OBJECTIVE

Gastrointestinal adverse effects occur in 20–30% of patients with metformin-treated type 2 diabetes, leading to premature discontinuation in 5–10% of the cases. Gastrointestinal intolerance may reflect localized high concentrations of metformin in the gut. We hypothesized that reduced transport of metformin via the plasma membrane monoamine transporter (PMAT) and organic cation transporter 1 (OCT1) could increase the risk of severe gastrointestinal adverse effects.

RESEARCH DESIGN AND METHODS

The study included 286 severe metformin-intolerant and 1,128 metformin-tolerant individuals from the IMI DIRECT (Innovative Medicines Initiative: DIabetes REsearCh on patient straTification) consortium. We assessed the association of patient characteristics, concomitant medication, and the burden of mutations in the SLC29A4 and SLC22A1 genes on odds of intolerance.

RESULTS

Women (P < 0.001) and older people (P < 0.001) were more likely to develop metformin intolerance. Concomitant use of transporter-inhibiting drugs increased the odds of intolerance (odds ratio [OR] 1.72, P < 0.001). In an adjusted logistic regression model, the G allele at rs3889348 (SLC29A4) was associated with gastrointestinal intolerance (OR 1.34, P = 0.005). rs3889348 is the top cis-expression quantitative trait locus for SLC29A4 in gut tissue where carriers of the G allele had reduced expression. Homozygous carriers of the G allele treated with transporter-inhibiting drugs had more than three times higher odds of intolerance compared with carriers of no G allele and not treated with inhibiting drugs (OR 3.23, P < 0.001). Use of a genetic risk score derived from rs3889348 and SLC22A1 variants found that the odds of intolerance were more than twice as high in individuals who carry three or more risk alleles compared with those carrying none (OR 2.15, P = 0.01).

CONCLUSIONS

These results suggest that intestinal metformin transporters and concomitant medications play an important role in the gastrointestinal adverse effects of metformin.

Metformin therapy can cause gastrointestinal (GI) discomfort that negatively affects quality of life and adherence to prescribed medications. GI adverse effects usually manifest as nausea, vomiting, diarrhea, flatulence, indigestion, bloating, abdominal discomfort, and stomach ache and occur in 20–30% of metformin-treated subjects with type 2 diabetes, leading to premature discontinuation in 5–10% of the cases (1,2). This inhibits adherence to therapy and may lead to a change of treatment, depriving intolerant patients of effective diabetes therapy. Despite its clinical importance, the underlying pathophysiology of metformin intolerance is not yet clear. However, multiple possible hypotheses have been proposed, including high intestinal metformin concentration (3,4), its effect on the gut microbiota (5), altered transportation of serotonin or direct serotonergic effects (6), and reduced ileal absorption of bile acid salts (7).

Metformin is not metabolized and is excreted unchanged in the urine. At physiologic pH, it is hydrophilic due to the presence of a quaternary ammonium group that results in a net positive charge. Therefore, metformin does not efficiently diffuse across the biological membranes and requires carrier-mediated transport. Multiple solute carrier transporters expressed in membranes of the enterocytes, hepatocytes, and the kidney are reported to be involved in the absorption, distribution, and elimination of metformin. Metformin requires the entire length of the small intestine to be absorbed (8): ∼20% of the administered dose is absorbed in the duodenum and 60% in the jejunum and ileum. The remainder reaches the colon and remains unabsorbed. Plasma membrane monoamine transporter (PMAT) and organic cation transporter 1 (OCT1) are reported to play the major role in the intestinal absorption of metformin (9). PMAT is expressed in the apical (luminal) membrane of the enterocytes, but intestinal localization of OCT1 is ambiguous (911). An association between reduced-function alleles in SLC22A1 and concomitant use of OCT1-inhibiting drugs with metformin intolerance has been reported (12,13). An interaction between OCT1 and serotonin transporter (SERT) also plays an important role in the pathophysiology of metformin intolerance (13).

Although PMAT shares extensive substrate and inhibitor overlap with OCTs (14), no studies have investigated its role in metformin intolerance. We therefore hypothesized that reduced transport of metformin by major transporters of metformin, PMAT and/or OCT1, could increase intestinal metformin concentration and subsequently increase the risk of GI adverse effects. To address this, we used prescribing, biochemistry, and clinical data from 286 metformin-intolerant and 1,128 metformin-tolerant individuals from the IMI DIRECT (Innovative Medicines Initiative: DIabetes REsearCh on patient straTification) consortium (15). Although OCT3 is expressed in the intestine, no common functional variants are described, and we therefore did not include OCT3 in this analysis.

Study Population

We identified 286 metformin-intolerant (case) and 1,128 metformin-tolerant (control) subjects from prescribing data in the IMI DIRECT consortium from participating centers across northern Europe (15). Each participant consented to participate in the study, and ethical approval was obtained from the medical ethics committees of the respective centers.

All metformin-intolerant (case) and metformin-tolerant (control) subjects had a clinical diagnosis of type 2 diabetes, a creatinine clearance ≥60 mL/min at metformin exposure, and were white Europeans aged between 18 and 90 years at recruitment.

