Clinical Pharmacogenomics

Barry J. Gales, Pharm.D.Professor, College of Pharmacy

Southwestern Oklahoma State Universitybarry.gales@swosu.edu

Objectives

Explain the influence that pharmacogenomics has on drug metabolism.

Identify current resources for pharmacogenomics information.

Discuss clinical practice issues surrounding pharmacogenomics.

Review current status and future of pharmacogenomic testing.

Question 1

What region of a gene is responsible for coding for protein production?a. Exonb. Intronc. Regulatoryd. SNPs

Question 2

Where is the best place to get drug specific pharmacogenomic recommendations?a. Wikipediab. Human Genome Projectc. American College of Medical

Geneticsd. Clinical Pharmacogenetics

Implementation Consortium

Question 3

Which of the following are challenges to the implementation of pharmacogenomics?a. Lack of data standardizationb. Lack of EHR integrationc. Cost of testingd. Data variability and discordancee. All of the above

Definitions

Pharmacogenetics – monogenetic variants affecting drug response.

Pharmacogenomics – entire spectrum of genes that interact (enzymes, transport proteins, receptors) to determine drug response.

Terms are frequently used interchangeably

Precision/Personalized Healthcare/Medicine

Human Genome Project

Commissioned by Congress in 1988

Goal – sequence entire human genome by 2005

Initiated in 1990

Completed in 2003 – 99% of gene-containing sequence with a 99.9% accuracy.

Genome Research Resources

Human genome available at National Center for Biotechnology Information website.

International HapMap Project1000 Genomes project – catalog less common

genetic variantsPharmacogenomics Research Network

(PGRN)

Human Genome Facts

3.2 billion nucleotide base pairs

Base pairs code for ~ 22,000 protein-coding genes

Only 0.1% of base pair variation makes us individuals (99.9% genetically identical)

Can now sequence 40 billion bases/hour

Human Genome Facts

Codon – 3 consecutive nucleotides

Codons code for individual amino acids or amino acid chain termination

Substantial coding redundancy – GGC, GGG & GGT all code for glycine

20 amino acids form all human proteins

Human Genome Facts

A gene is a series of codons that specify for a particular protein

Gene regionsExons – encode for final protein

production (1% of genome)Introns – intervening noncoding regionsRegulatory – control gene transcription

Human Genome Facts

Alleles – sequence of nucleic acid bases at a given gene chromosomal locus.

Each gene locus made up of 2 alleles (parents)Homozygous genotype – 2 identical allelesHeterozygous genotype – 2 different allelesPhenotype is the outward expression of the

genotype

Types of Genetic Variations

Rare mutations (< 1% of population) – Cystic Fibrosis, hemophilia & Huntington’s

Polymorphisms (>1% of population) –responsible for most genetic variability in metabolic function or drug responses

Single-nucleotide polymorphisms

SNPs (snips) most common genetic variationOccur ~1/300 base pairsSNPs single base pair differences between individualsProteins &/or function maybe altered

Wild type allele – original or most common Variant allele – less common or variant copy

Drug Metabolizing Phenotypes

Ultra-rapid Metabolizer (UM)–rapidly convert prodrugs (toxicity) & clear drugs ( efficacy)

Extensive Metabolizer (EM) – normal patient

Intermediate Metabolizer (IM)

Poor Metabolizer (PM) – slowly convert prodrugs ( efficacy) & clear drugs (toxicity)

CYP2D6 Substrates

Analgesics – codeine & tramadol (prodrugs)Antiarrhythmics – propafenone & flecainideAntipsychotics – haloperidol & thioridazineBeta-blockers – carvedilol & metoprololSSRIs – fluoxetine, paroxetine & sertralineTCAs - amitrip, desip, imip & nortriptSERM – tamoxifen (prodrug)

CYP2D6 Polymorphism

PMs – 5-10% white population, don’t convert prodrugs or clear drugs

IMs – Asian and African populations, may require lower doses to be therapeutic

EMs – normal population, may be more susceptible to drug interactions

UMs – rapidly convert prodrugs (codeine -toxicity) & clear drugs ( efficacy)

