| Autor: |
Kinya Seo, Jennifer Kim, Douglas Russo, David Jimenez-Morales, Lorenzo Cappello, Nathaniel Watson, Manuel A. Rivas, Archana Raja, Nathan Hammond, Marcelo Fernandez-Vina, Francis deSouza, Nathan Youlton, Steven G. Hershman, Kazutoyo Osoegawa, Olivier Delaneau, Shirley Sutton, Jessie T. Lauzon, Andra L. Blomkalns, Ruth O'Hara, Yongchan Kwon, Amy Kistler, Victoria N. Parikh, Yong Huang, Carlos Bustamante, Matthew T. Wheeler, Elizabeth Spiteri, Benjamin A. Pinsky, Jonasel Roque, Simone Rubinacci, Massa J. Shoura, Thanmayi Ranganath, Samuel Yang, John E. Gorzynski, Alina Isakova, Gary P. Schroth, Kyle Kai-How Farh, Yosuke Tanigawa, Ruchi Joshi, Hannah N. De Jong, Kalyan C. Mallempati, Catherine A. Blish, Christopher R. Hughes, Norma Neff, Justin Wong, Karan D. Bhatt, Sándor Szalma, Julia A. Palacios, Jimmy Zhen, Jack Kamm, Alexander G. Ioannidis, Anna Kirillova, Xiran Liu, Gonzalo Montero-Martín, Angela J. Rogers, Jeffrey W. Christle, David Amar, Maurizio Morri, Karen P. Dalton, Phil Febbo, Jaehee Kim, Victoria P. Cepeda-Espinoza, Sonia Moreno-Grau, Chunli Zhao, Christopher DeBoever, Euan A. Ashley, Kari C. Nadeau, Jacob Edelson, Daniel Mas Montserrat |
| Rok vydání: |
2021 |
| Předmět: |
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| Popis: |
The SARS-CoV-2 pandemic has differentially impacted populations of varied race, ethnicity and socioeconomic status. Admixture mapping and local ancestry inference represent powerful tools to examine genetic risk within multi-ancestry genomes independent of these confounding social constructs. Here, we leverage a pandemic tracking strategy in which we sequence viral and host genomes and transcriptomes from 1,327 nasopharyngeal swab residuals and integrate them with digital phenotypes from electronic health records. We demonstrate over-representation of individuals possessing Oceanian and Indigenous American ancestry in SARS-CoV-2 positive populations. Genome-wide-association disaggregated by admixture mapping reveals regions of chromosomes 5 and 14 associated with COVID19 severity within African and Oceanic local ancestries, respectively, independent of overall ancestry fraction. Phylodynamic tracking of consensus viral genomes reveals no association with disease severity or inferred ancestry. We further present summary data from a multi-omic investigation of human-leukocyte-antigen (HLA) typing, nasopharyngeal microbiome and human transcriptomics that reveal metagenomic and HLA associations with severe COVID19 infection. This work demonstrates the power of multi-omic pandemic tracking and genomic analyses to reveal distinct epidemiologic, genetic and biological associations for those at the highest risk. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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