Novel gut-based pharmacology of metformin in patients with type 2 diabetes mellitus

Abstract

Metformin, a biguanide derivate, has pleiotropic effects beyond glucose reduction, including improvement of lipid profiles and lowering microvascular and macrovascular complications associated with type 2 diabetes mellitus (T2DM). These effects have been ascribed to adenosine monophosphate-activated protein kinase (AMPK) activation in the liver and skeletal muscle. However, metformin effects are not attenuated when AMPK is knocked out and intravenous metformin is less effective than oral medication, raising the possibility of important gut pharmacology. We hypothesized that the pharmacology of metformin includes alteration of bile acid recirculation and gut microbiota resulting in enhanced enteroendocrine hormone secretion. In this study we evaluated T2DM subjects on and off metformin monotherapy to characterize the gut-based mechanisms of metformin. Subjects were studied at 4 time points: (i) at baseline on metformin, (ii) 7 days after stopping metformin, (iii) when fasting blood glucose (FBG) had risen by 25% after stopping metformin, and (iv) when FBG returned to baseline levels after restarting the metformin. At these timepoints we profiled glucose, insulin, gut hormones (glucagon-like peptide-1 (GLP-1), peptide tyrosine-tyrosine (PYY) and glucose-dependent insulinotropic peptide (GIP) and bile acids in blood, as well as duodenal and faecal bile acids and gut microbiota. We found that metformin withdrawal was associated with a reduction of active and total GLP-1 and elevation of serum bile acids, especially cholic acid and its conjugates. These effects reversed when metformin was restarted. Effects on circulating PYY were more modest, while GIP changes were negligible. Microbiota abundance of the phylum Firmicutes was positively correlated with changes in cholic acid and conjugates, while Bacteroidetes abundance was negatively correlated. Firmicutes and Bacteroidetes representation were also correlated with levels of serum PYY. Our study suggests that metformin has complex effects due to gut-based pharmacology which might provide insights into novel therapeutic approaches to treat T2DM and associated metabolic diseases.

Trial registration: www.ClinicalTrials.gov NCT01357876.

Conflict of interest statement

Competing Interests: The study was sponsored by GlaxoSmithKline R&D. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials. Employees of GlaxoSmithKline R&D were involved in the design of the study, data collection and analysis, decision to publish, and preparation of the manuscript.

Figures

Figure 1. Schematic of the study design.

Subjects were studied at 4 time points: (i) at baseline on metformin, (ii) 7 days after stopping metformin, (iii) when fasting blood glucose (FBG) had risen by 25% after stopping metformin, and (iv) when FBG returned to baseline levels after restarting the metformin.

Figure 2. Postprandial glucose profiles.

Mean plasma glucose profiles during the postprandial period of the day (left) and weighted mean AUC (± 95% confidence interval) over 0–4, 4–8 and 0–12 h (right). Data points are coded for visit number where: black circles  =  Visit 1; white circles  =  Visit 2; white triangles  =  Visit 3; black triangles  =  Visit 4.

Figure 3. Bile acids.

Bile acid concentrations (mean ± 95% confidence interval) in serum (AUC 4–8 h) (top), faeces (middle) and eluted bile from Entero-Test string (bottom). Bile acids: C  =  Cholic; CDC  =  Chenodeoxycholic; DC  =  Deoxycholic; LC  =  Lithocholic; Prim  =  Primary; Second  =  Secondary.

Figure 4. Postprandial serum bile acid profiles.

Mean serum total, primary and secondary bile acid concentration profiles over 12(left) and weighted mean AUC (± 95% confidence interval) over 0–4, 4–8 and 0–12 h (right). Data point shape and color represent different visits as described in Figure 2.

Figure 5. Circulating GLP-1 profiles.

Mean total (top) and active (bottom) plasma GLP-1 profiles over 12 h (left) and weighted mean AUC (± 95% confidence interval) over 0–4, 4–8 and 0–12 h (right). Data point shape and color represent different visits as described in Figure 2.

Figure 6. Circulating PYY profiles.

Mean plasma PYY mean profiles over 12(left) and weighted mean AUC (± 95% confidence interval) over 0–4, 4–8 and 0–12 h (right). Data point shape and color represent different visits as described in Figure 2.

Figure 7. Relative abundance of microbial species across stool samples based on 16s rRNA V1–V3 region analysis.

For each subject (S#), samples are ordered from first to last time points. Bacterial abundances determined at the phylum level are shown, although further analyses were completed at all intermediate taxonomic levels to genus.

Figure 8. Principal coordinate analysis of microbiome beta diversity.

QIIME software was used to generate PCoA plots of beta (inter-sample) diversity of samples which are colored by subject. Different PCoA axes plots shown are: (a) PCA1 vs PCA2; (b) PCA3vs PCA1, and (c) PCA3 vs PCA2.

Figure 9. Box plots of bacterial genus On-metformin versus Off-metformin.

Plots are shown for the bacterial genera (a) Adlercreutzia, (b) Firmicute (other), (c) Eubacterium and (d) SMB53. Bacterial adjusted P values used the FDR correction as described in the Methods.

Figure 10. Correlations of bacterial species abundance with bile acids and PYY.

Values are proportional changes in bacteria from baseline plotted for (a) Bacteriodetes vs cholic acid plus conjugates, (b) Firmicutes vs cholic acid plus conjugates, (c) Bacteriodetes vs PYY and (d) Firmicutes vs PYY. Adjusted P values used the FDR correction as described in the Methodology. Data point shape and color represent different visits as in Figure 2.