pharmacogenetic variation and metformin response

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1070 Current Drug Metabolism, 2013, 14, 1070-1082

Pharmacogenetic Variation and Metformin Response

Suning Chen1, Jie Zhou

3, Miaomiao Xi

1, Yanyan Jia

1, Yan Wong

1, Jinyi Zhao

1, Likun Ding

1, Jian Zhang

2*

and Aidong Wen1*

1Department of Pharmacy, Xijing Hospital, The Fourth Military Medical University, Xi’an, Shaanxi Province, 710032, People’s

Republic of China; 2The State Key Laboratory of Cancer Biology and The Department of Biochemistry and Molecular Biology, The

Fourth Military Medical University, Xi’an, Shaanxi Province, 710032, People’s Republic of China; 3Department of Endocrinology

and Metabolism, Xijing Hospital, The Fourth Military Medical University, Xi’an, Shaanxi Province, 710032, People’s Republic of

China

Abstract: Diabetes is a major health problem worldwide, and metformin, a traditional oral anti-hyperglycemic drug, is now believed to be the most widely prescribed antidiabetic drug. Metformin acts primarily by inhibiting hepatic glucose production and improving insulin

sensitivity. Metformin is absorbed predominately by the small intestine and excreted in an unaltered form in the urine. The pharmacoki-netics of metformin is primarily determined by membrane transporters, including the plasma membrane monoamine transporter (PMAT),

the organic cation transporters (OCTs), the multidrug and toxin extrusion (MATE) transporters, and the critical protein kinase AMP-activated protein kinase (AMPK). PMAT may play a role in the uptake of metformin from the gastrointestinal tract, while OCTs mediate

the intestinal absorption, hepatic uptake, and renal excretion of metformin. MATEs are believed to contribute to the hepatic and renal ex-cretion of the drug. The pharmacologic effects of metformin are primarily exerted in the liver, at least partly via the activation of AMPK

and the subsequent inhibition of gluconeogenesis. A considerable amount of pharmacogenetic research has demonstrated that genetic variation is one of the major factors affecting metformin response. Moreover, it has become increasingly clear that membrane transport-

ers are important determinants of the pharmacokinetics of metformin. In this review, we will discuss the genetic variants of major trans-porters that purportedly determine the pharmacokinetics of metformin in terms of drug bioavailability, distribution, and excretion, such as

PMAT, OCTs, and MATEs. Understanding how genetic variation affects metformin response will help promote more effective use of the drug for the treatment of type 2 diabetes (T2D).

Keywords: AMPK, MATE, metformin, OCT, pharmacogenetic, SNP, T2D.

1. INTRODUCTION

Type 2 diabetes (T2D) is a major global health problem of the 21

st century. Metformin, a traditional oral anti-hyperglycemic drug,

is widely used as a first-line therapy for T2D treatment and primar-ily acts by inhibiting hepatic glucose production and improving insulin sensitivity, thereby decreasing the insulin resistance that is prevalent in T2D [1]. The other beneficial effects of metformin include weight loss, reduced lipid levels, the prevention of vascular complications, and a lower risk of hypoglycemia [2]. The mecha-nism by which metformin decreases endogenous glucose produc-tion in T2D patients has been found to involve the inhibition of gluconeogenesis and, to a lesser extent, glycogenolysis, resulting in reduced plasma glucose levels; the effects of metformin have also been attributed to increased insulin-stimulated glucose uptake in skeletal muscles and adipocytes [3]. Consistent with these findings, data from other in vivo studies confirmed the inhibitory effect of metformin on gluconeogenesis [2]. In contrast to sulfonylureas, metformin does not lead to hypoglycemia in T2D patients or normal subjects (except under special conditions) and does not cause hyper-insulinemia. These reduced side effects may be the primary reasons for the popularity of metformin for T2D therapy worldwide.

The response to a drug is mainly determined by its pharmacoki-netic properties [4]. In this regard, the pharmacologic mechanism of metformin differs from those of other classes of oral anti-hyperglycemic agents. Chemically, metformin is a hydrophilic base that exists as a cationic species (>99.9%) under physiological pH

*Address correspondence to these authors at the Department of Pharmacy,

Xijing Hospital, and The State Key Laboratory of Cancer Biology and The Department of Biochemistry and Molecular Biology, The Fourth Military

Medical University, Xi’an, Shaanxi Province, 710032, People’s Republic of China; Tel: +86 29 84774517-8012; Fax: +86 29 84773947; E-mails: bioz-

[email protected]; [email protected]

conditions. The passive diffusion of metformin through cell mem-branes is therefore very limited. Metformin is absorbed predomi-nately by the small intestine and excreted unchanged in the urine and bile. In healthy subjects and diabetic patients with good renal function, the population mean renal clearance (CL(R)) and apparent total clearance (CL/F) after oral administration of metformin were estimated to be 510 ± 130 mL/min and 1140 ± 330 mL/min, respec-tively. Because CL(R) and CL/F decrease approximately in propor-tion to CL(R), the dosage of metformin should be reduced in pa-tients with renal impairment [5]. The primary reason for this pre-caution is that metformin does not undergo pharmacokinetic modi-fications in the body, with negligible hepatic metabolism and bil-iary excretion [6].

In terms of drug efficacy and toxicity, numerous factors con-tribute to interindividual variability, including age, gender, nutri-tional status, life style, and genetic factors [1b]. In this regard, ge-netic variation is undoubtedly one of the major factors affecting the response to metformin. Moreover, it has become increasingly clear that membrane transporters are important determinants of met-formin pharmacokinetics [7]. Some patients taking metformin do not respond sufficiently. In one study, 42% of T2D patients experi-enced secondary failure within the 2- to 5-year follow-up period, with an average secondary failure rate of 17.0% per year [8]. Meanwhile, although metformin-induced lactic acidosis is remarka-bly rare, it represents a serious side effect of the drug. For these reasons, understanding the potential causes of the different side effects observed in different patients is a major step in preventing their occurrence or development. Given the likely influence of ge-netic variation on the absorption, distribution, and excretion of many drugs and the dependence of drug concentration maintenance on transporter activity, it is reasonable to hypothesize that genetic variants of these transporters have important effects. Reflecting the importance of metformin for T2D treatment, a number of studies in

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Pharmacogenetic Variation and Metformin Response Current Drug Metabolism, 2013, Vol. 14, No. 10 1071

recent decades have focused on the transport efficiency of met-formin and analyzed how the pharmacokinetics of the drug are affected by genetic variants of different transporters. It is highly likely that the relationship between the pharmacokinetics of met-formin and the response to the drug is influenced by interindividual variability in terms of drug susceptibility, bioavailability, or the distribution to the pharmacological target tissues [1b].

