Bibliographic record
Abstract
Interindividual variation in drug response continues to pose a considerable challenge to optimal drug therapy. Drug-metabolizing enzymes have been established as critical determinants of drug disposition and response, and drug transporters are becoming widely appreciated for their role in these processes. We now know that transport is required for many drugs to pass through the membrane, and it is a rate-limiting step governing drug absorption and entry into target tissue.1 As reported by Nies and colleagues2 in this issue of HEPATOLOGY, both genetic and environmental factors contribute to interindividual variation in the expression of hepatic cation transporters. Indeed, genetic polymorphisms have been identified in most transport proteins, and many are now recognized as significant contributors to interindividual variation in drug exposure. For most drug transporters, the complex interaction of clinical and genetic parameters affects the observed drug disposition profile and response phenotype.1, 3, 4 ABC, adenosine triphosphate–binding cassette; ATP, adenosine triphosphate; BCRP, breast cancer resistance protein; BSEP, bile salt export pump; MATE1, multidrug and toxin extrusion 1; MDR, multidrug resistance; mRNA, messenger RNA; MRP, multidrug resistance–associated protein; NTCP, sodium-dependent taurocholate cotransporting polypeptide; OAT2, organic anion transporter 2; OATP, organic anion transporting polypeptide; OCT, organic cation transporter; SLC, solute carrier family. Drug transporters recognize structurally diverse compounds and may be broadly classified into two groups: the major facilitator superfamily and the adenosine triphosphate–binding cassette (ABC) superfamily. Transcriptional, translational, and posttranslational regulation can affect the amount, localization, and functional activity of the expressed protein. In the hepatocyte, transporters on the sinusoidal membrane include organic cation transporters [OCTs; solute carrier family 22 (SLC22)], organic anion-transporting polypeptides (SLCO), and organic anion transporters (SLC22). On the canalicular membrane, drug efflux is mediated primarily by ABC transporters1 (Fig. 1). Transporters expressed in the human hepatocyte. The cation uptake transporters OCT1 and OCT3 and the cation efflux transporters MATE1 and MDR1 are colored red. The anion uptake transporters OATPs, OAT2, and NTCP are purple, orange, and green, respectively. Transporters colored blue are efflux transporters of the ATP-binding cassette superfamily. Abbreviations: ATP, adenosine triphosphate; BCRP, breast cancer resistance protein; BSEP, bile salt export pump; MATE1, multidrug and toxin extrusion 1; MDR, multidrug resistance; MRP, multidrug resistance–associated protein; NTCP, sodium-dependent taurocholate cotransporting polypeptide; OAT2, organic anion transporter 2; OATP, organic anion transporting polypeptide; OCT, organic cation transporter. Uptake of cationic drugs into the liver occurs largely by OCTs, whereas their efflux is facilitated by a recently identified multidrug and toxin extrusion transporter [multidrug and toxin extrusion 1 (MATE1)] and the widely studied P-glycoprotein [multidrug resistance 1 (MDR1)/ABCB1].5 OCTs mediate electrogenic, sodium-independent transport and may be inhibited by a number of compounds not transported. OCT substrates include the oral antihyperglycemic drug metformin, the histamine receptor antagonist cimetidine, and antivirals such as acyclovir. Endogenous substrates of OCTs include acetylcholine and catecholamines.6 In this issue of HEPATOLOGY, Nies and colleagues2 report the expression of the two hepatic OCTs, OCT1 (SLC22A1) and OCT3 (SLC22A3), in 150 human liver samples. They found protein expression of OCT1 to be highly variable between individuals, although it was correlated with OCT1 messenger RNA (mRNA) levels. For OCT3, protein expression data were not obtained, but mRNA levels were also highly variable. The authors were able to correlate some of the observed variation to genetic polymorphisms in SLC22A1 and SLC22A3. Of 92 OCT-related variants, one nonsynonymous coding variant, OCT1-Arg61Cys (rs12208357), was associated with reduced OCT1 protein and mRNA expression. In addition, three noncoding OCT3 variants (rs2048327, rs1810126, and rs3088442) in linkage disequilibrium and one synonymous coding variant (rs2292334) were associated with decreased OCT3 mRNA expression.2 OCT polymorphisms have been extensively studied