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J. Pers. Med. 2018, 8(4), 40; doi:10.3390/jpm8040040
ATP-Binding Cassette Transporters in the Clinical Implementation of Pharmacogenetics
Pharmacy Department, Instituto de Investigación Sanitaria Gregorio Marañón, Hospital General Universitario Gregorio, 28007 Madrid, Spain
Spanish Clinical Research Network (SCReN), 28040 Madrid, Spain
Received: 31 August 2018 / Accepted: 3 December 2018 / Published: 5 December 2018
ATP-binding cassette (ABC) transporters are involved in a large number of processes and contribute to various human genetic diseases. Among other functions, ABC proteins are involved in the transport of multiple drugs through cells. Most of the genes coding for these transporters are highly polymorphic and DNA variants in these genes can affect the normal functioning of these proteins, affecting the way drugs are transported, increasing or decreasing drug levels. These changes in the intracellular and extracellular drug levels may be associated with altered drug effectiveness or severe drug-induced adverse events. This review presents a state-of-art of the most pharmacogenetics clinically relevant ABC transporters closed to the clinical implementation.
Keywords:pharmacogenomics; ATP-binding cassette; adverse drug reactions; drug efficacy
Although many authors identify DNA variants that affect the way an individual patient can respond to a drug or suffer severe adverse reactions, few of these variants have shown a high level of evidence and fewer still have sufficient evidence to be implemented in clinical practice. This statement for pharmacogenetics in general is also valid for ATP-binding cassette (ABC) transporters in particular. After a brief summary of ABC transporters and an introduction to pharmacogenetics, this review will delve into the variants of ABC transporters with a currently high or moderate level of evidence to be used in clinical practice. Since the level of evidence is sometimes a fuzzy line, this paper has considered the classification of clinical annotations in ABC transporters variants on the most reputable non-profit organization in pharmacogenetics, PharmGKB, and the guidelines of the Clinical Pharmacogenomics Implementation Consortium (CPIC). The most important genes containing these variants and the works on which this classification is based are presented. Finally, some ways to improve the clinical implementation of ABC-transporter pharmacogenetics are suggested.
1. ABC Transporters
ATP-binding cassette (ABC) transporters are a family of ATP-dependent proteins involved in a large number of processes that contribute to various human diseases, such as cardiovascular diseases, ulcerative colitis, or Alzheimer [1,2,3,4]. They also transport endogenous and exogenous molecules and regulate cell integrity, metabolism and homeostasis. They have a major role in the transport of a large number of drugs used in many diseases and are involved in their efficacy and toxicity. For this reason, changes in the level of expression and functionality of these transporters influence the efficacy and safety of the drugs transported. The study of ABC transporters in drug development is also critical . Among ABC transporters, multidrug resistance proteins are known to contribute significantly to multidrug-resistant cancer , but many other members have also demonstrated their relevance in interindividual variability response to drugs in many other diseases [7,8].
There are 48 known human ABC transporters, which are classified into 6 subfamilies (ABCA, ABCB, ABCC, ABCD, ABCE/ABCF and ABCG). ABC transporters have four domains: two nucleotide-binding domains (NBDs) and two transmembrane domains (TMDs). The NBDs bind and hydrolyze ATP, while the TMDs recognize and transport substrates . The ABCA family contains some of the largest transporters that have been linked primarily to lipid trafficking . The ABCB family contains four full and seven half transporters, some of them located in the blood-brain barrier, liver or mitochondria. They are involved in the transport of bile and peptides . ABCC transporters contain 13 full molecules, including the cystic fibrosis transmembrane conductance regulator (CFTR) protein, also known as ABCC7, which causes cystic fibrosis; cell-surface receptors, such as the sulfonylurea receptors (ABCC8, ABCC9) and the multidrug resistance proteins (MRPs) . ABCC proteins are mostly involved in the transport of endo- and xenobiotics. The ABCD family contains only four members and all of them are used in peroxisomes . ABCE and ABCF proteins are often considered as a single family and are not transporters. They maintain the ATP-domain but lack the transmembrane domain and are involved in the expression and regulation of protein synthesis . Finally, the ABCG family consist of six half-transporters involved in the transport of lipids, drug substrates, bile, cholesterol, and other steroids . However, not all of these ABC transporter genes have shown to be relevant in the way patients respond to drugs.
2. Pharmacogenetics and Clinical Evidence: What about ABC Transporter Variants
Pharmacogenetics is defined by the food and drug administration (FDA) and European European Medicines Agency (EMA) as the study of variations in DNA sequence as related to drug response while pharmacogenomics includes pharmacogenetics as well as study the variations of RNA characteristics as related to drug response, (http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2009/09/WC500002880.pdf). These disciplines do not include others such as proteomics and metabolomics, but they do include processes such as drug absorption and disposition, drug effects, drug efficacy and adverse effects of drugs. There are many well-stablished relations between DNA variants in genes involved in pharmacodynamics and pharmacokinetics of drugs. The international transporter consortium has recently published a review of the influence of transporter polymorphisms on drug availability and response . Although this paper reviews a large number of associations between polymorphisms in ABC transporters and drug response with a high statistically significant value, the clinical utility of these variants is in doubt.
In PharmGKB, the level of evidence of the clinical annotation of a DNA variant with the toxicity or efficacy of a drug is classified from 1 to 4. Level 1 corresponds to high evidence, level 2 to moderate evidence, level 3 to low evidence and level 4 to preliminary evidence. Categories 1 and 2 are also subdivided into levels, A and B, the former being more significant than the latter. Thus, level 1A is assigned to annotations for a variant-drug combination in a guideline or implemented at a major health system. Level 1B includes annotations with high evidence, but the association variant-drug must be replicated in more cohorts with significant p-values and with a strong effect size. Level 2 is also divided into A and B. Both have a moderate evidence, but in the case of 2A it corresponds to “very important pharmacogenes” as defined by PharmGKB . Regarding ABC-transporter genes, 14 of them with clinical annotations related to drug response or adverse events have been included in PharmGKB: CFTR, ABCA1, ABCB5, ABCB1, ABCC4, ABCC5, ABCC1, ABCC1, ABCC2, ABCC3, ABCC6, ABCC10, ABCG2 and ABCG1. DNA variants in CFTR and ivacaftor treatment are the only ABC transporters associations to reach level 1A or 1B and currently implemented in clinical pharmacogenetics . In the Table 1, a summary of associations from a level 1A to 2B is introduced.
