Background:Dietary advice remains the cornerstone of prevention and management of type 2 diabetes (T2D). However, understanding the efficacy of dietary interventions is confounded by the challenges inherent in assessing free living diet. Here we profiled dietary metabolites to investigate glycaemic deterioration and cardiometabolic risk in people at risk of or living with T2D.Methods:We analysed data from plasma collected at baseline and 18-month follow-up in individuals from the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohort 1 n = 403 individuals with normal or impaired glucose regulation (prediabetic) and cohort 2 n = 458 individuals with new onset of T2D. A dietary metabolite profile model (Tpred) was constructed using multivariable regression of 113 plasma metabolites obtained from targeted metabolomics assays. The continuous Tpred score was used to explore the relationships between diet, glycaemic deterioration and cardio-metabolic risk via multiple linear regression models.Findings:A higher Tpred score was associated with healthier diets high in wholegrain (?=3.36 g, 95% CI 0.31, 6.40 and ?=2.82 g, 95% CI 0.06, 5.57) and lower energy intake (?=-75.53 kcal, 95% CI -144.71, -2.35 and ?=-122.51 kcal, 95% CI -186.56, -38.46), and saturated fat (?=-0.92 g, 95% CI -1.56, -0.28 and ?=-0.98 g, 95% CI -1.53, -0.42 g), respectively for cohort 1 and 2. In both cohorts a higher Tpred score was also associated with lower total body adiposity and favourable lipid profiles HDL-cholesterol (?=0.07 mmol/L, 95% CI 0.03, 0.1), (?=0.08 mmol/L, 95% CI 0.04, 0.1), and triglycerides (?=-0.1 mmol/L, 95% CI -0.2, -0.03), (?=-0.2 mmol/L, 95% CI -0.3, -0.09), respectively for cohort 1 and 2. In cohort 2, the Tpred score was negatively associated with liver fat (?=-0.74%, 95% CI -0.67, -0.81), and lower fasting concentrations of HbA1c (?=-0.9 mmol/mol, 95% CI -1.5, -0.1), glucose (?=-0.2 mmol/L, 95% CI -0.4, -0.05) and insulin (?=-11.0 pmol/mol, 95% CI -19.5, -2.6). Longitudinal analysis showed at 18-month follow up a higher Tpred score was also associated lower total body adiposity in both cohorts and lower fasting glucose (?=-0.2 mmol/L, 95% CI -0.3, -0.01) and insulin (?=-9.2 pmol/mol, 95% CI -17.9, -0.4) concentrations in cohort 2.Interpretation:Plasma dietary metabolite profiling provides objective measures of diet intake, showing a relationship to glycaemic deterioration and cardiometabolic health.

Dietary metabolite profiling brings new insight into the relationship between nutrition and metabolic risk: An IMI DIRECT study

Bizzotto R;Mari A;
2020

Abstract

Background:Dietary advice remains the cornerstone of prevention and management of type 2 diabetes (T2D). However, understanding the efficacy of dietary interventions is confounded by the challenges inherent in assessing free living diet. Here we profiled dietary metabolites to investigate glycaemic deterioration and cardiometabolic risk in people at risk of or living with T2D.Methods:We analysed data from plasma collected at baseline and 18-month follow-up in individuals from the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohort 1 n = 403 individuals with normal or impaired glucose regulation (prediabetic) and cohort 2 n = 458 individuals with new onset of T2D. A dietary metabolite profile model (Tpred) was constructed using multivariable regression of 113 plasma metabolites obtained from targeted metabolomics assays. The continuous Tpred score was used to explore the relationships between diet, glycaemic deterioration and cardio-metabolic risk via multiple linear regression models.Findings:A higher Tpred score was associated with healthier diets high in wholegrain (?=3.36 g, 95% CI 0.31, 6.40 and ?=2.82 g, 95% CI 0.06, 5.57) and lower energy intake (?=-75.53 kcal, 95% CI -144.71, -2.35 and ?=-122.51 kcal, 95% CI -186.56, -38.46), and saturated fat (?=-0.92 g, 95% CI -1.56, -0.28 and ?=-0.98 g, 95% CI -1.53, -0.42 g), respectively for cohort 1 and 2. In both cohorts a higher Tpred score was also associated with lower total body adiposity and favourable lipid profiles HDL-cholesterol (?=0.07 mmol/L, 95% CI 0.03, 0.1), (?=0.08 mmol/L, 95% CI 0.04, 0.1), and triglycerides (?=-0.1 mmol/L, 95% CI -0.2, -0.03), (?=-0.2 mmol/L, 95% CI -0.3, -0.09), respectively for cohort 1 and 2. In cohort 2, the Tpred score was negatively associated with liver fat (?=-0.74%, 95% CI -0.67, -0.81), and lower fasting concentrations of HbA1c (?=-0.9 mmol/mol, 95% CI -1.5, -0.1), glucose (?=-0.2 mmol/L, 95% CI -0.4, -0.05) and insulin (?=-11.0 pmol/mol, 95% CI -19.5, -2.6). Longitudinal analysis showed at 18-month follow up a higher Tpred score was also associated lower total body adiposity in both cohorts and lower fasting glucose (?=-0.2 mmol/L, 95% CI -0.3, -0.01) and insulin (?=-9.2 pmol/mol, 95% CI -17.9, -0.4) concentrations in cohort 2.Interpretation:Plasma dietary metabolite profiling provides objective measures of diet intake, showing a relationship to glycaemic deterioration and cardiometabolic health.
2020
Istituto di Neuroscienze - IN -
Inglese
58
http://www.scopus.com/inward/record.url?eid=2-s2.0-85088933440&partnerID=q2rCbXpz
Sì, ma tipo non specificato
Cardiometabolic health
Dietary patterns
Metabolic profiling
Type 2 diabetes
This work was supported by the Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115317 (DIRECT), resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/20072013) and EFPIA companies in kind contribution. G.F. funded by Imperial College NIHR BRC and is an NIHR senior investigator. I.G.-P. is supported by a National Institute for Health Research (NIHR) Fellowship (NIHR-CDF-201710032). J.M.P. is supported by a Rutherford Fund Fellowship at Health Data Research (HDR) UK (MR/S004033/1). MMcC was a Wellcome Investigator (090532, 098381, 106130, 203141, 2122590 and an NIHR Senior Investigator (Niddk. U01- DK105535). RWK was funded by a STAR Award Novo Nordisk cofinanced PhD fellowship. This work was supported in part by ERC2015-CoG_NASCENT_681742 and the Swedish Research Council; strategic funding for Lund University Diabetes Centre, where some of the work described herein was performed, was provided by the Swedish Research Council, Strategic Research Area Exodiab, (Dnr 20091039), the Swedish Foundation for Strategic Research (IRC150067), the Swedish Research Council, Linnaeus grant (Dnr 3492006237). EP holds a Wellcome Trust Investigator award (grant reference 102820/Z/13/Z). Contributions to this work by SBru. were co-financed by the Novo Nordisk Foundation (grants NNF17OC0027594 and NNF14CC0001)
37
info:eu-repo/semantics/article
262
Eriksen, R; Perez, Ig; Posma, Jm; Haid, M; Sharma, S; Prehn, C; Thomas, Le; Koivula, Rw; Bizzotto, R; Mari, A; Giordano, Gn; Pavo, I; Schwenk, Jm; De ...espandi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/407028
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