CYP2C19 Substrates

SSRI – citalopram & escitalopramPPIs – lansoprazole, omeprazole,

pantoprazoleMiscellaneous

Clopidogrel (prodrug)CyclophosphamideDiazepamVoriconazole

CYP2C19 Polymorphism

PMs – [omeprazole] tenfold & H. pylori clearance, 13-23% Asian & 2-6% white

IMs – 10-30% of AsiansEMs – normal population, may be more

susceptible to drug interactionsUMs – may need higher doses of voriconizole

CYP2C9 Substrates

NSAIDS – diclofenac, ibuprofen, celecoxib,indomethacin, naproxen, piroxicam

Diabetic Agents – tolbutamide, glimepiride, glipizide, glyburide, nateglinide

Miscellaneous AgentsWarfarinPhenytoin

CYP2C9 Polymorphism

PMs – require phenytoin & warfarin doses, in whites vs. Asians & Africans

IMs – require phenytoin & warfarin doses, in whites vs. Asians & Africans

EMs – normal population, may be more susceptible to drug interactions

UMs – require phenytoin & warfarin doses

CYP2A6 Substrates

Nicotine – inability to metabolize nicotine associated with lower rates of smoking, amount smoked and greater success in being able to quit smoking.

CYP2A6 Polymorphism

PMs – 20% Asians vs. <1% whites, associated with reduced smoking rates

IMs – associated with reduced smoking ratesEMs – normal population, may be more

susceptible to drug interactionsUMs - ???

CYP2B6 Substrates

Cyclophosphamide & Ifosfamide

Efavirenz – NNRTIPMs & IMs experienced significant CNS ADRs at a higher rate while on efavirenz.

Efavirenz dose reduction reduced ADRs and was clinically efficacious.

Drug Transporter Gene PolymorphismsP-glycoprotein

throughout the body, digoxin, cyclosporine, tacrolimus, protease inhibitors, anthracyclines, vincaalkaloids, dexamethasone, phenytoin, phenobarbital

Solute carrier (SLC) – simvastatin

Drug Target Gene PolymorphismsReceptors – Beta-1 adrenergic receptor gene

(ADRB1)Enzymes – vitamin K oxidoreductase

(VKOR) & ACEIon Channels – K-ATP channelsIntracellular Signaling Proteins – G-Proteins

& GDP

American College of Medical Genetics (ACMG)Genomic sequencing is NOT a routine

screening test – targeted testing

Genomic sequencing identifies a causative variant in ~25% of tested patients

Genomic sequencing and result reporting should be done in conjunction with a geneticist

American College of Medical Genetics (ACMG)Incidental Findings Reporting (6.2% time)

57 genes tied to 24 disorders that can be treated by early interventions

Do not test children for adult onset diseases Only disclose disorders clearly tied to

genetic findings (near certainty) 3-5% “Non-father” findings

Genet Med 2013;15:565-74.

Clinical Pharmacogenetics Implementation Consortium (CPIC)International consortium providing guidance on how to use & incorporate existing pharmacogenetic data into the EHR NOTwhether to obtain pharmacogenetic data

CPIC guidelines & additional information are at the Pharmacogenomics Knowledge Base website (www.PharmGKB.org)

Published CPIC Guidelines

Do NOT address merit/need of/for testingUtilize a standard formatFull articles available on PharmGKB.orgPharmGKB.org summarizes genotypes,

phenotypes, implications, therapeutic recommendations & strength of recommendations

Actionable CPIC Guidelines

Abacavir Allopurinol Amitriptyline Atazanavir Azathioprine BoceprevirCapecitabine Carbamazepine Citalopram Clomipramine Clopidogrel CodeineDesipramine Doxepin EscitalopramFluoruracil Fluvoxamine Imipramine

