A Multicentric, Longitudinal study on measurement of Immune Responses in Multisystem Inflammatory Syndrome in Children (MIS-C)
Title of the Project: A Multicentric, Longitudinal study on measurement of Immune Responses in Multisystem Inflammatory Syndrome in Children (MIS-C)
Duration: 2 years
Funded by: Indian Council of Medical Research
Brief Description of the Project:
Background: Multisystem inflammatory syndrome in children (MIS-C) is a hyperinflammatory condition that is being reported in regions with receding SARS-CoV-2 infection peaks. The pathophysiology of MIS-C has not been explored much. Here, in such cases we will be profiling aberrant immune activation and its alteration with therapy.
Novelty: Measuring plasma levels of a broad range of pro-inflammatory biomarkers may not only help in understanding the pathophysiology of MIS-C but also differentiate it from similar hyperinflammatory conditions like Kawasaki disease. None of the prior studies have looked at the cytokine responses before and after the therapeutic intervention. Also, deeper immunophenotyping is required in different geographies where comorbidities and genetic background differ and may have a role to play in the prognosis. There is a dearth of Indian data on immune responses in MIS-C.
Objective of the study: To measure the immune responses in MIS-C patients at two time points, before and after therapeutic intervention and compare it with the control groups.
Methods: Study and control subjects in the age group 0 -19 years, fulfilling the inclusion and exclusion criteria will be enrolled. After a detailed clinical evaluation, the following tests will be done:
a. ELISA to detect IgG antibodies against SARS-CoV-2 virus
b. Surrogate assay for the detection of SARS-CoV-2 neutralizing antibodies
c. Soluble C5b-9 assay by ELISA
d. Proinflammatory biomarkers multiplex assay
Expected outcome: Plasma cytokines and other biomarkers, sC5b-9 and anti SARS-CoV-2 IgG and neutralizing antibody levels along with clinical correlation may help diagnose and differentiate MIS-C from other conditions with overlapping clinical features like Kawasaki disease. It may also help in the prognostication. Assessing a wider range of biosignatures may also give a better understanding of the pathophysiology of this hyperinflammatory condition.