Equity, ethics and the promise of partnership in genomic medicine

IF 31.7 1区 生物学 Q1 GENETICS & HEREDITY Nature genetics Pub Date : 2025-03-10 DOI:10.1038/s41588-025-02131-3
Nicola L. Hawley, Satupaitea Viali
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引用次数: 0

Abstract

A recent New York Times article1 highlights a pivotal moment for genetic research: a first revenue-sharing agreement between a biotech company, Variant Bio, and the communities with whom they partner to collect genomic data. Their attempt to address the systemic inequities and historical exploitation that has characterized genomic science raises important questions about how the field can responsibly and feasibly build on this first step.

Although underrepresented in genetic research, data from Indigenous and minoritized communities have propelled several important scientific discoveries2,3. However, these contributions have been historically characterized by a lack of informed consent, exclusion from decision-making, and inequitable distribution of benefits. Variant Bio aims to address this through community engagement, allocating up to 10% of project budgets to community programs and sharing 4% of their annual revenue, as well as seeking to make resulting medications affordable for these communities.

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来源期刊
Nature genetics
Nature genetics 生物-遗传学
CiteScore
43.00
自引率
2.60%
发文量
241
审稿时长
3 months
期刊介绍: Nature Genetics publishes the very highest quality research in genetics. It encompasses genetic and functional genomic studies on human and plant traits and on other model organisms. Current emphasis is on the genetic basis for common and complex diseases and on the functional mechanism, architecture and evolution of gene networks, studied by experimental perturbation. Integrative genetic topics comprise, but are not limited to: -Genes in the pathology of human disease -Molecular analysis of simple and complex genetic traits -Cancer genetics -Agricultural genomics -Developmental genetics -Regulatory variation in gene expression -Strategies and technologies for extracting function from genomic data -Pharmacological genomics -Genome evolution
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