Definition of Metformin Intolerance

The metformin intolerance phenotype was defined in two ways: firstly, individuals who switched to an alternative agent within 6 months of stopping metformin (including modified-release metformin) after having had up to 1,000 mg daily metformin for up to 6 weeks, who also reported GI adverse effects on the metformin treatment as the reason for switching or where GI adverse effects were clearly documented in the clinical record as a reason for transfer. In an alternative definition, intolerant individuals were defined as those who could not increase their metformin immediate-release dose >500 mg daily despite an HbA1c >7% (53 mmol/mol) and who reported GI adverse effects on >500 mg or where GI adverse effects were clearly documented in the clinical record as a reason for transfer.

Where the patient was asked to recall adverse effects, the intolerance event was limited to be within the last 5 years; if adverse effects were documented from clinical records, then there was no time limit. Participants who did not recall being on metformin or having adverse effects were excluded (unless clearly documented in clinical records).

Definition of Metformin Tolerance

Metformin-tolerant individuals were defined as those treated with ≥2,000 mg of metformin daily for more than a year (excluding modified-release formulations of metformin) and reported no adverse effects.

Clinical Covariates

Weight, height, and creatinine were defined as the closest measured values within 180 days before the index intolerance event (ITE), and BMI was calculated as weight in kg/height in m2. The ITE was defined as the date when patients reported GI symptoms of metformin intolerance for case subjects, and for control subjects it was the date when patients started 2,000 mg of metformin. Daily dose was the last dose during ITE for case subjects and was determined as the mean dose of prescriptions encashed during the first 6 months of metformin therapy for control subjects.

Concomitant Medications

Gut metformin transporters have strong substrate and inhibitor overlap (16). We therefore identified medications prescribed together with metformin previously reported to inhibit the PMAT and/or OCTs, proteins that mediate transmembrane trafficking of their target molecules and are required for metformin absorption in the gut. These drugs are selected based on their reported IC50 values. Accordingly, the use of any of the following medications with metformin was investigated: tricyclic antidepressants (TCAs) (17,18), proton pump inhibitors (PPIs) (19), citalopram (18), verapamil (17,18), diltiazem (18), doxazosin (17,18), spironolactone (17,18), clopidogrel (20), rosiglitazone (21), quinine (18), tramadol (18,22), codeine (23), disopyramide (24), quinidine (21), repaglinide (21), propafenone (17), ketoconazole (17), morphine (22,23), tropisetron (25), ondasetrone (25), antipsychotic agents (17), and tyrosine kinase inhibitors (26).

Genotyping

DNA samples from participants were genotyped at the University of Oxford using the Illumina HumanCoreExome-24 v1.0 BeadChip. Genotype calling was performed using the GenCall algorithm in the GenomeStudio software supplied by Illumina. Data were subjected to a series of standard quality control analyses to highlight poorly performing genetic markers and samples before imputation.

Samples were excluded for any of the following reasons: call rate <95%, heterozygosity >4 SD from the mean, high correlation to another sample (pi-hat ≥0.2), or identification as an ethnic outlier from constructed axes of genetic variation from principal components analysis implemented in Genome-wide Complex Trait Analysis (GCTA) software (v1.24.7) (27) using the 1000 Genomes as a reference. Further filtration was performed to remove nonautosomal markers, duplicate markers (sharing the same positions), markers with minor allele frequency (MAF) <1%, Hardy-Weinberg equilibrium P value <0.0001, and call rate <98%. Imputation to the 1000 Genomes Phase 3 CEU (Northern Europeans from Utah) reference panel was performed with ShapeIt (v2.r790) (28) and Impute2 (v2.3.2) (29).

Single Nucleotide Polymorphism Selection

As there are no functionally characterized common nonsynonymous single nucleotide polymorphisms (SNPs) in the SLC29A4 gene, the tagging intronic SNPs, rs3889348 and rs2685753 (r2 = 0.57, D’ = 1), had been previously shown to be associated with trough steady-state metformin concentration (30). Therefore, the rs3889348 G>A genotype was extracted from existing genome-wide data. The frequency of the minor allele (A) of rs3889348 was 38%. Data for previously reported missense SLC22A1 variants M420del (18.6%), R61C (7.1%), and G401S (3.1%) were also extracted from the genome-wide data. There was no deviation from Hardy-Weinberg equilibrium for any polymorphism (P > 0.05).

Statistical Methods

Categorical data are presented as frequency (percentage) and continuous variables as mean ± SD if normally distributed or as median and interquartile range (IQR) otherwise. The Student t test and the Mann-Whitney U test were used to compare differences in quantitative variables distributed normally or not, respectively. Comparison of categorical variables between case subjects and control subjects was done using χ2 test. Logistic regression was used to estimate the association of independent variables with metformin intolerance. Multivariate logistic regression analyses of metformin intolerance were performed with all of the covariates included using SNPTEST (v2.5.2) (31). Association of the intronic rs3889348 G>A in SLC29A4 was explored assuming an additive genetic model. SLC22A1 variants M420del, R61C, and G401S were grouped together by summing the number of risk alleles. A combined unweighted genetic risk score (GRS) was generated as 0, 1, or 2 according to the number of reduced-function alleles in each individual. The combined genotype was then added to the multivariate analyses assuming an additive model. A two-tailed P value of <0.025 was considered statistically significant.