Furthermore, The Clinical Pharmacogenetics Implementation Consortium (CPIC), the Royal Dutch Association for the Advancement of Pharmacy (DPWG), the Canadian Pharmacogenomics Network for Drug Safety (CPNDS) and other societies have made a great effort in this regard and have promoted the publication of dozens of guidelines. However, although many ABC transporters variants have been studied, no specific clinical recommendations are currently given, except for CFTR [18,19].
3. ABC Transporter Genes with High and Moderate Evidence of Clinical Implementation
Only 4 ABC transporters genes, as shown in Table S1, have level 1 or 2 evidence of clinical annotations. A detailed description of the works on which this classification is based is presented below.
CTFR functions as an ion channel and controls ion and water secretion and absorption in epithelial tissues, but it does not function as a transporter. CFTR is the only ligand-gated channel that consumes its ligand (ATP) during the gating cycle . Malfunction of this channel causes cystic fibrosis, a disorder that affects the production of sweat, digestive fluids and mucus causing difficulty breathing, and coughing up mucus as a result of lung infections . Ivacaftor drug label indicates its use in patients diagnosed with cystic fibrosis with at least one copy of any of a group of CFTR genetic variants. The variants required for genotyping prior to prescribing ivacaftor change according to regulatory agencies. For instance, the FDA includes 33 DNA variants, while the EMA includes only nine of them (see Table 2). All these DNA variants produce mutant CFTR forms with mild defects in CFTR processing or channel conductance . This was first observed for rs11971167, which produces a change from an Asp to an Asn at position 1270 of CFTR. This change is responsible for a 1.9-fold increase in chloride transport after ivacaftor treatment compared to baseline (no ivacaftor-treatment).
MDR1 or ABCB1 is an efflux transporter involved in the transport of multiple drugs and many processes. There is an important interindividual variability that can be explained mainly by genetic variants . Three polymorphisms have been extensively studied, two synonymous SNPs, 1236C > T, (rs1128503) in exon 12 and 3435C > T (rs1045642) in exon 26; and one nonsynonymous SNP, 2677G > T/A (rs2032582 in exon 21). These three polymorphisms are in linkage disequilibrium and define, among others, the haplotype ABCB1*2. This haplotype is related to an increased activity in MDR1 . Nevertheless, conflicting data of these polymorphisms make it difficult to apply them in clinical practice [63,64,65].
Variants in ABCB1 have been related to hundreds of drugs. However, only a few of them reach a level 2 of evidence in PharmGKB. The variants rs1128503 (1236C > T), rs2032582 (2677G > A/T) and rs1045642 (3435C > T) in ABCB1 have been associated with efficacy to simvastatin in men [21,22]. Since the three most studied SNPs in ABCB1 are in linkage disequilibrium, many authors have attempted to assign pharmacogenetic associations to the haplotypes defined by them. In this sense, two haplotypes are the most relevant: *1 with the genotype CGC and *2 with the genotype TTT. For instance, Becker and col. found that men simvastatin users with the 1236/2677/3434 TTT and CGT haplotypes had larger reductions in total cholesterol and low-density lipoprotein cholesterol compared to the wild-type CGC haplotype . Severe adverse reactions induced by simvastatin are also associated with ABCB1 polymorphisms. Thus, individuals carrying TTT haplotype developed less myalgia during simvastatin treatment than non-carriers . However, a more recent study shows that these ABCB1 variants have no effect on simvastatin pharmacokinetics in Korean men . This discrepancy may be responsible for not reaching a level 1 of evidence.
These variants in ABCB1 have also been associated with response or toxicity to other drugs. Thus, the allele T for rs1045642 is associated with methotrexate-induced toxicity with a level 2A. Therefore, the TT and CT genotypes for the rs1045642 and rs1128503 variants in ABCB1 were associated with severe neutropenia in children with acute lymphoblastic leukemia . These authors also showed that the polymorphism rs717620 ABCC2, another ABC efflux transporter, was associated with low methotrexate levels. However, the evidence for variant rs1045642 and methotrexate-induced toxicity is greater because other associations were also found between the T allele and hepatic toxicity , anemia and thrombocytopenia . Most of these works did not genotyped the polymorphisms rs1128503 and rs2032582, which are in linkage disequilibrium with rs1045642. For this reason, these other two ABCB1 polymorphisms may also be associated with methotrexate-induced toxicity. However, further studies are needed to clarify this issue.
The variant rs1045642 in ABCB1 is also associated with nevirapine-induced toxicity. Patients with the TT genotype for this variant may have a decreased, but not absent, risk for nevirapine-induced hepatotoxicity compared to patients with the CC genotype [24,25,26]. The ABCB1 *2/*2 diplotype was associated with a decrease in the clearance of atazanavir when taken alone or co-administrated with ritonavir, as well as of ritonavir taken alone compared to the *1/*1 or *2/*1 diplotypes [27,28].
Two variants of ABCB1 associated with toxicity and/or efficacy for ondansetron have been found with a level of evidence 2A. Variant rs1045642 is associated with likelihood of postoperative nausea and vomiting in patients with acute leukemia when treated with the antiemetic ondansetron [29,30]. Thus, patients with AA genotype suffer less nausea and vomiting than patients with CT or CC.
Variant rs1045642 has also been associated with the metabolism of digoxin with a level 2A. Patients carrying the allele T had higher serum concentrations, higher bioavailability, and less renal clearance of digoxin compared to those patients carrying the C allele [31,32,33].
Drugs that inhibit or induce ABCB1 expression, as well as DNA variants, can alter the efflux of blood-brain barrier and affect the efficacy of many drugs, such as opioids . The rs1045642 is related to the dose and efficacy of fentanyl, methadone, morphine, opioids, oxycodone or tramadol with an 2B evidence level. Patients with the AA genotype may experience improved opioid efficacy and may require a lower dose compared to patients with GG genotype and possible AG. However, the results are contradictory. Thus, some authors found a relationship between dose requirements for any of these drugs and pain [34,35,36,37,38], but many others did not [39,40,41,42,43,44]. Other authors even found an opposite relationship, showing how patients with genotype AA require a higher maintenance dose of methadone than patients with genotypes GG or AG .
