-reported medication use in relation to urine drug metabolite levels in a large cohort of patients with CKD, the German Chronic Kidney Disease study, we ascertained self-reported use of 158 substances and 41 medication groups, and coded active ingredients according to the Anatomical Therapeutic Chemical Classification System. We used a nontargeted mass spectrometry-based approach to quantify metabolites in urine; calculated specificity, sensitivity, and accuracy of medication use and corresponding metabolite measurements; and used multivariable regression models to evaluate associations and prescription patterns. RESULTS Among 4885 participants, there were 108 medication-drug metabolite pairs on the basis of reported medication use and 78 drug metabolites. Accuracy was excellent for measurements of 36 individual substances in which the unchanged drug was measured in urine (median, 98.5%; range, 61.1%-100%). For 66 pairs of substances and their related drug metabolites, median measurement-based specificity and sensitivity were 99.2% (range, 84.0%-100%) and 71.7% (range, 1.2%-100%), respectively. Commonly prescribed medications for hypertension and cardiovascular risk reduction-including angiotensin II receptor blockers, calcium channel blockers, and metoprolol-showed high sensitivity and specificity. Although self-reported use of prescribed analgesics (acetaminophen, ibuprofen) was <3% each, drug metabolite levels indicated higher usage (acetaminophen, 10%-26%; ibuprofen, 10%-18%). CONCLUSIONS This comprehensive screen of associations between urine drug metabolite levels and self-reported medication use supports the use of pharmacometabolomics to assess medication adherence and prescription patterns in persons with CKD, and indicates under-reported use of medications available over the counter, such as analgesics.
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Affiliation(s)
- Fruzsina Kotsis
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center – University of Freiburg, Freiburg, Germany,Department of Medicine IV: Nephrology and Primary Care, Faculty of Medicine and Medical Center – University of Freiburg, Freiburg, Germany
| | - Ulla T. Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center – University of Freiburg, Freiburg, Germany,Department of Medicine IV: Nephrology and Primary Care, Faculty of Medicine and Medical Center – University of Freiburg, Freiburg, Germany
| | - Matthias Wuttke
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center – University of Freiburg, Freiburg, Germany,Department of Medicine IV: Nephrology and Primary Care, Faculty of Medicine and Medical Center – University of Freiburg, Freiburg, Germany
| | - Pascal Schlosser
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center – University of Freiburg, Freiburg, Germany
| | - Johanna Mielke
- Division of Pharmaceuticals, Open Innovation and Digital Technologies, Bayer AG, Wuppertal, Germany
| | - Michael S. Becker
- Division of Pharmaceuticals, Cardiovascular Research, Bayer AG, Wuppertal, Germany
| | - Peter J. Oefner
- Institute of Functional Genomics, University of Regensburg, Regensburg, Germany
| | | | | | - Kai-Uwe Eckardt
- Department of Nephrology and Medical Intensive Care, Charité – Berlin University of Medicine, Berlin, Germany,Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich–Alexander University Erlangen–Nürnberg, Erlangen, Germany
| | - Peggy Sekula
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center – University of Freiburg, Freiburg, Germany
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center – University of Freiburg, Freiburg, Germany
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Schultheiss UT, Sekula P. The Promise of Metabolomics in Decelerating CKD Progression in Children. Clin J Am Soc Nephrol 2021; 16:1152-1154. [PMID: 34362783 PMCID: PMC8455046 DOI: 10.2215/cjn.07400521] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 06/04/2021] [Accepted: 06/04/2021] [Indexed: 02/04/2023]
Affiliation(s)
- Ulla T. Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany,Department of Medicine IV, Nephrology and Primary Care, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Peggy Sekula
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
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25
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Schultheiss UT, Kosch R, Kotsis F, Altenbuchinger M, Zacharias HU. Chronic Kidney Disease Cohort Studies: A Guide to Metabolome Analyses. Metabolites 2021; 11:460. [PMID: 34357354 PMCID: PMC8304377 DOI: 10.3390/metabo11070460] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 07/08/2021] [Accepted: 07/12/2021] [Indexed: 12/14/2022] Open
Abstract
Kidney diseases still pose one of the biggest challenges for global health, and their heterogeneity and often high comorbidity load seriously hinders the unraveling of their underlying pathomechanisms and the delivery of optimal patient care. Metabolomics, the quantitative study of small organic compounds, called metabolites, in a biological specimen, is gaining more and more importance in nephrology research. Conducting a metabolomics study in human kidney disease cohorts, however, requires thorough knowledge about the key workflow steps: study planning, sample collection, metabolomics data acquisition and preprocessing, statistical/bioinformatics data analysis, and results interpretation within a biomedical context. This review provides a guide for future metabolomics studies in human kidney disease cohorts. We will offer an overview of important a priori considerations for metabolomics cohort studies, available analytical as well as statistical/bioinformatics data analysis techniques, and subsequent interpretation of metabolic findings. We will further point out potential research questions for metabolomics studies in the context of kidney diseases and summarize the main results and data availability of important studies already conducted in this field.
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Affiliation(s)
- Ulla T. Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, 79106 Freiburg, Germany; (U.T.S.); (F.K.)
- Department of Medicine IV—Nephrology and Primary Care, Faculty of Medicine and Medical Center, University of Freiburg, 79106 Freiburg, Germany
| | - Robin Kosch
- Computational Biology, University of Hohenheim, 70599 Stuttgart, Germany;
| | - Fruzsina Kotsis
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, 79106 Freiburg, Germany; (U.T.S.); (F.K.)
- Department of Medicine IV—Nephrology and Primary Care, Faculty of Medicine and Medical Center, University of Freiburg, 79106 Freiburg, Germany
| | - Michael Altenbuchinger
- Institute of Medical Bioinformatics, University Medical Center Göttingen, 37077 Göttingen, Germany;
| | - Helena U. Zacharias
- Department of Internal Medicine I, University Medical Center Schleswig-Holstein, Campus Kiel, 24105 Kiel, Germany
- Institute of Clinical Molecular Biology, Kiel University and University Medical Center Schleswig-Holstein, Campus Kiel, 24105 Kiel, Germany
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Zacharias HU, Altenbuchinger M, Schultheiss UT, Raffler J, Kotsis F, Ghasemi S, Ali I, Kollerits B, Metzger M, Steinbrenner I, Sekula P, Massy ZA, Combe C, Kalra PA, Kronenberg F, Stengel B, Eckardt KU, Köttgen A, Schmid M, Gronwald W, Oefner PJ. A Predictive Model for Progression of CKD to Kidney Failure Based on Routine Laboratory Tests. Am J Kidney Dis 2021; 79:217-230.e1. [PMID: 34298143 DOI: 10.1053/j.ajkd.2021.05.018] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Accepted: 05/01/2021] [Indexed: 12/23/2022]
Abstract
RATIONALE & OBJECTIVE Stratification of chronic kidney disease (CKD) patients at risk for progressing to end-stage kidney disease (ESKD) requiring kidney replacement therapy (KRT) is important for clinical decision-making and trial enrollment. STUDY DESIGN Four independent prospective observational cohort studies. SETTING & PARTICIPANTS The development cohort was comprised of 4,915 CKD patients and three independent validation cohorts were comprised of a total of 3,063. Patients were followed-up for approximately five years. NEW PREDICTORS & ESTABLISHED PREDICTORS 22 demographic, anthropometric and laboratory variables commonly assessed in CKD patients. OUTCOMES Progression to ESKD requiring KRT. ANALYTICAL APPROACH A Least Absolute Shrinkage and Selection Operator (LASSO) Cox proportional hazards model was fit to select laboratory variables that best identified patients at high risk for ESKD. Model discrimination and calibration were assessed and compared against the 4-variable Tangri (T4) risk equation. Both used a resampling approach within the development cohort and in the validation cohorts using cause-specific concordance (C) statistics, net reclassification improvement, and calibration graphs. RESULTS The newly derived 6-variable (Z6) risk score included serum creatinine, albumin, cystatin C and urea, as well as hemoglobin and the urine albumin-to-creatinine ratio. Based on the resampling approach, Z6 achieved a median C value of 0.909 (95% CI, 0.868-0.937) at two years after the baseline visit, whereas the T4 achieved a median C value of 0.855 (95% CI, 0.799-0.915). In the three independent validation cohorts, Z6 C values were 0.894, 0.921, and 0.891, whereas the T4 C values were 0.882, 0.913, and 0.862. LIMITATIONS The Z6 was both derived and tested only in White European cohorts. CONCLUSIONS A new risk equation, based on six routinely available laboratory tests facilitates identification of patients with CKD who are at high risk of progressing to ESKD.
