Metabolomic biomarkers for personalised glucose lowering drugs treatment in type 2 diabetes

Abstract

We aimed to identify metabolites to predict patients' response to glucose lowering treatment during the first 5 years after detection of type 2 diabetes. Metabolites were measured by GC-MS in baseline samples from 346 screen-detected type 2 diabetes patients in the ADDITION-NL study. The response to treatment with metformin and/or sulphonylurea (SU) was analysed to identify metabolites predictive of 5 year HbA1c change by multiple regression analysis. Baseline glucose and 1,5 anhydro-glucitol were associated with HbA_1c decrease in all medication groups. In patients on SU no other metabolite was associated with HbA1c decrease. A larger set of metabolites was associated with HbA1c change in the metformin and the combination therapy (metformin + SU) groups. These metabolites included metabolites related to liver metabolism, such as 2-hydroxybutanoic acid, 3-hydroxybutanoic acid, 2-hydroxypiperidine and 4-oxoproline). Metabolites involved in oxidative stress and insulin resistance were higher when the HbA1c decrease was larger in the metformin/sulphonylurea group. The associations between baseline metabolites and responsiveness to medication are in line with its mode of action. If these results could be replicated in other populations, the most promising predictive candidates might be tested to assess whether they could enhance personalised treatment.

Keywords: Metabolomics; Metformin; Personalised medicine; Sulphonylurea.

Fig. 1

Relative HbA_1c after 5 years for each medication group (∆ %HbA_1c = ((t5-t0/t0)*100 %)) (C = no medication, M = metformin, M + S = combination metformin and sulphonylurea, S = sulphonylurea, red mean, pink 1 SD, blue 95 % confidence interval and ash individual data), n = 264 (Color figure online)