1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

An important function of hepatocytes is the biotransformation and elimination of various drugs, many of which are organic cations and are taken up by organic cation transporters (OCTs) of the solute carrier family 22 (SLC22). Because interindividual variability of OCT expression may affect response to cationic drugs such as metformin, we systematically investigated genetic and nongenetic factors of OCT1/SLC22A1 and OCT3/SLC22A3 expression in human liver. OCT1 and OCT3 expression (messenger RNA [mRNA], protein) was analyzed in liver tissue samples from 150 Caucasian subjects. Hepatic OCTs were localized by way of immunofluorescence microscopy. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and genome-wide single-nucleotide polymorphism microarray technology served to genotype 92 variants in the SLC22A1-A3/OCT1-3 gene cluster. Transport of metformin by recombinant human OCT1 and OCT3 was compared using transfected cells. OCT1 mRNA and protein expression varied 113- and 83-fold, respectively; OCT3 mRNA expression varied 27-fold. OCT1 transcript levels were on average 15-fold higher compared with OCT3. We localized the OCT3 protein to the basolateral hepatocyte membrane and identified metformin as an OCT3 substrate. OCT1 and OCT3 expression are independent of age and sex but were significantly reduced in liver donors diagnosed as cholestatic (P ≤ 0.01). Several haplotypes for OCT1 and OCT3 were identified. Multivariate analysis adjusted for multiple testing showed that only the OCT1-Arg61Cys variant (rs12208357) strongly correlated with decreased OCT1 protein expression (P < 0.0001), and four variants in OCT3 (rs2292334, rs2048327, rs1810126, rs3088442) were associated with reduced OCT3 mRNA levels (P = 0.03). Conclusion: We identified cholestasis and genetic variants as critical determinants for considerable interindividual variability of hepatic OCT1 and OCT3 expression. This indicates consequences for hepatic elimination of and response to OCT substrates such as metformin. (HEPATOLOGY 2009.)

Hepatic drug metabolism and elimination requires hepatocellular drug uptake that is decisively determined by transporters in the sinusoidal (basolateral) hepatocyte membrane.1–3 These membrane transporters also crucially contribute to drug delivery and response when hepatocytes are the pharmacological target cells. Variable transporter expression may contribute to interindividual variation in response to certain drugs. For a better understanding of drug response, it is therefore important to recognize and identify genetic as well as nongenetic (physiological and pathophysiological) factors affecting transporter expression.

At physiological pH, approximately 40% of drugs are organic cations or weak bases.5 Their cellular uptake may be mediated by organic cation transporters (OCTs) that belong to the solute carrier family 22 (SLC22).2, 6 In human liver, only OCT1 (SLC22A1)7–9 and OCT3 (SLC22A3)10, 11 transcripts are present, whereas OCT2 is primarily expressed in kidney and neither OCT2 (SLC22A2) messenger RNA (mRNA)7, 12 nor OCT2 protein13 are detectable in liver. OCT1 is localized in the sinusoidal membrane of rat as well as human hepatocytes.13, 14 The subcellular localization of OCT3 has not been described so far.

OCTs transport a variety of structurally diverse lipophilic organic cations of endogenous or xenobiotic origin; OCT-mediated transport is electrogenic, independent of a Na+ ion or proton gradient, and may occur in either direction across the plasma membrane.2, 15 Contrary to a multitude of endogenous and xenobiotic substances that inhibit OCT-mediated transport without being transported themselves,2, 15, 16 the number of proven OCT transport substrates is limited. In addition to prototypic cations (such as tetraethylammonium and 1-methyl-4-phenylpyridinium)2, 15 and endogenous substances (such as acetylcholine [an OCT1 substrate]17 and catecholamines [OCT3 substrates]),10, 17 several drugs have been identified as OCT substrates, and their number is increasing. Supporting Table 1 lists all currently known OCT1/OCT3 drug substrates. OCT1 substrates include antiviral drugs18–20 and the antidiabetic drug metformin.21 The anticancer drug oxaliplatin,22, 23 the histamine H2 receptor antagonist cimetidine,24, 25 and the antiviral drug lamivudine19, 20 are substrates for both OCT1 and OCT3. Notably, hepatocytes are the pharmacological target cells of lamivudine, when it is used to treat chronic hepatitis B,26 and of metformin.27

Table 1. Multivariate Analysis of Hepatic OCT1 and OCT3 Expression in Relation to Nongenetic Factors
 P Value
Nongenetic factorOCT1 mRNAOCT1 ProteinOCT3 mRNA
  1. Boldface indicates significant P value.

Presurgery medication0.780.550.09
Smoking habit0.080.130.19
Alcohol consumption0.160.460.33

The impact of an altered OCT1-mediated drug transport on pharmacokinetics can be exemplified by metformin. In Oct1+/+ mice, the liver concentration of metformin was approximately 30 times higher than in Oct1−/− mice;28 moreover, the blood glucose-lowering effect of metformin was completely abolished in Oct1−/− mice.29 In humans, several OCT1 variants with reduced transport function, including metformin transport, have been identified.29–32 Some of these variants were recently associated with a significantly decreased glucose-lowering response to metformin and altered metformin pharmacokinetics in healthy volunteers.29, 33 However, in another study, the prevalence of OCT1 variants did not differ between responders and nonresponders to metformin,34 which may be due to different ethnic study populations or to a small number of subjects in the latter study. However, factors other than genetics may contribute to pharmacokinetic variability.

