Predicting severity in COVID-19 disease using sepsis blood gene expression signatures

Abstract

Severely-afflicted COVID-19 patients can exhibit disease manifestations representative of sepsis, including acute respiratory distress syndrome and multiple organ failure. We hypothesized that diagnostic tools used in managing all-cause sepsis, such as clinical criteria, biomarkers, and gene expression signatures, should extend to COVID-19 patients. Here we analyzed the whole blood transcriptome of 124 early (1–5 days post-hospital admission) and late (6–20 days post-admission) sampled patients with confirmed COVID-19 infections from hospitals in Quebec, Canada. Mechanisms associated with COVID-19 severity were identified between severity groups (ranging from mild disease to the requirement for mechanical ventilation and mortality), and established sepsis signatures were assessed for dysregulation. Specifically, gene expression signatures representing pathophysiological events, namely cellular reprogramming, organ dysfunction, and mortality, were significantly enriched and predictive of severity and lethality in COVID-19 patients. Mechanistic endotypes reflective of distinct sepsis aetiologies and therapeutic opportunities were also identified in subsets of patients, enabling prediction of potentially-effective repurposed drugs. The expression of sepsis gene expression signatures in severely-afflicted COVID-19 patients indicates that these patients should be classified as having severe sepsis. Accordingly, in severe COVID-19 patients, these signatures should be strongly considered for the mechanistic characterization, diagnosis, and guidance of treatment using repurposed drugs.

Dysregulated early transcriptional signatures linked to mast cell and interferon responses are implicated in COVID-19 severity

“…A similarly- sized study of 124 participants with samples collected at two time points, 1-5 days post hospital admission and 6-20 days post admission, found upregulation of several pathways in those with severe COVID-19 disease. These pathways included neutrophil degranulation, interferon α/β/γ signalling, IL-4 and IL-13 signalling, oxidative stress and TNF-α signalling via NFκ-B a ( 48 ). They also compared the timing of sampling with disease outcome and although gene expression trajectories change over two time points taken, they found that the signatures were still significantly dysregulated between severe versus moderate COVID-19 and between those who died and those who survived.…”

Severe COVID-19 and non-COVID-19 severe sepsis converge transcriptionally after a week in the intensive care unit, indicating common disease mechanisms

“…Furthermore, long-term outcomes of both sepsis (post-sepsis syndrome) and COVID-19 (“long COVID”) share multiple neurocognitive and immune deficits ( 13 , 14 ). In addition, we recently showed that endotypes identified in a cohort of all-cause sepsis patients could also predict severity in COVID-19 patients, indicating further parallels in pathophysiology between the two diseases ( 15 , 16 ). Compared to other viral diseases such as influenza, COVID-19 generally has higher TNFα/IL-1β-associated inflammation ( 17 ) and lower interferon responses ( 18 ).…”

Differentiation of COVID-19 from other emergency infectious disease presentations using whole blood transcriptomics then rapid qPCR: a case-control and observational cohort study

“…A number of investigators have applied whole blood transcriptomics to identify predictive scores for deterioration in COVID-19 (20,(22)(23)(24)(25)(26). We did not attempt this in our cohort as the number of COVID-19 patient RNA samples that successfully underwent RNA-seq was relatively small (n=88) and all stemmed from the first (Wuhan) wave of COVID-19, prior to specific treatments being available, with limited access to intensive care or non-invasive ventilation, and at a time when inpatient mortality was very high, just under 30%.…”