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By improving disease risk prediction, polygenic risk scores (PRSs) could have a significant impact on health promotion and disease prevention. Due to the historical oversampling of populations with European ancestry for genome-wide association studies, PRSs perform less well in other, understudied populations, leading to concerns that clinical use in their current forms could widen health care disparities. The PRIMED Consortium was established to develop methods to improve the performance of PRSs in global populations and individuals of diverse genetic ancestry. To this end, PRIMED is aggregating and harmonizing multiple phenotype and genotype datasets on AnVIL, an interoperable secure cloud-based platform, to perform individual- and summary-level analyses using population and statistical genetics approaches. Study sites, the coordinating center, and representatives from the NIH work alongside other NHGRI and global consortia to achieve these goals. PRIMED is also evaluating ethical and social implications of PRS implementation and investigating the joint modeling of social determinants of health and PRS in computing disease risk. The phenotypes of interest are primarily cardiometabolic diseases and cancer, the leading causes of death and disability worldwide. Early deliverables of the consortium include methods for data sharing on AnVIL, development of a common data model to harmonize phenotype and genotype data from cohort studies as well as electronic health records, adaptation of recent guidelines for population descriptors to global cohorts, and sharing of PRS methods/tools. As a multisite collaboration, PRIMED aims to foster equity in the development and use of polygenic risk assessment., Competing Interests: Declaration of interests P.N. reports research grants from Allelica, Apple, Amgen, Boston Scientific, Genentech/Roche, and Novartis; personal fees from Allelica, Apple, AstraZeneca, Blackstone Life Sciences, Foresite Labs, Genentech/Roche, GV, HeartFlow, Magnet Biomedicine, and Novartis; scientific advisory board membership of Esperion Therapeutics, Preciseli, and TenSixteen Bio; scientific co-founder of TenSixteen Bio; equity in MyOme, Preciseli, and TenSixteen Bio; and spousal employment at Vertex Pharmaceuticals, all unrelated to the present work. E.E.K. has received personal fees from Regeneron Pharmaceuticals, 23&Me, Allelica, and Illumina; has received research funding from Allelica; and serves on the advisory boards for Encompass Biosciences, Overtone, and Galateo Bio., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Introduction: Implementation science frameworks with a focus on health equity have emerged to help guide the introduction of new interventions into healthcare and community settings while limiting health disparities. The purpose of this research was to explore the applicability of such frameworks to guide the equitable implementation of population genetic screening programs., Methods: We searched PubMed and reference lists for relevant frameworks and examples of their use in health settings. We then assessed if and how selected frameworks provide guidance for different stages of population genetic screening: recruitment, sample collection, result return, follow-up care and long-term management, and cascade screening. Findings were synthesized into a list of health equity considerations specific to each stage., Results: We identified 5 implementation frameworks that focus on health equity. Guidance varied by framework type: determinant (explaining what affects implementation outcomes), process (translating research into practice), or evaluation (assessing implementation). Common characteristics included focusing implementation efforts on populations who have historically experienced health inequities and adapting interventions to fit local contexts. Process models also highlighted the importance of community partnerships., Discussion: Overall, frameworks offered broad recommendations applicable to population genetic screening program implementation. However, gaps still exist in guidance provided for later stages of population genetic screening. To improve the equitable implementation of genetic screening, future programs may benefit from utilizing one or more of these frameworks or by incorporating the health equity considerations and outcomes compiled in this analysis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 Rao, Fullerton, Shirts, Chen and Henrikson.)

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.