Because interindividual variability of OCT1 and OCT3 expression may affect intrahepatic and systemic concentrations of several drugs (Supporting Table 1), it is of particular interest to identify factors influencing OCT expression in human liver. We therefore systematically analyzed in a large set of well-characterized human liver samples the variability of OCT1 and OCT3 expression in correlation with nongenetic factors, such as age, sex, and pathophysiological conditions, and with variants in both genes.

Patients and Methods

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

See the Supporting Material for detailed descriptions.

Human Liver and Blood Samples.

Liver tissue and corresponding blood samples were previously collected from patients undergoing liver surgery at the Department of General, Visceral, and Transplantation Surgery (A. K.Nuessler, P. Neuhaus, Campus Virchow, University Medical Center Charité, Humboldt University, Berlin, Germany).35 Liver samples were immediately shock-frozen and stored at −80°C. All tissue samples had been examined by a pathologist, and only histologically normal liver tissue was used for further studies. For each patient, detailed information was available regarding age, sex, smoking status, alcohol consumption, presurgery medication, indication for liver resection, and presurgery liver serum parameters. Samples from patients with hepatitis, cirrhosis, or chronic alcohol use were excluded. A total of 150 liver samples from which high quality RNA and complete documentation could be obtained were finally included (Supporting Tables 2 and 3). The study was approved by the local ethics committee following the principles of the Declaration of Helsinki. Written informed consent was obtained from each patient.

Selection of OCT Variants and Genotyping Strategies.

Selection of OCT1 and OCT3 variants for genotyping was based on two strategies. All variants associated with functional consequences proven by in vitro/in vivo data29–32, 36, 37 were included as well as variants in the 5′ and 3′ regions of the OCT1 and OCT3 genes that were available in the National Center for Biotechnology Information database (dbSNP build 127; Additionally, all variants covering the SLC22A1-A3/OCT1-3 gene cluster at chromosome 6 of the HumanHap300v1.1 chip (Illumina, San Diego, CA) were included.

Genomic DNA was isolated from ethylene diamine tetraacetic acid blood samples using the QIAmp DNA Blood Mini Kit System (Qiagen, Hilden, Germany). Genotyping was performed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) using the MassARRAY Compact system (Sequenom, San Diego, CA).38 Chip analysis was performed using the HumanHap300v1.1 chip by the Microarray facility of the University of Tübingen. Details of primers and genotyping assays are available upon request. Approximately 10% of samples within each assay were retyped as a quality control. Laboratory staff was blinded to case status of the study participants during the entire genotyping process.

RNA Isolation and Quantification.

High-quality total RNA (RNA integrity number >7) was isolated from human liver samples, and 1 μg of total RNA was reverse-transcribed as described.35 OCT1/OCT3 mRNAs were quantified by real-time quantitative polymerase chain reaction using the 5′-nuclease assay and the ABI Prism 7500 Sequence Detection System (Applied Biosystems, Foster City, CA). Oligonucleotide primers and TaqMan probes are given in Supporting Table 4.

For expression profiling of OCTs, commercial arrays comprising complementary DNAs (cDNAs) from 48 human tissues normalized to glyceraldehyde-3-phosphate dehydrogenase were used (TissueScan real-time quantitative polymerase chain reaction array, Origene Technologies, Rockville, MD).

Detection of OCT1 Splice Variants.

Two OCT1 variants have been cloned from human liver cDNA, a 1665-bp and predominant transcript, i.e. variant 1 (National Center for Biotechnology Information accession number NM_003057) encoding the functional OCT1 protein (NP_003048), and a 1521-bp transcript, i.e. variant 2 (NM_153187) encoding a nonfunctional protein with a distinct carboxy terminus.9 A polymerase chain reaction primer pair was designed for the simultaneous detection of both transcripts (Supporting Material).


The polyclonal antiserum CGR was raised in rabbits against a synthetic peptide corresponding to the carboxy-terminal sequence of human OCT3 (CGRNKKTPVSRSHL; NP_068812). The synthetic peptide was coupled via an additional amino-terminal cysteine to keyhole limpet hemocyanin (Peptide Specialty Laboratories, Heidelberg, Germany). Additionally, a polyclonal goat antiserum (C-14, Santa Cruz Biotechnology, Santa Cruz, CA) was used for OCT3 detection. (For further antibodies, see the Supporting Material.)

Immunofluorescence Microscopy of Tissue Samples and Cells.

Localization of OCTs in human liver samples and transfected cells was analyzed by way of immunofluorescence confocal laser scanning microscopy (see Supporting Material).

Immunoblot Analyses and Quantification of OCT1 Protein in Human Liver Samples.

Immunoblot analyses were performed to detect OCT1 and OCT3 proteins in membrane fractions from transfected cells and from human liver tissue as detailed in the Supporting Material. The OCT1-specific KEN antiserum13 was used for quantification of OCT1 protein in human liver (see Supporting Material).

Haplotype and Linkage Disequilibrium Analysis.

Observed and expected allele and genotype frequencies within the study population were compared by means of Hardy-Weinberg equilibrium calculations.39, 40OCT1 and OCT3 haplotypes of the study population were calculated with the PHASE program version 2.1.1,41 first using all respective variable sites. In subsequent separate analyses, the intronic sites were excluded. Analyses were run seven times, and haplotypes with a frequency >1% estimated in seven out of seven runs are given.

