Transporting pharmacogenomics into clinical practice
Authors: Scott L. Friedman
Journal: Journal of Hepatology (2014)

Synergistic interaction between genetics and disease on pravastatin dispositionJournal of HepatologyVol. 61Issue 1PreviewA genome wide association study and multiple pharmacogenetic studies have implicated the hepatic uptake transporter organic anion transporting polypeptide-1B1 (OATP1B1) in the pharmacokinetics and musculoskeletal toxicity of statin drugs. Other OATP uptake transporters can participate in the transport of pravastatin, partially compensating for the loss of OATP1B1 in patients carrying the polymorphism. Non-alcoholic steatohepatitis (NASH) in humans and in a diet-induced rodent model alter the expression of multiple OATP transporters. Full-Text PDF A very interesting and concise study by Clarke et al. in this month’s issue of the Journal highlights important principles about the genetic determinants of drug disposition and toxicity, and the impact of underlying liver disease on adverse events from medications. The findings provide an opportunity to consider the current state of our knowledge about how genetic variations affect drug metabolism (i.e., pharmacogenomics), and to highlight efforts being developed to integrate genetic information into the clinical care of patients. The Clarke study is the most recent work in a series of publications by the authors examining the behavior of the hepatic uptake transporter organic ion transporting polypeptide-1B1 (OATP1B1) in drug disposition. This well-characterized membrane transporter regulates the uptake of organic compounds from the circulation into the hepatocyte where they can be metabolized. OATP1B1 has a large number of genetic variants, or single nucleotide polymorphisms (SNPs), that confer widely variable uptake activity by the transporter [[1]Niemi M. Pasanen M.K. Neuvonen P.J. Organic anion transporting polypeptide 1B1: a genetically polymorphic transporter of major importance for hepatic drug uptake.Pharmacol Rev. 2011; 63: 157-181Crossref PubMed Scopus (510) Google Scholar]; variants that confer reduced uptake lead to slower clearance of substrates, and therefore higher blood levels. That is exactly the case with several single nucleotide polymorphisms (SNPs) that have been linked to increased risk of myopathy associated with statin drugs used to treat hypercholesterolemia [1Niemi M. Pasanen M.K. Neuvonen P.J. Organic anion transporting polypeptide 1B1: a genetically polymorphic transporter of major importance for hepatic drug uptake.Pharmacol Rev. 2011; 63: 157-181Crossref PubMed Scopus (510) Google Scholar, 2Group S.C. Link E. Parish S. Armitage J. Bowman L. Heath S. et al.SLCO1B1 variants and statin-induced myopathy – a genomewide study.N Engl J Med. 2008; 359: 789-799Crossref PubMed Scopus (1656) Google Scholar, 3Wilke R.A. Ramsey L.B. Johnson S.G. Maxwell W.D. McLeod H.L. Voora D. et al.The clinical pharmacogenomics implementation consortium: CPIC guideline for SLCO1B1 and simvastatin-induced myopathy.Clin Pharmacol Ther. 2012; 92: 112-117Crossref PubMed Scopus (269) Google Scholar]. While statins are remarkably safe in general, individuals with these variants can be at up to 20 times greater risk of myopathy. Moreover, because these transporters have hundreds of substrates, altered activity can also lead to many adverse drug-drug interactions, in addition to altering the pharmacokinetics of individual drugs [[1]Niemi M. Pasanen M.K. Neuvonen P.J. Organic anion transporting polypeptide 1B1: a genetically polymorphic transporter of major importance for hepatic drug uptake.Pharmacol Rev. 2011; 63: 157-181Crossref PubMed Scopus (510) Google Scholar]. As hepatologists know well, many patients with hypercholesterolemia who are treated with statins are also obese and have metabolic syndrome complicated by non-alcoholic fatty liver disease (NAFLD) or non-alcoholic steatohepatitis (NASH). These conditions introduce the confounding effect of underlying fatty liver disease, which may further alter hepatic drug metabolism [4Fisher C.D. Lickteig A.J. Augustine L.M. Ranger-Moore J. Jackson J.P. Ferguson S.S. et al.Hepatic cytochrome P450 enzyme alterations in humans with progressive stages of nonalcoholic fatty liver disease.Drug Metab Dispos. 2009; 37: 2087-2094Crossref PubMed Scopus (240) Google Scholar, 5Naik A. Belic A. Zanger U.M. Rozman D. Molecular interactions between NAFLD and xenobiotic metabolism.Front Genet. 2013; 4: 2Crossref PubMed Scopus (48) Google Scholar, 6Buechler C. Weiss T.S. Does hepatic steatosis affect drug metabolizing enzymes in the liver?.Curr Drug Metab. 2011; 12: 24-34Crossref PubMed Scopus (57) Google Scholar]. Additionally, the increased adipose mass in these patients can lead to accumulation of lipophilic drugs in fat cells and hepatocytes. The Clarke study examines how these two important variables, namely the genetic regulation of OATP1B1 activity and the presence of concurrent fatty liver disease, influence the disposition of pravastatin in a mouse model. To do so, they used a mouse in which the murine ortholog of OATP1B1 was genetically knocked out, which was combined with a fatty liver model induced by methionine choline deficient (MCD) diet. While most investigators in the field recognize that the MCD diet is not a particularly faithful model of NASH (in part because there is no insulin resistance), the authors have recently validated the relevance of this model to human disease in a paper in press, by reporting that both NASH in humans and the MCD diet in mice affect transporter activity similarly. As expected, genetic loss of the transporter alone led to increased circulating levels of pravastatin, whereas MCD-induced fatty liver alone did not affect the disposition of the drug. However, when genetic depletion was combined with MCD diet there was an almost threefold increase in plasma area under the curve for the drug (AUC), and a 5–10 fold increase in muscle levels of pravastatin. While these findings raise concern and are certainly relevant to patient management, the overall health benefits of statins are undeniable, and extensive clinical experience with statins has shown the drugs to be remarkably safe. This is true even in patients with metabolic syndrome, who are at heightened risk of cardiovascular events and will benefit from statins. Moreover, statins do not confer an increased risk of hepatotoxicity in fatty liver disease even when transaminases are elevated, which can occur in up to 5% of patients overall [[7]Chalasani N. Aljadhey H. Kesterson J. Murray M.D. Hall S.D. Patients with elevated liver enzymes are not at higher risk for statin hepatotoxicity.Gastroenterology. 