Proton pump inhibitors (PPIs) are widely used for acid suppression in the treatment and prevention of many conditions, including gastroesophageal reflux disease, gastric and duodenal ulcers, erosive esophagitis, Helicobacter pylori infection, and pathological hypersecretory conditions. Most PPIs are metabolized primarily by cytochrome P450 2C19 (CYP2C19) into inactive metabolites, and CYP2C19 genotype has been linked to PPI exposure, efficacy, and adverse effects. We summarize the evidence from the literature and provide therapeutic recommendations for PPI prescribing based on CYP2C19 genotype (updates at http://www.cpicpgx.org). The potential benefits of using CYP2C19 genotype data to guide PPI therapy include (i) identifying patients with genotypes predictive of lower plasma exposure and prescribing them a higher dose that will increase the likelihood of efficacy, and (ii) identifying patients on chronic therapy with genotypes predictive of higher plasma exposure and prescribing them a decreased dose to minimize the risk of toxicity that is associated with long‐term PPI use, particularly at higher plasma concentrations.

Introduction: Proton Pump inhibitors (PPIs) are commonly used for a variety of acid related disorders. Despite the overall effectiveness and safety profile of PPIs, some patients do not respond adequately or develop treatment related adverse events. This variable response among patients is in part due to genotype variability of CYP2C19, the gene encoding the CYP450 (CYP2C19) isoenzyme responsible for PPIs metabolism.Areas covered: This article provides an overview of the pharmacokinetics and mechanism of action of the currently available PPIs, including the magnitude of CYPC19 contribution to their metabolism. Additionally, the role of CYP2C19 genetic variability in the therapeutic effectiveness or outcomes of PPI therapy is highlighted in details, to provide supporting evidence for the potential value of CYP2C19 genotype-guided approaches to PPI drug therapy.Expert opinion: There is a large body of evidence describing the impact of CYP2C19 variability on PPIs and its potential role in individualizing PPI therapy, yet, CYP2C19 pharmacogenetics has not been widely implemented into clinical practice. More data are needed but CYP2C19 genotype-guided dosing of PPIs is likely to become increasingly common and is expected to improve clinical outcomes, and minimize side effects related to PPIs.

Recent advances in DNA sequencing technologies are revealing how human genetic variations associate with differential health risks, disease susceptibilities, and drug responses. Such information is now expected to help evaluate individual health risks, design personalized health plans and treat patients with precision. It is still challenging, however, to understand how such genetic variations cause the phenotypic alterations in pathobiologies and treatment response. Human induced pluripotent stem cell (iPSC) technologies are emerging as a promising strategy to fill the knowledge gaps between genetic association studies and underlying molecular mechanisms. Breakthroughs in genome editing technologies and continuous improvement in iPSC differentiation techniques are particularly making this research direction more realistic and practical. Pioneering studies have shown that iPSCs derived from a variety of monogenic diseases can faithfully recapitulate disease phenotypes in vitro when differentiated into disease-relevant cell types. It has been shown possible to partially recapitulate disease phenotypes, even with late onset and polygenic diseases. More recently, iPSCs have been shown to validate effects of disease and treatment-related single nucleotide polymorphisms identified through genome wide association analysis. In this review, we will discuss how iPSC research will further contribute to human health in the coming era of precision medicine.

This cross-sectional study assesses potential opportunities for genotype-guided prescribing in pediatric populations among multiple health systems by examining the prevalence of prescriptions for each drug with the highest level of evidence and estimating the prevalence of potentially actionable prescribing decisions.

Treatment of hypertension remains suboptimal, and a pharmacogenomics approach seeks to identify genetic biomarkers that could be used to guide treatment decisions; however, it is important to understand the biological underpinnings of genetic associations. Mouse models do not accurately recapitulate individual patient responses based on their genetics, and hypertension-relevant cells are difficult to obtain from patients. Induced pluripotent stem cell (iPSC) technology provides a great interface to bring patient cells with their genomic data into the laboratory and to study hypertensive responses. As an initial step, the present study established an iPSC bank from patients with primary hypertension and demonstrated an effective and reproducible method of generating functional vascular smooth muscle cells.

