Study Information

dbGaP Study Accession: phs002781

NIH Institute/Center: NICHD

RADx Data Program: RADx-rad

DOI: 10.60773/8yrw-qt94

Release Date: 07/21/2022

Study Description: SARS-CoV-2 infection exhibits a wide range of clinical outcomes in both children and adults, from asymptomatic and mild disease to severe viral pneumonia, ARDS, acute kidney injury, thrombotic disorders, and serious cardiac, cerebrovascular and vascular complications. It is now known that severe infection can occur both in young children and young adults (<21) and that nearly 40% of those who are admitted Covid-19 require ICU support, including mechanical ventilation. One of the most severe manifestations of SARS-CoV-2 infection is the multisystem inflammatory syndrome in children (MIS-C), a serious condition associated with severe inflammation with multi-organ involvement that can result in a variety of clinical presentations including pneumonia, sepsis, coagulation abnormalities, and renal/kidney failure. Thus, novel approaches for early and accurate diagnosis of COVID-19 associated syndromes and evaluation of clinical severity and outcomes of COVID-19 disease in children were urgently needed. This study identified RNA transcriptomic and cell-free DNA omics biomarkers that were used to develop and validate host-based assays from nasal swab and blood samples, with the goal of regulatory submission for FDA Emergency Use Authorization (EUA).

Updated Date: 01/18/2024

Principal Investigator: Chiu, Charles Yen

Has Data Files: Yes

Study Domain: Multisystem Inflammatory Syndrome (MIS); Diagnostic Testing; Medical Device/Tool Development; Multisystem Inflammatory Syndrome in Children (MIS-C)

Data Collection Method: Molecular (Nucleic Acid/PCR) Testing Device

Keywords: Pediatric; RNA Transcriptomic and Cell-free DNA Omics Biomarkers

Study Design: Longitudinal Cohort

Multi-Center Study: TRUE

Study Sites: Emory University; Children's National Research Institute; Cornell University

Data Types: Electronic Medical Records; Clinical; Genomic; Imaging; Individual Sequencing; Metagenomic; Questionnaires/Surveys

Study Start Date: 01/01/2021

Study End Date: 11/30/2022

Species: Non-Human Data; Human Data

Estimated Cohort Size: 800

Study Population Focus: Children; Adults

Publication URL: https://pubmed.ncbi.nlm.nih.gov/33521749/; https://pubmed.ncbi.nlm.nih.gov/34889874/; https://pubmed.ncbi.nlm.nih.gov/35396471/; https://pubmed.ncbi.nlm.nih.gov/36134603/; https://pubmed.ncbi.nlm.nih.gov/37279751/; https://pubmed.ncbi.nlm.nih.gov/34348808/

Acknowledgement Statement: This study was supported through funding, 4R61HD105618-02, for the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) as part of the RADx-rad program. We would like to acknowledge our collaborators who made subjects and samples available to this dataset: University of California, San Francisco (Drs. Charles Chiu, Charlotte Hsieh, and Theodore Ruel) Children’s Hospital of Atlanta / Emory University (Dr. Christina Rostad) Children’s National Medical Center (Drs. Roberta DeBiasi and Meghan Delaney). We acknowledge support from PIs Chiu, De Vlaminck, Rostad, and DeBiasi and from the US Centers for Disease Control and Prevention (CDC) (contract 75D30121C10991 to Chiu, PI). Approved users should acknowledge the provision of data access by dbGaP for accession phs002781.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: RFA-OD-20-023

NIH Grant or Contract Number(s): 4R61HD105618-02

Consent/Data Use Limitations: General Research Use

Data Files
Total Files: 5
Data Files: 3
Metadata Files: 1
Dictionary Files: 1
Study Datasets Table
File Name
File Type
File Format(s)
# of Records
# of Variables
Metadata
Dictionary
rad_023_618-01_UCSF_CDES_DATA_transformcopy.csvTabular Data - Harmonizedcsv1035

rad_023_618-01_UCSF_DATA_transformcopy.csvTabular Data - Harmonizedcsv701

rad_023_618-01_UCSF_DATA_origcopy.csvTabular Data - Non-harmonizedcsv768