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Affiliation(s)
- Helena U Zacharias
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany; Department of Internal Medicine I, University Medical Center Schleswig-Holstein, Campus Kiel, Kiel, Germany; Institute of Clinical Molecular Biology, Kiel University and University Medical Center Schleswig-Holstein, Campus Kiel, Kiel, Germany.
| | - Michael Altenbuchinger
- Chair of Statistical Bioinformatics, Institute of Functional Genomics, University of Regensburg, Regensburg, Germany; Computational Biology Group, University of Hohenheim, Stuttgart, Germany
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Medical Center - University of Freiburg, Faculty of Medicine, Freiburg, Germany; Renal Division, Department of Medicine IV, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Johannes Raffler
- Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Fruzsina Kotsis
- Institute of Genetic Epidemiology, Medical Center - University of Freiburg, Faculty of Medicine, Freiburg, Germany; Renal Division, Department of Medicine IV, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Sahar Ghasemi
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Ibrahim Ali
- Salford Royal Hospital and University of Manchester, Salford M6 8HD, UK
| | - Barbara Kollerits
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Marie Metzger
- Université Paris-Saclay, Université Versailles Saint Quentin, National Institute of Health and Medical Research (Inserm), Centre for Research in Epidemiology and Population Health (CESP), Clinical Epidemiology Team, Villejuif, France
| | - Inga Steinbrenner
- Institute of Genetic Epidemiology, Medical Center - University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Peggy Sekula
- Institute of Genetic Epidemiology, Medical Center - University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Ziad A Massy
- Université Paris-Saclay, Université Versailles Saint Quentin, National Institute of Health and Medical Research (Inserm), Centre for Research in Epidemiology and Population Health (CESP), Clinical Epidemiology Team, Villejuif, France; Department of Nephrology, Ambroise Paré University Hospital, APHP, Boulogne-Billancourt/Paris, France
| | - Christian Combe
- Service de Néphrologie Transplantation Dialyse Aphérèse, Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France; Inserm, U1026, Univ Bordeaux Segalen, Bordeaux, France
| | - Philip A Kalra
- Salford Royal Hospital and University of Manchester, Salford M6 8HD, UK
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Bénédicte Stengel
- Université Paris-Saclay, Université Versailles Saint Quentin, National Institute of Health and Medical Research (Inserm), Centre for Research in Epidemiology and Population Health (CESP), Clinical Epidemiology Team, Villejuif, France
| | - Kai-Uwe Eckardt
- Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Germany; Department of Nephrology and Hypertension, Friedrich-Alexander Universität Erlangen Nürnberg, Erlangen, Germany
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Medical Center - University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Matthias Schmid
- Department of Medical Biometry, Informatics and Epidemiology, Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Wolfram Gronwald
- Chair and Institute of Functional Genomics, University of Regensburg, Regensburg, Germany
| | - Peter J Oefner
- Chair and Institute of Functional Genomics, University of Regensburg, Regensburg, Germany.
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Steinbrenner I, Schultheiss UT, Kotsis F, Schlosser P, Stockmann H, Mohney RP, Schmid M, Oefner PJ, Eckardt KU, Köttgen A, Sekula P. Urine Metabolite Levels, Adverse Kidney Outcomes, and Mortality in CKD Patients: A Metabolome-wide Association Study. Am J Kidney Dis 2021; 78:669-677.e1. [PMID: 33839201 DOI: 10.1053/j.ajkd.2021.01.018] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Accepted: 01/22/2021] [Indexed: 01/01/2023]
Abstract
RATIONALE & OBJECTIVE Mechanisms underlying the variable course of disease progression in patients with chronic kidney disease (CKD) are incompletely understood. The aim of this study was to identify novel biomarkers of adverse kidney outcomes and overall mortality, which may offer insights into pathophysiologic mechanisms. STUDY DESIGN Metabolome-wide association study. SETTING & PARTICIPANTS 5,087 patients with CKD enrolled in the observational German Chronic Kidney Disease Study. EXPOSURES Measurements of 1,487 metabolites in urine. OUTCOMES End points of interest were time to kidney failure (KF), a combined end point of KF and acute kidney injury (KF+AKI), and overall mortality. ANALYTICAL APPROACH Statistical analysis was based on a discovery-replication design (ratio 2:1) and multivariable-adjusted Cox regression models. RESULTS After a median follow-up of 4 years, 362 patients died, 241 experienced KF, and 382 experienced KF+AKI. Overall, we identified 55 urine metabolites whose levels were significantly associated with adverse kidney outcomes and/or mortality. Higher levels of C-glycosyltryptophan were consistently associated with all 3 main end points (hazard ratios of 1.43 [95% CI, 1.27-1.61] for KF, 1.40 [95% CI, 1.27-1.55] for KF+AKI, and 1.47 [95% CI, 1.33-1.63] for death). Metabolites belonging to the phosphatidylcholine pathway showed significant enrichment. Members of this pathway contributed to the improvement of the prediction performance for KF observed when multiple metabolites were added to the well-established Kidney Failure Risk Equation. LIMITATIONS Findings among patients of European ancestry with CKD may not be generalizable to the general population. CONCLUSIONS Our comprehensive screen of the association between urine metabolite levels and adverse kidney outcomes and mortality identifies metabolites that predict KF and represents a valuable resource for future studies of biomarkers of CKD progression.
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Affiliation(s)
- Inga Steinbrenner
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg; Department of Medicine IV-Nephrology and Primary Care, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg
| | - Fruzsina Kotsis
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg; Department of Medicine IV-Nephrology and Primary Care, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg
| | - Pascal Schlosser
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg
| | - Helena Stockmann
- Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Berlin
| | | | - Matthias Schmid
- Department of Medical Biometry, Informatics and Epidemiology, University Hospital Bonn, Bonn
| | - Peter J Oefner
- Institute of Functional Genomics, University of Regensburg, Regensburg, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Berlin; Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen; Institute of Functional Genomics, University of Regensburg, Regensburg, Germany
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg.
| | - Peggy Sekula
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg.
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Schultheiss UT, Steinbrenner I, Nauck M, Schneider MP, Kotsis F, Baid-Agrawal S, Schaeffner E, Eckardt KU, Köttgen A, Sekula P. Thyroid function, renal events and mortality in chronic kidney disease patients: the German Chronic Kidney Disease study. Clin Kidney J 2021; 14:959-968. [PMID: 34349984 PMCID: PMC8328092 DOI: 10.1093/ckj/sfaa052] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Accepted: 03/18/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Hypothyroidism and low free triiodothyronine (FT3) syndrome [low FT3 levels with normal thyroid-stimulating hormone (TSH)] have been associated with reduced kidney function cross-sectionally in chronic kidney disease (CKD) patients with severely reduced estimated glomerular filtration rate (eGFR) or end-stage kidney disease (ESKD). Results on the prospective effects of impaired thyroid function on renal events and mortality for patients with severely reduced eGFR or from population-based cohorts are conflicting. Here we evaluated the association between thyroid and kidney function with eGFR (cross-sectionally) as well as renal events and mortality (prospectively) in a large, prospective cohort of CKD patients with mild to moderately reduced kidney function. METHODS Thyroid markers were measured among CKD patients from the German Chronic Kidney Disease study. Incident renal endpoints (combined ESKD, acute kidney injury and renal death) and all-cause mortality were abstracted from hospital records and death certificates. Time to first event analysis of complete data from baseline to the 4-year follow-up (median follow-up time 4.04 years) of 4600 patients was conducted. Multivariable linear regression and Cox proportional hazards models were fitted for single and combined continuous thyroid markers [TSH, free thyroxine (FT4), FT3] and thyroid status. RESULTS Cross-sectionally, the presence of low-FT3 syndrome showed a significant inverse association with eGFR and continuous FT3 levels alone showed a significant positive association with eGFR; in combination with FT4 and TSH, FT3 levels also showed a positive association and FT4 levels showed a negative association with eGFR. Prospectively, higher FT4 and lower FT3 levels were significantly associated with a higher risk of all-cause mortality (N events = 297). Per picomole per litre higher FT3 levels the risk of reaching the composite renal endpoint was 0.73-fold lower (95% confidence interval 0.65-0.82; N events = 615). Compared with euthyroid patients, patients with low-FT3 syndrome had a 2.2-fold higher risk and patients with hypothyroidism had a 1.6-fold higher risk of experiencing the composite renal endpoint. CONCLUSIONS Patients with mild to moderate CKD suffering from thyroid function abnormalities are at an increased risk of adverse renal events and all-cause mortality over time.
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Affiliation(s)
- Ulla T Schultheiss
- Institute of Genetic Epidemiology, Medical Center – University of Freiburg, Faculty of Medicine, Freiburg, Germany
- Department of Medicine IV – Nephrology and Primary Care, Medical Center - University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Inga Steinbrenner
- Institute of Genetic Epidemiology, Medical Center – University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Markus P Schneider
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Fruzsina Kotsis
- Institute of Genetic Epidemiology, Medical Center – University of Freiburg, Faculty of Medicine, Freiburg, Germany
- Department of Medicine IV – Nephrology and Primary Care, Medical Center - University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Seema Baid-Agrawal
- Department of Nephrology and Transplant Center, Sahlgrenska University Hospital, University of Gothenburg, Gothenburg, Sweden
| | - Elke Schaeffner
- Institute of Public Health, Charité–Universitätsmedizin Berlin, Berlin, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- Department of Nephrology and Medical Intensive Care, Charité–Universitätsmedizin Berlin, Berlin, Germany
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Medical Center – University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Peggy Sekula
- Institute of Genetic Epidemiology, Medical Center – University of Freiburg, Faculty of Medicine, Freiburg, Germany
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Zhou W, Brumpton B, Kabil O, Gudmundsson J, Thorleifsson G, Weinstock J, Zawistowski M, Nielsen JB, Chaker L, Medici M, Teumer A, Naitza S, Sanna S, Schultheiss UT, Cappola A, Karjalainen J, Kurki M, Oneka M, Taylor P, Fritsche LG, Graham SE, Wolford BN, Overton W, Rasheed H, Haug EB, Gabrielsen ME, Skogholt AH, Surakka I, Davey Smith G, Pandit A, Roychowdhury T, Hornsby WE, Jonasson JG, Senter L, Liyanarachchi S, Ringel MD, Xu L, Kiemeney LA, He H, Netea-Maier RT, Mayordomo JI, Plantinga TS, Hrafnkelsson J, Hjartarson H, Sturgis EM, Palotie A, Daly M, Citterio CE, Arvan P, Brummett CM, Boehnke M, de la Chapelle A, Stefansson K, Hveem K, Willer CJ, Åsvold BO. GWAS of thyroid stimulating hormone highlights pleiotropic effects and inverse association with thyroid cancer. Nat Commun 2020; 11:3981. [PMID: 32769997 PMCID: PMC7414135 DOI: 10.1038/s41467-020-17718-z] [Citation(s) in RCA: 64] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Accepted: 07/08/2020] [Indexed: 12/11/2022] Open
Abstract
Thyroid stimulating hormone (TSH) is critical for normal development and metabolism. To better understand the genetic contribution to TSH levels, we conduct a GWAS meta-analysis at 22.4 million genetic markers in up to 119,715 individuals and identify 74 genome-wide significant loci for TSH, of which 28 are previously unreported. Functional experiments show that the thyroglobulin protein-altering variants P118L and G67S impact thyroglobulin secretion. Phenome-wide association analysis in the UK Biobank demonstrates the pleiotropic effects of TSH-associated variants and a polygenic score for higher TSH levels is associated with a reduced risk of thyroid cancer in the UK Biobank and three other independent studies. Two-sample Mendelian randomization using TSH index variants as instrumental variables suggests a protective effect of higher TSH levels (indicating lower thyroid function) on risk of thyroid cancer and goiter. Our findings highlight the pleiotropic effects of TSH-associated variants on thyroid function and growth of malignant and benign thyroid tumors.
