[¹¹C]-Labeled Metformin Distribution in the Liver and Small Intestine Using Dynamic Positron Emission Tomography in Mice Demonstrates Tissue-Specific Transporter Dependency

Metformin is the preferred first-line drug in the treatment of type 2 diabetes because of its beneficial effects on cardiovascular outcomes and impressive safety profile. Metformin action involves suppression of mitochondrial function through inhibition of complex 1 in the respiratory chain (1). In the liver, metformin inhibits gluconeogenesis in mice via a decrease in energy state (2). In addition, metformin action in the duodenum lowers hepatic glucose production in rats, and the intestine may be an important target tissue for metformin (3). A common denominator for these suggested mechanisms of action is intracellular uptake of the drug. Therefore, understanding the biodistribution of metformin is essential to understanding its tissue-specific effects.

Metformin is hydrophilic and cannot pass cell membranes by passive diffusion; therefore, cellular uptake depends on organic cation transporters (OCT). The primary mediators of intestinal uptake are plasma membrane monoamine transporter (4) and OCT1 (5). Hepatic uptake depends on OCT1 and possibly OCT3 (6,7). Thus, knockout of OCT1 in mice reduces hepatic uptake of metformin determined ex vivo with [¹⁴C]-labeled metformin or high-performance liquid chromatography (8,9). In humans, reduced function alleles in SLC22A1, encoding OCT1, are associated with higher plasma levels of metformin (10). However, whether this translates into changes in hepatic uptake of metformin is unknown. Multidrug and toxin extrusion proteins (MATE) 1 eliminates metformin from hepatocytes in a H⁺-coupled electroneutral manner (11), and ablation of MATE1 in mice increases hepatic metformin concentration, determined ex vivo with high-performance liquid chromatography (12). Because of negligible metabolism of metformin in vivo, systemic elimination depends on renal excretion in the proximal tubules. OCT2, and to a minor degree OCT1, is responsible for basolateral uptake, whereas MATE1 and MATE2-K contribute to luminal excretion into the urine (13).

Until today, studies of tissue-specific uptake and elimination of metformin have been limited to ex vivo methods. Successful generation of [¹¹C]-labeled metformin ([¹¹C]-metformin) was recently demonstrated to be a powerful tool to noninvasively determine distribution of metformin in specific tissues (14–16). Therefore, the primary aim of the present study was to use dynamic positron emission tomography (PET) with [¹¹C]-metformin in mice to investigate the importance of OCT and MATE in dynamic hepatic and small intestinal distribution of metformin in vivo. We hypothesized that expression and functional impairment of these transporters affects distribution of metformin in target tissues.

[¹¹C]-Metformin was synthesized as previously published (16). The [¹¹C]-metformin (0.2–1.0 GBq) contained 0.1–0.5 µg/mL metformin and was >98% pure.

Female FVB OCT1/2^−/− and corresponding wild-type mice (aged 13–15 weeks) were purchased from Taconic. Female FVB mice (aged 14–17 weeks) were used for drug-drug interactions and biodistribution studies. Animals were fed standard chow and kept in a temperature- and humidity-controlled environment with a 12-h light/dark cycle. The studies were performed in accordance with the Danish Animal Experimentation Act and approved by the Animal Experiments Inspectorate, Denmark.

Wild-type (n = 7) and OCT1/2^−/− mice (n = 4) underwent functional PET and anatomical MRI using Mediso nanoScan PET/MR (Mediso Medical Imaging Systems, Budapest, Hungary). After induction of anesthesia with 5% isoflurane, the animal was placed in an acrylic glass head-holder, and anesthesia was maintained with mask-delivered isoflurane (1.8–2.0%). A bolus of [¹¹C]-metformin (5.7 ± 2.8 MBq/animal) was injected via a tail vein catheter, followed by 60-min dynamic PET and 30-min MRI. Body temperature and respiration frequency were monitored.

To pharmacologically inhibit OCT, mice were intravenously pretreated 5 min before the [¹¹C]-metformin injection with saline containing cimetidine (150 mg/kg) (n = 5) dissolved in 20% DMSO or pyrimethamine (5 mg/kg) (n = 4) in 40% DMSO. Control mice (n = 8) were intravenously pretreated with corresponding vehicle in equal volume. Chemicals were from Sigma-Aldrich and used as received.