Expression Quantitative Trait Locus Analyses

We investigated whether rs3889348 is a cis-quantitative trait locus (QTL) in the gut using expression QTL (eQTL) data sets comprising 246 colon transverse and 122 terminal ilium samples from the Genotype-Tissue Expression (GTEx) data release v6 (32). Tissue procurement, gene expression analysis, genotyping, and eQTL analysis have been previously described (3234).

Phenotypic Differences Between Tolerant and Intolerant Subjects

The characteristics of tolerant and intolerant subjects are presented in Table 1. Women (P < 0.001) and older people at diagnosis or at ITE (P < 0.001) were more likely to be metformin intolerant. Compared with tolerant subjects, metformin-intolerant individuals had lower weight (P < 0.001), lower creatinine clearance (P = 0.036), and were treated with a lower metformin dose (P < 0.001).

Table 1

Baseline characteristics of metformin-tolerant and metformin-intolerant subjects

VariableMetformin tolerant(n = 1,128)Metformin intolerant(n = 286)P
Age at diabetes diagnosis (years) 55.88 ± 9.44 58.62 ± 10.65 <0.0001 
Age at ITE (years) 60.73 ± 9.84 64.63 ± 9.91 <0.0001 
Sex   <0.0001 
 Males 696 (61.7) 117 (40.9)  
 Females 432 (38.3) 169 (59.1)  
Weight (kg) 94.57 ± 18.91 88.84 ± 17.75 <0.0001 
BMI (kg/m232.11 ± 6.01 31.60 ± 5.95 0.19 
Creatinine (µmol/dL) 79.89 ± 16.09 78.41 ± 19.33 0.25 
Creatinine clearance (mL/min) 85.17 ± 19.36 82.23 ± 29.44 0.04 
Dose at diagnosis (mg)* 1,500 (1,000–2,000) 1,000 (500–1,000) <0.0001 
Duration of diabetes (years) 4.0 (1.7–7.0) 4.0 (2.0–9.0) 0.09 
Use of metformin transporter-inhibiting drugs 274 (24.29) 95 (40.08) <0.0001 
VariableMetformin tolerant(n = 1,128)Metformin intolerant(n = 286)P
Age at diabetes diagnosis (years) 55.88 ± 9.44 58.62 ± 10.65 <0.0001 
Age at ITE (years) 60.73 ± 9.84 64.63 ± 9.91 <0.0001 
Sex   <0.0001 
 Males 696 (61.7) 117 (40.9)  
 Females 432 (38.3) 169 (59.1)  
Weight (kg) 94.57 ± 18.91 88.84 ± 17.75 <0.0001 
BMI (kg/m232.11 ± 6.01 31.60 ± 5.95 0.19 
Creatinine (µmol/dL) 79.89 ± 16.09 78.41 ± 19.33 0.25 
Creatinine clearance (mL/min) 85.17 ± 19.36 82.23 ± 29.44 0.04 
Dose at diagnosis (mg)* 1,500 (1,000–2,000) 1,000 (500–1,000) <0.0001 
Duration of diabetes (years) 4.0 (1.7–7.0) 4.0 (2.0–9.0) 0.09 
Use of metformin transporter-inhibiting drugs 274 (24.29) 95 (40.08) <0.0001 

Continuous data are presented as mean ± SD or median (IQR) and categorical data as n (%).

*Dose was calculated as the last dose during ITE for case subjects and was determined as the mean dose of prescriptions encashed during the first 6 months of metformin therapy for control subjects.

Concomitant Medications and Intolerance

This analysis was performed on 237 metformin-intolerant and 1,128 metformin-tolerant subjects who had complete data on history of concomitant medications. The analysis showed 40% of metformin-intolerant subjects were taking one or more cation transporter inhibitory drugs compared with 24% of tolerant subjects (P < 0.0001) (Table 1). A logistic regression model adjusted for age, sex, and weight showed concomitant use of these drugs increased the odds of being intolerant by 70% (odds ratio [OR] 1.72 [95% CI, 1.26–2.32], P < 0.001) (Supplementary Table 1). When the individual drug or drug groups were explored, concomitant use of metformin with PPIs, TCAs, or codeine increased the odds of metformin intolerance significantly (Fig. 1). The number of subjects who were coprescribed metformin with transporter-inhibiting drugs is reported in Supplementary Table 2.

Figure 1

Association of individual intestinal metformin transporter-inhibiting drugs with intolerance.

Figure 1

Association of individual intestinal metformin transporter-inhibiting drugs with intolerance.