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Affiliation(s)
- Wei Zhou
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA.
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA.
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.
| | - Ben Brumpton
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Department of Thoracic Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Omer Kabil
- Department of Biological Chemistry, University of Michigan Medical School, Ann Arbor, Michigan, USA
- Division of Metabolism Endocrinology and Diabetes, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | | | | | - Josh Weinstock
- Center for Statistical Genetics and Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Matthew Zawistowski
- Center for Statistical Genetics and Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Jonas B Nielsen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Internal Medicine, Division of Cardiology, University of Michigan Medical School, Ann Arbor, Michigan, USA
- Department of Epidemiology Research, Statens Serum Institute, Copenhagen, Denmark
| | - Layal Chaker
- Erasmus MC Academic Center for Thyroid Diseases, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Marco Medici
- Erasmus MC Academic Center for Thyroid Diseases, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
- Division of Endocrinology, Department of Internal Medicine, Radboud University Medical Centre, Radboud Institute for Molecular Life Sciences, 6500HB, Nijmegen, The Netherlands
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
| | - Silvia Naitza
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche Monserrato, Monserrato, Italy
| | - Serena Sanna
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche Monserrato, Monserrato, Italy
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Ulla T Schultheiss
- Faculty of Medicine and Medical Center, Institute of Genetic Epidemiology, University of Freiburg, Freiburg, Germany
- Faculty of Medicine and Medical Center, Department of Medicine IV-Nephrology and Primary Care, University of Freiburg, Freiburg, Germany
| | - Anne Cappola
- Division of Endocrinology, Diabetes, and Metabolism, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA
| | - Juha Karjalainen
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki, 00014, Finland
| | - Mitja Kurki
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki, 00014, Finland
| | - Morgan Oneka
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA
| | - Peter Taylor
- Thyroid Research Group, Systems Immunity Research Institute, Cardiff University School of Medicine, Cardiff, UK
| | - Lars G Fritsche
- Center for Statistical Genetics and Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Sarah E Graham
- Department of Internal Medicine, Division of Cardiology, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Brooke N Wolford
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA
- Center for Statistical Genetics and Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - William Overton
- Center for Statistical Genetics and Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Humaira Rasheed
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Eirin B Haug
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Maiken E Gabrielsen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Faculty of Medicine and Health Sciences, Department of Public Health and Nursing, Norwegian University of Science and Technology, NTNU, Trondheim, Norway
| | - Anne Heidi Skogholt
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Faculty of Medicine and Health Sciences, Department of Public Health and Nursing, Norwegian University of Science and Technology, NTNU, Trondheim, Norway
| | - Ida Surakka
- Department of Internal Medicine, Division of Cardiology, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - George Davey Smith
- Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Anita Pandit
- Center for Statistical Genetics and Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Tanmoy Roychowdhury
- Department of Internal Medicine, Division of Cardiology, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Whitney E Hornsby
- Department of Internal Medicine, Division of Cardiology, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Jon G Jonasson
- Landspitali-University Hospital, 101, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, 101, Reykjavik, Iceland
- The Icelandic Cancer Registry, 105, Reykjavik, Iceland
| | - Leigha Senter
- Division of Human Genetics, Ohio State University Comprehensive Cancer Center, Columbus, Ohio, 43210, USA
| | - Sandya Liyanarachchi
- Department of Cancer Biology and Genetics, Ohio State University Comprehensive Cancer Center, Columbus, Ohio, 43210, USA
| | - Matthew D Ringel
- Division of Endocrinology, Diabetes, and Metabolism, The Ohio State University, Columbus, Ohio, 43210, USA
| | - Li Xu
- Department of Head and Neck Surgery, and Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, 77030, USA
| | - Lambertus A Kiemeney
- Radboud University Medical Centre, Radboud Institute for Health Sciences, 6500HB, Nijmegen, The Netherlands
| | - Huiling He
- Department of Cancer Biology and Genetics, Ohio State University Comprehensive Cancer Center, Columbus, Ohio, 43210, USA
| | - Romana T Netea-Maier
- Division of Endocrinology, Department of Internal Medicine, Radboud University Medical Centre, Radboud Institute for Molecular Life Sciences, 6500HB, Nijmegen, The Netherlands
| | | | - Theo S Plantinga
- Department of Pathology, Radboud University Medical Center, Radboud Institute for Molecular Life Sciences, 6500HB, Nijmegen, The Netherlands
| | | | | | - Erich M Sturgis
- Department of Head and Neck Surgery, and Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, 77030, USA
| | - Aarno Palotie
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki, 00014, Finland
| | - Mark Daly
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki, 00014, Finland
| | - Cintia E Citterio
- Division of Metabolism Endocrinology and Diabetes, University of Michigan Medical School, Ann Arbor, Michigan, USA
- Universidad de Buenos Aires, Facultad de Farmacia y Bioquímica, Departamento de Microbiología, Inmunología y Biotecnología/Cátedra de Genética, Buenos Aires, C1113AAD, Argentina
- CONICET-Universidad de Buenos Aires, Instituto de Inmunología, Genética y Metabolismo (INIGEM), C1120AAR, Buenos Aires, Argentina
| | - Peter Arvan
- Division of Metabolism Endocrinology and Diabetes, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Chad M Brummett
- Division of Pain Medicine, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Michael Boehnke
- Center for Statistical Genetics and Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Albert de la Chapelle
- Department of Cancer Biology and Genetics, Ohio State University Comprehensive Cancer Center, Columbus, Ohio, 43210, USA
| | - Kari Stefansson
- deCODE genetics/AMGEN, 101, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, 101, Reykjavik, Iceland
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger, 7600, Norway
- Department of Medicine, Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, 7600, Norway
| | - Cristen J Willer
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA
- Department of Internal Medicine, Division of Cardiology, University of Michigan Medical School, Ann Arbor, Michigan, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, Michigan, USA
| | - Bjørn Olav Åsvold
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger, 7600, Norway.
- Department of Endocrinology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway.
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Sekula P, Tin A, Schultheiss UT, Baid-Agrawal S, Mohney RP, Steinbrenner I, Yu B, Luo S, Boerwinkle E, Eckardt KU, Coresh J, Grams ME, Kӧttgen A. Urine 6-Bromotryptophan: Associations with Genetic Variants and Incident End-Stage Kidney Disease. Sci Rep 2020; 10:10018. [PMID: 32572055 PMCID: PMC7308283 DOI: 10.1038/s41598-020-66334-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Accepted: 05/17/2020] [Indexed: 12/24/2022] Open
Abstract
Higher serum 6-bromotryptophan has been associated with lower risk of chronic kidney disease (CKD) progression, implicating mechanisms beyond renal clearance. We studied genetic determinants of urine 6-bromotryptophan and its association with CKD risk factors and incident end-stage kidney disease (ESKD) in 4,843 participants of the German Chronic Kidney Disease (GCKD) study. 6-bromotryptophan was measured from urine samples using mass spectrometry. Patients with higher levels of urine 6-bromotryptophan had higher baseline estimated glomerular filtration rate (eGFR, p < 0.001). A genome-wide association study of urine 6-bromotryptophan identified two significant loci possibly related to its tubular reabsorption, SLC6A19, and its production, ERO1A, which was also associated with serum 6-bromotryptophan in an independent study. The association between urine 6-bromotryptophan and time to ESKD was assessed using Cox regression. There were 216 ESKD events after four years of follow-up. Compared with patients with undetectable levels, higher 6-bromotryptophan levels were associated with lower risk of ESKD in models unadjusted and adjusted for ESKD risk factors other than eGFR (
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Affiliation(s)
- Peggy Sekula
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Adrienne Tin
- Division of Nephrology, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
- The Memory Impairment and Neurodegenerative Dementia Center, University of Mississippi Medical Center, Jackson, MS, USA
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Division of Nephrology, Department of Medicine, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Seema Baid-Agrawal
- Department of Nephrology and Transplant Center, Sahlgrenska University Hospital, University of Gothenburg, Gothenburg, Sweden
| | | | - Inga Steinbrenner
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Bing Yu
- School of Public Health, The University of Texas Health Science Center at Houston, Houston, USA
| | - Shengyuan Luo
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA
| | - Eric Boerwinkle
- School of Public Health, The University of Texas Health Science Center at Houston, Houston, USA
| | - Kai-Uwe Eckardt
- Department of Nephrology and Medical Intensive Care, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Department of Nephrology and Hypertension, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91054, Erlangen, Germany
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA
| | - Morgan E Grams
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA
- Division of Nephrology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Anna Kӧttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
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31
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Fazzini F, Lamina C, Raschenberger J, Schultheiss UT, Kotsis F, Schönherr S, Weissensteiner H, Forer L, Steinbrenner I, Meiselbach H, Bärthlein B, Wanner C, Eckardt KU, Köttgen A, Kronenberg F. Results from the German Chronic Kidney Disease (GCKD) study support association of relative telomere length with mortality in a large cohort of patients with moderate chronic kidney disease. Kidney Int 2020; 98:488-497. [PMID: 32641227 DOI: 10.1016/j.kint.2020.02.034] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Revised: 02/12/2020] [Accepted: 02/20/2020] [Indexed: 02/08/2023]
Abstract
Telomere length is known to be inversely associated with aging and has been proposed as a marker for aging-related diseases. Telomere attrition can be accelerated by oxidative stress and inflammation, both commonly present in patients with chronic kidney disease. Here, we investigated whether relative telomere length is associated with mortality in a large cohort of patients with chronic kidney disease stage G3 and A1-3 or G1-2 with overt proteinuria (A3) at enrollment. Relative telomere length was quantified in peripheral blood by a quantitative PCR method in 4,955 patients from the GCKD study, an ongoing prospective observational cohort. Complete four-year follow-up was available from 4,926 patients in whom we recorded 354 deaths. Relative telomere length was a strong and independent predictor of all-cause mortality. Each decrease of 0.1 relative telomere length unit was highly associated with a 14% increased risk of death (hazard ratio1.14 [95% confidence interval 1.06-1.22]) in a model adjusted for age, sex, baseline eGFR, urine albumin/creatinine ratio, diabetes mellitus, prevalent cardiovascular disease, LDL-cholesterol, HDL-cholesterol, smoking, body mass index, systolic and diastolic blood pressure, C-reactive protein and serum albumin. This translated to a 75% higher risk for those in the lowest compared to the highest quartile of relative telomere length. The association was mainly driven by 117 cardiovascular deaths (1.20 [1.05-1.35]) as well as 67 deaths due to infections (1.27 [1.07-1.50]). Thus, our findings support an association of shorter telomere length with all-cause mortality, cardiovascular mortality and death due to infections in patients with moderate chronic kidney disease.
