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Modelling longitudinal BMI and height over childhood for GWAS

Safe People

Organisation name

University of Bristol

Organisation sector

Academic Institute

Applicant name(s)

Kimberley BurrowsProfessor Debbie LawlorProfessor Sylvain SebertDr. Nicole WarringtonDr Mickaël CanouilDr. Anni HeiskalaDr Jonathan Bradfield

Safe Projects

Project ID

B3785

Lay summary

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.

Public benefit statement

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.

Latest approval date

17/05/2021