The differential performance of polygenic risk scores (PRSs) by group is one of the major ethical barriers to their clinical use. It is also one of the main practical challenges for any implementation effort. The social repercussions of how people are grouped in PRS research must be considered in communications with research participants, including return of results. Here, we outline the decisions faced and choices made by a large multi-site clinical implementation study returning PRSs to diverse participants in handling this issue of differential performance. Our approach to managing the complexities associated with the differential performance of PRSs serves as a case study that can help future implementers of PRSs to plot an anticipatory course in response to this issue., Competing Interests: Declaration of interests A.C.F.L. owns some stock in Fabric Genomics; E.D.E. is an employee and stockholder of Invitae, advisor and stockholder of Taproot Health, and advisor and stockholder of Exir; R.C.G. receives compensation for advising the following companies: Allelica, Atria, Fabric, Genomic Life, and Juniper Genomics; and is co-founder of Genome Medical and Nurture Genomics; E.E.K. has received personal fees from Regeneron Pharmaceuticals, 23&Me, Allelica, and Illumina; has received research funding from Allelica; and serves on the advisory boards for Encompass Biosciences, Overtone, and Galatea Bio; N.L. received personal fees from Illumina Inc; E.P. is a paid consultant for Allelica Inc.; M.S. is a member of the Institutional Review Board of the All of Us Research Program; J.W.S. is a member of the Scientific Advisory Board of Sensorium Therapeutics (with equity), has received grant support from Biogen, Inc., and is PI of a collaborative study of the genetics of depression and bipolar disorder sponsored by 23andMe for which 23andMe provides analysis time as in-kind support but no payments., (Copyright © 2024 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Transgender, gender diverse, and intersex (TGDI) individuals face significant health disparities due to individual and systemic experiences of discrimination, impacting their access to healthcare. While clinical genetic testing has become increasingly accessible to the general population, the field of clinical genetics perpetuates a narrative of biological essentialism, which creates barriers for TGDI patients. Biological essentialism upholds that sex is a binary, fixed, and innate characteristic, a misconception that has been historically weaponized against the TGDI community in both individual experiences of discrimination and anti-trans legislation, among other systemic forms of oppression. Rejecting this discriminatory framework requires careful consideration of, and changes to, long-established practices that often go unquestioned, such as quality control metrics in genetic testing, in order to improve TGDI patients' outcomes and access to genetic services. The sex-check, comparing an individuals reported sex against their sex chromosomes, is an example of how laboratory genetics practices reinforce the narrative that sex is determined purely by chromosomal composition. Additionally, the sex-check "outs" TGDI people in clinical settings, creating a discriminatory and unsafe environment for these patients. Alternative quality control procedures and inclusive practices, such as clearer delineation of sex and gender on test requisition forms, are proposed to improve TGDI patient experiences. Genetic counselors and other clinical providers have a responsibility to address historical discrimination and advocate for changes to laboratory practice, so as to create affirming experiences for TGDI patients., (© 2024 National Society of Genetic Counselors.)

Health equity is the state in which everyone has fair and just opportunities to attain their highest level of health. The field of human genomics has fallen short in increasing health equity, largely because the diversity of the human population has been inadequately reflected among participants of genomics research. This lack of diversity leads to disparities that can have scientific and clinical consequences. Achieving health equity related to genomics will require greater effort in addressing inequities within the field. As part of the commitment of the National Human Genome Research Institute (NHGRI) to advancing health equity, it convened experts in genomics and health equity research to make recommendations and performed a review of current literature to identify the landscape of gaps and opportunities at the interface between human genomics and health equity research. This Perspective describes these findings and examines health equity within the context of human genomics and genomic medicine., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Background: A major obstacle faced by families with rare diseases is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years and causal variants are identified in under 50%, even when capturing variants genome-wide. To aid in the interpretation and prioritization of the vast number of variants detected, computational methods are proliferating. Knowing which tools are most effective remains unclear. To evaluate the performance of computational methods, and to encourage innovation in method development, we designed a Critical Assessment of Genome Interpretation (CAGI) community challenge to place variant prioritization models head-to-head in a real-life clinical diagnostic setting., Methods: We utilized genome sequencing (GS) data from families sequenced in the Rare Genomes Project (RGP), a direct-to-participant research study on the utility of GS for rare disease diagnosis and gene discovery. Challenge predictors were provided with a dataset of variant calls and phenotype terms from 175 RGP individuals (65 families), including 35 solved training set families with causal variants specified, and 30 unlabeled test set families (14 solved, 16 unsolved). We tasked teams to identify causal variants in as many families as possible. Predictors submitted variant predictions with estimated probability of causal relationship (EPCR) values. Model performance was determined by two metrics, a weighted score based on the rank position of causal variants, and the maximum F-measure, based on precision and recall of causal variants across all EPCR values., Results: Sixteen teams submitted predictions from 52 models, some with manual review incorporated. Top performers recalled causal variants in up to 13 of 14 solved families within the top 5 ranked variants. Newly discovered diagnostic variants were returned to two previously unsolved families following confirmatory RNA sequencing, and two novel disease gene candidates were entered into Matchmaker Exchange. In one example, RNA sequencing demonstrated aberrant splicing due to a deep intronic indel in ASNS, identified in trans with a frameshift variant in an unsolved proband with phenotypes consistent with asparagine synthetase deficiency., Conclusions: Model methodology and performance was highly variable. Models weighing call quality, allele frequency, predicted deleteriousness, segregation, and phenotype were effective in identifying causal variants, and models open to phenotype expansion and non-coding variants were able to capture more difficult diagnoses and discover new diagnoses. Overall, computational models can significantly aid variant prioritization. For use in diagnostics, detailed review and conservative assessment of prioritized variants against established criteria is needed., (© 2024. The Author(s).)

