Supported by grants from: National Human Genome Research Institute (ELSI) HG/AG (The REVEAL Study); National Institute on Aging AG (The MIRAGE Study) and AG (BU Alzheimer’s Disease Center) Genetic Research in Dementia: Risk Evaluation & Education for Alzheimer’s Disease Scott Roberts, PhD 1 Robert C. Green, MD, MPH 1,2 Departments of Neurology 1 and Medicine 2 (Genetics Program) Alzheimer’s Disease Center Boston University School of Medicine

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 By 2050, 13.2 million older Americans are expected to have AD if current demographic trends continue and no preventive treatments become available. Alzheimer’s Disease & Public Health Source: NIA’s “Alzheimer's Disease: Unraveling the Mystery.” High caregiver burden (“death by a thousand subtractions”)

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):

APOE Genotypes in the General Population

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 Five negative consensus recommendations Discrimination or psychological harm may occur

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

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

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?

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

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

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

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

Test Uptake Across Diseases DisorderUsual age of onset Type of testing Effective prevention/ treatment options? Estimated uptake rate Familial adenomatous polyposis AdulthoodPredictiveYes85% Breast-ovarian cancerAdulthoodSusceptibilityYes43% Hereditary nonpolyposis colorectal cancer AdulthoodSusceptibilityYes30% Alzheimer’s diseaseLate adulthoodSusceptibilityNo24% Cystic fibrosisChildhoodCarrier screening No4-23% Huntington’s diseaseAdulthoodPredictiveNo10% Roberts et al., Genetics in Medicine, 2004

Reasons Associated with Test Uptake Strongly endorsed reason for seeking testing as predictor of study enrollment Odds ratio To prepare family for AD 3.33 To arrange personal affairs 2.62 To arrange long-term care 2.52 To learn information for family planning 2.25 Women strongly endorsed more reasons for seeking testing than men, p =.01 Roberts et al., ADAD, 2003

Mean Depression Scores Clinically significant depression

Mean Anxiety Scale Scores Clinically significant anxiety

Mean Impact of Event Scale Scores Clinically significant impact

Changes in Health Behaviors  4+ group >  4- group, p <.05 Most common changes: Adding vitamins (48%) Changing diet (13%) Exercise (6%)  4+  4- Control Respondents endorsing change to prevent AD 53%24%31%

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

Conclusions Genetic risk assessment will become increasingly important part of medical care Alzheimer’s disease and APOE represent an instructive paradigm Need to develop empirically validated methods of disclosing genetic risk information

Acknowledgments/Investigators Boston University Robert C. Green, MD, MPH Tamsen Brown, MS, CGC Dapo Akinleye, MPH Lindsay A. Farrer, PhD L. Adrienne Cupples, PhD George Annas, JD, MPH Weill Medical College/Cornell Univ. Norman R. Relkin, MD, PhD Lisa Ravdin, PhD Susan LaRusse, MS, CGC Beth Chisholm, MS Elana Cox, MS, CGC Howard University Charmaine Royal, PhD Thomas Obesisan, MD Grace-Ann Fasaye, ScM Case University Peter Whitehouse, MD, PhD Eric Juengst, PhD Melissa J. Barber, ScM Stephen Post, PhD Indiana University Kimberly A. Quaid, PhD University of British Columbia A. Dessa Sadovnick, PhD King’s College, London Theresa Marteau, PhD Nat’l Human Genome Research Inst. Barbara Biesecker, MS Elizabeth Thomson, MS, RN Duke University Robert Cook-Deegan, MD