The available studies in this field have identified the following

membrane transporters as the major determinants of metformin pharmacokinetics: the plasma membrane monoamine transporter (PMAT), organic cation transporters (OCTs), and multidrug and toxin extrusion (MATE) transporters. Most importantly, the phar-macological effect of metformin is reported to be heavily dependent on AMP-activated protein kinase (AMPK). In this review, we will summarize the state-of–the-art research examining genetic variants of the major molecules that determine the bioavailability, distribu-tion, excretion, and pharmacological effects of metformin, includ-ing PMAT, OCTs, MATEs, and AMPK. An improved understand-ing of the genetic variation in the transporters and the pharmacoki-netics of metformin will help improve the drug response and pre-vent undesired side effects of the drug in T2D patients.

2. PMAT

PMAT is a novel proton-activated organic cation transporter that was recently cloned and characterized and is mainly distributed in the human small intestine and kidney. In the small intestine, PMAT is concentrated on the tips of the mucosal epithelial layer. Similarly, PMAT is expressed on the apical membranes of renal epithelial cells in the kidney and specifically expressed in podo-cytes [9]. From the limited literature available, PMAT appears to play a role in the intestinal absorption of metformin, using the lu-minal proton gradient to drive organic cation reabsorption in the kidney. The available evidence suggests that PMAT-mediated met-formin transport is greatly stimulated by acidic pH, with the uptake rate being 4-fold higher at pH 6.6 than at pH 7.4 [10]. However,

there is little evidence that genetic variation in PMAT affects the pharmacokinetics of metformin.

3. OCTs

The OCTs consist of three major OCT subtypes, OCT1, OCT2, and OCT3, which are encoded by the genes SLC22A1, SLC22A2, and SLC22A3, respectively. OCTs are broad-specificity transporters critical for the uptake, distribution, and elimination of cationic drugs. They also participate in the excretion and distribution of endogenous organic cations, such as choline, creatinine, and cati-onic neurotransmitters. OCTs are present in many tissues, including the small intestine, liver, kidney, heart, and skeletal muscle. In epithelial cells, the OCTs are located in the basolateral or luminal membranes. In the liver, one crucial function of hepatocytes is to transform and eliminate various drugs, many of which are organic

cations taken up by OCTs [11]. It is clear that the oral absorption, hepatic uptake, and renal excretion of metformin are largely medi-ated by OCTs [5]. Additionally, various in vivo and human studies have shown that metformin is a good substrate for the organic cation transporters OCT1 and OCT2 [7c, 12]. It was recently re-ported that polymorphisms in the OCTs of T2D patients result in altered metformin pharmacokinetics and drug response [13]. The identification of polymorphisms in human OCTs therefore permits the identification of patients with an increased risk of adverse reac-tions to the drug.

3.1. OCT1

3.1.1. Physiological and Pharmacological Role of OCT1

Human OCT1 is encoded by the SLC22A1 gene, which is ex-pressed in the liver and various other organs, including the small intestine, lung, mammary gland, and adrenal gland [14]. OCT1 is

critical for the elimination of many endogenous small organic cations and a wide range of drugs and environmental toxins. The substrates of human OCT1 include many cations, such as met-

formin, tetraethylammonium (TEA), 1-methyl-4-phenylpyridinium (MPP), and 4-[4-(dimethylamino)-styryl]-N-methylpyridinium (ASP) [15]. The expression and transport activity of OCT1 dramatically influences the pharmacokinetics, dose-response, and toxicity of the drugs transported by OCT1. Wang et al. showed that metformin levels were greatly reduced in the liver and intestines of Oct1 knockout (KO) mice, whereas only slight differences were observed for the urinary excretion profile of metformin; these observations suggest that OCT1 is responsible for the entry of metformin into hepatocytes and enterocytes, while the renal distribution and excre-tion of the drug may be governed by other transport proteins [7b]. Many human genetic variants of OCT1 have been identified [13,

16], some of which reduce transport activity. Thus, if the SNPs in OCT1 alter its activity as a transporter of cationic drugs such as metformin, different drug responses and therapeutic effects in pa-tients can definitely be attributed to such genetic variants [17].

3.1.2. Effect of OCT1 Genetic Variants

In the studies examining the relationship between SNPs of OCT1 and metformin pharmacokinetics, some genotypes were

found to have a significant effect on metformin pharmacokinetics. For example, a greater area under the plasma concentration-time

curve (AUC), a higher maximal plasma concentration (Cmax), and a lower oral volume of distribution (V/F) were observed in indi-

viduals carrying the reduced-function OCT1 alleles R61C, G401S, M420del, and G465R. The OCT1 SNPs rs2282143 (the T allele)

and rs628031 (the G allele) were more common in Asians and Afri-can Americans than in Caucasians (0-2% versus 57.4-60%), which

influences the interindividual variation in clinical responses to met-formin therapy [18].

Recent data for 66 Japanese patients with T2D from the 1,000

Genomes Project indicated that P117L and R206C caused a reduced V(max), whereas Q97K caused an increased K(m) [19]. It is nota-

ble that the M420del and R61C variants were more sensitive to metformin, with IC(50) values up to 23 times lower than those of

the OCT1 reference [13]. Additionally, the OCT1 R61C and M420del variants were found to have a significant effect on met-

formin pharmacokinetics, with a higher area under the plasma con-centration-time curve (AUC) and a lower oral volume of distribu-

tion (V/F) in the T2D patients [4]. In addition to T2D treatment, metformin has also been used to treat women with polycystic ovary

syndrome (PCOS). Gambineri et al. found that four OCT1 variants (R61C, G401S, G465R, and M420del) were associated with hetero-

geneity in the metabolic response to metformin in women with PCOS [20].

HbA1c levels are critical for evaluating the response to met-

formin in diabetes mellitus patients. One population-based cohort study in Rotterdam showed that the minor C allele at rs622342 in

the SLC22A1 gene (OCT1) was associated with 0.28% less reduc-tion in glycated hemoglobin (HbA1c) levels [21]. Additionally, the

rs622342 SNP has been associated with a decreased effect on blood glucose in heterozygotes and a lack of an effect of metformin on plasma glucose in homozygotes [5].

