Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA; University of Maryland Institute for Health Computing, University of Maryland School of Medicine, North Bethesda, MD 20852, USA.
Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
Cell Genom. 2024 Nov 13;4(11):100692. doi: 10.1016/j.xgen.2024.100692. Epub 2024 Oct 31.
Latin Americans are underrepresented in genetic studies, increasing disparities in personalized genomic medicine. Despite available genetic data from thousands of Latin Americans, accessing and navigating the bureaucratic hurdles for consent or access remains challenging. To address this, we introduce the Genetics of Latin American Diversity (GLAD) Project, compiling genome-wide information from 53,738 Latin Americans across 39 studies representing 46 geographical regions. Through GLAD, we identified heterogeneous ancestry composition and recent gene flow across the Americas. Additionally, we developed GLAD-match, a simulated annealing-based algorithm, to match the genetic background of external samples to our database, sharing summary statistics (i.e., allele and haplotype frequencies) without transferring individual-level genotypes. Finally, we demonstrate the potential of GLAD as a critical resource for evaluating statistical genetic software in the presence of admixture. By providing this resource, we promote genomic research in Latin Americans and contribute to the promises of personalized medicine to more people.
拉丁美洲人在基因研究中代表性不足,这加剧了个性化基因组医学中的差异。尽管有来自数千名拉丁美洲人的可用遗传数据,但获取和克服同意或访问的官僚障碍仍然具有挑战性。为了解决这个问题,我们引入了拉丁美洲多样性的遗传学(GLAD)项目,该项目从 39 项研究中的 53738 名拉丁美洲人那里收集了全基因组信息,这些研究代表了 46 个地理区域。通过 GLAD,我们确定了美洲各地不同的祖先组成和最近的基因流动。此外,我们开发了基于模拟退火的 GLAD-match 算法,将外部样本的遗传背景与我们的数据库进行匹配,共享汇总统计数据(即等位基因和单倍型频率),而不传输个体水平的基因型。最后,我们展示了 GLAD 作为在混合存在的情况下评估统计遗传软件的重要资源的潜力。通过提供这个资源,我们促进了拉丁美洲人的基因组研究,并为更多人实现个性化医学的承诺做出了贡献。