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Blood gene expression predicts intensive care unit admission in hospitalised patients with COVID-19

Blood gene expression predicts intensive care unit admission in hospitalised patients with COVID-19
Blood gene expression predicts intensive care unit admission in hospitalised patients with COVID-19
Background: The COVID-19 pandemic has created pressure on healthcare systems worldwide. Tools that can stratify individuals according to prognosis could allow for more efficient allocation of healthcare resources and thus improved patient outcomes. It is currently unclear if blood gene expression signatures derived from patients at the point of admission to hospital could provide useful prognostic information.
Methods: Gene expression of whole blood obtained at the point of admission from a cohort of 78 patients hospitalised with COVID-19 during the first wave was measured by high resolution RNA sequencing. Gene signatures predictive of admission to Intensive Care Unit were identified and tested using machine learning and topological data analysis, TopMD.R
Results: The best gene expression signature predictive of ICU admission was defined using topological data analysis with an accuracy: 0.72 and ROC AUC: 0.76. The gene signature was primarily based on differentially activated pathways controlling epidermal growth factor receptor (EGFR) presentation, Peroxisome proliferator-activated receptor alpha (PPAR-α) signalling and Transforming growth factor beta (TGF-β) signalling.
Conclusions: Gene expression signatures from blood taken at the point of admission to hospital predicted ICU admission of treatment naïve patients with COVID-19.
COVID-19/genetics, ErbB Receptors, Gene Expression, Humans, Intensive Care Units, PPAR alpha, Pandemics, Transforming Growth Factor beta
1664-3224
Penrice-Randal, Rebekah
5cdbce6b-4d9b-46b0-b9b0-27657d78e021
Dong, Xiaofeng
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Shapanis, Andrew George
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Gardner, Aaron
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Harding, Nicholas
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Legebeke, Jelmer
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Lord, Jenny
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Vallejo, Andres F
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Poole, Stephen
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Brendish, Nathan J
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Hartley, Catherine
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Williams, Anthony P
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Wheway, Gabrielle
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Polak, Marta E
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Strazzeri, Fabio
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Schofield, James P R
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Skipp, Paul J
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Hiscox, Julian A
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Clark, Tristan W
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Baralle, Diana
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Penrice-Randal, Rebekah
5cdbce6b-4d9b-46b0-b9b0-27657d78e021
Dong, Xiaofeng
8330da42-4821-417a-bfd6-e1129c8cba8a
Shapanis, Andrew George
98b07884-92a9-4c00-afad-12194e339cbc
Gardner, Aaron
05f1f1a0-f518-49ef-a7a2-1833569cb886
Harding, Nicholas
a7b18a57-0b5d-4c5f-bd86-41ff2fc09f15
Legebeke, Jelmer
f6062b8c-22ac-465c-9528-3bac881137d0
Lord, Jenny
e1909780-36cd-4705-b21e-4580038d4ec6
Vallejo, Andres F
294fca39-0187-47b4-90ad-cadc7b888830
Poole, Stephen
440d7904-ab72-469c-892b-c910cd1cb19b
Brendish, Nathan J
a8a4189e-01eb-4ab3-933e-a24cd188a4d7
Hartley, Catherine
a27eeaf6-d1b6-47af-b417-a833b175807c
Williams, Anthony P
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Wheway, Gabrielle
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Polak, Marta E
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Strazzeri, Fabio
2fa6d25b-1ab5-43b9-a21c-c1e1454d0cb1
Schofield, James P R
b6d3a808-50ac-4365-bc0d-80da333a4ae7
Skipp, Paul J
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Hiscox, Julian A
d7cefa75-f159-4905-948f-b86a7f14f55d
Clark, Tristan W
712ec18e-613c-45df-a013-c8a22834e14f
Baralle, Diana
faac16e5-7928-4801-9811-8b3a9ea4bb91

Penrice-Randal, Rebekah, Dong, Xiaofeng, Shapanis, Andrew George, Gardner, Aaron, Harding, Nicholas, Legebeke, Jelmer, Lord, Jenny, Vallejo, Andres F, Poole, Stephen, Brendish, Nathan J, Hartley, Catherine, Williams, Anthony P, Wheway, Gabrielle, Polak, Marta E, Strazzeri, Fabio, Schofield, James P R, Skipp, Paul J, Hiscox, Julian A, Clark, Tristan W and Baralle, Diana (2022) Blood gene expression predicts intensive care unit admission in hospitalised patients with COVID-19. Frontiers in Immunology, 13, [988685]. (doi:10.3389/fimmu.2022.988685).