To elucidate the pharmacogenetic variations of metformin, seven polymorphisms in the OCT1, OCT2, and MATE1 genes were

compared in 53 T2D patients exhibiting side effects from met-formin and 193 metformin users without obvious symptoms of

discomfort. The results demonstrated that the rs628031 and rs36056065 SNPs in OCT1 were in strong linkage disequilibrium

and predisposed patients with T2D to the side effects of metformin [22]. It is therefore critical to evaluate these and other interindi-

vidual polymorphisms to predict or prevent the side effects of met-formin.

1072 Current Drug Metabolism, 2013, Vol. 14, No. 10 Chen et al.

Table 1. Genetic Variation in OCT1 (SLC22A1) and Metformin Sensitivity

Variants Study design Conclusion Reference

rs622342 A>C A population-based cohort study of 102 patients with

diabetes mellitus (Caucasians).

Genetic variation at rs622342 was associated with the

glucose-lowering effect of metformin. [21]

Q97K, P117L,

and R206C

Used data from the 1,000 Genomes Project and direct

sequencing of selected OCT1 amplicons from 66 DNA

samples from Japanese patients with T2D.

The uptake of metformin in cells expressing Q97K,

P117L, and R206C was significantly reduced relative to

the OCT1 reference.

[19]

R61C, G401S,

G465R, and

420del

Studied 150 Italian PCOS patients aged 18-45 years old.

Genetic variation in OCT1 may be associated with het-

erogeneity in the metabolic response to metformin in

women with PCOS.

[20]

R61C, G401S,

420del, G465R

Twenty healthy volunteers with known OCT1 genotype

received two oral doses of metformin; blood and urine

samples were subsequently collected.

OCT1 genotype is a determinant of metformin

pharmacokinetics. [4]

rs628031

rs36056065

Seven polymorphisms in the OCT1, OCT2, and MATE1

genes were compared in 53 T2D patients experiencing

metformin side effects and 193 metformin users without

metformin intolerance symptoms.

The two genetic variants of OCT1 are in strong linkage

disequilibrium and predispose patients with T2D to an

increased prevalence of metformin side effects.

[22]

rs2282143

rs628031

rs622342

A total of 112 unrelated healthy male and female subjects

of South Indian Tamil origin aged 18-60 years old were

recruited for the analysis of genetic variants of OCT1.

The SNPs rs2282143 (T allele) and rs628031 (G allele)

were more common in Asians and African Americans

than in Caucasians.

[18]

R61C

M420del

A total of 3,450 T2D patients were genotyped, and their

metformin responses were assessed by modeling the

maximum A1C reduction.

The R61C and M420del variants do not attenuate HbA1c

reduction resulting from metformin treatment in T2D

patients.

[65]

rs622342 A>C

A multiplicative interaction between the polymorphisms

and changes in HbA1c levels was analyzed in 98 incident

metformin users.

The effect of the MATE1 rs2289669 polymorphism on

the glucose-lowering effect of metformin is larger in

incident users with the OCT1 rs622342 CC genotype than

in incident users with the AA genotype.

[5, 45]

R61C, G401S,

420del, G465R

Investigated the pharmacokinetics of metformin in rela-

tion to genetic variants of OCT1, OCT2, OCT3, OCTN1,

and MATE1 in 103 healthy male Caucasians.

Renal OCT1 expression may be important for the re-

sponse to metformin and other drugs. [66]

R61C, V408M,

M420del, G465R

HEK293 cells expressing a human OCT1 reference or the

variants R61C, V408M, M420del, and G465R were used

to study the kinetics and inhibition patterns of different

OCT1 substrates.

The M420del and R61C variants were more sensitive to

drug inhibition, with IC(50) values up to 23 times lower

than those of the OCT1 reference.

[13]

R61C

(rs12208357)

Systematically investigated genetic and non-genetic

factors of OCT1/SLC22A1 and OCT3/SLC22A3 expres-

sion in liver tissue samples from 150 Caucasian subjects.

The OCT1-R61C variant (rs12208357) was strongly

correlated with decreased OCT1 protein expression. [11]

–43T>G;

V408M

(1222A>G)

Analyzed variants of OCT1 and OCT2 in 33 patients (24

responders and nine non-responders).

OCT1 mRNA levels tended to be lower in human livers

with the 408Met (1222A) variant, but the differences were

not significant.

[23a]

M420del

Seven nonsynonymous polymorphisms in OCT1 were

identified and tested for the effects of metformin on glu-

cose tolerance.

Genetic variation of OCT1 contributes to variation in the

response to metformin. [17b]

Oct1(-/-)

Oct1(+/+)

Tissue distribution of metformin was determined in Oct1

knockout and wild-type mice.

The distribution of metformin in the liver tissue of Oct1(-/-)

mice is more than 30 times lower than that in wild-type mice. [7b]

R61C, G401S,

420del, G465R

Assessed the pharmacokinetic variability of OCT1 vari-

ants by comparing healthy subjects and T2D patients.

There was no effect on the pharmacokinetics of metformin in

patients carrying the reduced-function OCT1 allele. [67]


Two independent studies found that two polymorphisms in SLC22A1, -43T>G in intron 1 and 408Met>Val (1222 A>G) in exon 7, were negative and positive predictors, respectively, of the efficacy of metformin [23]. Because metformin is not the only drug transported by OCT1, these genetic variants of OCT1 may also affect the response to other drugs. Two genetic variants of OCT1 identified in a Korean population, P283L and P341L, were analyzed using the oocyte expression model and found to decrease lami-vudine uptake by 85.1% and 48.7%, respectively, compared to wild-type OCT1 [24]. However, the OCT1 genetic polymorphisms had different effects on the uptake of various substrates (including MPP+, TEA, metformin, and lamivudine), suggesting that the up-take of drugs by OCT1 is substrate dependent.

A number of functional studies have established that many OCT1 genetic polymorphisms, particularly those in the coding re-gion, decrease OCT1 function and, consequently, metformin uptake efficiency. For example, as summarized in (Table 1), the C88R, S189K (rs45607934), G220V (rs45447195), G401S (rs45512393), G465R (rs45476695), and M420del (rs45545341, rs45465102, and rs45542538) variants reduce metformin uptake, whereas Ser14Phe (rs45504100) increases uptake [17b, 25].

