50-gene risk profiles in peripheral blood predict COVID-19 outcomes: A retrospective, multicenter cohort study
Brenda M. Juan Guardela,
Jiehuan Sun,
Tong Zhang,
Bing Xu,
Joseph Balnis,
Yong Huang,
Shwu-Fan Ma,
Philip L. Molyneaux,
Toby M. Maher,
Imre Noth,
Gaetane Michaud,
Ariel Jaitovich,
Jose D. Herazo-Maya
Affiliations
Brenda M. Juan Guardela
Divison of Pulmonary, Critical Care & Sleep Medicine. University of South Florida, Morsani College of Medicine, Tampa, FL 33602, USA
Jiehuan Sun
Division of Epidemiology and Biostatistics, University of Illinois at Chicago, Chicago, IL, USA
Tong Zhang
Division of Epidemiology and Biostatistics, University of Illinois at Chicago, Chicago, IL, USA
Bing Xu
Division of Epidemiology and Biostatistics, University of Illinois at Chicago, Chicago, IL, USA
Joseph Balnis
Division of Pulmonary and Critical Care Medicine, Albany Medical College, NY, USA
Yong Huang
Division of Pulmonary & Critical Care Medicine, The University of Virginia at Charlottesville, VA, USA
Shwu-Fan Ma
Division of Pulmonary & Critical Care Medicine, The University of Virginia at Charlottesville, VA, USA
Philip L. Molyneaux
National Heart and Lung Institute, Imperial College, London, UK; Royal Brompton Hospital, London, UK
Toby M. Maher
National Heart and Lung Institute, Imperial College, London, UK; Royal Brompton Hospital, London, UK; Hastings Centre for Pulmonary Research and Division of Pulmonary, Critical Care and Sleep Medicine, Keck School of Medicine, University of Southern California, LA, USA
Imre Noth
Division of Pulmonary & Critical Care Medicine, The University of Virginia at Charlottesville, VA, USA
Gaetane Michaud
Divison of Pulmonary, Critical Care & Sleep Medicine. University of South Florida, Morsani College of Medicine, Tampa, FL 33602, USA
Ariel Jaitovich
Division of Pulmonary and Critical Care Medicine, Albany Medical College, NY, USA
Jose D. Herazo-Maya
Divison of Pulmonary, Critical Care & Sleep Medicine. University of South Florida, Morsani College of Medicine, Tampa, FL 33602, USA; Corresponding author.
Background: COVID-19 has been associated with Interstitial Lung Disease features. The immune transcriptomic overlap between Idiopathic Pulmonary Fibrosis (IPF) and COVID-19 has not been investigated. Methods: we analyzed blood transcript levels of 50 genes known to predict IPF mortality in three COVID-19 and two IPF cohorts. The Scoring Algorithm of Molecular Subphenotypes (SAMS) was applied to distinguish high versus low-risk profiles in all cohorts. SAMS cutoffs derived from the COVID-19 Discovery cohort were used to predict intensive care unit (ICU) status, need for mechanical ventilation, and in-hospital mortality in the COVID-19 Validation cohort. A COVID-19 Single-cell RNA-sequencing cohort was used to identify the cellular sources of the 50-gene risk profiles. The same COVID-19 SAMS cutoffs were used to predict mortality in the IPF cohorts. Findings: 50-gene risk profiles discriminated severe from mild COVID-19 in the Discovery cohort (P = 0·015) and predicted ICU admission, need for mechanical ventilation, and in-hospital mortality (AUC: 0·77, 0·75, and 0·74, respectively, P < 0·001) in the COVID-19 Validation cohort. In COVID-19, 50-gene expressing cells with a high-risk profile included monocytes, dendritic cells, and neutrophils, while low-risk profile-expressing cells included CD4+, CD8+ T lymphocytes, IgG producing plasmablasts, B cells, NK, and gamma/delta T cells. Same COVID-19 SAMS cutoffs were also predictive of mortality in the University of Chicago (HR:5·26, 95%CI:1·81–15·27, P = 0·0013) and Imperial College of London (HR:4·31, 95%CI:1·81–10·23, P = 0·0016) IPF cohorts. Interpretation: 50-gene risk profiles in peripheral blood predict COVID-19 and IPF outcomes. The cellular sources of these gene expression changes suggest common innate and adaptive immune responses in both diseases.
