Nature Communications (Feb 2018)
A community approach to mortality prediction in sepsis via gene expression analysis
- Timothy E. Sweeney,
- Thanneer M. Perumal,
- Ricardo Henao,
- Marshall Nichols,
- Judith A. Howrylak,
- Augustine M. Choi,
- Jesús F. Bermejo-Martin,
- Raquel Almansa,
- Eduardo Tamayo,
- Emma E. Davenport,
- Katie L. Burnham,
- Charles J. Hinds,
- Julian C. Knight,
- Christopher W. Woods,
- Stephen F. Kingsmore,
- Geoffrey S. Ginsburg,
- Hector R. Wong,
- Grant P. Parnell,
- Benjamin Tang,
- Lyle L. Moldawer,
- Frederick E. Moore,
- Larsson Omberg,
- Purvesh Khatri,
- Ephraim L. Tsalik,
- Lara M. Mangravite,
- Raymond J. Langley
Affiliations
- Timothy E. Sweeney
- Stanford Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine
- Thanneer M. Perumal
- Sage Bionetworks
- Ricardo Henao
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University
- Marshall Nichols
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University
- Judith A. Howrylak
- Division of Pulmonary and Critical Care Medicine, Penn State Milton S. Hershey Medical Center
- Augustine M. Choi
- Department of Medicine, Cornell Medical Center
- Jesús F. Bermejo-Martin
- Hospital Clínico Universitario de Valladolid/IECSCYL
- Raquel Almansa
- Hospital Clínico Universitario de Valladolid/IECSCYL
- Eduardo Tamayo
- Hospital Clínico Universitario de Valladolid/IECSCYL
- Emma E. Davenport
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School
- Katie L. Burnham
- Wellcome Trust Centre for Human Genetics, University of Oxford
- Charles J. Hinds
- William Harvey Research Institute, Barts and The London School of Medicine, Queen Mary University
- Julian C. Knight
- Wellcome Trust Centre for Human Genetics, University of Oxford
- Christopher W. Woods
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University
- Stephen F. Kingsmore
- Rady Children’s Institute for Genomic Medicine
- Geoffrey S. Ginsburg
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University
- Hector R. Wong
- Division of Critical Care Medicine, Cincinnati Children’s Hospital Medical Center and Cincinnati Children’s Research Foundation
- Grant P. Parnell
- Centre for Immunology and Allergy Research, Westmead Institute for Medical Research
- Benjamin Tang
- Centre for Immunology and Allergy Research, Westmead Institute for Medical Research
- Lyle L. Moldawer
- Department of Surgery, University of Florida College of Medicine
- Frederick E. Moore
- Department of Surgery, University of Florida College of Medicine
- Larsson Omberg
- Sage Bionetworks
- Purvesh Khatri
- Stanford Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine
- Ephraim L. Tsalik
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University
- Lara M. Mangravite
- Sage Bionetworks
- Raymond J. Langley
- Department of Pharmacology, University of South Alabama
- DOI
- https://doi.org/10.1038/s41467-018-03078-2
- Journal volume & issue
-
Vol. 9,
no. 1
pp. 1 – 10
Abstract
Sepsis is characterized by deregulated host response to infection. Efficient therapies are still needed but a limitation for sepsis treatment is the heterogeneity in patients. Here Sweeney et al. generate prognostic models based on gene expression to improve risk stratification classification and prediction for 30-day mortality of patients.
