Deconvoluting complex correlates of COVID-19 severity with a multi-omic pandemic tracking strategy
| Autor: | Victoria N. Parikh, Alexander G. Ioannidis, David Jimenez-Morales, John E. Gorzynski, Hannah N. De Jong, Xiran Liu, Jonasel Roque, Victoria P. Cepeda-Espinoza, Kazutoyo Osoegawa, Chris Hughes, Shirley C. Sutton, Nathan Youlton, Ruchi Joshi, David Amar, Yosuke Tanigawa, Douglas Russo, Justin Wong, Jessie T. Lauzon, Jacob Edelson, Daniel Mas Montserrat, Yongchan Kwon, Simone Rubinacci, Olivier Delaneau, Lorenzo Cappello, Jaehee Kim, Massa J. Shoura, Archana N. Raja, Nathaniel Watson, Nathan Hammond, Elizabeth Spiteri, Kalyan C. Mallempati, Gonzalo Montero-Martín, Jeffrey Christle, Jennifer Kim, Anna Kirillova, Kinya Seo, Yong Huang, Chunli Zhao, Sonia Moreno-Grau, Steven G. Hershman, Karen P. Dalton, Jimmy Zhen, Jack Kamm, Karan D. Bhatt, Alina Isakova, Maurizio Morri, Thanmayi Ranganath, Catherine A. Blish, Angela J. Rogers, Kari Nadeau, Samuel Yang, Andra Blomkalns, Ruth O’Hara, Norma F. Neff, Christopher DeBoever, Sándor Szalma, Matthew T. Wheeler, Christian M. Gates, Kyle Farh, Gary P. Schroth, Phil Febbo, Francis deSouza, Omar E. Cornejo, Marcelo Fernandez-Vina, Amy Kistler, Julia A. Palacios, Benjamin A. Pinsky, Carlos D. Bustamante, Manuel A. Rivas, Euan A. Ashley |
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| Rok vydání: | 2021 |
| Předmět: |
Genome
Multidisciplinary SARS-CoV-2 Prevention Human Genome General Physics and Astronomy COVID-19 General Chemistry Genome Viral General Biochemistry Genetics and Molecular Biology Infectious Diseases Good Health and Well Being Clinical Research Pneumonia & Influenza Genetics Humans Viral Infection Lung Pandemics Genome-Wide Association Study |
| Zdroj: | Nature communications, vol 13, iss 1 |
| ISSN: | 2041-1723 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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