1. Academic Validation
  2. Circulating Metabolites Associate With and Improve the Prediction of All-Cause Mortality in Type 2 Diabetes

Circulating Metabolites Associate With and Improve the Prediction of All-Cause Mortality in Type 2 Diabetes

  • Diabetes. 2022 Jun 1;71(6):1363-1370. doi: 10.2337/db22-0095.
Maria Giovanna Scarale 1 Mario Mastroianno 2 Cornelia Prehn 3 Massimiliano Copetti 4 Lucia Salvemini 1 Jerzy Adamski 5 6 7 Salvatore De Cosmo 8 Vincenzo Trischitta 1 9 Claudia Menzaghi 1
Affiliations

Affiliations

  • 1 Research Unit of Diabetes and Endocrine Diseases, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico "Casa Sollievo della Sofferenza," San Giovanni Rotondo, Italy.
  • 2 Scientific Direction, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico "Casa Sollievo della Sofferenza," San Giovanni Rotondo, Italy.
  • 3 Metabolomics and Proteomics Core (MPC), Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
  • 4 Biostatistics Unit, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico "Casa Sollievo della Sofferenza," San Giovanni Rotondo, Italy.
  • 5 Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
  • 6 Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
  • 7 Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
  • 8 Department of Clinical Sciences, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico "Casa Sollievo Della Sofferenza," San Giovanni Rotondo, Italy.
  • 9 Department of Experimental Medicine, "Sapienza" University, Rome, Italy.
Abstract

Death rate is increased in type 2 diabetes. Unraveling biomarkers of novel pathogenic pathways capable to identify high-risk patients is instrumental to tackle this burden. We investigated the association between serum metabolites and all-cause mortality in type 2 diabetes and then whether the associated metabolites mediate the effect of inflammation on mortality risk and improve ENFORCE (EstimatioN oF mORtality risk in type2 diabetic patiEnts) and RECODe (Risk Equation for Complications Of type 2 Diabetes), two well-established all-cause mortality prediction models in diabetes. Two cohorts comprising 856 individuals (279 all-cause deaths) were analyzed. Serum metabolites (n = 188) and pro- and anti-inflammatory cytokines (n = 7) were measured. In the pooled analysis, hexanoylcarnitine, kynurenine, and tryptophan were significantly and independently associated with mortality (hazard ratio [HR] 1.60 [95% CI 1.43-1.80]; 1.53 [1.37-1.71]; and 0.71 [0.62-0.80] per 1 SD). The kynurenine-to-tryptophan ratio (KTR), a proxy of indoleamine-2,3-dioxygenase, which degrades tryptophan to kynurenine and contributes to a proinflammatory status, mediated 42% of the significant association between the antiatherogenic interleukin (IL) 13 and mortality. Adding the three metabolites improved discrimination and reclassification (all P < 0.01) of both mortality prediction models. In type 2 diabetes, hexanoylcarnitine, tryptophan, and kynurenine are associated to and improve the prediction of all-cause mortality. Further studies are needed to investigate whether interventions aimed at reducing KTR also reduce the risk of death, especially in patients with low IL-13.

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