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The ethical challenges of diversifying genomic data: A qualitative evidence synthesis.

Faranak HardcastleKate LyleRachel Helen HortonGabrielle SamuelSusie WellerLisa BallardRachel ThompsonLuiz Valerio De Paula TrindadeJosé David Gómez UrregoDaniel KochinTess JohnsonNechama Tatz-WiederElizabeth Redrup HillFlorence Robinson AdamsYoseph EskandarEli HarrissKrystal S TsosiePadraig DixonMaxine MackintoshLyra NightingaleAnneke M Lucassen
Published in: Cambridge prisms. Precision medicine (2023)
This article aims to explore the ethical issues arising from attempts to diversify genomic data and include individuals from underserved groups in studies exploring the relationship between genomics and health. We employed a qualitative synthesis design, combining data from three sources: 1) a rapid review of empirical articles published between 2000 and 2022 with a primary or secondary focus on diversifying genomic data, or the inclusion of underserved groups and ethical issues arising from this, 2) an expert workshop and 3) a narrative review. Using these three sources we found that ethical issues are interconnected across structural factors and research practices. Structural issues include failing to engage with the politics of knowledge production, existing inequities, and their effects on how harms and benefits of genomics are distributed. Issues related to research practices include a lack of reflexivity, exploitative dynamics and the failure to prioritise meaningful co-production. Ethical issues arise from both the structure and the practice of research, which can inhibit researcher and participant opportunities to diversify data in an ethical way. Diverse data are not ethical in and of themselves, and without being attentive to the social, historical and political contexts that shape the lives of potential participants, endeavours to diversify genomic data run the risk of worsening existing inequities. Efforts to construct more representative genomic datasets need to develop ethical approaches that are situated within wider attempts to make the enterprise of genomics more equitable.
Keyphrases
  • electronic health record
  • healthcare
  • big data
  • decision making
  • copy number
  • single cell
  • public health
  • systematic review
  • risk assessment
  • dna methylation
  • artificial intelligence
  • social media
  • deep learning
  • quantum dots