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CENTER FOR
INDIVIDUALIZED
MEDICINE
Genetic Knowledge and Return of Results
Preferences in the Mayo Clinic Biobank
Janet E. Olson, Ph.D.
©2012 MFMER | slide-1
The Mayo Clinic Biobank
A Mayo Clinic initiative to enroll 50,000 Mayo
Clinic patients regardless of their health history
(no specific disease) by end of 2016
Launched 4/1/2009
Eligible:
Mayo patients
18 years+
US resident
Center for INDIVIDUALIZED MEDICINE
3039880-2
©2012 MFMER | slide-2
Mayo Clinic Biobank
Invited via mail prior to medical appointment
Over 40,000 consented to date
Blood
QN data
Over 110 projects approved to date
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-3
Excerpt from Biobank Consent form:
“9. What if researchers discover something about my
health?
 During individual studies, researchers could find out
important information about your health. They might
discover something about your health right now, or
about your risk of getting sick in the future.
Researchers will not discover something about every
donor, so you are not guaranteed to receive results.
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-4
Excerpt from Biobank Consent form:
 Since decisions about health and disease are very
personal, no one can predict which results donors will
want in the future. One of the important jobs that BTOG
has is to decide which research results, if any, will be
returned to Biobank donors. They will make this
decision for each individual study after consulting with
the appropriate researchers, doctors, and the
Community Advisory Board. Names will not be
mentioned during this process.”
 Outcome of Biobank Access Committee on February
16, 2011:
 Genetic test results would be returned if warranted
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-5
Genetic Knowledge Survey
©2012 MFMER | slide-6
Questions
What is the level of genetic knowledge in our
population?
As we think about returning results in the future
what are the interests of our population in
receiving results?
What do they think about the use of new Whole
Genome Sequencing technology?
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-7
Survey Study Design
Stratified random sample of 1200 Biobank
participants stratified by
Age Group (18-30, 30’s, 40’s, 50’s, 60’s 70+)
Education (< High School, > High School)
Sex
Mailed packet (letter, QN) to home address
Two mailings, 1 month apart
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-8
Responders vs. Non-Responders
Category
Responders
N=685 (57%)
Non-Responders
N=515
Age (mean, years)
55
46
Sex, Female (%)
52
47
Education (% >
High school)
56
45
Race (% white)
96
88
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-9
Table 1 – Description of Participants
Category
Completers
N=685
Age Categories
18-30
31-40
41-50
51-60
61-70
70+
68 (10%)
94 (14%)
101 (15%)
136 (20%)
149 (22%)
137 (20%)
HS or Less
Some College
College degree +
304 (44%)
146 (21%)
235 (34%)
Education
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-10
Sections of the Survey
General Knowledge of Genetics
Interest in Return of Research Results
Case Scenarios – Return of Research Results
Cystic Fibrosis
HBOC
Whole Genome Sequencing
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-11
When people talk about
“Individualized” medicine or
If I have a genetic
variant
“personalized”
medicine
theythat
linked to
a certain
areisusually
referring
to disease,
using
then
it
is
certain
that
I will
98% The
If I long-term
were told Igoal
had of
angenetic 95% information from a person’s
89%
someday
that to
disease.
research
studies
is to
increased
genetic
risk for
a
genome
(theirget
DNA)
help
eventually
help improve
health
disease,
it would
mean that
I
guide80%
that person’s health
through
betterof
have a care
greater
possibility
care.
76%
70% I
preventions
or treatments..
getting
that disease
because
have one or more genetic
variants that are linked to that
55%
True
disease.
Overall Genetic Knowledge
100%
90%
80%
70%
60%
50%
False
40%
DK
30%
20%
10%
0%
Gen. Res
Goal
Genes Def. Variants Def. Genomics Increased risk Certainty of Indiv. Med.
Def.
disease
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-12
Testing my genes can…
Show if I have a genetic risk for one or more
diseases or conditions
87% correctly identified this as true
Show if my genetic makeup plays a role in a
disease or condition that I already have
82% correctly identified this as true
Give me a clean bill of health
81% correctly identified this as false
Give me information about me and my relatives
75% correctly identified this as true
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-13
Return of Results Preferences
©2012 MFMER | slide-14
It is important to me to find out
70 other genetic variants
if I have
that might be important to my
60
health.
It is important to me to find out if I
have other genetic variants that
might be important to my
children’s health.
63
48
50
42
40
Answers to Q1 and Q2 are
strongly associated.
(Concordance of 92%)
%
30
29
20
10
7
5
3
3
0
My Health
Strongly Disagree
Children's Health
Somewhat disagree
Somewhat Agree
Strongly Agree
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-15
I60
would be concerned
about any of my
genetic information
50 into my medical
going
record.
I would be concerned if
any of my genetic
information was available
to health and life
insurance companies.
55
40
33
People who were 29
concerned
30
tended to be in poor health.
24
Q4 had no association with
26
health status
20
14
8
10
11
0
Medical Record
Strongly Disagree
Insurance Companies
Somewhat disagree
Somewhat Agree
Strongly Agree
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-16
I would want to know about
my 80
genetic information even if
I or my doctor could not do
70
anything
to diagnose, treat, or
prevent a disease or disorder.
