Genetic Susceptibility Testing for Adult-Onset Disorders

1. Genetic Susceptibility Testing for Adult-Onset Disorders Supported by grants from: National Human Genome Research Institute (HG/AG-02213 REVEAL Study) National Institute on Aging (AG-025914; AG-13846, BU Alzheimer’s Disease Center) U-M Comprehensive Cancer Center Scott Roberts, PhD Department of Health Behavior & Health Education University of Michigan School of Public Health

2. Overview • Genetic risk assessment for common, complex diseases • Alzheimer’s disease and APOE as paradigm • Clinical trials data: Risk Evaluation & Education for AD • Current and future research directions • Focus on cancer genetics

3. Examples of Adult-Onset, Complex Genetic Conditions #2 • Cancer • Neurodegenerative disorders • Heart disease • Psychiatric disorders • Diabetes • Osteoporosis • Stroke Top 10 causes of mortality in the U.S., 2001 #8 #1 #6 #3

4. Genetic Risk Assessment • Genetic risk factors rapidly being identified • Implications for assessment and treatment • Challenges of translating genetic discoveries into clinical practice • Risk communication • Psychological impact • Genetic discrimination

5. “Human genetics inhabits a volatile space at the intersection of medicine, biology, corporate profits, law, government funding of science, state health programs, private insurance companies, genetic counseling services…and popular culture.” - Alice Wexler, in Mapping Fate

6. Alzheimer’s Disease & Public Health • AD is the most common cause of dementia among people age 65 and older. • An estimated 4.5 million in the US currently have AD. • Annual costs estimated at $100 billion • High caregiver burden (“death by a thousand subtractions”) • By 2050, 13.2 million older Americans are expected to have AD if current demographic trends continue and no preventive treatments become available. Source: NIA’s “Alzheimer's Disease: Unraveling the Mystery.”

7. Forecast of AD Prevalence in the U.S. 2000 2030 2050 4.5 Million (est) 7.7 Million (est) 13.2 Million (est) 65-74 Years 75-84 Years 85+ Years Source: Hebert LE, et al. Arch Neurol. 2003;60:1119-1122.

8. Known risk factors: Aging Family history/genetics Down syndrome Possible risk factors: Female sex African American ethnicity Head trauma Depression / distress Vascular disease Diabetes Risk / Protective Factors for Alzheimer’s Disease Possible protective factors: • Higher level of education • Anti-oxidants (Vitamins C, E) • NSAIDS • Moderate alcohol use • Statin medications • Low fat diet • e.g., fish, blueberries • Physical exercise • Mental exercise

9. Established Gene Markers for AD Deterministic Mutations: Amyloid Precursor Protein (APP) Presenilin-1 (PS-1) Presenilin-2 (PS-2) Susceptibility Polymorphism: Apolipoprotein E (APOE) Lendon CL, et al. JAMA 1997;277(10):825-831

10. Apoliprotein E (APOE) & AD • Plasma protein involved in lipid transport • Initial AD findings at Duke in 1993 • 3 common alleles: e2, e3, e4 • e3 is most common variant • e2 may be a protective factor against AD • e4 is a “dose-dependent” risk factor (estimates of up to 8-fold risk depending on genotype) • Pleiotropic effects of APOE • e4 as risk for CVD; e2 as risk for HLP III

11. One allele is inherited from each parent

12. APOE Genotypes in the General Population

13. APOE Genotyping for Risk Assessment Why should we NOT do risk assessment for Alzheimer’s disease (at least with APOE)? • APOE genotype is not a highly accurate marker • No progression/prevention intervention available • Discrimination or psychological harm may occur • Five negative consensus recommendations

14. APOE Genotyping for Risk Assessment Why SHOULD we do risk assessment for Alzheimer’s disease (using APOE)? • Define at-risk populations for prevention trials • Identify responsive subgroups for treatment • Respond to clinical requests (or DTC will) • Develop new “clinical technologies” for • susceptibility markers in common disorders

15. “I don’t skate where the puck is. I skate to where it’s going.” - Hockey superstar Wayne Gretzky

16. Risk Evaluation & Education for AD (The REVEAL Study) An Intervention Trial where Information is the Intervention: What is the impact of genetic risk assessment for adult children of people with AD?

17. Importance of Acronyms • Stanbrook et al. 2006 NEJM article on acronym-named randomized trials in medicine • Acronym-named studies had higher citation rates than those without acronyms (relative rate = 2.43, p < .001)

18. Key Questions Who wants to know? What happens to them? What do they do?

19. Study Protocol Enrollment Education Blood Draw and Randomization Risk Disclosure and Counseling using family hx, gender, APOE Risk Disclosure and Counseling using family hx, gender alone Follow up (6 weeks, 6 months, 12 months)

20. Study Education Session • Conducted by trained genetic counselor • Study protocol reviewed • Education on AD, genetics, current treatments • Follow up with cognitive, psychiatric screening

21. Risk Communication • GCs provided lifetime risk estimates (range: 13-57%) based on large-scale genetic epidemiology studies of families with AD • APOE test results disclosed to Intervention Arm participants • Risk information presented in oral, written, and visual formats

23. Baseline Demographics by Randomization Group Demographic Characteristic Control (N = 51) Intervention (N = 111) 52.0 (10.0); 30-76 55.3 (9.0); 37-78 Mean Age, yrs. (SD); Range Sex, % female 69.4% 78.4% 90.2% Race/ethnicity, % White 95.5% 16.7 (2.2); 12-22 Mean yrs of education (SD); Range 16.8 (2.5); 10-22 Marital status, % married 66.7% 60.8% No. of affected relatives, % 1 2+ 40.5% 59.5% 45.1% 54.9% Median income bracket $70K-$99,999 $70K-$99,999

