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Key Considerations for Indigenous Participation in a Hereditary Cancer Genomic Variant Commons

By: Janis Geary, PhD

 

The rights and interests of tribal nations and Indigenous peoples require specific attention to ensure their inclusion. Here, we draw on a literature review and interviews with experts to summarize some of the key considerations (see Appendix 1 for more details).

The current under-representation of Indigenous groups in genomic variant databases could exacerbate inequities in hereditary cancer. Indigenous people already have less access to medical care, and therefore lower access to genetic tests and cancer care (1,2). Those who get genetic testing are more likely to receive inconclusive genetic risk assessments (3). Efforts to include Indigenous genomes in data initiatives are accused of exploiting Central and Southern American Indigenous population genetics, and selling data to commercial entities to offer popular genetic tests for “blood quantum” of indigeneity (4). Indigenous people who wish to obtain hereditary cancer testing may question how their data will be used and if it will have commercial uses that their group members disapprove of, or from which they will never receive benefits.

Indigenous populations share some challenges in participating in genomics with other small populations. There is no doubt that in order for Indigenous populations to receive benefits from advances in hereditary cancer genetics, there has to be some sort of data compilation to support assessing clinical significance of gene variants in the population. Without representation in a robust reference library, Indigenous peoples seeking assessment for hereditary cancer risks will receive inconclusive test results more often. Yet, compiling data from individuals from small populations adds additional risks to individuals’ privacy, as less information is needed to render an individual potentially identifiable.

Indigenous peoples often want to participate in scientific advancement, but they do not trust research institutions. The history (and ongoing reality) of medicine and research exploiting Indigenous peoples in the US and globally is a necessary lens to view all challenges related to hereditary cancer testing and data sharing (5–11). See Appendix 2 for more examples. Researchers have left Indigenous communities feeling used (either from simply disappearing with data or returning with results that fail to fulfill promises made), and in some cases have conducted research without the informed consent of the communities and participants (12).

BOX 1: SING

The Summer Internship for Indigenous Genomics began in the US in 2011, and has since grown into an international consortium.

The consortium has a goal to increase Indigenous representation in genomics and other sciences, and members have published guidelines for Indigenous genomics.

https://www.singconsortium.org/

 

Some practices exacerbate existing distrust. Indigenous peoples globally have successfully advocated for greater rights and control over research about them (13), but harmful practices persist. Indigenous scholars have warned about research approaches that appear to attempt to access Indigenous participants without the approval of Indigenous governments. One example is recruiting individual Indigenous participants directly rather than through tribal nations (14). Similarly, distrust is exacerbated by patient consent processes founded on non-Indigenous conceptualizations of individual consent, which ignore concepts of community consent (15).

 

Nonetheless, there have been many examples of forming trusting relationships that support Indigenous research. These relationships often rely on specific individuals being deemed “trustworthy,” ideally in the context of institutional structures that support Indigenous research requirements [Box 1] (16). Building trust between institutions and tribal nations or other Indigenous authorities will require acceptance of self-governance, communication, transparency, and accountability. See Appendix 3 for more examples.

Tribal nations and Indigenous peoples need to govern their own data. Indigenous peoples in the US are different from other marginalized populations because many belong to tribal nations that have their own governmental institutions and laws, including those for protecting health and genomic information (17). In addition to legally-enshrined rights, it is simply unacceptable to many Indigenous groups that data derived from their members be obtained, stored, or disseminated without the direct control of a recognized authority from that specific Indigenous group (18).

Despite the fact that many Indigenous groups have sovereign rights over data from their members, many remain reliant on non-Indigenous institutions, infrastructure, and resources if they want their members to benefit from advances in genomics technology. Successful partnerships are built with community consent, in addition to individual consent, and provide the resources for infrastructure development that enable tribal authorities to generate, manage, and govern data from their members. However, Indigenous peoples living in the US may not belong to a tribal nation, leaving questions about which authority or community representatives to engage for data governance. In cases where there is no specific authority, community advisory boards can help ensure accountability and enforce rules for the use of Indigenous data.

Respecting self-governance entails a willingness to modify Western conceptualizations of ownership and individual rights and privacy. Many Indigenous groups believe genomic information belongs to the group and not individuals (19), or question the idea that an individual could transfer ownership of their personal information. Conversations on privacy typically focus on an individual’s privacy and neglect Indigenous concepts of community privacy or group consent (15). Any effort to engage Indigenous participants in a genomic data commons must be genuine in its willingness to incorporate Indigenous worldviews into governance and not just Indigenous data into databases.

 

BOX 2: Silent Genomes

This project is using an Indigenous lens to develop governance of genomic data, and create an Indigenous background variant library to help reduce barriers to diagnosis of genetic diseases in Indigenous children.

https://www.bcchr.ca/silent-genomes-project

Effective communication is key to building relationships between Indigenous peoples, their governments or representatives, and any data compilation initiative. But this communication must be bi-directional, aimed at educating about hereditary cancer in general, providing transparent information about the goals and processes of compiling hereditary cancer genomic variant data, and receiving information about community data governance concerns and needs. Any group or organization responsible for communication must have a channel to ensure accountability, as communication without action will be perceived as token and will erode trust.

 

Despite all of the challenges, there are opportunities to achieve significant benefits, and examples of successful collaborations exist [Box 2] (20). See Appendix 4 for more examples. Through participation—on their own terms—in a robust hereditary cancer genomic variant commons, Indigenous peoples may experience better clinical assessment of rare variants not found in other population groups. Tribal authorities could use genomics data to advocate for resources in their communities. Groups could leverage partnerships to develop infrastructure in their own communities under their own control (21).