60
50
40
40
When I die, I would
want my family
members to have
access to my genetic
information.
71
44
30
24
20
11
10
6
2
3
0
Not actionable
Strongly Disagree
Family Access
Somewhat disagree
Somewhat Agree
Strongly Agree
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-17
Case Scenarios
Recessive - Cystic Fibrosis
Pulmonary disease with early onset
Expected younger subjects to be most interested
Dominant – Hereditary Breast & Ovarian
Cancer (HBOC)
Increased risk for cancers of the breast, ovaries,
prostate, pancreas with adult onset
Expected most interest among older women
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-18
Scenarios: Cystic Fibrosis
100
90
80
70
60
%
50
40
30
20
10
0
18-30
31-40
41-50
51-60
61-70
70+
CF-Yes
Age
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-19
Scenarios: Cystic Fibrosis – by sex
100
90
80
70
60
%
50
40
30
20
10
0
18-30
31-40
41-50
CF-Yes
51-60
Females
61-70
70+
Males
Age
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-20
Scenarios: HBOC
100
90
80
70
60
%
50
40
30
20
10
0
18-30
31-40
41-50
HBOC-Yes
51-60
Females
61-70
70+
Males
Age
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-21
Scenarios: HBOC – by age
100
90
80
70
60
%
50
40
30
20
10
0
18-30
31-40
HBOC-Yes
41-50
51-60
%Yes Females
61-70
70+
% Yes Males
Age
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-22
Preferred Method of Receiving Results
1. In person – Genetic Counselor
Ranked #1 by 61% (CF); 64% (HBOC)
2. On the phone – genetic counselor
Ranked #1 by 20% (CF); 18% (HBOC)
3. E-visit
Ranked #1 by 15% (CF); 12% (HBOC)
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-23
Whole Genome Sequencing
Obtain genetic information about all sequences
in their genomic materials
Potential for obtaining risk information on hundreds
of different diseases
Potential for large-scale WGS within the Mayo
Clinic Biobank
Large scale return of results
Discussed at time of survey development
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-24
70
60
I approve of the Mayo Clinic
Biobank applying this new
technology on stored
participant DNA samples.
63%
50
40
30%
%
30
20
10
2%
4%
2%
0
Strongly disagree
Somewhat disagree
Somewhat agree
Strongly agree
Missing
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-25
40
35
30
I would want the Mayo Clinic
Biobank to re-contact me so I
can give my permission for this
particular project before they
apply this new technology on
my stored DNA sample.
24
25
20
36
20
18
%
15
10
4
5
0
Strongly disagree
Somewhat disagree
Somewhat agree
Strongly agree
Missing
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-26
80
70
60
If the Mayo Clinic Biobank
asked for my permission to
allow my stored DNA sample
to be used in a whole genome
sequencing project, I would
approve the request.
71
50
40
%
30
23
20
10
1
4
2
0
Strongly disagree
Somewhat disagree
Somewhat agree
Strongly agree
Missing
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-27
Conclusions
Generally high level of genetic knowledge in
our population
Interest in receiving results is high for
Recessive traits, regardless of age
Dominant traits
Approve of WGS technology and its use on
samples
Some sort of re-contact desired
Making plans for re-contact via bi-annual newsletter
Center for INDIVIDUALIZED MEDICINE
©2012 MFMER | slide-28
Acknowledgements
• Dave Schowalter, MD, PhD
• Administration
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Stephen N. Thibodeau, PhD
James R. Cerhan, MD, PhD
Alex Parker, PhD
Michael Van Norstrand, M.D., Ph.D.
Lawrence J. Mandarino, Ph.D.
Chris Schad
Scott Beck
Jolene Summer Bolster
Malinda Woodward
• Bioethics
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Jennifer B. McCormick, PhD
Richard Sharp, PhD
Gail Onderak (CAB Co-Chair)
Umbelina Cremer (CAB Co-Chair)
Karen Maschke, PhD
Barbara Koenig, PhD
• Genetics
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•
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Erin Winkler, MS, CGC
Kiley Johnson, MS, CGC
Noralane Lindor, MD
Douglas Riegert-Johnson
• Patient Recruitment:
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Janet Olson, PhD
Jody Morrisette
Michelle Arnold
Bernardo Cerda Gonzalez
Lindsay Fogel
Lisa Hines
Laura Kveene
Kelly Lyke (Student Project)
Brenda Maringer
JoAnn Peterson
Kristen Quinn
Deb Schultz
The Mayo Clinic Biobank is sponsored by the Mayo
Clinic Center for Individualized Medicine
©2012 MFMER | slide-29
• IT/Statistics Group:
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•
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•
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Euijung Ryu, PhD
Kari Anderson
Josh Bublitz
Zach Frederickson
Mathew Hathcock
Ruchi Sharma
Aaron Kurtzhals
Brandon Dallman
• BAP Lab:
•
•
•
•
•
Miné Cicek, PhD
Ed Highsmith, PhD
Melody Powers
Josh Gorman
Karla Kopp
• Other Affiliated Staff
• Lisa Boardman, MD
• Tim Beebe, PhD
• Suzette Bielinski, PhD
• Cathy Devine
• Mark Liebow, MD
• Paul Takahashi, MD
• Myra Wick, MD
Center for INDIVIDUALIZED MEDICINE