Differences in blood gene expression among patients with varying COVID-19 severity

Children's Health

Infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), but the clinical manifestations are highly variable. While some individuals remain asymptomatic, others manifest mild flu-like symptoms and some contract a severe life-threatening disease requiring mechanical ventilation and intensive care. There have been several deaths reported due to COVID-19. Why is there a difference in severity? Why do different people respond differently to the same infection?

A new study published on the medRxiv* pre-print server and currently undergoing peer-review aims to answer this question through whole blood transcriptomics of individuals with varying degrees of COVID-19 severity. Transcriptomics, done by RNA sequencing, gives insights into the genes expressed in a cell at a given time point. It gives an analysis of all RNA molecules within a cell, in this case, whole blood.

Whole blood transcriptomics

Patients with infectious diseases and inflammatory conditions have been analyzed using whole blood transcriptomic profiling. This has helped understand infectious disease dynamics and variations in the host response to different pathogens and different disease severity. It has also helped to identify the biomarkers of infection.

A few studies on whole blood transcriptomics from SARS-CoV-2 infected individuals have already been published. However, there is no data on transcriptomic profiles from individuals with varying severities of COVID-19.

The GEN-COVID project is led by Dr. F. Martinón-Torres and Dr. Antonio Salas Ellacuariaga from the Genetics, Vaccines, Infections and Pediatrics Research Group (GENVIP), Hospital Clinico Universitario de Santiago, Spain. This is a study with national and international integration, and it aims to evaluate the influence of genetic factors on SARS-CoV-2 infection. One of the project’s objectives is to study differential expression patterns in different host samples, particularly identifying transcriptomic signatures.

Study design

This study recruited adult patients with COVID-19 from the GEN-COVID study group. Participants were categorized into three groups – mild, moderate or severe disease. Patients with mild symptoms were always outpatients with emergency department attendance as the ceiling of care. Patients categorized as moderate were admitted to the hospital, and ward-based therapy was the ceiling of care with supportive care limited to oxygen delivery. Under the severe category were patients admitted to ICU at any time throughout the course of their disease. They had to be provided supportive care, including high flow oxygen, non-invasive ventilation (NIV), invasive ventilation, inotropic support, renal replacement therapy or extracorporeal membrane oxygenation (ECMO). The severe category also included the patients who died.

RNA sequencing

Whole blood was collected from the participants at the time of recruitment for RNA sequencing.

This RNA sequencing data was used to:

  1. Estimate immune cell-type fractions and compare between the three patient categories.
  2. Compare the effect of immunomodulatory treatment on the transcriptome of patients with moderate COVID-19 receiving steroids to the patients with moderate COVID-19 not receiving steroids
  3. Analyze differential expression of RNA within the COVID-19 severity groups. These were pairwise comparisons – moderate vs. mild, severe vs. mild and severe vs. moderate.
  4. Analyze pathway enrichment between the above-mentioned pairs. Pathway enrichment analysis helps to identify biological pathways enriched in the list of expressed RNAs. This gives a biological insight into the functional roles of these RNAs.

A total of 55 patients with COVID-19 were analyzed with 19 mild, 26 moderate and 26 severe disease symptoms.

Transcriptomic differences

The proportions of different immune cells like CD4 T-cells, CD8 T-cells, neutrophils, monocytes and natural killer (NK) cells were significantly different between the different pairwise severity comparisons. The B cell proportions remained the same between the groups. The levels of CD4 T-cells, CD8 T-cells and NK cells reduced with increasing severity while neutrophil estimations increased with severity.

Contrasting the severe category to either moderate or mild category also revealed the downregulation of many T-cell-related pathways.

There were considerable transcriptomic differences between patients who received steroids vs. those who did not. Therefore, immunomodulatory treatment has a significant impact on gene expression.

There was upregulation of genes and pathways related to the inflammatory immune response as the severity increased. Notably, the pathways related to neutrophil- and macrophage-mediated immunity were upregulated. Conversely, the pathways related to T cell-mediated immunity were downregulated. A lot of immune system-associated pathways were upregulated with increasing severity, particularly the inflammatory immune pathways. The pathways related to macrophage activation were identified with increasing severity. Also, immunoglobulin genes were upregulated with increasing severity.

Limitations of the study

It is possible that some of the observed differences may be due to age rather than severity. Due to the modest sample size, it is difficult to make generalizations.

Implications of the study

This study will improve our understanding of the course of the disease. It will also help identify improved treatments and aid in preventing severe COVID-19.

*Important notice

medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Journal reference:
  • Jackson H, Calle IR, Broderick C, et al. Characterisation of the blood RNA host response underpinning severity in COVID-19 patients. medRxiv. January 2021:2021.09.16.21263170. doi:10.1101/2021.09.16.21263170.

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