Introduction: Obesity is associated with numerous chronic conditions and an increased risk for surgical complications. Laparoscopic and robotic adrenalectomy have proven effective in the resection of adrenal tumors. This study analyzes the outcomes of severely obese patients (body-mass index [BMI] ≥35 kg/m 2 ) following minimally invasive adrenalectomy. Materials and Methods: A retrospective analysis of patients who underwent minimally invasive adrenalectomy at our institution between 2010 and 2023 was conducted. Two matching analyses were performed. The first analysis compared patients with BMI greater versus lower than 35 kg/m 2 . The second analysis compared outcomes between robotic and laparoscopic adrenalectomy in patients with a BMI ≥35 kg/m 2 . Results: A total of 278 patients were included in the study. The median tumor size was 29 mm. Adrenal tumors had similar laterality, and most were hormonally active (66.2%). The most common pathological diagnosis was pheochromocytoma (25.5%). No statistical difference was found in peri- and postoperative outcomes between patients with BMI ≥35 and <35 kg/m 2 who underwent minimally invasive adrenalectomy. When the surgical approach was compared in severely obese patients, robotic adrenalectomy was associated with shorter hospital length of stay with similar operative time as the laparoscopic approach. Conclusions: Minimally invasive adrenalectomy is safe and feasible in patients with BMI ≥35 kg/m 2 . Robotic and laparoscopic approaches are both safe and efficient for the resection of adrenal tumors in severely obese patients.

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.

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., Competing Interests: Declaration of Competing Interests C.J.G. and S.M.F. are members of the Investigative Genetic Genealogy Working Group of the Scientific Working Group on DNA Analysis Methods. A.L.M. is a former member of the FamilyTreeDNA Citizen’s Panel. C.J.G. is a member of the Policy and Practice Subcommittee of the National Technology Validation and Implementation Collaborative Forensic Investigative Genetic Genealogy Technical Validation Working Group. She is also a member of the Advisory Board of the Investigative Genetic Genealogy Accreditation Board., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

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., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Introduction: In the USA, patients who undergo genetic testing for hereditary cancer risk are responsible for informing relatives about their genetic test results, but many relatives never find out they might be at risk. A health system-mediated relative notification program might help fill this gap, but questions remain about the acceptability of this approach., Methods: We analyzed qualitative data from a single-arm, nonrandomized, mixed-methods study to understand how patients and families experienced a new health system-mediated relative notification program. We invited all study participants to participate in semi-structured telephone interviews at 6-8 weeks after return of genetic test results. We used a template analysis approach to thematically analyze interview transcripts., Results: We interviewed 32 participants, including 17 probands and 15 relatives. Relatives reported positive experiences with the notification program, noting they felt in control of decisions and appreciated genetic counselor involvement in communicating the proband's test results. Benefits of direct contact included reduced burden for probands, increased family discussions about health, and notification of relatives who otherwise would not have learned results. No participants reported adverse effects from the program., Conclusion: Overall, the relative notification program was acceptable to participants and supported probands in reaching at-risk relatives who otherwise might not have been notified. These findings could inform the implementation of future genetic risk family notification programs with the potential to improve uptake of cascade testing and advance cancer prevention and early detection efforts., (© 2024 The Author(s). Published by S. Karger AG, Basel.)

