Mobile Menu

Biomarkers Linked to Severe COVID-19 Infection

Researchers from the CHUM Research Centre have used data-driven and hypothesis-driven approaches to identify biomarkers that have been linked to severe COVID-19 symptoms in infected patients. It is hoped that a better understanding of the disease biomarkers will enable identification of novel therapeutic targets.

The immune response and severe forms of COVID-19

Recent research has shown that the immune response plays a pivotal role in the severity of disease caused by SARS-CoV-2. Understanding the immune response generated during the course of the disease is therefore important to identify patients who are at the highest risk of serious complications and death from COVID-19, and identify novel therapeutic targets. Several risk factors for a negative clinical outcome have been identified. However, the mechanisms of effective and impaired immune responses to SARS-CoV-2 remain unclear.

Age, obesity, and cardiovascular comorbidities such as high blood pressure and diabetes significantly increase the risk of severe forms of COVID-19. Notably, all of these risk factors are associated with alterations in the immune response and a state of chronic low-grade inflammation. Identified dysregulations of the immune profile in SARS-CoV-2-infected hospitalised patients include increased levels of circulating IL-6 and decreased peripheral lymphocytes/neutrophils ratio, which are predictive of worse clinical outcome. There is also accumulating evidence that suggests hyperactivation and exhaustion of different T and B cells subsets characterise COVID-19 infection. More specifically, a state of activation of CD4+ T cells with an increased CD4+/CD8+ ratio has recently been linked to COVID-19 severity.

However, it is not yet known whether the reported immune alterations are specific to SARS-CoV-2 infection or are triggered by a range of acute illnesses. Therefore, the researchers behind this study performed characterization of circulating innate and adaptive immune cells. Their dataset contained 50 COVID-19 patients, 22 patients hospitalised for other acute illnesses and 49 healthy controls (HC).

Approaches to identify biomarkers linked to severe COVID-19 infection

The researchers used two approaches to identify dysregulations in immune cell subsets that are associated with acute SARS-CoV-2 infection and non-COVID-19 related acute illnesses. The first approach was data-driven, using the Phenograph and FlowSOM algorithms to cluster similar cells. This data-driven approach was used to show common and distinct alterations in immune cell populations in SARS-CoV-2 positive and negative hospitalised patients. The second approach was hypothesis-driven analysis with a conventional manual gating strategy. This was used to corroborate the observations identified in the data-driven approach. The hypothesis-driven approach generated heatmaps showing the median frequency of immune cell populations identified as significantly altered in SARS-CoV-2 positive and negative patients

Using these combined approaches, the researchers identified 21 cell clusters in the monocyte and neutrophil gate, 31 cell clusters in the monocyte and lymphocyte gates, and 18 cell clusters in the monocyte and lymphocyte gate. The distribution of clustered populations, as illustrated by the Uniform Manifold Approximation and Projection (UMAP) algorithm, showed distinct populations and relative abundances of the subsets in the blood samples.

Therapeutic potential of understanding biomarkers linked in COVID-19 infection

As mentioned previously, understanding the specific immune responses associated with SARS-CoV-2 infection is essential for the development of targeted therapies. The researchers identified specific differences in myeloid and lymphocyte subsets that are associated with SARS-CoV-2 status, as shown in figure 1; for example, elevated proportions of ICAM-1+ mature/activated neutrophils, ALCAM+ monocytes, and CD38+CD8+ T cells. A subset of the SARS-CoV-2-specific immune alterations were found to be correlated with disease severity, disease outcome at 30 days and mortality.

Overall, their study provides the foundations to develop specific peripheral blood biomarkers to identify SARS-CoV-2+ patients who are at risk of an unfavourable outcome and identify candidate molecules as potential therapeutic targets. From a clinical perspective, the similarities that these researchers uncovered between the immune profiles of SARS-CoV-2 positive, and SARS-CoV-2 negative patients suggests that therapeutics targeting general non-specific inflammatory processes could be tested in multiple severe acute illnesses when lymphopenia and neutrophilia are observed, especially in older patients. Previous studies have shown that some therapies used to treat sepsis could be applied to COVID-19, specifically steroids in severe COVID-19.

Figure 1 Taken directly from the article. Comparison of frequencies of immune cell populations in the peripheral blood of hospitalised patients. The red arrow indicates increased frequencies, the green arrow equals decreased frequencies and the yellow arrow indicates comparable frequencies of immune cells in the blood of SARS-Cov-2 positive and negative patients, severe vs. moderate, unfavourable vs. good outcome, and decreased patients vs. survivors.

Biomarkers linked to severe COVID-19

Using data-driven and hypothesis-driven approaches, the researchers behind this study were able to identify biomarkers associated with unfavourable outcomes in COVID-19 patients. These biomarkers could represent relevant potential therapeutic targets, which needs to be explored further. In particular, PD-1 on CD4+ T cells, and ICAM-1 and ALCAM on neutrophils and antigen presenting cells. Finally, their longitudinal studies identified markers that could predict worse outcome and correlate with medical complications and mortality.

Image credit: kjpargeter – FreePik

More on these topics

Biomarkers / Covid-19 / data analysis

Share this article