Linkage disequilibrium (LD) analysis of the OCT1-3 gene cluster was performed with Haploview39 using either results from the study population of 150 Caucasian subjects or the publicly available HapMap data (

Transport Studies.

Transport of metformin by OCT1 and OCT3 and inhibition of uptake of 1-methyl-4-phenylpyridinium (MPP) was measured in Chinese hamster ovary cells (cell line CHO-K1) that were stably transfected with OCT1 or OCT3 (see Supporting Material).

Computational Structural Analyses.

Secondary mRNA structure was predicted with MFold ( Prediction of functional effects of nonsynonymous variants was calculated with PolyPhen ( and SIFT (Sorting Intolerant from Tolerant) version 2 ( (For further details, see Supporting Material.)


Multivariate statistical analyses were performed with the statistics software package R version 2.6.2 ( For each genetic variant, a log-linear regression model (codominant model) and analysis of variance were applied to assess its effect on OCT expression. These effects were corrected for the nongenetic factors age, sex, cholestasis, smoking habit, alcohol consumption, and presurgery medication. Resulting analysis of variance P values for each genetic variant were adjusted for multiple testing according to Holm.43 Log-linear regression models and analysis of variance were also used in order to estimate effects of the six nongenetic factors alone on OCT expression, and in combination with the OCT1 or OCT3 haplotypes. Statistical significance was defined as P < 0.05. (For further statistical methods, see Supporting Material.)


  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information


Histologically normal liver tissue together with complete presurgery serum liver parameters was obtained from 150 Caucasian subjects undergoing partial hepatectomy because of different indications (Supporting Tables 2 and 3). Presurgery medication, usually as part of combination therapy, included proton pump inhibitors (23 patients), β-adrenoreceptor antagonists (21 patients), angiotensin-converting enzyme inhibitors (18 patients), diuretics (18 patients), Ca2+ channel antagonists (17 patients), H2 receptor antagonists (16 patients), nonsteroidal anti-inflammatory drugs (12 patients), and benzodiazepines (11 patients). Twenty-four patients had cholestatic liver injury according to published criteria.44

OCT1 and OCT3 mRNA Expression Profiling in Human Tissues.

A comprehensive analysis using glyceraldehyde-3-phosphate dehydrogenase–normalized cDNAs from 48 human tissues revealed that OCT1 mRNA is most prominently expressed in liver (Fig. 1A). Other tissues with much lower but considerable OCT1 mRNA expression are adrenal gland and lung. OCT3 transcripts were detectable in a variety of human tissues, with the highest amount in the adrenal gland (Fig. 2A). Other tissues with appreciable OCT3 mRNA levels include the uterus, prostate, liver, and lung. The ratio of hepatic OCT1/OCT3 mRNA levels was 32.

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Figure 1. OCT1 expression in different (A) human tissues and (B-F) liver samples. OCT1 mRNA (NM_003057) was quantified by way of TaqMan technology (A, B). OCT1 protein expression was analyzed by way of immunoblotting (C, E) and confocal laser scanning microscopy (D) using the KEN antiserum.13 (A) OCT1 mRNA quantification in 48 human tissues (cDNA array) relative to the hepatic expression. (B) Histogram in combination with a normal probability plot (right axis) of OCT1 mRNA quantification in 150 human liver samples. (C) Immunoblot analysis of 10 μg of membrane fractions from vector-transfected Madin-Darby canine kidney (MDCK) cells (Co), MDCK-OCT1, MDCK-OCT2, CHO-OCT3 transfectants, and 50 μg from liver samples and detection of OCT1 at ≈70 kDa. As shown before,13 the KEN antiserum detects two bands in OCT1-expressing MDCK cells, the band of ≈70 kDa corresponding to glycosylated OCT1 and the band at ≈50 kDa to the unglycosylated protein. (D) Double-label immunofluorescence analysis to detect OCT1 (green) in the sinusoidal and MRP2 (red) in the canalicular hepatocyte membrane. Bar, 10 μm. (E) Histogram in combination with a normal probability plot (right axis) of OCT1 protein quantification in 136 human liver samples. (F) Correlation of OCT1 protein and normalized OCT1 mRNA levels in 136 human liver samples; rS, Spearman rank order correlation coefficient.

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Figure 2. OCT3 expression in (A) different human tissues and (B-E) human liver samples. OCT3 mRNA (NM_021977) was quantified by TaqMan technology (A,B). OCT3 protein expression was analyzed by way of immunoblotting and confocal laser scanning microscopy using rabbit CGR and goat C-14 antiserum (D,E). (A) OCT3 mRNA quantification in 48 human tissues (cDNA array) relative to OCT3 expression in the adrenal gland. (B) Histogram in combination with a normal probability plot (right axis) of OCT3 mRNA quantification in 150 human liver samples. (C) Correlation of normalized OCT1 and OCT3 mRNA levels in 150 human liver samples; rS, Spearman rank order correlation coefficient. (D,E, left panels) Immunoblot analyses of 1 μg of membrane fractions from vector-transfected CHO cells (Co) and MDCK-OCT1, MDCK-OCT2, CHO-OCT3 transfectants and detection of OCT3 at ≈80 kDa with rabbit or goat antiserum. (D,E, middle and right panels) Immunolocalization analyses of OCT3 (green) in the plasma membrane of CHO-OCT3 transfectants and in the sinusoidal membrane of human hepatocytes (red: MRP2 in the canalicular membrane). Bars, 10 μm.

