Validation in type 2 diabetes of a metabolomic signature of all-cause mortality

被引:2
作者
Copetti, Massimiliano [1 ,15 ]
Baroni, Marco Giorgio [2 ,3 ]
Buzzetti, Raffaella [4 ]
Cavallo, Maria Gisella [4 ]
Cossu, Efiso [5 ]
D'Angelo, Paola [6 ]
De Cosmo, Salvatore [7 ]
Leonetti, Frida [8 ]
Morano, Susanna [4 ]
Morviducci, Lelio [9 ]
Napoli, Nicola [10 ]
Prudente, Sabrina [11 ]
Pugliese, Giuseppe [12 ]
Savino, Antonio Fernando [13 ]
Trischitta, Vincenzo [4 ,14 ,16 ]
机构
[1] Fdn IRCCS Casa Sollievo Sofferenza, Unit Biostat, San Giovanni Rotondo, Italy
[2] Univ Aquila, Dept Clin Med Publ Hlth Life & Environm Sci MeSVA, Laquila, Italy
[3] IRCCS Neuromed, Neuroendocrinol & Metab Dis, Pozzilli, Italy
[4] Sapienza Univ Rome, Dept Expt Med, Rome, Italy
[5] Univ Cagliari, Dept Med Sci & Publ Hlth, Cagliari, Italy
[6] Sandro Pertini Hosp, Dept Clin Med & Hlth Serv Integrat, aslrm2, Diabetol & Nutr Unit, Rome, Italy
[7] Fdn IRCCS Casa Sollievo Sofferenza, Dept Med, San Giovanni Rotondo, Italy
[8] Sapienza Univ Rome, Dept Med Surg Sci & Biotechnol, Rome, Italy
[9] Santo Spirito Hosp, Unit Diabetol, ASL RM1, Rome, Italy
[10] Campus Biomed Univ Rome, Dept Med, Unit Endocrinol & Diabet, Rome, Italy
[11] Fdn IRCCS Casa Sollievo Sofferenza, Res Unit Metab & Cardiovasc Dis, San Giovanni Rotondo, Italy
[12] Sapienza Univ Rome, Dept Clin & Mol Med, Rome, Italy
[13] Fdn IRCCS Casa Sollievo Sofferenza, Lab Clin Chem, San Giovanni Rotondo, Italy
[14] Fdn IRCCS Casa Sollievo Sofferenza, Res Unit Diabet & Endocrine Dis, San Giovanni Rotondo, Italy
[15] IRCCS Casa Sollievo Sofferenza, Unit Biostat, Viale Padre Pio, I-71013 San Giovanni Rotondo, Italy
[16] Sapienza Univ Rome, Ist CSS Mendel, Dept Expt Med, Viale Regina Margherita 261, I-00198 Rome, Italy
关键词
metabolomics; mortality; prognostic models; risk prediction model; type; 2; diabetes; validation; MAGNETIC-RESONANCE METABOLOMICS; INDIVIDUAL PARTICIPANT DATA; RISK EQUATIONS; COMPLICATIONS; EPIDEMIOLOGY; CURVE;
D O I
10.1002/dmrr.3734
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Context:Mortality in type 2 diabetes is twice that of the normoglycemic population. Unravelling biomarkers that identify high-risk patients for referral to the most aggressive and costly prevention strategies is needed. Objective:To validate in type 2 diabetes the association with all-cause mortality of a 14-metabolite score (14-MS) previously reported in the general population and whether this score can be used to improve well-established mortality prediction models. Methods:This is a sub-study consisting of 600 patients from the "Sapienza University Mortality and Morbidity Event Rate" (SUMMER) study in diabetes, a prospective multicentre investigation on all-cause mortality in patients with type 2 diabetes. Metabolic biomarkers were quantified from serum samples using high-throughput proton nuclear magnetic resonance metabolomics. Results:In type 2 diabetes, the 14-MS showed a significant (p < 0.0001) association with mortality, which was lower (p < 0.0001) than that reported in the general population. This difference was mainly due to two metabolites (histidine and ratio of polyunsaturated fatty acids to total fatty acids) with an effect size that was significantly (p = 0.01) lower in diabetes than in the general population. A parsimonious 12-MS (i.e. lacking the 2 metabolites mentioned above) improved patient discrimination and classification of two well-established mortality prediction models (p < 0.0001 for all measures). Conclusions:The metabolomic signature of mortality in the general population is only partially effective in type 2 diabetes. Prediction markers developed and validated in the general population must be revalidated if they are to be used in patients with diabetes.
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页数:7
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