When the Human Genome Project was completed almost ten years ago it cost millions of dollars to sequence an individual's genome. Yet, the evolution of high-throughput sequencing and computational tools has been swift and it will soon be possible to genotype anyone for a nominal price. The ability to generate genomic data coincides with the adoption of electronic health records, setting the stage for large-scale personalized medicine research, the results of which can improve the efficiency, effectiveness, and safety of healthcare delivery.

A big data ecosystem is evolving in our society in which people may have, or feel they have, little control over the flow of their personal health information, and thus their privacy. Further, although there has been significant discussion related to big data and privacy at the highest levels of government, there is little consensus among scholars and stakeholders as to what privacy actually is, not to mention a lack of data from individuals as to personal conceptions of privacy.

American Indian and Alaska Native concerns about genomic research have, in a very real sense, been foundational in ethical, legal, and social implications scholarship. Sadly, many of these issues remain unresolved. Concerns about the protection of samples and data continue to engage many tribal communities, as do problems with the actual and potential abuse of genetic information. At the same time, many tribes are creating new relationships between science and society, especially in tribal research offices that are increasingly common.

Precision medicine is an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person. The Precision Medicine Initiative (PMI) was recently launched by the NIH to accelerate the pace of discovery. Though initially focused on cancer, the PMI will eventually generate knowledge applicable to a range of diseases, including infectious diseases.

Living donor kidney transplantation (LDKT) is promoted to redress the shortage of kidneys for transplantation. However, studies show that living donors (LDs) have a greater risk of kidney failure than healthy non-LDs post-donation.4-6 Moreover, African American (AA) LDs have an even greater risk of kidney failure post-donation than European American (EA) LDs.4,5 These findings have generated heightened concerns in the transplant community over protecting LDs' safety and improving LDs' informed consent.7-14 Genetics may help explain this disparity.

Family history is an essential predictor of disease risk, yet it is often incomplete, inaccurate, and underutilized in today's clinical settings. With the increasingly widespread adoption of electronic medical records (EMRs), many individuals are born today into a health system in which many of their family members have substantial longitudinal EMRs. These records present a vast untapped resource for deriving Data-Driven Family Histories - family histories constructed directly from the EMRs of patients' family members.

Individual institutions across the country have worked to support research in a wide variety of areas, including precision medicine research, by developing large biorepositories comprised of biospecimens and health data collected from local patients and controls. However, these local cohorts rarely provide the diversity and size needed to identify and study subsets of patients who share biological mechanisms for their disease, and are thus more likely to respond to the same targeted therapies.

The emergence of genomic medicine has not been without unique concerns that continue to challenge clinicians working in this arena. Genomic test results have implications for individuals other than the person tested. Related to this, interpretation of genomic data often requires several related individuals; and even then what can be known about the meaning of an individual's specific variants is, and will continue to be, a function of big data analysis of the genomic data of many thousands (or even millions) of individuals.

The advent of clinical genome sequencing to identify patients at risk for serious diseases and to tailor treatments promises to greatly improve health outcomes and provide a foundation for the delivery of Precision Medicine. However, even as laboratory methods to perform sequencing become highly efficient, uncertainty around the optimal breadth and economic value of sequencing as well as ambiguity around which individuals should be tested presents a critical barrier to wider use.

The overall goal of the proposed research is to advance policy approaches to support Precision Medicine research (PMR) with American Indian and Alaska Native (AIAN) people through culturally respectful dialogue, empiric data collection, and deliberation with rural and urban AIAN community members and tribal representatives in Alaska and Montana.