Identifying biomarker signatures of prognostic value for Multisystem Inflammatory Syndrome in Children (MIS-C)

PROJECT SUMMARY / ABSTRACTIn adults, SARS-CoV-2 infection exhibits a wide range of clinical outcomes, from asymptomatic and mild diseaseto severe viral pneumonia, respiratory distress, acute kidney injury, thrombotic disorders, and serious cardiac,cerebrovascular and vascular complications. Severe infection can also occur both in children and young adults(< 21), and a significant proportion of children admitted with Covid-19 require ICU support, frequently includingmechanical ventilation. In addition, children and adolescents with initially asymptomatic SARS-CoV-2 infectionhave presented with a rare, but very severe multisystem inflammatory syndrome (MIS-C). Epidemiologic, clinicaland laboratory predictors of progression towards severe forms of acute infection with SARS-CoV-2 and MIS-Care thus urgently needed in the fight against Covid-19 in this population. As defined in the NIH RapidAcceleration of Diagnostics (RADx) program, biomarker discovery can enable risk stratification and guideinterventional studies to target Covid-19 patients at enhanced risk of developing complications and/or severedisease. To target this discovery initiative, herein we will use a battery of biological, immunological and moleculartests, including Grating-Coupled Fluorescence Plasmonic (GCFP) and advanced flow cytometry, to studychildren and young adults (<21 years) with mild, moderate or severe SARS-CoV-2 infection. GCFP allows theuse of disposable biosensor chips that can be mass-produced at low cost and spotted in microarray format togreatly increase multiplexing capabilities. In addition, we will use a similar biomarker approach for rapiddifferentiation of patients with MIS-C versus other pediatric infectious or inflammatory conditions where theclinical presentation resembles MIS-C, most importantly Kawasaki disease. A child's biologic and immunologicresponse to SARS-CoV-2 exposure is likely influenced by a variety of factors, including genetics, epigeneticsand products of the mucosa/gut-brain axis, adipose tissue and neuroendocrine immune network, and furthermodulated by environmental exposures. With these factors in mind, we hypothesize that a child's biomarkerprofile in response to SARS-CoV-2 infection enables a timely and accurate prediction of severity of Covid-19and diagnosis of MIS-C, and will help guide treatment strategies, and predict patient outcomes. To test thishypothesis, we will use a non-traditional diagnostic and comprehensive biomarker discovery to characterize theclinical and laboratory spectrum of children and adolescents with mild, moderate and severe SARS-CoV-2infection, as well as MIS-C. We will then validate our newly developed diagnostic and prognostic algorithm todistinguish MIS-C from other inflammatory disorders with overlapping clinical manifestations, including Kawasakidisease, and predict the longitudinal risk of complications.