in the context of metformin pharmacokinetics and response.3, 5-14 Metformin is widely prescribed to treat diabetes mellitus type 2, with considerable variability in efficacy. Reduced-function OCT1 alleles—OCT1-Arg61Cys, OCT1-Gly401Ser, OCT1-420del, and OCT1-Gly465Arg—have been demonstrated by Shu and colleagues8 to increase systemic exposure to metformin. This observation provides a mechanistic basis for the reduced response to metformin observed in healthy volunteer carriers of the polymorphisms,9 as hepatic entry of metformin is required for its glucose-lowering effect. A study of 33 Japanese patients showed no difference in the frequency of OCT1 polymorphisms in metformin responders versus nonresponders, however, it is important to note that the polymorphisms studied by Shu et al. were not detected in this population.10 A larger cohort of 1531 patients on metformin therapy failed to show a significant association between OCT1-Arg61Cys and OCT1-420del and levels of glycosylated hemoglobin.11 Most recently, a tagging OCT1 single nucleotide polymorphism (rs622342) was associated with impaired glucose lowering by metformin in 102 patients; however, a linkage between this and previously identified single nucleotide polymorphisms is not known.12 The reduction of OCT1-Arg61Cys mRNA and protein described here provides some insight into the basis for altered metformin pharmacokinetics among carriers of this allele. Furthermore, the identification by Nies and coworkers2 of OCT3 as a novel transporter of metformin raises the possibility that genetic variation in OCT1 alone may not be sufficient in some patients to result in an altered response to metformin. OCT3 may also contribute to hepatic metformin uptake, particularly when OCT1 is functionally impaired. Thus, the role of OCT3 in organic cation clearance may have been underestimated, and the impact of OCT3 polymorphisms on substrate drug disposition in humans warrants further investigation. Nies and colleagues2 also note that elevated cholestatic liver serum parameters appear to be nongenetic factors associated with reduced OCT1 and OCT3 expression. The alteration of hepatic transporter expression during cholestasis is well established. Regulation of transporters has traditionally been studied in the context of bile acid transport, and much of our initial understanding of the involvement of transporters in cholestasis has come from animal models. In humans, the importance of transport proteins in bile acid homeostasis is illustrated by the role of transporter mutations in inherited forms of cholestasis: progressive familial intrahepatic cholestasis types 2 and 3 are caused by mutations in bile salt export pump (ABCB11) and MDR3 (ABCB4), respectively. Less deleterious mutations in these transporters are associated with benign recurrent intrahepatic cholestasis and increased susceptibility to intrahepatic cholestasis of pregnancy.15 Observations of reduced transporter expression during cholestasis raise the important question of drug response in patients with cholestatic liver disease. Finally, the impact of transporter expression in other tissues, particularly those involved in drug elimination or expressed in the target tissue, must not be overlooked. The contribution of hepatic OCT3 expression versus enteric OCT3 expression to plasma metformin levels with respect to the hepatic concentration is not yet clear. Polymorphisms in renally expressed OCT2 have been associated with metformin pharmacokinetics,13 and polymorphisms in the cation transporter MATE1 have also been associated with metformin efficacy in a diabetic population.16 Most recently, Tzvetkov and colleagues14 reported that polymorphisms of OCT1, but not OCT2 or OCT3, play a significant role in the renal clearance of metformin. We now realize that drug transporters, particularly those expressed in the liver, are important determinants of interindividual variation in drug clearance and response. The work by Nies and colleagues2 contributes to our understanding of the role of genetic variation and clinical factors in the expression and function of OCT1 and OCT3. As with organic anion-transporting polypeptides, there may be a degree of redundancy to hepatic OCTs, given new information regarding expression and substrate overlap. All in all, the field of hepatic drug transporters appears poised to contribute new insights into our understanding of drug disposition and response.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".