When coronavirus disease 2019 (COVID-19) first spread worldwide, many hospitals were overwhelmed with new patients, and the lack of drugs designed to treat coronavirus diseases became immediately apparent. Many countries were forced to enact costly and restrictive lockdowns, and it was not until a series of vaccines were developed that these were able to be lifted.
Study: Plasma Proteome Fingerprints Reveal Distinctiveness and Clinical Outcome of SARS-CoV-2 Infection. Image Credit: stockklemedia/Shutterstock
However, many new variants show the ability to evade both vaccine-induced and natural immunity, and the need for new anti-COVID-19 drugs remains prevalent. In a study published in Viruses, researchers from the Charité—Universitätsmedizin in Berlin have examined the difference in protein levels in COVID-19 patients.
The researchers examined aliquots of standard of care samples taken from patients when they presented themselves to the emergency departments. Commercially available proximity extension assays were used to determine the plasma levels of the different proteins, and the final results were examined using principal component analysis.
In total, the researchers examined the data from 141 patients at the emergency department. These were split into those with negative severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) test results but symptoms similar to COVID-19, patients with positive SARS-CoV-2 test results that did not require hospitalization, and patients with positive SARS-CoV-2 test results that did require hospitalization.
These groups had roughly equal numbers, with slightly more positive test results and hospitalization. Within this group, 24 went to the ICU, 16 were ventilated, 6 experienced TE, and seven died. The groups showed no significant difference regarding sex or comorbidities.
Upon admission, the data showed no major difference in clinical parameters when comparing symptomatic non-COVID patients compared to hospitalized and non-hospitalized patients. However, standard of care parameter (CRP), procalcitonin (PCT), and lactate dehydrogenase (LDH) differed slightly. The comparison of hospitalized and non-hospitalized COVID-19 patients found significantly higher LDH, CRP, Troponin T (TNT), and lower glomerular filtration rates (eGFRs) among the hospitalized patients cadre.
When exploring the levels of plasma proteins circulating, the researchers identified 177 individual proteins that could be informative. Only 14 of these mostly inflammatory proteins (CXCL10, CXCL11, CXCL5, Gal-9, INF-gamma, IL-18, IL-18R1, LIF-R, MCP-2, MCP-3, MERTK, MMP-1, PD-L1, and TNF) differed significantly between COVID-19 patients and symptomatic non-COVID-19 patients. The scientists suggest that this shows pathogenomic proteome changes triggered by the disease and highlights the relatively low number of changes.
Following this, they examined the differences in protein levels between discharged and hospitalized COVID-19 patients. The section of significantly elevated proteins in hospitalized patients included markers of cellular degradation and hormones and proteins known to interact with viruses. These included ADM, CTSL1, HGF, IL-27, IL-6, KIM1, MERTK, MMP-1, MMP-12, OPG, TNFRSF10A, and TRAIL-R2.
Further narrowing their analyses, the researchers examined the difference in response to the clinical outcomes of the hospitalized group, concentrating on those who required admittance to the ICU, died, needed mechanical ventilation, or experienced TE. In the ICU patients, the levels of CCL23, IL6, MCP-1, MCP-3, PD-L1, and TRAIL-R2 were significantly higher. In patients that required ventilation, the levels of DCN, IL6, MCP-1, MCP-3, and TRAIL-R29 were significantly higher. Levels of ADM and LPL were both strongly associated with death.
Finally, the researchers combined these results into a predictive model, selecting five of the proteins that they viewed as the most discriminatory for hospitalized patients. They decided that ADM, IL-6, MCP-3, TRAIL-R2, and PD-L1 were the most effective at predicting ICU treatment, TE, ventilation, and death, and following principal component analysis separated these further. ADM, IL-6, and TRAIL-R2 were most effective at predicting hospitalization, and all markers tended to increase in patients that died during their hospitalization.
The authors highlight that the model they have created, alongside the in-depth analysis, describes the phenotype of specific physiologies of COVID-19 and determines the difference in the protein landscape between those with similar symptoms and those infected SARS-CoV-2. They show that these proteins can predict the clinical outcome with reasonable accuracy.
The proteomic fingerprinting could help identify patients at risk of cytokine storm, helping healthcare workers protect the most at-risk individuals, and identify a series of other markers associated with specific clinical events, opening the way for the creation of tests that could allow treatment to be more personalized. These markers could also be potential therapeutic targets, and this study could help identify areas for drug manufacturers to focus on.