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., (© 2023. The Author(s), under exclusive licence to European Society of Human Genetics.)

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., Competing Interests: Declaration of interests W.K.C. is on the Board of Directors of Prime Medicine. J.F.P. was a paid consultant for Natera Inc. M. Sabatello and I.A.H. are members of the IRB for All of Us., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Competing Interests: Conflict of Interest C.J.Z.-M. is a director of a cytogenomics testing laboratory that offers cancer diagnostic testing. M.A. is a director of a molecular testing laboratory that offers carrier screening. K.B. is a genetic counselor of a molecular testing laboratory that offers carrier screening. F.Q.-R. is a director of a cytogenomics testing laboratory that offers cancer diagnostic testing. M.V. is a director of a molecular testing laboratory that offers carrier screening and sponsored panel testing. All other authors declare no conflicts of interest.

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., (© 2023. The Author(s).)

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., Competing Interests: The authors declare no competing interests., (© 2023 The Author(s).)

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., Competing Interests: Conflict of Interest N.S.A.-H. is an employee and equity holder of 23andMe; serves as a scientific advisory board member for Allelica, Inc; received personal fees from Genentech Inc, Allelica Inc, and 23andMe; received research funding from Akcea Therapeutics; and was previously employed by Regeneron Pharmaceuticals. T.W. has grant funding from Gilead Sciences, Inc. L.O. and T.R.-B are founders of a company developing MeTree. T.S., E.D.E., and E.H. are employees and stockholders of Invitae Corporation. E.M.M. has been a consultant for Avidity Bioscience, Amgen Inc, AstraZeneca, Cytokinetics, Invitae Corporation, Janssen Pharmaceuticals, Pfizer Inc, PepGen Inc, Tenaya Therapeutics, and Stealth BioTherapeutics Inc; she is also the founder of Ikaika Therapeutics. E.E.K. received personal fees from Illumina Inc, 23andMe, and Regeneron Pharmaceuticals and serves as a scientific advisory board member for Encompass Bioscience, Foresite Labs, and Galateo Bio. B.K. is an advisory board member and stockholder of Genome Medical. M.S. is a member of the Institutional Review Board of the All of Us Research Program. E.F.P. is a paid consultant for Allecia Inc. J.F.P. is a paid consultant for Natera Inc. All other authors declare no conflicts of interest., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

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., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Competing Interests: Conflict of Interest Funding and support listed in this section did not support the development of this document unless included in the acknowledgments section. M.K.T., M.C., P.R.G., and A.R.S. all serve as directors in clinical laboratories that perform a breadth of genetic and genomic analyses on a fee-for-service basis. D.R.S. is supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics of the National Cancer Institute, Rockville, MD, and also performs contract clinical telehealth services for Genome Medical, Inc in accordance with relevant National Cancer Institute ethics policies. All other authors declare no conflicts of interest.

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.

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., (© 2023 The Author(s). Published by S. Karger AG, Basel.)

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.

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Spencer and Fullerton.)

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., (Copyright ©2022, Yale Journal of Biology and Medicine.)

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., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2022 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Background: An alternative to population-based genetic testing, automated cascade genetic testing facilitated by sharing of family health history, has been conceptualized as a more efficient and cost-effective approach to identify hereditary genetic conditions. However, existing software and applications programming interfaces (API) for the practical implementation of this approach in health care settings have not been described. Methods: We reviewed API available for facilitating cascade genetic testing in electronic health records (EHRs). We emphasize any information regarding informed consent as provided for each tool. Using semi-structured key informant interviews, we investigated uptake of and barriers to integrating automated family cascade genetic testing into the EHR. Results: We summarized the functionalities of six tools related to utilizing family health history to facilitate cascade genetic testing. No tools were explicitly capable of facilitating family cascade genetic testing, but few enterprise EHRs supported family health history linkage. We conducted five key informant interviews with four main considerations that emerged including: 1) incentives for interoperability, 2) HIPAA and regulations, 3) mobile-app and alternatives to EHR deployment, 4) fundamental changes to conceptualizing EHRs. Discussion: Despite the capabilities of existing technology, limited bioinformatic support has been developed to automate processes needed for family cascade genetic testing and the main barriers for implementation are nontechnical, including an understanding of regulations, consent, and workflow. As the trade-off between cost and efficiency for population-based and family cascade genetic testing shifts, the additional tools necessary for their implementation should be considered., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Haas, Ralston, Fullerton, Scrol and Henrikson.)

