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Potential risks and solutions for sharing genome summary data from African populations.

Nicki Tiffin1,2,3

  • 1Computational Biology Division, Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa. nicki.tiffin@uct.ac.za.

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|November 6, 2019
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Summary

Genomic data from African populations can advance global research but risks harm. Revisions to open-access policies are needed to protect these vulnerable groups from re-identification and discrimination.

Keywords:
African diversityAfrican genomesCommunity harmsGenome summary results

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Area of Science:

  • Genomics
  • Bioethics
  • Population Health

Background:

  • Open access to aggregated genomic data from African populations can aid global genetic research but poses risks of community-level harms.
  • Recent National Institutes of Health (NIH) policy mandates open internet access to genomic summary results, with exemptions for sensitive populations.
  • African populations possess a diverse genomic landscape, increasing the risk of re-identification through genomic profiles and summary data.

Purpose of the Study:

  • To highlight the potential community harms to African populations due to unregulated online exposure of their genome summary data.
  • To advocate for the exemption of all African populations as sensitive or vulnerable groups under current NIH open-access policies.
  • To propose risk-mitigating mechanisms for sharing African genomic data in global health research.

Main Methods:

  • Analysis of the implications of current NIH open-access policies on African populations.
  • Identification of specific vulnerabilities of African populations, including genomic identifiability, healthcare access, socioeconomic challenges, and ethnic discrimination.
  • Proposal of three risk-mitigating mechanisms for sharing genomic data.

Main Results:

  • African populations are uniquely identifiable through their genomic profiles, posing risks of re-identification and associated harms.
  • Current NIH policy may inadvertently cause community-level harm to African populations due to the lack of access oversight.
  • Three risk-mitigating strategies are proposed: Beacon Protocol, African Genome Variation Database, and regional data aggregation.

Conclusions:

  • The NIH should recognize the potential for community harms and exempt African populations from unregulated online exposure of genome summary data.
  • Implementing the Beacon Protocol, African Genome Variation Database, and regional data aggregation can facilitate responsible sharing of African genomic data.
  • Protecting African populations from re-identification and discrimination is crucial while advancing global genomic health research.