Manca , M L , Solini , A , Haukka , J K , Sandholm , N , Forsblom , C , Groop , P H & Ferrannini , E 2021 , ' Differential metabolomic signatures of declining renal function in Types 1 and 2 diabetes ' , Nephrology Dialysis Transplantation , vol. 36 , no. 10 , pp. 1859-1866 . https://doi.org/10.1093/ndt/gfaa175
Title: | Differential metabolomic signatures of declining renal function in Types 1 and 2 diabetes |
Author: | Manca, Maria Laura; Solini, Anna; Haukka, Jani K.; Sandholm, Niina; Forsblom, Carol; Groop, Per Henrik; Ferrannini, Ele |
Contributor organization: | HUS Abdominal Center Faculty of Medicine University of Helsinki Nefrologian yksikkö CAMM - Research Program for Clinical and Molecular Metabolism Research Programs Unit Clinicum Medicum Institute for Molecular Medicine Finland Diabetes and Obesity Research Program Department of Medicine Per Henrik Groop / Principal Investigator |
Date: | 2021-10-01 |
Language: | eng |
Number of pages: | 8 |
Belongs to series: | Nephrology Dialysis Transplantation |
ISSN: | 0931-0509 |
DOI: | https://doi.org/10.1093/ndt/gfaa175 |
URI: | http://hdl.handle.net/10138/340442 |
Abstract: | Background: Chronic kidney disease (CKD) shows different clinical features in Types1 (T1D) and 2 diabetes (T2D). Metabolomics have recently provided useful contribution to the identification of biomarkers of CKD progression in either form of the disease. However, no studies have so far compared plasma metabolomics between T1D and T2D in order to identify differential signatures of progression of estimated glomerular filtration rate (eGFR) decline. Methods: We used two large cohorts of T1D (from Finland) and T2D (from Italy) patients followed up to 7 and 3 years, respectively. In both groups, progression was defined as the top quartile of yearly decline in eGFR. Pooled data from the two groups were analysed by univariate and bivariate random forest (RF), and confirmed by bivariate partial least squares (PLS) analysis, the response variables being type of diabetes and eGFR progression. Results: In progressors, yearly eGFR loss was significantly larger in T2D [-5.3 (3.0), median (interquartile range)mL/min/1.73 m2/year] than T1D [-3.7 (3.1) mL/min/1.73 m2/year; P = 0.018]. Out of several hundreds, bivariate RF extracted 22 metabolites associated with diabetes type (all higher in T1D than T2D except for 5-methylthioadenosine, pyruvate and β-hydroxypyruvate) and 13 molecules associated with eGFR progression (all higher in progressors than non-progressors except for sphyngomyelin). Three of the selected metabolites (histidylphenylalanine, leucylphenylalanine, tryptophylasparagine) showed a significant interaction between disease type and progression. Only eight metabolites were common to both bivariate RF and PLS. Conclusions: Identification of metabolomic signatures of CKD progression is partially dependent on the statistical model. Dual analysis identified molecules specifically associated with progressive renal impairment in both T1D and T2D. |
Description: | Publisher Copyright: © 2020 The Author(s) 2020. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. |
Subject: |
3121 General medicine, internal medicine and other clinical medicine
GFR metabolomics nephropathy Type 1 diabetes Type 2 diabetes METABOLITES MAST-CELLS RISK NEPHROPATHY SERUM URIC-ACID INDIVIDUALS PLASMA DYSFUNCTION CHRONIC KIDNEY-DISEASE ASSOCIATION |
Peer reviewed: | Yes |
Rights: | unspecified |
Usage restriction: | openAccess |
Self-archived version: | acceptedVersion |
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