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., Competing Interests: DECLARATION OF INTERESTS The authors declare no competing interests.

Background: Genetic testing for pathogenic variants associated with hereditary breast and ovarian cancer risk can improve cancer outcomes through enhanced preventive care in both people with known variants and their biologic relatives. Cascade screening-the process of case-finding in relatives by notifying and inviting them to consider testing-currently relies on the patient to notify their own at-risk relatives. However, many of these relatives never learn they might be at risk. We developed and implemented a new health system-led familial genetic risk notification process where the care team offers to contact at-risk relatives directly. This protocol describes a study to assess the feasibility, acceptability, and limited efficacy of this intervention., Methods: This feasibility study will use a single-arm, nonrandomized, mixed-methods prospective design. We will enroll two groups of participants: probands and relatives of probands. Eligible probands are currently enrolled Kaiser Permanente Washington (KPWA) members with an upcoming appointment for pre-test genetic counseling for hereditary Lynch syndrome, breast, or ovarian cancer. Eligible relatives, who do not have to be KPWA members, are first-and second-degree relatives of probands. During the appointment with the proband, the genetic counselor will determine whether the proband is appropriate for genetic testing and if so, which relatives might benefit from cascade testing. The genetic counselor then will offer to contact any or all identified relatives directly to discuss genetic risk and testing. The primary outcome of this study is the feasibility of the implemented familial notification process, which we will measure using quantitative and qualitative data on intervention reach, intervention acceptability, and limited efficacy. Analyses will be primarily descriptive and exploratory, with the intent of preparing for a future, larger trial of direct contact interventions., Discussion: Our findings will provide new, foundational evidence for the creation of US-based familial notification systems that directly address logistical and ethical challenges while prioritizing the preferences of patients and families., (© 2022. The Author(s).)

US funding agencies have begun to institutionalize expectations that biomedical studies achieve defined thresholds for diversity among research participants, including in precision medicine research (PMR). In this paper, we examine how practices of recruitment have unfolded in the wake of these diversity mandates. We find that a very common approach to seeking diverse participants leverages understandings of spatial, geographic, and site diversity as proxies and access points for participant diversity. That is, PMR investigators recruit from a diverse sampling of geographic areas, neighborhoods, sites, and institutional settings as both opportunistic but also meaningful ways to "bake in" participant diversity. In this way, logics of geographic and institutional diversity shift the question from who to recruit, to where. However, despite seeing geographic and site diversity as social and scientific 'goods' in the abstract and as key to getting diverse participants, PMR teams told us that working with diverse sites was often difficult in practice due to constraints in funding, time, and personnel, and inadequate research infrastructures and capacity. Thus, the ways in which these geographic and institutional diversity strategies were implemented resulted ultimately in limiting the meaningful inclusion of populations and organizations that had not previously participated in biomedical research and reproduced the inclusion of institutions that are already represented. These prevailing assumptions about and practices of "baked-in" diversity in fact exacerbate and produce other forms of inequity, in research capacity and research representation. These findings underscore how structural inequities in research resources must be addressed for diversity to be achieved in both research sites and research participants., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

'The Apportionment of Human Diversity' stands as a noteworthy intervention, both for the field of human population genetics as well as in the annals of public communication of science. Despite the widespread uptake of Lewontin's conclusion that racial classification is of 'virtually no genetic or taxonomic significance', the biomedical research community continues to grapple with whether and how best to account for race in its work. Nowhere is this struggle more apparent than in the latest attempts to translate genetic associations with complex disease risk to clinical use in the form of polygenic risk scores, or PRS. In this perspective piece, we trace current challenges surrounding the appropriate development and clinical application of PRS in diverse patient cohorts to ongoing difficulties deciding which facets of population structure matter, and for what reasons, to human health. Despite numerous analytical innovations, there are reasons that emerge from Lewontin's work to remain sceptical that accounting for population structure in the context of polygenic risk estimation will allow us to more effectively identify and intervene on the significant health disparities which plague marginalized populations around the world. This article is part of the theme issue 'Celebrating 50 years since Lewontin's apportionment of human diversity'.

