Please use this identifier to cite or link to this item:
https://doi.org/10.1186/s12920-021-01006-w
Title: | A blood RNA transcriptome signature for COVID-19 | Authors: | Kwan, Philip Kam Weng Cross, Gail B Naftalin, Claire M Ahidjo, Bintou A Mok, Chee Keng Fanusi, Felic Permata Sari, Intan Chia, Siok Ching Kumar, Shoban Krishna Alagha, Rawan Tham, Sai Meng Archuleta, Sophia Sessions, October M Hibberd, Martin L Paton, Nicholas I |
Keywords: | Science & Technology Life Sciences & Biomedicine Genetics & Heredity SARS-CoV-2 COVID-19 Gene expression Biomarkers RNA sequencing Whole blood TUBERCULOSIS EXPRESSION DIAGNOSIS P53 |
Issue Date: | 11-Jun-2021 | Publisher: | BMC | Citation: | Kwan, Philip Kam Weng, Cross, Gail B, Naftalin, Claire M, Ahidjo, Bintou A, Mok, Chee Keng, Fanusi, Felic, Permata Sari, Intan, Chia, Siok Ching, Kumar, Shoban Krishna, Alagha, Rawan, Tham, Sai Meng, Archuleta, Sophia, Sessions, October M, Hibberd, Martin L, Paton, Nicholas I (2021-06-11). A blood RNA transcriptome signature for COVID-19. BMC MEDICAL GENOMICS 14 (1). ScholarBank@NUS Repository. https://doi.org/10.1186/s12920-021-01006-w | Abstract: | Background: COVID-19 is a respiratory viral infection with unique features including a more chronic course and systemic disease manifestations including multiple organ involvement; and there are differences in disease severity between ethnic groups. The immunological basis for disease has not been fully characterised. Analysis of whole-blood RNA expression may provide valuable information on disease pathogenesis. Methods: We studied 45 patients with confirmed COVID-19 infection within 10 days from onset of illness and a control group of 19 asymptomatic healthy volunteers with no known exposure to COVID-19 in the previous 14 days. Relevant demographic and clinical information was collected and a blood sample was drawn from all participants for whole-blood RNA sequencing. We evaluated differentially-expressed genes in COVID-19 patients (log2 fold change ≥ 1 versus healthy controls; false-discovery rate < 0.05) and associated protein pathways and compared these to published whole-blood signatures for respiratory syncytial virus (RSV) and influenza. We developed a disease score reflecting the overall magnitude of expression of internally-validated genes and assessed the relationship between the disease score and clinical disease parameters. Results: We found 135 differentially-expressed genes in the patients with COVID-19 (median age 35 years; 82% male; 36% Chinese, 53% South Asian ethnicity). Of the 117 induced genes, 14 were found in datasets from RSV and 40 from influenza; 95 genes were unique to COVID-19. Protein pathways were mostly generic responses to viral infections, including apoptosis by P53-associated pathway, but also included some unique pathways such as viral carcinogenesis. There were no major qualitative differences in pathways between ethnic groups. The composite gene-expression score was correlated with the time from onset of symptoms and nasal swab qPCR CT values (both p < 0.01) but was not related to participant age, gender, ethnicity or the presence or absence of chest X-ray abnormalities (all p > 0.05). Conclusions: The whole-blood transcriptome of COVID-19 has overall similarity with other respiratory infections but there are some unique pathways that merit further exploration to determine clinical relevance. The approach to a disease score may be of value, but needs further validation in a population with a greater range of disease severity. | Source Title: | BMC MEDICAL GENOMICS | URI: | https://scholarbank.nus.edu.sg/handle/10635/206218 | ISSN: | 17558794 | DOI: | 10.1186/s12920-021-01006-w |
Appears in Collections: | Staff Publications Elements |
Show full item record
Files in This Item:
File | Description | Size | Format | Access Settings | Version | |
---|---|---|---|---|---|---|
A blood RNA transcriptome signature for COVID-19.pdf | Published version | 911.96 kB | Adobe PDF | OPEN | Published | View/Download |
SCOPUSTM
Citations
8
checked on May 28, 2023
Page view(s)
154
checked on May 25, 2023
Download(s)
2
checked on May 25, 2023
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.