Dynamic PET data were reconstructed with a three-dimensional ordered subset expectation maximization algorithm (Tera-Tomo 3D; Mediso Medical Imaging Systems) with four iterations and six subsets and voxel size of 0.4 × 0.4 × 0.4 mm³. Data were corrected for dead-time, decay, and randoms using delayed coincidence window without corrections for attenuation and scatter. The 60-min dynamic PET scans were reconstructed as 30 frames increasing in duration from 5 s to 10 min. Multiple regions of interest were placed on coronal slices in the organ of interest using PMOD 3.5 software (PMOD Technologies Ltd., Zurich, Switzerland) creating a volume of interest (VOI). Image-derived arterial input function was generated by averaging images from the first 20 s and placing a circle with a diameter of 15 pixels on the six most intensive slices over the heart (68 µL), representing primarily the blood pool in the left ventricle. Hepatic VOIs were drawn in the anterior part of the liver on PET images averaged from 0 to 15 min in which the liver easily is identified (Fig. 1). Small intestinal VOIs were localized on MRIs and drawn on PET images identical to VOIs for the liver (Fig. 1). Half moon–shaped VOIs were placed in the kidney cortex on all PET images averaged. Positioning of all VOIs was controlled in each time frame. Time-activity curves were generated from the individual VOIs.

Data are expressed as the tissue-to-blood ratio at each time point. The area under the curve (AUC) of the tissue-to-blood ratio reflects the tissue extraction ratio (17) and represents the relationship between uptake and elimination from the tissue of interest.

During the first minutes after PET tracer injection, the efflux in the liver can be assumed to be much smaller than the influx (17). Tracer supply through the portal vein within this time is negligible. Consequently, we used an irreversible single-compartment model to calculate the initial rate of hepatic [¹¹C]-metformin uptake, influx rate constant (mL blood/mL tissue/min) (18), from 0 to 60 s using the image-derived arterial input function.

Anesthetized mice were administered [¹¹C]-metformin (6.7 ± 2.6 MBq/body weight) through the tail vein. At 15 and 60 min after injection, the gallbladder, small intestinal wall, gastric wall, liver, and blood were harvested from five mice per time point. Tissue radioactivity was determined using a well-crystal scintillation detector (Packard BioScience) and expressed relative to blood radioactivity. All measurements were corrected for decay.

Data are expressed as mean ± SE. Distribution was tested using the Shapiro-Wilk normality test. Normally distributed data were compared using the Student t test or one-way ANOVA. The Mann-Whitney rank sum test was used for data with unequal variance. Significance was assumed at P < 0.05. SigmaPlot 11.0 software (Systat Software) was used for all analyses.

During scannings, most of the metformin was detected in the urinary bladder, kidneys, and small intestine. When coregistering PET with anatomical MRIs, hepatic and small intestinal distributions were well visualized from 0 to 15 min and primarily the small intestine from 15 to 60 min (Fig. 1A and B). We did not observe spillover from the kidneys to the intestine and liver. Time-activity curves from blood, liver, small intestine, and kidney during the 60 min are shown in Supplementary Figs. 1–4.

Pretreatment with cimetidine, a nonspecific OCT inhibitor (19), lowered the initial uptake of metformin in the liver, reflected as a significant reduction in influx rate constant (Fig. 2B). This was associated with an increased hepatic AUC for metformin from 2 to 60 min, reflecting pronounced inhibition of hepatic elimination.

Dynamic distribution of metformin in the liver of OCT1/2^−/− mice revealed stable influx rates during the first minute after tracer injection, with no significant differences between groups (Fig. 2C and D). From 2 to 60 min, hepatic distribution was severely lowered in OCT1/2^−/− mice (Fig. 2D).

Pretreatment with pyrimethamine, in doses that specifically inhibit MATE1 (14), caused hepatic accumulation of metformin (Fig. 2E). The influx rate constant did not vary significantly between groups, whereas hepatic distribution from 2 to 60 min was significantly increased by pyrimethamine pretreatment (Fig. 2F).

Distribution of metformin in the small intestine was calculated as AUC of the small intestine–to–blood ratio from 0 to 60 min. Pretreatment with cimetidine significantly reduced uptake of metformin (Fig. 3A) and the AUC for metformin (Fig. 3B).

As shown in Fig. 3C and D, uptake of metformin in the small intestine was severely reduced in OCT1/2^−/− mice, resulting in significant reduction in AUC. Pretreatment with pyrimethamine was not associated with statistically significant effects (Fig. 3F).

