Integrative analysis of prognostic biomarkers derived from multiomics panels helps discrimination of chronic kidney disease trajectories in people with type 2 diabetes.

Aged Bayes Theorem Biomarkers / blood Case-Control Studies Diabetes Mellitus, Type 2 / complications Female Glomerular Filtration Rate Hepatitis A Virus Cellular Receptor 1 / blood Humans Male Middle Aged Natriuretic Peptide, Brain / blood Peptide Fragments / blood Renal Insufficiency, Chronic / blood
biomarkers chronic kidney disease integrative analysis multiomics prognosis type 2 diabetes

Journal

Kidney international
ISSN: 1523-1755
Titre abrégé: Kidney Int
Pays: United States
ID NLM: 0323470

Informations de publication

Date de publication:
12 2019
Historique:
received: 02 05 2019
revised: 11 07 2019
accepted: 25 07 2019
pubmed: 5 11 2019
medline: 5 11 2020
entrez: 5 11 2019
Statut: ppublish

Résumé

Clinical risk factors explain only a fraction of the variability of estimated glomerular filtration rate (eGFR) decline in people with type 2 diabetes. Cross-omics technologies by virtue of a wide spectrum screening of plasma samples have the potential to identify biomarkers for the refinement of prognosis in addition to clinical variables. Here we utilized proteomics, metabolomics and lipidomics panel assay measurements in baseline plasma samples from the multinational PROVALID study (PROspective cohort study in patients with type 2 diabetes mellitus for VALIDation of biomarkers) of patients with incident or early chronic kidney disease (median follow-up 35 months, median baseline eGFR 84 mL/min/1.73 m

Identifiants

DOI: 10.1016/j.kint.2019.07.025 PMID: 31679767
pubmed: 31679767
pii: S0085-2538(19)30841-5
doi: 10.1016/j.kint.2019.07.025
pii:
doi:

Substances chimiques

Biomarkers 0
HAVCR1 protein, human 0
Hepatitis A Virus Cellular Receptor 1 0
Peptide Fragments 0
pro-brain natriuretic peptide (1-76) 0
Natriuretic Peptide, Brain 114471-18-0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1381-1388

Informations de copyright

Copyright © 2019 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.

Auteurs

Michael Kammer (M)

Department of Nephrology, Medical University of Vienna, Vienna, Austria; Center for Medical Statistics, Informatics and Intelligent Systems, Section for Clinical Biometrics, Medical University of Vienna, Vienna, Austria.

Andreas Heinzel (A)

Department of Nephrology, Medical University of Vienna, Vienna, Austria.

Jill A Willency (JA)

Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana, USA.

Kevin L Duffin (KL)

Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana, USA.

Gert Mayer (G)

Department of Internal Medicine IV (Nephrology and Hypertension), Medical University of Innsbruck, Innsbruck, Austria.

Kai Simons (K)

Lipotype GmbH, Tatzberg, Dresden, Germany.

Mathias J Gerl (MJ)

Lipotype GmbH, Tatzberg, Dresden, Germany.

Christian Klose (C)

Lipotype GmbH, Tatzberg, Dresden, Germany.

Georg Heinze (G)

Center for Medical Statistics, Informatics and Intelligent Systems, Section for Clinical Biometrics, Medical University of Vienna, Vienna, Austria.

Roman Reindl-Schwaighofer (R)

Department of Nephrology, Medical University of Vienna, Vienna, Austria.

Karin Hu (K)

Department of Nephrology, Medical University of Vienna, Vienna, Austria.

Paul Perco (P)

Department of Internal Medicine IV (Nephrology and Hypertension), Medical University of Innsbruck, Innsbruck, Austria.

Susanne Eder (S)

Department of Internal Medicine IV (Nephrology and Hypertension), Medical University of Innsbruck, Innsbruck, Austria.

Laszlo Rosivall (L)

International Nephrology Research and Training Centre, Institute of Pathophysiology, Semmelweis University, Budapest, Hungary.

Patrick B Mark (PB)

Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.

Wenjun Ju (W)

Department of Internal Medicine, Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA.

Matthias Kretzler (M)

Department of Internal Medicine, Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA.

Mark I McCarthy (MI)

Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK; Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK.

Hiddo L Heerspink (HL)

Clinical Pharmacy and Pharmacology, Faculty of Medical Sciences, University Medical Center Groningen, Groningen, The Netherlands.

Andrzej Wiecek (A)

Department of Nephrology, Transplantation and Internal Medicine, Medical University of Silesia, Katowice, Poland.

Maria F Gomez (MF)

Department of Clinical Sciences in Malmö, Lund University Diabetes Centre, Lund, Sweden.

Rainer Oberbauer (R)

Department of Nephrology, Medical University of Vienna, Vienna, Austria. Electronic address: rainer.oberbauer@meduniwien.ac.at.

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Classifications MeSH

questionsmedicales.fr › Personnes › Tranches d'âge › Adulte › Sujet âgé › Integrative analysis of prognostic biomarkers...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Statistiques comme sujet › Probabilité › Théorème de Bayes › Integrative analysis of prognostic biomarkers...
questionsmedicales.fr › Facteurs biologiques › Marqueurs biologiques › Integrative analysis of prognostic biomarkers...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Caractéristiques des études épidémiologiques › Études épidémiologiques › Études cas-témoins › Integrative analysis of prognostic biomarkers...
questionsmedicales.fr › Maladies endocriniennes › Diabète › Diabète de type 2 › Integrative analysis of prognostic biomarkers...
questionsmedicales.fr › Phénomènes physiologiques des appareils urinaire et reproducteur › Phénomènes physiologiques des voies urinaires › Débit de filtration glomérulaire › Integrative analysis of prognostic biomarkers...
questionsmedicales.fr › Acides aminés, peptides et protéines › Protéines › Protéines membranaires › Récepteurs de surface cellulaire › Récepteurs viraux › Récepteur cellulaire-1 du virus de l'hépatite A › Integrative analysis of prognostic biomarkers...
questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › Integrative analysis of prognostic biomarkers...
questionsmedicales.fr › Personnes › Tranches d'âge › Adulte › Adulte d'âge moyen › Integrative analysis of prognostic biomarkers...
questionsmedicales.fr › Acides aminés, peptides et protéines › Protéines › Protéines de tissu nerveux › Peptide natriurétique cérébral › Integrative analysis of prognostic biomarkers...
questionsmedicales.fr › Acides aminés, peptides et protéines › Peptides › Fragments peptidiques › Integrative analysis of prognostic biomarkers...
questionsmedicales.fr › États, signes et symptômes pathologiques › Processus pathologiques › Caractéristiques de la maladie › Maladie chronique › Insuffisance rénale chronique › Integrative analysis of prognostic biomarkers...