Imperial College London
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Dr Joram M. Posma PhD MSc B AS MRSC

Faculty of Medicine, Department of Metabolism, Digestion and Reproduction

Senior Lecturer in Biomedical Informatics
 
 
 
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Contact

 

j.posma11 Website

 
 
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Location

 

E305Burlington DanesHammersmith Campus

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Summary

 

Publications

Citation

BibTex format

@article{Eriksen:2020:10.1016/j.ebiom.2020.102932,
author = {Eriksen, R and Garcia, Perez I and Posma, JM and Haid, M and Sharma, S and Prehn, C and Thomas, LE and Koivula, RW and Bizzotto, R and Prehn, C and Mari, A and Giordano, GN and Pavo, I and Schwenk, JM and De, Masi F and Tsirigos, KD and Brunak, S and Viñuela, A and Mahajan, A and McDonald, TJ and Kokkola, T and Rutter, F and Teare, H and Hansen, TH and Fernandez, J and Jones, A and Jennison, C and Walker, M and McCarthy, MI and Pedersen, O and Ruetten, H and Forgie, I and Bell, JD and Pearson, ER and Franks, PW and Adamski, J and Holmes, E and Frost, G},
doi = {10.1016/j.ebiom.2020.102932},
journal = {EBioMedicine},
pages = {1--9},
title = {Dietary metabolite profiling brings new insight into the relationship between nutrition and metabolic risk: An IMI DIRECT study},
url = {http://dx.doi.org/10.1016/j.ebiom.2020.102932},
volume = {58},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - BackgroundDietary 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.MethodsWe 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.FindingsA higher Tpred score was associated with healthier diets high in wholegrain (β=3.36g, 95% CI 0.31, 6.40 and β=2.82g, 95% CI 0.06, 5.57) and lower energy intake (β=-75.53kcal, 95% CI -144.71, -2.35 and β=-122.51kcal, 95% CI -186.56, -38.46), and saturated fat (β=-0.92g, 95% CI -1.56, -0.28 and β=–0.98g, 95% CI -1.53, -0.42g), 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=0.07mmol/L, 95% CI 0.03, 0.1), (β=0.08mmol/L, 95% CI 0.04, 0.1), and triglycerides (β=-0.1mmol/L, 95% CI -0.2, -0.03), (β=-0.2mmol/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=-0.9mmol/mol, 95% CI -1.5, -0.1), glu
AU  - Eriksen,R
AU  - Garcia,Perez I
AU  - Posma,JM
AU  - Haid,M
AU  - Sharma,S
AU  - Prehn,C
AU  - Thomas,LE
AU  - Koivula,RW
AU  - Bizzotto,R
AU  - Prehn,C
AU  - Mari,A
AU  - Giordano,GN
AU  - Pavo,I
AU  - Schwenk,JM
AU  - De,Masi F
AU  - Tsirigos,KD
AU  - Brunak,S
AU  - Viñuela,A
AU  - Mahajan,A
AU  - McDonald,TJ
AU  - Kokkola,T
AU  - Rutter,F
AU  - Teare,H
AU  - Hansen,TH
AU  - Fernandez,J
AU  - Jones,A
AU  - Jennison,C
AU  - Walker,M
AU  - McCarthy,MI
AU  - Pedersen,O
AU  - Ruetten,H
AU  - Forgie,I
AU  - Bell,JD
AU  - Pearson,ER
AU  - Franks,PW
AU  - Adamski,J
AU  - Holmes,E
AU  - Frost,G
DO  - 10.1016/j.ebiom.2020.102932
EP  - 9
PY  - 2020///
SN  - 2352-3964
SP  - 1
TI  - Dietary metabolite profiling brings new insight into the relationship between nutrition and metabolic risk: An IMI DIRECT study
T2  - EBioMedicine
UR  - http://dx.doi.org/10.1016/j.ebiom.2020.102932
UR  - https://www.sciencedirect.com/science/article/pii/S235239642030308X?via%3Dihub
UR  - http://hdl.handle.net/10044/1/81638
VL  - 58
ER  -
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