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Affiliation(s)
- Federica Fazzini
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Claudia Lamina
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Julia Raschenberger
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany; Renal Division, Department of Medicine IV, Medical Center-University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Fruzsina Kotsis
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany; Renal Division, Department of Medicine IV, Medical Center-University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Sebastian Schönherr
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Hansi Weissensteiner
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Lukas Forer
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Inga Steinbrenner
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Heike Meiselbach
- Department of Nephrology and Hypertension, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Barbara Bärthlein
- Medical Centre for Information and Communication Technology (MIK), University Hospital Erlangen, Erlangen, Germany
| | - Christoph Wanner
- Division of Nephrology, Department of Internal Medicine I, University Hospital Würzburg, Würzburg, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany; Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck, Austria.
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32
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Mirna M, Topf A, Wernly B, Rezar R, Paar V, Jung C, Salmhofer H, Kopp K, Hoppe UC, Schulze PC, Kretzschmar D, Schneider MP, Schultheiss UT, Sommerer C, Paul K, Wolf G, Lichtenauer M, Busch M. Novel Biomarkers in Patients with Chronic Kidney Disease: An Analysis of Patients Enrolled in the GCKD-Study. J Clin Med 2020; 9:jcm9030886. [PMID: 32213894 PMCID: PMC7141541 DOI: 10.3390/jcm9030886] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2020] [Revised: 03/16/2020] [Accepted: 03/19/2020] [Indexed: 12/12/2022] Open
Abstract
Background: Chronic kidney disease (CKD) and cardiovascular diseases (CVD) often occur concomitantly, and CKD is a major risk factor for cardiovascular mortality. Since some of the most commonly used biomarkers in CVD are permanently elevated in patients with CKD, novel biomarkers are warranted for clinical practice. Methods: Plasma concentrations of five cardiovascular biomarkers (soluble suppression of tumorigenicity (sST2), growth differentiation factor 15 (GDF-15), heart-type fatty acid-binding protein (H-FABP), insulin-like growth factor-binding protein 2 (IGF-BP2), and soluble urokinase plasminogen activator receptor) were analyzed by means of enzyme-linked immunosorbent assay (ELISA) in 219 patients with CKD enrolled in the German Chronic Kidney Disease (GCKD) study. Results: Except for sST2, all of the investigated biomarkers were significantly elevated in patients with CKD (2.0- to 4.4-fold increase in advanced CKD (estimated glomerular filtration rate (eGFR) < 30 mL/min/1.73 m² body surface area (BSA)) and showed a significant inverse correlation with eGFR. Moreover, all but H-FABP and sST2 were additionally elevated in patients with micro- and macro-albuminuria. Conclusions: Based on our findings, sST2 appears to be the biomarker whose diagnostic performance is least affected by decreased renal function, thus suggesting potential viability in the management of patients with CVD and concomitant CKD. The predictive potential of sST2 remains to be proven in endpoint studies.
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Affiliation(s)
- Moritz Mirna
- Department of Internal Medicine II, Division of Cardiology, Paracelsus Medical University of Salzburg, 5020 Salzburg, Austria; (M.M.); (A.T.); (B.W.); (R.R.); (V.P.); (K.K.); (U.C.H.)
| | - Albert Topf
- Department of Internal Medicine II, Division of Cardiology, Paracelsus Medical University of Salzburg, 5020 Salzburg, Austria; (M.M.); (A.T.); (B.W.); (R.R.); (V.P.); (K.K.); (U.C.H.)
| | - Bernhard Wernly
- Department of Internal Medicine II, Division of Cardiology, Paracelsus Medical University of Salzburg, 5020 Salzburg, Austria; (M.M.); (A.T.); (B.W.); (R.R.); (V.P.); (K.K.); (U.C.H.)
| | - Richard Rezar
- Department of Internal Medicine II, Division of Cardiology, Paracelsus Medical University of Salzburg, 5020 Salzburg, Austria; (M.M.); (A.T.); (B.W.); (R.R.); (V.P.); (K.K.); (U.C.H.)
| | - Vera Paar
- Department of Internal Medicine II, Division of Cardiology, Paracelsus Medical University of Salzburg, 5020 Salzburg, Austria; (M.M.); (A.T.); (B.W.); (R.R.); (V.P.); (K.K.); (U.C.H.)
| | - Christian Jung
- Department of Cardiology, Pulmonology and Vascular Medicine, Medical Faculty, Heinrich Heine University Duesseldorf, 40225 Duesseldorf, Germany;
| | - Hermann Salmhofer
- Department of Internal Medicine I, Division of Nephrology, Paracelsus Medical University of Salzburg, 5020 Salzburg, Austria;
| | - Kristen Kopp
- Department of Internal Medicine II, Division of Cardiology, Paracelsus Medical University of Salzburg, 5020 Salzburg, Austria; (M.M.); (A.T.); (B.W.); (R.R.); (V.P.); (K.K.); (U.C.H.)
| | - Uta C. Hoppe
- Department of Internal Medicine II, Division of Cardiology, Paracelsus Medical University of Salzburg, 5020 Salzburg, Austria; (M.M.); (A.T.); (B.W.); (R.R.); (V.P.); (K.K.); (U.C.H.)
| | - P. Christian Schulze
- Department of Internal Medicine I, Division of Cardiology, Friedrich Schiller University Jena, 07743 Jena, Germany; (P.C.S.); (D.K.)
| | - Daniel Kretzschmar
- Department of Internal Medicine I, Division of Cardiology, Friedrich Schiller University Jena, 07743 Jena, Germany; (P.C.S.); (D.K.)
| | - Markus P. Schneider
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg, 91054 Erlangen, Germany;
| | - Ulla T. Schultheiss
- Department of Medicine IV – Nephrology and Primary Care, Institute of Genetic Epidemiology, Medical Center–University of Freiburg, Faculty of Medicine, 79106 Freiburg, Germany;
| | - Claudia Sommerer
- Department of Nephrology, University of Heidelberg, 69117 Heidelberg, Germany;
| | - Katharina Paul
- Department of Internal Medicine III, Friedrich Schiller University Jena, 07743 Jena, Germany; (K.P.); (G.W.); (M.B.)
| | - Gunter Wolf
- Department of Internal Medicine III, Friedrich Schiller University Jena, 07743 Jena, Germany; (K.P.); (G.W.); (M.B.)
| | - Michael Lichtenauer
- Department of Internal Medicine II, Division of Cardiology, Paracelsus Medical University of Salzburg, 5020 Salzburg, Austria; (M.M.); (A.T.); (B.W.); (R.R.); (V.P.); (K.K.); (U.C.H.)
- Correspondence:
| | - Martin Busch
- Department of Internal Medicine III, Friedrich Schiller University Jena, 07743 Jena, Germany; (K.P.); (G.W.); (M.B.)
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Schmidt IM, Hübner S, Nadal J, Titze S, Schmid M, Bärthlein B, Schlieper G, Dienemann T, Schultheiss UT, Meiselbach H, Köttgen A, Flöge J, Busch M, Kreutz R, Kielstein JT, Eckardt KU. Patterns of medication use and the burden of polypharmacy in patients with chronic kidney disease: the German Chronic Kidney Disease study. Clin Kidney J 2019; 12:663-672. [PMID: 31584562 PMCID: PMC6768303 DOI: 10.1093/ckj/sfz046] [Citation(s) in RCA: 73] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Indexed: 02/06/2023] Open
Abstract
Background Patients with chronic kidney disease (CKD) bear a substantial burden of comorbidities leading to the prescription of multiple drugs and a risk of polypharmacy. However, data on medication use in this population are scarce. Methods A total of 5217 adults with an estimated glomerular filtration rate (eGFR) between 30 and 60 mL/min/1.73 m2 or an eGFR ≥60 mL/min/1.73m2 and overt proteinuria (>500 mg/day) were studied. Self-reported data on current medication use were assessed at baseline (2010-12) and after 4 years of follow-up (FU). Prevalence and risk factors associated with polypharmacy (defined as the regular use of five or more drugs per day) as well as initiation or termination of polypharmacy were evaluated using multivariable logistic regression. Results The prevalence of polypharmacy at baseline and FU was almost 80%, ranging from 62% in patients with CKD Stage G1 to 86% in those with CKD Stage G3b. The median number of different medications taken per day was eight (range 0-27). β-blockers, angiotensin-converting enzyme inhibitors and statins were most frequently used. Increasing CKD G stage, age and body mass index, diabetes mellitus, cardiovascular disease and a history of smoking were significantly associated with both the prevalence of polypharmacy and its maintenance during FU. Diabetes mellitus was also significantly associated with the initiation of polypharmacy [odds ratio (OR) 2.46, (95% confidence interval 1.36-4.45); P = 0.003]. Conclusion Medication burden in CKD patients is high. Further research appears warranted to address the implications of polypharmacy, risks of drug interactions and strategies for risk reduction in this vulnerable patient population.
