The Illusion of Inclusion — The “All of Us” Research Program and Indigenous Peoples’ DNA

Posted in Articles, Health/Medicine/Genetics, Media Archive, Native Americans/First Nation, United States on 2020-09-13 02:16Z by Steven

The Illusion of Inclusion — The “All of Us” Research Program and Indigenous Peoples’ DNA

The New England Journal of Medicine
Issue 383 (2020-07-30)
pages 411-413
DOI: 10.1056/NEJMp1915987

Keolu Fox, Ph.D.
University of California, San Diego

Raw data, including digital sequence information derived from human genomes, have in recent years emerged as a top global commodity. This shift is so new that experts are still evaluating what such information is worth in a global market. In 2018, the direct-to-consumer genetic-testing company 23andMe sold access to its database containing digital sequence information from approximately 5 million people to GlaxoSmithKline for $300 million. Earlier this year, 23andMe partnered with Almirall, a Spanish drug company that is using the information to develop a new antiinflammatory drug for autoimmune disorders. This move marks the first time that 23andMe has signed a deal to license a drug for development.

Eighty-eight percent of people included in large-scale studies of human genetic variation are of European ancestry, as are the majority of participants in clinical trials.1 Corporations such as Geisinger Health System, Regeneron Pharmaceuticals, AncestryDNA, and 23andMe have already mined genomic databases for the strongest genotype–phenotype associations. For the field to advance, a new approach is needed. There are many potential ways to improve existing databases, including “deep phenotyping,” which involves collecting precise measurements from blood panels, questionnaires, cognitive surveys, and other tests administered to research participants. But this approach is costly and physiologically and mentally burdensome for participants. Another approach is to expand existing biobanks by adding genetic information from populations whose genomes have not yet been sequenced — information that may offer opportunities for discovering globally rare but locally common population-specific variants, which could be useful for identifying new potential drug targets.

Many Indigenous populations have been geographically isolated for tens of thousands of years. Over time, these populations have developed adaptations to their environments that have left specific variant signatures in their genomes. As a result, the genomes of Indigenous peoples are a treasure trove of unexplored variation. Some of this variation will inevitably be identified by programs like the National Institutes of Health (NIH) “All of Us” research program. NIH leaders have committed to the idea that at least 50% of this program’s participants should be members of underrepresented minority populations, including U.S. Indigenous communities (Native Americans, Alaskan Natives, and Native Hawaiians), a decision that explicitly connects diversity with the program’s goal of promoting equal enjoyment of the future benefits of precision medicine.

But there are reasons to believe that this promise may be an illusion. Previous government-funded, large-scale human genome sequencing efforts, such as the Human Genome Diversity Project, the International HapMap Project, and the 1000 Genomes Project, provide examples of the ways in which open-source data have been commodified in the past. These initiatives, which promised unrestricted, open access to data on population-specific biomarkers, ultimately enabled the generation of nearly a billion dollars’ worth of profits by pharmaceutical and ancestry-testing companies. If the All of Us program uses the same unrestricted data-access and sharing protocols, there will be no built-in mechanisms to protect against the commodification of Indigenous peoples’ DNA…

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Will Precision Medicine Move Us beyond Race?

Posted in Articles, Health/Medicine/Genetics, Media Archive on 2016-07-05 18:27Z by Steven

Will Precision Medicine Move Us beyond Race?

The New England Journal of Medicine
2016-05-26 (Volume 374, Number 21)
DOI: 10.1056/NEJMp1511294

Vence L. Bonham, J.D., Senior Advisor to the NHGRI Director on Genomics and Health Disparities
National Human Genome Research Institute, Bethesda, Maryland

Shawneequa L. Callier, J.D., Professorial Lecturer in Law
Georgetown University, Washington, D.C.

Charmaine D. Royal, Ph.D., Associate Professor of African and African American Studies and Genome Sciences
Duke University, Durham, North Carolina

Although self-identified race may correlate with geographical ancestry, it does not predict an individual patient’s genotype or drug response. Precision medicine may eventually replace the use of race in treatment decisions, but several hurdles will have to be overcome.

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Self-Reported Race and Genetic Admixture

Posted in Articles, Health/Medicine/Genetics, Media Archive, United States on 2011-12-09 03:44Z by Steven

Self-Reported Race and Genetic Admixture

The New England Journal of Medicine
Number 354, Number 4 (2006-01-26)
pages 431-422
DOI: 10.1056/NEJMc052515

Moumita Sinha, M.Stat.
Case Western Reserve University, Cleveland, Ohio

Emma K. Larkin, M.H.S.
Case Western Reserve University, Cleveland, Ohio

Robert C. Elston, Ph.D.
Case Western Reserve University, Cleveland, Ohio

Susan Redline, M.D., M.P.H.
Case Western Reserve University, Cleveland, Ohio

To the Editor:

The use of data on self-reported race in health research has been highly debated. For example, Burchard et al. recently argued that important information on disease susceptibility may be derived from the use of data on self-reported race, whereas Cooper et al. cited Wilson et al., who argued that ethnic labels “are inaccurate representations of the inferred genetic clusters.” Cooper et al., however, ignored later work that identified limitations in the analyses of Wilson et al. — specifically, inappropriate classification of groups, the use of a suboptimal model for cluster identification, and reliance on only 39 microsatellite markers for cluster analyses. With larger numbers of markers, it was shown that genetically distinct groups can be almost completely inferred from self-reported race…

…With support from a U.S. Public Health Service grant, we applied an admixture analysis to a sample population in Cleveland. Participants were clearly separated into unique groups with the use of this genetic approach. Whereas 93 percent of self-reported whites were classified as having predominantly European ancestry, less than 2 percent of blacks were so classified. Only 4 percent who reported their race as black had predominantly African ancestry; yet, the admixture proportions of this group made it possible to separate the population into two groups, in which 94 percent of self-reported blacks and 7 percent of self-reported whites were classified as being of mixed race (Figure 1: Frequency Histogram Showing the Percentage of African Ancestry in a Population Living in Cleveland). The sharp peak at the left in Figure 1 indicates that there are many persons who have no African ancestry (i.e., the values correspond to those of self-reported whites), and the broad peak at the right indicates that most blacks are of mixed race and do not originate from any single population. Thus, self-reported race and genetic ethnic ancestry appear to be highly correlated as a dichotomy, with those who self-report as being black comprising, as expected from historical and cultural practices in the United States, a broad range of African ancestry…

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