COVID-19 or Influenza Sepsis: Which Patient is Most Vulnerable?

A new model for understanding which patients with sepsis, COVID-19, and influenza have immune dysfunction and are more likely to suffer poor outcomes has been developed by researchers at the Wellcome Sanger Institute. The study is published in Science Translational Medicine. This study identified 19 genes that predict the way that the body’s immune system responds to sepsis, COVID-19, and influenza infection, and how immune response can go wrong in some individuals.

The small number of genes used in the model paves the way for applying precision medicine techniques, such as prioritizing individuals for particular interventions, to diseases like sepsis that have proven difficult to diagnose and treat.

Sepsis is caused by an ‘inappropriate‘ immune response to infection or injury, which can spread to the whole body. For reasons unknown, in sepsis immune response becomes overactive or underactive and causes damage to healthy cells, rather than just the source of infection.

It is difficult to predict who will get sepsis, who will recover, and who will have poor outcomes such as post-sepsis syndrome (PSS) and death. Globally, it is estimated that there are around 49 million sepsis cases and 11 million deaths each year.

Despite hundreds of clinical trials aimed at improving sepsis outcomes, there are currently no targeted treatments. Researchers believe that a stronger understanding of sepsis at the molecular level so that patients to classify it according to the particular characteristics of their illness.

Genetic Model for Sepsis and COVID-19

In this new study, researchers at the Wellcome Sanger Institute and the University of Oxford set out to develop a gene expression model for understanding which patients with sepsis are more likely to have particular responses and potentially poor outcomes.

This included 1,655 samples from sepsis patients collected as part of the UK Genomic Advances in Sepsis study, which were then sequenced at the Wellcome Sanger Institute to identify which genes were expressed.

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There is an urgent need for better ways to understand what goes wrong with the immune system in response to infection to cause sepsis, a disease with devastating results for millions of people each year around the world.

A fast, accurate test to predict who has a particular type of immune response to infection and is at greater risk from poorer outcomes in sepsis would help massively and now seems a genuine possibility.

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To gauge whether the 19-gene model could also be applied to other diseases, a machine-learning framework was developed to test it on sepsis, SARS-CoV-2, and influenza. The model was able to successfully predict an individual’s likelihood of poor outcomes for all three diseases.

The next step for the researchers will be to understand more about the underlying immune dysfunction involved in sepsis and work with colleagues to develop biomarker-led clinical trials.

This work would aim to help target the most effective therapies for those who would benefit most, for example using the type of 19-gene model developed in this study.



Source-Eurekalert