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Affiliation(s)
- Insa M Schmidt
- Department of Clinical Pharmacology and Toxicology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Silvia Hübner
- Department of Nephrology and Hypertension, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Jennifer Nadal
- Department of Medical Biometry, Informatics, and Epidemiology, University Hospital, Bonn, Germany
| | - Stephanie Titze
- Department of Nephrology and Hypertension, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Matthias Schmid
- Department of Medical Biometry, Informatics, and Epidemiology, University Hospital, Bonn, Germany
| | - Barbara Bärthlein
- Department of Medical Informatics, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany.,Medical Centre for Information and Communication Technology, University Hospital Erlangen, Erlangen, Germany
| | - Georg Schlieper
- Division of Nephrology and Clinical Immunology, RWTH Aachen University Hospital, Aachen, Germany
| | - Thomas Dienemann
- Department of Nephrology and Hypertension, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Heike Meiselbach
- Department of Nephrology and Hypertension, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Jürgen Flöge
- Division of Nephrology and Clinical Immunology, RWTH Aachen University Hospital, Aachen, Germany
| | - Martin Busch
- Department of Internal Medicine III, University Hospital Jena, Jena, Germany
| | - Reinhold Kreutz
- Department of Clinical Pharmacology and Toxicology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Jan T Kielstein
- Medical Clinic V - Nephrology, Rheumatology, Blood Purification, Academic Teaching Hospital Braunschweig, Braunschweig, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany.,Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Berlin, Germany
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Fazzini F, Lamina C, Fendt L, Schultheiss UT, Kotsis F, Hicks AA, Meiselbach H, Weissensteiner H, Forer L, Krane V, Eckardt KU, Köttgen A, Kronenberg F. Mitochondrial DNA copy number is associated with mortality and infections in a large cohort of patients with chronic kidney disease. Kidney Int 2019; 96:480-488. [PMID: 31248648 DOI: 10.1016/j.kint.2019.04.021] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Revised: 03/29/2019] [Accepted: 04/05/2019] [Indexed: 12/16/2022]
Abstract
Damage of mitochondrial DNA (mtDNA) with reduction in copy number has been proposed as a biomarker for mitochondrial dysfunction and oxidative stress. Chronic kidney disease (CKD) is associated with increased mortality and risk of cardiovascular disease, but the underlying mechanisms remain incompletely understood. Here we investigated the prognostic role of mtDNA copy number for cause-specific mortality in 4812 patients from the German Chronic Kidney Disease study, an ongoing prospective observational national cohort study of patients with CKD stage G3 and A1-3 or G1-2 with overt proteinuria (A3) at enrollment. MtDNA was quantified in whole blood using a plasmid-normalized PCR-based assay. At baseline, 1235 patients had prevalent cardiovascular disease. These patients had a significantly lower mtDNA copy number than patients without cardiovascular disease (fully-adjusted model: odds ratio 1.03, 95% confidence interval [CI] 1.01-1.05 per 10 mtDNA copies decrease). After four years of follow-up, we observed a significant inverse association between mtDNA copy number and all-cause mortality, adjusted for kidney function and cardiovascular disease risk factors (hazard ratio 1.37, 95% CI 1.09-1.73 for quartile 1 compared to quartiles 2-4). When grouped by causes of death, estimates pointed in the same direction for all causes but in a fully-adjusted model decreased copy numbers were significantly lower only in infection-related death (hazard ratio 1.82, 95% CI 1.08-3.08). A similar association was observed for hospitalizations due to infections in 644 patients (hazard ratio 1.19, 95% CI 1.00-1.42 in the fully-adjusted model). Thus, our data support a role of mitochondrial dysfunction in increased cardiovascular disease and mortality risks as well as susceptibility to infections in patients with CKD.
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Affiliation(s)
- Federica Fazzini
- Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Claudia Lamina
- Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Liane Fendt
- Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany; Renal Division, Department of Medicine IV, Medical Center-University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Fruzsina Kotsis
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Andrew A Hicks
- Institute for Biomedicine, EURAC Research, Affiliated Institute of the University of Lübeck, Bolzano, Italy
| | - Heike Meiselbach
- Department of Nephrology and Hypertension, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Hansi Weissensteiner
- Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Lukas Forer
- Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Vera Krane
- Division of Nephrology, Department of Internal Medicine I, Division of Nephrology and Comprehensive Heart Failure Centre, University Hospital Würzburg, Würzburg, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany; Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Florian Kronenberg
- Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Medical University of Innsbruck, Innsbruck, Austria.
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35
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Zacharias HU, Altenbuchinger M, Schultheiss UT, Samol C, Kotsis F, Poguntke I, Sekula P, Krumsiek J, Köttgen A, Spang R, Oefner PJ, Gronwald W. A Novel Metabolic Signature To Predict the Requirement of Dialysis or Renal Transplantation in Patients with Chronic Kidney Disease. J Proteome Res 2019; 18:1796-1805. [PMID: 30817158 DOI: 10.1021/acs.jproteome.8b00983] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Identification of chronic kidney disease patients at risk of progressing to end-stage renal disease (ESRD) is essential for treatment decision-making and clinical trial design. Here, we explored whether proton nuclear magnetic resonance (NMR) spectroscopy of blood plasma improves the currently best performing kidney failure risk equation, the so-called Tangri score. Our study cohort comprised 4640 participants from the German Chronic Kidney Disease (GCKD) study, of whom 185 (3.99%) progressed over a mean observation time of 3.70 ± 0.88 years to ESRD requiring either dialysis or transplantation. The original four-variable Tangri risk equation yielded a C statistic of 0.863 (95% CI, 0.831-0.900). Upon inclusion of NMR features by state-of-the-art machine learning methods, the C statistic improved to 0.875 (95% CI, 0.850-0.911), thereby outperforming the Tangri score in 94 out of 100 subsampling rounds. Of the 24 NMR features included in the model, creatinine, high-density lipoprotein, valine, acetyl groups of glycoproteins, and Ca2+-EDTA carried the highest weights. In conclusion, proton NMR-based plasma fingerprinting improved markedly the detection of patients at risk of developing ESRD, thus enabling enhanced patient treatment.
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Affiliation(s)
- Helena U Zacharias
- Institute of Computational Biology, Helmholtz Zentrum München , Neuherberg 85764 , Germany
| | | | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology, and Medical Bioinformatics, Faculty of Medicine and Medical Center , University of Freiburg , Freiburg 79106 , Germany.,Renal Division, Department of Medicine IV, Faculty of Medicine and Medical Center , University of Freiburg , Freiburg 79106 , Germany
| | | | - Fruzsina Kotsis
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology, and Medical Bioinformatics, Faculty of Medicine and Medical Center , University of Freiburg , Freiburg 79106 , Germany.,Renal Division, Department of Medicine IV, Faculty of Medicine and Medical Center , University of Freiburg , Freiburg 79106 , Germany
| | - Inga Poguntke
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology, and Medical Bioinformatics, Faculty of Medicine and Medical Center , University of Freiburg , Freiburg 79106 , Germany
| | - Peggy Sekula
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology, and Medical Bioinformatics, Faculty of Medicine and Medical Center , University of Freiburg , Freiburg 79106 , Germany
| | - Jan Krumsiek
- Institute of Computational Biology, Helmholtz Zentrum München , Neuherberg 85764 , Germany.,Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Department of Physiology and Biophysics , Weill Cornell Medicine , New York , New York 10065 , United States
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology, and Medical Bioinformatics, Faculty of Medicine and Medical Center , University of Freiburg , Freiburg 79106 , Germany
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36
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Jing J, Ekici AB, Sitter T, Eckardt KU, Schaeffner E, Li Y, Kronenberg F, Köttgen A, Schultheiss UT. Genetics of serum urate concentrations and gout in a high-risk population, patients with chronic kidney disease. Sci Rep 2018; 8:13184. [PMID: 30181573 PMCID: PMC6123425 DOI: 10.1038/s41598-018-31282-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2017] [Accepted: 08/14/2018] [Indexed: 12/22/2022] Open
Abstract
We evaluated genetics of hyperuricemia and gout, their interaction with kidney function and medication intake in chronic kidney disease (CKD) patients. Genome-wide association studies (GWAS) of urate and gout were performed in 4941 CKD patients in the German Chronic Kidney Disease (GCKD) study. Effect estimates of 26 known urate-associated population-based single nucleotide polymorphisms (SNPs) were examined. Interactions of urate-associated variants with urate-altering medications and clinical characteristics of gout were evaluated. Genome-wide significant associations with serum urate and gout were identified for known loci at SLC2A9 and ABCG2, but not for novel loci. Effects of the 26 known SNPs were of similar magnitude in CKD patients compared to population-based individuals, except for SNPs at ABCG2 that showed greater effects in CKD. Gene-medication interactions were not significant when accounting for multiple testing. Associations with gout in specific joints were significant for SLC2A9 rs12498742 in wrists and midfoot joints. Known genetic variants in SLC2A9 and ABCG2 were associated with urate and gout in a CKD cohort, with effect sizes for ABCG2 significantly greater in CKD compared to the general population. CKD patients are at high risk of gout due to reduced kidney function, diuretics intake and genetic predisposition, making treatment to target challenging.