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Hepatic OCT1 and OCT3 Expression.

A systematic analysis revealed OCT1 transcript variant 1 as the predominant transcript in all 150 human liver samples. Variant 2 was readily detectable in 41 of the 150 samples. Because only transcript variant 1 encodes the full-length and functional OCT1 protein,9 a TaqMan primer-probe set was designed that exclusively detects this variant. OCT1-variant 1 mRNA expression data were not normally distributed and varied 113-fold within the study population (median, 0.013; lower quartile, 0.008; upper quartile, 0.022) (Fig. 1B). The KEN antiserum was used to specifically detect OCT1 in human liver by way of immunoblotting (Fig. 1C) and immunofluorescence analyses (Fig. 1D). In addition to the most prominent localization of OCT1 in the sinusoidal hepatocyte membrane, immunostaining was also present in the plasma membrane of cholangiocytes (Supporting Fig. 1). The distinct differences in band intensities in the liver samples indicated interindividual variation of OCT1 protein levels (Fig. 1C, lower panel). OCT1 protein expression data were not normally distributed and varied 83-fold among the 136 specimens, from which membrane fractions could be prepared (median, 3.8; lower quartile, 2.3; upper quartile, 6.9) (Fig. 1E). OCT1 protein and transcript levels were significantly correlated (rs = 0.53, P < 0.0001) (Fig. 1F).

OCT3 mRNA expression data were not normally distributed and varied 27-fold (median, 0.8 × 10−3; lower quartile, 0.5 × 10−3; upper quartile, 1.3 × 10−3) (Fig. 2B). The median ratio of OCT1/OCT3 transcripts was 14.8 (lower quartile, 8.5; upper quartile, 30.4). The OCT1 and OCT3 transcript levels weakly correlated with each other in all 150 samples (rs = 0.33, P<0.0001) (Fig. 2C). OCT3 protein expression was analyzed in OCT-transfected cells and in cryosections of human liver by way of immunoblotting and immunofluorescence microscopy (Fig. 2D,E). Rabbit CGR and goat C-14 antiserum were only reactive in membrane fractions from OCT3-transfected cells, but not from OCT1-, OCT2-, or vector-transfected cells; OCT3 was detected as a broad band of ≈80 kDa and a smaller band of ≈55 kDa (Fig. 2D,E, left panels). After deglycosylation, only a single band of ≈45 kDa was detectable with both antisera (data not shown).

Both antisera intensely stained the plasma membranes of OCT3-transfected but not vector-transfected cells (Fig. 2D,E, middle panels), and yielded distinct fluorescent signals in sinusoidal hepatocyte membranes (Fig. 2D,E, right panels) and to a lesser extent in plasma membranes of cholangiocytes (Supporting Fig. 1). Immunostaining and immunoblot reactivity were completely abolished when the CGR antiserum was preincubated with 10 μM of the synthetic CGR peptide used for immunization. Membrane fractions from human liver yielded only very weak OCT3-specific bands in immunoblot analyses so that OCT3 protein levels could not be systematically quantified in human liver samples.

Impact of Nongenetic Factors on OCT Expression.

Univariate and multivariate analyses showed that the nongenetic factors age, sex, alcohol consumption, smoking habit, or presurgery medication were not significantly associated with OCT1 and OCT3 expression (Table 1). However, OCT1 (mRNA, protein) and OCT3 expression were significantly decreased in individuals with cholestatic liver serum parameters (Fig. 3). This result was confirmed on multivariate analysis (Table 1).

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Figure 3. Correlation of hepatic OCT expression and serum parameters of cholestasis. Scatter plot of normalized (A) OCT1 mRNA, (B) OCT1 protein, and (C) OCT3 mRNA levels in livers classified as normal or cholestatic. The Mann-Whitney U test was used for pair comparisons.

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OCT1 and OCT3 Transport and Inhibition Studies.

We measured uptake of various concentrations of metformin traced with [14C]metformin into CHO cells that were stably transfected with OCT1 or OCT3 (Fig. 4). For these measurements, an incubation time of 2 minutes was used, which was within the linear phase of metformin uptake. Km values of 2.16 ± 0.36 mM (OCT1) and 2.26 ± 0.57 mM (OCT3) and Vmax values of 4.84 ± 1.15 nmol × mg protein−1 × minute−1 (OCT1) and 10.4 ± 2.9 nmol × mg−1 × minute−1 (OCT3) were obtained (mean ± standard deviation of three independent experiments, P < 0.05 for difference between Vmax values). The affinity of metformin was also determined by measuring the inhibition of uptake of 0.1 μM [3H]MPP by various concentrations of metformin (Supporting Fig. 2). Note that [3H]MPP uptake was measured after 1 second of incubation to remain within the short linear uptake phase of this rapidly transported compound. For inhibition of [3H]MPP uptake by metformin, IC50 values of 3.42 ± 0.77 mM (OCT1) and 2.98 ± 0.67 mM (OCT3) were determined (mean ± standard deviation of three independent experiments).