3.2. OCT2


OCT2 is predominantly expressed in the proximal tubules of the kidney and mediates the renal secretion of small organic cations, such as metformin [26]. It is also present in the small intes-tine, lungs, skin, placenta, brain, and choroid plexus [27]. OCT2 localizes to the basolateral membrane of epithelial cells and the luminal membrane of epithelial cells in the trachea and bronchi [27a, 28]. OCT2 is a crucial renal uptake transporter that plays a key role in the plasma disposition and renal clearance of drugs and endogenous compounds [29]. In the basolateral membrane of the distal tubule in the kidney, OCT2 promotes the uptake of organic cations from the blood to the proximal tubular cells during renal secretion [30]. Thus, like OCT1, OCT2 can also transport many organic cations and plays a critical role in the pharmacological, pharmacokinetic, and toxicological properties of therapeutic agents. In this regard, altering the expression or transporter activity of OCT2 may alter the responses to a drug. Several reports have shown that T2D patients with genetic variations in OCT2 exhibit different responses to metformin.


In a murine experiment, the kidney and circulating metformin levels were found to be comparable in Oct1

–/– and control mice

[17b], suggesting that OCT2 rather than OCT1 may be the major metformin transporter and determinant of renal metformin process-ing [12]. A study of 23 healthy volunteers, including 14 individuals homozygous for the OCT2 reference allele (808G/G) and nine indi-viduals heterozygous for a variant allele (808G>T) resulting in amino acid alteration A270S, was performed to analyze the re-sponse to metformin [26]. The metformin concentrations measured in the plasma and urine indicated that OCT2-808T had a greater capacity than the reference protein for metformin transport, sug-gesting that genetic variation in OCT2 plays an important role in the CL(R) and secretion (SrCL(R)) of metformin in healthy volun-teers [26]. By assessing homozygosity for the OCT2-808T trypto-phan variant, Song, et al. confirmed gene dosage effects of the transporter activity and the high linear association with the pharma-cokinetic parameters of metformin [31].

A study by Wang et al. was the first to investigate genetic po-lymorphisms of OCT2 in a Chinese population and revealed that the 808G>T polymorphism is associated with a reduction in met-formin renal or tubular clearance [32]. Moreover, the inhibition of metformin renal tubular secretion by cimetidine also appeared to depend on this genetic polymorphism [32]. In addition to the

808G>T variant, two additional genetic variants of OCT2, 596C>T and 602C>T, were also found to yield significant differences in metformin pharmacokinetics; specifically, a higher peak plasma concentration, a greater area under the curve, and reduced renal clearance were observed for the variants compared to wild-type OCT2 [33].

Choi et al. identified several genetic variants of OCT1 and OCT2, including OCT1-P283L and -P341L and OCT2-T199I, -T201M, and -A270S, in a Korean population. Using an in vitro oocyte expression model system, the uptake of 1-methyl-4-phenylpyridinium (MPP+), tetraethyl ammonium (TEA), met-formin, and lamivudine was found to be significantly decreased with the OCT2-T199I, -T201M, and -A270S variants compared to wild-type OCT2 [24]. Using an in vitro model for the renal proxi-mal tubule and LLC-PK1 cells, Song et al. investigated the effects of OCT2-T199I, -T201M, and -A270S [34]. As shown in (Table 2), the finding that these genetic variants decreased the transport activ-ity of metformin is consistent with their contribution to interindi-vidual variation in metformin disposition and the pivotal role of OCT2 in renal excretion, a major component of metformin disposi-tion [34].

3.3. OCT3


The three genes encoding the human cation transporters OCT1, OCT2, and OCT3 are located in a cluster on chromosome 6. OCT3 is encoded by the SLC22A3 gene, which has a broad tissue distribu-tion, including the skeletal muscle, heart, brain, and placenta. Inter-estingly, OCT3 is highly expressed on the membranes of skeletal muscle and liver cells, which are the major target tissues of met-formin [35]. OCT3 is a polyspecific transporter whose transport function is independent of sodium. The known substrates for trans-port by OCT3 include metformin, histamine, serotonin, norepineph-rine, and dopamine. However, the transport capacity and affinity for these substrates may differ between rats and humans [36]. The transport activity of OCT3 can be inhibited by many pharmaceuti-cal drugs, including MDMA, amphetamine, methamphetamine, and cocaine [36a]. Compared to the wealth of research on OCT1 and OCT2 in terms of the pharmacokinetics of metformin, few studies have investigated the role of OCT3 in the response to the drug. However, OCT3 has been identified as an important determinant of the effects of metformin in skeletal muscle [35]. Specifically, the effect of metformin on AMPK phosphorylation was greatly inhib-ited by cimetidine in cultured skeletal muscle cells [37] as well as OCT3 shRNA [35], indicating that OCT3 may play a major role in the therapeutic action of metformin [35]. It is therefore reasonable to hypothesize that genetic variation in OCT3 may also influence the pharmacokinetics of metformin.


Nies, A.T. et al. systematically investigated the genetic and non-genetic factors of OCT1/SLC22A1 and OCT3/SLC22A3 ex-pression in human liver in 150 Caucasian subjects. The group iden-tified four OCT3 variants (rs2292334, rs2048327, rs1810126, and rs3088442) that were associated with reduced OCT3 mRNA levels [11] (Table 1 and Table 4). Using data from the 1,000 Genomes Project and the Pharmacogenomics of Membrane Transporters pro-ject, Chen, L. et al. identified six novel missense variants of OCT3 and tested their transport activity [35]. Three variants, T44M (c.131C>T), T400I (c.1199C>T), and V423F (c.1267G>T), exhib-ited altered substrate specificity. Notably, in cells expressing T400I and V423F, the uptake of metformin and catecholamines was sig-nificantly reduced, while the uptake of metformin, MPP+, and his-tamine increased by more than 50% in cells expressing T44M [35]. It is likely that additional OCT3 SNPs affecting metformin uptake will be identified and that this type of information will help im-prove metformin therapy for T2D patients.


