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

Rebeca Eriksen (Lead / Corresponding author), Isabel Garcia Perez, Joram M. Posma, Mark Haid, Sapna Sharma, Cornelia Prehn, Louise E. Thomas, Robert W. Koivula, Roberto Bizzotto, Cornelia Prehn, Andrea Mari, Giuseppe N. Giordano, Imre Pavo, Jochen M. Schwenk, Federico De Masi, Konstantinos D. Tsirigos, Søren Brunak, Ana Viñuela, Anubha Mahajan, Timothy J. McDonaldTarja Kokkola, Femke Rutter, Harriet Teare, Tue H. Hansen, Juan Fernandez, Angus Jones, Chris Jennison, Mark Walker, Mark I. McCarthy, Oluf Pedersen, Hartmut Ruetten, Ian Forgie, Jimmy D. Bell, Ewan R. Pearson, Paul W. Franks, Jerzy Adamski, Elaine Holmes, Gary Frost

Research output: Contribution to journalArticle

13 Downloads (Pure)

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 (β=3.36 g, 95% CI 0.31, 6.40 and β=2.82 g, 95% CI 0.06, 5.57) and lower energy intake (β=-75.53 kcal, 95% CI -144.71, -2.35 and β=-122.51 kcal, 95% CI -186.56, -38.46), and saturated fat (β=-0.92 g, 95% CI -1.56, -0.28 and β=-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 (β=0.07 mmol/L, 95% CI 0.03, 0.1), (β=0.08 mmol/L, 95% CI 0.04, 0.1), and triglycerides (β=-0.1 mmol/L, 95% CI -0.2, -0.03), (β=-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 (β=-0.74%, 95% CI -0.67, -0.81), and lower fasting concentrations of HbA1c (β=-0.9 mmol/mol, 95% CI -1.5, -0.1), glucose (β=-0.2 mmol/L, 95% CI -0.4, -0.05) and insulin (β=-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 (β=-0.2 mmol/L, 95% CI -0.3, -0.01) and insulin (β=-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.

Original languageEnglish
Article number102932
Number of pages9
JournalEBioMedicine
Volume58
Early online date4 Aug 2020
DOIs
Publication statusPublished - Aug 2020

Keywords

  • Metabolic profiling
  • Dietary patterns
  • Type 2 diabetes
  • Cardiometabolic health

Fingerprint Dive into the research topics of 'Dietary metabolite profiling brings new insight into the relationship between nutrition and metabolic risk: An IMI DIRECT study'. Together they form a unique fingerprint.

  • Cite this

    Eriksen, R., Perez, I. G., Posma, J. M., Haid, M., Sharma, S., Prehn, C., Thomas, L. E., Koivula, R. W., Bizzotto, R., Prehn, C., Mari, A., Giordano, G. N., Pavo, I., Schwenk, J. M., De Masi, F., Tsirigos, K. D., Brunak, S., Viñuela, A., Mahajan, A., ... Frost, G. (2020). Dietary metabolite profiling brings new insight into the relationship between nutrition and metabolic risk: An IMI DIRECT study. EBioMedicine, 58, [102932]. https://doi.org/10.1016/j.ebiom.2020.102932