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Figure 4. Transport of metformin in CHO cells stably transfected with OCT1 or OCT3. (A,B) Time courses of the uptake of 5 μM [14C]metformin performed in the absence (○) or presence of 2 mM MPP (•) (typical experiments out of three). (C,D) Concentration dependence of metformin uptake using an incubation time of 2 minutes (typical experiments). The metformin uptake was corrected for the nonspecific uptake measured in the presence of 2 mM MPP.

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OCT1 and OCT3 Genetic Variants, Allele Frequencies, and Haplotypes.

Ninety-two variants in the OCT1-3 gene cluster on chromosome 6 were genotyped either using Illumina chip technology (41 variants) or highly multiplexed MALDI-TOF MS assays (51 variants). Supporting Table 5 specifies each investigated variant, its location, predicted consequence, minor allele frequency, and genotyping method. No deviations from the Hardy-Weinberg equilibrium were observed. Nine nonsynonymous OCT1 variants were identified in our study population: Gly38Asp, Arg61Cys, Cys88Arg, Phe160Leu, Pro341Leu, Gly401Ser, Met408Val, Met420del, and Gly465Arg (Table 3). The only nonsynonymous OCT3 variant was Thr400Ile that was detected as single copy in one sample. Several OCT2 and OCT3 variants were in LD, whereas OCT1 and OCT3 variants were not in LD (Fig. 5A). Notably, the OCT3 variants rs2048327 (intron 7), rs1810126 (3′-untranslated region [UTR]), and rs3088442 (3′-UTR) were completely linked, and variant rs2292334 (OCT3-Ala411Ala) showed almost complete linkage with these three OCT3 variants (D′ = 1, r2 = 0.97). When using the HapMap data, similar LD maps were obtained for individuals with northern/western European ancestry and for Asian individuals, whereas the LD map of African individuals was different (Supporting Fig. 3).

Table 3. Characteristics of Nonsynonymous SLC22A1/OCT1 and SLC22A3/OCT3 Variants, Their Predicted Functional Consequences, and In Vitro Transport Data
Geners#Amino Acid ChangeMinor Allele Frequency in 150 CaucasiansSIFT Score*Polyphen PredictionTransport In Vitro in Comparison to refseq NP_003048 (OCT1)
  • Abbreviations: NA, not applicable; SIFT, sorting intolerant from tolerant algorithm; TEA, tetraethylammonium.

  • *

    See Supporting Material for further information.

SLC22A134447885Ser14Phe01.00Possibly damaging∼190%31 ∼60%29
 35888596Gly38Asp0.0030.00Possibly damaging   
 2297373Phe41Leu00.00Probably damaging   
 12208357Arg61Cys0.0970.01Probably damaging30%,30 ∼30%31 ∼5%29
 55918055Cys88Arg0.0030.00Probably damaging1.4%30  
 683369Phe160Leu0.231.00BenignSimilar30, 31 Similar29
 34104736Ser189Leu00.16BenignSimilar31 ∼20%29
 36103319Gly220Val00.11Benign0%31 0%29
 4646277Pro283Leu00.00Probably damaging0%51∼10%,520%51 
 4646278Arg287Gly00.00Probably damaging0%51∼6%,520%51 
 2282143Pro341Leu0.0170.00Probably damaging∼65%31∼60%,52 65%51Similar29
 34205214Arg342His00.03BenignSimilar31 Similar29
 34130495Gly401Ser0.010.01Benign0.9%,30 0%31 ∼10%29
 628031Met408Val0.4290.41BenignSimilar31 Similar29
  Met420del0.17NANASimilar30, 31 ∼30%29
 34059508Gly465Arg0.0430.00Probably damaging0%31 0%29
 35270274Arg488Met00.31BenignSimilar31 Similar29
      Norepinephrine Transport In Vitro in Comparison to refseq NP_068812 (OCT3)
  Met370Ile00.03Probably damaging∼50%37  
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Figure 5. (A) Pairwise LD map of the SLC22A1-3/OCT1-3 gene cluster on chromosome 6, including all 92 variants genotyped in the 150 individuals. Coloring corresponds to the standard Haploview (D'/LOD).39 (B) SLC22A1 and SLC22A3 haplotypes of the study population were calculated with PHASE version excluding intronic sites. Analyses were run seven times, and haplotypes with frequencies >1% estimated in seven out of seven runs are given.

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When excluding all intronic variants, 11 and 13 haplotypes with frequencies >1% were calculated for OCT1 and OCT3, respectively, in our study population (Fig. 5B).

Analysis of OCT1 and OCT3 Phenotype-Genotype Correlations in Human Liver.

Multivariate modeling including all genetic variants and the above-described nongenetic factors identified several variants being significantly correlated with hepatic OCT expression (Table 2). After correction for multiple testing, the OCT1 variant rs12208357 (OCT1-Arg61Cys) and four OCT3 variants (rs2292334, rs2048327, rs1810126, rs3088442) remained significantly correlated with OCT1 protein and OCT3 mRNA expression, respectively (Table 2, Fig. 6A,B,D,E). Semiquantitative immunofluorescence analysis indicated that the intense sinusoidal OCT1 immunostaining of variant livers for rs12208357 (OCT1-Arg61Cys) was significantly reduced compared with wild-type (Fig. 6C, Supporting Fig. 4). Similarly, sinusoidal OCT3 immunostaining was significantly lower in livers with the OCT3 variant rs3088442 than in wild-type samples (Fig. 6F, Supporting Fig. 4).

