The Potential of Pharmacogenomics to Advance Kidney Disease Treatment

Identifying factors underlying the variable and often unpredictable response to drugs remains one of the most complex challenges facing modern therapeutics (¹). Commonly recognized factors for drug response variability include age, sex, ancestry, concomitant drug interactions, and underlying liver or kidney disease. Pharmacogenomics contributes to this effort by examining the role of genetic variation in drug response. The field seeks to provide information allowing clinicians to maximize drug response while minimizing adverse drug reactions in an individual patient (²) and is the core of the Precision Medicine Initiative goal “to provide the right drug, at the right dose, for the right patient” (³). To guide actions, the Food and Drug Administration has listed 238 biomarker/drug pairs with pharmacogenomic information in their drug labeling; the term biomarker includes polymorphisms and mutations, and some labels include specific actions to be taken on the basis of genotype. (https://www.fda.gov/drugs/scienceresearch/researchareas/pharmacogenetics/ucm083378.htm).

Pharmacogenomics has met its goals for certain drugs. A prime example is clopidogrel, an antiplatelet drug routinely used after placing coronary stents. Clopidogrel is a prodrug metabolized to its active form by the enzyme CYP2C19 (⁴). Loss of function variants in CYP2C19 lead to greatly decreased activity of the enzyme, less active drug, and increased risk of thrombosis (⁵). For patients carrying such variants, an alternative drug (prasugrel) can be used. In kidney disease, pharmacogenomic studies have been limited, although the commonly used immunosuppressive drug tacrolimus has been examined in kidney transplant recipients. Tacrolimus is a calcineurin inhibitor that is largely metabolized by the cytochrome p450 enzymes CYP3A4 and -3A5. A single-nucleotide polymorphism (SNP) in CYP3A5 (rs776746) leads to truncated protein and thus, decreased expression of CYP3A5 protein (⁶). Individuals with at least one functional copy require higher tacrolimus doses to achieve the same tacrolimus blood concentration as those homozygous for nonexpression (⁷). Thus, knowing the genotype ahead of time leads to better selection of the initial tacrolimus dose. However, despite advances in our understanding of the pharmacogenomics of immunosuppressant drugs, studies in patients with CKD on maintenance dialysis have been scarce.

Investigation of drugs commonly given to patients with CKD on maintenance dialysis is important and needed to better personalize the therapies used to treat the underlying kidney disease and its complications, such as altered bone mineral metabolism. In this issue of the Clinical Journal of the American Society of Nephrology, Moe et al. (⁸) used a candidate gene approach to examine SNPs in the gene encoding the calcium-sensing receptor (CASR) and their association with drug response to cinacalcet, a medication used to treat secondary hyperparathyroidism. Cinacalcet is a calcimimetic that allosterically activates the CASR and decreases parathyroid hormone, calcium, and phosphorus in patients on maintenance dialysis (⁹). The population in this study is from the Evaluation of Cinacalcet Hydrochloride Therapy to Lower Cardiovascular Events Trial, in which 3883 patients on maintenance hemodialysis with moderate to severe secondary hyperparathyroidism were randomized to receive cinacalcet or placebo (while continuing conventional therapy) (¹⁰). In the primary trial, 24% of placebo- and 12% of cinacalcet-treated patients continued to have severe hyperparathyroidism, indicating that a portion of patients were clinically unresponsive to cinacalcet add-on therapy. The authors hypothesized that underlying genetic variability in the CASR gene was associated with biochemical and clinical phenotypes of secondary hyperparathyroidism and examined this using a candidate gene association study of 18 CASR SNPs. Because of concerns for confounding by ancestry, the study population was divided into whites (n=1067) and blacks (n=405). The primary phenotypes tested were biochemical bone metabolism markers, including calcium, parathyroid hormone, fibroblast growth factor 23, and phosphorus, assessed at baseline and as percentage change at 20 weeks; the risk of symptomatic bone fracture was also tested.

Modest associations with CASR SNPs were observed, but the results differed by biochemical marker and ancestry group. When looking at the actual clinical values corresponding to these associations, the difference in values by genotype was also modest. This could be in part because that contribution of genotype was already partially removed with the conventional therapy before cinacalcet was started. For the percentage change phenotypes, one SNP, rs9740, was found to be associated with calcium in both the white and black groups, with a larger decrease in cinacalcet-treated patients, although this association did not reach the set significance threshold. For the fracture phenotype, three SNPs in strong linkage disequilibrium were nominally associated with increased fracture risk in the white group only, and this risk was reduced in patients taking cinacalcet.

