Public Perspectives on Investigative Genetic Genealogy: Findings from a National Focus Group Study.

BACKGROUND: Investigative genetic genealogy (IGG) is a technique that involves uploading genotypes developed from perpetrator DNA left at a crime scene, or DNA from unidentified remains, to public genetic genealogy databases to identify genetic relatives and, through the creation of a family tree, the individual who was the source of the DNA. As policymakers demonstrate interest in regulating IGG, it is important to understand public perspectives on IGG to determine whether proposed policies are aligned with public attitudes. METHODS: We conducted eight focus groups with members of the public (N = 72), sampled from four geographically diverse US regions, to explore general attitudes and perspectives regarding aspects of IGG practices, applications, and policies. Five major topics were explored in each focus group: when IGG should be used; who should perform IGG; how to approach consent for genetic database users; what systems of oversight should govern IGG practitioners; and whether to notify database users if their data are involved in law enforcement (LE) matching. RESULTS: Participants were supportive of IGG in most scenarios, especially for cold and violent cases. The favorable attitudes toward IGG were, however, tempered by distrust of law enforcement among some participants. All participants agreed that databases must inform users if IGG is allowed, but they did not agree on how individual database users should be allowed to opt out or whether to notify them if their data are involved in specific investigations. All participants agreed that IGG should be subject to some prescriptive guidelines, regulations, or accountability mechanisms. CONCLUSIONS: These findings suggest broad public support for IGG, and interest in developing systems of accountability for its practice. Our study provides useful insight for policy makers, genomic database stewards, law enforcement, and other stakeholders in IGG's practice, and suggests multiple directions for future research.

IGG in the trenches: Results of an in-depth interview study on the practice, politics, and future of investigative genetic genealogy.

Investigative genetic genealogy (IGG) is a new technique for identifying criminal suspects and unidentified deceased and living persons that has sparked controversy. In a criminal case, the technique involves uploading genetic information left by a putative perpetrator at the crime scene to one or more direct-to-consumer genetic genealogy databases with the intention of identifying the perpetrator's genetic relatives and, eventually, locating the perpetrator on the family tree. In 2018, IGG helped to identify the Golden State Killer, and it has since been used in hundreds of investigations in the United States. Here, we report findings from in-depth interviews with 24 U.S.-based individuals involved in IGG that are relevant to the technique's current practice and predicted future. Key findings include: an emphasis on restricting IGG as a conceptual and technical matter to lead generation; the rapid growth of a private and largely self-regulating industry to support IGG; general recognition of three categories of cases associated with distinct practical, ethical, and policy questions, as well as varying degrees of controversy; and the significant influence of perceived public opinion on IGG practice. The experiences and perspectives of individuals in the IGG trenches related to these and other issues are potentially useful inputs to ongoing efforts to regulate the technique.

Risk perception and intended behavior change after uninformative genetic results for adult-onset hereditary conditions in unselected patients.

Population genetic screening for preventable adult-onset hereditary conditions may improve disease management and morbidity but most individuals will receive uninformative results that do not indicate higher risk for disease. Investigation into subsequent psychosocial health and behaviors is necessary to inform population screening feasibility, effectiveness, and cost considerations. We conducted a prospective survey study of unselected University of Washington Medicine patients enrolled in a genetic research study screening for pathogenic variation in medically important genes. Survey questions adapted from the Feelings About genomiC Testing Results (FACToR) questionnaire and designed to understand perceived disease risk change and planned health behaviors were administered after receipt of results. Overall, 2761 people received uninformative results and 1352 (49%) completed survey items. Respondents averaged 41 years old, 62% were female, and 56% were Non-Hispanic Asian. Results from the FACToR instrument showed mean (SD) scores of 0.92 (1.34), 7.63 (3.95), 1.65 (2.23), and 0.77 (1.50) for negative emotions, positive emotions, uncertainty, and privacy concerns, respectively, suggesting minimal psychosocial harms from genetic screening. Overall, 12.2% and 9.6% of survey respondents believed that their risk of cancer or heart disease, respectively, had changed after receiving their uninformative genetic screening results. Further, 8.5% of respondents planned to make healthcare changes and 9.1% other behavior changes. Future work is needed to assess observed behavior changes attributable to uninformative screening results and if small changes in behavior among this population have large downstream impacts.

