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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 • • • • • • • • • 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 • • • • • • Jennifer B. McCormick, PhD Richard Sharp, PhD Gail Onderak (CAB Co-Chair) Umbelina Cremer (CAB Co-Chair) Karen Maschke, PhD Barbara Koenig, PhD • Genetics • • • • Erin Winkler, MS, CGC Kiley Johnson, MS, CGC Noralane Lindor, MD Douglas Riegert-Johnson • Patient Recruitment: • • • • • • • • • • • • 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: • • • • • • • • 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