Previous studies have shown associations between CASR SNPs and serum ionized calcium in nondialysis populations (¹¹), but there is limited information on patients on maintenance hemodialysis and the pharmacogenomics of cinacalcet. One smaller study of 70 Korean patients on dialysis showed associations of the CASR SNPs rs1042636 and rs1802757 with cinacalcet response (¹²). The SNP rs1042636 was associated with parathyroid hormone in the white group in the study by Moe et al. (⁸), although it was not associated with cinacalcet response. The study by Moe et al. (⁸) is considerably larger, examining a total of 1473 patients, although power was still limited, particularly in the black group, where the minor allele frequencies for some SNPs were small. Despite this limited power, two SNPs were associated with percentage change in fibroblast growth factor 23 and calcium in the black group, and the change was affected by cinacalcet use.

Currently, two broad approaches to pharmacogenomic studies are used. First, on the basis of pharmacokinetic and pharmacodynamic pathways, candidate single or multiple genes are selected in relation to their role on the metabolism or transport of drugs, drug targets, or disease susceptibility (¹). This was the approach chosen by Moe et al. (⁸), and they focused on the CASR. A useful example of this approach that has been translated into clinical practice has been the gene encoding thiopurine methyltransferase. Loss of function variants in this gene cause myelosuppression in patients taking azathioprine (¹³), and therefore, potential users are routinely tested for this genetic variation before receiving a prescription. Second, unbiased approaches can be used, including genome-wide association studies and exome and whole-genome sequencing. In genome-wide association studies, the association between hundreds of thousands to millions of SNPs and complex phenotypes is tested in hundreds to thousands of persons. Sequencing of the entire exome or the whole genome provides the most dense coverage of human variation for research (¹⁴), which could add greater value to its application in clinical care. Although more costly and complex, these last two approaches offer the opportunity to discover unexpected mechanisms or pathways, because they are “hypothesis-free” approaches (¹⁵). It is possible that other not yet clearly defined gene pathways are important to cinacalcet drug response beyond variation in the CASR gene, and an unbiased pharmacogenomics approach might lead to new findings. As the cost of whole-genome sequencing continues to drop, this will become more readily available.

After a genetic association is found, an important next step is to validate the association in an independent study cohort. Although thought provoking, all of the associations found in this study were limited by a lack of a validation cohort, which the authors acknowledged. Another caution in pharmacogenomics is realizing that positive findings represent association and not causation. The polymorphism identified as associated may be located close to a variant that is driving the findings. As a result, further functional or confirmatory studies and tools, such as pathway analyses, are essential to understanding the role of the associated variant and the phenotype of interest (¹⁶).

Despite its promise, pharmacogenetics is still in its early stages, particularly in the setting of kidney disease. Currently, many efforts have focused on identifying “high-risk drugs,” characterized by responses that are significantly influenced by well defined genes (¹⁴). These discoveries have begun and will continue to contribute to therapeutic decision making, but implementing pharmacogenetics into clinical practice continues to face many challenges. One challenge has been the identification of gene-drug pairs that will bring actionable information (¹⁷). Pharmacogeneticists must provide information leading to the use of an alternative drug or a change in dose, ideally implemented at the point of care. The Clinical Pharmacogenomics Implementation Consortium (CPIC) works to identify actionable gene-drug pairs using research-based evidence to produce guidelines useful for the practicing clinician (¹⁸). Currently, the CPIC has 33 guidelines, but only a few have direct relevance to the kidney disease population (¹⁹). An additional challenge is the definition of specific drug response phenotypes. Technology has brought the resources to manage and interrogate genome data robustly (¹⁷), but the identification of clinically important phenotypes is still quite labor intensive. Overcoming these challenges is crucial as we move forward into the Precision Medicine era, but meeting these challenges in kidney disease and beyond is an opportunity to bring better care to the patient sitting in front of you. Although it has limitations, the study by Moe et al. (⁸), the largest study to date to examine CASR variants and cinacalcet response in patients on dialysis, is a step in the right direction to meeting the challenge.

Disclosures

None.