Close modal

Genetic Variation in the Gut Metformin Transporters and Metformin Intolerance

In a logistic regression model, carriers of the G allele had 1.39 (95% CI 1.15–1.69, P < 0.001) times higher odds of being intolerant to metformin (unadjusted). When rs3889348 was added to a model adjusted for age, sex, weight, and genetic substructure, the presence of the G allele was independently associated with metformin intolerance (OR 1.34 [1.09–1.65], P = 0.005) (Supplementary Table 1). No statistically significant difference in any of the baseline phenotypes by genotype was observed (Supplementary Table 3). In addition, no significant interaction between rs3889348, the use of metformin transporter-inhibiting drugs, and any of the other clinical variables (age, sex) was observed.

We then grouped subjects based on the combination of SLC29A4 genotype and concomitant use of metformin transporter-inhibiting drugs. Taking those with no risk allele and who were not treated with transporter-inhibiting drugs as the reference group, carriers of one and two G alleles who were treated with transporter-inhibiting drugs had more than twofold (2.44 [95% CI 1.30–4.78]) and threefold (3.23 [1.71–6.39]) higher odds of intolerance, respectively, after adjusting for age, sex, and weight (Supplementary Table 4).

The association between SLC22A1 genotypes and metformin intolerance has been previously reported (12,35). We analyzed the association between two reduced-function (R61C and G401S) and one loss-of-function (M420del) SLC22A1 SNPs and metformin intolerance by using a combined unweighted GRS. In a logistic regression model adjusted for age, sex, weight, genetic substructure, and concomitant use of transporter-inhibiting drugs, the SLC22A1 GRS was not statistically significantly associated with metformin intolerance (OR 1.35 [95% CI 0.84–2.12], P = 0.21).

A GRS was then generated from SLC29A4 and SLC22A1 variants by summing the number of risk alleles for each individual. Compared with those with no risk allele, metformin-treated subjects with type 2 diabetes who had two risk alleles had nearly a twofold (1.93 [95% CI 1.10–3.65]) increased odds of GI intolerance. Those who carried three or more risk alleles had more than twice (2.15 [1.20–4.12]) the odds of intolerance (Fig. 2).

Figure 2

Association of a GRS derived from SLC29A4 (PMAT) and SLC22A1 (OCT1) with metformin intolerance. Bars indicate SE around the mean. *P < 0.05.

Figure 2

Association of a GRS derived from SLC29A4 (PMAT) and SLC22A1 (OCT1) with metformin intolerance. Bars indicate SE around the mean. *P < 0.05.

Close modal

Sensitivity Analysis

There was a big difference in sample size between metformin-intolerant and metformin-tolerant subjects. In addition, there were significant differences in age and sex between case subjects and control subjects. We therefore performed a sensitivity analysis by comparing the intolerant group (n = 237) with an age- and sex-matched subgroup of tolerant subjects (n = 711). The main findings from the larger metformin-tolerant group were confirmed in this sensitivity analysis (Supplementary Tables 5 and 6).

rs3889348 Is Associated With Altered PMAT Expression in the Gut

Given PMAT is one of the major metformin transporters in the gut, we explored the possibility that the intronic SNP rs3889348 is a cis-eQTL in the intestine by using the publicly available data set from the GTEx portal (v6p) (32). The G allele of rs3889348 (associated with higher risk of intolerance) was significantly associated with lower expression of SLC29A4 in the terminal ileum of the small intestine (β = −0.42, P = 2.1 × 10−04) and the transverse colon (β = −0.45, P = 1.4 × 10−08) (Supplementary Fig. 1). rs3889348 is the top cis-eQTL for SLC29A4 in the transverse colon.

Intestinal absorption of metformin is modulated by the function of cation transporters expressed in the gut. An association between reduced-function alleles in the SLC22A1, encoding OCT1, and metformin-related GI adverse effects has been previously reported (12,13,36). However, the data on intestinal localization of OCT1 are ambiguous, with mixed reports suggesting in the apical (10) and basolateral (11,37) sides. In addition to OCT1, PMAT also contributes to the intestinal absorption of metformin. PMAT is abundantly expressed in the human intestine and is concentrated on the tips of the mucosal epithelial layer (38). Carriers of the G allele at this locus (rs3889348) had significantly reduced expression of SLC29A4 in the gut (32). This could lead to higher luminal concentration of metformin. In this current study, we demonstrated a significant association of the G allele of an intronic SNP, rs3889348, in SLC29A4 encoding PMAT, with higher odds of GI intolerance after metformin therapy. Each copy of the G allele was associated with 1.34 times higher odds of metformin intolerance. We also showed that those who carried two or more variants at SLC29A4 or SLC22A1 were twofold more likely to have GI intolerance. Given that PMAT is apically located, this finding suggests that intolerance is driven by increased luminal concentration of metformin rather than by increased enterocyte concentration and direct toxicity to the enterocytes.

