Corpas Manuel, Pius Mkpouto, Poburennaya Marie, Guio Heinner, Dwek Miriam, Nagaraj Shivashankar, Lopez-Correa Catalina, Popejoy Alice, Fatumo Segun
Life Sciences, University of Westminster, 115 New Cavendish Street, W1W 6UW London, UK; The Alan Turing Institute, London, UK; Cambridge Precision Medicine Ltd., ideaSpace, University of Cambridge Biomedical Innovation Hub, Cambridge, UK.
Life Sciences, University of Westminster, 115 New Cavendish Street, W1W 6UW London, UK.
Cell Genom. 2025 Jan 8;5(1):100724. doi: 10.1016/j.xgen.2024.100724. Epub 2024 Dec 17.
Achieving diverse representation in biomedical data is critical for healthcare equity. Failure to do so perpetuates health disparities and exacerbates biases that may harm patients with underrepresented ancestral backgrounds. We present a quantitative assessment of representation in datasets used across human genomics, including genome-wide association studies (GWASs), pharmacogenomics, clinical trials, and direct-to-consumer (DTC) genetic testing. We suggest that relative proportions of ancestries represented in datasets, compared to the global census population, provide insufficient representation of global ancestral genetic diversity. Some populations have greater proportional representation in data relative to their population size and the genomic diversity present in their ancestral haplotypes. As insights from genomics become increasingly integrated into evidence-based medicine, strategic inclusion and effective mechanisms to ensure representation of global genomic diversity in datasets are imperative.
在生物医学数据中实现多样化的代表性对于医疗公平至关重要。若做不到这一点，健康差距将持续存在，可能伤害祖先背景代表性不足的患者的偏见也会加剧。我们对人类基因组学中使用的数据集的代表性进行了定量评估，这些数据集包括全基因组关联研究（GWAS）、药物基因组学、临床试验和直接面向消费者（DTC）的基因检测。我们认为，与全球人口普查数据相比，数据集中所代表的各祖先群体的相对比例，无法充分体现全球祖先遗传多样性。相对于其人口规模及其祖先单倍型中存在的基因组多样性，一些群体在数据中的比例代表性更高。随着基因组学的见解越来越多地融入循证医学，确保数据集中全球基因组多样性代表性的战略纳入和有效机制势在必行。