Conflating race and ancestry: Tracing decision points about population descriptors over the precision medicine research life course.

Responding to calls for human genomics to shift away from the use of race, genomic investigators are coalescing around the possibility of using genetic ancestry. This shift has renewed questions about the use of social and genetic concepts of difference in precision medicine research (PMR). Drawing from qualitative data on five PMR projects, we illustrate negotiations within and between research teams as genomic investigators deliberate on the relevance of race and genetic ancestry for different analyses and contexts. We highlight how concepts of both social and genetic difference are embedded within and travel through research practices, and identify multiple points across the research life course at which conceptual slippage and conflation between race and genetic ancestry occur. We argue that moving beyond race will require PMR investigators to confront the entrenched ways in which race is built into research practices and biomedical infrastructures.

Interrogating the Value of Return of Results for Diverse Populations: Perspectives from Precision Medicine Researchers.

BACKGROUND: Over the last decade, the return of results (ROR) in precision medicine research (PMR) has become increasingly routine. Calls for individual rights to research results have extended the "duty to report" from clinically useful genetic information to traits and ancestry results. ROR has thus been reframed as inherently beneficial to research participants, without a needed focus on who benefits and how. This paper addresses this gap, particularly in the context of PMR aimed at increasing participant diversity, by providing investigator and researcher perspectives on and questions about the assumed value of ROR in PMR. METHODS: Semi-structured interviews with a purposive sample of investigators and researchers across federally funded PMR studies in three national consortia, as well as observations of study activities, focused on how PM researchers conceptualize diversity and implement inclusive practices across research stages, including navigating ROR. RESULTS: Interviewees (1) validated the value of ROR as a benefit of PMR, while others (2) questioned the benefit of clinically actionable results to individuals in the absence of sufficient resources for translating findings into health care for diverse and disadvantaged populations; (3) expressed uncertainties in applying the presumed value of ROR as a benefit for non-clinical results; and (4) and debated when the promise of the value of ROR may undermine trust in PMR, and divert efforts to return value beyond ROR. CONCLUSIONS: Conceptualizations of diversity and inclusion among PM researchers and investigators raise unique ethical questions where unexamined assumptions of the value of ROR inform study recruitment efforts to enroll minoritized and under-represented populations. A lack of consideration for resources and infrastructure necessary to translate ROR into actionable information may hinder trustworthy community-research relationships. Thus, we argue for a more intentional interrogation of ROR practices as an offer of benefit and for whom.

An Ethical Framework for Research Using Genetic Ancestry.

A wide range of research uses patterns of genetic variation to infer genetic similarity between individuals, typically referred to as genetic ancestry. This research includes inference of human demographic history, understanding the genetic architecture of traits, and predicting disease risk. Researchers are not just structuring an intellectual inquiry when using genetic ancestry, they are also creating analytical frameworks with broader societal ramifications. This essay presents an ethics framework in the spirit of virtue ethics for these researchers: rather than focus on rule following, the framework is designed to build researchers' capacities to react to the ethical dimensions of their work. The authors identify one overarching principle of intellectual freedom and responsibility, noting that freedom in all its guises comes with responsibility, and they identify and define four principles that collectively uphold researchers' intellectual responsibility: truthfulness, justice and fairness, anti-racism, and public beneficence. Researchers should bring their practices into alignment with these principles, and to aid this, the authors name three common ways research practices infringe these principles, suggest a step-by-step process for aligning research choices with the principles, provide rules of thumb for achieving alignment, and give a worked case. The essay concludes by identifying support needed by researchers to act in accord with the proposed framework.

Factors Influencing Genetic Screening Enrollment among a Diverse, Community-Ascertained Cohort.