There are a number of putative mechanisms whereby increased luminal metformin may increase GI intolerance to metformin (outlined in Fig. 3). Firstly, a higher concentration of metformin in the gut has been shown to inhibit uptake of histamine and serotonin, leading to increased luminal concentration of these biogenic amines (13). Metformin also inhibits diamine oxidase, an enzyme that degrades histamine, at therapeutic doses (6). Biogenic amines play an important role in the GI pathophysiology. Elevated levels of serotonin and histamine in the GI tract cause GI symptoms such as nausea, vomiting, and diarrhea (6,39). Serotonin is produced mainly in the gut and stored in the enterochromaffin cells of the epithelium. Its release activates gut sensory neurons that will increase intestinal motility, secretion, and sensation (39,40). Increased colon motility and softening of stool consistency have also been observed in serotonin reuptake transporter (SERT) knock-out mice (39,40). In addition, a recent study from the GoDARTS (Genetics of Diabetes Audit and Research in Tayside Scotland) cohort showed association of a composite SERT genotype, 5-HTTLPR (5-hydroxy tryptamine [serotonin] transporter-linked polymorphic region)/rs25531, with intolerance to metformin in subjects with type 2 diabetes (13). In this study, carriers of the low-expressing SERT S* alleles had >30% increased odds of metformin intolerance (OR 1.31 [95% CI 1.02–1.67], P = 0.031). Histamine is a monogenic amine stored in the enterochromaffin-like cells within the gastric glands of the stomach. Binding of histamine to the H1, H2, and H4 receptors that are highly expressed in the gut stimulates gastric acid secretion and increases intestinal motility and smooth muscle inflammation (6).

Figure 3

Possible mechanisms for metformin intolerance. A: Metformin is absorbed from the gut lumen via cation transporters such as PMAT, OCT1, SERT, and OCT3. B: Increased level of metformin in the gut lumen is observed when metformin is taken with cation transporter-inhibiting drugs such as PPIs, TCAs, and codeine. These drugs competitively inhibit metformin uptake by the cation transporters. Metformin is also shown to inhibit diamine oxide, an enzyme that metabolizes biogenic amines. In addition, transport capacity of the cation transporters could be reduced in carriers of reduced function (420del, 61C, 401S in SLC22A1) or low-expressing alleles (rs3889348_G in SLC29A4) and hence increase luminal metformin level. The increased level of metformin increases the level of biogenic amines, affects the gut microbiota, and elevates bile acid levels. These may cause symptoms of GI adverse effects.

Figure 3

Possible mechanisms for metformin intolerance. A: Metformin is absorbed from the gut lumen via cation transporters such as PMAT, OCT1, SERT, and OCT3. B: Increased level of metformin in the gut lumen is observed when metformin is taken with cation transporter-inhibiting drugs such as PPIs, TCAs, and codeine. These drugs competitively inhibit metformin uptake by the cation transporters. Metformin is also shown to inhibit diamine oxide, an enzyme that metabolizes biogenic amines. In addition, transport capacity of the cation transporters could be reduced in carriers of reduced function (420del, 61C, 401S in SLC22A1) or low-expressing alleles (rs3889348_G in SLC29A4) and hence increase luminal metformin level. The increased level of metformin increases the level of biogenic amines, affects the gut microbiota, and elevates bile acid levels. These may cause symptoms of GI adverse effects.

Close modal

In addition to the potential role of local concentrations of serotonin and histamine, increased luminal concentrations of metformin could also cause intolerance by other mechanisms that need to be explored. For example, intolerance could be mediated by a reduction in bile acid reabsorption in the ileum leading to elevated bile acid levels in the colon (41), which is known to cause GI disturbances (42). In addition, metformin affects composition and function of the gut microbiota favoring the growth of some species like Akkermansia (5,4346). Furthermore, increased levels of active and total glucagon-like peptide 1 levels in subjects with type 2 diabetes and without type 2 diabetes treated with metformin (47) were also reported, and this might increase GI adverse effects (48) (Fig. 3).

In this study, we observed an increased risk of intolerance with older age, female sex, lower weight, and lower creatinine levels. Concomitant use of metformin with PPIs and TCAs also increases the risk of intolerance. These findings are largely consistent with the results of previous studies, providing further evidence for clinical practice (12,35). The U.S. Food and Drug Administration Adverse Events Reporting System suggested that women experience more adverse effects than men (49). Several factors can contribute to these differences. Sex-based variability in intestinal expression of drug transporters may result in variability in drug concentrations in the gut. Women also have slower gastric emptying, altered bile composition, and slower intestinal transit time than men (50). These factors could in turn affect the rate and/or extent of absorption of oral medications and hence local drug concentrations in the gut. For a better understanding of the basic mechanisms of sex differences in metformin intolerance, future studies should be designed with a primary focus on this topic.

In summary, we have identified a variant that alters intestinal expression of the cation transporter PMAT (SLC29A4) that increases the risk of metformin-associated GI intolerance. Combined with the previously reported SLC22A1 variants, this genotype profile can increase the odds of metformin intolerance more than twofold. The apical location of PMAT means that reduced expression will result in increased luminal metformin concentration, suggesting that metformin intolerance is caused by this increased luminal concentration rather than by increased enterocyte concentration.

A limitation of this study was the definition for metformin-induced GI intolerance. Even though we examined patient reports and clinical records for GI intolerance as a reason for stopping metformin and switching to other medications, there could have been other reasons for stopping metformin such as comorbidities that might cause GI disturbance. In addition, initial conclusions drawn from this study need validation and replication in well-powered independent studies.

