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COVID-19 Precision Health Genomics for Children: A Multiomic Study of the ABCCC (Alberta Childhood COVID-19 Cohort)

Status: 
Active
Competition: 
COVID-19 Regional Genomics Initiative
Sector: 
Health
Genome Centre(s):
Genome Alberta
Project Leader(s):
Francois Bernier (University of Calgary), Jim Kellner (University of Calgary)
GE3LS: 
No
Fiscal Year Project Launched: 
2020-2021
Project Description: 

Children may well hold the key to unlocking some of the mysteries of the asymmetric severity of the SARS-CoV2 virus pandemic. Despite a lower incidence of severe disease (e.g. COVID-19) in young people compared to adults, learning more about children's experiences with this coronavirus will serve to answer key questions:• How do children fit in the chain of transmission of COVID-19?• What proportion of children have asymptomatic infections, and how many of these are contagious?• Why do so few children have symptomatic disease?• Are there biological differences in the response of children to COVID-19 that may shed light on ways to better combat the effect seen in adults?• Are there genetic or other differences between children who have severe and mild infections? Working in concert with Alberta Health Services Public Health Officers, leading clinicians and Alberta Public Laboratories, the team will recruit the Alberta Childhood COVID-19 Cohort (ABCCC), consisting of all children under the age of 18 who undergo testing for the SARS-COV2 virus. This proposal represents the laboratory science arm of the ABCCC study and brings together some of Alberta’s leading experts in infectious diseases, immunology, virology, genomics and public health. Specifically, the project will 1) assess the role of children’s immune response, as well as their genetic makeup, in order to determine risk factors for severe illness and gain insight into targeted treatments, and 2) study the epidemiology of pediatric COVID-19 infections by reading the viral genome to determine the origin and transmission patterns in Alberta of pediatric COVID-19 infections. We will use advanced data science and artificial intelligence methods to develop data-driven and precision COVID-19 risk prediction models and treatment decision tools. We aim to contribute to the global pandemic research call by 1) developing actionable novel tests for risk prediction and targeted therapeutic strategies, 2) a legacy resource of clinical information, biological data and samples that will enable future research, and 3) valuable data on Alberta transmission patterns and the impact of suppression policies.