Finally, another association between ABCB1 variants and drug response with an evidence level 2B refers to sunitinib. Patients with renal cell carcinoma and the haplotype ABCB1 *2/*2 may show a decreased response to sunitinib compared to other patients. Decreased overall survival and progression-free survival were showed along with a reduced risk of neutropenia [71,72].
3.3. ABCC4 and ABCG2
ABCC4, also known as MRP4, transports many xenobiotics and is expressed in organs and cells relevant for drug delivery, such as liver, kidneys and blood cells. The structural pattern of this transporter and the effect of some polymorphisms on it has recently been reported . Similarly, some variants have shown to differentially modulate the transport of methylated arsenic metabolites and physiological organic anions . In terms of major clinical associations of ABCC4, the TT genotype for rs1751034 SNP in ABCC4 has been associated with increased tenofovir renal clearance and a lower intracellular tenofovir diphosphate in HIV patients [45,46]. The lack of further research and the low but significant p-value (0.4–0.5) may be responsible for having only a level 2B of evidence.
ABCG2, also known as BCRP, MXR or MCF-7, is an ABC half transporter involved in the transport or substances such as chemotherapeutics, antivirals, antibiotics, and flavonoids . Several ABCG2 DNA variants, such as Phe489Leu (c.1465 T> C) and Tyr469Ala have been shown to reduce its protein expression by affecting the effect of drugs that interacts with ABCG2 . However, another variant, rs2231142 (Gln141Glu), is the most relevant for the pharmacogenetics of ABCG2. The T allele of this SNP is associated with a decrease in allopurinol response in patients with gout. People with GG genotype may have a better response when treated with allopurinol and may require a lower dose compared to patients with the GT or TT genotypes [47,48].
Unlike patients taking allopurinol, those taking rosuvastatin and carrying the T allele for rs2231142 SNP in ABCG2 may have a higher plasma concentration of the drug and a greater response determined by a higher reduction in low-density lipoprotein cholesterol in hypercholesterolemia and myocardial infarction [50,51,52,53,54,55,56,57,58]. These associations have a level of evidence 2B in PharmGKB.
4. Ways to Improve Clinical Implementation of ABC Transporters Pharmacogenetics
Current knowledge of the pharmacogenetics of ABC transporters can be improved in three different ways: first, by studying more known variants; second, by using genome-wide techniques that can also discover new variants; and third, by increasing the evidences already stablished.
As for the first point, searching for potentially relevant DNA variants in ABC transporter genes in the Exome Aggregation Consortium (ExAC) browser (http://exac.broadinstitute.org/) may give us a view of possible polymorphisms to study in future work . Supplemental Table S1 presents a search for variants in ExAC with a minor allele frequency higher than 1% in a general population of 60,706 humans and located in coding or regulatory regions (5′UTR, 3′UTR or splice regions) in ABC transporter genes with clinical annotations in PharmGKB. Among these variants, we find the most studied SNPs in pharmacogenetics of ABC transporters. However, not all of these variants have been included in previous studies, which opens the door to their selection and analysis as good candidates in the future.
The second way is the use of next generation sequencing and genome-wide association studies. This type of analysis is also contributing and will contribute to increasing the number of known pharmacogenetic variants in ABC transporters .
Probably, the quickest option to improve the clinical implementation of ABC-transporter pharmacogenetics is to increase studies in variants with level of evidence 1B, 2A and 2B. The lack of strong evidence of association of genetic variants with drug response has been one of the main reasons why clinical implementation of pharmacogenetics has experienced many difficulties . Even, when solid evidence is found, its clinical usefulness is often questioned.
All these ways together are the best options to generate guidelines to help for the clinical implementation of ABC transporters pharmacogenetics.
5. Conclusions and Perspectives
Obviously, there are many more studies relating DNA variants in ABC-transporter genes associated with drug response or toxicity than those shown in this review. However, these associations do not have a high evidence level because most of the time results are contradictory. There are findings showing the association of a variant with a specific drug response or induced-toxicity, and others with the same credibility that show the lack of association, or worse, that show the same association but with the opposite allele. For instance, the T alleles in ABCB1 variants rs1045642, rs1128503 and rs2032582 SNPs have been associated with both a lower and a higher risk of severe irinotecan-induced toxicity [80,81,82]. Examples like this are very common in pharmacogenetics in general, and in ABC-transporters in particular.
Nevertheless, the successful example of CFTR variants and ivacaftor treatment, and the promising biomarkers such as those rated as level 2A and B by PharmGKB, allow us to be optimistic in the future. We are required to rise knowledge of these 2A–2B biomarkers to advance clinical implementation. In addition, the expected amount of information that come with massive sequencing programs under development in several countries could boost pharmacogenetic knowledge of ABC transporters. Finally, future meta-analysis and clinical trials could help further develop the implementation of ABC-transporters pharmacogenetics.
The following are available online at https://www.mdpi.com/2075-4426/8/4/40/s1, Table S1: Main variants in the ABC transporter genes with the greatest potential interest in pharmacogenetics.
This study was partially supported by the Ministry of Economy and Competitiveness ISCIII-FIS grant CPII13/00008. The study was co-funded by ERDF Funds (FEDER) from the European Commission, “A way of making Europe”.
The author thanks Alicia Lopez for English corrections and Xandra García-González for critical reading of the manuscript.
Conflicts of Interest
The authors declare no conflict of interest.