Acknowledgments. The authors are very grateful to all participants who took part in these studies.

Funding. The work leading to this publication has received support from the Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115317 (DIRECT), resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and an in-kind contribution from the European Federation of Pharmaceutical Industries and Associations. E.R.P. holds a Wellcome Trust New Investigator Award (102820/Z/13/Z).

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

Author Contributions. A.Y.D. analyzed data, wrote the manuscript, and performed research. K.Z. analyzed data, designed research, and revised the manuscript. N.v.L., R.K., P.J.M.E., and S.P.R. collected data and revised the manuscript. A.M. and N.R. analyzed data and revised the manuscript. A.G.J., R.W.H., and J.C.S. designed research, collected data, and revised the manuscript. P.W.F. designed and performed research and revised the manuscript. M.I.M. designed research, analyzed data, and revised the manuscript. L.M.‘tH. designed research, collected and analyzed data, and revised the manuscript. E.R.P. designed and performed research, analyzed data, and wrote and revised the manuscript. A.Y.D. and E.R.P. are guarantors of this work and, as such, had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

1.
Garber
AJ
,
Duncan
TG
,
Goodman
AM
,
Mills
DJ
,
Rohlf
JL
.
Efficacy of metformin in type II diabetes: results of a double-blind, placebo-controlled, dose-response trial
.
Am J Med
1997
;
103
:
491
497
[PubMed]
2.
Hirst
JA
,
Farmer
AJ
,
Ali
R
,
Roberts
NW
,
Stevens
RJ
.
Quantifying the effect of metformin treatment and dose on glycemic control
.
Diabetes Care
2012
;
35
:
446
454
[PubMed]
3.
Bailey
CJ
,
Wilcock
C
,
Scarpello
JH
.
Metformin and the intestine
.
Diabetologia
2008
;
51
:
1552
1553
[PubMed]
4.
Wilcock
C
,
Bailey
CJ
.
Accumulation of metformin by tissues of the normal and diabetic mouse
.
Xenobiotica
1994
;
24
:
49
57
[PubMed]
5.
Napolitano
A
,
Miller
S
,
Nicholls
AW
, et al
.
Novel gut-based pharmacology of metformin in patients with type 2 diabetes mellitus
.
PLoS One
2014
;
9
:
e100778
[PubMed]
6.
Yee
SW
,
Lin
L
,
Merski
M
, et al
.
Prediction and validation of enzyme and transporter off-targets for metformin
.
J Pharmacokinet Pharmacodyn
2015
;
42
:
463
475
[PubMed]
7.
Yi
F
,
Sun
J
,
Lim
GE
,
Fantus
IG
,
Brubaker
PL
,
Jin
T
.
Cross talk between the insulin and Wnt signaling pathways: evidence from intestinal endocrine L cells
.
Endocrinology
2008
;
149
:
2341
2351
[PubMed]
8.
Vidon
N
,
Chaussade
S
,
Noel
M
,
Franchisseur
C
,
Huchet
B
,
Bernier
JJ
.
Metformin in the digestive tract
.
Diabetes Res Clin Pract
1988
;
4
:
223
229
[PubMed]
9.
Han
TK
,
Proctor
WR
,
Costales
CL
,
Cai
H
,
Everett
RS
,
Thakker
DR
.
Four cation-selective transporters contribute to apical uptake and accumulation of metformin in Caco-2 cell monolayers
.
J Pharmacol Exp Ther
2015
;
352
:
519
528
[PubMed]
10.
Han
TK
,
Everett
RS
,
Proctor
WR
, et al
.
Organic cation transporter 1 (OCT1/mOct1) is localized in the apical membrane of Caco-2 cell monolayers and enterocytes
.
Mol Pharmacol
2013
;
84
:
182
189
[PubMed]
11.
Müller
J
,
Lips
KS
,
Metzner
L
,
Neubert
RH
,
Koepsell
H
,
Brandsch
M
.
Drug specificity and intestinal membrane localization of human organic cation transporters (OCT)
.
Biochem Pharmacol
2005
;
70
:
1851
1860
[PubMed]
12.
Dujic
T
,
Zhou
K
,
Donnelly
LA
,
Tavendale
R
,
Palmer
CN
,
Pearson
ER
.
Association of organic cation transporter 1 with intolerance to metformin in type 2 diabetes: a GoDARTS study
.
Diabetes
2015
;
64
:
1786
1793
[PubMed]
13.
Dujic
T
,
Zhou
K
,
Tavendale
R
,
Palmer
CN
,
Pearson
ER
.
Effect of serotonin transporter 5-HTTLPR polymorphism on gastrointestinal intolerance to metformin: a GoDARTS study
.
Diabetes Care
2016
;
39
:
1896
1901
[PubMed]
14.
Duan
H
,