INTRODUCTION: Genetic screening for preventable adult-onset hereditary conditions has been proposed as a mechanism to reduce health disparities. Analysis of how race and ethnicity influence decision-making to receive screening can inform recruitment efforts and more equitable population screening design. A study at the University of Washington Medicine that invited unselected patients to participate in genetic screening for pathogenic variation in medically important genes provided an opportunity to evaluate these factors. METHODS: We analyzed screening enrollee survey data to understand factors most important and least important in decision-making about screening overall and across different race and ethnicity groups. Electronic health record race and ethnicity and survey-reported race and ethnicity were compared to assist with interpretation. Comments provided about reasons for not enrolling in screening were analyzed using content analysis. RESULTS: Overall, learning about disease risk and identifying risk early for prevention purposes were important factors in decision-making to receive screening, and regrets about screening and screening being against one's moral code were not viewed as important. Although racial identity was challenging to assign in all cases, compared to other enrollees, African-American and Asian enrollees considered test accuracy and knowing more about the test to be of greater importance. Three themes emerged related to nonparticipation: benefits do not outweigh risks, don't want to know, and challenges with study logistics. CONCLUSION: Our results highlight important motivators for receiving screening and areas that can be addressed to increase screening interest and accessibility. This knowledge can inform future population screening program design including recruitment and education approaches.

Studying the impact of translational genomic research: Lessons from eMERGE.

Two major goals of the Electronic Medical Record and Genomics (eMERGE) Network are to learn how best to return research results to patient/participants and the clinicians who care for them and also to assess the impact of placing these results in clinical care. Yet since its inception, the Network has confronted a host of challenges in achieving these goals, many of which had ethical, legal, or social implications (ELSIs) that required consideration. Here, we share impediments we encountered in recruiting participants, returning results, and assessing their impact, all of which affected our ability to achieve the goals of eMERGE, as well as the steps we took to attempt to address these obstacles. We divide the domains in which we experienced challenges into four broad categories: (1) study design, including recruitment of more diverse groups; (2) consent; (3) returning results to participants and their health care providers (HCPs); and (4) assessment of follow-up care of participants and measuring the impact of research on participants and their families. Since most phases of eMERGE have included children as well as adults, we also address the particular ELSI posed by including pediatric populations in this research. We make specific suggestions for improving translational genomic research to ensure that future projects can effectively return results and assess their impact on patient/participants and providers if the goals of genomic-informed medicine are to be achieved.

Community Engagement in Precision Medicine Research: Organizational Practices and Their Impacts for Equity.

BACKGROUND: In the wake of mandates for biomedical research to increase participation by members of historically underrepresented populations, community engagement (CE) has emerged as a key intervention to help achieve this goal. METHODS: Using interviews, observations, and document analysis, we examine how stakeholders in precision medicine research understand and seek to put into practice ideas about who to engage, how engagement should be conducted, and what engagement is for. RESULTS: We find that ad hoc, opportunistic, and instrumental approaches to CE exacted significant consequences for the time and resources devoted to engagement and the ultimate impacts it has on research. Critical differences emerged when engagement and research decisionmaking were integrated with each other versus occurring in parallel, separate parts of the study organization, and whether community members had the ability to determine which issues would be brought to them for consideration or to revise or even veto proposals made upstream based on criteria that mattered to them. CE was understood to have a range of purposes, from instrumentally facilitating recruitment and data collection, to advancing community priorities and concerns, to furthering long-term investments in relationships with and changes in communities. These choices about who to engage, what engagement activities to support, how to solicit and integrate community input into the workflow of the study, and what CE was for were often conditioned upon preexisting perceptions and upstream decisions about study goals, competing priorities, and resource availability. CONCLUSIONS: Upstream choices about CE and constraints of time and resources cascade into tradeoffs that often culminated in "pantomime community engagement." This approach can create downstream costs when engagement is experienced as improvised and sporadic. Transformations are needed for CE to be seen as a necessary scientific investment and part of the scientific process.

Cloud-based biomedical data storage and analysis for genomic research: Landscape analysis of data governance in emerging NIH-supported platforms.