Actionable CPIC Guidelines

Ivacaftor Mercaptopurine NortriptylineParoxetine PEG Interferon alfa - 2a & 2bPhenytoin Rasburicase Sertraline Simvastatin Tacrolimus TegafurThioguanine Trimipramine Warfarin

Clinical Genome Resource (ClinGen)

NIH sponsoredLaunched in 2013Genetic data from patients, clinicians,

laboratories and researchersAuthoritative central resource that defines the

clinical relevance of genomic variantsClinVar database developed to handle data

Clinical Genome Resource (ClinGen) Goals

Centralized shareable databaseStandardize annotation, interpretation and

weighting of genomic variantsAssess the “medical action ability” of variantsStructure genomic data for EHR useEnhance genomic use in diverse populationsDevelop expert panels to interpret data

Genomic Testing Results

52,000 adults followed for 5 years – 64.8% received a drug known to be influenced by pharmacogenomics (potential issue)

91% of patients had actionable results following 5 gene preemptive testing

Clin Pharmacol Ther 2012;92:235-42.

Genomic Testing Results

78% pediatric patients with actionable results following 4 gene preemptive testing

97% US patients with actionable results following 12 pharmacogene testing

738,000,000 RXs in 2013 for the 30 most common drugs with actionable results

Am J Med Genet C Semin Med Genet 2014;166C:45-55.Annu Rev Pharmacol Toxicol 2015;55:89-106.

Genomic Testing Results

5 CYP Isoenzymes

22,225 patients tested

20,534 patients with medication lists

Mean age 60y (1-108 y)

Mean # drugs 9.1 (1-49) Am J Health-Syst Pharm 2016;73:61-7

Genomic Testing Results

7% with NO at risk phenotype33% with ONE at risk phenotype41% with TWO at risk phenotypes17% with THREE at risk phenotypes2% with FOUR at risk phenotypes6 patients had FIVE at risk phenotypes

Genomic Testing Results

69.1% with at least one DDI, DGI or DDGI

8.9% with >1 “Change” interaction36.7% with >1 “Consider Change” interaction23.5% with >1 “Monitor” interaction30.9% with >1 “No Change” needed

Genomic Testing Results

Top 10 Interacting Drugs1. Metoprolol 2. Clopidogrel3. Hcodone/APAP 4. Warfarin5. Tramadol 6. Carvedilol7. Oxycodone 8. Omeprazole9. Citalopram 10. Bupropion

Clinical Practice Issues

Testing discordance between laboratories is not uncommon

Data is in silos not large usable poolsClinical presentation may be discordant with

genetic testing resultsData on UMs & PMs most useful currentlyHow to protect genetic patient information

Clinical Practice Issues

How do we determine what are “actionable findings”?

Does the action ability of findings differ for initiation of drug therapy vs. continuation of drug therapy?

Clinical Practice Issues

Will hospitals be expected to utilize/develop pharmacogenomic driven patient specific formularies?

Will insurers be expected to consider pharmacogenomics when making drug coverage and prior authorization decisions?

Clinical Practice Issues

Exome testing – sequences only protein producing section of the DNA. This is faster cheaper and the most common type of assay.

Genome testing – sequences whole DNA profile. Slower, more expensive but potentially may provide important data from the reactive region and introns we will need.

Reactive vs. Pre-emptive GenotypingReactive – ordered when a drug is being considered, delay in reporting, limited data (2C19 for clopidogrel)

Pre-emptive – data in EHR, more complete data, continuously available, less expensive in long run, requires good decision support software; Run at birth????

Question 1

What region of a gene is responsible for coding for protein production?a. Exonb. Intronc. Regulatoryd. SNPs

Question 2

Where is the best place to get drug specific pharmacogenomic recommendations?a. Wikipediab. Human Genome Projectc. American College of Medical

Geneticsd. Clinical Pharmacogenetics Implementation Consortium

Question 3

Which of the following are challenges to the implementation of pharmacogenomics?a. Lack of data standardizationb. Lack of EHR integrationc. Cost of testingd. Data variability and discordancee. All of the above