Precision Medicine Under the Big Sky

Transcription

1 Precision Medicine Under the Big Sky Erica L. Woodahl, Ph.D. Associate Professor Department of Biomedical and Pharmaceutical Sciences University of Montana

2 Disclosure Statement Presenter has no financial or nonfinancial disclosures

3 Learning Objectives Identify resources for guidelines on pharmacogenetic testing and pharmacogenetics-guided dosing recommendations Interpret pharmacogenetic guidelines for drug-gene pairs Assess obstacles and opportunities to pharmacogenetic implementation in clinical practice

4 Pharmacogenomics and Precision Medicine Identify interindividual variability in genes, environment, and lifestyle to tailor disease treatment and prevention I am a responder I am a nonresponder I am at risk for an adverse event I received the wrong dose

5 Pharmacogenomic Biomarkers in Drug Labels (Source: FDA; updated November 2018) Number of Drug-Gene Pairs Number of Therapeutic Areas Number of Biomarkers Listed Therapeutic Areas Number of Labels Oncology 108 Psychiatry 33 Infectious Disease 30 Neurology 19 Cardiovascular 15 Gastroenterology 15 Hematology 14 Anesthesiology 10 Other 41 Drug Labeling Sections Indications and Usage Clinical Pharmacology Warnings and Precautions Contraindications Dosage and Administration Clinical Studies Drug Interactions Boxed Warning Adverse Reactions Patient Counseling Information Use in Specific Populations Overdosage

6 Challenges to Pharmacogenetics Implementation Survey: What do you think are the most challenging aspects of the implementation of pharmacogenetics into the clinic? 1. Process to interpret genetic tests and to translate genetic information into clinical actions (e.g. dose and/or drug selection) 2. Need for recommendations for selecting the drug/gene pairs to implement clinically 3. Clinicians' resistance to considering pharmacogenetic information 4. Concerns about test costs and reimbursements Relling and Klein, Clin Pharmacol Ther, 89:464-7 (2011)

7 Clinical Pharmacogenetics Implementation Consortium (CPIC) Guidelines Guidelines designed to help providers understand how available genetic test results should be used to optimize drug therapy Key Assumptions: Clinical high-throughput and pre-emptive (pre-prescription) genotyping will become more widespread Providers will be faced with having patients' genotypes available

8 Clinical Pharmacogenetics Implementation Consortium (CPIC) Guidelines Prioritization of drug-gene pairs and guidance recommendations CPIC Level A B Level of evidence Preponderance of evidence is high or moderate in favor of changing prescribing Preponderance of evidence is weak with little conflicting data Strength of Recommendation of Prescribing Change At least one moderate or strong action recommended At least one optional action is recommended C Evidence levels can vary No actions are recommended D Evidence levels can vary No actions are recommended CPIC Level A and B: prescribing action recommended; alternative therapies or dosing are highly likely to be safe and effective

9 CPIC: 138 gene-drug pairs reach CPIC Level A and B Published Guidelines (Clinical Pharmacology andtherapeutics): 47 gene-drug pairs Abacavir HLA-B Escitalopram CYP2C19 Ribavirin IFNL3 Allopurinol HLA-B Fluorouracil DPYD Sertraline CYP2C19 Amitriptyline CYP2C19, CYP2D6 Fluvoxamine CYP2D6 Simvastatin SLCO1B1 (OATP1B1) Atazanavir UGT1A1 Imipramine CYP2C19, CYP2D6 Tacrolimus CYP3A5 Azathioprine TPMT Ivacaftor CFTR Tamoxifen CYP2D6 Capecitabine DPYD Mercaptopurine TPMT Tegafur DPYD Carbamazepine HLA-A, HLA-B Nortriptyline CYP2D6 Thioguanine TPMT Citalopram CYP2C19 Ondansetron CYP2D6 Trimipramine CYP2C19, CYP2D6 Clomipramine CYP2C19, CYP2D6 Oxcarbazepine HLA-B Tropisetron CYP2D6 Clopidogrel CYP2C19 Paroxetine CYP2D6 Voriconazole CYP2C19 Codeine CYP2D6 Peginterferon alfa-2a/2b IFNL3 Warfarin CYP2C9, CYP4F2,VKORC1 Desipramine CYP2C19, CYP2D6 Phenytoin CYP2C9, HLA-B Doxepin CYP2C19, CYP2D6 Rasburicase G6PD

10 Pharmacogenomics in Rural and Underserved Populations

11 Pharmacogenomics in Diverse Populations Minority groups are disproportionately represented in populations that are considered medically underserved Sampling bias in genetic studies Ethnic diversity in genetic studies is crucial Popejoy and Fullerton, Nature, 538: (2016)

12 Pharmacogenetic Biomarkers Pharmacogenes Pharmacogenes Pharmacokinetics Pharmacodynamics Drug Metabolizing Enzymes Drug Targets Drug Transporters Toxicities

