TY - JOUR
T1 - Multi-objective optimization identifies a specific and interpretable COVID-19 host response signature
AU - Cappuccio, Antonio
AU - Chawla, Daniel G.
AU - Chen, Xi
AU - Rubenstein, Aliza B.
AU - Cheng, Wan Sze
AU - Mao, Weiguang
AU - Burke, Thomas W.
AU - Tsalik, Ephraim L.
AU - Petzold, Elizabeth
AU - Henao, Ricardo
AU - McClain, Micah T.
AU - Woods, Christopher W.
AU - Chikina, Maria
AU - Troyanskaya, Olga G.
AU - Sealfon, Stuart C.
AU - Kleinstein, Steven H.
AU - Zaslavsky, Elena
N1 - Generated from Scopus record by KAUST IRTS on 2023-02-15
PY - 2022/12/21
Y1 - 2022/12/21
N2 - The identification of a COVID-19 host response signature in blood can increase the understanding of SARS-CoV-2 pathogenesis and improve diagnostic tools. Applying a multi-objective optimization framework to both massive public and new multi-omics data, we identified a COVID-19 signature regulated at both transcriptional and epigenetic levels. We validated the signature's robustness in multiple independent COVID-19 cohorts. Using public data from 8,630 subjects and 53 conditions, we demonstrated no cross-reactivity with other viral and bacterial infections, COVID-19 comorbidities, or confounders. In contrast, previously reported COVID-19 signatures were associated with significant cross-reactivity. The signature's interpretation, based on cell-type deconvolution and single-cell data analysis, revealed prominent yet complementary roles for plasmablasts and memory T cells. Although the signal from plasmablasts mediated COVID-19 detection, the signal from memory T cells controlled against cross-reactivity with other viral infections. This framework identified a robust, interpretable COVID-19 signature and is broadly applicable in other disease contexts. A record of this paper's transparent peer review process is included in the supplemental information.
AB - The identification of a COVID-19 host response signature in blood can increase the understanding of SARS-CoV-2 pathogenesis and improve diagnostic tools. Applying a multi-objective optimization framework to both massive public and new multi-omics data, we identified a COVID-19 signature regulated at both transcriptional and epigenetic levels. We validated the signature's robustness in multiple independent COVID-19 cohorts. Using public data from 8,630 subjects and 53 conditions, we demonstrated no cross-reactivity with other viral and bacterial infections, COVID-19 comorbidities, or confounders. In contrast, previously reported COVID-19 signatures were associated with significant cross-reactivity. The signature's interpretation, based on cell-type deconvolution and single-cell data analysis, revealed prominent yet complementary roles for plasmablasts and memory T cells. Although the signal from plasmablasts mediated COVID-19 detection, the signal from memory T cells controlled against cross-reactivity with other viral infections. This framework identified a robust, interpretable COVID-19 signature and is broadly applicable in other disease contexts. A record of this paper's transparent peer review process is included in the supplemental information.
UR - https://linkinghub.elsevier.com/retrieve/pii/S2405471222004677
UR - http://www.scopus.com/inward/record.url?scp=85144521601&partnerID=8YFLogxK
U2 - 10.1016/j.cels.2022.11.008
DO - 10.1016/j.cels.2022.11.008
M3 - Article
C2 - 36549275
SN - 2405-4720
VL - 13
SP - 989-1001.e8
JO - Cell Systems
JF - Cell Systems
IS - 12
ER -