4. MATE

4.1. Physiological and Pharmacological Role of MATEs

Among more than 50 different SLC (solute carrier) families, the family of multidrug and toxin extrusion proteins (MATEs, SLC47A) has gained particular attention because MATE transport-ers use the proton gradient as a driving force for substrate efflux, in contrast to the ABC efflux pumps driven by ATP hydrolysis [38]. MATE proteins act as proton/cation antiporters at the brush border membrane of proximal tubule cells in the kidney and in the ca-nalicular membranes of hepatocytes. Through this activity, they permit the excretion of cationic endogenous substances and xenobi-otics, including clinical drugs such as metformin and cimetidine [39]. The uptake of metformin into the renal epithelial cells from circulation is primarily facilitated by OCTs, but the renal excretion of metformin is mediated primarily by MATE1/SLC47A1 and MATE2-K/SLC47A2 [40]. Thus, MATE1 and MATE2 play impor-tant roles in metformin disposition.

To investigate the roles of MATE1/SLC47A1 and MATE2-K/SLC47A2 in the renal excretion of metformin, Toyama, K. et al. analyzed the effects of heterozygous MATE variants on metformin disposition in both mice and humans. They found that heterozy-gosity for the MATE variants investigated did not influence met-formin disposition in diabetic patients [41]. In another in vivo study, Tsuda, M. et al. reported an essential role of MATE1 in the systemic clearance of metformin. The renal clearance and renal secretory clearance of metformin observed in Mate1 (-/-) mice were approximately 18% and 14% of the wild-type levels, respec-tively [42]. Sixty minutes after metformin administration, the hepatic concentration of metformin was markedly higher in Mate1(-/-) mice than in Mate1(+/+) mice. Furthermore, MATE1 dysfunction elevated the metformin concentration in the liver and

led to lactic acidosis, indicating that homozygosity for the MATE1 variant analyzed may represent a risk factor for metformin-induced lactic acidosis [43].

4.2. Effect of MATE Genetic Variants

Becker et al. investigated the genetic variation of the SLC47A1 gene and its effect on the ability of metformin to lower A1C [44]. As shown in (Table 3), the rs2289669 G>A SNP is associated with reduced A1C levels, which is consistent with reduced MATE1 transporter activity and indicates an important role of the MATE1 transporter in the pharmacokinetics of metformin [44]. Graham et al. found that the MATE1 rs2289669 G>A SNP results in a small increase in the anti-hyperglycemic effect of metformin [5]. Additionally, the effect of the MATE1 rs2289669 polymorphism on the glucose-lowering effect of metformin was greater in incident users with the OCT1 rs622342 CC genotype than in incident users with the AA genotype [45].

Kajiwara, M. et al. sequenced all of the exons of the genes en-coding MATE1 and MATE2-K in 89 Japanese subjects and identi-fied coding SNPs (cSNPs) in MATE1 (V10L, G64D, A310V, D328A, and N474S) and MATE2-K (K64N and G211V) [46]; this report was the first to demonstrate cSNP-induced functional im-pairment of the MATE family. These findings suggest that the loss of transport activity observed in the MATE1 G64D and MATE2-K G211V variants was due to altered protein expression in cell sur-face membranes [46]. Chen, Y. et al. found that two single variants of MATE1, G64D and V480M, resulted in a complete loss of func-tion for all four tested substrates and that three polymorphic vari-ants (allele frequencies greater than or equal to 2%), L125F, V338I, and C497S, significantly altered MATE1 transport activity in a substrate-dependent manner. The authors proposed that nonsyn-onymous variants of MATE1 may alter the drug disposition and

Table 2. Genetic Variation in OCT2 (SLC22A2) and Metformin Sensitivity


808G>T

(A270S)

Assess the effect of genetic variant OCT2-808G>T on the

pharmacokinetics of metformin.

OCT2 genotype was a significant predictor of metformin

CL(R) and SrCL(R). [26]

808G>T Use metabolomics to comprehensively monitor changes in

primary metabolites associated with OCT2 polymorphisms.

Tryptophan can serve as an endogenous substrate of OCT2

as well as a biomarker candidate. [31]

596C>T

602C>T

808G>T

Evaluate the effects of three variations in OCT2 on the

pharmacokinetics of metformin, particularly renal elimina-

tion.

SLC22A2 variants result in reduced metformin CL(R) and

consequently lead to increased plasma concentrations. [33]

808G>T

(A270S)

Address the role of OCT2 808G>T in the renal disposition

of endogenous compounds and drugs other than metformin.

OCT2 808G>T significantly alters the uptake of endogenous

compounds and drugs. [68]

T199I

T201M

A270S

Investigate the effects of genetic variants of OCT1 and

OCT2 on the transport of substrates associated with these

transporters in a Korean population.

The OCT2-T199I, -T201M, and -A270S variants signifi-

cantly decrease the uptake of MPP+, TEA, metformin, and

lamivudine.

[24]

T199I,

T201M

A270S

Investigate the effects of genetic variants of OCT2 on

metformin transport using LLC-PK1 as an in vitro model. Genetic variants of OCT2 (OCT2-T199I, -T201M, and -

A270S) decrease the transport activity of metformin. [34]

808G>T

(A270S)

Direct sequencing of all OCT2 exons and the surrounding

introns was performed using genomic DNA from 112

healthy Chinese participants.

The 808G>T polymorphism is associated with reduced met-

formin renal or tubular clearance. [32]

808G>T

(A270S)

The SLC22A2 808G>T variant was genotyped in 400 T2D

patients with or without metformin treatment, and the

fasting plasma lactic acid levels were measured.

The 808G>T variant of OCT2 can affect the plasma lactate

level and the incidence of hyperlactacidemia in T2DM pa-

tients undergoing metformin therapy.

[69]


ultimately affect the clinical drug response [47]. Two nonsynony-mous variants of MATE2, 485 C>T and 1177 G>A, were found to be associated with significantly reduced metformin uptake and reduced protein expression levels [48]. Diabetic patients homozy-gous for the -130 G>A SNP of the MATE2-K basal promoter had a significantly worse response to metformin treatment, as indicated by the relative change in glycated hemoglobin (HbA1c) compared to the reference allele [48].

Taken together, these findings indicate that genetic variants of both MATE1 and MATE2 influence the excretion and disposition of metformin. The altered expression and function of MATEs may therefore contribute to interindividual variability in the pharma-cokinetics and response to metformin [49].