The storage, sharing, and analysis of genomic data poses technical and logistical challenges that have precipitated the development of cloud-based computing platforms designed to facilitate collaboration and maximize the scientific utility of data. To understand cloud platforms' policies and procedures and the implications for different stakeholder groups, in summer 2021, we reviewed publicly available documents (N = 94) sourced from platform websites, scientific literature, and lay media for five NIH-funded cloud platforms (the All of Us Research Hub, NHGRI AnVIL, NHLBI BioData Catalyst, NCI Genomic Data Commons, and the Kids First Data Resource Center) and a pre-existing data sharing mechanism, dbGaP. Platform policies were compared across seven categories of data governance: data submission, data ingestion, user authentication and authorization, data security, data access, auditing, and sanctions. Our analysis finds similarities across the platforms, including reliance on a formal data ingestion process, multiple tiers of data access with varying user authentication and/or authorization requirements, platform and user data security measures, and auditing for inappropriate data use. Platforms differ in how data tiers are organized, as well as the specifics of user authentication and authorization across access tiers. Our analysis maps elements of data governance across emerging NIH-funded cloud platforms and as such provides a key resource for stakeholders seeking to understand and utilize data access and analysis options across platforms and to surface aspects of governance that may require harmonization to achieve the desired interoperability.

Diagnostic yield of genetic screening in a diverse, community-ascertained cohort.

BACKGROUND: Population screening for genetic risk of adult-onset preventable conditions has been proposed as an attractive public health intervention. Screening unselected individuals can identify many individuals who will not be identified through current genetic testing guidelines. METHODS: We sought to evaluate enrollment in and diagnostic yield of population genetic screening in a resource-limited setting among a diverse population. We developed a low-cost, short-read next-generation sequencing panel of 25 genes that had 98.4% sensitivity and 99.98% specificity compared to diagnostic panels. We used email invitations to recruit a diverse cohort of patients in the University of Washington Medical Center system unselected for personal or family history of hereditary disease. Participants were sent a saliva collection kit in the mail with instructions on kit use and return. Results were returned using a secure online portal. Enrollment and diagnostic yield were assessed overall and across race and ethnicity groups. RESULTS: Overall, 40,857 people were invited and 2889 (7.1%) enrolled. Enrollment varied across race and ethnicity groups, with the lowest enrollment among African American individuals (3.3%) and the highest among Multiracial or Other Race individuals (13.0%). Of 2864 enrollees who received screening results, 106 actionable variants were identified in 103 individuals (3.6%). Of those who screened positive, 30.1% already knew about their results from prior genetic testing. The diagnostic yield was 74 new, actionable genetic findings (2.6%). The addition of more recently identified cancer risk genes increased the diagnostic yield of screening. CONCLUSIONS: Population screening can identify additional individuals that could benefit from prevention, but challenges in recruitment and sample collection will reduce actual enrollment and yield. These challenges should not be overlooked in intervention planning or in cost and benefit analysis.

Trustworthiness matters: Building equitable and ethical science.

Trustworthy science requires research practices that center issues of ethics, equity, and inclusion. We announce the Leadership in the Equitable and Ethical Design (LEED) of Science, Technology, Mathematics, and Medicine (STEM) initiative to create best practices for integrating ethical expertise and fostering equitable collaboration.

Returning integrated genomic risk and clinical recommendations: The eMERGE study.

PURPOSE: Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk. METHODS: To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores, monogenic risks, family history, and clinical risk assessments via a genome-informed risk assessment (GIRA) report and will assess uptake of care recommendations after return of results. RESULTS: GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022. CONCLUSION: Return of a novel report for communicating monogenic, polygenic, and family history-based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.

Population genomic screening: Ethical considerations to guide age at implementation.

Currently, most genetic testing involves next generation sequencing or panel testing, indicating future population-based screening will involve simultaneous testing for multiple disease risks (called here "panel testing"). Genomic screening typically focuses on single or groups of related disorders, with little utilization of panel testing. Furthermore, the optimal age for test ordering is rarely addressed in terms of whether it should coincide with the age of majority (18 years old) or after the age of majority (26 years old). We conducted an ethical analysis utilizing a hypothetical "narrow" panel test comprised of the CDC Tier 1 Genomic Applications: Familial Hypercholesterolemia (FH), increases individuals' cardiovascular risk due to elevated low-density lipoprotein (LDL) cholesterol levels; Hereditary Breast and Ovarian Cancer (HBOC), increases lifetime risk of developing cancer; and Lynch Syndrome (LS), increases lifetime risk of developing colorectal cancer. We conducted a utilitarian analysis, on the assumption that health systems seek to maximize utility for patients. Screening at the "age of majority" is preferred for FH due to lowering FH patients' cholesterol levels via statins providing high lifetime benefits and low risks. Screening "after the age of majority" is preferred for HBOC and LS due to availability of effective surveillance, the recommendation for screening activities to begin at age 26, and prophylactic interventions connected to surveillance. We also utilized a supplemental principlist-based approach that identified relevant concerns and trade-offs. Consideration of clinical, non-clinical, and family planning implications suggests narrow panel testing would be best deployed after 26 (rather than at 18) years of age.