- Zaiou, M.; Bakillah, A. Epigenetic Regulation of ATP-Binding Cassette Protein A1 (ABCA1) Gene Expression: A New Era to Alleviate Atherosclerotic Cardiovascular Disease. Diseases 2018, 6. [Google Scholar] [CrossRef]
- Mijac, D.; Vukovic-Petrovic, I.; Mijac, V.; Perovic, V.; Milic, N.; Djuranovic, S.; Bojic, D.; Popovic, D.; Culafic, D.; Krstic, M.; et al. MDR1 gene polymorphisms are associated with ulcerative colitis in a cohort of Serbian patients with inflammatory bowel disease. PLoS ONE 2018, 13, e0194536. [Google Scholar] [CrossRef]
- Aikawa, T.; Holm, M.-L.; Kanekiyo, T. ABCA7 and Pathogenic Pathways of Alzheimer’s Disease. Brain Sci. 2018, 8. [Google Scholar] [CrossRef]
- Schumacher, T.; Benndorf, R.A. ABC Transport Proteins in Cardiovascular Disease—A Brief Summary. Molecules 2017, 22, 589. [Google Scholar] [CrossRef]
- Benadiba, M.; Maor, Y. Importance of ABC Transporters in Drug Development. Curr. Pharm. Des. 2016, 22, 5817–5829. [Google Scholar] [CrossRef]
- Robey, R.W.; Pluchino, K.M.; Hall, M.D.; Fojo, A.T.; Bates, S.E.; Gottesman, M.M. Revisiting the role of ABC transporters in multidrug-resistant cancer. Nat. Rev. Cancer 2018, 18, 452–464. [Google Scholar] [CrossRef]
- Fohner, A.E.; Brackman, D.J.; Giacomini, K.M.; Altman, R.B.; Klein, T.E. PharmGKB summary: Very important pharmacogene information for ABCG2. Pharmacogenet. Genom. 2017, 27, 420–427. [Google Scholar] [CrossRef]
- Carter, S.C.; McKone, E.F. Pharmacogenetics of cystic fibrosis treatment. Pharmacogenomics 2016, 17, 1453–1463. [Google Scholar] [CrossRef]
- Dean, M.; Hamon, Y.; Chimini, G. The human ATP-binding cassette (ABC) transporter superfamily. J. Lipid Res. 2001, 42, 1007–1017. [Google Scholar] [CrossRef]
- Albrecht, C.; Viturro, E. The ABCA subfamily—Gene and protein structures, functions and associated hereditary diseases. Pflugers Arch. 2007, 453, 581–589. [Google Scholar] [CrossRef]
- Strazielle, N.; Ghersi-Egea, J.-F. Efflux transporters in blood-brain interfaces of the developing brain. Front. Neurosci. 2015, 9, 21. [Google Scholar] [CrossRef]
- Ghanem, C.I.; Manautou, J.E. Modulation of Hepatic MRP3/ABCC3 by Xenobiotics and Pathophysiological Conditions: Role in Drug Pharmacokinetics. Curr. Med. Chem. 2018. [Google Scholar] [CrossRef]
- Okamoto, T.; Kawaguchi, K.; Watanabe, S.; Agustina, R.; Ikejima, T.; Ikeda, K.; Nakano, M.; Morita, M.; Imanaka, T. Characterization of human ATP-binding cassette protein subfamily D reconstituted into proteoliposomes. Biochem. Biophys. Res. Commun. 2018, 496, 1122–1127. [Google Scholar] [CrossRef]
- Woodward, O.M.; Kottgen, A.; Kottgen, M. ABCG transporters and disease. FEBS J. 2011, 278, 3215–3225. [Google Scholar] [CrossRef]
- Yee, S.W.; Brackman, D.J.; Ennis, E.A.; Sugiyama, Y.; Kamdem, L.K.; Blanchard, R.; Galetin, A.; Zhang, L.; Giacomini, K.M. Influence of Transporter Polymorphisms on Drug Disposition and Response: A Perspective from the International Transporter Consortium. Clin. Pharmacol. Ther. 2018. [Google Scholar] [CrossRef]
- Whirl-Carrillo, M.; McDonagh, E.M.; Hebert, J.M.; Gong, L.; Sangkuhl, K.; Thorn, C.F.; Altman, R.B.; Klein, T.E. Pharmacogenomics knowledge for personalized medicine. Clin. Pharmacol. Ther. 2012, 92, 414–417. [Google Scholar] [CrossRef]
- McDonagh, E.M.; Clancy, J.P.; Altman, R.B.; Klein, T.E. PharmGKB summary: Very important pharmacogene information for CFTR. Pharmacogenet. Genom. 2015, 25, 149–156. [Google Scholar] [CrossRef]
- Aminkeng, F.; Ross, C.J.D.; Rassekh, S.R.; Hwang, S.; Rieder, M.J.; Bhavsar, A.P.; Smith, A.; Sanatani, S.; Gelmon, K.A.; Bernstein, D.; et al. Recommendations for genetic testing to reduce the incidence of anthracycline-induced cardiotoxicity. Br. J. Clin. Pharmacol. 2016, 82, 683–695. [Google Scholar] [CrossRef]
- Clancy, J.P.; Johnson, S.G.; Yee, S.W.; McDonagh, E.M.; Caudle, K.E.; Klein, T.E.; Cannavo, M.; Giacomini, K.M. Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for ivacaftor therapy in the context of CFTR genotype. Clin. Pharmacol. Ther. 2014, 95, 592–597. [Google Scholar] [CrossRef]
- Van Goor, F.; Yu, H.; Burton, B.; Hoffman, B.J. Effect of ivacaftor on CFTR forms with missense mutations associated with defects in protein processing or function. J. Cyst. Fibros. 2014, 13, 29–36. [Google Scholar] [CrossRef]
- Fiegenbaum, M.; da Silveira, F.R.; Van der Sand, C.R.; Van der Sand, L.C.; Ferreira, M.E.W.; Pires, R.C.; Hutz, M.H. The role of common variants of ABCB1, CYP3A4, and CYP3A5 genes in lipid-lowering efficacy and safety of simvastatin treatment. Clin. Pharmacol. Ther. 2005, 78, 551–558. [Google Scholar] [CrossRef]
