A recent study published in the scientific journal Immunity identified potential predictive humoral immune response markers in COVID-19 patients.
The research was led by Galit Alter, PhD, group leader at the Ragon Institute of MGH, MIT and Harvard and professor of medicine at Harvard Medical School; Helen Chu, MD, associate professor of medicine, Division of Allergy and Infectious Diseases, University of Washington School of Medicine, and UW Medicine physician.
The study focused on collecting information and samples from hospitalized COVID-19 patients in order to create a detailed profile of the immune response and to compare the immune responses of the patients who survived to those who didn’t.
“Any given feature tells only a small part of the story. By looking at the overall profile of the immune response, we can begin to truly understand how the immune system responds to COVID-19 and then use that knowledge to prevent the worst outcomes of this disease,” said Alter.
COVID-19 and SARS-CoV-2 were caused by a virus composed of two main proteins – the spike (S) protein and the nucleocapsid (N) protein – that the humoral immune system, which is responsible for antibody production, responds to.
The researchers found that patients who had recovered had a humoral immune response that responded mostly to S protein, while deceased individuals had a shift in immunodominance such that they had a stronger immune response to the N protein.
“Most vaccine candidates in development are designed to elicit antibodies against spike antigen, which is the response we observed with individuals who survived natural infection,” Chu said.
“The shift in immunodominance was only apparent after comparing robust, detailed profiles of the immune response from different groups of patients,” Alter said.
According to Medical Xpress / Immunity, this immunodominance shift could be detected by measuring five immune response markers on which researchers built a model that could precisely classify clinical samples as belonging to deceased or recovered patients.
In order to verify this model, 40 clinical COVID-19 samples from Boston, 20 from recovered patients and 20 from deceased patients, were analyzed. The results of the study showed the same S protein to N protein shift in immunodominance in deceased individuals compared to recovered ones.
Furthermore, in the samples analyzed, this immunodominance shift was more predictive of recovery or death than using demographic factors such as age or sex.
“Finding these early antibody signatures may have implications for assessing COVID-19 vaccine candidates to ensure they produce an immune response similar to that of individuals who survive natural infection,” Chu said.
However, the influence of risk factors of COVID-19, time course of infection, or severity of disease on these predictive immune markers is not known.
This study provided a potential way that at-risk patients can be identified based on individual immune responses and may help the design of a future vaccine.
This study used samples from a cohort of 22 individuals, 12 of whom recovered and 10 of whom died.