13 Interindividual Variability Patient phenotype predicted from genotype Ultrarapid Metabolizer (UM) Increased gain of function Extensive Metabolizer (EM) normal metabolism Intermediate Metabolizer (IM) Intermediate metabolism Poor Metabolizer (PM) Deficient null metabolism Zanger and Schwab, Pharmacol Ther, 138: (2013)

14 Pharmacogenetic-Guided Dose Adjustments UMs EMs PMs IMs PMs IMs EMs UMs Kirchheiner et al, Nature Rev Drug Disc, 4: (2005)

15 Clinical Examples of Pharmacogenomics Codeine and CYP2D6 Tamoxifen and CYP2D6 Citalopram/escitalopram and CYP2C19 Phenytoin and HLA-B + CYP2C9

16 CYP2D6 codeine Case Study #1 The Toronto Case Codeine prescribed for obstetric pain while breast-feeding On day 7 after delivery infant experiencing difficulty breastfeeding and lethargy Infant succumbed on day 13 Case Study #2 2-yr old boy with sleep apnea underwent adenotonsillectomy Instructed to take mg codeine/120 mg acetaminophen syrup every 4-6 hrs as needed Second evening after surgery: Fever and wheezing Following morning: no vital signs

17 CYP2D6 codeine

18 CYP2D6 codeine Case #1: High morphine levels in breast milk Postmortem analysis found blood morphine concentrations of 70 ng/ml (normal ~0-2.2 ng/ml) Mother was genotyped as ultrarapid metabolizer Case #2 Postmortem analysis found morphine concentration of 32 ng/ml Boy was genotyped as ultrarapid metabolizer

19 Is codeine safe in breast-feeding women and young children? FDA Public Health Advisory Use of codeine by some breastfeeding mothers may lead to life-threatening side effects in nursing babies Added warning to the product label CPIC Guidelines Avoid codeine use due to potential for toxicity in patients with ultrarapid genotype Consider alternative analgesics such as morphine or a nonopioid Not recommended for children less than 2 years of age Crews et al, Clin Pharmacol Ther, 91: (2011) Crews et al, Clin Pharmacol Ther, 95: (2014)

20 CYP2D6 Tamoxifen Tamoxifen is bioactivated to its active metabolite, endoxifen Recruited AIAN women receiving adjuvant tamoxifen therapy in Montana and Alaska Genotyped CYP2D6, CYP3A4, CYP3A5, and CYP2C9 Khan et al, Clin Transl Sci, 11: (2018)

21 Metabolic ratio Metabolic ratio Endoxifen Plasma Concentration (ng/ml) Metabolic ratio CYP2D6 Tamoxifen CYP2D6 variation associated with endoxifen levels and metabolic ratios Endoxifen Plasma Concentration p = OH-Tam / Tamoxifen p = 4.5 x 10-5 Outcome Gene p-value Endoxifen Endoxifen / Tamoxifen CYP2D ** CYP3A CYP3A CYP2C CYP2D6 4.4x10-7*** CYP3A CYP3A * CYP2C * p <.05; ** p <.001; *** p < Activity Score Activity Score Endoxifen / Tamoxifen Endoxifen / 4-OH-Tam p = 4.0 x 10-7 p = Activity Score Activity Score 10 8 Khan et al, Clin Transl Sci, 11: (2018)

22 CPIC Guideline: CYP2D6 Tamoxifen Goetz et al, Clin Pharmacol Ther, 103: (2018)

23 CYP2C19 citalopram and escitalopram Citalopram and escitalopram Metabolized by CYP2C19 to less active metabolites Ultrarapid metabolizers: 5 30% of patients Poor metabolizers: 2 15% of patients

24 CYP2C19 citalopram and escitalopram Efficacy: Ultrarapid metabolizers at higher risk of failing therapy Safety: Poor metabolizers at higher risk of QT prolongation FDA recommends 50% dose reduction for PMs due to risk of QT prolongation Hodgson et al, J Psychopharmacol, 28: (2014) Rudberg et al, Clin Pharmacol Ther, 83: (2008)

25 CYP2C19 citalopram and escitalopram Hicks et al, Clin Pharmacol Ther, 98: (2015)

26 HLA-B + CYP2C9 and phenytoin CYP2C9 poor metabolizers are at higher risk of adverse events due to increased phenytoin exposure HLA-B*15:02 is associated with cutaneous hypersensitivity reactions Also seen with carbamazepine 1 10% in Asians and Oceanians

27 CPIC Guideline: HLA-B + CYP2C9 and phenytoin Caudle et al, Clin Pharmacol Ther, 96:542-8 (2014)

28 Obstacles and Opportunities to Implementation in Clinical Practice

29 Accuracy of Genotyping Example: CYP2D6 Extreme phenotypes common 5 14% of Europeans are poor metabolizers 30% of Ethiopians are ultrarapid metabolizers CYP2D6 is difficult to genotype Extensive sequence variation Structural variation Testing panels may exclude rare but clinically relevant variants; may be population-specific Normal Duplication Deletion 2D6/2D7 Hybrid 2D7/2D6 Hybrid Accurate CYP2D6 phenotype prediction requires accurate genotyping data