- Becker, M.L.; Visser, L.E.; van Schaik, R.H.N.; Hofman, A.; Uitterlinden, A.G.; Stricker, B.H.C. Common genetic variation in the ABCB1 gene is associated with the cholesterol-lowering effect of simvastatin in males. Pharmacogenomics 2009, 10, 1743–1751. [Google Scholar] [CrossRef]
- Zgheib, N.K.; Akra-Ismail, M.; Aridi, C.; Mahfouz, R.; Abboud, M.R.; Solh, H.; Muwakkit, S.A. Genetic polymorphisms in candidate genes predict increased toxicity with methotrexate therapy in Lebanese children with acute lymphoblastic leukemia. Pharmacogenet. Genom. 2014, 24, 387–396. [Google Scholar] [CrossRef]
- Ciccacci, C.; Borgiani, P.; Ceffa, S.; Sirianni, E.; Marazzi, M.C.; Altan, A.M.D.; Paturzo, G.; Bramanti, P.; Novelli, G.; Palombi, L. Nevirapine-induced hepatotoxicity and pharmacogenetics: A retrospective study in a population from Mozambique. Pharmacogenomics 2010, 11, 23–31. [Google Scholar] [CrossRef]
- Ritchie, M.D.; Haas, D.W.; Motsinger, A.A.; Donahue, J.P.; Erdem, H.; Raffanti, S.; Rebeiro, P.; George, A.L.; Kim, R.B.; Haines, J.L.; et al. Drug transporter and metabolizing enzyme gene variants and nonnucleoside reverse-transcriptase inhibitor hepatotoxicity. Clin. Infect. Dis. 2006, 43, 779–782. [Google Scholar] [CrossRef]
- Haas, D.W.; Bartlett, J.A.; Andersen, J.W.; Sanne, I.; Wilkinson, G.R.; Hinkle, J.; Rousseau, F.; Ingram, C.D.; Shaw, A.; Lederman, M.M.; et al. Pharmacogenetics of nevirapine-associated hepatotoxicity: An Adult AIDS Clinical Trials Group collaboration. Clin. Infect. Dis. 2006, 43, 783–786. [Google Scholar] [CrossRef]
- Anderson, P.L.; Aquilante, C.L.; Gardner, E.M.; Predhomme, J.; McDaneld, P.; Bushman, L.R.; Zheng, J.-H.; Ray, M.; MaWhinney, S. Atazanavir pharmacokinetics in genetically determined CYP3A5 expressors versus non-expressors. J. Antimicrob. Chemother. 2009, 64, 1071–1079. [Google Scholar] [CrossRef]
- Kile, D.A.; MaWhinney, S.; Aquilante, C.L.; Rower, J.E.; Castillo-Mancilla, J.R.; Anderson, P.L. A Population Pharmacokinetic-Pharmacogenetic Analysis of Atazanavir. AIDS Res. Hum. Retrovir. 2012, 28, 1227–1234. [Google Scholar] [CrossRef]
- Choi, E.M.; Lee, M.G.; Lee, S.H.; Choi, K.W.; Choi, S.H. Association of ABCB1 polymorphisms with the efficacy of ondansetron for postoperative nausea and vomiting. Anaesthesia 2010, 65, 996–1000. [Google Scholar] [CrossRef]
- He, H.; Yin, J.-Y.; Xu, Y.-J.; Li, X.; Zhang, Y.; Liu, Z.-G.; Zhou, F.; Zhai, M.; Li, Y.; Li, X.-P.; et al. Association of ABCB1 polymorphisms with the efficacy of ondansetron in chemotherapy-induced nausea and vomiting. Clin. Ther. 2014, 36, 1242–1252.e2. [Google Scholar] [CrossRef]
- Aarnoudse, A.-J.L.H.J.; Dieleman, J.P.; Visser, L.E.; Arp, P.P.; van der Heiden, I.P.; van Schaik, R.H.N.; Molokhia, M.; Hofman, A.; Uitterlinden, A.G.; Stricker, B.H.C. Common ATP-binding cassette B1 variants are associated with increased digoxin serum concentration. Pharmacogenet. Genom. 2008, 18, 299–305. [Google Scholar] [CrossRef]
- Kurata, Y.; Ieiri, I.; Kimura, M.; Morita, T.; Irie, S.; Urae, A.; Ohdo, S.; Ohtani, H.; Sawada, Y.; Higuchi, S.; et al. Role of human MDR1 gene polymorphism in bioavailability and interaction of digoxin, a substrate of P-glycoprotein. Clin. Pharmacol. Ther. 2002, 72, 209–219. [Google Scholar] [CrossRef]
- Hoffmeyer, S.; Burk, O.; von Richter, O.; Arnold, H.P.; Brockmoller, J.; Johne, A.; Cascorbi, I.; Gerloff, T.; Roots, I.; Eichelbaum, M.; et al. Functional polymorphisms of the human multidrug-resistance gene: Multiple sequence variations and correlation of one allele with P-glycoprotein expression and activity in vivo. Proc. Natl. Acad. Sci. USA 2000, 97, 3473–3478. [Google Scholar] [CrossRef]
- Campa, D.; Gioia, A.; Tomei, A.; Poli, P.; Barale, R. Association of ABCB1/MDR1 and OPRM1 gene polymorphisms with morphine pain relief. Clin. Pharmacol. Ther. 2008, 83, 559–566. [Google Scholar] [CrossRef]
- Lotsch, J.; von Hentig, N.; Freynhagen, R.; Griessinger, N.; Zimmermann, M.; Doehring, A.; Rohrbacher, M.; Sittl, R.; Geisslinger, G. Cross-sectional analysis of the influence of currently known pharmacogenetic modulators on opioid therapy in outpatient pain centers. Pharmacogenet. Genom. 2009, 19, 429–436. [Google Scholar] [CrossRef]
- Zhao, Q.; Sun, J.; Tao, Y.; Wang, S.; Jiang, C.; Zhu, Y.; Yu, F.; Zhu, J. A logistic equation to determine the validity of tramadol from related gene polymorphisms and psychological factors. Pharmacogenomics 2014, 15, 487–495. [Google Scholar] [CrossRef]
- Candiotti, K.; Yang, Z.; Xue, L.; Zhang, Y.; Rodriguez, Y.; Wang, L.; Hao, S.; Gitlin, M. Single-nucleotide polymorphism C3435T in the ABCB1 gene is associated with opioid consumption in postoperative pain. Pain Med. 2013, 14, 1977–1984. [Google Scholar] [CrossRef]
