Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
Nat Commun. 2022 Aug 30;13(1):5107. doi: 10.1038/s41467-022-32397-8.
The SARS-CoV-2 pandemic has differentially impacted populations across race and ethnicity. A multi-omic approach represents a powerful tool to examine risk across multi-ancestry genomes. We leverage a pandemic tracking strategy in which we sequence viral and host genomes and transcriptomes from nasopharyngeal swabs of 1049 individuals (736 SARS-CoV-2 positive and 313 SARS-CoV-2 negative) and integrate them with digital phenotypes from electronic health records from a diverse catchment area in Northern California. Genome-wide association disaggregated by admixture mapping reveals novel COVID-19-severity-associated regions containing previously reported markers of neurologic, pulmonary and viral disease susceptibility. Phylodynamic tracking of consensus viral genomes reveals no association with disease severity or inferred ancestry. Summary data from multiomic investigation reveals metagenomic and HLA associations with severe COVID-19. The wealth of data available from residual nasopharyngeal swabs in combination with clinical data abstracted automatically at scale highlights a powerful strategy for pandemic tracking, and reveals distinct epidemiologic, genetic, and biological associations for those at the highest risk.
SARS-CoV-2 大流行在不同种族和民族的人群中产生了不同的影响。多组学方法是一种强大的工具，可以在多祖先基因组中检查风险。我们利用一种大流行跟踪策略，从 1049 个人（736 例 SARS-CoV-2 阳性和 313 例 SARS-CoV-2 阴性）的鼻咽拭子中对病毒和宿主基因组及转录组进行测序，并将其与来自加利福尼亚州北部一个多样化集水区的电子健康记录中的数字表型进行整合。通过混合映射进行全基因组关联分解，揭示了与 COVID-19 严重程度相关的新区域，其中包含先前报道的神经、肺部和病毒疾病易感性的标记物。共识病毒基因组的系统发育追踪未发现与疾病严重程度或推断的祖源有关。多组学研究的汇总数据揭示了与严重 COVID-19 相关的宏基因组和 HLA 关联。从剩余的鼻咽拭子中获得的大量数据与大规模自动提取的临床数据相结合，突出了一种强大的大流行跟踪策略，并揭示了那些处于最高风险的人群的独特流行病学、遗传和生物学关联。