Table 2. Multivariate Analysis of Hepatic OCT1 and OCT3 Expression in Relation to 24 Genetic Variants Corrected for Nongenetic Factors
  P Value (P Value After Holm Correction)
Genetic Variant* OCT1 mRNAOCT1 proteinOCT3 mRNA
  • Abbreviation: NS, not significant.

  • *

    The remaining 68 genetic variants, also corrected for the nongenetic factors, did not show any significant associations. See Supporting Table 5 for additional details of the genetic variants.

  • Boldface indicates significant P value after Holm correction.

rs456598 0.01 (0.81)NSNS
rs12208357OCT1-Arg61Cys0.002 (0.12)<0.000001 (<0.00001)0.05 (1.00)
rs4646272 0.04 (1.00)NSNS
rs683369OCT1-Phe160Leu0.02 (1.00)0.04 (1.00)NS
rs3798168 0.04 (1.00)NSNS
rs34130495  OCT1-Gly401SerNS0.04 (1.00)NS
rs628031OCT1-Met408Val0.001 (0.07)NSNS
rs34059508  OCT1-Gly465ArgNS0.004 (0.24)NS
rs1564348 0.002 (0.14)NSNS
rs474617 NSNS0.04 (1.00)
rs366920 NSNS0.03 (1.00)
rs569919/rs520685 0.004 (0.25)NSNS
rs3004077 NSNS0.03 (1.00)
rs520829 NSNS0.004 (0.29)
rs3004078 NSNS0.008 (0.51)
rs10455781 NSNS0.04 (1.00)
rs884742 NSNS0.01 (0.77)
rs10806731 NSNS0.009 (0.57)
rs376563 NSNS0.03 (1.00)
rs8187725  OCT3-Thr400IleNS0.04 (1.00)NS
rs2292334  OCT3-Ala411AlaNSNS0.0004 (0.03)
rs2048327/rs1810126/rs3088442 NSNS0.0005 (0.03)
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Figure 6. Hepatic OCT1 and OCT3 expression in relation to cholestasis and those genetic variants that were identified by multivariate analysis and adjustment for multiple testing as having significant effects (Tables 1 and 2). Box plot analyses of (A) hepatic OCT1 mRNA and (B) OCT1 protein levels against OCT1 variant rs12208357 and of OCT3 mRNA levels against OCT3 variants (D) rs2292334 and (E) rs3088442 using SPSS 15.0 (see Supporting Material). Boxes give the median and interquartile range; whiskers depict the minimum and maximum; open circles depict outliers >1.5 times the box height. (C) Representative immunostaining of OCT1 in livers (n = 7) with the variant rs12208357-CT (inset: wild-type) using the KEN antiserum. (F) Representative immunostaining of OCT3 in livers (n = 7) with the variant rs3088442-AA (inset: wild-type) using the CGR antiserum. See Supporting Fig. 4 for semiquantitative immunofluorescence analyses. Bars, 20 μm.

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  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

This study provides a comprehensive analysis of the hepatic expression of OCT1 and OCT3, the only OCTs occurring in human liver. We detected a high interindividual variability of expression on mRNA and/or protein level for these two cationic drug transporters and identified cholestasis and genetic variants as major determinants of hepatic expression. Moreover, we localized OCT3 to the sinusoidal hepatocyte membrane and identified metformin as an OCT3 substrate.

Based on our expression profiling analysis, the liver was the tissue with the highest OCT1 expression (Fig. 1A), as expected based on previous studies.7, 19, 45 This prompted us to elucidate systematically the interindividual variability of hepatic OCT1 expression and underlying factors. Besides several other tissues, OCT3 transcripts were also detected in human liver using the tissue array (Fig. 2A). Whereas hepatic OCT3 mRNA has been determined previously,10, 11 hepatic OCT3 protein expression and particularly the localization of this membrane transporter has not been studied. The rabbit CGR antiserum, directed against the C-terminus of human OCT3, permitted selective detection of human OCT3, which was indicated by exclusive immunoreactivity of this antiserum with membrane fractions and the plasma membrane of OCT3-transfected cells and abolishment of these reactivities by the CGR antigenic peptide (Fig. 2D). Similarly, immunoblotting and immunofluorescence analyses of OCT3-transfected cells (Fig. 2E) revealed that the goat C-14 antiserum also selectively reacts with OCT3. Both antisera served to localize OCT3 to the sinusoidal membrane of human hepatocytes (Fig. 2D,E, right panels). OCT3 is thereby the second identified OCT transporter that may mediate, in addition to OCT1, the uptake of organic cations from blood into hepatocytes.

Both antisera showed only very weak reactivity in membrane fractions from human liver. This may either be due to a limited affinity of both antisera to OCT3 in immunoblots or to low OCT3 protein levels in liver. Correspondingly low OCT3 mRNA levels, which were on average only one-fifteenth of the OCT1 mRNA levels, were detected in the 150 liver samples.