- Dzambazovska-Trajkovska, V.; Nojkov, J.; Kartalov, A.; Kuzmanovska, B.; Spiroska, T.; Seljmani, R.; Trajkovski, G.; Matevska-Geshkovska, N.; Dimovski, A. Association of Single-Nucleotide Polymorhism C3435T in the ABCB1 Gene with Opioid Sensitivity in Treatment of Postoperative Pain. Prilozi 2016, 37, 73–80. [Google Scholar] [CrossRef]
- Mouly, S.; Bloch, V.; Peoc’h, K.; Houze, P.; Labat, L.; Ksouda, K.; Simoneau, G.; Decleves, X.; Bergmann, J.F.; Scherrmann, J.-M.; et al. Methadone dose in heroin-dependent patients: Role of clinical factors, comedications, genetic polymorphisms and enzyme activity. Br. J. Clin. Pharmacol. 2015, 79, 967–977. [Google Scholar] [CrossRef]
- Hajj, A.; Halepian, L.; Osta, N.E.; Chahine, G.; Kattan, J.; Rabbaa Khabbaz, L. OPRM1 c.118A>G Polymorphism and Duration of Morphine Treatment Associated with Morphine Doses and Quality-of-Life in Palliative Cancer Pain Settings. Int. J. Mol. Sci. 2017, 18. [Google Scholar] [CrossRef]
- Choi, S.-W.; Lam, D.M.H.; Wong, S.S.C.; Shiu, H.H.C.; Wang, A.X.M.; Cheung, C.-W. Effects of Single Nucleotide Polymorphisms on Surgical and Postsurgical Opioid Requirements: A Systematic Review and Meta-Analysis. Clin. J. Pain 2017, 33, 1117–1130. [Google Scholar] [CrossRef]
- Naito, T.; Takashina, Y.; Yamamoto, K.; Tashiro, M.; Ohnishi, K.; Kagawa, Y.; Kawakami, J. CYP3A5*3 affects plasma disposition of noroxycodone and dose escalation in cancer patients receiving oxycodone. J. Clin. Pharmacol. 2011, 51, 1529–1538. [Google Scholar] [CrossRef] [PubMed]
- Bastami, S.; Gupta, A.; Zackrisson, A.-L.; Ahlner, J.; Osman, A.; Uppugunduri, S. Influence of UGT2B7, OPRM1 and ABCB1 gene polymorphisms on postoperative morphine consumption. Basic Clin. Pharmacol. Toxicol. 2014, 115, 423–431. [Google Scholar] [CrossRef]
- Aubrun, F.; Zahr, N.; Langeron, O.; Boccheciampe, N.; Cozic, N.; Belin, L.; Hulot, J.-S.; Khiami, F.; Riou, B. Opioid-related genetic polymorphisms do not influence postoperative opioid requirement: A prospective observational study. Eur. J. Anaesthesiol. 2018, 35, 496–504. [Google Scholar] [CrossRef] [PubMed]
- Kiser, J.J.; Carten, M.L.; Aquilante, C.L.; Anderson, P.L.; Wolfe, P.; King, T.M.; Delahunty, T.; Bushman, L.R.; Fletcher, C. V The effect of lopinavir/ritonavir on the renal clearance of tenofovir in HIV-infected patients. Clin. Pharmacol. Ther. 2008, 83, 265–272. [Google Scholar] [CrossRef]
- Kiser, J.J.; Aquilante, C.L.; Anderson, P.L.; King, T.M.; Carten, M.L.; Fletcher, C.V. Clinical and genetic determinants of intracellular tenofovir diphosphate concentrations in HIV-infected patients. J. Acquir. Immune Defic. Syndr. 2008, 47, 298–303. [Google Scholar] [CrossRef]
- Wen, C.C.; Yee, S.W.; Liang, X.; Hoffmann, T.J.; Kvale, M.N.; Banda, Y.; Jorgenson, E.; Schaefer, C.; Risch, N.; Giacomini, K.M. Genome-wide association study identifies ABCG2 (BCRP) as an allopurinol transporter and a determinant of drug response. Clin. Pharmacol. Ther. 2015, 97, 518–525. [Google Scholar] [CrossRef]
- Roberts, R.L.; Wallace, M.C.; Phipps-Green, A.J.; Topless, R.; Drake, J.M.; Tan, P.; Dalbeth, N.; Merriman, T.R.; Stamp, L.K. ABCG2 loss-of-function polymorphism predicts poor response to allopurinol in patients with gout. Pharmacogenom. J. 2017, 17, 201–203. [Google Scholar] [CrossRef] [PubMed]
- Wright, D.F.B.; Dalbeth, N.; Phipps-Green, A.J.; Merriman, T.R.; Barclay, M.L.; Drake, J.; Tan, P.; Horne, A.; Stamp, L.K. The impact of diuretic use and ABCG2 genotype on the predictive performance of a published allopurinol dosing tool. Br. J. Clin. Pharmacol. 2018, 84, 937–943. [Google Scholar] [CrossRef]
- Tomlinson, B.; Hu, M.; Lee, V.W.Y.; Lui, S.S.H.; Chu, T.T.W.; Poon, E.W.M.; Ko, G.T.C.; Baum, L.; Tam, L.S.; Li, E.K. ABCG2 polymorphism is associated with the low-density lipoprotein cholesterol response to rosuvastatin. Clin. Pharmacol. Ther. 2010, 87, 558–562. [Google Scholar] [CrossRef]
- Hu, M.; Lui, S.S.H.; Mak, V.W.L.; Chu, T.T.W.; Lee, V.W.Y.; Poon, E.W.M.; Tsui, T.K.C.; Ko, G.T.C.; Baum, L.; Tam, L.-S.; et al. Pharmacogenetic analysis of lipid responses to rosuvastatin in Chinese patients. Pharmacogenet. Genom. 2010, 20, 634–637. [Google Scholar] [CrossRef] [PubMed]
- Zhang, W.; Yu, B.-N.; He, Y.-J.; Fan, L.; Li, Q.; Liu, Z.-Q.; Wang, A.; Liu, Y.-L.; Tan, Z.-R.; Jiang, F.; et al. Role of BCRP 421C>A polymorphism on rosuvastatin pharmacokinetics in healthy Chinese males. Clin. Chim. Acta 2006, 373, 99–103. [Google Scholar] [CrossRef] [PubMed]
- Keskitalo, J.E.; Zolk, O.; Fromm, M.F.; Kurkinen, K.J.; Neuvonen, P.J.; Niemi, M. ABCG2 polymorphism markedly affects the pharmacokinetics of atorvastatin and rosuvastatin. Clin. Pharmacol. Ther. 2009, 86, 197–203. [Google Scholar] [CrossRef] [PubMed]
