Transcript Predictive Testing for Alzheimer’s Disease

Genetic Research in Dementia:
Risk Evaluation & Education
for Alzheimer’s Disease
Scott Roberts, PhD1
Robert C. Green, MD, MPH1,2
Departments of Neurology1 and Medicine2 (Genetics Program)
Alzheimer’s Disease Center
Boston University School of Medicine
Supported by grants from:
National Human Genome Research Institute (ELSI) HG/AG-02213 (The REVEAL Study);
National Institute on Aging AG-09029 (The MIRAGE Study)
and AG-13846 (BU Alzheimer’s Disease Center)
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.”
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
APOE Genotypes in the General Population
3/3, 67%
2/4, 3%
4/4, 2%
2/3, 8%
3/4, 20%
2/2, 1%
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
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
• Respond to clinical requests
• Develop new “clinical technologies” for
susceptibility markers in common disorders
“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?
Key Questions
Who wants to know?
What happens to them?
What do they do?
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)
Baseline Demographics
by Randomization Group
Demographic
Characteristic
Control
(N = 51)
Intervention
(N = 111)
Mean Age, yrs. (SD);
Range
Sex, % female
Race/ethnicity, % White
55.3 (9.0);
37-78
52.0 (10.0);
30-76
78.4%
90.2%
69.4%
95.5%
Mean yrs of education (SD);
Range
Marital status, % married
16.8 (2.5);
10-22
16.7 (2.2);
12-22
60.8%
66.7%
45.1%
54.9%
$70K-$99,999
40.5%
59.5%
No. of affected relatives, %
1
2+
Median income bracket
$70K-$99,999
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
Disorder
Usual age of
onset
Type of
testing
Effective prevention/
treatment options?
Estimated
uptake rate
Familial
adenomatous
polyposis
Adulthood
Predictive
Yes
85%
Breast-ovarian cancer
Adulthood
Susceptibility
Yes
43%
Hereditary
nonpolyposis
colorectal cancer
Adulthood
Susceptibility
Yes
30%
Late adulthood
Susceptibility
No
24%
Cystic fibrosis
Childhood
Carrier
screening
No
4-23%
Huntington’s disease
Adulthood
Predictive
No
10%
Alzheimer’s disease
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
Controls
All intervention
e4+
e4-
27
Mean CES-D Scores
24
21
18
Clinically significant depression
15
12
9
6
3
0
Baseline
6 weeks
6 months
1 year
Mean Anxiety Scale Scores
Controls
All intervention
e4+
e4-
27
24
Mean BAI Scores
21
18
Clinically significant anxiety
15
12
9
6
3
0
Baseline
6 weeks
6 months
1 year
Mean Impact of Event Scale Scores
Mean IES Scores
Controls
All intervention
26
24
22
20
18
16
14
12
10
8
6
4
2
0
e4+
e4-
Clinically significant impact
6 weeks
6 months
1 year
Changes in Health Behaviors
Respondents
endorsing
change to
prevent AD
e4+
e4-
Control
53%
24%
31%
e4+ group > e4- group, p < .05
Most common changes:
Adding vitamins (48%)
Changing diet (13%)
Exercise (6%)
Insurance Changes
Reported at 12 Month Follow-Up
Control
E4 Negative
E4 Positive
30%
25%
*
20%
15%
10%
5%
0%
Health
Life
Disability
LTC
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