Plasma Metabolomics Identifies Markers of Impaired Renal Function: A Meta-analysis of 3089 Persons with Type 2 Diabetes.


Journal

The Journal of clinical endocrinology and metabolism
ISSN: 1945-7197
Titre abrégé: J Clin Endocrinol Metab
Pays: United States
ID NLM: 0375362

Informations de publication

Date de publication:
01 07 2020
Historique:
received: 27 11 2019
accepted: 08 04 2020
pubmed: 10 4 2020
medline: 3 2 2021
entrez: 10 4 2020
Statut: ppublish

Résumé

There is a need for novel biomarkers and better understanding of the pathophysiology of diabetic kidney disease. To investigate associations between plasma metabolites and kidney function in people with type 2 diabetes (T2D). 3089 samples from individuals with T2D, collected between 1999 and 2015, from 5 independent Dutch cohort studies were included. Up to 7 years follow-up was available in 1100 individuals from 2 of the cohorts. Plasma metabolites (n = 149) were measured by nuclear magnetic resonance spectroscopy. Associations between metabolites and estimated glomerular filtration rate (eGFR), urinary albumin-to-creatinine ratio (UACR), and eGFR slopes were investigated in each study followed by random effect meta-analysis. Adjustments included traditional cardiovascular risk factors and correction for multiple testing. In total, 125 metabolites were significantly associated (PFDR = 1.5×10-32 - 0.046; β = -11.98-2.17) with eGFR. Inverse associations with eGFR were demonstrated for branched-chain and aromatic amino acids (AAAs), glycoprotein acetyls, triglycerides (TGs), lipids in very low-density lipoproteins (VLDL) subclasses, and fatty acids (PFDR < 0.03). We observed positive associations with cholesterol and phospholipids in high-density lipoproteins (HDL) and apolipoprotein A1 (PFDR < 0.05). Albeit some metabolites were associated with UACR levels (P < 0.05), significance was lost after correction for multiple testing. Tyrosine and HDL-related metabolites were positively associated with eGFR slopes before adjustment for multiple testing (PTyr = 0.003; PHDLrelated < 0.05), but not after. This study identified metabolites associated with impaired kidney function in T2D, implying involvement of lipid and amino acid metabolism in the pathogenesis. Whether these processes precede or are consequences of renal impairment needs further investigation.

Identifiants

pubmed: 32271379
pii: 5818360
doi: 10.1210/clinem/dgaa173
pii:
doi:

Substances chimiques

Biomarkers 0

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© Endocrine Society 2020. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Auteurs

Nete Tofte (N)

Steno Diabetes Center, Copenhagen, Denmark.

Nicole Vogelzangs (N)

Department of Epidemiology & Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, the Netherlands.
Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands.

Dennis Mook-Kanamori (D)

Departments of Clinical Epidemiology and Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands.

Adela Brahimaj (A)

Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands.
Department of General Practice, Erasmus Medical Center, Rotterdam, the Netherlands.

Jana Nano (J)

Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands.
Institute of Epidemiology, Helmholtz Zentrum, Munich, Germany.
German Center for Diabetes Research, Munich, Germany.

Fariba Ahmadizar (F)

Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands.

Ko Willems van Dijk (KW)

Departments of Human Genetics and Internal Medicine/Endocrinology, Leiden University Medical Center, Leiden, the Netherlands.

Marie Frimodt-Møller (M)

Steno Diabetes Center, Copenhagen, Denmark.

Ilja Arts (I)

Department of Epidemiology & Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, the Netherlands.
Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands.

Joline W J Beulens (JWJ)

Department of Epidemiology and Biostatistics, Amsterdam University Medical Center, Amsterdam, the Netherlands.

Femke Rutters (F)

Department of Epidemiology and Biostatistics, Amsterdam University Medical Center, Amsterdam, the Netherlands.

Amber A van der Heijden (AA)

Department of General Practice and Elderly Care Medicine, Amsterdam University Medical Center, Amsterdam, the Netherlands.

Maryam Kavousi (M)

Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands.

Coen D A Stehouwer (CDA)

Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands.
Department of Internal Medicine, Maastricht University Medical Center, Maastricht, the Netherlands.

Giel Nijpels (G)

Department of General Practice and Elderly Care Medicine, Amsterdam University Medical Center, Amsterdam, the Netherlands.

Marleen M J van Greevenbroek (MMJ)

Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands.
Department of Internal Medicine, Maastricht University Medical Center, Maastricht, the Netherlands.

Carla J H van der Kallen (CJH)

Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands.
Department of Internal Medicine, Maastricht University Medical Center, Maastricht, the Netherlands.

Peter Rossing (P)

Steno Diabetes Center, Copenhagen, Denmark.
University of Copenhagen, Copenhagen, Denmark.

Tarunveer S Ahluwalia (TS)

Steno Diabetes Center, Copenhagen, Denmark.

Leen M 't Hart (LM)

Department of Epidemiology and Biostatistics, Amsterdam University Medical Center, Amsterdam, the Netherlands.
Department of Cell and Chemical Biology & Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.

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