Do research participants share genomic screening results with family members?

The public health impact of genomic screening can be enhanced by cascade testing. However, cascade testing depends on communication of results to family members. While the barriers and facilitators of family communication have been researched following clinical genetic testing, the factors impacting the dissemination of genomic screening results are unknown. Using the pragmatic Electronic Medical Records and Genomics Network-3 (eMERGE-3) study, we explored the reported sharing practices of participants who underwent genomic screening across the United States. Six eMERGE-3 sites returned genomic screening results for mostly dominant medically actionable disorders and surveyed adult participants regarding communication of results with first-degree relatives. Across the sites, 279 participants completed a 1-month and/or 6-month post-results survey. By 6 months, only 34% of the 156 respondents shared their results with all first-degree relatives and 4% did not share with any. Over a third (39%) first-degree relatives were not notified of the results. Half (53%) of participants who received their results from a genetics provider shared them with all first-degree relatives compared with 11% of participants who received their results from a non-genetics provider. The most frequent reasons for sharing were a feeling of obligation (72%) and that the information could help family members make medical decisions (72%). The most common reasons indicated for not sharing were that the family members were too young (38%), or they were not in contact (25%) or not close to them (25%). These data indicate that the professional returning the results may impact sharing patterns, suggesting that there is a need to continue to educate healthcare providers regarding approaches to facilitate sharing of genetic results within families. Finally, these data suggest that interventions to increase sharing may be universally effective regardless of the origin of the genetic result.

Pediatric Decision Making: Consensus Recommendations.

Despite apparent disagreement in the scholarly literature on standards of pediatric decision making, a recognition that similar norms underpin many of the dominant frameworks motivated a June 2022 symposium "Best Interests and Beyond: Standards of Decision Making in Pediatrics" in St Louis, MO. Over the course of this 3-day symposium, 17 expert scholars (see author list) deliberated on the question "In the context of US pediatric care, what moral precepts ought to guide parents and clinicians in medical decision making for children?" The symposium and subsequent discussion generated 6 consensus recommendations for pediatric decision making, constructed with the primary goals of accessibility, teachability, and feasibility for practicing clinicians, parents, and legal guardians. In this article, we summarize these recommendations, including their justification, limitations, and remaining concerns.

Developing Ethics and Equity Principles, Terms, and Engagement Tools to Advance Health Equity and Researcher Diversity in AI and Machine Learning: Modified Delphi Approach.

BACKGROUND: Artificial intelligence (AI) and machine learning (ML) technology design and development continues to be rapid, despite major limitations in its current form as a practice and discipline to address all sociohumanitarian issues and complexities. From these limitations emerges an imperative to strengthen AI and ML literacy in underserved communities and build a more diverse AI and ML design and development workforce engaged in health research. OBJECTIVE: AI and ML has the potential to account for and assess a variety of factors that contribute to health and disease and to improve prevention, diagnosis, and therapy. Here, we describe recent activities within the Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) Ethics and Equity Workgroup (EEWG) that led to the development of deliverables that will help put ethics and fairness at the forefront of AI and ML applications to build equity in biomedical research, education, and health care. METHODS: The AIM-AHEAD EEWG was created in 2021 with 3 cochairs and 51 members in year 1 and 2 cochairs and ~40 members in year 2. Members in both years included AIM-AHEAD principal investigators, coinvestigators, leadership fellows, and research fellows. The EEWG used a modified Delphi approach using polling, ranking, and other exercises to facilitate discussions around tangible steps, key terms, and definitions needed to ensure that ethics and fairness are at the forefront of AI and ML applications to build equity in biomedical research, education, and health care. RESULTS: The EEWG developed a set of ethics and equity principles, a glossary, and an interview guide. The ethics and equity principles comprise 5 core principles, each with subparts, which articulate best practices for working with stakeholders from historically and presently underrepresented communities. The glossary contains 12 terms and definitions, with particular emphasis on optimal development, refinement, and implementation of AI and ML in health equity research. To accompany the glossary, the EEWG developed a concept relationship diagram that describes the logical flow of and relationship between the definitional concepts. Lastly, the interview guide provides questions that can be used or adapted to garner stakeholder and community perspectives on the principles and glossary. CONCLUSIONS: Ongoing engagement is needed around our principles and glossary to identify and predict potential limitations in their uses in AI and ML research settings, especially for institutions with limited resources. This requires time, careful consideration, and honest discussions around what classifies an engagement incentive as meaningful to support and sustain their full engagement. By slowing down to meet historically and presently underresourced institutions and communities where they are and where they are capable of engaging and competing, there is higher potential to achieve needed diversity, ethics, and equity in AI and ML implementation in health research.

Whole-genome sequencing in newborn screening? A statement on the continued importance of targeted approaches in newborn screening programmes.

The advent and refinement of sequencing technologies has resulted in a decrease in both the cost and time needed to generate data on the entire sequence of the human genome. This has increased the accessibility of using whole-genome sequencing and whole-exome sequencing approaches for analysis in both the research and clinical contexts. The expectation is that more services based on these and other high-throughput technologies will become available to patients and the wider population. Some authors predict that sequencing will be performed once in a lifetime, namely, shortly after birth. The Public and Professional Policy Committee of the European Society of Human Genetics, the Human Genome Organisation Committee on Ethics, Law and Society, the PHG Foundation and the P3G International Paediatric Platform address herein the important issues and challenges surrounding the potential use of sequencing technologies in publicly funded newborn screening (NBS) programmes. This statement presents the relevant issues and culminates in a set of recommendations to help inform and guide scientists and clinicians, as well as policy makers regarding the necessary considerations for the use of genome sequencing technologies and approaches in NBS programmes. The primary objective of NBS should be the targeted analysis and identification of gene variants conferring a high risk of preventable or treatable conditions, for which treatment has to start in the newborn period or in early childhood.