Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOC) with varying capacities to evade vaccine-induced immunity continue to emerge, the latest one being the B.1.1.529 (Omicron) variant, and the coronavirus disease 2019 (COVID-19) pandemic continues to challenge the global healthcare systems despite the availability of vaccines and novel treatments.
Study: A multiplex protein panel assay determines disease severity and is prognostic about outcome in COVID-19 patients. Image Credit: Plo/Shutterstock
The study
This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources
In a recent work posted to the medRxiv* pre-print server, a team of researchers demonstrated the response of COVID-19 patients to SARS-CoV-2 using a multiplex proteomic panel assay for accurate classification of disease severity. The biomarker panel used for COVID-19 severity prediction comprised of 50 peptides, derived from 30 COVID-19 plasma proteins (severity markers), monitored in a single measurement using analytical flow rate liquid chromatography and multiple reaction monitoring (LC-MRM).
The peptide panel was developed based on the World Health Organization (WHO) ordinal scale and included plasma proteins involved in the COVID-19 host response and pathophysiology, like the innate immune response, the complement cascade, and coagulation.
Finally, the researchers tested whether native reference peptides were unique to a corresponding protein within the human proteome and found that 44 out of 50 peptides met this criterion. Eventually, all the 50 peptides met the selection criteria and were included in the peptide biomarker panel.
Findings
In a longitudinal cohort, this proteomic panel assay outperformed other established risk assessments, such as SOFA and APACHE II, in predicting the survival of COVID-19 inpatients. The assay stratified patients based on their responsiveness to novel therapeutic interventions. Upon further improvisation, this assay predicted outcomes among severely affected patients that are difficult to distinguish by clinical parameters. However, that required the selection of a peptide panel specific for stratification within the similar COVID-19 severity group.
When used for assessment on a patient-by-patient basis, the assay panel correctly identified a milder form of COVID-19 in three samples that belonged to four WHO patients with DNI (‘do not intubate’) orders in place. On the other hand, the Kaplan-Meier survival analysis plots COVID-19 outcome with respect to the time until death without distinguishing between the correct and false predictions, thus demonstrating the effectiveness of this assay panel in identifying disease severity correctly even in cases with fatal outcomes.
Discussion and Conclusions
Several past studies have highlighted the prognostic value of plasma proteomes and presented them as a promising new alternative for predicting COVID-19 severity. However, this technology is difficult to establish in clinical routine due to technical reasons, throughput, and cost.
The researchers working on this study thus chose to develop a COVID-19 biomarker panel assay on a proteomics platform that could be deployed for clinical use within existing regulatory frameworks and used broadly available laboratory equipment. They deployed triple quadrupole mass spectrometers coupled to high flow liquid chromatography as they are already widely used in other clinical areas, such as newborn screening. Also, they are widely available in a large hospital and diagnostic laboratories, regulated (e.g. CLIA) laboratories, and contract research organizations. The biomarker tests are accredited within existing regulatory standards in GCP, ISO:17025, ISO:15189, and CLIA environments.
The biomarker panel used in the study used only 5µl of plasma which could easily be collected via finger-prick microsampling, implying that remote patient monitoring at home is also possible using this method.
Furthermore, the proteomics platform used in the study can easily support rapid iteration of the biomarker panel composition if additional patient cohorts are studied and more prognostic biomarkers are discovered. The assay can predict the future course of COVID-19 disease in patients and help healthcare professionals, amid this pandemic situation, in making timely clinical decisions. Taken together, these advantages offered by the biomarker panel and the underlying analytical platform can further help provide a continuous pandemic response in addition to its utility in hospitalized patient cohorts demonstrated here.
There is an unmet clinical need for personalized tests that can capture and monitor the individual response of COVID-19 patients. According to the authors of this study, this assay could support clinical decision-making, guide the development of novel treatments, and expand the collection of risk assessment procedures for COVID-19. To conclude, the technology outlined here has the potential to identify severely ill COVID-19 patients with a good prognosis and direct them to optimal treatment and thus can bridge the gap from discovery proteomics to clinical application in COVID-19.
This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources
Article Revisions
- May 8 2023 - The preprint preliminary research paper that this article was based upon was accepted for publication in a peer-reviewed Scientific Journal. This article was edited accordingly to include a link to the final peer-reviewed paper, now shown in the sources section.
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