2004; 126: 1287-1292Abstract Full Text Full Text PDF PubMed Scopus (366) Google Scholar]. Expert panels have acknowledged that elevations in aminotransferases are a class effect of statins, and the drugs can increase the incidence of liver failure, transplant or death, but these latter catastrophic events are extremely rare and probably idiosyncratic [8Cohen D.E. Anania F.A. Chalasani N. National Lipid Association Statin Safety Task Force Liver Expert P. An assessment of statin safety by hepatologists.Am J Cardiol. 2006; 97: 77C-81CAbstract Full Text Full Text PDF PubMed Scopus (317) Google Scholar, 9Chalasani N. Younossi Z. Lavine J.E. Diehl A.M. Brunt E.M. Cusi K. et al.The diagnosis and management of non-alcoholic fatty liver disease: practice Guideline by the American Association for the Study of Liver Diseases, American College of Gastroenterology, and the American Gastroenterological Association.Hepatology. 2012; 55: 2005-2023Crossref PubMed Scopus (2591) Google Scholar]. Common sense would dictate, however, that while the risk of statin hepatotoxicity is no greater in patients with significant liver disease, if severe idiosyncratic injury occurs in these individuals, their outcomes are likely to be worse than if their livers are normal. The Clarke study raises the larger issue of the extraordinary genetic variability in drug metabolism in all individuals, both healthy patients and those with underlying liver disease. For most drugs we still typically employ a “one dose fits all” schedule, yet this approach is increasingly naïve as evidence mounts that genetics profoundly impact drug metabolism. To address this issue, the NIDDK-sponsored Drug Induced Liver Injury Network (DILIN) has been created in part to uncover genetic determinants that might predispose patients to risk of hepatotoxicity. Elucidating genetically determined idiosyncratic drug toxicity is like finding a needle in a haystack, but it is a tractable problem. It is also possible that rare cases of drug-induced liver injury represents a confluence of risks, including not only genetic variability in metabolism or clearance, but also concurrent drug use, as well as the impact of underlying disease in the liver or other organs. As the hundreds of genetic variants that influence drug metabolism and toxicity are catalogued, we expect this information to somehow translate into improved management of patients. Indeed, this is the promise of “personalized medicine”. But how do we translate complex genetic information into real world systems that are accessible to practitioners? The scale of the infrastructure for such efforts is daunting, yet it is materializing. One effort in the commercial sector is a DNA chip to genotype the many variants of two major isoforms of cytochrome P450 that together metabolize up to 25% of all prescription drugs (http://molecular.roche.com/assays/Pages/AmpliChipCYP450Test.aspx). With the increasing access to affordable whole human genome sequencing, however, much more comprehensive genetic information can now be integrated into these efforts. For example, the National Human Genome Research Institute sponsors the Electronic Medical Records and Genomics (eMERGE) Network, which is a consortium of US medical research institutions intended to “develop, disseminate and apply approaches to research that combine DNA bio-repositories with electronic medical record systems for large-scale, high-throughput genetic research” [[10]Gottesman O. Kuivaniemi H. Tromp G. Faucett W.A. Li R. Manolio T.A. et al.The Electronic Medical Records and Genomics (eMERGE) Network: past, present, and future.Genet Med. 2013; 15: 761-771Abstract Full Text Full Text PDF PubMed Scopus (464) Google Scholar]. Even this effort alone does not solve the problem, as software needs to be developed that not only interprets genetic information, but also translates it into clinical decision support embedded in the electronic medical record, where it can direct practitioners in real time to prescribe those drugs that are safe in their patients, and to specify the correct dose [[11]Overby C.L. Kohane I. Kannry J.L. Williams M.S. Starren J. Bottinger E. et al.Opportunities for genomic clinical decision support interventions.Genet Med. 2013; 15: 817-823Abstract Full Text Full Text PDF PubMed Scopus (52) Google Scholar]. While improving patient safety and outcomes by incorporating genomic information and clinical decision support tools is not imminent, it is clear that the groundwork is being laid for exactly such a cultural shift. Linking the levels of reimbursement to patient outcomes by payors and government health care systems is likely to accelerate this shift. The concentric circles of challenges and opportunities raised by the study of Clarke et al. will steadily and incrementally transport us into a new era of data-driven, individualized medication prescribing. The author declared that he does not have anything to disclose regarding funding or conflict of interest with respect to this manuscript.