 

REFERENCES

1.         Frerichs L, Bell R, Lich KH, Reuland D, Warne DK. Health insurance coverage among American Indians and Alaska Natives in the context of the Affordable Care Act. Ethn Health. 2019 Jun 10;0(0):1–16.

2.         Guadagnolo BA, Petereit DG, Coleman CN. Cancer Care Access and Outcomes for American Indian Populations in the United States: Challenges and Models for Progress. Semin Radiat Oncol. 2017 Apr 1;27(2):143–9.

3.         Hall MJ, Reid JE, Burbidge LA, Pruss D, Deffenbaugh AM, Frye C, et al. BRCA1 and BRCA2 mutations in women of different ethnicities undergoing testing for hereditary breast-ovarian cancer. Cancer. 2009;115(10):2222–33.

4.         Tsosie K, Anderson M. Two Native American geneticists interpret Elizabeth Warren’s DNA test [Internet]. The Conversation. [cited 2020 May 22]. Available from: http://theconversation.com/two-native-american-geneticists-interpret-elizabeth-warrens-dna-test-105274

5.         After Havasupai litigation, Native Americans wary of genetic research. Am J Med Genet A. 2010;152A(7):fm ix–fm ix.

6.         Stokstad E. Genetics lab accused of misusing African DNA. Science. 2019 Nov 1;366(6465):555–6.

7.         Bowekaty MB, Davis DS. Cultural Issues in Genetic Research with American Indian and Alaskan Native People. IRB Ethics Hum Res. 2003;25(4):12–5.

8.         Schnarch B. Ownership, Control, Access, and Possession (OCAP) or Self-Determination Applied to Research: A Critical Analysis of Contemporary First Nations Research and Some Options for First Nations  Communities. J Aborig Health. 2004 Jan;80–95.

9.         Smith PLT. Decolonizing Methodologies: Research and Indigenous Peoples. Zed Books Ltd.; 2013. 255 p.

10.       Beans JA, Saunkeah B, Brian Woodbury R, Ketchum TS, Spicer PG, Hiratsuka VY. Community Protections in American Indian and Alaska Native Participatory Research—A Scoping Review. Soc Sci Basel Switz [Internet]. 2019 Apr [cited 2020 May 14];8(4). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6713452/

11.       Valeggia CR, Snodgrass JJ. Health of Indigenous Peoples. Annu Rev Anthropol. 2015;44(1):117–35.

12.       Mello MM, Wolf LE. The Havasupai Indian Tribe Case — Lessons for Research Involving Stored Biologic Samples. N Engl J Med. 2010;363(3):204–7.

13.       Garrison NA, Hudson M, Ballantyne LL, Garba I, Martinez A, Taualii M, et al. Genomic Research Through an Indigenous Lens: Understanding the Expectations. Annu Rev Genomics Hum Genet. 2019;20(1):null.

14.       KaiserMay. 29 J, 2019, Pm 1:40. Million-person U.S. study of genes and health stumbles over including Native American groups [Internet]. Science | AAAS. 2019 [cited 2020 May 23]. Available from: https://www.sciencemag.org/news/2019/05/million-person-us-study-genes-and-health-stumbles-over-including-native-american-groups

15.       Tsosie KS, Yracheta JM, Dickenson D. Overvaluing individual consent ignores risks to tribal participants. Nat Rev Genet. 2019 Sep;20(9):497–8.

16.       Claw KG, Anderson MZ, Begay RL, Tsosie KS, Fox K, Garrison NA. A framework for enhancing ethical genomic research with Indigenous communities. Nat Commun. 2018 Jul 27;9(1):1–7.

17.       Harding Anna, Harper Barbara, Stone Dave, O’Neill Catherine, Berger Patricia, Harris Stuart, et al. Conducting Research with Tribal Communities: Sovereignty, Ethics, and Data-Sharing Issues. Environ Health Perspect. 2012 Jan 1;120(1):6–10.

18.       Research Data Alliance International Indigenous Data Sovereignty Interest Group. CARE Principles for Indigenous Data Governance. The Global Indigenous Data Alliance [Internet]. 2019. Available from: GIDA-global.org

19.       Tsosie R. Cultural Challenges to Biotechnology: Native American Genetic Resources and the Concept of Cultural Harm. J Law Med Ethics. 2007 Aug 1;35(3):396–411.

20.       Caron NR, Chongo M, Hudson M, Arbour L, Wasserman WW, Robertson S, et al. Indigenous Genomic Databases: Pragmatic Considerations and Cultural Contexts. Front Public Health [Internet]. 2020 Apr 24 [cited 2020 May 23];8. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7193324/

21.       BRAICELET [Internet]. SPHERE. [cited 2020 May 23]. Available from: http://med.stanford.edu/sphere/research-intiatives/braicelet.html

 

 

Appendix 1: Methods and mapping themes

I analysed transcripts of Sulston Project interviews to identify content relevant to Indigenous participation in a hereditary cancer genomic variant commons, and pulled themes from published literature and other resources on Indigenous genomics (sources identified from expert advice, literature searches, and snowball sampling).

 

I used RQDA (a qualitative analysis tool developed in R) to identify concepts and group them into themes. I used the network feature to display the relationship between key concepts and drawing tools to emphasize topic-overlap among themes (see below).

 

 

 

 

Appendix 2: Examples of research and initiatives that have harmed Indigenous peoples directly or contributed to distrust of researchers

 

Appendix 3: Examples of policies and guidelines that support Indigenous peoples in genomics

 

Appendix 4: Examples of research and initiatives that are led or driven by Indigenous peoples