Oxford BioDynamics has published the results of a biomarker discovery programme supporting the development of its qPCR EpiSwitch Covid-19 Severity Test.
The top 50 immune-related markers showed good separation of mild and severe outcomes, with an accuracy of 92%.
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EpiSwitch is a well-established 3D genomics platform used by pharmaceutical and clinical research teams for patient stratification in prognostic, predictive and early diagnostic applications for immune-oncology, autoimmune and neurodegenerative indications.
The prognostic test is now being adapted to identify high-risk individuals who are likely to experience severe complications requiring intensive care unit (ICU) support if exposed to the SARS-CoV-2 virus.
Oxford BioDynamics used the EpiSwitch biomarker discovery array to analyse blood from a global cohort of Covid-19 patients.
Over one million data points across the whole genome were generated for each patient and used to identify the most informative EpiSwitch markers that were associated with different severities of Covid-19 outcomes.
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By GlobalDataThe biomarker analysis has confirmed earlier independent observations about important Covid-19-related pathways.
These pathways link together dysregulations in innate and adaptive immunity, olfactory receptors, ACE2, hypoxia, calcium signalling and blood clotting.
University of Oxford biochemistry professor Jane Mellor said: “I am encouraged that the 3D genomic biomarkers shown by this data to define Covid-19 severity of response are also tightly associated with distinct known clinical outcomes – they make sense. This is another illustration of how fundamental genome architecture regulation is. OBD’s EpiSwitch technology has great potential, both as a Covid-19 prognostic test and to continue improving our understanding of this deadly disease.”
Oxford BioDynamics is now validating the 3D genomic markers discovered in this work as a deployable qPCR test, the EpiSwitch Covid-19 Severity Test (CST).
The test will help assess an individual’s level of risk to help predict which adults would most likely require critical care should they become infected with the virus. It has the potential to be applied by physicians for risk evaluation, including of individuals free of infection or early in the infection cycle.
The EpiSwitch CST could also become a tool to support informed lifestyle choices and workplace strategies.
The biomarker discovery programme has been supported by an international group of experts in the UK and US, including West Hertfordshire NHS Trust, the Universities of Oxford and East Anglia, and Oregon Health & Science University.
Biomarkers are being used by many researchers to try and predict Covid-19 severity.
In January, the US National Cancer Institute and National Institute of Biomedical Imaging and Bioengineering announced that they would be entering into a Phase II study to advance physIQ’s artificial intelligence (AI)-based digital biomarker development for Covid-19.