24. Genotypes of Study Participants Study group# of cases APOE 4+ (2/4, 3/4 or 4/4) 53 APOE 4- (2/3 or 3/3)58 Controls (no genotype disclosed) 51

25. Who Wants Genetic Risk Assessment? • 24% of systematically contacted research registry participants enrolled in the RCT • 80% of Education Session attendees subsequently proceeded to randomization • Age (younger), education (higher), and gender (female) predicted RCT enrollment Roberts et al., Genetics in Medicine, 2004

26. Test Uptake Across Diseases Roberts et al., Genetics in Medicine, 2004

27. Reasons Associated with Test Uptake Women strongly endorsed more reasons for seeking testing than men, p = .01 Roberts et al., ADAD, 2003

28. Psychological Impact • Depression • Anxiety • Test-specific distress • Self-reported impact • Perception of AD risk

29. Mean Depression Scores Clinically significant depression

30. Mean Anxiety Scale Scores Clinically significant anxiety

31. Mean Impact of Event Scale Scores Clinically significant impact

32. Subjective Impact of Testing 6 Weeks Post-Disclosure • Most participants rate impact as positive • 67% positive vs. 17% negative • Participants more likely to report lower (vs. higher) anxiety about AD as result of testing • 43% lower vs. 11% higher • Test result influences subjective ratings • APOE e4- group particularly likely to report positive impact (85%), lower anxiety (73%)

33. Understanding of Risk Information • Accuracy of recall • APOE genotype more salient than lifetime risk estimates • 75% correctly recall e4 status at 6 weeks (vs. 59% within 5 pts. of LTR) • Perception of risk as a result of test information • APOE e4- status lowers perceived risk (but not vice versa) • High baseline risk perceptions may account for results Marteau, Roberts et al., Risk Analysis, 2005

34. Impact of Genotype Disclosure • Subgroup analysis of Control Arm women vs. Intervention Arm women with e3/e3 genotype • Both groups received 29% lifetime risk estimates, but Intervention Arm participants also knew they were e4- • Did perceptions of risk differ b/w the groups?

35. Family History and ε3/ε3 Genotype Impact of Genotype Disclosure:When 29% ≠ 29% 80% Family History Only 60% % Endorsing Response at 6 weeks After Disclosure 40% 20% 0% I believe I will develop AD My personal sense of risk is lower My anxiety about developing AD is lower LaRusse, Roberts et al., Genetics in Medicine, 2005

36. Changes in Health Behaviors e4+ group > e4- group, p < .05 Most common changes: Adding vitamins (48%) Changing diet (13%) Exercise (6%)

37. Behavioral Impact: Insurance

38. Insurance Changes Reported at 12 Month Follow-Up * Zick, Mathews, Roberts et al., Health Affairs, 2005

39. Genetics & LTC Insurance • Use of genetic info in underwriting prohibited in only two states (Montana, New Mexico) • But allowed with actuarial justification • Only four states (CO, MA, OR, VT) prohibit required genetic tests for applicants • But allow use of existing test results

40. REVEAL II Aims • Assess a more clinically feasible “condensed” protocol • Explore provider differences (GC vs. MD) • Expand focus on older adults, African Americans • Both groups at high risk for AD • Examine process of genetic counseling and education in this context • Use of RIAS coding method

41. REVEAL II Sample Characteristics • N = 280 first-degree relatives • Mean age = 58 years • 70% female • 21% African American • Relatively high SES (mean education = 16 years, median income = $70K-$99,999)

42. Extended vs. Condensed Protocols Extended: Condensed: In-person education Education brochure session (30 – 45 min) sent by mail Individual counseling Q & A only Blood draw Blood draw (45-60 min) (30 – 45 min) Risk assessment Risk assessment Risk assessment with APOE with APOE with APOE disclosure by GC disclosure by GC disclosure by MD

44. Extended vs. Condensed • Comparable outcomes across multiple domains • Psychological impact (except slightly higher distress at 6 weeks among CP participants) • Risk recall • Health behaviors • Comparable outcomes for GC vs. MD disclosure • GCs rated slightly higher on interpersonal communication skills

45. Age Group Differences • No differences in psychological impact • Notable differences in risk recall • Older group less likely to recall lifetime risk, APOE genotype, and e4 status • Younger relatives significantly more likely to: • Plan on making a change to their long-term care insurance (p < 0.01) • Plan on making health & wellness changes

46. Race Group Differences • Baseline risk perception higher among Whites • Whites more likely to overrate their own risk • Comparable psychological impact • Despite AAs receiving higher risk estimates • No significant differences in health/wellness changes • Need to examine mediating/moderating variables related to stress & coping

48. Examining Process & Outcome in Genetic Counseling • How is counseling process related to key outcomes following risk disclosure? • How is counseling process affected by patient & provider characteristics? • R03 to analyze risk disclosure session audiotapes in REVEAL II (N = 264)

49. Roter Interaction Analysis System • World’s most widely used system for assessment of medical interactions • Developed by Dr. Debra Roter at Johns Hopkins • Recently adapted for study of genetic counseling • Can be used to relate process variables to key outcomes

50. Patient and provider variables Question asking Open vs. Closed questions Biomedical focus Psychosocial focus Provider variables Provider verbal dominance Patient education Patient counseling Patient-centered counseling style Patient variables Patient verbal activity Patient psychosocial disclosure Affective impression of the provider Patient and provider affective tone Positive affect Negative affect Session length RIAS Variables of Interest