Hot Topics in Genomics Research

1. Ellen Wright Clayton, MD, JD Craig-Weaver Professor of Pediatrics Director, Center for Biomedical Ethics and Society Vanderbilt University Hot Topics in Genomics Research

2. Topics for today • Data Sharing • Identifiability • Return of research results

3. Data sharing • Why is this an issue? • Sharing promotes research BUT • Desire to reap fruit of one’s labors • Competition • Difficult to do • Differences in consent, IRBs, communities, data formats • Research participants may not want it • Concerns about particular recipients – Pharma, government • Concerns about risks

4. GWAS data sharing policy • Applications and proposals that include GWAS, regardless of the requested costs, are expected to include as part of the Research Plan either a plan for submission of GWAS data to the NIH-designated GWAS data repository, or an appropriate explanation for why submission to the repository will not be possible. • NOT-OD-08-013 • Threshold otherwise $500K

5. Written certification (1) • The data submission is consistent with all applicable laws and regulations, as well as institutional policies ; . . . • The identities of research participants will not be disclosed to the NIH GWAS data repository; and • An IRB and/or Privacy Board, as applicable, reviewed and verified that: . . . • The investigator’s plan for de-identifying datasets is consistent with the standards outlined above; . . . • NOT-OD-07-088

6. De-identification standards for dbGaP • the identities of data subjects cannot be readily ascertained or otherwise associated with the data by the repository staff or secondary data users (45 C.F.R. 46.102(f)); • the 18 identifiers enumerated at section 45 C.F.R. 164.514(b)(2) (the HIPAA Privacy Rule) are removed; and • the submitting institution has no actual knowledge that the remaining information could be used alone or in combination with other information to identify the subject of the data. Keys to codes will be held by submitting institutions. • NOT-OD-07-088

7. What are the re-identification risks? • External • Prosecutor – try to identify specific person • Journalist – try to identify any person • Marketer – try to identify many people with errors acceptable • Internal

8. What are the re-identification risks? • They all depend at present on pre-existing identified data • They depend on level of data security • The level of risk can be quantified • But should we look at the risk relative to other levels of privacy?

9. Written certification (2) • The appropriate research uses of the data and the uses that are specifically excluded by the informed consent documents are delineated; • An IRB and/or Privacy Board, as applicable, reviewed and verified that: . . .The submission of data to the NIH GWAS data repository and subsequent sharing for research purposes are consistent with the informed consent of study participants from whom the data were obtained; • It has considered the risks to individuals, their families, and groups or populations associated with data submitted to the NIH GWAS data repository; and • The genotype and phenotype data to be submitted were collected in a manner consistent with 45 C.F.R. Part 46. • NOT-OD-07-088

10. Data use certification by user and institution • Use the data only for the approved research; Protect data confidentiality; Follow appropriate data security protections; Follow all applicable laws, regulations and local institutional policies and procedures for handling GWAS data; Not attempt to identify individual participants from whom data within a dataset were obtained; Not sell any of the data elements from datasets obtained from the NIH GWAS data repository;Not share with individuals other than those listed in the request any of the data elements from datasets obtained from the NIH GWAS data repository; Agree to the listing of a summary of approved research uses within the NIH GWAS data repository along with his or her name and organizational affiliation; Agree to report, in real time, violations of the GWAS policy to the appropriate DAC;Acknowledge the GWAS policy with regard to publication and intellectual property; and Provide annual progress reports on research using the GWAS dataset.

11. Returning results of research What are we talking about returning? • Nothing at all • “Incidental findings” • Quality control – eMERGE experience • Pleiotropy • Is there a duty to look? • Individual research results

12. What people say about return of results • Clinicians sometimes feel compelled to disclose • Patients/research participants often say they want/expect results • May be particularly true when the research is being conducted by their own health care provider group • Surveys and focus groups by Genetics and Public Policy Center • The next two slides were used in a talk by David Kaufman

13. Relative importance of study benefits “In deciding whether or not to participate, how important would the following be to you?” Health information 94 Travel expenses 81 Health care benefits 79 Monetary compensation 75 Internet connection 64 Gas card or gift card 61 Gift item 31

14. “I would want to know my individual research results about:” Strongly Disagree Disagree Agree Strongly Agree Agree Disagree “conditions that can be prevented or treated.” 4% 96% “health risks, even if there is nothing I could do about them.” 9% 91%

15. What some people say • Not all want results • Marshfield – people chose to have their information included in GWAS because they would not get results • Vanderbilt – 1/65 respondents wanted results • Well documented differences between what information people say they want and what they choose to get

16. Returning results of research • Is retaining way to return results required? • What criteria? • Clinically actionable • Reproductive utility • Personal meaning • For what time? • Who should decide if criteria are met? • Who should return results? • Initial investigator? • Biobank? • Downstream investigator?

17. Some residual concerns • Need for compliance with CLIA • Errors • Pleiotropy • Complexity • We cannot assume that returning results will improve health • Risk of increasing health care costs

18. Some concluding thoughts • We are losing sight of the big picture • Lots of information about us is available • Long history of epidemiology research using data • What is special (or not) about genomics • The discourses about issues in genomics sometimes conflict – privacy v. return of results • Issues with blurring research and the clinic • “Therapeutic misconception” • Not all information obtained in clinical care is or should be acted on