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Modelling longitudinal BMI and height over childhood for GWAS
Safe People
University of Bristol
Academic Institute
Kimberley BurrowsProfessor Debbie LawlorProfessor Sylvain SebertDr. Nicole WarringtonDr Mickaël CanouilDr. Anni HeiskalaDr Jonathan Bradfield
Safe Projects
B3785
GWAS have been enormously successful in uncovering novel genetic variants associated with a range of complex human diseases, but the majority have used cross-sectional data and relatively simplistic statistical tests. Longitudinal studies are advantageous for investigating genetic associations as they: 1) facilitate the detection of genetic variants that influence change in a trait over time; and 2) allow the detection of genes that are associated with the age of onset of a trait. Improving analytic techniques for conducting longitudinal GWAS offers the opportunity to advance our understanding of the aetiology of health and disease.
To contribute to the wider understanding of the genetic contribution to growth throughout childhood and adolescence. This work will not only potentially contribute novel findings to help understand wider mechanisms involved in child growth, but will also contribute to designing and implementing efficient methodologies for genetic studies of longitudinal trait analysis.
17/05/2021