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Affiliation(s)
- Jiaojiao Jing
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, Medical Center-University of Freiburg, Faculty of Medicine, Freiburg, Germany
- Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Arif B Ekici
- Institute of Human Genetics, University of Erlangen-Nürnberg, Erlangen, Germany
| | - Thomas Sitter
- Department of Nephrology and Hypertension, Ludwig-Maximilians University, Munich, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Medical Intensive Care, Charité, University-Medicine, Berlin, Germany
| | - Elke Schaeffner
- Institute of Public Health, Charité, University-Medicine, Berlin, Germany
| | - Yong Li
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, Medical Center-University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Florian Kronenberg
- Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, Innsbruck, Austria
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, Medical Center-University of Freiburg, Faculty of Medicine, Freiburg, Germany.
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, Medical Center-University of Freiburg, Faculty of Medicine, Freiburg, Germany
- Renal Division, Department of Medicine IV, Medical Center - University of Freiburg, Faculty of Medicine, Freiburg, Germany
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Li Y, Sekula P, Wuttke M, Wahrheit J, Hausknecht B, Schultheiss UT, Gronwald W, Schlosser P, Tucci S, Ekici AB, Spiekerkoetter U, Kronenberg F, Eckardt KU, Oefner PJ, Köttgen A. Genome-Wide Association Studies of Metabolites in Patients with CKD Identify Multiple Loci and Illuminate Tubular Transport Mechanisms. J Am Soc Nephrol 2018; 29:1513-1524. [PMID: 29545352 DOI: 10.1681/asn.2017101099] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2017] [Accepted: 02/09/2018] [Indexed: 12/24/2022] Open
Abstract
Background The kidneys have a central role in the generation, turnover, transport, and excretion of metabolites, and these functions can be altered in CKD. Genetic studies of metabolite concentrations can identify proteins performing these functions.Methods We conducted genome-wide association studies and aggregate rare variant tests of the concentrations of 139 serum metabolites and 41 urine metabolites, as well as their pairwise ratios and fractional excretions in up to 1168 patients with CKD.Results After correction for multiple testing, genome-wide significant associations were detected for 25 serum metabolites, two urine metabolites, and 259 serum and 14 urinary metabolite ratios. These included associations already known from population-based studies. Additional findings included an association for the uremic toxin putrescine and variants upstream of an enzyme catalyzing the oxidative deamination of polyamines (AOC1, P-min=2.4×10-12), a relatively high carrier frequency (2%) for rare deleterious missense variants in ACADM that are collectively associated with serum ratios of medium-chain acylcarnitines (P-burden=6.6×10-16), and associations of a common variant in SLC7A9 with several ratios of lysine to neutral amino acids in urine, including the lysine/glutamine ratio (P=2.2×10-23). The associations of this SLC7A9 variant with ratios of lysine to specific neutral amino acids were much stronger than the association with lysine concentration alone. This finding is consistent with SLC7A9 functioning as an exchanger of urinary cationic amino acids against specific intracellular neutral amino acids at the apical membrane of proximal tubular cells.Conclusions Metabolomic indices of specific kidney functions in genetic studies may provide insight into human renal physiology.
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Affiliation(s)
- Yong Li
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology, and Medical Bioinformatics, and
| | - Peggy Sekula
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology, and Medical Bioinformatics, and
| | - Matthias Wuttke
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology, and Medical Bioinformatics, and
| | - Judith Wahrheit
- BIOCRATES Life Sciences Aktiengesellschaft, Innsbruck, Austria
| | | | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology, and Medical Bioinformatics, and
| | - Wolfram Gronwald
- Institute of Functional Genomics, University of Regensburg, Regensburg, Germany; and
| | - Pascal Schlosser
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology, and Medical Bioinformatics, and
| | - Sara Tucci
- Department of General Pediatrics, Center for Pediatrics and Adolescent Medicine, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Arif B Ekici
- Insitute of Human Genetics, University of Erlangen-Nürnberg, Erlangen, Germany
| | - Ute Spiekerkoetter
- Department of General Pediatrics, Center for Pediatrics and Adolescent Medicine, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Florian Kronenberg
- Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | | | - Peter J Oefner
- Institute of Functional Genomics, University of Regensburg, Regensburg, Germany; and
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology, and Medical Bioinformatics, and
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Schultheiss UT, Daya N, Grams ME, Seufert J, Steffes M, Coresh J, Selvin E, Köttgen A. Thyroid function, reduced kidney function and incident chronic kidney disease in a community-based population: the Atherosclerosis Risk in Communities study. Nephrol Dial Transplant 2017; 32:1874-1881. [PMID: 27540046 PMCID: PMC5837276 DOI: 10.1093/ndt/gfw301] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2016] [Accepted: 07/12/2016] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Reduced kidney function is a common public health problem that increases risk for a wide variety of adverse outcomes, making the identification of potentially modifiable factors associated with the development of incident chronic kidney disease (CKD) important. Alterations in the hypothalamic-pituitary-thyroid axis have been linked to reduced kidney function, but the association of thyroid function with the development of incident CKD is largely uncharacterized. METHODS Concentrations of thyroid stimulating hormone (TSH), free thyroxine (FT4), triiodothyronine (T3) and thyroid peroxidase antibody (TPOAb) were quantified in 12 785 black and white participants of the ongoing community-based prospective Atherosclerosis Risk in Communities study. Thyroid markers and clinical categories of thyroid dysfunction (euthyroidism, combined subclinical and overt hypothyroidism, combined subclinical and overt hyperthyroidism) were also evaluated for their association with reduced kidney function (estimated glomerular filtration rate <60 mL/min/1.73 m2) at study baseline and with incident CKD over a median follow-up time of 19.6 years. RESULTS Higher TSH and FT4 as well as lower T3 concentrations were strongly and independently associated with reduced kidney function at study baseline. The clinical entities hypothyroidism and hyperthyroidism were also associated with higher odds of baseline reduced kidney function, but this was not significant. However, none of the markers of thyroid function nor different clinical categories of thyroid dysfunction (hypothyroidism, hyperthyroidism or TPOAb positivity) were associated with incident CKD in adjusted analyses. CONCLUSIONS Elevated TSH, FT4 and reduced T3 concentrations were associated with reduced kidney function cross-sectionally. The lack of association with the development of incident CKD suggests that altered thyroid function in the general population is not causally related to CKD development, but screening for thyroidal status may be especially relevant in persons with reduced kidney function.
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Affiliation(s)
- Ulla T Schultheiss
- Renal Division, Department of Medicine IV, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Division of Genetic Epidemiology, Institute of Medical Biometry and Statistics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Natalie Daya
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Morgan E Grams
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Division of Nephrology, Johns Hopkins University, Baltimore, MD, USA
| | - Jochen Seufert
- Division of Endocrinology and Diabetology, Department of Medicine II, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Michael Steffes
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Elizabeth Selvin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Anna Köttgen
- Renal Division, Department of Medicine IV, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Division of Genetic Epidemiology, Institute of Medical Biometry and Statistics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
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Wunnenburger S, Schultheiss UT, Walz G, Hausknecht B, Ekici AB, Kronenberg F, Eckardt KU, Köttgen A, Wuttke M. Associations between genetic risk variants for kidney diseases and kidney disease etiology. Sci Rep 2017; 7:13944. [PMID: 29066732 PMCID: PMC5655008 DOI: 10.1038/s41598-017-13356-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2017] [Accepted: 09/21/2017] [Indexed: 01/10/2023] Open
Abstract
Chronic kidney disease (CKD) is a global health problem with a genetic component. Genome-wide association studies have identified variants associated with specific CKD etiologies, but their genetic overlap has not been well studied. This study examined SNP associations across different CKD etiologies and CKD stages using data from 5,034 CKD patients of the German Chronic Kidney Disease study. In addition to confirming known associations, a systemic lupus erythematosus-associated risk variant at TNXB was also associated with CKD attributed to type 1 diabetes (p = 2.5 × 10-7), a membranous nephropathy-associated variant at HLA-DQA1 was also associated with CKD attributed to systemic lupus erythematosus (p = 5.9 × 10-6), and an IgA risk variant at HLA-DRB1 was associated with both CKD attributed to granulomatosis with polyangiitis (p = 2.0 × 10-4) and to type 1 diabetes (p = 4.6 × 10-11). Associations were independent of additional risk variants in the respective genetic regions. Evaluation of CKD stage showed a significant association of the UMOD risk variant, previously identified in population-based studies for association with kidney function, for advanced (stage ≥G3b) compared to early-stage CKD (≤stage G2). Shared genetic associations across CKD etiologies and stages highlight the role of the immune response in CKD. Association studies with detailed information on CKD etiology can reveal shared genetic risk variants.
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Affiliation(s)
- Sebastian Wunnenburger
- Institute of Genetic Epidemiology, Medical Center - University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Medical Center - University of Freiburg, Faculty of Medicine, Freiburg, Germany
- Division of Nephrology, University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Gerd Walz
- Division of Nephrology, University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Birgit Hausknecht
- Department of Nephrology and Hypertension, University of Erlangen-Nürnberg, Erlangen, Germany
| | - Arif B Ekici
- Institute of Human Genetics, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Florian Kronenberg
- Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, University of Erlangen-Nürnberg, Erlangen, Germany
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Medical Center - University of Freiburg, Faculty of Medicine, Freiburg, Germany.
| | - Matthias Wuttke
- Institute of Genetic Epidemiology, Medical Center - University of Freiburg, Faculty of Medicine, Freiburg, Germany
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40
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Obrador GT, Schultheiss UT, Kretzler M, Langham RG, Nangaku M, Pecoits-Filho R, Pollock C, Rossert J, Correa-Rotter R, Stenvinkel P, Walker R, Yang CW, Fox CS, Köttgen A. Genetic and environmental risk factors for chronic kidney disease. Kidney Int Suppl (2011) 2017; 7:88-106. [PMID: 30675423 DOI: 10.1016/j.kisu.2017.07.004] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
In order to change the current state of chronic kidney disease knowledge and therapeutics, a fundamental improvement in the understanding of genetic and environmental causes of chronic kidney disease is essential. This article first provides an overview of the existing knowledge gaps in our understanding of the genetic and environmental causes of chronic kidney disease, as well as their interactions. The second part of the article formulates goals that should be achieved in order to close these gaps, along with suggested timelines and stakeholders that are to be involved. A better understanding of genetic and environmental factors and their interactions that influence kidney function in healthy and diseased conditions can provide novel insights into renal physiology and pathophysiology and result in the identification of novel therapeutic or preventive targets to tackle the global public health care problem of chronic kidney disease.
