Researchers from the University of Colorado School of Medicine, along with co-workers from the UCHealth University of Colorado Hospital identified specific genetic biomarkers that reveal who is infected with COVID-19 along with providing insights into how severe the disease might be, filling a key diagnostic gap.
Image Credit: University of Colorado Anschutz Medical Campus.
I think this study is a tremendous proof-of-concept in the realm of COVID-19 testing, one that can be applied to other diseases. It’s a major move forward in the world of precision medicine.”
Kathleen Barnes, PhD, Study Lead Author and Professor, School of Medicine, University of Colorado Anschutz Medical Campus
The study indicates that certain signals from a mechanism named DNA methylation differ between those infected and those not infected with SARS-CoV-2. They can also denote the severity of the disease even in the early stages. The research was published on October 26th, 2021, in the Communications Medicine journal.
DNA methylation, vital for cell function, is an epigenetic signaling tool that cells employ to turn genes off. Any error in the mechanism can induce numerous diseases.
Barnes considers that heeding attention to these signals can help fill the required gap in the current world of COVID testing. A majority of the COVID-19 antigen or rapid tests depend on viral strains and nurture the possibility of high false-negative rates. These tests do not predict if the virus is viable and replicating, and they do not foretell clinical outcomes.
A pre-symptomatic patient might test negative for the SARS-CoV-2 virus while patients who recovered might still test positive despite no longer being infectious.
The study claims that “Accurate diagnostics are urgently required to control continued communal spread, to better understand host response, and for the development of vaccines and antivirals. Identification of which SARS-CoV-2 infected patients are most likely to develop severe disease would enable clinicians to triage patients via augmented clinical decision support.”
However, the researchers stated that they were not aware of any test that can foretell the clinical course of COVID-19.
On this basis, the researchers examined the epigenome in blood samples from individuals with and without COVID-19. The researchers achieved this by customizing a tool from Illumina known as the Infinium Methylation EPIC array to improve immune response detection. Scientists later profiled peripheral blood samples from 164 COVID-19 patients and 296 control patients.
Researchers gathered the peripheral blood DNA samples from patients at UCHealth and analyzed them for SARS-CoV-2 epigenetic signatures starting March 1st, 2020.
A majority of the blood specimens were gathered from the University of Colorado Emergency Medicine Specimen Bank under the direction of study co-author Andrew Monte, MD, Ph.D., and passed on to the Colorado Anschutz Research Genetics Organization (CARGO). Further specimens were gathered from patients who consented to the University of Colorado COVID-19 Biorepository.
The scientists identified specific genetic markers of SARS-CoV-2 infection along with implications of disease severity.
“These signals of disease progression were present from the initial blood draw when first walking into the hospital. Together, these approaches demonstrate the potential of measuring the epigenome for monitoring SARS-CoV-2 status and severity,” claims the research.
Barnes remarks that the observations can eventually lead to a novel and more precise means to test for COVID-19.
We are exploring how this platform could add value to the COVID diagnostic world. We think it adds value to knowing what patients develop more serious disease. This could tell you if you could ride out the infection or if it is likely to get worse.”
Kathleen Barnes, PhD, Study Lead Author and Professor, School of Medicine, University of Colorado Anschutz Medical Campus
Source:
Journal reference:
Konigsberg, I. R., et al. (2021) Host methylation predicts SARS-CoV-2 infection and clinical outcome. Communications Medicine. doi.org/10.1038/s43856-021-00042-y.