dbGaP Study Accession: phs002553
NIH Institute/Center: NICHD
RADx Data Program: RADx-rad
DOI: 10.60773/vaeg-ht26
Release Date: 11/07/2022
Updated Date: 01/18/2024
Study Description: In the wake of COVID-19 pandemic, Multisystem Inflammatory Syndrome in Children (MIS-C) has evolved as a new threat to children exposed to SARS-CoV-2. The emergence of MIS-C is so new and so rapidly evolving that there are currently no diagnostic tests to identify these patients nor are there tools to predict disease progression. Through established, funded, multi-center consortia in the U.S. (CHARMS: Characterization of MIS-C and its Relationship to Kawasaki Disease funded by PCORI) and the UK (DIAMONDS), clinical data and samples were collected to support the proposed studies. First, transcript, protein and antibody datasets from children with COVID-19, MIS-C, and with other febrile illnesses were generated. These data were used to devise tests to distinguish children at risk of progression to severe COVID-19 or MIS-C and diagnostic tests to distinguish these conditions from other causes of fever in children. Continuing the established collaboration with Columbia University, the antibody repertoire against all known human coronaviruses was defined and how pre-existing antibody to other coronaviruses may shape the immune response in acute SARS-CoV-2 infection and MIS-C was determined. The first two years (R61) built on the expertise of the assembled teams to discover unique proteomic and transcriptomic patterns in MIS-C and SARS-CoV-2-infected patients and relate clinical parameters to the antibody response to coronaviral antigens profiled on peptide arrays. This work leveraged already banked plasma, serum, and RNA samples from children with COVID-19, MIS-C, Kawasaki disease and other inflammatory conditions. Rigorous Go/No-Go criteria were established and used to determine progression to the R33 phase. The final two years (R33) focused on platform development and multicenter and bi-national test validation to diagnose and predict severity in children with SARS-CoV-2 infection or MIS-C based on aptamer technology, lateral-flow protein detection, point-of-service RNA or antibody profiling with commercial partners. De-identified clinical and molecular data were deposited in the RADx-rad hub to facilitate data sharing. Many potential hurdles in this type of research have already been overcome: a) IRB-approved patient recruitment for data and samples is on-going, b) clinical samples have been banked, c) strong preliminary data has been generated on RNAseq, aptamer proteomics, and coronaviral antibody responses, and d) the teams have a strong track record of previous collaboration and productivity. The synergistic expertise of these investigative teams in this multi-center proposal provided a unique opportunity to create diagnostic and prognostic tools for children suffering from the spectrum of SARS- CoV-2 illnesses. Public Health Relevance: As the COVID-19 pandemic evolved in early 2020, case reports appeared describing children with unusual febrile illnesses with elevated inflammatory markers and multi-system involvement that is now termed Multisystem Inflammatory Syndrome in Children (MIS-C). The illness occurs weeks following exposure to SARS-CoV-2 and these children have a wide spectrum of disease severity ranging from cardiogenic shock to milder illness that can be self-limited. To address an urgent, unmet clinical need, investigative teams across three countries joined forces to discover and validate a diagnostic test to identify children with MIS-C and predict progression of disease.
Principal Investigator: Burns, Jane C
Has Data Files: Yes
Study Domain: Multisystem Inflammatory Syndrome in Children (MIS-C); Medical Device/Tool Development; Virological Testing; Multisystem Inflammatory Syndrome (MIS)
Data Collection Method: Biobank Samples
Keywords: Disease Progression; Cardiogenic Shock; Febrile Illness
Study Design: Device Validation Study
Multi-Center Study: TRUE
Study Sites: Children's Hospital Boston; Children's Hospital Colorado; Children's Hospital Los Angeles; Division of Cardiology; Children's Hospital of Orange County; Children's National Health System; Children's Hospital of Michigan; David Geffen School of Medicine at UCLA; Indiana University of School of Medicine; Joe Dimaggio Children's Hospital; Louisiana State University of Health Sciences Center; Maria Fareri Children's Hospital at Westchester Medical Center; Miller Children's Hospital; Long Beach; Nationwide Children's Hospital; Seattle Children's; Texas Children's Hospital; The Ann & Robert H. Lurie Children's Hospital of Chicago; The University of Chicago Department of Pediatrics; UAB Children's of Alabama; UC Davis Children's Hospital; UCSF Benioff Children's Hospital-Oakland/San Francisco; UPMC Children's Hospital of Pittsburgh; University of Hawaii; Kapi'olani Medical Specialists; University of Nebraska Medical Center; University of Utah Health Care; Valley Childrens Healthcare; University of California San Diego
Data Types: Clinical
Study Start Date: 01/01/2021
Study End Date: 11/30/2022
Species: Human Data
Estimated Cohort Size: 250
Study Population Focus: Children
Publication URL: https://pubmed.ncbi.nlm.nih.gov/35806225/; https://pubmed.ncbi.nlm.nih.gov/34464357/; https://pubmed.ncbi.nlm.nih.gov/34599760/; https://pubmed.ncbi.nlm.nih.gov/35350199/; https://pubmed.ncbi.nlm.nih.gov/35360001/; https://pubmed.ncbi.nlm.nih.gov/35445250/; https://pubmed.ncbi.nlm.nih.gov/35577777/; https://pubmed.ncbi.nlm.nih.gov/35732822/; https://pubmed.ncbi.nlm.nih.gov/35806225/; https://pubmed.ncbi.nlm.nih.gov/36150781/; https://pubmed.ncbi.nlm.nih.gov/34260489/; https://pubmed.ncbi.nlm.nih.gov/34261329/; https://pubmed.ncbi.nlm.nih.gov/34464357/; https://pubmed.ncbi.nlm.nih.gov/34599760/; https://pubmed.ncbi.nlm.nih.gov/35350199/; https://pubmed.ncbi.nlm.nih.gov/35360001/; https://pubmed.ncbi.nlm.nih.gov/35445250/; https://pubmed.ncbi.nlm.nih.gov/35577777/; https://pubmed.ncbi.nlm.nih.gov/35732822/; https://pubmed.ncbi.nlm.nih.gov/36150781/
Acknowledgement Statement: This study was supported through funding, 3R61HD105590-02S1, for the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) as part of the RADx-rad program. Data were obtained through the COVID-19 RADx-rad Predicting Viral-Associated Inflammatory Disease Severity in Children with Laboratory Diagnostics and Artificial Intelligence (PreVAIL kIds), sponsored under the PreVAIL kIds Program. We would like to give a special acknowledgment to our collaborators and to the participants and families that made this study possible. Approved users should acknowledge the provision of data access by dbGaP for accession phs002553.v1.p1, and the NIH RADx Data Hub. Approved users should also acknowledge the specific version(s) of the dataset(s) obtained from the NIH RADx Data Hub.
Funding Opportunity Announcement (FOA) Number: PA-20-272
NIH Grant or Contract Number(s): 3R61HD105590-02S1
Consent/Data Use Limitations: General Research Use