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Affiliation(s)
- Gregorio T Obrador
- Department of Epidemiology, Biostatistics and Public Health, Universidad Panamericana School of Medicine, Mexico City, Mexico
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Medical Center and Faculty of Medicine-University of Freiburg, Freiburg, Germany.,Renal Division, Department of Medicine IV, Medical Center-University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Matthias Kretzler
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA.,Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA
| | - Robyn G Langham
- Monash Rural Health, Monash University, Clayton VIC, Australia
| | - Masaomi Nangaku
- Department of Hemodialysis and Apheresis, Division of Nephrology and Endocrinology, University of Tokyo Graduate School of Medicine, Tokyo, Japan
| | - Roberto Pecoits-Filho
- Department of Internal Medicine, School of Medicine, Pontificia Universidade Catolica do Paraná, Curitiba, Brazil
| | - Carol Pollock
- Kolling Institute of Medical Research, University of Sydney, Sydney, NSW, Australia
| | | | - Ricardo Correa-Rotter
- Department of Nephrology and Mineral Metabolism, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zuibrán, Mexico City, Mexico
| | - Peter Stenvinkel
- Division of Renal Medicine, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden
| | - Robert Walker
- Department of Medicine, University of Otago, Dunedin, New Zealand
| | - Chih-Wei Yang
- Kidney Research Center, Department of Nephrology, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Caroline S Fox
- Genetics and Pharmacogenomics, Merck Research Laboratories, Boston, Massachusetts, USA
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Medical Center and Faculty of Medicine-University of Freiburg, Freiburg, Germany
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Busch M, Nadal J, Schmid M, Paul K, Titze S, Hübner S, Köttgen A, Schultheiss UT, Baid-Agrawal S, Lorenzen J, Schlieper G, Sommerer C, Krane V, Hilge R, Kielstein JT, Kronenberg F, Wanner C, Eckardt KU, Wolf G. Glycaemic control and antidiabetic therapy in patients with diabetes mellitus and chronic kidney disease - cross-sectional data from the German Chronic Kidney Disease (GCKD) cohort. BMC Nephrol 2016; 17:59. [PMID: 27286816 PMCID: PMC4902996 DOI: 10.1186/s12882-016-0273-z] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2015] [Accepted: 06/02/2016] [Indexed: 01/08/2023] Open
Abstract
Background Diabetes mellitus (DM) is the leading cause of end-stage renal disease. Little is known about practice patterns of anti-diabetic therapy in the presence of chronic kidney disease (CKD) and correlates with glycaemic control. We therefore aimed to analyze current antidiabetic treatment and correlates of metabolic control in a large contemporary prospective cohort of patients with diabetes and CKD. Methods The German Chronic Kidney Disease (GCKD) study enrolled 5217 patients aged 18–74 years with an estimated glomerular filtration rate (eGFR) between 30–60 mL/min/1.73 m2 or proteinuria >0.5 g/d. The use of diet prescription, oral anti-diabetic medication, and insulin was assessed at baseline. HbA1c, measured centrally, was the main outcome measure. Results At baseline, DM was present in 1842 patients (35 %) and the median HbA1C was 7.0 % (25th–75th percentile: 6.8–7.9 %), equalling 53 mmol/mol (51, 63); 24.2 % of patients received dietary treatment only, 25.5 % oral antidiabetic drugs but not insulin, 8.4 % oral antidiabetic drugs with insulin, and 41.8 % insulin alone. Metformin was used by 18.8 %. Factors associated with an HbA1C level >7.0 % (53 mmol/mol) were higher BMI (OR = 1.04 per increase of 1 kg/m2, 95 % CI 1.02–1.06), hemoglobin (OR = 1.11 per increase of 1 g/dL, 95 % CI 1.04–1.18), treatment with insulin alone (OR = 5.63, 95 % CI 4.26–7.45) or in combination with oral antidiabetic agents (OR = 4.23, 95 % CI 2.77–6.46) but not monotherapy with metformin, DPP-4 inhibitors, or glinides. Conclusions Within the GCKD cohort of patients with CKD stage 3 or overt proteinuria, antidiabetic treatment patterns were highly variable with a remarkably high proportion of more than 50 % receiving insulin-based therapies. Metabolic control was overall satisfactory, but insulin use was associated with higher HbA1C levels. Electronic supplementary material The online version of this article (doi:10.1186/s12882-016-0273-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Martin Busch
- Department of Internal Medicine III, University Hospital Jena - Friedrich Schiller University, Erlanger Allee 101, D - 07747, Jena, Germany.
| | - Jennifer Nadal
- Institute of Medical Biometry, Informatics and Epidemiology, University of Bonn, Bonn, Germany
| | - Matthias Schmid
- Institute of Medical Biometry, Informatics and Epidemiology, University of Bonn, Bonn, Germany
| | - Katharina Paul
- Department of Internal Medicine III, University Hospital Jena - Friedrich Schiller University, Erlanger Allee 101, D - 07747, Jena, Germany
| | - Stephanie Titze
- Department of Nephrology and Hypertension, University of Erlangen-Nürnberg, Erlangen, Germany
| | - Silvia Hübner
- Department of Nephrology and Hypertension, University of Erlangen-Nürnberg, Erlangen, Germany
| | - Anna Köttgen
- Department of Internal Medicine IV, Medical Center University of Freiburg, Freiburg, Germany
| | - Ulla T Schultheiss
- Department of Internal Medicine IV, Medical Center University of Freiburg, Freiburg, Germany
| | - Seema Baid-Agrawal
- Department of Medicine, Division of Nephrology and Medical Intensive Care, University Hospital Charité, Berlin, Germany
| | - Johan Lorenzen
- Hannover Medical School, Clinic for Nephrology, Hannover, Germany
| | - Georg Schlieper
- Department of Medicine II - Nephrology and Clinical Immunology, University Hospital Aachen, Aachen, Germany
| | - Claudia Sommerer
- Department of Medicine, Division of Nephrology, University Hospital Heidelberg, Heidelberg, Germany
| | - Vera Krane
- Department of Medicine I, Division of Nephrology, University Hospital Würzburg, Würzburg, Germany
| | - Robert Hilge
- Department of Medicine IV, Division of Nephrology, University Hospital of Ludwig-Maximilians University Munich, Munich, Germany
| | - Jan T Kielstein
- Hannover Medical School, Clinic for Nephrology, Hannover, Germany
| | - Florian Kronenberg
- Division of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Christoph Wanner
- Department of Medicine I, Division of Nephrology, University Hospital Würzburg, Würzburg, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, University of Erlangen-Nürnberg, Erlangen, Germany
| | - Gunter Wolf
- Department of Internal Medicine III, University Hospital Jena - Friedrich Schiller University, Erlanger Allee 101, D - 07747, Jena, Germany
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Beck H, Titze SI, Hübner S, Busch M, Schlieper G, Schultheiss UT, Wanner C, Kronenberg F, Krane V, Eckardt KU, Köttgen A. Correction: Heart Failure in a Cohort of Patients with Chronic Kidney Disease: The GCKD Study. PLoS One 2015; 10:e0131034. [PMID: 26075728 PMCID: PMC4468263 DOI: 10.1371/journal.pone.0131034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022] Open
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Schultheiss UT, Teumer A, Medici M, Li Y, Daya N, Chaker L, Homuth G, Uitterlinden AG, Nauck M, Hofman A, Selvin E, Völzke H, Peeters RP, Köttgen A. A genetic risk score for thyroid peroxidase antibodies associates with clinical thyroid disease in community-based populations. J Clin Endocrinol Metab 2015; 100:E799-807. [PMID: 25719932 PMCID: PMC4422885 DOI: 10.1210/jc.2014-4352] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
CONTEXT Antibodies against thyroid peroxidase (TPOAbs) are detected in 90% of all patients with Hashimoto thyroiditis, the most common cause of hypothyroidism. Hypothyroidism is associated with a range of adverse outcomes. The current knowledge of its genetic underpinnings is limited. OBJECTIVE The purpose of this study was to identify novel genetic variants associated with TPOAb concentrations and positivity using genome-wide association data and to characterize their association with thyroid function and disease. DESIGN, SETTING, AND PARTICIPANTS We studied European ancestry participants of 3 independent prospective population-based studies: Atherosclerosis Risk In Communities study (n = 7524), Study of Health in Pomerania (n = 3803), and Study of Health in Pomerania-TREND (n = 887). EXPOSURE Single nucleotide polymorphisms (SNPs), individually and combined into a genetic risk score (GRS), were examined. MAIN OUTCOMES The main outcomes were TPOAb concentrations and positivity, thyroid hormone concentrations (TSH, free T4), and clinical thyroid diseases (subclinical and overt hypothyroidism and goiter). RESULTS Significantly associated single nucleotide polymorphisms (P < 5 · 10(-8)) mapped into 4 genomic regions not previously implicated for TPOAbs (RERE, extended HLA region) and into 5 previously described loci. A higher Genetic Risk Score (GRS) based on these 9 SNPs showed strong and graded associations with higher TPOAb, TSH, and lower free T4 concentrations (P < .001). Compared with individuals in the lowest GRS quartile, those in the highest quartile had 1.80-fold higher odds of subclinical hypothyroidism (95% confidence interval, 1.27-2.55) and 1.89-fold higher odds of overt hypothyroidism (95% confidence interval, 1.24-2.87). CONCLUSION The identification of 4 novel genetic loci associated with TPOAb concentrations and positivity gives further insight into the genetic underpinnings of hypothyroidism. A GRS showed strong and graded associations with markers of thyroid function and disease in independent population-based studies.