5. AMPK

5.1. Physiological and Pharmacological Role of AMPK

The enzyme AMPK plays an important role in cellular energy homeostasis. Three subunits ( , , and ) compose the hetero-trimeric AMPK protein, which is a functional enzyme conserved from yeast to humans [50]. Each of these three subunits has a spe-cific role in both the stability and activity of AMPK. The , , and subunits are encoded by PRKAA1 and PRKAA2; PRKAB1 and PRKAB2; and PRKAG1, PRKAG2, and PRKAG3, respectively [51]. AMPK is expressed in a number of tissues, including the liver, brain, and skeletal muscle. AMPK activation promotes the oxida-tion of hepatic fatty acids and inhibits the lipolysis and lipogenesis of adipocytes and the synthesis of cholesterol. More importantly, AMPK can stimulate skeletal muscle fatty acid oxidation, muscle

glucose uptake, and insulin secretion by pancreatic beta-cells. Thus, AMPK acts as a metabolic master switch regulating several intra-cellular systems, including the cellular uptake of glucose and the -oxidation of fatty acids [52].

The energy-sensing capability of AMPK reflects its ability to detect and react to fluctuations in the AMP:ATP ratio during rest and energy stress conditions. Under starvation or muscle stimula-tion, AMP increases while ATP decreases; moreover, the binding of AMP renders AMPK a good substrate for activation via an up-stream AMPKK kinase complex, such as liver kinase B1 (LKB1), which phosphorylates AMPK at the Thr-172 site [53]. AMPK activity increases when muscle cells experience metabolic stress brought about by an extreme cellular demand for ATP. AMPK activation affects many pathways, generally resulting in ATP con-servation and production [54]. Upon activation, AMPK increases cellular energy levels by inhibiting the energy-consuming anabolic pathways (e.g., fatty acid synthesis and protein synthesis) and stimulating energy-producing catabolic pathways (e.g., fatty acid oxidation and glucose transport).

Notably, recent research has established that metformin can stimulate AMPK activation in the liver and skeletal muscles [55], which in turn leads to reduced glucose production in the liver, in-creased glycogen synthesis, and lower insulin resistance in the muscle [2, 55]. In isolated hepatocytes, the action of metformin largely requires the enzymatic activity of AMPK, a master sensor and regulator of cell energy homeostasis [55a]. Thus, the genes that encode the various AMPK subunits are intriguing candidates for the hereditary basis of T2D [56].

Table 3. Genetic Variation in MATE1 (SLC47A1) and Metformin Sensitivity


rs2289669 G>A Studied the effect of SNPs in SLC47A1 on the A1C-

lowering effect of metformin. Reduced MATE1 transporter activity. [44, 45]

404T>C 1012G>A

Assessed the cellular accumulation effect of shared

substrates using OCT2 and MATE1 double-

transfected cells.

Altered the renal cationic drug elimination activity of

MATE1. [70]

G64D

V480M

L125F

V338I

C497S

A population-based cohort study of 272 individuals

(68 Caucasians, 68 African Americans, 68 Asian

Americans, and 68 Mexican Americans). G64D and V480M fully eliminated transport function,

while L125F, V338I, and C497S significantly altered

transport capability.

[47]

G>A, SNP rs2289669 Analyze the renal clearance and clinical effect of

metformin in diabetes patients with MATE1 variants.

Associated with a small increase in the anti-

hyperglycemic effect of metformin. [5]

MATE1 (V10L, G64D,

A310V, D328A, and

N474S), MATE2-K

(K64N and G211V)

Sequenced all exons of MATE1 and MATE2-K in 89

Japanese subjects and identified coding SNPs

(cSNPs) in MATE1 (V10L, G64D, A310V, D328A,

and N474S) and MATE2-K (K64N and G211V).

The MATE1 G64D and MATE2-K G211V variants

exhibit a loss of transport activity resulting from altered

protein expression in cell surface membranes.

[46]

Mate1 knockout

Assess the concentration of metformin in Mate1

knockout (-/-), heterozygous (+/-), and wild-type

(+/+) mice.

The hepatic concentration of metformin was markedly

higher in Mate1(-/-) mice than in Mate1(+/+) mice. [43]

Heterozygous MATE

variants

Evaluate the effects of heterozygous MATE variants

on the disposition of metformin in mice and humans.

Heterozygous MATE variants did not influence the dis-

position of metformin in diabetic patients. [41]

Mate1(-/-) mice and

Mate1(+/+) mice

Analyze the renal clearance and renal secretory clearance

of metformin in Mate1(-/-) and wild-type mice.

The renal clearance and renal secretory clearance levels

of metformin in Mate1(-/-) mice were approximately

18% and 14% of those in Mate1(+/+) mice, respectively.

[42]


Table 4. Genetic Variation in Other Genes and Drug Sensitivity


OCT3

131C>T (T44M)

1199C>T (T400I)

1267G>T (V423F)

Determine the role of OCT3 in the pharmacologi-

cal action of metformin; identify and functionally

characterize genetic variants of OCT3 in terms of

the uptake of metformin and monoamines.

The uptake of metformin and catecholamines was signifi-

cantly reduced in cells expressing T400I and V423F, while

a significant increase in metformin uptake was observed in

the T44M group.

[35]

MATE2-K

(SLC47A2)

Assess the impact of MATE2-K genetic variants

on the metformin response.

Patients with diabetes who were homozygous for -130

G>A had a significantly worse response to metformin

treatment.

[48]

PPARG P12A

(a target of thiazolidin-

edione medications)

Examine whether PPARG P12A affects the pro-

gression from impaired glucose tolerance to dia-

betes.

PPARG P12A increases the risk of diabetes in individuals

with impaired glucose tolerance. [71]

PPARG and PPARA

T2D patients with PPARA and PPARG variants

were randomized for 26-week monotherapy regi-

mens with the dual-acting PPAR alpha/gamma

agonist ragaglitazar.

PPARG P12A may be a useful tool for reducing the risk of

PPARG agonist-induced fluid retention and edema in T2D

patients.

[72]

PRKAG2

Analyze the association between 1,590 SNPs and

incident diabetes and the response to metformin

or lifestyle interventions in 2,994 DPP partici-

pants.

The most significant association with diabetes incidence

was observed for the AMPK subunit gene PRKAG2. [57]

KCNJ11 E23K

Examine the effect of sulfonylurea treatment on

glycemic control with respect to the KCNJ11

E23K variant.

Carriers of the KCNJ11 K-allele have better therapeutic

responses to gliclazide. [73]

STK11 (also known as

LKB1; C/C, C/G, and

G/G genotypes)

A total of 312 women with PCOS were included

in the study to identify predictive genetic poly-

morphisms and other determinants of the ovula-

tory response.

A polymorphism in the STK11 gene was associated with a

significantly decreased probability of ovulation in women

with PCOS receiving metformin.