The immunolocalization of OCT1 and OCT3 in the same liver samples (Figs. 1D and 2D,E) demonstrates that both transporters are simultaneously expressed in hepatocytes. OCT3 is likely important for the hepatocellular uptake of those organic cations that have been identified as exclusive OCT3 substrates, such as the neurotransmitters adrenaline, noradrenaline, and histamine.2, 10 Moreover, because OCT1 and OCT3 have partly overlapping substrate specificities (Supporting Table 1),2, 15 OCT3 may substitute for OCT1 when OCT1 expression and function is impaired, for example, by certain genetic variants (see below). For instance, oxaliplatin and cimetidine are substrates for both OCT1 and OCT3.22–25

Our transport studies identify metformin as an OCT3 substrate (Fig. 4) with an affinity for OCT3 similar to that for OCT121, 28, 29 and a twofold higher maximal transport rate compared with OCT1. Recently, Shu et al.29, 33 showed significant alteration of pharmacokinetics of metformin and its glucose-lowering effect in individuals with reduced-function OCT1 variants. Nevertheless, it is unclear to what extent OCT3 contributes to metformin disposition. Because OCT3 transports metformin with a higher efficacy than OCT1, it may be important for metformin disposition in patients with low expression of OCT1.

Because OCT1 and OCT3 expression is highly variable in human liver (Figs. 1B,E and 2B), nongenetic as well as genetic factors may explain interindividual variability. Among several clinical factors such as age, sex, alcohol consumption, smoking habit, and presurgery medication, cholestasis was the only parameter that resulted in a significantly reduced OCT1 mRNA and protein expression (Fig. 3), even on multivariate analysis (Table 1). The same association was found for OCT3 transcripts. Whereas OCT1 and OCT3 expression has not yet been studied in cholestatic human liver, other hepatocellular uptake transporters such as Na+/taurocholate cotransporter and organic anion transporter OATP1B1 are clearly down-regulated in patients with cholestatic liver disease.46, 47 Interestingly, obstructive and ethinylestradiol-induced cholestasis in rats significantly reduced hepatic Oct1 mRNA and protein levels,48–50 which fits well with our data in humans. Further studies are warranted to elucidate, for instance, whether drug response to the OCT1 and OCT3 substrate metformin is altered in diabetic patients with cholestasis.

In addition to cholestasis, we show for the first time that sequence variations in the OCT1 and OCT3 gene significantly influence OCT expression and function. Several genetic variants of OCT1 and OCT3 with impaired transport function in vitro have been described so far (Table 3),29–31, 37, 51, 52 and interestingly, some of them have already been associated with altered metformin pharmacokinetics.33 Comprehensive genotyping of 92 variants in the OCT1-3 gene cluster by MALDI-TOF MS and Illumina DNA chip technology revealed the occurrence of 10 nonsynonymous variants (nine in OCT1 and one in OCT3) in our population of 150 Caucasian subjects (Table 3, Supporting Table 5) with allele frequencies corresponding to those published for northern/western European populations.30, 31, 36 No significant linkage between the OCT1 and OCT3 genes by haploblock analysis (Fig. 5A) was found, which was in line with data from a Korean population.53 Remarkably, the haploblock structure of our 150 liver bank samples (Fig. 5A) is comparable to the HapMap data of northern/western Europeans (Supporting Fig. 3, CEU), supporting the Caucasian origin of our study population.

The data of our comprehensive genotype–phenotype correlation analysis clearly showed a significant alteration of OCT1 mRNA and protein expression for several variants (Table 2), particularly for the Arg61Cys variant (rs12208357) (Fig. 6). Notably, this coding variant was still significantly (P < 0.0001) associated with decreased OCT1 protein levels after multivariate analysis, including nongenetic factors and adjustment for multiple testing. Again, cholestasis was identified as a second predictor.

We previously described functional consequences of the OCT1-Arg61Cys variant in vitro using the oocyte expression system and detected a 70% reduction of MPP transport activity compared with the OCT1 reference sequence.30 When recombinantly expressed in mammalian human embryonic kidney cells and using metformin as the substrate, OCT1-Arg61Cys showed only 5% transport activity compared with the reference sequence, which was attributed to posttranscriptional changes, such as reduced plasma membrane localization.29 The significantly reduced protein levels in human livers with the OCT1-Arg61Cys variant probably result directly from the likewise reduced mRNA expression (Fig. 6A,B). Moreover, the reduced sinusoidal staining of the OCT1-61Cys variant (rs12208357 CT) in the liver samples (Fig. 6C, Supporting Fig. 4) is in agreement with the reduced plasma membrane localization in human embryonic kidney cells.29

For OCT3, interestingly, we identified two variants in the 3′-UTR region (rs1810126, rs3088442), linked to one intronic (rs2048327) and in part to one synonymous variant (rs2292334), which were strongly associated with decreased OCT3 mRNA expression in the multivariate analysis after correction for multiple testing (P = 0.03). The functional consequences of the 3′-UTR variants were tested by way of computational structural analyses, indicating that both variants alter mRNA folding (Supporting Fig. 5), which may explain lower OCT3 transcript levels. The reduced intensity of sinusoidal OCT3 immunostaining in variant livers for rs3088442 (Fig. 6F, Supporting Fig. 4) also indicates decreased hepatic OCT3 protein levels. The rs3088442 variant is in complete linkage to the intronic OCT3 variant rs2048327 and, of note, in a genome-wide association study investigating susceptibility for coronary artery disease,54 this variant was recently identified. Thus, in addition to a potential clinical relevance of OCT3 for drug response (such as efficacy of oxaliplatin chemotherapy,55 lamivudine as drug substrate19, 20) OCT3 (SLC22A3) may contribute also as a susceptibility factor for development of certain diseases such as coronary artery disease54 but also other diseases (such as obsessive-compulsive disorder37).

