To date, IGNITE
Network
grants have
supported

0

publications

Institutional profile: University of Florida Health Personalized Medicine Program

Cavallari LH, Weitzel KW, Elsey AR, Liu X, Mosley SA, Smith DM, Staley BJ, Winterstein AG, Mathews CA, Franchi F, Rollini F, Angiolillo DJ, Starostik P, Clare-Salzler MJ, Nelson DR, Johnson JA.

2017 Apr;18(5):421-426. doi: 10.2217

Is Universal HLA-B*15:02 Screening a Cost-Effective Option in an Ethnically-Diverse Population? A Case Study of Malaysia

Chong HY, Mohamed Z, Tan LL, Wu DB, Shabaruddin FH, Dahlui M, Apalasamy YD, Snyder SR, Williams MS, Hao J, Cavallari LH, Chaiyakunapruk N

Br J Dermatol. 2017 Mar 27. doi: 10.1111/bjd.15498.

The IGNITE Pharmacogenetics Working Group: An Opportunity for Building Evidence with Pharmacogenetic Implementation in a Real-World Setting

Cavallari LH, Beitelshees AL, Blake KV, Dressler LG, Duarte JD, Elsey A, Eichmeyer JN, Empey PE, Franciosi JP, Hicks JK, Holmes AM, Jeng L, Lee CR, Lima JJ, Limdi NA, Modlin J, Obeng AO,Petry N, Pratt VM, Skaar TC, Tuteja S, Voora D, Wagner M, Weitzel KW, Wilke RA, Peterson JF,Johnson JA.

Clin Trans Sci 2017 [Epub ahead of print].  PMID: 28294551

Impact of the CYP2C19 genotype on voriconazole exposure in adults with invasive fungal infections

Hamadeh IS, Klinker KP, Borgert SJ, Richards AI, Li W, Mangal N, Hiemenz JW, Schmidt S, Langaee TY, Peloquin CA, Johnson JA, Cavallari LH.

Pharmacogenet Genomics 2017 PMID: 28306618.

High-Throughput Assays to Assess the Functional Impact of Genetic Variants: A Road Towards Genomic-Driven Medicine

Ipe J, Swart M, Burgess KS, Skaar TC

Clin Transl Sci.  Epub 2017 Feb 18.

PMID: 28213901;  DOI: 10.1111/cts.12440

The Pharmacogenomics Research Network Translational Pharmacogenetics Program: outcomes and metrics of pharmacogenetics implementation across diverse healthcare systems

Authors: Luzum JA, Pakyz RE, Elsey AR, Haidar CE, Peterson JF, Whirl-Carrillo M, Handelman SK, Palmer K, Pulley JM, Beller M, Schildcrout JS, Field JR, Weitzel KW, Cooper-DeHoff RM, Cavallari LH, O’Donnell PH, Altman RB, Pereira N, Ratain MJ, Roden DM, Embi PJ, Sadee W, Klein TE, Johnson JA, Relling MV, Wang L, Weinshilboum RM, Shuldiner AR, Freimuth RR 

Clin Pharmacol Ther 2017 Jan 16  PMID: 28090649

Race, Genomics and Chronic Disease: What Patients with African Ancestry Have to Say

Authors: Carol R. Horowitz, Kadija Ferryman, Rennie Negron, Tatiana Sabin, Mayra Rodriguez, Randi F. Zinberg, Erwin Böttinger, Mimsie Robinson

DOI: 10.1353/hpu.2017.0020

Educational strategies to enable expansion of pharmacogenomics-based care

Authors: Weitzel KW, Aquilante CL, Johnson S, Kisor DF, Empey PE.

Am J Health Syst Pharm. 2016 Dec 1;73(23):1986-1998

Weitzel KW, Aquilante CL, Johnson S, Kisor DF, Empey PE. Educational strategies to enable expansion of pharmacogenomics-based care. Am J Health Syst Pharm. 2016 Dec 1;73(23):1986-1998. PMID: 27864206 DOI: 10.2146/ajhp160104

PMID: 27864206

doi: 10.2146/ajhp160104

Genetic Determinants of PY212 Inhibitors and Clinical Implication and Clinical Implications

Authors: Cavallari, L.H., Obeng A.O

Interv Cardiol Clin. 2017 Jan;6(1):141-149

Cavallari, L.H., Obeng A.O. Genetic Determinants of P2Y12 Inhibitors and Clinical Implications. Intervent Cardiol Clin. 6 (2017) 141–149

PMID: 27886818

doi: 10.1016/j.iccl.2016.08.010

Inpatient models of pharmacogenetic implementation

Author: Cavallari LH, Lee CR, Duarte JD, Nutescu EA, Weitzel KW, Stouffer GA, Johnson JA

Am J Health Syst Pharm. 2016 Dec 1;73(23):1944-1954

Cavallari LH, Lee CR, Duarte JD, Nutescu EA, Weitzel KW, Stouffer GA, Johnson JA. Inpatient models of pharmacogenetic implementation. Am J Health Syst Pharm.

PMID: 27864202

doi: 10.2146/ajhp150946

Pharmacists should jump onto the clinical pharmacogenetics train

Author: Johnson, J.A

Am J Health-Syst Pharm. 2016; 73:2013-6

Johnson, J.A. Pharmacists should jump onto the clinical pharmacogenetics train. Am J Health-Syst Pharm. 2016; 73:2013-6.

PMID: 27864209

doi: 10.2146/ajhp160046

Pharmacogenomics competencies in pharmacy practice: A blueprint for change

Authors: Roederer MW, Kuo GM, Kisor DF, Frye RF, Hoffman JM, Jenkins J, Weitzel KW

J Am Pharm Assoc (2003). 2016 Nov 2. pii: S1544-3191(16)30801-9.

The emerging use of genomic data to inform medication therapy populates the medical literature and provides evidence for guidelines in the prescribing information for many medications. Despite the availability of pharmacogenomic studies, few pharmacists feel competent to use these new data in patient care. The first pharmacogenomics competency statement for pharmacists was published in 2002. In 2011, the Pharmacogenomics Special Interest Group of the American Association of Colleges of Pharmacy led a process to update this competency statement with the use of a consensus-based method that incorporated input from multiple key professional pharmacy organizations to reflect growth in genomic science as well as the need for pharmacist application of genomic data. Given the rapidly evolving science, educational needs, and practice models in this area, a standardized competency-based approach to pharmacist education and training in pharmacogenomics is needed to equip pharmacists for leadership roles as essential members of health care teams that implement clinical utilization strategies for genomic data.

PMID: 27816542

doi: 10.1016/j.japh.2016.08.014

Implementing Algorithm-Guided Warfarin Dosing in an Ethnically Diverse Patient Population Using Electronic Health Records and Preemptive CYP2C9 and VKORC1 Genetic Testing

Authors: Obeng AO, Kaszemacher T, Abul-Husn NS, Gottesman O, Vega A, Waite E, Myers K, Cho J, Bottinger EP, Ellis SB, Scott SA..

Clin Pharmacol Ther. 2016 Nov;100(5):427-430.

doi: 10.1002/cpt.425

PMID: 27393744

Lessons Learned When Introducing Pharmacogenomic Panel Testing Into Clinical Practice

Author: Marc B. Rosenman, Brian Decker, Kenneth D. Levy, Ann M. Holmes, Victoria M. Pratt, Michael T. Eadon

Value Health. 2016 October [Epub ahead of print].

PMID: N/A

doi: 10.1016/j.jval.2016.08.727

Genome-Wide Association of CKD Progression: The Chronic Renal Insufficiency Cohort Study

Authors: Parsa A, Kanetsky PA, Xiao R, Gupta J, Mitra N, Limou S, Xie D, Xu H, Anderson AH, Ojo A, Kusek JW, Lora CM, Hamm LL, He J, Sandholm N, Jeff J, Raj DE, Böger CA, Bottinger E, Salimi S, Parekh RS, Adler SG, Langefeld CD, Bowden DW; FIND Consortium., Groop PH, Forsblom C, Freedman BI, Lipkowitz M, Fox CS, Winkler CA, Feldman HI; and the Chronic Renal Insufficiency Cohort (CRIC) Study Investigators

.J Am Soc Nephrol. 2016 Oct 11.

pii: ASN.2015101152.

Effects of Using Personal Genotype Data on Student Learning and Attitudes in a Pharmacogenomics Course.

Authors: Weitzel KW, McDonough CW, Elsey AR, Burkley B, Cavallari LH, Johnson JA

Am J Pharm Educ. 2016 Sep 25;80(7):122.

Abstract: Objective. To evaluate the impact of personal genotyping and a novel educational approach on student attitudes, knowledge, and beliefs regarding pharmacogenomics and genomic medicine. Methods. Two online elective courses (pharmacogenomics and genomic medicine) were offered to student pharmacists at the University of Florida using a flipped-classroom, patient-centered teaching approach. In the pharmacogenomics course, students could be genotyped and apply results to patient cases. Results. Thirty-four and 19 student pharmacists completed the pharmacogenomics and genomic medicine courses, respectively, and 100% of eligible students (n=34) underwent genotyping. Student knowledge improved after the courses. Seventy-four percent (n=25) of students reported better understanding of pharmacogenomics based on having undergone genotyping. Conclusions. Completion of a novel pharmacogenomics elective course sequence that incorporated personal genotyping and genomic medicine was associated with increased student pharmacist knowledge and improved clinical confidence with pharmacogenomics.

PMID: 27756930

The Spectrum of Clinical Utilities in Molecular Pathology Testing Procedures for Inherited Conditions and Cancer: A Report of the Association for Molecular Pathology

Author: Joseph L, Cankovic M, Caughron S, Chandra P, Emmadi R, Hagenkord J, Hallam S, Jewell KE, Klein RD, Pratt VM, Rothberg PG, Temple-Smolkin RL, Lyon E.

J Mol Diagn. 2016 Sep;18(5):605-19

PMID: 27542512

doi: 10.1016/j.jmoldx.2016.05.007

Clopidogrel pharmacogenetics: from evidence to implementation.