[58]

TCF7L2 rs12255372

and rs7903146

A total of 901 incident sulfonylurea users and 945

metformin users were examined to determine the

effect of the TCF7L2 rs12255372 and rs7903146

genotypes on the glycemic response.

TCF7L2 variants influence the therapeutic response to

sulfonylureas but not the response to metformin. [74]

KCNQ1 rs163184

(T>G)

KCNQ1 genotypes and the effect of 6-month

sulfonylurea therapy in addition to metformin on

glycemic control were evaluated in 87 patients

with T2D.

The FPG response to sulfonylurea was significantly lower

in carriers of the risk-associated GG genotype of KCNQ1

rs163184.

[60]

PRKAA2, PRKAB1,

and PRKAB2

Assess the impact of common variants of the

genes encoding three AMPK subunits on T2D

symptoms and related phenotypes.

An analysis of single-marker and multi-marker tests re-

vealed no associations with T2D, fasting plasma glucose,

or insulin sensitivity.

[56]

OCT3

rs2292334, rs2048327,

rs1810126, rs3088442

Systematically investigated genetic and non-

genetic factors of OCT1/SLC22A1 and

OCT3/SLC22A3 expression in human liver.

Four OCT3 variants (rs2292334, rs2048327, rs1810126,

and rs3088442) were associated with reduced OCT3

mRNA levels.

[11]

OCT1 (P283L and

P341L)

OCT2 (T199I, T201M,

and A270S)

Investigate the effect of genetic variants of OCT1

and OCT2 identified in a Korean population on

lamivudine transport.

The effect of genetic variation in OCT1 and OCT2 on the

uptake of MPP+, TEA, metformin, and lamivudine was

substrate dependent.

[24]

OCT1, OCT2, MATE1,

MATE 2, and PMAT

Evaluate the effect of genetic variation in OCT1,

OCT2, MATE1, MATE 2, and PMAT on the

trough steady-state plasma concentration of met-

formin and hemoglobin A1c (Hb1Ac).

OCT1 activity affects metformin steady-state pharmacoki-

netics, and a patient’s OCT1 genotype influences HbA1c

levels during metformin treatment.

[75]


Table (4) contd……


c.404T>C (p.159T>M);

c.1012G>A

(p.338V>A)

Investigate the interplay between the renal cati-

onic transporters OCT2 and MATE1 and perform

a functional assessment of the genetic variation in

human MATE1.

The coordinate functions of MATE1 and OCT2 likely

contribute to the vectorial renal elimination of organic

cationic drugs.

[70]

FTO rs9939609; IN-

SIG2 rs7566605

FTO SNP rs9939609 and INSIG2 SNP rs7566605

were tested for genotype-treatment interactions in

terms of changes in obesity-related traits in the

DPP.

FTO and INSIG2 are nominally associated with quantita-

tive measures of obesity; the direct association may result

from metformin interaction or lifestyle intervention.

[61]

STK11 rs8111699

Studied the effects of STK11 rs8111699 on endo-

crine-metabolic and body composition indexes

before and after 1 year of metformin treatment in

85 hyperinsulinemic girls with androgen excess.

The STK11 rs8111699 SNP influences insulin sensitivity

and metformin efficacy in hyperinsulinemic girls with

androgen excess.

[59]

Ataxia telangiectasia

mutated (ATM)

rs11212617

Analyze the glycemic response to metformin and

the rs11212617 SNP at a locus that includes the

ataxia telangiectasia mutated (ATM) gene in

multiple additional populations.

A gene variant of ATM is significantly associated with

response to metformin treatment in T2D patients from the

Netherlands and the UK.

[63]

Ataxia telangiectasia

mutated (ATM)

rs11212617

A genome-wide association study for glycemic

response to metformin in 1,024 Scottish individu-

als with T2D; two replicate cohorts included

1,783 Scottish individuals and 1,113 individuals

from the UK Prospective Diabetes Study.

ATM plays a role in the effect of metformin upstream of

AMP-activated protein kinase, and variation in ATM af-

fects the glycemic response to metformin.

[64]

GCKR SNP 446L

allele

Genotyped two GCKR SNPs in 3,346 DPP par-

ticipants and evaluated the association between

these SNPs and the progression to diabetes.

The GCKR SNP P446 allele appears to enhance respon-

siveness to the homeostasis model assessment of the insu-

lin resistance (HOMA-IR)-lowering effect of metformin.

[76]

5.2. Effect of AMPK Genetic Variants

Based on previously reported functional studies, expression

patterns, genetic linkage, and pharmacological evidence, Sun. et al.

selected PRKAA2, PRKAB1, and PRKAB2 from the seven iso-

forms encoding AMPK because of their higher likelihood of an

association with T2D. After correcting for the testing of multiple hypotheses by permutation, the group found that the nominal P

values of 0.05 for rs2393550 in PRKAB1 and 0.04 for test 38 in

PRKAB2 no longer indicated statistical significance [56] (Table 4).

BMI (body mass index) comparisons across genotypic groups re-

vealed nominal P values less than 0.05 for several tests in PRKAA2

and PRKAB1, but after correction by permutation testing, the best

results did not retain empirical statistical significance [56]. Using

previous genome-wide association studies (GWASs), Jablonski et

al. analyzed the association between 1,590 SNPs and the incidence

of diabetes and the response to metformin or lifestyle interventions

in 2,994 Diabetes Prevention Program (DPP) participants. The

study confirmed the association of variants of the metformin trans-porter gene SLC47A1 with metformin response and detected nomi-

nal interactions with the AMPK gene STK11, the AMPK subunit

genes PRKAA1 and PRKAA2, and a missense SNP in SLC22A1,

which encodes another metformin transporter. The most significant

association with diabetes incidence was observed for the AMPK

subunit gene PRKAG2 [57]. However, these results need to be con-

firmed by other independent studies.

