The National Institutes of Health has awarded eight research grants to refine new technologies for early diagnosis of severe illnesses resulting from SARS-CoV-2 infection in children. The new awards follow grants issued in 2020 to foster methods for diagnosing children at high risk for Multisystem Inflammatory Syndrome in Children (MIS-C), a rare, severe and sometimes fatal after-effect of SARS-CoV-2 infection or exposure in children.
The new awards will allow researchers to continue their efforts to develop ways to rapidly diagnose MIS-C and identify those at risk for serious and long-term effects of SARS-CoV-2. Earlier identification of those most at risk will allow for earlier interventions to prevent severe health effects.
Awardees:
- Jane C. Burns, University of California, San Diego Diagnosing and predicting risk in children with SARS-CoV-2-related illness
- Cedric Manlhiot, Johns Hopkins University, Baltimore Data science approach to MIS-C identification and management associated with SARS
- Ananth V. Annapragada, Baylor College of Medicine, Houston AICORE-kids: Artificial intelligence COVID-19 risk assessment for kids
- Audrey R. Odom John, Children’s Hospital of Philadelphia Diagnosis of MIS-C in febrile children
- Usha Sethuraman, Central Michigan University, Mount Pleasant Severity predictors integrating salivary transcriptomics and proteomics with multineural network intelligence in SARS-CoV2 infection in children
- Juan C. Salazar, Connecticut Children’s Medical Center, Hartford Identifying biomarker signatures of prognostic value for MIS-C
- Charles Yen Chiu, University of California, San Francisco Discovery and clinical validation of host biomarkers of disease severity and MIS-C with COVID-19
- Lawrence Kleinman, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey COVID-19 network of networks expanding clinical and translational approaches to predict severe illness in children