Authors: Cavallari LH, Duarte JD

Future Cardiol. 2016 Sep;12(5):511-4. doi: 10.2217/fca-2016-0045. Epub 2016 Aug 19.

PMID: 27539287

Attitudes of clinicians following large-scale pharmacogenomics implementation.

Authors: Peterson JF, Field JR, Shi Y, Schildcrout JS, Denny JC, McGregor TL, Van Driest SL, Pulley JM, Lubin IM, Laposata M, Roden DM, Clayton EW

Pharmacogenomics J. 2016 Aug;16(4):393-8.

Abstract: Clinician attitudes toward multiplexed genomic testing may be vital to the success of translational programs. We surveyed clinicians at an academic medical center about their views on a large pharmacogenomics implementation, the PREDICT (Pharmacogenomic Resource for Enhanced Decisions in Care and Treatment) program. Participants were asked about test ordering, major factors influencing use of results, expectations of efficacy and responsibility for applying results to patient care. Virtually all respondents (99%) agreed that pharmacogenomics variants influence patients’ response to drug therapy. The majority (92%) favored immediate, active notification when a clinically significant drug-genome interaction was present. However, clinicians were divided on which providers were responsible for acting on a result when a prescription change was indicated and whether patients should be directly notified of a significant result. We concluded genotype results were valued for tailoring prescriptions, but clinicians do not agree on how to appropriately assign clinical responsibility for actionable results from a multiplexed panel.The Pharmacogenomics Journal advance online publication, 11 August 2015; doi:10.1038/tpj.2015.57.

PMID: 26261062

Family health history: An essential starting point for personalized risk assessment and disease prevention

Author: Henrich VC, Orlando LA

Pers Med. 2016;13(5):499-510

doi: 10.2217/pme-2016-0007

Implementation of a pharmacogenomics consult service to support the INGENIOUS trial.

Authors: Eadon MT, Desta Z, Levy KD, Decker BS, Pierson RC, Pratt VM, Callaghan JT, Rosenman MB, Carpenter JS, Holmes AM, McDonald CA, Benson EA, Patil AS, Vuppalanchi R, Gufford BT, Dave N, Robarge JD, Hyder MA, Haas DM, Kreutz RP, Dexter PR, Skaar TC, Flockhart DA

Clin Pharmacol Ther. 2016 Jul;100(1):63-6

Abstract: Hospital systems increasingly utilize pharmacogenomic testing to inform clinical prescribing. Successful implementation efforts have been modeled at many academic centers. In contrast, this report provides insights into the formation of a pharmacogenomics consultation service at a safety-net hospital, which predominantly serves low-income, uninsured, and vulnerable populations. The report describes the INdiana GENomics Implementation: an Opportunity for the UnderServed (INGENIOUS) trial and addresses concerns of adjudication, credentialing, and funding.

PMID: 26850569

Physician response to implementation of genotype-tailored antiplatelet therapy.

Authors: Peterson JF, Field JR, Unertl KM, Schildcrout JS, Johnson DC, Shi Y, Danciu I, Cleator JH, Pulley JM, McPherson JA, Denny JC, Laposata M, Roden DM, Johnson KB

Clin Pharmacol Ther. 2016 Jul;100(1):67-74

Abstract: Physician responses to genomic information are vital to the success of precision medicine initiatives. We prospectively studied a pharmacogenomics implementation program for the propensity of clinicians to select antiplatelet therapy based on CYP2C19 loss-of-function variants in stented patients. Among 2,676 patients, 514 (19.2%) were found to have a CYP2C19 variant affecting clopidogrel metabolism. For the majority (93.6%) of the cohort, cardiologists received active and direct notification of CYP2C19 status. Over 12 months, 57.6% of poor metabolizers and 33.2% of intermediate metabolizers received alternatives to clopidogrel. CYP2C19 variant status was the most influential factor impacting the prescribing decision (hazard ratio [HR] in poor metabolizers 8.1, 95% confidence interval [CI] [5.4, 12.2] and HR 5.0, 95% CI [4.0, 6.3] in intermediate metabolizers), followed by patient age and type of stent implanted. We conclude that cardiologists tailored antiplatelet therapy for a minority of patients with a CYP2C19 variant and considered both genomic and nongenomic risks in their clinical decision-making.

PMID: 26693963

CUSTOM-SEQ: a prototype for oncology rapid learning in a comprehensive EHR environment

Author: Warner JL, Wang L, Pao W, Sosman JA, Atreya RV, Carney P, Levy MA

J Am Med Inform Assoc. 2016 Jul;23(4):692-700

PMID: 27008846

doi: 10.1093/jamia/ocw008

Impact of Genetic Testing and Family Health History Based Risk Counseling on Behavior Change and Cognitive Precursors for Type 2 Diabetes

Author: Wu RR, Meyers RA, Hauser ER, Vorderstrasse A, Cho A, Ginsburg GS, Orlando LA

J Genet Couns 2017 Feb;26(1):133-140. Epub 2016 Jun 14.

PMID: 27296809

doi: 10.1007/s10897-016-9988-z

CYP2C19 and CES1 Polymorphisms and Efficacy of Clopidogrel and Aspirin Dual Antiplatelet Therapy in Patients with Symptomatic Intracranial Atherosclerotic Disease

Authors: Hoh BL, Gong Y, McDonough CW, Waters MF, Royster AJ, Sheehan TO, Burkley B, Langaee TY, Mocco J, Zuckerman SL, Mummareddy N, Stephens ML II, Ingram C, Shaffer CM, Denny JC, Brilliant MH, Kitchner TE, Linneman JG, Roden DM, Johnson JA

J Neurosurg. 2016 Jun;124(6):1746-1751. Epub 2015 Nov 20

PMID: 26587656

doi: 10.3171/2015.6.JNS15795

Development and preliminary evaluation of an online educational video about whole-genome sequencing for research participants, patients, and the general public

Authors: Sanderson SC, Suckiel SA, Zweig M, Bottinger EP, Jabs EW, Richardson LD

Genet Med. 2016 May;18(5):501-12.

doi: 10.1038/gim.2015.118

PMID: 26334178

Implementing Pharmacogenomics at Your Institution: Establishment and Overcoming Implementation Challenges.

Authors: Arwood MJ, Chumnumwat S, Cavallari LH, Nutescu EA, Duarte JD

Clin Transl Sci. 2016 May 23;

Abstract: With advancements in pharmacogenomics research and genotyping technology, implementation of pharmacogenomics into clinical practice is now feasible. The aim of this publication is to serve as a tutorial for institutions interested in developing pharmacogenomics services. Topics covered include resources needed, clinical decision support establishment, choosing a genotyping platform, and challenges faced with pharmacogenomics service implementation. This tutorial provides practical advice, drawing upon experience of two established clinical pharmacogenomics services. This article is protected by copyright. All rights reserved.

PMID: 27214750

Multiplex SNaPshot-a new simple and efficient CYP2D6 and ADRB1 genotyping method.

Authors: Ben S, Cooper-DeHoff RM, Flaten HK, Evero O, Ferrara TM, Spritz RA, Monte AA

Hum Genomics. 2016 Apr 23;10:11.

Abstract: Reliable, inexpensive, high-throughput genotyping methods are required for clinical trials. Traditional assays require numerous enzyme digestions or are too expensive for large sample volumes. Our objective was to develop an inexpensive, efficient, and reliable assay for CYP2D6 and ADRB1 accounting for numerous polymorphisms including gene duplications. MATERIALS AND METHODS: We utilized the multiplex SNaPshot® custom genotype method to genotype CYP2D6 and ADRB1. We compared the method to reference standards genotyped using the Taqman Copy Number Variant Assay followed by pyrosequencing quantification and determined assigned genotype concordance. RESULTS: We genotyped 119 subjects. Seven (5.9 %) were found to be CYP2D6 poor metabolizers (PMs), 18 (15.1 %) intermediate metabolizers (IMs), 89 (74.8 %) extensive metabolizers (EMs), and 5 (4.2 %) ultra-rapid metabolizers (UMs). We genotyped two variants in the β1-adrenoreceptor, rs1801253 (Gly389Arg) and rs1801252 (Ser49Gly). The Gly389Arg genotype is Gly/Gly 18 (15.1 %), Gly/Arg 58 (48.7 %), and Arg/Arg 43 (36.1 %). The Ser49Gly genotype is Ser/Ser 82 (68.9 %), Ser/Gly 32 (26.9), and Gly/Gly 5 (4.2 %). The multiplex SNaPshot method was concordant with genotypes in reference samples. CONCLUSIONS: The multiplex SNaPshot method allows for specific and accurate detection of CYP2D6 genotypes and ADRB1 genotypes and haplotypes. This platform is simple and efficient and suited for high throughput.

PMID: 27108086

The Path(way) Less Traveled: A Pathway-Oriented Approach to Providing Information about Precision Cancer Medicine on My Cancer Genome

Author: Taylor AD, Micheel CM, Anderson IA, Levy MA, Lovly CM

Transl Oncol. 2016 Apr;9(2):163-5

PMID: 27084433

doi: 10.1016/j.tranon.2016.03.001

A prognostic model based on readily available clinical data enriched a pre-emptive pharmacogenetic testing program.

Authors: Schildcrout JS, Shi Y, Danciu I, Bowton E, Field JR, Pulley JM, Basford MA, Gregg W, Cowan JD, Harrell FE, Roden DM, Peterson JF, Denny JC

J Clin Epidemiol. 2016 Apr;72:107-15

Abstract: OBJECTIVES: We describe the development, implementation, and evaluation of a model to pre-emptively select patients for genotyping based on medication exposure risk. STUDY DESIGN AND SETTING: Using deidentified electronic health records, we derived a prognostic model for the prescription of statins, warfarin, or clopidogrel. The model was implemented into a clinical decision support (CDS) tool to recommend pre-emptive genotyping for patients exceeding a prescription risk threshold. We evaluated the rule on an independent validation cohort and on an implementation cohort, representing the population in which the CDS tool was deployed. RESULTS: The model exhibited moderate discrimination with area under the receiver operator characteristic curves ranging from 0.68 to 0.75 at 1 and 2 years after index dates. Risk estimates tended to underestimate true risk. The cumulative incidences of medication prescriptions at 1 and 2 years were 0.35 and 0.48, respectively, among 1,673 patients flagged by the model. The cumulative incidences in the same number of randomly sampled subjects were 0.12 and 0.19, and in patients over 50 years with the highest body mass indices, they were 0.22 and 0.34. CONCLUSION: We demonstrate that prognostic algorithms can guide pre-emptive pharmacogenetic testing toward those likely to benefit from it.

