A framework for conducting GWAS using repeated measures data with an application to childhood BMI
Year: 2024
Type: article
Study design: Observational Study
Abstract: Genetic effects on changes in human traits over time are understudied and may have important pathophysiological impact. We propose a framework that enables data quality control, implements mixed models to evaluate trajectories of change in traits, and estimates phenotypes to identify age-varying genetic effects in GWAS. Using childhood BMI as an example trait, we included 71,336 participants from six cohorts and estimated the slope and area under the BMI curve within four time periods (infancy, early childhood, late childhood and adolescence) for each participant, in addition to the age and BMI at the adiposity peak and the adiposity rebound. GWAS of the 12 estimated phenotypes identified 28 genome-wide significant variants at 13 loci, one of which (in DAOA) has not been previously associated with childhood or adult BMI. Genetic studies of changes in human traits over time could uncover unique biological mechanisms influencing quantitative traits.
Source: Nature Communications
Authors: Kimberley Burrows, Anni Heiskala, Jonathan P. Bradfield, Zhanna Balkhiyarova, Lijiao Ning, Mathilde Boissel, Yee-Ming Chan, Philippe Froguel, Amelie Bonnefond, Hakon Hakonarson, Alexessander Couto Alves, Deborah A. Lawlor, Marika Kaakinen, Marjo-Riitta Järvelin, Struan F. A. Grant, Kate Tilling, Inga Prokopenko, Sylvain Sebert, Mickaël Canouil, Nicole M. Warrington
Institutions: University of Bristol, MRC Integrative Epidemiology Unit, University of Oulu, Children's Hospital of Philadelphia, Quantinuum (United States), University of Surrey, Imperial College London, Centre National de la Recherche Scientifique, Inserm, Université de Lille, Institut Pasteur de Lille, Boston Children's Hospital, Harvard University, MRC Centre for Environment and Health, Brunel University of London, University of Pennsylvania, The University of Queensland, Institute for Molecular Bioscience
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,068
Awards: G108234597, Accelerator Award, G1178615512, Obesity: Biological, socioCultural, and environmental risk Trajectories, G2312768730, Dynamic longitudinal exposome trajectories in cardiovascular and metabolic non-communicable diseases, G2822846613, G310833229, G3201241063, G3882732315, G3909006727, Fighting childhood obesity to stay healthy all over the life, G434337789, Using genetics to identify optimal times to intervene on early life growth and reduce future risk of cardio-metabolic disease, G4937468798, G5342329443, G6049260834, G6093732709, G6689231961, G705543216, G801210579, G8450161423, Molecular phenotyping of pulmonary hypertension
OpenAlex ID: W4404532215