Integrating data across heterogeneous research environments is a key challenge in multi-site, collaborative research projects. While it is important to allow for natural variation in data collection protocols across research sites, it is also important to achieve interoperability between datasets in order to reap the full benefits of collaborative work. However, there are few standards to guide the data coordination process from project conception to completion. In this paper, we describe the experiences of the Clinical Sequence Evidence-Generating Research (CSER) consortium Data Coordinating Center (DCC), which coordinated harmonized survey and genomic sequencing data from seven clinical research sites from 2020 to 2022. Using input from multiple consortium working groups and from CSER leadership, we first identify 14 lessons learned from CSER in the categories of communication, harmonization, informatics, compliance, and analytics. We then distill these lessons learned into 11 recommendations for future research consortia in the areas of planning, communication, informatics, and analytics. We recommend that planning and budgeting for data coordination activities occur as early as possible during consortium conceptualization and development to minimize downstream complications. We also find that clear, reciprocal, and continuous communication between consortium stakeholders and the DCC is equally important to maintaining a secure and centralized informatics ecosystem for pooling data. Finally, we discuss the importance of actively interrogating current approaches to data governance, particularly for research studies that straddle the research-clinical divide., Competing Interests: The authors declare no competing interests., (© 2022 The Author(s).)

We must embrace a multidimensional, continuous view of ancestry and move away from continental ancestry categories.

In recent decades, genetic genealogy has become popular as a result of direct-to-consumer (DTC) genetic testing. Some DTC genetic testing companies offer genetic relative-finder (GRF) services that compare the DNA of consenting participants to identify genetic relatives among them and provide each participant a list of their relative matches. We surveyed a convenience sample of GRF service participants to understand the prevalence of discoveries and associated experiences. Almost half (46%) of the 23,196 respondents had participated in GRF services only for non-specific reasons that included interest in building family trees and general curiosity. However, most (82%) also learned the identity of at least one genetic relative. Separately, most respondents (61%) reported learning something new about themselves or their relatives, including potentially disruptive information such as that a person they believed to be their biological parent is in fact not or that they have a sibling they had not known about. Respondents generally reported that discovering this new information had a neutral or positive impact on their lives, and most had low regret regarding their decision to participate in GRF services. Yet some reported making life changes as a result of their discoveries. Compared to respondents making other types of discoveries, those who learned that they were donor conceived reported the highest decisional regret and represented the largest proportion reporting net-negative consequences for themselves. Our findings indicate that discoveries from GRF services may be common and that the consequences for individuals, while generally positive, can be far-reaching and complex., Competing Interests: Declaration of interests C.J.G. and S.M.F. are members of the Investigative Genetic Genealogy Working Group of the Scientific Working Group on DNA Analysis Methods. A.L.M. was a founding member of the FamilyTreeDNA Citizen’s Panel. B.K. is founder and owner of Watershed DNA, LLC. All other authors declare no competing interests., (Copyright © 2022 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Purpose: To identify meanings of and challenges to enacting equitable diversification of genomics research, and specifically precision medicine research (PMR), teams., Methods: We conducted in-depth interviews with 102 individuals involved in three U.S.-based precision medicine research consortia and conducted over 400 observation hours of their working group meetings, consortium-wide meetings, and conference presentations. We also reviewed published reports on genomic workforce diversity (WFD), particularly those relevant to the PMR community., Results: Our study finds that many PMR teams encounter challenges as they strive to achieve equitable diversification on scientific teams. Interviewees articulated that underrepresented team members were often hired to increase the study's capacity to recruit diverse research participants, but are limited to on-the-ground staff positions with little influence over study design. We find existing hierarchies and power structures in the academic research ecosystem compound challenges for equitable diversification., Conclusion: Our results suggest that meaningful diversification of PMR teams will only be possible when team equity is prioritized as a core value in academic research communities., Competing Interests: The authors have declared that no competing interests exist.

