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Integrating Genomics into Clinical Practice

Integrating Genomics into Clinical Practice

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Integrating Genomics into Clinical Practice

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  1. Integrating Genomics into Clinical Practice Janice S. Dorman, PhD University of Pittsburgh School of Nursing

  2. Applications of Genomics to Clinical Practice • Prediction of a healthy person’s risk of disease • Including cancer, cardiovascular disease, diabetes, etc • Analysis of patterns of gene expression for diagnosis • Evaluation of responses to environmental agents and drugs • Pharmacogenomics • Molecular diagnosis of infectious diseases

  3. Challenges Facing Clinical Practice in the Genomics Era • How can we better train the current / next generation of clinicians to practice genomic medicine? • How can increasingly complex genetic knowledge be made readily accessible to all practitioners when they need it?

  4. Challenges Facing Clinical Practice in the Genomics Era • Where should a clinician begin? “Even when an individual’s genome can be displayed on a personal microchip, interpreting that information will depend in large part, on the biological and environmental contexts in which the genome is expressed, and the family milieu is as good a guide as any.”Pyeritz RE. JAMA 278:235. 1997 Why start with a family history?

  5. Family History • Is an important risk factor for chronic diseases that reflects • Inherited genetic susceptibility • Shared environment risk factors (HBP, lipids) • Cultural factors (diet) • Common behaviors (smoking, physical activity) • Prior to offering any genetic testing, a clinician needs to assess the family history of disease • What genes should be tested? • Who should be tested?

  6. Family History of CVD • Cardiovascular disease at an early age at onset is familial • In Utah, 8% of population have 2+ first degree relatives with CHD (Health Family Tree Program) • In these families, risk of CHD (before age 50 years) is increased 3 to 6-fold • FH identifies a group of high risk individuals • Using a simple and inexpensive approach • Permits personalized intervention / prevention • Allows for the development of family-based risk factor modification strategies • Some family members may benefit from a referral for genetic testing

  7. Collecting Family History Information in Clinical Practice • Barriers • Underestimation of value of family history information • Limited knowledge and training in human genetics • National Coalition for Health Professional Education in Genetics (NCHPEG) endorsed core competencies for all health-care professionals in 2000

  8. NCHPEG Core Competencies • Represents minimum knowledge, skills and attitudes necessary for health professionals in all disciplines to provide patient care that involves awareness of genetic issues and concerns • Medicine - Dentistry • Nursing - Psychology • Public Health - Social workers

  9. NCHPEG Core Competencies • Appreciate limitations of his or her genetic expertise • Understand the social and psychological implications of genetic services • Know how and when to make a referral to a genetics professional

  10. Some NCHPEG Recommendations • Knowledge • Importance of family history (minimum of 3 generations) in assessing predisposition to disease • The range of genetic approaches to treatment of disease • Prevention • Pharmacogenomics • Genetic profiling • Resources available to assist clients seeking genetic information • The indications for genetic testing and / or gene-based interventions

  11. Some NCHPEG Recommendations • Skills • Gather genetic FH information, including multiple generation pedigrees • Identify families who would benefit from genetic services • Educate individuals regarding these services, and their risks and benefits • Attitudes • Appreciate the sensitivity of genetic information and the need for privacy and confidentiality • Demonstrate willingness to update genetics knowledge at frequent intervals

  12. Collecting Family History Information in Clinical Practice • Other barriers?

  13. Collecting Family History Information in Clinical Practice • Other barriers • Lack of time • Lack of reimbursement for collecting the information • Concerns about insurance / employment discrimination • Lack of convenient tools / software for data collection

  14. Family History Tools in the Popular Literature

  15. US Surgeon General’s Family History Initiative • National Family History Day,Thanksgiving, 11/25/2004 • US Partners • Office of the Surgeon General • National Human Genome Research Institute (NHGRI) • Centers for Disease Control and Prevention (CDC) • Agency for Healthcare Research and Quality (AHRQ) • Health Resources and Services Administration (HRSA) Developed tool “My Family Health Portrait” • Download free at http://www.hhs.gov/family • Focuses on several diseases (which diseases?)

