A diagnostic host response biosignature for COVID-19 from RNA profiling of nasal swabs and blood
Dianna Ng, Andrea Granados, Yale Santos, Venice Servellita, Gregory M. Goldgof, Cem Meydan, Alicia Sotomayor-González, Andrew G. Levine, Joanna Balcerek, Lucy M. Han, Naomi Akagi, Kent Truong, Neil M. Neumann, David N. Nguyen, Sagar P. Bapat, Jing Cheng, Claudia Sánchez-San Martín, Scot Federman, Jonathan Foox, Allan Gopez, Tony Li, Ray Chun‐Fai Chan, Cynthia S. Chu, Chiara A. Wabl, Amelia S. Gliwa, Kevin Reyes, Chao‐Yang Pan, Hugo Guevara, Debra A. Wadford, Steve Miller, Christopher E. Mason, Charles Y. Chiu
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease-19 (COVID-19), has emerged as the cause of a global pandemic. We used RNA sequencing to analyze 286 nasopharyngeal (NP) swab and 53 whole-blood (WB) samples from 333 patients with COVID-19 and controls. Overall, a muted immune response was observed in COVID-19 relative to other infections (influenza, other seasonal coronaviruses, and bacterial sepsis), with paradoxical down-regulation of several key differentially expressed genes. Hospitalized patients and outpatients exhibited up-regulation of interferon-associated pathways, although heightened and more robust inflammatory responses were observed in hospitalized patients with more clinically severe illness. Two-layer machine learning-based host classifiers consisting of complete (>1000 genes), medium (<100), and small (<20) gene biomarker panels identified COVID-19 disease with 85.1-86.5% accuracy when benchmarked using an independent test set. SARS-CoV-2 infection has a distinct biosignature that differs between NP swabs and WB and can be leveraged for COVID-19 diagnosis.