The Precision Medicine Initiative: Consultative PGx and Data Sharing at Stanford University

On February 25th, one year after the announcement of the Precision Medicine Initiative (PMI), the White House hosted the Precision Medicine Summit. A White House press release described how various public and private groups will be taking steps to advance the goals of the PMI. As part of the PMI Stanford will launch a consultative pharmacogenetics practice for physicians to refer patients with unusual drug responses. Dr. Russ Altman, Co-Principal Investigator (Co-PI) of PharmGKB will lead the pharmacogenetics consultative practice. The consultative practice will evaluate genetic variants in patients with unusual drug responses and will use Clinical Pharmacogenetics Implementation Consortium (CPIC) dosing guidelines to focus attention on gene-drug pairs with the best evidence for actionability. In addition, Stanford University will also make the genomic data of 77 individuals of Iranian descent publicly available. The genomes of those 77 individuals were sequenced as part of the Iranian Genome Project, for which Dr. Altman is also the PI. Dr. Roxana Daneshjou, a former student in Dr. Altman’s lab is the lead researcher for the project.  Although Dr. Daneshjou is leading the data analysis for the project, Dr. Altman explained “we wanted to get the data out into the public as soon as possible, so (we) have taken the slightly unusual measure of making the data available before we get our paper out… we want people to use it.” A major goal of the PMI is to “open up data and technology tools to invite citizen participation, unleash new discoveries, and bring together diverse collaborators to share their unique skills.”

EPIC Integrates Genelex's Pharmacogenomics Decision Support System into Electronic Health Records

On Feb 23^rd, Pharmagenomics (PGx) testing company Genelex announced enhanced connection with  Epic, the most widely used electronic health record (EHR) system in US. With this new connectivity, healthcare systems and providers using Epic EHRs will be able to use Genelex's YouScript Precision Prescribing software to better identify patients who are at greater risk of adverse drug events based on pharmacogenetic information. In a GenomeWebnews article, Genelex CEO Kristine Ashcraft said “It's an indicator of market adoption and market demand for pharmacogenetic information”.

Translating pharmacogenomics knowledge into clinical practice has not been an easy task. Barriers that prevent the widespread use of PGx diagnostics include the lack of incentives for health care systems to conduct tests as well as lack of clear clinical guidelines for translating genetic variations into actionable recommendations. Additionally, computational tools for clinical decision support (CDS) will need to be developed and integrated in the EHR to prompt and guide clinicians on how to use genetic information when prescribing drugs. CPIC was formed in 2009 as a collaborative project between PharmGKB and the Pharmacogenomics ResearchNetwork to address some of the challenges in clinical implementation. Its goal was to create guidelines to aid clinicians on how genetic test results should be translated into specific prescribing actions. CPIC guidelines are simultaneously published and maintained on PharmGKB website, in both plain text as well as computable form for easy integration into clinical decision support tools. Many of the CPIC guidelines have been endorsed by professional societies such as The American Society of Health-System Pharmacists (ASHP). CPIC have also established informatics subgroup to support the adoption of the CPIC guidelines by developing tools to combine clinical information from the EHR with the information from the CPIC guidelines and use them for clinical decision support. Preemptive pharmacogenomic testing programs using EHRs and decision support tools have been deployed at several academic medical centers, eg. St. Jude,  Vanderbilt University and University of Florida.

Read the GenomeWeb article:

EpicIntegrating Genelex PGx Decision Support Into EHR Systems

Read the press release from Genelex:

http://genelex.com/genelex-announces-integration-with-epic/

More information about CPIC and CPIC informatics working group:

https://cpicpgx.org/

https://cpicpgx.org/informatics/

A Study of the Transcriptomic Variation Affecting Pharmacogenes

In an effort to capture differences in the expression of pharmacogenes between individuals and between tissue types and to characterize novel pharmacogene splice variants, researchers conducted a transcriptomic analysis of 389 pharmacologically important genes in liver, kidney (cortex), heart (left ventricle), and adipose tissue from 139 individuals as well as 45 lymphoblastoid cell lines (LCLs). Tissue samples came from various Pharmacogenomics Reseach Network (PGRN) groups. The list of pharmacogenes was compiled from several sources, including PharmGKB. The results were recently published in The Pharmacogenomics Journal.

The study, “Transcriptomic variation of pharmacogenes in multiple human tissues and lymphoblastoid cell lines”, reports that many pharmacogenes were highly expressed in liver or kidney when compared to other tissues, although some were consistently expressed at high or low levels in all tissue types, and that many pharmacogenes showed variable expressed when comparing between individuals and tissue types. The authors suspect that some differences in expression between individuals may reflect environmental and health differences between people. Expression of most pharmacogenes was almost always lower in LCLs when compared to the other tissue types that were examined. Finally, the authors report the discovery of several novel pharmacogene splicing events and splice variant differences between tissue types.

These findings suggest that variable expression of pharmacogenes between tissue types and individuals as well as differences in alternative splicing patterns could contribute to the observed variation in drug dosing, response, and toxicities.

January SNPits Summary

The January issue of SNPits, the University of Florida’s Personalized Medicine Program e-newsletter, summarizes pharmacogenetics studies.