6. OTHER DETERMINANTS OF METFORMIN RESPONSE

In addition to PMAT, OCTs, MATEs, and AMPK, many other

genetic variants affect the pharmacokinetics and pharmacodynam-ics of metformin. Metformin is used to induce ovulation in women

with polycystic ovary syndrome (PCOS). However, the ovulatory

response is variable, and the underlying cause of this variation is

poorly understood. In an analysis of metformin-treated subjects in a

prospective randomized trial, Legro, R.S. et al. showed that a

polymorphism in STK11 (also called LKB1), a kinase expressed in the liver and implicated in metformin action, is associated with the

ovulatory response to metformin treatment [58]. However, this

association was not found in the other two study groups analyzed,

suggesting that the mechanism may have reflected drug-drug inter-

actions in the combined group rather than metformin metabolism

[58]. Because the serine-threonine kinase STK11 catalyzes the

AMP-activated protein kinase complex, genetic variants of STK11

may also contribute to variations in insulin sensitivity and met-

formin efficacy. In hyperinsulinemic girls with androgen excess,

the STK11 rs8111699 SNP influences insulin sensitivity and met-

formin efficacy [59]. Relative to the baseline, the mutated G allele

in STK11 rs8111699 resulted in higher insulin and IGF-I levels. STK11 GG homozygotes had an improved and robust metabolic

metformin response, while CC homozygotes exhibited almost no

response. Thus, the girls with the least favorable endocrine meta-

bolic profile exhibited the most improvement with metformin ther-

apy [59].

To identify factors predictive of the response to sulfonylurea treatment, Schroner, Z. et al. analyzed KCNQ1 genotypes (KCNQ1 rs163184 (T>G)) and the quantitative effects of treatment with sul-fonylurea in addition to metformin on glycemic control parameters (Table 4). The results suggest that the magnitude of fasting plasma glucose (FPG) reduction after 6 months of sulfonylurea treatment in addition to metformin in T2D patients was affected by variation in KCNQ1 [60]. Specifically, the FPG response to sulfonylurea was significantly lower in carriers of the higher-risk GG genotype [60].


Metformin was also used to prevent the development of T2D. In another study, Franks et al. found that the minor A allele at rs9939609 of the fat mass and obesity associated gene (FTO) was positively associated with baseline BMI but not with baseline adi-posity. For the rs7566605 genotype of insulin-induced gene 2 (IN-SIG2), the minor C allele was associated with greater subcutaneous adiposity [61]. During the follow-up period, CC homozygotes of INSIG2 rs7566605 lost more weight than G allele carriers. Within the DPP study population, common variants in FTO and INSIG2 were nominally associated with quantitative measures of obesity, possibly reflecting direct metformin interaction or lifestyle inter-vention [61].

Ataxia telangiectasia mutated (ATM) is a serine/threonine pro-tein kinase that is recruited and activated by DNA double-strand

breaks. ATM phosphorylates several key proteins that initiate the activation of the DNA damage checkpoint leading to cell cycle

arrest and DNA repair or apoptosis [62]. Notably, in a combined meta-analysis, Zhou, K. et al. observed that the ATM SNP

rs11212617 is associated with metformin treatment success [63] (Table 4). Furthermore, the inhibition of ATM with KU-55933

attenuated the phosphorylation and activation of AMPK in response to metformin. Thus, ATM may contribute to the effects of met-

formin upstream of AMP-activated protein kinase, and the available evidence indicates that variation in this gene alters the glycemic

response to metformin [64]. In a meta-analysis of three cohorts analyzed separately or combined with previously published cohorts,

rs11212617 was significantly associated with metformin treatment response in T2D patients from the Netherlands and the UK [63].

This was the first robustly replicated common susceptibility locus to be associated with metformin treatment response.

7. PERSPECTIVE

Metformin is now believed to be the most widely prescribed an-tidiabetic drug in the world. Accordingly, it has become increasingly

urgent to improve the safety and efficiency of metformin treatment. In recent decades, considerable advances have been made in our

knowledge of metformin disposition and action. As one example, numerous genes that influence the pharmacogenetics of metformin

have been discovered. It is well established that the PMAT, OCT, and MATE membrane transporters regulate metformin transport and ex-

cretion. Additionally, the pharmacological effect of metformin is heavily dependent on AMPK (Fig. 1). There is a great deal of evi-

dence indicating that genetic variation in these transporters and AMPK affects the response to metformin. With additional advances

in pharmacogenetics, we will continue to learn more about the relationship between genetic variation affecting critical proteins (such

as transporters and kinases) and the PK/PD of metformin. The ongoing development of personalized therapy also requires increased

investigation of pharmacogenetic correlations and more detailed knowledge of the underlying mechanisms, which can subsequently be

used to adjust the prescribed dose of metformin. By ultimately improving metformin treatment, additional pharmacogenetic informa-

tion will make it easier for T2D patients to cope with this disease. However, it is important to be mindful that more SNPs related to

metformin pharmacokinetics have yet to be identified and that further research in this field is required to meet these goals.

Fig. (1). Key transporters and proteins putatively involved in the absorption, distribution, biological function, and excretion of metformin.

The absorption of metformin from intestinal epithelial cells into the blood may involve PMAT and OCT1. Metformin is subsequently transported into hepato-

cytes and myocytes via OCT1 and OCT3. The biological function of metformin is primarily dependent on the activation of the LKB1/AMPK pathway, which

inhibits hepatic gluconeogenesis and increases glucose uptake. The therapeutic response to metformin is also affected by other molecules, including GCKR,

ATM, INSIG2, KCNQ1, and PPARG. Finally, metformin is secreted in the urine via transport mediated by OCT2, MATE1, and MATE2-K.


CONFLICT OF INTEREST

The authors confirm that this article content has no conflicts of interest.

ACKNOWLEDGEMENTS

This work was supported by grants from the National Natural Science Foundation of China (No. 81202091,81202085,81173514 and 81001673) and Key Technologies for New Drug Innovation and Development of China (No.2012ZXJ09303011 and No.2012BAK25B00). We also acknowledge the assistance of Ms. Jingyuan Wang in drawing the summary figure of metformin trans-portation and secretion.

AMPK = AMP-activated protein kinase

ATM = Ataxia telangiectasia mutated

CL/F = Apparent total clearance

CL(R) = Renal clearance

Cmax = Maximal plasma concentration

DPP = Diabetes Prevention Program

GCKR = Glucokinase regulatory protein

INSIG2 = Insulin-induced gene 2

LKB1 = Liver kinase B1

MATE = Multidrug and toxin extrusion transporters

OCTs = Organic cation transporters

PMAT = Plasma membrane monoamine transporter

PPARG = Peroxisome proliferator-activated receptor gamma

SLC = Solute carrier

T2D = Type 2 diabetes

V/F = Lower oral volume of distribution

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Received: August 22, 2013 Revised: November 22, 2013 Accepted: December 1, 2013

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