Highlights
Aspiring toward equitable benefits from genomic advances to individuals of ancestrally diverse backgrounds
From the abstract: "Despite the promise of genomic technologies, their full potential remains untapped without including individuals of diverse ancestries and integrating social determinants of health (SDOHs). The NHGRI launched the 2020 Strategic Vision with ten bold predictions by 2030, including “individuals from ancestrally diverse backgrounds will benefit equitably from advances in human genomics." Meeting this goal requires a holistic approach that brings together genomic advancements with careful consideration to healthcare access as well as SDOHs to ensure that translation of genetics research is inclusive, affordable, and accessible and ultimately narrows rather than widens health disparities. "
Genetic Researchers' Use of and Interest in Research With Diverse Ancestral Groups.
From the article: " Question: Are genetic researchers interested in research with diverse ancestral groups, and how can data stewards encourage that use?
Findings: In this survey study of 294 genetic researchers, significantly more respondents reported working with data from European ancestral populations than any other ancestral population, and European samples were more likely to be considered by researchers as adequate across data-steward type. Most researchers were interested in using more diverse ancestral populations and reported that increasing ancestral diversity of existing databases would enable such research. Meaning: These findings suggest that there are specific gaps in access to and composition of genetic databases, underscoring the need to boost diversity in existing research samples to improve inclusivity in genetic research practices."
Overcoming barriers to single-cell RNA sequencing adoption in low- and middle-income countries
TB Serebour et al, EJHG, April 2, 2024
From the abstract: " The advent of single-cell resolution sequencing and spatial transcriptomics has enabled the delivery of cellular and molecular atlases of tissues and organs, providing new insights into tissue health and disease. However, if the full potential of these technologies is to be equitably realised, ancestrally inclusivity is paramount. Such a goal requires greater inclusion of both researchers and donors in low- and middle-income countries (LMICs). In this perspective, we describe the current landscape of ancestral inclusivity in genomic and single-cell transcriptomic studies. We discuss the collaborative efforts needed to scale the barriers to establishing, expanding, and adopting single-cell sequencing research in LMICs."
Utilizing geospatial artificial intelligence to map cancer disparities across health regions
A Fadiel et al, Sci Report, April 2, 2024
From the abstract: "We have developed an innovative tool, the Intelligent Catchment Analysis Tool (iCAT), designed to identify and address healthcare disparities across specific regions. Powered by Artificial Intelligence and Machine Learning, our tool employs a robust Geographic Information System (GIS) to map healthcare outcomes and disease disparities. iCAT allows users to query publicly available data sources, health system data, and treatment data, offering insights into gaps and disparities in diagnosis and treatment paradigms. "
