A 2-Gene Host Signature for Improved Accuracy of COVID-19 Diagnosis Agnostic to Viral Variants
Jack Albright, Eran Mick, Estella Sanchez-Guerrero, Jack Kamm, Anthea Mitchell, Angela M. Detweiler, Norma Neff, Alexandra Tsitsiklis, Paula Hayakawa Serpa, Kalani Ratnasiri, Diane V. Havlir, Amy Kistler, Joseph L. DeRisi, Angela Oliveira Pisco, Charles Langelier
Abstract
In this work, we study upper respiratory tract gene expression to develop and validate a 2-gene host-based COVID-19 diagnostic classifier and then demonstrate its implementation in a clinically practical qPCR assay. We find that the host classifier has utility for mitigating false-negative results, for example due to SARS-CoV-2 variants harboring mutations at primer target sites, and for mitigating false-positive viral PCR results due to laboratory cross-contamination. Both types of error carry serious consequences of either unrecognized viral transmission or unnecessary isolation and contact tracing. This work is directly relevant to the ongoing COVID-19 pandemic given the continued emergence of viral variants and the continued challenges of false-positive PCR assays. It also suggests the feasibility of pan-respiratory virus host-based diagnostics that would have value in congregate settings, such as hospitals and nursing homes, where unrecognized respiratory viral transmission is of particular concern.