Document Type
Article
Publication Date
7-10-2025
Original Citation
Chew T,
Pelaia T,
Phu A,
Teoh S,
Wang Y,
Deshpande N,
Kim K,
Herwanto V,
Gunawan ,
Karvunidis T,
Zerbib Y,
Short K,
Macdonald S,
Thevarajan I,
Rinchai D,
Kuan W,
Knippenberg B,
Iredell J,
Britton P,
Hutchings O,
Britton W,
Eden J,
Orde S,
Tang B,
McLean A,
Chaussabel D,
Schughart K,
Shojaei M.
Molecular landscape of respiratory infection: A large-scale, multi-centre blood transcriptome dataset. Sci Data. 2025;12(1):1175.
Keywords
JGM, Humans, Transcriptome, Respiratory Tract Infections, COVID-19, Influenza, Human, Coinfection
JAX Source
Sci Data. 2025;12(1):1175.
ISSN
2052-4463
PMID
40640204
DOI
https://doi.org/10.1038/s41597-025-05488-6
Abstract
Respiratory infections pose significant challenges to global health, impacting millions of individuals annually. Understanding the molecular mechanisms underlying the pathogenicity of these infections is crucial for developing effective interventions. RNA sequencing provides insights into a patient's global transcriptome changes, facilitating the identification of host gene signatures in response to infection and potential therapeutic targets. Here we present an extensive whole blood transcriptome dataset from a demographically diverse cohort of 502 patients with infections including COVID-19, seasonal coronavirus, influenza A or influenza B, sepsis, septic shock, and co-infections (Viral/Viral, Bacterial/Viral, Bacterial/Viral/Fungal, Viral/Fungal, Viral/ Viral/Fungal). The cohort size and depth of data showcase its potential to unravel respiratory infection pathogenesis for the development of better diagnostics, treatments, and preventive strategies for respiratory infections and future global health crises.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.