In conclusion, the hepatic expression of the cationic drug uptake transporters OCT1 and OCT3 in Caucasians is significantly affected by cholestasis and certain genetic variants. Because OCT1 and OCT3 are involved in the hepatic uptake of the antidiabetic agent metformin and of other drugs, these factors may contribute to the variability in drug response which needs further studies.


  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

We gratefully acknowledge Dr. Peter Fritz, chief pathologist at the Robert-Bosch Hospital (Stuttgart), for expert histological examination of all liver samples. We greatly appreciate the expert technical assistance of Silvia Kubitzsch, Ursula Waldherr, Monika Elbl, Heidi Köhler, and Igor Liebermann (all Stuttgart).


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  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Additional Supporting Information may be found in the online version of this article.

HEP_23103_sm_SupportingData.doc188KSupporting Material
HEP_23103_sm_SupportingFigure1.tif9852KSupporting Figure S1. Localization of OCT1 (A-C) and OCT3 (D-F) in hepatocytes and in cholangiocytes. Cryosections were double-stained with an antibody against cytokeratin 19 to detect cholangiocytes4 and the KEN antiserum to detect OCT13 or the CGR antiserum to detect OCT3. In addition to the most prominent staining of OCT1 in the sinusoidal membrane of hepatocytes (arrows), very faint immunostaining was also apparently present in the plasma membrane of cholangiocytes (A-C, representative picture from 8 investigated liver samples). For OCT3 (D-F, representative picture from 7 investigated liver samples), staining was also observed in the plasma membrane of cholangiocytes. Because OCT3 staining tended to be lower in periportal (arrows) than in pericentral hepatocytes, the intensity of staining of cholangiocytes and periportal hepatocytes appeared similar. Arrowheads point to OCT staining in cholangiocytes. Bars, 20 μm.
HEP_23103_sm_SupportingFigure2.tif2992KSupporting Figure S2. Inhibition of MPP uptake by metformin in CHO cells that were stably transfected with OCT1 or OCT3. (A, B) Time courses of the uptake of 0.1 μM [3H]MPP were measured in the absence (?) or presence (•) of 2 mM of nonlabeled MPP. Typical experiments are shown. (C, D) Inhibition of the uptake of 0.1 μM [3H]MPP by metformin using an incubation time of 1 sec. Nonspecific [3H]MPP uptake which was measured in the presence of 2 mM nonlabeled MPP was subtracted. Mean values + SD of normalized data from three independent experiments are shown. The indicated curves were obtained by fitting the Hill equation to the compiled data sets. The Hill equation was also fitted to each individual experiment. From the individual IC50 values, mean values of 3.42 + 0.77 mM (OCT1) and 2.98 + 0.67 mM (OCT3) were calculated.
HEP_23103_sm_SupportingFigure3.tif12334KSupporting Figure S3. Pairwise linkage disequilibrium maps of the SLC22A1-A3/OCT1-3 gene cluster visualized with Haploview10 and using the publicly available data from the International HapMap project ( that include samples from Caucasians (CEU, Utah residents with ancestry from northern and western Europe), Africans (YRI, Yoruba in Ibadan, Nigeria), and Asians (CHB, Han Chinese in Beijing, China; JPT, Japanese in Tokyo, Japan). Coloring corresponds to the standard Haploview (D′/LOD).
HEP_23103_sm_SupportingFigure4.tif2421KSupporting Figure S4. Semi-quantitative immunofluorescence analysis of OCT1 (A-C, KEN antiserum) and OCT3 (D-F, CGR antiserum) immunostaining in human liver. (A, B) Representative figures indicating a reduced intensity of sinusoidal OCT1 immunostaining in livers with variant rs12208357 CT (OCT1-61Cys) as compared to “wild-type” livers with rs12208357 CC (OCT1-61Arg). (C) When staining intensities are classified into 4 categories as described in Supporting Methods, the number of pixels of very high (gray level values 192-255) and high (gray level values 128-191) staining intensity was significantly reduced in livers with variant rs12208357 CT. A total of 20 fields (rs12208357 CC, 3 different livers) and of 35 fields (rs12208357 CT, 7 different livers) was analyzed. (D, E) Representative figures indicating a reduced intensity of OCT3 immunostaining in livers with variant rs3088442 AA as compared to “wild-type” livers with rs3088442 GG. Similar to OCT1, this reduction is largely due to a reduced sinusoidal membrane staining. (F) The number of pixels of very high (gray level values 192-255) and high (gray level values 128-191) staining intensity was significantly reduced in livers with OCT3 variant rs3088442 AA. A total of 10 fields (rs3088442 GG, 2 livers) and of 35 fields (rs3088442 AA, 7 livers) was analyzed. Values are means ± SD. ***, P<0.0001; **, P<0.01; *, P<0.05. Bars, 20 μm.
HEP_23103_sm_SupportingFigure5.tif11262KSupporting Figure S5. Prediction of the secondary OCT3 mRNA structure using MFold.17 The optimal structures of the reference sequence (left, initial ?G: -1804.4 kcal/mol) and the OCT3 mRNA with the linked variants rs1810126/rs3088442 (right, initial ?G: -1801.8 kcal/mol) are shown.

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