PMID: 26628336

Toward rapid learning in cancer treatment selection: An analytical engine for practice-based clinical data.

Authors: Finlayson SG, Levy M, Reddy S, Rubin DL

J Biomed Inform. 2016 Apr;60:104-13

Abstract: OBJECTIVE: Wide-scale adoption of electronic medical records (EMRs) has created an unprecedented opportunity for the implementation of Rapid Learning Systems (RLSs) that leverage primary clinical data for real-time decision support. In cancer, where large variations among patient features leave gaps in traditional forms of medical evidence, the potential impact of a RLS is particularly promising. We developed the Melanoma Rapid Learning Utility (MRLU), a component of the RLS, providing an analytical engine and user interface that enables physicians to gain clinical insights by rapidly identifying and analyzing cohorts of patients similar to their own. MATERIALS AND METHODS: A new approach for clinical decision support in Melanoma was developed and implemented, in which patient-centered cohorts are generated from practice-based evidence and used to power on-the-fly stratified survival analyses. A database to underlie the system was generated from clinical, pharmaceutical, and molecular data from 237 patients with metastatic melanoma from two academic medical centers. The system was assessed in two ways: (1) ability to rediscover known knowledge and (2) potential clinical utility and usability through a user study of 13 practicing oncologists. RESULTS: The MRLU enables physician-driven cohort selection and stratified survival analysis. The system successfully identified several known clinical trends in melanoma, including frequency of BRAF mutations, survival rate of patients with BRAF mutant tumors in response to BRAF inhibitor therapy, and sex-based trends in prevalence and survival. Surveyed physician users expressed great interest in using such on-the-fly evidence systems in practice (mean response from relevant survey questions 4.54/5.0), and generally found the MRLU in particular to be both useful (mean score 4.2/5.0) and useable (4.42/5.0). DISCUSSION: The MRLU is an RLS analytical engine and user interface for Melanoma treatment planning that presents design principles useful in building RLSs. Further research is necessary to evaluate when and how to best use this functionality within the EMR clinical workflow for guiding clinical decision making. CONCLUSION: The MRLU is an important component in building a RLS for data driven precision medicine in Melanoma treatment that could be generalized to other clinical disorders. Copyright © 2016 Elsevier Inc. All rights reserved.

PMID: 26836975

An openly available online tool for implementing the ACMG/AMP standards and guidelines for the interpretation of sequence variants.

Authors: Kleinberger J, Maloney KA, Pollin TI, Jeng LJ

Genet Med. 2016 Mar 17;

To the Editor: The joint consensus recommendation of the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) on standards and guidelines for the interpretation of sequence variants, published in the May 2015 issue of Genetics in Medicine, is an excellent resource and reference for interpreting the clinical significance of next-generation sequencing variants using multiple categories and degrees of evidence.1 In our activities concerned with variant interpretation, we use the directives in the article extensively.
To facilitate the process, we created an interactive tool based on the article that has been a valuable addition to our process, and we believe it would be useful for others performing variant interpretation.

PMID: 26986878

Implementing and Improving Automated Electronic Tumor Molecular Profiling

Authors: Rioth MJ, Staggs DB, Hackett L, Haberman E, Tod M, Levy M, Warner J

J Oncol Pract. 2016 Mar;12(3):e332-7

PMID: 26813927

doi: 10.1200/JOP.2015.008276

 

Clinical utility of a Web-enabled risk-assessment and clinical decision support program.

Authors: Orlando LA, Wu RR, Myers RA, Buchanan AH, Henrich VC, Hauser ER, Ginsburg GS

Genet Med. 2016 2016 Oct;18(10):1020-8. doi: 10.1038/gim.2015.210. Epub 2016 Mar 3.

PURPOSE: Risk-stratified guidelines can improve quality of care and cost-effectiveness, but their uptake in primary care has been limited. MeTree, a Web-based, patient-facing risk-assessment and clinical decision support tool, is designed to facilitate uptake of risk-stratified guidelines. METHODS: A hybrid implementation-effectiveness trial of three clinics (two intervention, one control). PARTICIPANTS: consentable nonadopted adults with upcoming appointments. PRIMARY OUTCOME: agreement between patient risk level and risk management for those meeting evidence-based criteria for increased-risk risk-management strategies (increased risk) and those who do not (average risk) before MeTree and after. MEASURES: chart abstraction was used to identify risk management related to colon, breast, and ovarian cancer, hereditary cancer, and thrombosis. RESULTS: Participants = 488, female = 284 (58.2%), white = 411 (85.7%), mean age = 58.7 (SD = 12.3). Agreement between risk management and risk level for all conditions for each participant, except for colon cancer, which was limited to those <50 years of age, was (i) 1.1% (N = 2/174) for the increased-risk group before MeTree and 16.1% (N = 28/174) after and (ii) 99.2% (N = 2,125/2,142) for the average-risk group before MeTree and 99.5% (N = 2,131/2,142) after. Of those receiving increased-risk risk-management strategies at baseline, 10.5% (N = 2/19) met criteria for increased risk. After MeTree, 80.7% (N = 46/57) met criteria. CONCLUSION: MeTree integration into primary care can improve uptake of risk-stratified guidelines and potentially reduce “overuse” and “underuse” of increased-risk services.

PMID: 26938783

Cardiovascular Pharmacogenomics-Implications for Patients With CKD.

Authors: Cavallari LH, Mason DL

Adv Chronic Kidney Dis. 2016 Mar;23(2):82-90

Abstract: CKD is an independent risk factor for cardiovascular disease (CVD). Thus, patients with CKD often require treatment with cardiovascular drugs, such as antiplatelet, antihypertensive, anticoagulant, and lipid-lowering agents. There is significant interpatient variability in response to cardiovascular therapies, which contributes to risk for treatment failure or adverse drug effects. Pharmacogenomics offers the potential to optimize cardiovascular pharmacotherapy and improve outcomes in patients with CVD, although data in patients with concomitant CKD are limited. The drugs with the most pharmacogenomic evidence are warfarin, clopidogrel, and statins. There are also accumulating data for genetic contributions to β-blocker response. Guidelines are now available to assist with applying pharmacogenetic test results to optimize warfarin dosing, selection of antiplatelet therapy after percutaneous coronary intervention, and prediction of risk for statin-induced myopathy. Clinical data, such as age, body size, and kidney function have long been used to optimize drug prescribing. An increasing number of institutions are also implementing genetic testing to be considered in the context of important clinical factors to further personalize drug therapy for patients with CVD.

PMID: 26979147

Analytical Validation of a Personalized Medicine APOL1 Genotyping Assay for Nondiabetic Chronic Kidney Disease Risk Assessment

Authors: Zhang J, Fedick A, Wasserman S, Zhao G, Scott SA.

The Journal of molecular diagnostics : JMD. 2016 Mar;18(2):260-6.

Determining the effects and challenges of incorporating genetic testing into primary care management of hypertensive patients with African ancestry.

Authors: Horowitz CR, Abul-Husn NS, Ellis S, Ramos MA, Negron R, Suprun M, Zinberg RE, Sabin T, Hauser D, Calman N, Bagiella E, Bottinger EP

Contemp Clin Trials. 2016 Mar;47:101-8

Abstract: People of African ancestry (Blacks) have increased risk of kidney failure due to numerous socioeconomic, environmental, and clinical factors. Two variants in the APOL1 gene are now thought to account for much of the racial disparity associated with hypertensive kidney failure in Blacks. However, this knowledge has not been translated into clinical care to help improve patient outcomes and address disparities. GUARDD is a randomized trial to evaluate the effects and challenges of incorporating genetic risk information into primary care. Hypertensive, non-diabetic, adults with self-reported African ancestry, without kidney dysfunction, are recruited from diverse clinical settings and randomized to undergo APOL1 genetic testing at baseline (intervention) or at one year (waitlist control). Providers are educated about genomics and APOL1. Guided by a genetic counselor, trained staff return APOL1 results to patients and provide low-literacy educational materials. Real-time clinical decision support tools alert clinicians of their patients’ APOL1 results and associated risk status at the point of care. Our academic-community-clinical partnership designed a study to generate information about the impact of genetic risk information on patient care (blood pressure and renal surveillance) and on patient and provider knowledge, attitudes, beliefs, and behaviors. GUARDD will help establish the effective implementation of APOL1 risk-informed management of hypertensive patients at high risk of CKD, and will provide a robust framework for future endeavors to implement genomic medicine in diverse clinical practices. It will also add to the important dialog about factors that contribute to and may help eliminate racial disparities in kidney disease.

PMID: 26747051

Genomics in CKD: Is This the Path Forward?

Authors: Nadkarni GN, Horowitz CR

Adv Chronic Kidney Dis. 2016 Mar;23(2):120-4

Abstract: Recent advances in genomics and sequencing technology have led to a better understanding of genetic risk in CKD. Genetics could account in part for racial differences in treatment response for medications including antihypertensives and immunosuppressive medications due to its correlation with ancestry. However, there is still a substantial lag between generation of this knowledge and its adoption in routine clinical care. This review summarizes the recent advances in genomics and CKD, discusses potential reasons for its underutilization, and highlights potential avenues for application of genomic information to improve clinical care and outcomes in this particularly vulnerable population.
PMID: 26979150

Integrating electronic health record genotype and phenotype datasets to transform patient care.