Targeting Representation: Interpreting Calls for Diversity in Precision Medicine Research.

Scientists have identified a "diversity gap" in genetic samples and health data, which have been drawn predominantly from individuals of European ancestry, as posing an existential threat to the promise of precision medicine. Inadequate inclusion as articulated by scientists, policymakers, and ethicists has prompted large-scale initiatives aimed at recruiting populations historically underrepresented in biomedical research. Despite explicit calls to increase diversity, the meaning of diversity - which dimensions matter for what outcomes and why - remain strikingly imprecise. Drawing on our document review and qualitative data from observations and interviews of funders and research teams involved in five precision medicine research (PMR) projects, we note that calls for increasing diversity often focus on "representation" as the goal of recruitment. The language of representation is used flexibly to refer to two objectives: achieving sufficient genetic variation across populations and including historically disenfranchised groups in research. We argue that these dual understandings of representation are more than rhetorical slippage, but rather allow for the contemporary collection of samples and data from marginalized populations to stand in as correcting historical exclusion of social groups towards addressing health inequity. We trace the unresolved historical debates over how and to what extent researchers should procure diversity in PMR and how they contributed to ongoing uncertainty about what axes of diversity matter and why. We argue that ambiguity in the meaning of representation at the outset of a study contributes to a lack of clear conceptualization of diversity downstream throughout subsequent phases of the study.

Recommendations on the use and reporting of race, ethnicity, and ancestry in genetic research: Experiences from the NHLBI TOPMed program.

How race, ethnicity, and ancestry are used in genomic research has wide-ranging implications for how research is translated into clinical care and incorporated into public understanding. Correlation between race and genetic ancestry contributes to unresolved complexity for the scientific community, as illustrated by heterogeneous definitions and applications of these variables. Here, we offer commentary and recommendations on the use of race, ethnicity, and ancestry across the arc of genetic research, including data harmonization, analysis, and reporting. While informed by our experiences as researchers affiliated with the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, these recommendations are applicable to basic and translational genomic research in diverse populations with genome-wide data. Moving forward, considerable collaborative effort will be required to ensure that race, ethnicity, and ancestry are described and used appropriately to generate scientific knowledge that yields broad and equitable benefit.

Social and scientific motivations to move beyond groups in allele frequencies: The TOPMed experience.

For the genomics community, allele frequencies within defined groups (or "strata") are useful across multiple research and clinical contexts. Benefits include allowing researchers to identify populations for replication or "look up" studies, enabling researchers to compare population-specific frequencies to validate findings, and facilitating assessment of variant pathogenicity in clinical contexts. However, there are potential concerns with stratified allele frequencies. These include potential re-identification (determining whether or not an individual participated in a given research study based on allele frequencies and individual-level genetic data), harm from associating stigmatizing variants with specific groups, potential reification of race as a biological rather than a socio-political category, and whether presenting stratified frequencies-and the downstream applications that this presentation enables-is consistent with participants' informed consents. The NHLBI Trans-Omics for Precision Medicine (TOPMed) program considered the scientific and social implications of different approaches for adding stratified frequencies to the TOPMed BRAVO (Browse All Variants Online) variant server. We recommend a novel approach of presenting ancestry-specific allele frequencies using a statistical method based upon local genetic ancestry inference. Notably, this approach does not require grouping individuals by either predominant global ancestry or race/ethnicity and, therefore, mitigates re-identification and other concerns as the mixture distribution of ancestral allele frequencies varies across the genome. Here we describe our considerations and approach, which can assist other genomics research programs facing similar issues of how to define and present stratified frequencies in publicly available variant databases.