Hu
T
,
Foti
RS
,
Pan
Y
,
Swaan
PW
,
Wang
J
.
Potent and selective inhibition of plasma membrane monoamine transporter by HIV protease inhibitors
.
Drug Metab Dispos
2015
;
43
:
1773
1780
[PubMed]
15.
Koivula
RW
,
Heggie
A
,
Barnett
A
, et al.;
DIRECT Consortium
.
Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: rationale and design of the epidemiological studies within the IMI DIRECT Consortium
.
Diabetologia
2014
;
57
:
1132
1142
[PubMed]
16.
Engel
K
,
Wang
J
.
Interaction of organic cations with a newly identified plasma membrane monoamine transporter
.
Mol Pharmacol
2005
;
68
:
1397
1407
[PubMed]
17.
Ahlin
G
,
Chen
L
,
Lazorova
L
, et al
.
Genotype-dependent effects of inhibitors of the organic cation transporter, OCT1: predictions of metformin interactions
.
Pharmacogenomics J
2011
;
11
:
400
411
[PubMed]
18.
Ahlin
G
,
Karlsson
J
,
Pedersen
JM
, et al
.
Structural requirements for drug inhibition of the liver specific human organic cation transport protein 1
.
J Med Chem
2008
;
51
:
5932
5942
[PubMed]
19.
Nies
AT
,
Hofmann
U
,
Resch
C
,
Schaeffeler
E
,
Rius
M
,
Schwab
M
.
Proton pump inhibitors inhibit metformin uptake by organic cation transporters (OCTs)
.
PLoS One
2011
;
6
:
e22163
[PubMed]
20.
Li
L
,
Song
F
,
Tu
M
, et al
.
In vitro interaction of clopidogrel and its hydrolysate with OCT1, OCT2 and OAT1
.
Int J Pharm
2014
;
465
:
5
10
[PubMed]
21.
Bachmakov
I
,
Glaeser
H
,
Fromm
MF
,
König
J
.
Interaction of oral antidiabetic drugs with hepatic uptake transporters: focus on organic anion transporting polypeptides and organic cation transporter 1
.
Diabetes
2008
;
57
:
1463
1469
[PubMed]
22.
Tzvetkov
MV
,
Saadatmand
AR
,
Lötsch
J
,
Tegeder
I
,
Stingl
JC
,
Brockmöller
J
.
Genetically polymorphic OCT1: another piece in the puzzle of the variable pharmacokinetics and pharmacodynamics of the opioidergic drug tramadol
.
Clin Pharmacol Ther
2011
;
90
:
143
150
[PubMed]
23.
Tzvetkov
MV
,
dos Santos Pereira
JN
,
Meineke
I
,
Saadatmand
AR
,
Stingl
JC
,
Brockmöller
J
.
Morphine is a substrate of the organic cation transporter OCT1 and polymorphisms in OCT1 gene affect morphine pharmacokinetics after codeine administration
.
Biochem Pharmacol
2013
;
86
:
666
678
[PubMed]
24.
Nies
AT
,
Koepsell
H
,
Damme
K
,
Schwab
M
.
Organic cation transporters (OCTs, MATEs), in vitro and in vivo evidence for the importance in drug therapy. In Drug Transporters. Fromm MF, Kim RB, Eds. Berlin, Heidelberg, Springer, 2011. (Handbook of Experimental Pharmacology, vol. 201)
25.
Tzvetkov
MV
,
Saadatmand
AR
,
Bokelmann
K
,
Meineke
I
,
Kaiser
R
,
Brockmöller
J
.
Effects of OCT1 polymorphisms on the cellular uptake, plasma concentrations and efficacy of the 5-HT(3) antagonists tropisetron and ondansetron
.
Pharmacogenomics J
2012
;
12
:
22
29
[PubMed]
26.
Minematsu
T
,
Giacomini
KM
.
Interactions of tyrosine kinase inhibitors with organic cation transporters and multidrug and toxic compound extrusion proteins
.
Mol Cancer Ther
2011
;
10
:
531
539
[PubMed]
27.
Yang
J
,
Manolio
TA
,
Pasquale
LR
, et al
.
Genome partitioning of genetic variation for complex traits using common SNPs
.
Nat Genet
2011
;
43
:
519
525
[PubMed]
28.
Delaneau
O
,
Zagury
JF
,
Marchini
J
.
Improved whole-chromosome phasing for disease and population genetic studies
.
Nat Methods
2013
;
10
:
5
6
[PubMed]
29.
Howie
BN
,
Donnelly
P
,
Marchini
J
.
A flexible and accurate genotype imputation method for the next generation of genome-wide association studies
.
PLoS Genet
2009
;
5
:
e1000529
[PubMed]
30.
Christensen
MM
,
Brasch-Andersen
C
,
Green
H
, et al
.
The pharmacogenetics of metformin and its impact on plasma metformin steady-state levels and glycosylated hemoglobin A1c
.
Pharmacogenet Genomics
2011
;
21
:
837
850
[PubMed]
31.
Marchini
J
,
Howie
B
,
Myers
S
,
McVean
G
,
Donnelly
P
.
A new multipoint method for genome-wide association studies by imputation of genotypes