Record type: Article

Abstract

Background: The COVID-19 pandemic has created pressure on healthcare systems worldwide. Tools that can stratify individuals according to prognosis could allow for more efficient allocation of healthcare resources and thus improved patient outcomes. It is currently unclear if blood gene expression signatures derived from patients at the point of admission to hospital could provide useful prognostic information.
Methods: Gene expression of whole blood obtained at the point of admission from a cohort of 78 patients hospitalised with COVID-19 during the first wave was measured by high resolution RNA sequencing. Gene signatures predictive of admission to Intensive Care Unit were identified and tested using machine learning and topological data analysis, TopMD.R
Results: The best gene expression signature predictive of ICU admission was defined using topological data analysis with an accuracy: 0.72 and ROC AUC: 0.76. The gene signature was primarily based on differentially activated pathways controlling epidermal growth factor receptor (EGFR) presentation, Peroxisome proliferator-activated receptor alpha (PPAR-α) signalling and Transforming growth factor beta (TGF-β) signalling.
Conclusions: Gene expression signatures from blood taken at the point of admission to hospital predicted ICU admission of treatment naïve patients with COVID-19.

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More information

Accepted/In Press date: 29 August 2022
e-pub ahead of print date: 20 September 2022
Published date: 20 September 2022
Additional Information: Copyright © 2022 Penrice-Randal, Dong, Shapanis, Gardner, Harding, Legebeke, Lord, Vallejo, Poole, Brendish, Hartley, Williams, Wheway, Polak, Strazzeri, Schofield, Skipp, Hiscox, Clark and Baralle.
Keywords: COVID-19/genetics, ErbB Receptors, Gene Expression, Humans, Intensive Care Units, PPAR alpha, Pandemics, Transforming Growth Factor beta

Identifiers

Local EPrints ID: 469749
URI: http://eprints.soton.ac.uk/id/eprint/469749
ISSN: 1664-3224
PURE UUID: 475b8385-a812-4155-9384-a675b65a5631
ORCID for Andrew George Shapanis: ORCID iD orcid.org/0000-0003-4147-6956
ORCID for Jelmer Legebeke: ORCID iD orcid.org/0000-0003-1194-8959
ORCID for Jenny Lord: ORCID iD orcid.org/0000-0002-0539-9343
ORCID for Nathan J Brendish: ORCID iD orcid.org/0000-0002-9589-4937
ORCID for Gabrielle Wheway: ORCID iD orcid.org/0000-0002-0494-0783
ORCID for Paul J Skipp: ORCID iD orcid.org/0000-0002-2995-2959
ORCID for Tristan W Clark: ORCID iD orcid.org/0000-0001-6026-5295
ORCID for Diana Baralle: ORCID iD orcid.org/0000-0003-3217-4833

Catalogue record

Date deposited: 23 Sep 2022 17:15
Last modified: 21 Mar 2023 03:01

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Contributors

Author: Rebekah Penrice-Randal
Author: Xiaofeng Dong
Author: Aaron Gardner
Author: Jelmer Legebeke ORCID iD
Author: Jenny Lord ORCID iD
Author: Andres F Vallejo
Author: Stephen Poole
Author: Catherine Hartley
Author: Marta E Polak
Author: Fabio Strazzeri
Author: James P R Schofield
Author: Paul J Skipp ORCID iD
Author: Julian A Hiscox
Author: Tristan W Clark ORCID iD
Author: Diana Baralle ORCID iD

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