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. 2022 Sep 20:13:988685.
doi: 10.3389/fimmu.2022.988685. eCollection 2022.

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

Rebekah Penrice-Randal  1   2 , Xiaofeng Dong  1 , Andrew George Shapanis  3 , Aaron Gardner  2 , Nicholas Harding  2 , Jelmer Legebeke  3   4 , Jenny Lord  3 , Andres F Vallejo  5 , Stephen Poole  4   5 , Nathan J Brendish  4   5 , Catherine Hartley  1 , Anthony P Williams  6 , Gabrielle Wheway  3 , Marta E Polak  5   7 , Fabio Strazzeri  2 , James P R Schofield  2 , Paul J Skipp  2   8 , Julian A Hiscox  1   9   10 , Tristan W Clark  4   5 , Diana Baralle  3   4
Affiliations

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

Rebekah Penrice-Randal et al. Front Immunol. .

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.

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.

Keywords: COVID-19; Critical Care; RNA-seq - RNA sequencing; biomarkers; prognosis; topology; transcriptome.

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Conflict of interest statement

TC has received speaker fees, honoraria, travel reimbursement, and equipment and consumables free of charge for the purposes of research from BioFire diagnostics LLC and BioMerieux. TC has received discounted equipment and consumables for the purposes of research from QIAGEN. TC has received consultancy fees from Biofire diagnostics LLC, BioMerieux, Synairgen research Ltd, Randox laboratories Ltd and Cidara therapeutics. TC has been a member of advisory boards for Roche and Janssen and has received reimbursement for these. TC is member of two independent data monitoring committees for trials sponsored by Roche. TC has previously acted as the UK chief investigator for trials sponsored by Janssen. TC is currently a member of the NHSE COVID-19 Testing Technologies Oversight Group and the NHSE COVID-19 Technologies Validation Group. JS is a founding director, CEO, employee, and shareholder in TopMD Precision Medicine Ltd. FS is a founding director, CTO, employee, and shareholder in TopMD Precision Medicine Ltd. PS is a founding director, employee and shareholder in TopMD Precision Medicine Ltd. AG is an employee and shareholder in TopMD Precision Medicine Ltd. RP-R is an employee at TopMD Precision Medicine Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
The importance of genes in a classification of ICU admission with Random Forest. The higher the value of importance of the variable (mean decrease gini score), the higher the importance of the gene(s) in the model.
Figure 2
Figure 2
ROC analysis of the overall performance of the TopMD-defined gene signature predictive of ICU admission. ROC curve with split 62/38, using top 10 pathways with top 10 genes for a total of 79 genes overall.
Figure 3
Figure 3
Differential expression of top genes in the top 3 pathways between patients admitted to ICU and not admitted to ICU of the training set. Connections represent known gene interactions according to STRING-db. (A) SNX2 - controlling epidermal growth factor receptor (EGFR) presentation, (B) ACAA1-peak pathway, representing peroxisome proliferator-activated receptor alpha (PPAR-α) signalling, (C) FAM89B-peak pathway, mediating transforming growth factor beta (TGF-β) signalling. Pathways and genes identified by topological data analysis, TopMD.
See this image and copyright information in PMC

References

    1. Dorward DA, Russell CD, Um IH, Elshani M, Armstrong SD, Penrice-Randal R, et al. Tissue-specific immunopathology in fatal COVID-19. Am J Respir Crit Care Med (2021) 203(2):192–201. doi: 10.1164/rccm.202008-3265OC - DOI - PMC - PubMed
    1. Russell CD, Valanciute A, Gachanja NN, Stephen J, Penrice-Randal R, Armstrong SD, et al. Tissue proteomic analysis identifies mechanisms and stages of immunopathology in fatal COVID-19. Am J Respir Cell Mol Biol (2022) 66(2):196–205. doi: 10.1165/rcmb.2021-0358OC - DOI - PMC - PubMed
    1. Lal A, Erondu NA, Heymann DL, Gitahi G, Yates R. Fragmented health systems in COVID-19: rectifying the misalignment between global health security and universal health coverage. Lancet (2021) 397(10268):61–7. doi: 10.1016/S0140-6736(20)32228-5 - DOI - PMC - PubMed
    1. Liu X, Speranza E, Muñoz-Fontela C, Haldenby S, Rickett NY, Garcia-Dorival I, et al. Transcriptomic signatures differentiate survival from fatal outcomes in humans infected with Ebola virus. Genome Biol (2017) 18(1):4. doi: 10.1186/s13059-016-1137-3 - DOI - PMC - PubMed
    1. Ye W, Chen G, Li X, Lan X, Ji C, Hou M, et al. Dynamic changes of d-dimer and neutrophil-lymphocyte count ratio as prognostic biomarkers in COVID-19. Respir Res (2020) 21(1):169. doi: 10.1186/s12931-020-01428-7 - DOI - PMC - PubMed

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