Authors: Roden DM, Denny JC
Clin Pharmacol Ther. 2016 Mar;99(3):298-305
Abstract: The Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009 mandates the development and implementation of electronic health record (EHR) systems across the country. While a primary goal is to improve the care of individual patients, EHRs are also key enabling resources for a vision of individualized (or personalized or precision) medicine: the aggregation of multiple EHRs within or across healthcare systems should allow discovery of patient subsets that have unusual and definable clinical trajectories that deviate importantly from the expected response in a “typical” patient. The spectrum of such personalized care can then extend from prevention to choice of medication to intensity or nature of follow-up.

PMID: 26667791

Impact of GGCX, STX1B, and FPGS Polymorphisms on Warfarin Dose Requirements in European Americans and Egyptians

Authors: Hamadeh IS, Shahin MH, Lima SM, Oliveira F, Wilson L, Khalifa SI, Langaee TY, Cooper-DeHoff RM, Cavallari LH, Johnson JA

Clin Transl Sci. 2016 Feb;9(1):36-42. Epub 2016 Jan 19.

PMID: 26751406

doi: 10.1111/cts.12385

Advancing Pharmacogenomics as a Component of Precision Medicine: How, Where, and Who?

Authors: Johnson JA, Weitzel KW

Clin Pharmacol Ther. 2016 Feb;99(2):154-6

Abstract: Pharmacogenomics is an important element of precision medicine. Advances in pharmacogenomics implementation have been made but significant barriers remain, including evidence, reimbursement, and clinician knowledge, among others. Widespread adoption of pharmacogenomics requires overcoming these barriers, a clinician champion group, which we propose will be pharmacists, and an easily accessible setting, which may be the community pharmacy. Whatever the path, it must be evidence-driven and pharmacogenomics must improve drug-related outcomes to become a standard of care.

PMID: 26440500

Genetic and Nongenetic Factors Affecting Clopidogrel Response in the Egyptian Population.

Authors: Khalil BM, Shahin MH, Solayman MH, Langaee T, Schaalan MF, Gong Y, Hammad LN, Al-Mesallamy HO, Hamdy NM, El-Hammady WA, Johnson JA

Clin Transl Sci. 2016 Feb;9(1):23-8

Abstract: Aspirin and clopidogrel are the mainstay oral antiplatelet regimens, yet a substantial number of major adverse cardiac events (MACE) still occur. Herein, we investigated genetic and nongenetic factors associated with clopidogrel response in Egyptians. In all, 190 Egyptians with acute coronary syndrome (ACS) and/or percutaneous coronary intervention (PCI), treated with clopidogrel (75 mg/day) for at least a month, were genotyped for CYP2C19 *2, *3, *6, *8, *10, and *17, CES1 G143E and ABCB1*6 and *8. These variants along with nongenetic factors were tested for association with the risk of having MACE in clopidogrel-treated patients. CYP2C19 loss-of-function (LOF) alleles carriers had increased risk of MACE vs. noncarriers (odds ratio 2.52; 95% confidence interval 1.23-5.15, P = 0.011). In a logistic regression, CYP2C19 LOF variants (P = 0.011), age (P = 0.032), and body mass index (BMI, P = 0.039) were significantly associated with the incidence of MACE in patients taking clopidogrel. CYP2C19 genetic variants, age, and BMI are potential predictors associated with variability to clopidogrel response in Egyptians.

PMID: 26757134

Hypertension pharmacogenomics: in search of personalized treatment approaches.

Authors: Cooper-DeHoff RM, Johnson JA

Nat Rev Nephrol. 2016 Feb;12(2):110-22

Abstract: Cardiovascular and renal diseases are associated with many risk factors, of which hypertension is one of the most prevalent. Worldwide, blood pressure control is only achieved in ∼50% of those treated for hypertension, despite the availability of a considerable number of antihypertensive drugs from different pharmacological classes. Although many reasons exist for poor blood pressure control, a likely contributor is the inability to predict to which antihypertensive drug an individual is most likely to respond. Hypertension pharmacogenomics and other ‘omics’ technologies have the potential to identify genetic signals that are predictive of response or adverse outcome to particular drugs, and guide selection of hypertension treatment for a given individual. Continued research in this field will enhance our understanding of how to maximally deploy the various antihypertensive drug classes to optimize blood pressure response at the individual level. This Review summarizes the available literature on the most convincing genetic signals associated with antihypertensive drug responses and adverse cardiovascular outcomes. Future research in this area will be facilitated by enhancing collaboration between research groups through consortia such as the International Consortium for Antihypertensives Pharmacogenomics Studies, with the goal of translating replicated findings into clinical implementation.

PMID: 26592190

Pharmacogenetic allele nomenclature: International workgroup recommendations for test result reporting.

Authors: Kalman LV, Agúndez J, Appell ML, Black JL, Bell GC, Boukouvala S, Bruckner C, Bruford E, Caudle K, Coulthard SA, Daly AK, Tredici AD, den Dunnen JT, Drozda K, Everts RE, Flockhart D, Freimuth RR, Gaedigk A, Hachad H, Hartshorne T, Ingelman-Sundberg M, Klein TE, Lauschke VM, Maglott DR, McLeod HL, McMillin GA, Meyer UA, Müller DJ, Nickerson DA, Oetting WS, Pacanowski M, Pratt VM, Relling MV, Roberts A, Rubinstein WS, Sangkuhl K, Schwab M, Scott SA, Sim SC, Thirumaran RK, Toji LH, Tyndale RF, van Schaik R, Whirl-Carrillo M, Yeo K, Zanger UM

Clin Pharmacol Ther. 2016 Feb;99(2):172-85

Abstract: This article provides nomenclature recommendations developed by an international workgroup to increase transparency and standardization of pharmacogenetic (PGx) result reporting. Presently, sequence variants identified by PGx tests are described using different nomenclature systems. In addition, PGx analysis may detect different sets of variants for each gene, which can affect interpretation of results. This practice has caused confusion and may thereby impede the adoption of clinical PGx testing. Standardization is critical to move PGx forward.

PMID: 26479518

Pharmacogenomically actionable medications in a safety net health care system.

Authors: Carpenter JS, Rosenman MB, Knisely MR, Decker BS, Levy KD, Flockhart DA.

SAGE Open Med. 2016 Jan 7;4:2050312115624333

Abstract: OBJECTIVE: Prior to implementing a trial to evaluate the economic costs and clinical outcomes of pharmacogenetic testing in a large safety net health care system, we determined the number of patients taking targeted medications and their clinical care encounter sites. METHODS: Using 1-year electronic medical record data, we evaluated the number of patients who had started one or more of 30 known pharmacogenomically actionable medications and the number of care encounter sites the patients had visited. RESULTS: Results showed 7039 unique patients who started one or more of the target medications within a 12-month period with visits to 73 care sites within the system. CONCLUSION: Findings suggest that the type of large-scale, multi-drug, multi-gene approach to pharmacogenetic testing we are planning is widely relevant, and successful implementation will require wide-scale education of prescribers and other personnel involved in medication dispensing and handling.

PMID: 26835014

The IGNITE network: a model for genomic medicine implementation and research.

Authors: Weitzel KW, Alexander M, Bernhardt BA, Calman N, Carey DJ, Cavallari LH, Field JR, Hauser D, Junkins HA, Levin PA, Levy K, Madden EB, Manolio TA, Odgis J, Orlando LA, Pyeritz R,

Wu RR, Shuldiner AR, Bottinger EP, Denny JC, Dexter PR, Flockhart DA, Horowitz CR, Johnson JA, Kimmel SE, Levy MA, Pollin TI, Ginsburg GS, IGNITE Network

BMC Med Genomics. 2016 Jan 5;9:1

Abstract: BACKGROUND: Patients, clinicians, researchers and payers are seeking to understand the value of using genomic information (as reflected by genotyping, sequencing, family history or other data) to inform clinical decision-making. However, challenges exist to widespread clinical implementation of genomic medicine, a prerequisite for developing evidence of its real-world utility. METHODS: To address these challenges, the National Institutes of Health-funded IGNITE (Implementing GeNomics In pracTicE; www.ignite-genomics.org ) Network, comprised of six projects and a coordinating center, was established in 2013 to support the development, investigation and dissemination of genomic medicine practice models that seamlessly integrate genomic data into the electronic health record and that deploy tools for point of care decision making. IGNITE site projects are aligned in their purpose of testing these models, but individual projects vary in scope and design, including exploring genetic markers for disease risk prediction and prevention, developing tools for using family history data, incorporating pharmacogenomic data into clinical care, refining disease diagnosis using sequence-based mutation discovery, and creating novel educational approaches. RESULTS: This paper describes the IGNITE Network and member projects, including network structure, collaborative initiatives, clinical decision support strategies, methods for return of genomic test results, and educational initiatives for patients and providers. Clinical and outcomes data from individual sites and network-wide projects are anticipated to begin being published over the next few years. CONCLUSIONS: The IGNITE Network is an innovative series of projects and pilot demonstrations aiming to enhance translation of validated actionable genomic information into clinical settings and develop and use measures of outcome in response to genome-based clinical interventions using a pragmatic framework to provide early data and proofs of concept on the utility of these interventions. Through these efforts and collaboration with other stakeholders, IGNITE is poised to have a significant impact on the acceleration of genomic information into medical practice.

PMID: 26729011

Characterization of 137 Genomic DNA Reference Materials for 28 Pharmacogenetic Genes: A GeT-RM Collaborative Project.