The value of utilizing a multigene pharmacogenetic panel to tailor pharmacotherapy is contingent on the prevalence of prescribed medications with an actionable pharmacogenetic association. The Clinical Pharmacogenetics Implementation Consortium (CPIC) has categorized over 35 gene‐drug pairs as “level A,” for which there is sufficiently strong evidence to recommend that genetic information be used to guide drug prescribing. The opportunity to use genetic information to tailor pharmacotherapy among adult patients was determined by elucidating the exposure to CPIC level A drugs among 11 Implementing Genomics In Practice Network (IGNITE)‐affiliated health systems across the US. Inpatient and/or outpatient electronic‐prescribing data were collected between January 1, 2011 and December 31, 2016 for patients ≥ 18 years of age who had at least one medical encounter that was eligible for drug prescribing in a calendar year. A median of ~ 7.2 million adult patients was available for assessment of drug prescribing per year. From 2011 to 2016, the annual estimated prevalence of exposure to at least one CPIC level A drug prescribed to unique patients ranged between 15,719 (95% confidence interval (CI): 15,658–15,781) in 2011 to 17,335 (CI: 17,283–17,386) in 2016 per 100,000 patients. The estimated annual exposure to at least 2 drugs was above 7,200 per 100,000 patients in most years of the study, reaching an apex of 7,660 (CI: 7,632–7,687) per 100,000 patients in 2014. An estimated 4,748 per 100,000 prescribing events were potentially eligible for a genotype‐guided intervention. Results from this study show that a significant portion of adults treated at medical institutions across the United States is exposed to medications for which genetic information, if available, should be used to guide prescribing.

Objective The aim of this study is to identify single-nucleotide polymorphisms (SNPs) influencing blood pressure (BP) response to the β-blocker atenolol. Methods Genome-wide association analysis of BP response to atenolol monotherapy was performed in 233 white participants with uncomplicated hypertension in the pharmacogenomic evaluation of antihypertensive responses study. Forty-two polymorphisms with P less than 10−5 for association with either diastolic or systolic response to atenolol monotherapy were validated in four independent groups of hypertensive individuals (total n = 2114). Results In whites, two polymorphisms near the gene PTPRD (rs12346562 and rs1104514) were associated with DBP response to atenolol (P = 3.2 × 10−6 and P = 5.9 × 10−6, respectively) with directionally opposite association for response to hydrochlorothiazide in another group of 228 whites (P = 0.0018 and P = 0.00012). A different polymorphism (rs10739150) near PTPRD was associated with response to atenolol in 150 black hypertensive individuals (P = 8.25 ×10−6). rs12346562 had a similar trend in association with response to bisoprolol (a different β-blocker) in 207 Finnish men in the genetics of drug responsiveness in essential hypertension study. In addition, an intronic single-nucleotide polymorphism (rs4742610) in the PTPRD gene was associated with resistant hypertension in whites and Hispanics in the international verapamil SR trandolapril study (meta-analysis P = 3.2 × 10−5). Conclusion PTPRD was identified as a novel locus potentially associated with BP response to atenolol and resistant hypertension in multiple ethnic groups.

Recent CYP2D6 phenotype standardization efforts by CYP2D6 activity score (AS) are based on limited pharmacokinetic (PK) and pharmacodynamic (PD) data. Using data from two independent clinical trials of metoprolol, we compared metoprolol PK and PD across CYP2D6 AS with the goal of determining whether the PK and PD data support the new phenotype classification. S-metoprolol apparent oral clearance (CLo), adjusted for clinical factors, was correlated with CYP2D6 AS (p < 0.001). The natural log of CLo was lower with an AS of 1 (7.6 ± 0.4 mL/min) vs. 2-2.25 (8.3 ± 0.6 mL/min; p=0.012), similar between an AS of 1 and 1.25-1.5 (7.8 ± 0.5 mL/min; p=0.702), and lower with an AS of 1.25-1.5 vs. 2-2.25 (p=0.03). There was also a greater reduction in HR with metoprolol among study participants with AS of 1 (-10.8 ± 5.5) vs. 2-2.25 (-7.1 ± 5.6; p<0.001) and no significant difference between those with an AS of 1 and 1.25-1.5 (-9.2 ± 4.7; p=0.095). These data highlight linear trends between CYP2D6 AS and metoprolol PK and PD, but inconsistencies with the phenotypes assigned by AS based on the current standards. Overall, this case study with metoprolol suggests that utilizing CYP2D6 AS, instead of collapsing AS into phenotype categories, may be the most precise approach for utilizing CYP2D6 pharmacogenomics in clinical practice.