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Circulating metabolites improve the prediction of renal impairment in patients with type 2 diabetes.
Trischitta, Vincenzo; Mastroianno, Mario; Scarale, Maria Giovanna; Prehn, Cornelia; Salvemini, Lucia; Fontana, Andrea; Adamski, Jerzy; Schena, Francesco Paolo; Cosmo, Salvatore De; Copetti, Massimiliano; Menzaghi, Claudia.
Afiliação
  • Trischitta V; Research Unit of Diabetes and Endocrine Diseases, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy c.menzaghi@operapadrepio.it vincenzo.trischitta@uniroma1.it.
  • Mastroianno M; Experimental Medicine, University of Rome La Sapienza, Rome, Italy.
  • Scarale MG; Scientific Direction, Fondazione IRCCS "Casa Sollievo della Sofferenza", San Giovanni Rotondo, Italy.
  • Prehn C; Research Unit of Diabetes and Endocrine Diseases, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy.
  • Salvemini L; Institute of Experimental Genetics, Helmholtz Zentrum München, Neuherberg, Germany.
  • Fontana A; Research Unit of Diabetes and Endocrine Diseases, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy.
  • Adamski J; Unit of Biostatistics, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy.
  • Schena FP; Institute of Experimental Genetics, Helmholtz Zentrum München, Neuherberg, Germany.
  • Cosmo S; Department of Biochemistry, National University Singapore Yong Loo Lin School of Medicine, Singapore.
  • Copetti M; Recerch Center, Fondazione Schena, Bari, Italy.
  • Menzaghi C; Unit of Internal Medicine, IRCCS Casa Sollievo della Sofferenza San Giovanni Rotondo, Foggia, Italy.
Article em En | MEDLINE | ID: mdl-37734903
ABSTRACT

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) (ß 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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Diabetes Mellitus Tipo 2 Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Diabetes Mellitus Tipo 2 Idioma: En Ano de publicação: 2023 Tipo de documento: Article