The first is a 2009 article from the journal Gastroenterology. The authors conducted a multi center, randomized controlled trial whereby patients were given high or low-dose celecoxib, or placebo, and were followed up with colonoscopies at one and three years. The authors reported that risk of cardiovascular adverse events may be influenced by CYP2C9 genotype, and that risk of developing adenoma may not differ by high vs. low dose celecoxib for all genotypes. The authors conclude that further research into the implications of CYP2C9 genotype for the routine use of celecoxib is needed.
Read the summary here: http://personalizedmedicine.ufhealth.org/2016/01/04/celecoxib-cyp2c9-variability-influences-colorectal-adenoma-prevention/

The second is from 2015 and comes from the journal Thrombosis Research. The authors measured residual platelet reactivity (RPR) in coronary heart disease patients who were on duel anti platelet therapy (aspirin and clopidogrel). Some patients were also taking esomeprazole, a proton pump inhibitor. Clopidogrel is activated by CYP2C19, and esomeprazole is a major substrate of CYP2C19. The authors investigated whether concomitant use of esomeprazole and clopidogrel, as well as whether polymorphisms in CYP2C19 in patients taking esomeprazole and clopidogrel had any influence on RPR or adverse events. The authors reported that concomitant use of esomeprazole and clopidogrel had no significant effect on RPR, or outcomes regardless of CYP2C19 phenotype as compared to patients not taking esomeprazole. However, RPR did vary according to the number of CYP2C19 loss of function alleles in a patient, regardless of esomeprazole use.
Read the summary here: http://personalizedmedicine.ufhealth.org/2016/01/15/clopidogrel-effect-of-esomeprazole-on-platelet-activity-clinical-outcomes/

The Pharmacogenetic Phenome Compendium, A Chemical–Genetic Interaction Map

Development of new drugs is a complicated and difficult process, with many initially promising compounds falling by the wayside due to unforeseen off-target or genotype-specific effects. In an effort to address some of these problems a new paper by Breinig et. al. describes a high-throughput process for screening small molecules against a library of cancer cells with known gene knockouts in key signaling pathways. Using 384-well plates for testing the drug-cell combinations and an automated image analysis pipeline, the authors tracked changes in twenty different key drug-specific phenotypic features such as the cell count, shape, and DNA appearance.  Based on the drug-specific phenotypic differences the authors produced a chemical-genomic interaction map of the cancer cells.  These data were used to examine how drugs perturb genetic networks and to investigate cross-talk between pathways, as well as to explain some of the observed off-target activity and drug synergism. The group has released this data online as the Pharmacogenetic Phenome Compendium (PGPC) for other researchers to use.

Constellation: tool for automated CYP2D6 phenotype assignment from WGS

A team from Children’s Mercy and the University of Missouri in Kanas City including Andrea Gaedigk and Greyson Twist published an article about a CYP2D6 phenotype assignment tool in Genomic Medicine (http://www.nature.com/articles/npjgenmed20157). Constellation, a probabilistic scoring system, enables automated ascertainment of CYP2D6 activity scores based on CYP2D6 diplotypes from whole-genome sequences (WGS).

CYP2D6 is involved in the metabolism of about 25% of drugs in clinical use and genetic variations leading to functional consequences affecting drug efficacy and risk of adverse events.  

The gene is highly polymorphic with over 100 allelic variants (star alleles) assigned including CYP2D6 copy number variations and rearrangements with the neighboring CYP2D7. This high degree of variation, high sequence similarity to CYP2D7 and CYP2D8, GC content, repetitive and low-complexity sequences are challenges in analyzing this locus.

The performance of the developed algorithm is evaluated by comparing the CYP2D6 diplotype assigned by the probabilistic WGS analysis using Constellation with the diplotype determined by manual integration (consensus reference) of results obtained by quantitative copy-number assessment, a panel of TaqMan genotype assays, and Sanger sequencing of long-range genomic PCR in 61 samples. Phenotype prediction is consistent between the consensus reference and Constellation calls with the exception of three cases. Constellation was able to accurately identify all poor and ultrarapid metabolizers in WGS data. 

The authors anticipate Constellation to be extensible to identify variations in other pharmacogenomic-relevant genes, enabling future uses of WGS data.

Cisplatin FDA label changes

In 2013 we blogged about the controversy with the FDA labeling for cisplatin and its warning for TPMT variants and increased risk of ototoxicity in children. The 2012 label stated:

“Certain genetic variants in the thiopurine S-methyltransferase gene (e.g., TPMT*3B and TPMT*3C) are associated with an increased risk of ototoxicity in children administered conventional doses of cisplatin...Children who do not have one of these TPMT gene variants remain at risk for ototoxicity. All pediatric patients receiving cisplatin should have audiometric testing at baseline, prior to each subsequent dose, of drug and for several years post therapy.”

The label change appeared to be based on a single study from 2009.  Several years have passed and there is still very limited data in the public domain about TPMT and risk for cisplatin-induced ototoxicity: four papers comprising seven studies and a meta-analysis [PMID:19898482] [PMID:23820299] [PMID:23588304] [PMID:25551397]. The meta-analysis found no association with any of the TPMT variants and that the studies were significantly heterogeneous in terms of cancer types, ethnicities, age and co-treatments, all of which influence risk for ototoxicity.

The FDA has requested changes to the cisplatin label removing the whole Pharmacogenomics section, to now state :

“Genetic factors (e.g. variants in the thiopurine S-methyltransferase [TPMT] gene) may contribute to cisplatin-induced ototoxicity; although this association has not been consistent across populations and study designs.” 


This better reflects the current uncertainty about this gene-drug relationship and is more in line with the level of evidence we have assessed in our clinical annotations for the TPMT variants and cisplatin.