NIH funds eight studies to advance rapid diagnosis of COVID-19-related inflammatory syndrome in children
The awards are from NIH’s Predicting Viral-Associated Inflammatory Disease Severity in Children with Laboratory Diagnostics and Artificial Intelligence (PreVAIL kIds) initiative.
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