Authors: Pratt VM, Everts RE, Aggarwal P, Beyer BN, Broeckel U, Epstein-Baak R, Hujsak P, Kornreich R, Liao J, Lorier R, Scott SA, Smith CH, Toji LH, Turner A, Kalman LV

J Mol Diagn. 2016 Jan;18(1):109-23

Abstract: Pharmacogenetic testing is increasingly available from clinical laboratories. However, only a limited number of quality control and other reference materials are currently available to support clinical testing. To address this need, the Centers for Disease Control and Prevention-based Genetic Testing Reference Material Coordination Program, in collaboration with members of the pharmacogenetic testing community and the Coriell Cell Repositories, has characterized 137 genomic DNA samples for 28 genes commonly genotyped by pharmacogenetic testing assays (CYP1A1, CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4, CYP3A5, CYP4F2, DPYD, GSTM1, GSTP1, GSTT1, NAT1, NAT2, SLC15A2, SLC22A2, SLCO1B1, SLCO2B1, TPMT, UGT1A1, UGT2B7, UGT2B15, UGT2B17, and VKORC1). One hundred thirty-seven Coriell cell lines were selected based on ethnic diversity and partial genotype characterization from earlier testing. DNA samples were coded and distributed to volunteer testing laboratories for targeted genotyping using a number of commercially available and laboratory developed tests. Through consensus verification, we confirmed the presence of at least 108 variant pharmacogenetic alleles. These samples are also being characterized by other pharmacogenetic assays, including next-generation sequencing, which will be reported separately. Genotyping results were consistent among laboratories, with most differences in allele assignments attributed to assay design and variability in reported allele nomenclature, particularly for CYP2D6, UGT1A1, and VKORC1. These publicly available samples will help ensure the accuracy of pharmacogenetic testing.

PMID: 26621101

When Participants in Genomic Research Grow Up: Contact and Consent at the Age of Majority.

Authors: Brothers KB, Holm IA, Childerhose JE, Antommaria AH, Bernhardt BA, Clayton EW, Gelb BD, Joffe S, Lynch JA, McCormick JB, McCullough LB, Parsons DW, Sundaresan AS, Wolf WA, Yu JH, Wilfond BS, Pediatrics Workgroup of the Clinical Sequencing Exploratory Research (CSER) Consortium, Pediatrics Workgroup of the Clinical Sequencing Exploratory Research CSER Consortium

J Pediatr. 2016 Jan;168:226-31.e1

PMID: 26477867

Guiding Oncology Patients Through the Maze of Precision Medicine

Authors: Giuse NB, Kusnoor SV, Koonce TY, Naylor HM, Chen SC, Blasingame MN, Anderson IA, Micheel CM, Levy MA, Ye F, Lovly CM

J Health Commun. 2016;21 Suppl 1:5-17

PMID: 27043753

doi: 10.1080/10810730.2015.1131772

Undiagnosed MODY: Time for Action.

Authors: Kleinberger JW, Pollin TI

Curr Diab Rep. 2015 Dec;15(12):110

Abstract: Maturity-onset diabetes of the young (MODY) is a monogenic form of diabetes that accounts for at least 1 % of all cases of diabetes mellitus. MODY classically presents as non-insulin-requiring diabetes in lean individuals typically younger than 25 with evidence of autosomal dominant inheritance, but these criteria do not capture all cases and can also overlap with other diabetes types. Genetic diagnosis of MODY is important for selecting the right treatment, yet ~95 % of MODY cases in the USA are misdiagnosed. MODY prevalence and characteristics have been well-studied in some populations, such as the UK and Norway, while other ethnicities, like African and Latino, need much more study. Emerging next-generation sequencing methods are making more widespread study and clinical diagnosis increasingly feasible; at the same time, they are detecting other mutations in the same genes of unknown clinical significance. This review will cover the current epidemiological studies of MODY and barriers and opportunities for moving toward a goal of access to an appropriate diagnosis for all affected individuals.

PMID: 26458381

Protocol for the “Implementation, adoption, and utility of family history in diverse care settings” study.

Authors: Wu RR, Myers RA, McCarty CA, Dimmock D, Farrell M, Cross D, Chinevere TD, Ginsburg GS, Orlando LA, Family Health History Network

Implement Sci. 2015 Nov 24;10:163.

Abstract: BACKGROUND: Risk assessment with a thorough family health history is recommended by numerous organizations and is now a required component of the annual physical for Medicare beneficiaries under the Affordable Care Act. However, there are several barriers to incorporating robust risk assessments into routine care. MeTree, a web-based patient-facing health risk assessment tool, was developed with the aim of overcoming these barriers. In order to better understand what factors will be instrumental for broader adoption of risk assessment programs like MeTree in clinical settings, we obtained funding to perform a type III hybrid implementation-effectiveness study in primary care clinics at five diverse healthcare systems. Here, we describe the study’s protocol. METHODS/DESIGN: MeTree collects personal medical information and a three-generation family health history from patients on 98 conditions. Using algorithms built entirely from current clinical guidelines, it provides clinical decision support to providers and patients on 30 conditions. All adult patients with an upcoming well-visit appointment at one of the 20 intervention clinics are eligible to participate. Patient-oriented risk reports are provided in real time. Provider-oriented risk reports are uploaded to the electronic medical record for review at the time of the appointment. Implementation outcomes are enrollment rate of clinics, providers, and patients (enrolled vs approached) and their representativeness compared to the underlying population. Primary effectiveness outcomes are the percent of participants newly identified as being at increased risk for one of the clinical decision support conditions and the percent with appropriate risk-based screening. Secondary outcomes include percent change in those meeting goals for a healthy lifestyle (diet, exercise, and smoking). Outcomes are measured through electronic medical record data Abstract:ion, patient surveys, and surveys/qualitative interviews of clinical staff. DISCUSSION: This study evaluates factors that are critical to successful implementation of a web-based risk assessment tool into routine clinical care in a variety of healthcare settings. The result will identify resource needs and potential barriers and solutions to implementation in each setting as well as an understanding potential effectiveness. TRIAL REGISTRATION: NCT01956773.

PMID: 26597091

Integration of Genomics in Primary Care

Authors: Larson EA, and Wilke RA

Am J Med. 2015 Nov;128(11):1251.e1-5

PMID: 26031886

doi: 10.1016/j.amjmed.2015.05.011

Pharmacogenetics: Using Genetic Information to Guide Drug Therapy.

Authors: Chang KL, Weitzel K, Schmidt S

Am Fam Physician. 2015 Oct 1;92(7):588-94

Abstract: Clinical pharmacogenetics, the use of genetic data to guide drug therapy decisions, is beginning to be used for medications commonly prescribed by family physicians. However, clinicians are largely unfamiliar with principles supporting clinical use of this type of data. For example, genetic variability in the cytochrome P450 2D6 drug metabolizing enzyme can alter the clinical effects of some opioid analgesics (e.g., codeine, tramadol), whereas variability in the CYP2C19 enzyme affects the antiplatelet agent clopidogrel. If testing is performed, patients who are ultrarapid or poor metabolizers of CYP2D6 should avoid codeine use (and possibly tramadol, hydrocodone, and oxycodone) because of the potential for increased toxicity or lack of effectiveness. Patients undergoing percutaneous coronary intervention for acute coronary syndromes who are known to be poor metabolizers of CYP2C19 should consider alternate antiplatelet therapy (e.g., ticagrelor, prasugrel). Some guidelines are available that address appropriate drug therapy changes, and others are in development. Additionally, a number of clinical resources are emerging to support family physicians in the use of pharmacogenetics. When used appropriately, pharmacogenetic testing can be a practical tool to optimize drug therapy and avoid medication adverse effects.

PMID: 26447442

Family Health History: An Entry for Personalized Medical Practice in Primary Care

Authors: Henrich VC, Orlando LA

Fam Med Med Sci Res. 2015 Oct 15;4:185.

The successful practice of personalized medicine in primary care depends upon understanding a patient’s individual disease risk and anticipating the best course of treatment with the goal of maintaining good health. A personalized disease risk assessment leads to recommendations for evidence-based interventions that can delay/prevent disease onset or reduce the severity of disease. As the sophistication of medical diagnoses develops and new interventions become available, the value of collecting and analyzing family health history (FHH) for maintaining patient wellness by determining ‘the right treatment, at the right time, for the right patient’ is more apparent than ever. FHH remains underutilized in primary care, however, because of numerous barriers. Ironically, the introduction of genetic tests and genomic methods that identify carriers who might be vulnerable to a variety of medical conditions and diseases has simply raised the importance of collecting and utilizing FHH to guide patient management in primary care.

doi: 10.4172/2327-4972.1000185

Genetics of resistant hypertension: a novel pharmacogenomics phenotype.

Authors: El Rouby N, Cooper-DeHoff RM

Curr Hypertens Rep. 2015 Sep;17(9):583

Abstract: Resistant hypertension (RHTN), defined as an uncontrolled blood pressure despite the use of multiple antihypertensive medications, is an increasing clinical problem associated with increased cardiovascular (CV) risk, including stroke and target organ damage. Genetic variability in blood pressure (BP)-regulating genes and pathways may, in part, account for the variability in BP response to antihypertensive agents, when taken alone or in combination, and may contribute to the RHTN phenotype. Pharmacogenomics focuses on the identification of genetic factors responsible for inter-individual variability in drug response. Expanding pharmacogenomics research to include patients with RHTN taking multiple BP-lowering medications may identify genetic markers associated with RHTN. To date, the available evidence surrounding pharmacogenomics in RHTN is limited and primarily focused on candidate genes. In this review, we summarize the most current data in RHTN pharmacogenomics and offer some recommendations on how to advance the field.

PMID: 26198781

Pharmacogenomics of hypertension and heart disease.

Authors: Arwood MJ, Cavallari LH, Duarte JD

Curr Hypertens Rep. 2015 Sep;17(9):586

Abstract: Heart disease is a leading cause of death in the United States, and hypertension is a predominant risk factor. Thus, effective blood pressure control is important to prevent adverse sequelae of hypertension, including heart failure, coronary artery disease, atrial fibrillation, and ischemic stroke. Over half of Americans have uncontrolled blood pressure, which may in part be explained by interpatient variability in drug response secondary to genetic polymorphism. As such, pharmacogenetic testing may be a supplementary tool to guide treatment. This review highlights the pharmacogenetics of antihypertensive response and response to drugs that treat adverse hypertension-related sequelae, particularly coronary artery disease and atrial fibrillation. While pharmacogenetic evidence may be more robust for the latter with respect to clinical implementation, there is increasing evidence of genetic variants that may help predict antihypertensive response. However, additional research and validation are needed before clinical implementation guidelines for antihypertensive therapy can become a reality.

PMID: 26272307

A conceptual model for translating omic data into clinical action.

Authors: Herr TM, Bielinski SJ, Bottinger E, Brautbar A, Starren J, et al.

