BibTex format
@article{Moradi:2023:10.1016/j.jinf.2023.10.009,
author = {Moradi, Marjaneh M and Challenger, J and salas, A and Gómez-Carballa, A and Sivananthan, A and Rivero-Calle, I and Barbeito-Castiñeiras, G and Foo, C and Wu, Y and Liew, F and Jackson, H and Habgood-Coote, D and D'Souza, G and Nichols, S and Wright, V and Levin, M and Kaforou, M and Thwaites, R and Okell, L and Martinon-Torres, F and Cunnington, A and PERFORM, Consortium and GEN-COVID, Study Group},
doi = {10.1016/j.jinf.2023.10.009},
journal = {Journal of Infection},
pages = {538--550},
title = {Analysis of blood and nasal epithelial transcriptomes to identify mechanisms associated with control of SARS-CoV-2 viral load in the upper respiratory tract},
url = {http://dx.doi.org/10.1016/j.jinf.2023.10.009},
volume = {87},
year = {2023}
}
RIS format (EndNote, RefMan)
TY - JOUR
AB - Objectives:The amount of SARS-CoV-2 detected in the upper respiratory tract (URT viral load) is a key driver of transmission of infection. Current evidence suggests that mechanisms constraining URT viral load are different from those controlling lower respiratory tract viral load and disease severity. Understanding such mechanisms may help to develop treatments and vaccine strategies to reduce transmission. Combining mathematical modelling of URT viral load dynamics with transcriptome analyses we aimed to identify mechanisms controlling URT viral load.Methods:COVID-19 patients were recruited in Spain during the first wave of the pandemic. RNA sequencing of peripheral blood and targeted NanoString nCounter transcriptome analysis of nasal epithelium were performed and gene expression analysed in relation to paired URT viral load samples collected within 15 days of symptom onset. Proportions of major immune cells in blood were estimated from transcriptional data using computational differential estimation. Weighted correlation network analysis (adjusted for cell proportions) and fixed transcriptional repertoire analysis were used to identify associations with URT viral load, quantified as standard deviations (z-scores) from an expected trajectory over time.ResultsEighty-two subjects (50% female, median age 54 years (range 3–73)) with COVID-19 were recruited. Paired URT viral load samples were available for 16 blood transcriptome samples, and 17 respiratory epithelial transcriptome samples. Natural Killer (NK) cells were the only blood cell type significantly correlated with URT viral load z-scores (r = −0.62, P = 0.010). Twenty-four blood gene expression modules were significantly correlated with URT viral load z-score, the most significant being a module of genes connected around IFNA14 (Interferon Alpha-14) expression (r = −0.60, P = 1e-10). In fixed repertoire analysis, prostanoid-related gene expression was significantly associated with higher vir
AU - Moradi,Marjaneh M
AU - Challenger,J
AU - salas,A
AU - Gómez-Carballa,A
AU - Sivananthan,A
AU - Rivero-Calle,I
AU - Barbeito-Castiñeiras,G
AU - Foo,C
AU - Wu,Y
AU - Liew,F
AU - Jackson,H
AU - Habgood-Coote,D
AU - D'Souza,G
AU - Nichols,S
AU - Wright,V
AU - Levin,M
AU - Kaforou,M
AU - Thwaites,R
AU - Okell,L
AU - Martinon-Torres,F
AU - Cunnington,A
AU - PERFORM,Consortium
AU - GEN-COVID,Study Group
DO - 10.1016/j.jinf.2023.10.009
EP - 550
PY - 2023///
SN - 0163-4453
SP - 538
TI - Analysis of blood and nasal epithelial transcriptomes to identify mechanisms associated with control of SARS-CoV-2 viral load in the upper respiratory tract
T2 - Journal of Infection
UR - http://dx.doi.org/10.1016/j.jinf.2023.10.009
UR - https://www.journalofinfection.com/article/S0163-4453(23)00540-6/fulltext
UR - http://hdl.handle.net/10044/1/107456
VL - 87
ER -
