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.
【저자키워드】 COVID-19, Biomarkers, Critical care, Prognosis, Transcriptome., Topology, RNA-seq - RNA sequencing, 【초록키워드】 Treatment, Transcriptome, COVID-19 pandemic, hospital, intensive care unit, RNA, outcomes, Cohort, RNA-Seq, ROC, Whole blood, healthcare, RNA sequencing, Patient, ICU admission, pathway, Alpha, receptor, EGFR, prognostic, information, resource, First wave, expression, Admission, Blood, TGF-β, Healthcare system, Predictive, transforming growth factor, individual, naïve, growth factor, gene expression signature, gene signature, peroxisome, topological data analysis, hospitalised, was measured, defined, tested, predicted, activated, epidermal, patients with COVID-19, with COVID-19, 【제목키워드】 Gene Expression, intensive care, Admission, predict, hospitalised patient, with COVID-19,