Journal of pathology informatics. 2015 Aug 31;6:46.

Clinician Perspectives on Using Pharmacogenomics in Clinical Practice.

Authors: Unertl KM, Field JR, Price L, Peterson JF

Per Med. 2015 Aug;12(4):339-347

Abstract: AIM: To describe the knowledge and attitudes of clinicians participating in a large pharmacogenomics implementation program. MATERIALS & METHODS: Semi-structured interviews with 15 physicians and nurse practitioners were conducted. RESULTS: Three categories of themes were identified: preparation and knowledge, pharmacogenomics usage in practice, and future management of genomic variants. Providers expressed an inability to keep up with the rapid pace of evidence generation and indicated strong support for clinical decision support to assist with genotype-tailored therapies. Concerns raised by clinicians included effectively communicating results, long-term responsibility for actionable results and hand-offs with providers outside the implementation program. CONCLUSIONS: Clinicians identified their own knowledge deficits, workflow integration, and longitudinal responsibility as challenges to successful usage of pharmacogenomics in clinical practice.

PMID: 26635887

Effect of Genetic African Ancestry on eGFR and Kidney Disease

Authors: Udler MS, Nadkarni GN, Belbin G, Lotay V, Wyatt C, Gottesman O, Bottinger EP, Kenny EE, Peter I

J Am Soc Nephrol. 2015 Jul;26(7):1682-92.

doi: 10.1681/ASN.2014050474.PMID:25349204

FDA’s draft guidance on laboratory-developed tests increases clinical and economic risk to adoption of pharmacogenetic testing.

Authors: Levy KD, Pratt VM, Skaar TC, Vance GH, Flockhart DA

J Clin Pharmacol. 2015 Jul;55(7):725-7

PMID: 26053647

Cypiripi: exact genotyping of CYP2D6 using high-throughput sequencing data.

Authors: Numanagić I, Malikić S, Pratt VM, Skaar TC, Flockhart DA, Sahinalp SC

Bioinformatics. 2015 Jun 15;31(12):i27-34

Abstract: MOTIVATION: CYP2D6 is highly polymorphic gene which encodes the (CYP2D6) enzyme, involved in the metabolism of 20-25% of all clinically prescribed drugs and other xenobiotics in the human body. CYP2D6 genotyping is recommended prior to treatment decisions involving one or more of the numerous drugs sensitive to CYP2D6 allelic composition. In this context, high-throughput sequencing (HTS) technologies provide a promising time-efficient and cost-effective alternative to currently used genotyping techniques. To achieve accurate interpretation of HTS data, however, one needs to overcome several obstacles such as high sequence similarity and genetic recombinations between CYP2D6 and evolutionarily related pseudogenes CYP2D7 and CYP2D8, high copy number variation among individuals and short read lengths generated by HTS technologies. RESULTS: In this work, we present the first algorithm to computationally infer CYP2D6 genotype at basepair resolution from HTS data. Our algorithm is able to resolve complex genotypes, including alleles that are the products of duplication, deletion and fusion events involving CYP2D6 and its evolutionarily related cousin CYP2D7. Through extensive experiments using simulated and real datasets, we show that our algorithm accurately solves this important problem with potential clinical implications. AVAILABILITY AND IMPLEMENTATION: Cypiripi is available at http://sfu-compbio.github.io/cypiripi.

PMID: 26072492

Personalized medicine in diabetes mellitus: current opportunities and future prospects.

Authors: Kleinberger JW, Pollin TI

Ann N Y Acad Sci. 2015 Jun;1346(1):45-56

Abstract: Diabetes mellitus affects approximately 382 million individuals worldwide and is a leading cause of morbidity and mortality. Over 40 and nearly 80 genetic loci influencing susceptibility to type 1 and type 2 diabetes, respectively, have been identified. In addition, there is emerging evidence that some genetic variants help to predict response to treatment. Other variants confer apparent protection from diabetes or its complications and may lead to development of novel treatment approaches. Currently, there is clear clinical utility to genetic testing to find the at least 1% of diabetic individuals who have monogenic diabetes (e.g., maturity-onset diabetes of the young and KATP channel neonatal diabetes). Diagnosing many of these currently underdiagnosed types of diabetes enables personalized treatment, resulting in improved and less invasive glucose control, better prediction of prognosis, and enhanced familial risk assessment. Efforts to enhance the rate of detection, diagnosis, and personalized treatment of individuals with monogenic diabetes should set the stage for effective clinical translation of current genetic, pharmacogenetic, and pharmacogenomic research of more complex forms of diabetes.

PMID: 25907167

Pharmacogenomics in cardiology—genetics and drug response: 10 years of progress.

Authors: Cavallari LH, Weitzel K

Future Cardiol. 2015 May;11(3):281-6

PMID: 26021633

Phenotyping Adverse Drug Reactions: Statin-Related Myotoxicity.

Authors: Wiley LK, Moretz JD, Denny JC, Peterson JF, Bush WS

AMIA Jt Summits Transl Sci Proc. 2015 Mar 25;2015:466-70.

Abstract: It is unclear the extent to which best practices for phenotyping disease states from electronic medical records (EMRs) translate to phenotyping adverse drug events. Here we use statin-induced myotoxicity as a case study to identify best practices in this area. We compared multiple phenotyping algorithms using administrative codes, laboratory measurements, and full-text keyword matching to identify statin-related myopathy from EMRs. Manual review of 300 deidentified EMRs with exposure to at least one statin, created a gold standard set of 124 cases and 176 controls. We tested algorithms using ICD-9 billing codes, laboratory measurements of creatine kinase (CK) and keyword searches of clinical notes and allergy lists. The combined keyword algorithms produced were the most accurate (PPV=86%, NPV=91%). Unlike in most disease phenotyping algorithms, addition of ICD9 codes or laboratory data did not appreciably increase algorithm accuracy. We conclude that phenotype algorithms for adverse drug events should consider text based approaches.

PMID: 26306287

Report of new haplotype for ABCC2 gene: rs17222723 and rs8187718 in cis.

Authors: Pratt VM, Beyer BN, Koller DL, Skaar TC, Flockhart DA, Levy KD, Vance GH

J Mol Diagn. 2015 Mar;17(2):201-5

Abstract: The ATP-binding cassette, subfamily C [CFTR/MRP], member 2 (ABCC2) gene is a member of the ATP-binding cassette transporters and is involved in the transport of molecules across cellular membranes. Substrates transported by ABCC2 include antiepileptics, statins, tenofovir, cisplatin, irinotecan, and carbamazepine. Because of the pharmacogenomics implications, we developed a clinical laboratory-developed assay to test for seven variants in the ABCC2 gene: c.3563T>A (p.V1188E, rs17222723), c.1249G>A (p.V417I, rs2273697), c.3972C>T (p.I1324I, rs3740066), c.2302C>T (p.R768W, rs56199535), c.2366C>T (p.S789F, rs56220353), c.-24C>T (5’UTR, rs717620), and c.4544G>A (p.C1515Y, rs8187710). During the validation process, we noted several DNA samples, obtained from the Coriell Cell Repository, that contained both c.3563T>A, c.4544G>A, and a third variant, suggesting that c.3563T>A and c.4544G>A are in cis on the chromosome in some individuals. We obtained DNA samples from a trio (father, mother, and child), tested their ABCC2 variants, and confirmed that c.3563T>A and c.4544G>A were in cis on the same chromosome. Here, we report a new haplotype in ABCC2.

PMID: 25554586

Incorporating temporal EHR data in predictive models for risk stratification of renal function deterioration

Authors: Singh A, Nadkarni G, Gottesman O, Ellis SB, Bottinger EP, Guttag JV.
J Biomed Inform. 2015 Feb;53:220-8.

doi: 10.1016/j.jbi.2014.11.005.

PMID:25460205

Loss of heterozygosity at the CYP2D6 locus in breast cancer: implications for tamoxifen pharmacogenetic studies.

Authors: Johnson JA, Hamadeh IS, Langaee TY.

J Natl Cancer Inst. 2015 Jan 31;107(2)

PMID: 25638249

A novel simple method for determining CYP2D6 gene copy number and identifying allele(s) with duplication/multiplication.

Authors: Langaee T, Hamadeh I, Chapman AB, Gums JG, Johnson JA

PLoS One. 2015 Jan 27;10(1):e0113808

Abstract: BACKGROUND: Cytochrome P450 2D6 (CYP2D6) gene duplication and multiplication can result in ultrarapid drug metabolism and therapeutic failure or excessive response in patients. Long range polymerase chain reaction (PCR), restriction fragment length polymorphism (RFLP) and sequencing are usually used for genotyping CYP2D6 duplication/multiplications and identification, but are labor intensive, time consuming, and costly. METHODS: We developed a simple allele quantification-based Pyrosequencing genotyping method that facilitates CYP2D6 copy number variation (CNV) genotyping while also identifying allele-specific CYP2D6 CNV in heterozygous samples. Most routine assays do not identify the allele containing a CNV. A total of 237 clinical and Coriell DNA samples with different known CYP2D6 gene copy numbers were genotyped for CYP2D6 *2, *3, *4, *6, *10, *17, *41 polymorphisms and CNV determination. RESULTS: The CYP2D6 gene allele quantification/identification were determined simultaneously with CYP2D6*2, *3, *4, *6, *10, *17, *41 genotyping. We determined the exact CYP2D6 gene copy number, identified which allele had the duplication or multiplication, and assigned the correct phenotype and activity score for all samples. CONCLUSIONS: Our method can efficiently identify the duplicated CYP2D6 allele in heterozygous samples, determine its copy number in a fraction of time compared to conventional methods and prevent incorrect ultrarapid phenotype calls. It also greatly reduces the cost, effort and time associated with CYP2D6 CNV genotyping.

PMID: 25625348

Warfarin pharmacogenetics.