- Lee, H.-K.; Hu, M.; Lui, S.S.; Ho, C.-S.; Wong, C.-K.; Tomlinson, B. Effects of polymorphisms in ABCG2, SLCO1B1, SLC10A1 and CYP2C9/19 on plasma concentrations of rosuvastatin and lipid response in Chinese patients. Pharmacogenomics 2013, 14, 1283–1294. [Google Scholar] [CrossRef] [PubMed]
- DeGorter, M.K.; Tirona, R.G.; Schwarz, U.I.; Choi, Y.-H.; Dresser, G.K.; Suskin, N.; Myers, K.; Zou, G.; Iwuchukwu, O.; Wei, W.-Q.; et al. Clinical and pharmacogenetic predictors of circulating atorvastatin and rosuvastatin concentrations in routine clinical care. Circ. Cardiovasc. Genet. 2013, 6, 400–408. [Google Scholar] [CrossRef] [PubMed]
- Birmingham, B.K.; Bujac, S.R.; Elsby, R.; Azumaya, C.T.; Zalikowski, J.; Chen, Y.; Kim, K.; Ambrose, H.J. Rosuvastatin pharmacokinetics and pharmacogenetics in Caucasian and Asian subjects residing in the United States. Eur. J. Clin. Pharmacol. 2015, 71, 329–340. [Google Scholar] [CrossRef] [PubMed]
- Bailey, K.M.; Romaine, S.P.R.; Jackson, B.M.; Farrin, A.J.; Efthymiou, M.; Barth, J.H.; Copeland, J.; McCormack, T.; Whitehead, A.; Flather, M.D.; et al. Hepatic metabolism and transporter gene variants enhance response to rosuvastatin in patients with acute myocardial infarction: The GEOSTAT-1 Study. Circ. Cardiovasc. Genet. 2010, 3, 276–285. [Google Scholar] [CrossRef] [PubMed]
- Kashihara, Y.; Ieiri, I.; Yoshikado, T.; Maeda, K.; Fukae, M.; Kimura, M.; Hirota, T.; Matsuki, S.; Irie, S.; Izumi, N.; et al. Small-Dosing Clinical Study: Pharmacokinetic, Pharmacogenomic (SLCO2B1 and ABCG2), and Interaction (Atorvastatin and Grapefruit Juice) Profiles of 5 Probes for OATP2B1 and BCRP. J. Pharm. Sci. 2017, 106, 2688–2694. [Google Scholar] [CrossRef]
- Hwang, T.-C.; Kirk, K.L. The CFTR ion channel: Gating, regulation, and anion permeation. Cold Spring Harb. Perspect. Med. 2013, 3, a009498. [Google Scholar] [CrossRef] [PubMed]
- Hwang, T.-C.; Yeh, J.-T.; Zhang, J.; Yu, Y.-C.; Yeh, H.-I.; Destefano, S. Structural mechanisms of CFTR function and dysfunction. J. Gen. Physiol. 2018, 150, 539–570. [Google Scholar] [CrossRef]
- Schwab, M.; Eichelbaum, M.; Fromm, M.F. Genetic polymorphisms of the human MDR1 drug transporter. Annu. Rev. Pharmacol. Toxicol. 2003, 43, 285–307. [Google Scholar] [CrossRef] [PubMed]
- Kim, R.B.; Leake, B.F.; Choo, E.F.; Dresser, G.K.; Kubba, S.V.; Schwarz, U.I.; Taylor, A.; Xie, H.G.; McKinsey, J.; Zhou, S.; et al. Identification of functionally variant MDR1 alleles among European Americans and African Americans. Clin. Pharmacol. Ther. 2001, 70, 189–199. [Google Scholar] [CrossRef] [PubMed]
- Chinn, L.W.; Kroetz, D.L. ABCB1 pharmacogenetics: Progress, pitfalls, and promise. Clin. Pharmacol. Ther. 2007, 81, 265–269. [Google Scholar] [CrossRef] [PubMed]
- Hodges, L.M.; Markova, S.M.; Chinn, L.W.; Gow, J.M.; Kroetz, D.L.; Klein, T.E.; Altman, R.B. Very important pharmacogene summary: ABCB1 (MDR1, P-glycoprotein). Pharmacogenet. Genom. 2011, 21, 152–161. [Google Scholar] [CrossRef] [PubMed]
- Wolking, S.; Schaeffeler, E.; Lerche, H.; Schwab, M.; Nies, A.T. Impact of Genetic Polymorphisms of ABCB1 (MDR1, P-Glycoprotein) on Drug Disposition and Potential Clinical Implications: Update of the Literature. Clin. Pharmacokinet. 2015, 54, 709–735. [Google Scholar] [CrossRef] [PubMed]
- Choi, H.Y.; Bae, K.-S.; Cho, S.-H.; Ghim, J.-L.; Choe, S.; Jung, J.A.; Jin, S.-J.; Kim, H.-S.; Lim, H.-S. Impact of CYP2D6, CYP3A5, CYP2C19, CYP2A6, SLCO1B1, ABCB1, and ABCG2 gene polymorphisms on the pharmacokinetics of simvastatin and simvastatin acid. Pharmacogenet. Genom. 2015, 25, 595–608. [Google Scholar] [CrossRef] [PubMed]
- Suthandiram, S.; Gan, G.-G.; Zain, S.M.; Bee, P.-C.; Lian, L.-H.; Chang, K.-M.; Ong, T.-C.; Mohamed, Z. Effect of polymorphisms within methotrexate pathway genes on methotrexate toxicity and plasma levels in adults with hematological malignancies. Pharmacogenomics 2014, 15, 1479–1494. [Google Scholar] [CrossRef] [PubMed]
- Gregers, J.; Green, H.; Christensen, I.J.; Dalhoff, K.; Schroeder, H.; Carlsen, N.; Rosthoej, S.; Lausen, B.; Schmiegelow, K.; Peterson, C. Polymorphisms in the ABCB1 gene and effect on outcome and toxicity in childhood acute lymphoblastic leukemia. Pharmacogenom. J. 2015, 15, 372–379. [Google Scholar] [CrossRef] [PubMed]
- Solhaug, V.; Molden, E. Individual variability in clinical effect and tolerability of opioid analgesics—Importance of drug interactions and pharmacogenetics. Scand. J. Pain 2017, 17, 193–200. [Google Scholar] [CrossRef] [PubMed]
- Hung, C.-C.; Chiou, M.-H.; Huang, B.-H.; Hsieh, Y.-W.; Hsieh, T.-J.; Huang, C.-L.; Lane, H.-Y. Impact of genetic polymorphisms in ABCB1, CYP2B6, OPRM1, ANKK1 and DRD2 genes on methadone therapy in Han Chinese patients. Pharmacogenomics 2011, 12, 1525–1533. [Google Scholar] [CrossRef]