.
Nat Genet
2007
;
39
:
906
913
[PubMed]
32.
GTEx Consortium
.
The Genotype-Tissue Expression (GTEx) project
.
Nat Genet
2013
;
45
:
580
585
[PubMed]
33.
Gamazon
ER
,
Wheeler
HE
,
Shah
KP
, et al.;
GTEx Consortium
.
A gene-based association method for mapping traits using reference transcriptome data
.
Nat Genet
2015
;
47
:
1091
1098
[PubMed]
34.
Gamazon
ER
,
Segrè
AV
,
van de Bunt
M
, et al.;
GTEx Consortium
.
Using an atlas of gene regulation across 44 human tissues to inform complex disease- and trait-associated variation
.
Nat Genet
2018
;
50
:
956
967
[PubMed]
35.
Dujic
T
,
Causevic
A
,
Bego
T
, et al
.
Organic cation transporter 1 variants and gastrointestinal side effects of metformin in patients with type 2 diabetes
.
Diabet Med
2016
;
33
:
511
514
[PubMed]
36.
Tarasova
L
,
Kalnina
I
,
Geldnere
K
, et al
.
Association of genetic variation in the organic cation transporters OCT1, OCT2 and multidrug and toxin extrusion 1 transporter protein genes with the gastrointestinal side effects and lower BMI in metformin-treated type 2 diabetes patients
.
Pharmacogenet Genomics
2012
;
22
:
659
666
[PubMed]
37.
Wang
DS
,
Jonker
JW
,
Kato
Y
,
Kusuhara
H
,
Schinkel
AH
,
Sugiyama
Y
.
Involvement of organic cation transporter 1 in hepatic and intestinal distribution of metformin
.
J Pharmacol Exp Ther
2002
;
302
:
510
515
[PubMed]
38.
Zhou
M
,
Xia
L
,
Wang
J
.
Metformin transport by a newly cloned proton-stimulated organic cation transporter (plasma membrane monoamine transporter) expressed in human intestine
.
Drug Metab Dispos
2007
;
35
:
1956
1962
[PubMed]
39.
Gershon
MD
.
Review article: serotonin receptors and transporters -- roles in normal and abnormal gastrointestinal motility
.
Aliment Pharmacol Ther
2004
;
20
(
Suppl. 7
):
3
14
[PubMed]
40.
Mawe
GM
,
Hoffman
JM
.
Serotonin signalling in the gut--functions, dysfunctions and therapeutic targets
.
Nat Rev Gastroenterol Hepatol
2013
;
10
:
473
486
[PubMed]
41.
Scarpello
JH
,
Hodgson
E
,
Howlett
HC
.
Effect of metformin on bile salt circulation and intestinal motility in type 2 diabetes mellitus
.
Diabet Med
1998
;
15
:
651
656
[PubMed]
42.
Kelly
OB
,
Mroz
MS
,
Ward
JB
, et al
.
Ursodeoxycholic acid attenuates colonic epithelial secretory function
.
J Physiol
2013
;
591
:
2307
2318
[PubMed]
43.
Lee
H
,
Ko
G
.
Effect of metformin on metabolic improvement and gut microbiota
.
Appl Environ Microbiol
2014
;
80
:
5935
5943
[PubMed]
44.
McCreight
LJ
,
Bailey
CJ
,
Pearson
ER
.
Metformin and the gastrointestinal tract
.
Diabetologia
2016
;
59
:
426
435
[PubMed]
45.
Shin
NR
,
Lee
JC
,
Lee
HY
, et al
.
An increase in the Akkermansia spp. population induced by metformin treatment improves glucose homeostasis in diet-induced obese mice
.
Gut
2014
;
63
:
727
735
[PubMed]
46.
Kinaan
M
,
Ding
H
,
Triggle
CR
.
Metformin: an old drug for the treatment of diabetes but a new drug for the protection of the endothelium
.
Med Princ Pract
2015
;
24
:
401
415
[PubMed]
47.
Preiss
D
,
Dawed
A
,
Welsh
P
, et al.;
DIRECT Consortium Group
.
Sustained influence of metformin therapy on circulating glucagon-like peptide-1 levels in individuals with and without type 2 diabetes
.
Diabetes Obes Metab
2017
;
19
:
356
363
[PubMed]
48.
Bettge
K
,
Kahle
M
,
Abd El Aziz
MS
,
Meier
JJ
,
Nauck
MA
.
Occurrence of nausea, vomiting and diarrhoea reported as adverse events in clinical trials studying glucagon-like peptide-1 receptor agonists: a systematic analysis of published clinical trials
.
Diabetes Obes Metab
2017
;
19
:
336
347
[PubMed]
49.
Tran
C
,
Knowles
SR
,
Liu
BA
,
Shear
NH
.
Gender differences in adverse drug reactions
.
J Clin Pharmacol
1998
;
38
:
1003
1009
[PubMed]
50.
Soldin
OP
,
Mattison
DR
.
Sex differences in pharmacokinetics and pharmacodynamics
.
Clin Pharmacokinet
2009
;
48
:
143
157
[PubMed]
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