Authors: Johnson JA, Cavallari LH

Trends Cardiovasc Med. 2015 Jan;25(1):33-41

Abstract: The cytochrome P450 (CYP) 2C9 and vitamin K epoxide reductase complex 1 (VKORC1) genotypes have been strongly and consistently associated with warfarin dose requirements, and dosing algorithms incorporating genetic and clinical information have been shown to be predictive of stable warfarin dose. However, clinical trials evaluating genotype-guided warfarin dosing produced mixed results, calling into question the utility of this approach. Recent trials used surrogate markers as endpoints rather than clinical endpoints, further complicating translation of the data to clinical practice. The present data do not support genetic testing to guide warfarin dosing, but in the setting where genotype data are available, use of such data in those of European ancestry is reasonable. Outcomes data are expected from an on-going trial, observational studies continue, and more work is needed to define dosing algorithms that incorporate appropriate variants in minority populations; all these will further shape guidelines and recommendations on the clinical utility of genotype-guided warfarin dosing.

PMID: 25282448

The DNA of Pharmacy Education: CAPE Outcomes and Pharmacogenomics.

Authors: Kisor DF, Smith HE, Grace E, Johnson SG, Weitzel KW, Farrell CL

2015.  AACP Special Interest Group CAPE Paper

Emerging roles for pharmacists in clinical implementation of pharmacogenomics.

Authors: Owusu-Obeng A, Weitzel KW, Hatton RC, Staley BJ, Ashton J, Cooper-Dehoff RM, Johnson JA

Pharmacotherapy. 2014 Oct;34(10):1102-12

Abstract: Pharmacists are uniquely qualified to play essential roles in the clinical implementation of pharmacogenomics. However, specific responsibilities and resources needed for these roles have not been defined. We describe roles for pharmacists that emerged in the clinical implementation of genotype-guided clopidogrel therapy in the University of Florida Health Personalized Medicine Program, summarize preliminary program results, and discuss education, training, and resources needed to support such programs. Planning for University of Florida Health Personalized Medicine Program began in summer 2011 under leadership of a pharmacist, with clinical launch in June 2012 of a clopidogrel-CYP2C19 pilot project aimed at tailoring antiplatelet therapies for patients undergoing percutaneous coronary intervention and stent placement. More than 1000 patients were genotyped in the pilot project in year 1. Essential pharmacist roles and responsibilities that developed and/or emerged required expertise in pharmacy informatics (development of clinical decision support in the electronic medical record), medication safety, medication-use policies and processes, development of group and individual educational strategies, literature analysis, drug information, database management, patient care in targeted areas, logistical issues in genetic testing and follow-up, research and ethical issues, and clinical precepting. In the first 2 years of the program (1 year planning and 1 year postimplementation), a total of 14 different pharmacists were directly and indirectly involved, with effort levels ranging from a few hours per month, to 25-30% effort for the director and associate director, to nearly full-time for residents. Clinical pharmacists are well positioned to implement clinical pharmacogenomics programs, with expertise in pharmacokinetics, pharmacogenomics, informatics, and patient care. Education, training, and practice-based resources are needed to support these roles and to facilitate the development of financially sustainable pharmacist-led clinical pharmacogenomics practice models.

PMID: 25220280

The clinical pharmacogenetics implementation consortium guideline for SLCO1B1 and simvastatin-induced myopathy: 2014 update.

Authors: Ramsey LB, Johnson SG, Caudle KE, Haidar CE, Voora D, Wilke RA, Maxwell WD, McLeod HL, Krauss RM, Roden DM, Feng Q, Cooper-DeHoff RM, Gong L, Klein TE, Wadelius M, Niemi M

Clin Pharmacol Ther. 2014 Oct;96(4):423-8

Abstract: Simvastatin is among the most commonly used prescription medications for cholesterol reduction. A single coding single-nucleotide polymorphism, rs4149056T>C, in SLCO1B1 increases systemic exposure to simvastatin and the risk of muscle toxicity. We summarize evidence from the literature supporting this association and provide therapeutic recommendations for simvastatin based on SLCO1B1 genotype. This article is an update to the 2012 Clinical Pharmacogenetics Implementation Consortium guideline for SLCO1B1 and simvastatin-induced myopathy.

PMID: 24918167

Willingness to participate in genomics research and desire for personal results among underrepresented minority patients: a structured interview study

Authors: Sanderson SC, Diefenbach MA, Zinberg R, Horowitz CR, Richardson LD.

Journal of community genetics. 2013 Oct;4(4):469-82.

Prerequisites to implementing a pharmacogenomics program in a large health-care system.

Authors: Levy KD, Decker BS, Carpenter JS, Flockhart DA, Dexter PR, Desta Z, Skaar TC

Clin Pharmacol Ther. 2014 Sep;96(3):307-9

Abstract: Pharmacogenomics (PGx) technology is advancing rapidly; however, clinical adoption is lagging. The Indiana Institute of Personalized Medicine (IIPM) places a strong focus on translating PGx research into clinical practice. We describe what have been found to be the key requirements that must be delivered in order to ensure a successful and enduring PGx implementation within a large health-care system.

PMID: 24807457

Meaningful use of pharmacogenetics

Authors: Ratain M, Johnson JA

Clin Pharmacol Ther 2014;96:650-52

PMID: 25399712

doi: 10.1038/clpt.2014.188

The influence of the CYP2C19*10 allele on clopidogrel activation and CYP2C19*2 genotyping.

Authors: Langaee TY, Zhu HJ, Wang X, El Rouby N, Markowitz JS, Goldstein JA, Johnson JA

Pharmacogenet Genomics. 2014 Aug;24(8):381-6

Abstract: BACKGROUND/OBJECTIVES: The polymorphic hepatic enzyme CYP2C19 catalyzes the metabolism of clinically important drugs such as clopidogrel, proton-pump inhibitors, and others and clinical pharmacogenetic testing for clopidogrel is increasingly common. The CYP2C19*10 single-nucleotide polymorphism (SNP) is located 1 bp upstream the CYP2C19*2 SNP. Despite the low frequency of the CYP2C19*10 allele, its impact on metabolism of CYP2C19 substrates and CYP2C19*2 genotyping makes it an important SNP to consider for pharmacogenetic testing of CYP2C19. However, the effect of the CYP2C19*10 allele on clopidogrel metabolism has not been explored to date. METHODS: We measured the enzymatic activity of the CYP2C19.10 protein against clopidogrel. DNA samples from two clinical studies were genotyped for CYP2C19*2 and *10 by pyrosequencing genotyping method. RESULTS: The catalytic activity of CYP2C19.10 in the biotransformation of clopidogrel and 2-oxo-clopidogrel was significantly decreased relative to the wild-type CYP2C19.1B. We also reported that the CYP2C19*10 SNP interferes with the CYP2C19*2 TaqMan genotyping assay, resulting in miscalling of CYP2C19*10/*2 as CYP2C19*2/*2. CONCLUSIONS: Our data provide evidence that CYP2C19.10 variant partially metabolizes clopidogrel and 2-oxo-clopidogrel, and the presence of CYP2C19*10 allele affects the CY2C19*2 TaqMan genotyping assay and results in misclassification of CYP2C19*10/*2 as CYP2C19*2/*2.

PMID: 24945780

Implementation and utilization of genetic testing in personalized medicine Pharmacogenomics and personalized medicine

Authors: Abul-Husn NS, Owusu Obeng A, Sanderson SC, Gottesman O, Scott SA.

2014 Aug 13;7:227-40.

Use of a patient-entered family health history tool with decision support in primary care: impact of identification of increased risk patients on genetic counseling attendance

Authors: Buchanan A, Christianson CA, Himmel T, Powell KP, Agbaje A, Ginsburg GS, Henrich VC, Orlando LA

J Genet Couns 2015 Feb;24(1):179-88. Epub 2014 Aug 15.

PMID: 25120038

doi: 10.1007/s10897-014-9753-0

CYP2C19 polymorphisms and therapeutic drug monitoring of voriconazole: are we ready for clinical implementation of pharmacogenomics?

Authors: Owusu Obeng A, Egelund EF, Alsultan A, Peloquin CA, Johnson JA

Pharmacotherapy. 2014 Jul;34(7):703-18

Abstract: Since its approval by the U.S. Food and Drug Administration in 2002, voriconazole has become a key component in the successful treatment of many invasive fungal infections including the most common, aspergillosis and candidiasis. Despite voriconazole’s widespread use, optimizing its treatment in an individual can be challenging due to significant interpatient variability in plasma concentrations of the drug. Variability is due to nonlinear pharmacokinetics and the influence of patient characteristics such as age, sex, weight, liver disease, and genetic polymorphisms in the cytochrome P450 2C19 gene (CYP2C19) encoding for the CYP2C19 enzyme, the primary enzyme responsible for metabolism of voriconazole. CYP2C19 polymorphisms account for the largest portion of variability in voriconazole exposure, posing significant difficulty to clinicians in targeting therapeutic concentrations. In this review, we discuss the role of CYP2C19 polymorphisms and their influence on voriconazole’s pharmacokinetics, adverse effects, and clinical efficacy. Given the association between CYP2C19 genotype and voriconazole concentrations, as well as the association between voriconazole concentrations and clinical outcomes, particularly efficacy, it seems reasonable to suggest a potential role for CYP2C19 genotype to guide initial voriconazole dose selection followed by therapeutic drug monitoring to increase the probability of achieving efficacy while avoiding toxicity.

PMID: 24510446

Return of genomic results to research participants: the floor, the ceiling, and the choices in between.