30 Results from Genotype-Phenotype Study Compare CYP2D6 genotypes assigned by sequencing methods alone and with structural variation data Structural variation is common (n=618 alleles) Deletions (3.7%); duplications (7.6%); gene hybrids (6.3%) Misclassification of individuals (n=309) Genotypes for 66 samples (21.4%) were incorrectly assigned Phenotype prediction for 25 samples (8.1%) were incorrect Commercially-available pharmacogenetic tests are not designed to accurately identify these individuals with extreme phenotypes Dalton et al, in preparation

31 Evaluation of commercial pharmacogenetic testing in psychiatry: focus on CYP2D6 and CYP2C19 Tests evaluated on recommendations published by the CDC and CPIC 20 pharmacogenetic testing panels Bousman et al, Pharmacogenetics and Genomics, 27: (2017)

32 Commercially-available tests do not meet reporting recommendations Bousman et al, Pharmacogenetics and Genomics, 27: (2017)

33 Cost Reimbursement is variable, but coverage is increasing May require prior authorization Individual gene tests: $200 - $500 out of pocket Genesight panel: No cost to patients on traditional Medicare or Medicaid plans (psychiatric Rx) Other insurances ~$330 or less out of pocket for patients

34 Integration in the electronic health record

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38 Challenges in rural settings

39 Diverse practice settings Lake County, MT Missoula County, MT King County, WA Population 28, ,299 1,940,777 NCHS classification Nonmetropolitan county Small metropolitan county Large metropolitan county Median age (years) % below poverty level in past year Mean household income % population unemployed 23.1% 16.7% 10.9% $49,775 $60,114 $95, % 5.8% 5.2% % AI/AN 28.8% 4.0% 2.0% PCP: population 1:1370 1:1140 1:888 NCHS: National Center for Health Statistics PCP: primary care provider Dorfman et al, Pharmacogenomics, 16: (2015)

40 Disparities are greater among people living in nonmetropolitan areas than metropolitan areas

41 Genetic screening rates are lower for people in nonmetropolitan areas Kolor et al, MMWR Surveill Summ, 66(No. SS-15):1 11 (2017)

42 In the era of precision medicine, how can we ensure that those outside of metropolitan communities aren t left behind?

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46 Early adopter sites

47 New approaches are needed for implementation beyond major medical systems Implementation Science strategies for pharmacogenetics Promotes the uptake of evidence-based interventions Possible model: Substance Abuse and Mental Health Services Administration (SAMHSA) Centralized pharmacogenetics resource Telehealth/Telepharmacy Possible model: Extension for Community Healthcare Outcomes (Project ECHO) Comprehensive implementation toolkits

48 Next steps in pharmacogenetics implementation Ongoing Strengthen relationships with clinical champions and other key stakeholders Short- to mid-term In-depth analysis of barriers and facilitators Implementation toolkit development Pilot test at one early adopter site Long-term Expand to additional pilot sites and beyond

49 Summary Pharmacogenetic testing improves drug efficacy and safety Population-specific genetic data is key to advancing precision medicine Guidelines are available to make specific prescribing decisions for patient care Considerations of barriers to implementation of pharmacogenetics is important Implementation strategies must consider unique challenges in rural and underserved healthcare settings

50 References Bousman et al, Pharmacogenetics and Genomics, 27: (2017) Caudle et al, Clin Pharmacol Ther, 96:542-8 (2014) Crews et al, Clin Pharmacol Ther, 91: (2011) Crews et al, Clin Pharmacol Ther, 95: (2014) Dorfman et al, Pharmacogenomics, 16: (2015) Goetz et al, Clin Pharmacol Ther, 103: (2018) Hicks et al, Clin Pharmacol Ther, 98: (2015) Hodgson et al, J Psychopharmacol, 28: (2014) Khan et al, Clin Transl Sci, 11: (2018) Kirchheiner et al, Nature Rev Drug Disc, 4: (2005) Kolor et al, MMWR Surveill Summ, 66(No. SS-15):1 11 (2017) Popejoy and Fullerton, Nature, 538: (2016) Relling and Klein, Clin Pharmacol Ther, 89:464-7 (2011) Rudberg et al, Clin Pharmacol Ther, 83: (2008) Zanger and Schwab, Pharmacol Ther, 138: (2013)

51 Acknowledgements University of Montana Rachel Dalton Katie George Niki Graham Burhan Khan Jack Staples Liz Putnam Confederated Salish and Kootenai Tribes LeeAnna Muzquiz Teresa Wall McDonald CSKT Tribal Council Community Pharmacogenetics Advisory Council University of Washington Wylie Burke Alison Fohner Diane Korngiebel Steven Lee Debbie Nickerson Tim Thornton Ken Thummel Southcentral Foundation Denise Dillard Vanessa Hiratsuka Oregon Health & Science University Bert Boyer Scarlett Hopkins Funding: R01HG P01GM U01GM U54GM115371

52 Questions?