NIH Funds Eight Studies to Uncover Risk Factors for COVID-19-Related Inflammatory Syndrome in Children

The National Institutes of Health has awarded eight research grants to develop approaches for identifying children at high risk for Multisystem Inflammatory Syndrome in Children (MIS-C), a rare and severe after-effect of COVID-19 or exposure to the virus that causes it. Up to $20 million will be provided for the projects over four years, pending the availability of funds.

“These awards underscore NIH’s commitment to identifying children at risk for MIS-C, which will inform development of interventions to improve their health outcomes,” said Diana Bianchi, MD, director of NIH’s Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD). NICHD and the National Heart, Lung, and Blood Institute lead the NIH-wide effort to understand the SARS-CoV-2 spectrum of illness among children.

In most cases, children exposed to or infected with SARS-COV-2, the virus that causes COVID-19, will not develop any symptoms or will develop only a mild illness. Some children become seriously ill at the time of infection. Others who initially have no symptoms may go on to develop MIS-C(link is external), a severe, sometimes fatal, condition marked by inflammation of one or more organs, including the heart, lungs, kidneys, brain, skin, eyes and gastrointestinal tract.

The NIH awards will fund studies enrolling children with diverse geographic, racial and ethnic backgrounds across 30 U.S. States, Canada, the U.K. and South America. The studies will explore how genetic, immune, viral, environmental, and other factors influence the severity of COVID-19 in children and the chances of progression to MIS-C and other long-term complications. The awards come from NIH’s Predicting Viral-Associated Inflammatory Disease Severity in Children with Laboratory Diagnostics and Artificial Intelligence (PreVAIL kIds) initiative. These awards are part of the Rapid Acceleration of Diagnostics (RADx) Radical (RADx-rad) program to support new, non-traditional approaches and reimagined uses of existing tools to address gaps in COVID-19 testing and surveillance.

The new awards will evaluate genes, immune system proteins, and other biomarkers, examine how the virus interacts with the body and how the immune system responds to it. These studies will rely on artificial intelligence and machine learning to interpret the data they acquire, to understand risk factors underlying the severity of COVID-19 and MIS-C.

The awardees and project names are as follows:

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
A data science approach to identify and manage MIS-C associated with SARS-CoV-2 infection and Kawasaki disease in pediatric patients

Ananth V. Annapragada, Baylor College of Medicine, Houston
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 multi neural 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

Source: National Institutes of Health (NIH):

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