PuSH - Publication Server of Helmholtz Zentrum München: Circulating metabolites improve the prediction of renal impairment in patients with type 2 diabetes.

Information

Clues to quality of journals

Open Access Policy of Helmholtz Association 2016

CC Licencences

Publication Metrics

Navigation

Home

Deutsch

Research

Advanced Search

Browse by ...

... HMGU-Authors/Consortia

... Organizational Structure

... Journal

... Publication Type

... Research Data

... Arbeitsgruppen

... Publication Year

Publication overview

Statistics

Statistics (last 5 years)

OA Publications

Publish

Submit Publication

Import publication from...

...EVA

Report missing publication

Highlights

Support & Contact

Contact persons

Help

Data protection

Helmholtz Open Science

JANE Journal Estimator

SHERPA/RoMEO

DOAJ

Export:

Text

Endnote (RIS) BIB

BibTeX

Trischitta, V.* ; Mastroianno, M.* ; Scarale, M.G.* ; Prehn, C. ; Salvemini, L.* ; Fontana, A.* ; Adamski, J. ; Schena, F.P.* ; De Cosmo, S.* ; Copetti, M.* ; Menzaghi, C.*

Circulating metabolites improve the prediction of renal impairment in patients with type 2 diabetes.

BMJ Open Diab. Res. Care 11:e003422 (2023)

Publ. Version/Full Text

DOI

PMC

	Open Access Gold

Abstract
Metrics
Extra information

Introduction Low glomerular filtration rate (GFR) is a leading cause of reduced lifespan in type 2 diabetes. Unravelling biomarkers capable to identify high-risk patients can help tackle this burden. We investigated the association between 188 serum metabolites and kidney function in type 2 diabetes and then whether the associated metabolites improve two established clinical models for predicting GFR decline in these patients. Research design and methods Two cohorts comprising 849 individuals with type 2 diabetes (discovery and validation samples) and a follow-up study of 575 patients with estimated GFR (eGFR) decline were analyzed. Results Ten metabolites were independently associated with low eGFR in the discovery sample, with nine of them being confirmed also in the validation sample (ORs range 1.3-2.4 per 1SD, p values range 1.9×10 -2 -2.5×10 -9). Of these, five metabolites were also associated with eGFR decline (ie, tiglylcarnitine, decadienylcarnitine, total dimethylarginine, decenoylcarnitine and kynurenine) (β range -0.11 to -0.19, p values range 4.8×10 -2 to 3.0×10 -3). Indeed, tiglylcarnitine and kynurenine, which captured all the information of the other three markers, improved discrimination and reclassification (all p<0.01) of two clinical prediction models of GFR decline in people with diabetes. Conclusions Further studies are needed to validate our findings in larger cohorts of different clinical, environmental and genetic background.

Impact Factor

Scopus SNIP

Altmetric

4.100

0.000