[¹¹C]-Metformin activity in the small intestinal wall was significantly higher than in the gallbladder at 15 and 60 min after tracer administration (Fig. 4). Hepatic [¹¹C]-metformin activity was significantly higher than gallbladder activity 15 min after injection. In fact, [¹¹C]-metformin activity of the gallbladder resembled the gastric wall, where only minor [¹¹C]-metformin activity was observed on PET images.

The current study demonstrates the importance of OCT and MATE in the dynamic distribution of metformin in the liver and small intestine using PET imaging with [¹¹C]-metformin in vivo. Absence or inhibition of OCT1 and -2 reduce distribution of metformin to the liver and small intestine, whereas MATE1 inhibition impairs elimination of metformin from the liver.

Our data support an emerging role of the intestines as a target for metformin action. In rodents, the glucose-lowering effect of metformin, when administrated orally, is superior to that in intravenous and portal administration (20), and metformin action in the duodenum lowers hepatic glucose production in rats (3). We observed a rapid and significant uptake of metformin in the small intestine after intravenous administration that was dependent on expression of OCT1 and -2. In contrast, MATE1 inhibition did not cause major differences in metformin uptake in the small intestines after intravenous administration, but whether MATE1 is involved in metformin uptake after oral administration remains to be determined. Biliary secretion of metformin has been suggested as a major route of elimination (17,21). This could form the basis for enterohepatic cycling and thereby explain metformin in the small intestines after intravenous administration. However, we observed only negligible [¹¹C]-metformin content in the gallbladder 15 min after tracer administration, but a significant uptake in the small intestine was detected at the same time. Biliary elimination is therefore unlikely to be a major contributor for intestinal uptake after intravenous administration. Instead, the metformin uptake in the small intestine under these conditions may reflect basolateral transport capacity.

Hepatic distribution of metformin was severely lowered in OCT1/2^−/− mice, and this is in accordance with previous findings (22). Interestingly, the initial influx rate was normal in OCT1/2^−/− mice but was significantly lower after pretreatment with cimetidine. This could indicate additional transporter capacity in OCT1/2^−/− mice. Recent data show decreased antiglycemic effects of metformin in OCT3^−/− mice (23), and our data could indicate a minor hepatic OCT3-mediated uptake of metformin. Inhibition of MATE1 with pyrimethamine did not affect hepatic uptake of metformin, consistent with a recent study by Shingaki et al. (15). To further test the role of MATE1, we pretreated two OCT1/2^−/− mice with pyrimethamine and determined metformin distribution. Although the number of animals was insufficient to draw firm conclusions, we did not observe further reduction in hepatic uptake under these conditions, indicating an insignificant role of MATE1 in hepatic uptake of metformin. Instead, inhibition of MATE1 profoundly affected hepatic elimination of metformin, which supports previous reports from pyrimethamine-treated mice (24). These prominent effects open the possibility to potentiate metformin action by cotreatment with MATE1 inhibitors.

The tracer doses of metformin used in these experiments are far below therapeutic metformin concentrations. Thus, high-affinity, low-capacity transporter proteins could theoretically affect distribution of [¹¹C]-metformin without affecting metformin at therapeutic levels. However, concomitant treatment with metformin in therapeutic doses does not affect [¹¹C]-metformin distribution in pigs (16). Consequently, no data suggest that distribution of [¹¹C]-metformin disassociates from therapeutic use of metformin.

In conclusion, dynamic tissue-specific distribution of metformin can be determined in vivo by [¹¹C]-metformin functional PET imaging. The present data demonstrate that OCT1/2 are important for normal distribution of metformin in the liver and small intestine, whereas MATE1 is necessary for hepatic elimination. Furthermore, MATE1 eliminates hepatic metformin primarily to the systemic circulation. [¹¹C]-Metformin holds great potential to determine unsolved pharmacokinetics properties of metformin in clinical PET studies.

Funding. This work was supported by Danish Council for Independent Research (Det Frie Forskningsråd) (grant DFF–4183-00384) and a Novo Nordisk Foundation Excellence Project grant to N.J.

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

Author Contributions. J.B.J., E.I.S., S.J., and N.J. participated in designing the study. J.B.J., E.I.S., S.J., and O.L.M. conducted experiments and analyzed the data. J.B.J., E.I.S., S.J., L.C.G., O.L.M., J.F., and N.J. contributed to writing the manuscript. N.J. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.