- Chu, Y.-H.; Li, H.; Tan, H.S.; Koh, V.; Lai, J.; Phyo, W.M.; Choudhury, Y.; Kanesvaran, R.; Chau, N.M.; Toh, C.K.; et al. Association of ABCB1 and FLT3 Polymorphisms with Toxicities and Survival in Asian Patients Receiving Sunitinib for Renal Cell Carcinoma. PLoS ONE 2015, 10, e0134102. [Google Scholar] [CrossRef] [PubMed]
- Diekstra, M.H.M.; Swen, J.J.; Boven, E.; Castellano, D.; Gelderblom, H.; Mathijssen, R.H.J.; Rodríguez-Antona, C.; García-Donas, J.; Rini, B.I.; Guchelaar, H.-J. CYP3A5 and ABCB1 Polymorphisms as Predictors for Sunitinib Outcome in Metastatic Renal Cell Carcinoma. Eur. Urol. 2015, 68, 621–629. [Google Scholar] [CrossRef]
- Chantemargue, B.; Di Meo, F.; Berka, K.; Picard, N.; Arnion, H.; Essig, M.; Marquet, P.; Otyepka, M.; Trouillas, P. Structural patterns of the human ABCC4/MRP4 exporter in lipid bilayers rationalize clinically observed polymorphisms. Pharmacol. Res. 2018. [Google Scholar] [CrossRef] [PubMed]
- Banerjee, M.; Marensi, V.; Conseil, G.; Le, X.C.; Cole, S.P.C.; Leslie, E.M. Polymorphic variants of MRP4/ABCC4 differentially modulate the transport of methylated arsenic metabolites and physiological organic anions. Biochem. Pharmacol. 2016, 120, 72–82. [Google Scholar] [CrossRef] [PubMed]
- Robey, R.W.; Ierano, C.; Zhan, Z.; Bates, S.E. The challenge of exploiting ABCG2 in the clinic. Curr. Pharm. Biotechnol. 2011, 12, 595–608. [Google Scholar] [CrossRef] [PubMed]
- Ripperger, A.; Krischer, A.; Robaa, D.; Sippl, W.; Benndorf, R.A. Pharmacogenetic Aspects of the Interaction of AT1 Receptor Antagonists With ATP-Binding Cassette Transporter ABCG2. Front. Pharmacol. 2018, 9, 463. [Google Scholar] [CrossRef] [PubMed]
- Lek, M.; Karczewski, K.J.; Minikel, E.V.; Samocha, K.E.; Banks, E.; Fennell, T.; O’Donnell-Luria, A.H.; Ware, J.S.; Hill, A.J.; Cummings, B.B.; et al. Exome Aggregation Consortium Analysis of protein-coding genetic variation in 60,706 humans. Nature 2016, 536, 285–291. [Google Scholar] [CrossRef]
- Yamamoto, Y.; Tsunedomi, R.; Fujita, Y.; Otori, T.; Ohba, M.; Kawai, Y.; Hirata, H.; Matsumoto, H.; Haginaka, J.; Suzuki, S.; et al. Pharmacogenetics-based area-under-curve model can predict efficacy and adverse events from axitinib in individual patients with advanced renal cell carcinoma. Oncotarget 2018, 9, 17160–17170. [Google Scholar] [CrossRef]
- García-González, X.; Cabaleiro, T.; Herrero, M.J.; McLeod, H.; López-Fernández, L.A. Clinical implementation of pharmacogenetics. Drug Metab. Pers. Ther. 2016, 31. [Google Scholar] [CrossRef]
- Glimelius, B.; Garmo, H.; Berglund, A.; Fredriksson, L.A.; Berglund, M.; Kohnke, H.; Byström, P.; Sørbye, H.; Wadelius, M. Prediction of irinotecan and 5-fluorouracil toxicity and response in patients with advanced colorectal cancer. Pharmacogenom. J. 2011, 11, 61–71. [Google Scholar] [CrossRef]
- Cortejoso, L.; García, M.I.; García-Alfonso, P.; González-Haba, E.; Escolar, F.; Sanjurjo, M.; López-Fernández, L.A. Differential toxicity biomarkers for irinotecan- and oxaliplatin-containing chemotherapy in colorectal cancer. Cancer Chemother. Pharmacol. 2013, 71. [Google Scholar] [CrossRef]
- Salvador-Martín, S.; García-González, X.; García, M.I.; Blanco, C.; García-Alfonso, P.; Robles, L.; Grávalos, C.; Pachón, V.; Longo, F.; Martínez, V.; et al. Clinical utility of ABCB1 genotyping for preventing toxicity in treatment with irinotecan. Pharmacol. Res. 2018, 136, 133–139. [Google Scholar] [CrossRef] [PubMed]
Table 1. ATP-binding cassette (ABC) transporter variants with a level of evidence from 1A to 2B.
|2A||rs2032582||ABCB1||Simvastatin||Efficacy||16321621 , 19891551 |
|2A||rs1045642||ABCB1||Nevirapine||Toxicity||20017669 , 16912956 , 16912957 |
|2A||ABCB1*1, ABCB1*2||ABCB1||Atazanavir||Toxicity/PK||19710077 |
|2A||rs1045642||ABCB1||Digoxin||Others||18334914 , 12189368 , 10716719 |
|2B||rs1045642||ABCB1||Fentanyl, methadone, morphine, opioids, oxycodone, tramadol||Dosage/efficacy||[34,35,36,37,38,39,40,41,42,43,44]|
|2B||rs1751034||ABCC4||Tenofovir||Pk||17597712 , 18398970 |
|2B||rs2231142||ABCG2||Allopurinol||Dosage/efficacy||25676789 , 26810134 , 29341237 |
|2B||rs2231142||ABCG2||Rosuvastatin||Efficacy||20130569 , 20679960 , 16784736 , 19474787 , 23930675 , 23930675 , 23876492 , 25630984 , 20207952 , 28322941 |
Table 2. CFTR DNA variants included in the drug label by different drug regulatory agencies.
|Amino-Acid Change||SNP ID||FDA||EMA||HCSC|
SNP: single nucleotide polymorphisms; EMA: European Medicines Agency; FDA: Food and drug administration; HCSC: Health Canada (Santé Canada).
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