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Affiliation(s)
- Ulla T Schultheiss
- Renal Division (U.T.S., Y.L., A.K.), Department of Medicine IV, Medical Center, University of Freiburg, 79106 Freiburg, Germany; Department of Internal Medicine and Rotterdam Thyroid Center (M.M., L.C., A.G.U., R.P.P.) and Department of Epidemiology (L.C., A.H.), Erasmus Medical Center, 3015 GE Rotterdam, The Netherlands; Institute for Community Medicine (A.T., H.V.), Interfaculty Institute for Genetics and Functional Genomics (G.H.), and Institute of Clinical Chemistry and Laboratory Medicine (M.N.), University Medicine Greifswald, 17475 Greifswald, Germany; and Department of Epidemiology (N.D., E.S., A.K.), Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205
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Beck H, Titze SI, Hübner S, Busch M, Schlieper G, Schultheiss UT, Wanner C, Kronenberg F, Krane V, Eckardt KU, Köttgen A. Heart failure in a cohort of patients with chronic kidney disease: the GCKD study. PLoS One 2015; 10:e0122552. [PMID: 25874373 PMCID: PMC4395150 DOI: 10.1371/journal.pone.0122552] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2014] [Accepted: 02/22/2015] [Indexed: 01/13/2023] Open
Abstract
Background and Aims Chronic kidney disease (CKD) is a risk factor for development and progression of heart failure (HF). CKD and HF share common risk factors, but few data exist on the prevalence, signs and symptoms as well as correlates of HF in populations with CKD of moderate severity. We therefore aimed to examine the prevalence and correlates of HF in the German Chronic Kidney Disease (GCKD) study, a large observational prospective study. Methods and Results We analyzed data from 5,015 GCKD patients aged 18–74 years with an estimated glomerular filtration rate (eGFR) of <60 ml/min/1.73m² or with an eGFR ≥60 and overt proteinuria (>500 mg/d). We evaluated a definition of HF based on the Gothenburg score, a clinical HF score used in epidemiological studies (Gothenburg HF), and self-reported HF. Factors associated with HF were identified using multivariable adjusted logistic regression. The prevalence of Gothenburg HF was 43% (ranging from 24% in those with eGFR >90 to 59% in those with eGFR<30 ml/min/1.73m2). The corresponding estimate for self-reported HF was 18% (range 5%-24%). Lower eGFR was significantly and independently associated with the Gothenburg definition of HF (p-trend <0.001). Additional significantly associated correlates included older age, female gender, higher BMI, hypertension, diabetes mellitus, valvular heart disease, anemia, sleep apnea, and lower educational status. Conclusions The burden of self-reported and Gothenburg HF among patients with CKD is high. The proportion of patients who meet the criteria for Gothenburg HF in a European cohort of patients with moderate CKD is more than twice as high as the prevalence of self-reported HF. However, because of the shared signs, symptoms and medications of HF and CKD, the Gothenburg score cannot be used to reliably define HF in CKD patients. Our results emphasize the need for early screening for HF in patients with CKD.
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Affiliation(s)
- Hanna Beck
- Department of Medicine, Division of Nephrology, Medical Center—University of Freiburg, Freiburg, Germany
| | - Stephanie I. Titze
- Department of Nephrology and Hypertension, University of Erlangen-Nürnberg, Erlangen, Germany
| | - Silvia Hübner
- Department of Nephrology and Hypertension, University of Erlangen-Nürnberg, Erlangen, Germany
| | - Martin Busch
- Department of Internal Medicine III, University of Jena, Jena, Germany
| | - Georg Schlieper
- Division of Nephrology and Clinical Immunology, Medical Faculty RWTH Aachen University, Aachen, Germany
| | - Ulla T. Schultheiss
- Department of Medicine, Division of Nephrology, Medical Center—University of Freiburg, Freiburg, Germany
| | - Christoph Wanner
- Department of Internal Medicine I, Division of Nephrology, University of Würzburg, Würzburg, Germany
- Comprehensive Heart Failure Centre, University of Würzburg, Würzburg, Germany
| | - Florian Kronenberg
- Department of Medical Genetics, Molecular and Clinical Pharmacology, Division of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Vera Krane
- Department of Internal Medicine I, Division of Nephrology, University of Würzburg, Würzburg, Germany
- Comprehensive Heart Failure Centre, University of Würzburg, Würzburg, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, University of Erlangen-Nürnberg, Erlangen, Germany
| | - Anna Köttgen
- Department of Medicine, Division of Nephrology, Medical Center—University of Freiburg, Freiburg, Germany
- * E-mail:
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Eckardt KU, Bärthlein B, Baid-Agrawal S, Beck A, Busch M, Eitner F, Ekici AB, Floege J, Gefeller O, Haller H, Hilge R, Hilgers KF, Kielstein JT, Krane V, Köttgen A, Kronenberg F, Oefner P, Prokosch HU, Reis A, Schmid M, Schaeffner E, Schultheiss UT, Seuchter SA, Sitter T, Sommerer C, Walz G, Wanner C, Wolf G, Zeier M, Titze S. The German Chronic Kidney Disease (GCKD) study: design and methods. Nephrol Dial Transplant 2011; 27:1454-60. [PMID: 21862458 DOI: 10.1093/ndt/gfr456] [Citation(s) in RCA: 112] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND Chronic kidney disease (CKD) is increasingly recognized as a global health problem. The conditions leading to CKD, the health impact of CKD and the prognosis differ markedly between affected individuals. In particular, renal failure and cardiovascular mortality are competing risks for CKD patients. Opportunities for targeted intervention are very limited so far and require an improved understanding of the natural course of CKD, of the risk factors associated with various clinical end points and co-morbidities as well as of the underlying pathogenic mechanisms. METHODS The German Chronic Kidney Disease (GCKD) study is a prospective observational national cohort study. It aims to enrol a total of 5000 patients with CKD of various aetiologies, who are under nephrological care, and to follow them for up to 10 years. At the time of enrolment, male and female patients have an estimated glomerular filtration rate (eGFR) of 30-60 mL/min×1.73 m2 or overt proteinuria in the presence of an eGFR>60 mL/min×1.73 m2. Standardized collection of biomaterials, including DNA, serum, plasma and urine will allow identification and validation of biomarkers associated with CKD, CKD progression and related complications using hypothesis-driven and hypothesis-free approaches. Patient recruitment and follow-up is organized through a network of academic nephrology centres collaborating with practising nephrologists throughout the country. CONCLUSIONS The GCKD study will establish one of the largest cohorts to date of CKD patients not requiring renal replacement therapy. Similarities in its design with other observational CKD studies, including cohorts that have already been established in the USA and Japan, will allow comparative and joint analyses to identify important ethnic and geographic differences and to enhance opportunities for identification of relevant risk factors and markers.
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Affiliation(s)
- Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, University of Erlangen-Nürnberg, Erlangen, Germany.
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Otto EA, Trapp ML, Schultheiss UT, Helou J, Quarmby LM, Hildebrandt F. NEK8 mutations affect ciliary and centrosomal localization and may cause nephronophthisis. J Am Soc Nephrol 2008; 19:587-92. [PMID: 18199800 DOI: 10.1681/asn.2007040490] [Citation(s) in RCA: 144] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
Nephronophthisis, an autosomal recessive kidney disease, is the most frequent genetic cause of chronic renal failure in the first 3 decades of life. Causative mutations in 8 genes (NPHP1-8) have been identified, and homologous mouse models for NPHP2/INVS and NPHP3 have been described. The jck mouse is another model of recessive cystic kidney disease, and this mouse harbors a missense mutation, G448V, in the highly conserved RCC1 domain of Nek8. We hypothesized that mutations in NEK8 might cause nephronophthisis in humans, so we performed mutational analysis in a worldwide cohort of 588 patients. We identified 3 different amino acid changes that were conserved through evolution (L330F, H425Y, and A497P) and that were absent from at least 80 ethnically matched controls. All 3 mutations were within RCC1 domains, and the mutation H425Y was positioned within the same RCC1 repeat as the mouse jck mutation. To test the functional significance of these mutations, we introduced them into full-length mouse Nek8 GFP-tagged cDNA constructs. We transiently overexpressed the constructs in inner medullary collecting duct cells (IMCD-3 cell line) and compared the subcellular localization of mutant Nek8 to wild-type Nek8. All mutant forms of Nek8 showed defects in ciliary localization to varying degrees; the H431Y mutant (human H425Y) was completely absent from cilia and the amount localized to centrosomes was decreased. Overexpression of these mutants did not affect overall ciliogenesis, mitosis, or centriole number. Our genetic and functional data support the assumption that mutations in NEK8 cause nephronophthisis (NPHP9), adding another link between proteins mutated in cystic kidney disease and their localization to cilia and centrosomes.
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Affiliation(s)
- Edgar A Otto
- University of Michigan Health System, 8220C MSRB III, 1150 West Medical Center Drive, Ann Arbor, MI 48109-5646, USA
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Schultheiss UT, Göbel H, von Gersdorff G, Stubanus M, Walz G, Gerke P. Quiz page December 2007: diarrhea and anuria in a recipient of an en bloc infant kidney transplant. Am J Kidney Dis 2007; 50:A41-3. [PMID: 18037088 DOI: 10.1053/j.ajkd.2007.07.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2007] [Accepted: 07/26/2007] [Indexed: 11/11/2022]
Affiliation(s)
- Ulla T Schultheiss
- Renal Division, Department of Medicine, University Hospital Freiburg, Freiburg, Germany
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