The ethics of returning nonactionable genetic research results to individuals are unclear. Apolipoprotein L1 ( APOL1 ) genetic variants are nonactionable, predominantly found in people of West African ancestry, and contribute to kidney disease disparities. To inform ethical research practice, we interviewed researchers, clinicians, and African American community members ( n   =  76) about the potential risks and benefits of returning APOL1 research results. Stakeholders strongly supported returning APOL1 results. Benefits include reciprocity for participants, community education and rebuilding trust in research, and expectation of future actionability. Risks include analytic validity, misunderstanding, psychological burdens, stigma and discrimination, and questionable resource tradeoffs., Conclusions: APOL1 results should be offered to participants. Responsibly fulfilling this offer requires careful identification of best communication practices, broader education about the topic, and ongoing community engagement.

Importance: Multiple polygenic risk scores (PRSs) for breast cancer have been developed from large research consortia; however, their generalizability to diverse clinical settings is unknown., Objective: To examine the performance of previously developed breast cancer PRSs in a clinical setting for women of European, African, and Latinx ancestry., Design, Setting, and Participants: This cohort study using the Electronic Medical Records and Genomics (eMERGE) network data set included 39 591 women from 9 contributing medical centers in the US that had electronic medical records (EMR) linked to genotype data. Breast cancer cases and controls were identified through a validated EMR phenotyping algorithm., Main Outcomes and Measures: Multivariable logistic regression was used to assess the association between breast cancer risk and 7 previously developed PRSs, adjusting for age, study site, breast cancer family history, and first 3 ancestry informative principal components., Results: This study included 39 591 women: 33 594 with European, 3801 with African, and 2196 with Latinx ancestry. The mean (SD) age at breast cancer diagnosis was 60.7 (13.0), 58.8 (12.5), and 60.1 (13.0) years for women with European, African, and Latinx ancestry, respectively. PRSs derived from women with European ancestry were associated with breast cancer risk in women with European ancestry (highest odds ratio [OR] per 1-SD increase, 1.46; 95% CI, 1.41-1.51), women with Latinx ancestry (highest OR, 1.31; 95% CI, 1.09-1.58), and women with African ancestry (OR, 1.19; 95% CI, 1.05-1.35). For women with European ancestry, this association with breast cancer risk was largest in the extremes of the PRS distribution, with ORs ranging from 2.19 (95% CI, 1.84-2.53) to 2.48 (95% CI, 1.89-3.25) for the 3 different PRSs examined for those in the highest 1% of the PRS compared with those in the middle quantile. Among women with Latinx and African ancestries at the extremes of the PRS distribution, there were no statistically significant associations., Conclusions and Relevance: This cohort study found that PRS models derived from women with European ancestry for breast cancer risk generalized well for women with European, Latinx, and African ancestries across different clinical settings, although the effect sizes for women with African ancestry were smaller, likely because of differences in risk allele frequencies and linkage disequilibrium patterns. These results highlight the need to improve representation of diverse population groups, particularly women with African ancestry, in genomic research cohorts.

Health benefits to relatives of people at known genetic risk for hereditary cancer syndromes is key to realizing the promise of precision medicine. We conducted a qualitative study to design a patient- and family-centered program for direct contact of relatives to recommend cascade genetic testing. We conducted two rounds of data collection using focus groups followed by individual interviews with patients with HBOC or Lynch syndrome and a separate sample of people with a family history of hereditary cancers. Results indicate that U.S.-based health system-led direct contact of relatives is acceptable to patients and families, should take a programmatic approach, include consent of relatives before proband testing, complement to existing patient-mediated disclosure, and allow for relative control of information. Our findings suggest a set of requirements for U.S.-based direct contact programs that could ultimately benefit more relatives than current approaches.