  16. Diseases Included in ‘My Family Health Portrait’ • Substantial public health burden • Heart disease, stroke, diabetes and cancer (colorectal, breast, ovarian • Clear case definition • High awareness of disease status among relatives • Accurate reporting by family members • Family history is an established risk factor • Effective interventions for primary and secondary prevention

  17. ‘My Family Health Portrait’ Software is called Family Healthware • Age, gender, race / ethnicity • Number of relatives in each category (mother, father, children, etc.) • Personal history of 6 diseases, age at diagnosis • Risk factors (e.g., BMI, diet, exercise, etc.) • Generates report • Pedigree drawing • Listing of family history data entered • Statement about the importance of sharing the history with health care providers

  18. Familial Risk Classification • Based on risk algorithm • Risk level determined mainly by • Number and closeness of affected relatives • Their ages at disease onset • Modeled after ‘Health Family Tree Program’ Family History Score, University of Utah • Compare observed family data to expected based on age, gender and race-specific incidence data

  19. Familial Risk Classification Standard Public Health Prevention Recommendations Average Personalized Prevention Recommendations Family Healthware Above Average Personalized Prevention Recommendations and Referral for Genetic Evaluation Much Above Average

  20. Familial Risk Classification • Simple, easily applied, inexpensive • Use to guide and inform prevention activities • Resource manual for health care professionals is under development • Will be organized into disease-specific chapters that include recommended prevention interventions for each level of risk • How valid is family history information?

  21. Validity of FH Information • Reporting bias • Age, gender, ethnicity of proband • Number of affected relatives • Family dynamics • Access to health care • Medical knowledge • Risk perception • Proband recall • Age, gender, ethnicity of proband • Familial relationship • Brother, sister, mother, father, etc. • Method of data collection • Verification of information recalled

  22. Evaluation Framework

  23. Evaluation Framework • Analytical validity • How well does the tool identify affected relatives? • Clinical validity • How well does the tool predict disease? • Clinical utility • How useful is the FH tool prevent disease? • ELSI implications • What are the negative aspects of using the FH tool to identify high risk individuals / families?

  24. Understudied: Clinical Utility • Will identification of high risk families lead to behavior change? • Will FH assessment permit targeted intervention? • Is FH useful for changing behavior? • Is the approach cost-effective?

  25. Understudied: ELSI Implications • Knowledge of family history may bring unexpected negative effects • Is there stigma associated with being above average risk? • Is there any psychological impact of risk labeling? • Is there discrimination or adverse effects on personal and family life? • Do family members have a duty to inform each other of disease (genetic) risk factors?

  26. Identification and Prevention for High Risk CVD Families • Targeted lifestyle changes such as diet, exercise and stopping smoking • Screening at earlier ages, more frequently and with more intensive methods than might be used of average risk individuals • Use of chemoprevention approaches • Aspirin • Referral to a specialist for assessment of genetic risk factors

  27. Lipoprotein Genes Known to Contribute to CAD Risk

  28. Genomic Profiling • After reviewing Mr. C’s (age 50) FH, his physician notices that this father had a heart attack at age 59 years • His physical exam (including ECG and treadmill test) were fine • His cholesterol was ‘a little high’ • Recommended reduced-fat diet and lipid lowering drug • Mr. C has heard about a new DNA test that provided an individual genetic profile and personalized recommendation for nutritional supplements to prevent CAD • Should he get the test (offered through several web sites)?

  29. Genomic Profiling • Direct to physician / consumer marketing • Genovations - http://www.genovations.com • Gene Link: Genetic Biosciences for Improving the Quality of Life - http://www.bankdna.com • Sciona – http://www.sciona.com • Combination of gene variants screed is considered proprietary and are usually not disclosed on their websites or advertisements • CardioGenomic Profile • DetoxiGeonmic Profile • ImmunoGenomic Profile • Obesity Susceptibility Profile • Osteopenia Susceptibility Profile • Oxidative Stress for Skin Health and Aging Profile • Tissue Repair Screen and Alcohol Metabolism Screen