Your browser doesn't support javascript.
Deconvoluting complex correlates of COVID-19 severity with a multi-omic pandemic tracking strategy.
Parikh, Victoria N; Ioannidis, Alexander G; Jimenez-Morales, David; Gorzynski, John E; De Jong, Hannah N; Liu, Xiran; Roque, Jonasel; Cepeda-Espinoza, Victoria P; Osoegawa, Kazutoyo; Hughes, Chris; Sutton, Shirley C; Youlton, Nathan; Joshi, Ruchi; Amar, David; Tanigawa, Yosuke; Russo, Douglas; Wong, Justin; Lauzon, Jessie T; Edelson, Jacob; Mas Montserrat, Daniel; Kwon, Yongchan; Rubinacci, Simone; Delaneau, Olivier; Cappello, Lorenzo; Kim, Jaehee; Shoura, Massa J; Raja, Archana N; Watson, Nathaniel; Hammond, Nathan; Spiteri, Elizabeth; Mallempati, Kalyan C; Montero-Martín, Gonzalo; Christle, Jeffrey; Kim, Jennifer; Kirillova, Anna; Seo, Kinya; Huang, Yong; Zhao, Chunli; Moreno-Grau, Sonia; Hershman, Steven G; Dalton, Karen P; Zhen, Jimmy; Kamm, Jack; Bhatt, Karan D; Isakova, Alina; Morri, Maurizio; Ranganath, Thanmayi; Blish, Catherine A; Rogers, Angela J; Nadeau, Kari.
  • Parikh VN; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Ioannidis AG; Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
  • Jimenez-Morales D; Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA.
  • Gorzynski JE; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • De Jong HN; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Liu X; Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
  • Roque J; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Cepeda-Espinoza VP; Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
  • Osoegawa K; Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA.
  • Hughes C; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Sutton SC; Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
  • Youlton N; Histocompatibility & Immunogenetics Laboratory, Stanford Blood Center, Stanford Health Care, Stanford, USA.
  • Joshi R; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Amar D; Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
  • Tanigawa Y; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Russo D; Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
  • Wong J; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Lauzon JT; Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
  • Edelson J; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Mas Montserrat D; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Kwon Y; Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
  • Rubinacci S; Department of Statistics, Stanford University, Stanford, CA, USA.
  • Delaneau O; Department of Statistics, Stanford University, Stanford, CA, USA.
  • Cappello L; Department of Aeronautics and Astronautics, Stanford University, Stanford, CA, USA.
  • Kim J; Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
  • Shoura MJ; Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
  • Raja AN; Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
  • Watson N; Department of Computational Biology and Swiss Institute of Bioinformatics, University of Lausanne, Lausanne, Switzerland.
  • Hammond N; Department of Computational Biology and Swiss Institute of Bioinformatics, University of Lausanne, Lausanne, Switzerland.
  • Spiteri E; Department of Statistics, Stanford University, Stanford, CA, USA.
  • Mallempati KC; Department of Computational Biology, Cornell University, Ithaca, NY, USA.
  • Montero-Martín G; Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
  • Christle J; Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
  • Kim J; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Kirillova A; Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
  • Seo K; Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
  • Huang Y; Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
  • Zhao C; Histocompatibility & Immunogenetics Laboratory, Stanford Blood Center, Stanford Health Care, Stanford, USA.
  • Moreno-Grau S; Histocompatibility & Immunogenetics Laboratory, Stanford Blood Center, Stanford Health Care, Stanford, USA.
  • Hershman SG; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Dalton KP; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Zhen J; Medical Scientist Training Program, University of Pittsburgh and Carnegie Mellon University, Pittsburgh, PA, USA.
  • Kamm J; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Bhatt KD; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Isakova A; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Morri M; Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
  • Ranganath T; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Blish CA; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Rogers AJ; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Nadeau K; Chan Zuckerburg Biohub, San Francisco, CA, USA.
Nat Commun ; 13(1): 5107, 2022 08 30.
Article in English | MEDLINE | ID: covidwho-2016695
ABSTRACT
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.
Subject(s)
Fulltext
Print
XML
PubMed Links
Search on Google

Full text: Available Collection: International databases Database: MEDLINE Main subject: Pandemics / COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Nat Commun Journal subject: Biology / Science Year: 2022 Document Type: Article Affiliation country: S41467-022-32397-8

Similar

MEDLINE
LILACS
LIS
Fulltext
Print
XML
PubMed Links
Search on Google

Full text: Available Collection: International databases Database: MEDLINE Main subject: Pandemics / COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Nat Commun Journal subject: Biology / Science Year: 2022 Document Type: Article Affiliation country: S41467-022-32397-8