Your browser doesn't support javascript.
Multiomic analysis reveals cell-type-specific molecular determinants of COVID-19 severity.
Zhang, Sai; Cooper-Knock, Johnathan; Weimer, Annika K; Shi, Minyi; Kozhaya, Lina; Unutmaz, Derya; Harvey, Calum; Julian, Thomas H; Furini, Simone; Frullanti, Elisa; Fava, Francesca; Renieri, Alessandra; Gao, Peng; Shen, Xiaotao; Timpanaro, Ilia Sarah; Kenna, Kevin P; Baillie, J Kenneth; Davis, Mark M; Tsao, Philip S; Snyder, Michael P.
  • Zhang S; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; VA Palo Alto Epidemiology Research and Information Center for Genomics, VA Palo Alto Health Care System, Palo Alto, CA 94304, USA; Center for Genomics and Personalized Medicine, Stanford University School of Med
  • Cooper-Knock J; Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield S10 2HQ, UK.
  • Weimer AK; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Shi M; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Kozhaya L; The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA.
  • Unutmaz D; The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA.
  • Harvey C; Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield S10 2HQ, UK.
  • Julian TH; Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield S10 2HQ, UK.
  • Furini S; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy.
  • Frullanti E; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy; Medical Genetics, Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy.
  • Fava F; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy; Medical Genetics, Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy; Genetica Medica, Azienda Ospedaliero-Universitaria Senese, 53100 Siena, Italy.
  • Renieri A; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy; Medical Genetics, Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy; Genetica Medica, Azienda Ospedaliero-Universitaria Senese, 53100 Siena, Italy.
  • Gao P; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Shen X; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Timpanaro IS; Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, 3584 CX Utrecht, the Netherlands.
  • Kenna KP; Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, 3584 CX Utrecht, the Netherlands.
  • Baillie JK; Roslin Institute, University of Edinburgh, Easter Bush, Midlothian EH25 9RG, UK; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh EH4 2XU, UK; Intensive Care Unit, Royal Infirmary of Edinburgh, Edinburgh EH16 4SA, UK.
  • Davis MM; Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University School of Medicine,
  • Tsao PS; VA Palo Alto Epidemiology Research and Information Center for Genomics, VA Palo Alto Health Care System, Palo Alto, CA 94304, USA; Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Medicine, Stanford University School of Medicine, Stanf
  • Snyder MP; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA; Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA 94305, USA.
Cell Syst ; 13(8): 598-614.e6, 2022 Aug 17.
Article in English | MEDLINE | ID: covidwho-1930802
ABSTRACT
The determinants of severe COVID-19 in healthy adults are poorly understood, which limits the opportunity for early intervention. We present a multiomic analysis using machine learning to characterize the genomic basis of COVID-19 severity. We use single-cell multiome profiling of human lungs to link genetic signals to cell-type-specific functions. We discover >1,000 risk genes across 19 cell types, which account for 77% of the SNP-based heritability for severe disease. Genetic risk is particularly focused within natural killer (NK) cells and T cells, placing the dysfunction of these cells upstream of severe disease. Mendelian randomization and single-cell profiling of human NK cells support the role of NK cells and further localize genetic risk to CD56bright NK cells, which are key cytokine producers during the innate immune response. Rare variant analysis confirms the enrichment of severe-disease-associated genetic variation within NK-cell risk genes. Our study provides insights into the pathogenesis of severe COVID-19 with potential therapeutic targets.
Subject(s)
Keywords
Fulltext
Print
XML
PubMed Links
Search on Google

Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Prognostic study Topics: Variants Limits: Adult / Humans Language: English Journal: Cell Syst Year: 2022 Document Type: Article

Similar

MEDLINE
LILACS
LIS
Fulltext
Print
XML
PubMed Links
Search on Google

Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Prognostic study Topics: Variants Limits: Adult / Humans Language: English Journal: Cell Syst Year: 2022 Document Type: Article