Protein expression signatures may reveal classifiers of COVID-19 severity


  • Heather Mason
  • Univadis Medical News
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Low-cost high-throughput, high-precision mass spectrometry proteomics has identified 27 potential biomarkers differentially expressed depending on the severity of COVID-19, according to a study in Cell Systems.

Validated against healthy controls and independent patients, the primary exploratory cohort of 31 COVID-19 patients hospitalised in Berlin, Germany, was used to identify clinical classifiers, candidate biomarkers, and potential targets that picture the host immune response, specific to a SARS-CoV-2 infection.

The biomarkers associated several proteins with COVID-19 severity not previously associated with the infection and host response. Protein expression signatures were identified that could classify COVID-19 patients according to World Health Organisation (WHO) grading, introduced as of April 2020.

The biomarkers highlighted the role of complement factors, the coagulation system, inflammation modulators, and pro-inflammatory upstream and downstream of interleukin 6 and identified prognostic markers for COVID-19.

In two patients with different proteomic signatures, one was misdiagnosed and was actually suffering from Influenza B, and the other case revealed a strong comorbidity caused by anti-cancer chemotherapy. No current clinical test revealed this situation.

The development of routine proteomic assays can aid clinical decision making and generate hypotheses about potential COVID-19 therapeutic targets, at a cost of less than €10 per sample.

 

"As an exception during this period of health crisis, some of the publications mentioned are at the time of writing still in pre-publication, undergoing peer review and subject to change. The results of this pre-print study should be interpreted with utmost caution."