In our study, we used a comprehensive proteomics approach to measure a large number of proteins in plasma of COVID-19 patients with moderate and severe disease. Our study reports, in addition to large proteomics data from COVID-19 patients, several important findings.
First, age and sex have been reported as important factors predisposing to COVID-19 severity[17–21] and our results are in concordance with the reports that age is an important determinant from COVID-19 severity. Although, concentrations of 327 proteins were significantly correlated with age in our cohort, 21% also showed a correlation with disease severity even after correcting for age suggesting their role in influencing disease severity across different adult patient age categories. This includes proteins such as KRT19, VSIGA, TNFRSF10B and FASL.
Second, we identified 218 proteins that are significantly different between severe and moderate COVID-19 disease. It is important to validate how many of these proteins are also associated with COVID-19 severity in independent studies. In this context, a recent study has compared five different studies that applied the Olink affinity proteomics platform to analyse the proteomic profile between COVID-19 patients and controls[7]. Thirteen proteins out of 253 tested were consistently associated to COVID-19 susceptibility in all studies: CCL16, CCL7, CXCL10, CCL8, LGALS9, CXCL11, IL1RN, CCL2, CD274, IL6, IL18, MERTK, IFNg, and IL18R1. The authors hypothesize that the heterogeneity of the studies might be due to the difference in the disease severity of the patients and the difference in comorbidities in the controls included in the studies. Nevertheless, six of those proteins were also differentially regulated in our study of COVID-19 severity (CCL7, LGALS9, CD274, IL6, MERTK, IL18R1), suggesting that their dysregulation is associated with disease severity.
When we focus on COVID-19 severity, comparing studies is even more challenging, as the severity of the disease was classified using different indicators. For example, in the US cohort study[6], the patients were classified based on an acuity level defined by the authors, while we used the WHO clinical progression score. To overcome this difference, in this study we focused only on groups that matched our established criteria for defining severity (oxygen requirement). Hence, out of the 306 individuals included in the US cohort, we limited out analysis to 174 individuals. This also allowed us to have comparable sample sizes. Moreover, in our cohort 68.5% of the patients required oxygen, while in the US cohort were 76.4%. Even with this comparable sample size and definition of severity, we only replicated 8.6% of the proteins identified in our cohort using the US cohort. It is important to note that we only identified 31 proteins differentially regulated in the US cohort, while 221 were dysregulated in our cohort. This result suggests that COVID-19 patient cohorts are extremely heterogeneous and large-scale population-specific biomarker studies might be helpful useful to explain this heterogeneity.
Third, our analysis on identifying endotypes within the European cohort identified significantly different protein signatures between patients. The fact that we used a large number of proteins, instead of a specific panel with limited number of proteins, provided this resolution to identify subtypes of patients. Patients belonging to cluster 3 in our analysis were characterized by extreme severity and proteins associated with this cluster were enriched for many pathways including 45 pathways not identified based on the WHO-score. Among these pathways we observed the Complement and coagulation cascades, RIG-I-like receptor signaling and IL-17 signaling pathway which have extensively been described in COVID-19 literature. Interestingly these pathways were not among the significant pathway using the WHO score, suggesting patient clusters based on the proteome reduce the heterogeneity and therefore increase the sensitivity to detect more specific pathways. Although, it still needs to be investigated how proteins involved in pathways regulating pluripotency of stem cells and phosphatidylinositol signaling system, determine the incidence of respiratory failure and mortality, it is an important finding.
Finally, we validated the set of proteins for the identification of the Covid-19 endotypes and the endotypes in the US COVID-19 cohort. We identified three clusters with different degrees of severity and levels of clinical parameters indicating organ damage, inflammation and coagulation problems. These results indicate that the identified endotypes can be extrapolated to other populations and cohorts.
The main strength of this study is that it does not limit to the critically ill patients hospitalized in the ICU, but it is focusing on the clustering of patients hospitalized in the general wards without and with need of oxygen well before critical illness develops. A study using the Explore panel to investigate the plasma proteome profile of COVID-19 patients with mild to moderate symptoms has been performed by Zhong et al.[8] Their study focused on comparing the protein profile of the patients at the time of diagnosis and 14 days later, identifying 239 differentially regulated proteins. Although the authors focused on a less severe group of patients, in which only 4% of their cohort had breathing issues, they observed that most proteins are elevated or down-regulated in a similar way as in the US COVID-19 cohort which includes severe cases (76.4% required oxygen).