Patient engagement is critical for implementation of the genomic component of precision medicine--with care taken to include the perspectives and needs of patients. Yet many patients may experience significant barriers to understanding genetic information and/or using the electronic patient portals that many health systems are using to meet the terms of meaningful use related to the return of laboratory and test results.

A major challenge for precision medicine research is including historically under-represented groups in numbers sufficient to ensure statistically valid inferences of the influence of relevant risk factors, including genetic contributions to disease risk. Precision medicine researchers have recognized the critical need to enhance diversity and have implemented a wide variety of approaches to achieve this.

Genetic testing has a multigenerational impact, as actionable pathogenic variants can identify multiple family members at risk. Currently in the United States, a person at actionable risk through genetic testing is responsible for contacting their own family members and communicating risk. However, incomplete or non-disclosure to relatives is prevalent, and up to a third of at-risk relatives who may have actionable genetic findings go un-notified.

From the passage of the country's first sterilization law in Indiana in 1907 until the 1960s approximately 60,000 people were sterilized based on eugenic criteria that sought to regulate the reproduction of the "unfit" and mentally deficient. California performed about 20,000, or one-third, of all documented sterilizations nationwide. Few empirical historical analyses of this practice are available. In 2007, while conducting historical research at the Department of Mental Health (now Department of State Hospitals) in Sacramento, Dr.

As genomic sequence data are being produced faster and at lower cost, the most significant challenge in clinical genetic testing today is variant classification. Currently, there are marked differences in variant classification among clinical laboratories, with clinically significant discrepancies in 29% of variants interpreted. Variants that were previously categorized as pathogenic are now known to be benign with the increasing availability of more ethnically diverse reference data, and this is issue is more common for individuals of non-European ancestry.

Candidate: Kayte Spector-Bagdady, JD, MBE, is an attorney and medical ethicist focused on the governance of secondary research use of human specimens and genetic data. Her long-term career goal is to become an independent investigator leading the development, conduct, and translation of mixed methods ethical, legal, and social implications research into improved genetic data-sharing governance. Research Context: “Precision medicine” and other advances in genetic research offer opportunities to improve diagnosis and therapy for millions of patients.

Stephanie Kraft, JD, is an Acting Instructor in the Division of Bioethics, Department of Pediatrics, University of Washington School of Medicine. She has a background in law and economics and has completed postdoctoral fellowships in bioethics at the Stanford Center for Biomedical Ethics and the Treuman Katz Center for Pediatric Bioethics at Seattle Children?s Hospital and Research Institute. Her prior work includes mixed methods studies related to informed consent and the ethical, legal, and social implications (ELSI) of genetics and genomics.

A large and highly heterogeneous group of individuals conducts genetic and genomic research outside of traditional corporate and academic settings. They can be an important source of innovation, but their activities largely take place beyond the purview of existing regulatory systems for promoting safe and ethical practices. Historically the gene-targeting technology available for non-traditional biology (NTB) experiments has been limited, and therefore they have attracted little regulatory attention.

The application of new computerized methods of data analysis to vast collections of medical, biological, and other data is emerging as a central feature of a broad vision of precision medicine (PM) in which systems based on artificial intelligence (AI) assist clinicians in treatment, diagnosis, or prognosis. The use of AI to analyze big data for clinical decision-making opens up a new domain for ELSI inquiry to address a possible future when the implications of genetics and genomics become embedded into algorithms, pervasive yet implicit and difficult to identify.

The proposed project is a qualitative study of recruitment and retention into the All of Us Research Program (AoURP) at a federally qualified health center (FQHC). A key component of the NIH's Precision Medicine Initiative, the AoURP is unprecedented in scope. AoURP will enroll over one million Americans in its cohort and ask for a 10+ year commitment to participation at sign-up.