Session Introduction: Overcoming health disparities in precision medicine.

The following sections are included:OverviewDealing with the lack of diversity in current research datasetsDevelopment of fair machine learning algorithmsRace, genetic ancestry, and population structureConclusionAcknowledgments.

Establishing a blockchain-enabled Indigenous data sovereignty framework for genomic data.

Technological advances have enabled the rapid generation of health and genomic data, though rarely do these technologies account for the values and priorities of marginalized communities. In this commentary, we conceptualize a blockchain genomics data framework built out of the concept of Indigenous Data Sovereignty.

Mid-pass whole genome sequencing enables biomedical genetic studies of diverse populations.

BACKGROUND: Historically, geneticists have relied on genotyping arrays and imputation to study human genetic variation. However, an underrepresentation of diverse populations has resulted in arrays that poorly capture global genetic variation, and a lack of reference panels. This has contributed to deepening global health disparities. Whole genome sequencing (WGS) better captures genetic variation but remains prohibitively expensive. Thus, we explored WGS at "mid-pass" 1-7x coverage. RESULTS: Here, we developed and benchmarked methods for mid-pass sequencing. When applied to a population without an existing genomic reference panel, 4x mid-pass performed consistently well across ethnicities, with high recall (98%) and precision (97.5%). CONCLUSION: Compared to array data imputed into 1000 Genomes, mid-pass performed better across all metrics and identified novel population-specific variants with potential disease relevance. We hope our work will reduce financial barriers for geneticists from underrepresented populations to characterize their genomes prior to biomedical genetic applications.

Diversity, Race, and Health.

The events of 2020 threw into stark relief the long-standing inequities in healthcare and the disproportionate toll they exert on communities of color. We asked physicians and scientists to share their experiences in confronting and tackling health disparities, and their Voices highlight the need for concerted and widespread action.

A framework for enhancing ethical genomic research with Indigenous communities.

Integration of genomic technology into healthcare settings establishes new capabilities to predict disease susceptibility and optimize treatment regimes. Yet, Indigenous peoples remain starkly underrepresented in genetic and clinical health research and are unlikely to benefit from such efforts. To foster collaboration with Indigenous communities, we propose six principles for ethical engagement in genomic research: understand existing regulations, foster collaboration, build cultural competency, improve research transparency, support capacity building, and disseminate research findings. Inclusion of underrepresented communities in genomic research has the potential to expand our understanding of genomic influences on health and improve clinical approaches for all populations.