Authors: Jarvik GP, Amendola LM, Berg JS, Brothers K, Clayton EW, Chung W, Evans BJ, Evans JP, Fullerton SM, Gallego CJ, Garrison NA, Gray SW, Holm IA, Kullo IJ, Lehmann LS, McCarty C, Prows CA, Rehm HL, Sharp RR, Salama J, Sanderson S, Van Driest SL, Williams MS, Wolf SM, Wolf WA, eMERGE Act-ROR Committee and CERC Committee, CSER Act-ROR Working Group, Burke W

Am J Hum Genet. 2014 Jun 5;94(6):818-26

Abstract: As more research studies incorporate next-generation sequencing (including whole-genome or whole-exome sequencing), investigators and institutional review boards face difficult questions regarding which genomic results to return to research participants and how. An American College of Medical Genetics and Genomics 2013 policy paper suggesting that pathogenic mutations in 56 specified genes should be returned in the clinical setting has raised the question of whether comparable recommendations should be considered in research settings. The Clinical Sequencing Exploratory Research (CSER) Consortium and the Electronic Medical Records and Genomics (eMERGE) Network are multisite research programs that aim to develop practical strategies for addressing questions concerning the return of results in genomic research. CSER and eMERGE committees have identified areas of consensus regarding the return of genomic results to research participants. In most circumstances, if results meet an actionability threshold for return and the research participant has consented to return, genomic results, along with referral for appropriate clinical follow-up, should be offered to participants. However, participants have a right to decline the receipt of genomic results, even when doing so might be viewed as a threat to the participants’ health. Research investigators should be prepared to return research results and incidental findings discovered in the course of their research and meeting an actionability threshold, but they have no ethical obligation to actively search for such results. These positions are consistent with the recognition that clinical research is distinct from medical care in both its aims and its guiding moral principles.

PMID: 24814192

Clinical pharmacogenetics implementation: approaches, successes, and challenges.

Authors: Weitzel KW, Elsey AR, Langaee TY, Burkley B, Nessl DR, Obeng AO, Staley BJ, Dong HJ, Allan RW, Liu JF, Cooper-Dehoff RM, Anderson RD, Conlon M, Clare-Salzler MJ, Nelson DR, Johnson JA

Am J Med Genet C Semin Med Genet. 2014 Mar;166C(1):56-67

Abstract: Current challenges exist to widespread clinical implementation of genomic medicine and pharmacogenetics. The University of Florida (UF) Health Personalized Medicine Program (PMP) is a pharmacist-led, multidisciplinary initiative created in 2011 within the UF Clinical Translational Science Institute. Initial efforts focused on pharmacogenetics, with long-term goals to include expansion to disease-risk prediction and disease stratification. Herein we describe the processes for development of the program, the challenges that were encountered and the clinical acceptance by clinicians of the genomic medicine implementation. The initial clinical implementation of the UF PMP began in June 2012 and targeted clopidogrel use and the CYP2C19 genotype in patients undergoing left heart catheterization and percutaneous-coronary intervention (PCI). After 1 year, 1,097 patients undergoing left heart catheterization were genotyped preemptively, and 291 of those underwent subsequent PCI. Genotype results were reported to the medical record for 100% of genotyped patients. Eighty patients who underwent PCI had an actionable genotype, with drug therapy changes implemented in 56 individuals. Average turnaround time from blood draw to genotype result entry in the medical record was 3.5 business days. Seven different third party payors, including Medicare, reimbursed for the test during the first month of billing, with an 85% reimbursement rate for outpatient claims that were submitted in the first month. These data highlight multiple levels of success in clinical implementation of genomic medicine.

PMID: 24616371

Warfarin pharmacogenetics: an illustration of the importance of studies in minority populations.

Authors: Perera MA, Cavallari LH, Johnson JA

Clin Pharmacol Ther. 2014 Mar;95(3):242-4

PMID: 24548987

Physician Attitudes toward Adopting Genome-Guided Prescribing through Clinical Decision Support

Authors: Overby CL, Erwin AL, Abul-Husn NS, Ellis SB, Scott SA, Obeng AO, Kannry JL, Hripcsak G, Bottinger EP, Gottesman O.

J Pers Med. 2014 Feb 27;4(1):35-49.

doi: 10.3390/jpm4010035.

PMID:25562141

Quality of family history collection with use of a patient facing family history assessment tool

Authors: Wu RR, Himmel T, Buchanan A, Powell KP, Hauser E, Ginsburg GS, Henrich VC, Orlando LA

BMC Fam Pract 2014 Feb 13;15:31.

PMID: 2452081

doi: 10.1186/1471-2296-15-31

Providing Patient Education: Impact on Quantity and Quality of Family Health History Collection

Authors: Beadles C, Wu RR, Himmel T, Buchanan A, Powell KP, Hauser E, Henrich VC, Ginsburg GS, Orlando LA

Fam Cancer. 2014 Jun;13(2):325-32

PMID: 24515581

doi: 10.1007/s10689-014-9701-z

The CLIPMERGE PGx Program: clinical implementation of personalized medicine through electronic health records and genomics-pharmacogenomics

Authors: Gottesman O, Scott SA, Ellis SB, Overby CL, Bottinger EP, et al.

Clinical pharmacology and therapeutics. 2013 Aug;94(2):214-7.

Patient and primary care provider experience using a family health history collection, risk stratification, and clinical decision support tool: a type 2 hybrid controlled implementation-effectiveness trial

Authors: Wu Rebekah, Orlando LA, Himmel T, Buchanan A, Powell K, Hauser E, Agbaje A, Henrich VC, and Ginsburg GS

BMC Fam Pract  2013 Aug 6;14:111.

PMID: 23915256

doi: 10.1186/1471-2296-14-111

Collection of family health history for assessment of chronic disease risk in primary care.

Authors: Powell KP, Christianson CA, Hahn SE, Dave G, Evans L, Blanton SH, Hauser E, Agbaje A, Orlando LA, Ginsburg GS, Henrich VC

N C Med J. 2013 Jul-Aug;74(4):279-86

PMID: 24044144

Collection of Family Health History in Primary Care for Chronic Diseases

Authors: Powell KP, Christianson CA, Hahn SE, Dave G, Evans L, Blanton SH, Hauser E, Agbaje A, Orlando LA, Ginsburg GS, Henrich VC

N C Med J. 2013 Jul-Aug;74(4):279-286

PMID: 24044144

Development and validation of a primary care-based family health history and decision support program (MeTree).

Authors: Orlando LA, Buchanan AH, Hahn SE, Christianson CA, Powell KP, Skinner CS, Chesnut B, Blach C, Due B, Ginsburg GS, Henrich VC

N C Med J. 2013 Jul-Aug;74(4):287-96.

Abstract: INTRODUCTION: Family health history is a strong predictor of disease risk. To reduce the morbidity and mortality of many chronic diseases, risk-stratified evidence-based guidelines strongly encourage the collection and synthesis of family health history to guide selection of primary prevention strategies. However, the collection and synthesis of such information is not well integrated into clinical practice. To address barriers to collection and use of family health histories, the Genomedical Connection developed and validated MeTree, a Web-based, patient-facing family health history collection and clinical decision support tool. MeTree is designed for integration into primary care practices as part of the genomic medicine model for primary care. METHODS: We describe the guiding principles, operational characteristics, algorithm development, and coding used to develop MeTree. Validation was performed through stakeholder cognitive interviewing, a genetic counseling pilot program, and clinical practice pilot programs in 2 community-based primary care clinics. RESULTS: Stakeholder feedback resulted in changes to MeTree’s interface and changes to the phrasing of clinical decision support documents. The pilot studies resulted in the identification and correction of coding errors and the reformatting of clinical decision support documents. MeTree’s strengths in comparison with other tools are its seamless integration into clinical practice and its provision of action-oriented recommendations guided by providers’ needs. LIMITATIONS: The tool was validated in a small cohort. CONCLUSION: MeTree can be integrated into primary care practices to help providers collect and synthesize family health history information from patients with the goal of improving adherence to risk-stratified evidence-based guidelines.

PMID: 24044145

The Genomic Medicine Model: An Integrated Approach to Implementation of Family Health History in Primary Care

Authors: Orlando LA, Henrich VC, Hauser E, Wilson C, Ginsburg GS, for The Genomedical Connection

Pers Med. 2013. 10(3):295-306

doi: 10.2217/pme.13.20

Implementing family health history risk stratification in primary care: impact of guideline criteria on populations and resource demand.

Author: Orlando LA, Wu RR, Beadles C, Himmel T, Buchanan AH, Powell KP, Hauser ER, Henrich VC, Ginsburg GS.

Am J Med Genet C Semin Med Genet. 2014 Mar;166C(1):24-33. doi: 10.1002/ajmg.c.31388. Epub 2014 Mar 10.

PMID: 24616329

doi: 10.1002/ajmg.c.31388

Genetic and lifestyle causal beliefs about obesity and associated diseases among ethnically diverse patients: a structured interview study.

Authors: Sanderson SC, Diefenbach MA, Streicher SA, Jabs EW, Smirnoff M, Horowitz CR, Zinberg R, Clesca C, Richardson LD

Public Health Genomics. 2013;16(3):83-93

Abstract: BACKGROUND: New genetic associations with obesity are rapidly being discovered. People’s causal beliefs about obesity may influence their obesity-related behaviors. Little is known about genetic compared to lifestyle causal beliefs regarding obesity, and obesity-related diseases, among minority populations. This study examined genetic and lifestyle causal beliefs about obesity and 3 obesity-related diseases among a low-income, ethnically diverse patient sample. METHODS: Structured interviews were conducted with patients attending an inner-city hospital outpatient clinic. Participants (n=205) were asked how much they agreed that genetics influence the risk of obesity, type 2 diabetes, heart disease, and cancer. Similar questions were asked regarding lifestyle causal beliefs (overeating, eating certain types of food, chemicals in food, not exercising, smoking). In this study, 48% of participants were non-Hispanic Black, 29% Hispanic and 10% non-Hispanic White. RESULTS: Over two-thirds (69%) of participants believed genetics cause obesity ‘some’ or ‘a lot’, compared to 82% for type 2 diabetes, 79% for heart disease and 75% for cancer. Participants who held genetic causal beliefs about obesity held more lifestyle causal beliefs in total than those who did not hold genetic causal beliefs about obesity (4.0 vs. 3.7 lifestyle causal beliefs, respectively, possible range 0-5, p=0.025). There were few associations between causal beliefs and sociodemographic characteristics. CONCLUSIONS: Higher beliefs in genetic causation of obesity and related diseases are not automatically associated with decreased lifestyle beliefs. Future research efforts are needed to determine whether public health messages aimed at reducing obesity and its consequences in racially and ethnically diverse urban communities may benefit from incorporating an acknowledgement of the role of genetics in these conditions.

PMID: 23235350