A framework for conducting GWAS using repeated measures data with an application to childhood BMI
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-va...
Saved in:
| Main Authors: | , , , , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-11-01
|
| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-024-53687-3 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850129140300120064 |
|---|---|
| author | 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 |
| author_facet | 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 |
| author_sort | Kimberley Burrows |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-28fab4a6a11341f3a0e4eff51ab735a7 |
| institution | OA Journals |
| issn | 2041-1723 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-28fab4a6a11341f3a0e4eff51ab735a72025-08-20T02:33:06ZengNature PortfolioNature Communications2041-17232024-11-0115111810.1038/s41467-024-53687-3A framework for conducting GWAS using repeated measures data with an application to childhood BMIKimberley Burrows0Anni Heiskala1Jonathan P. Bradfield2Zhanna Balkhiyarova3Lijiao Ning4Mathilde Boissel5Yee-Ming Chan6Philippe Froguel7Amelie Bonnefond8Hakon Hakonarson9Alexessander Couto Alves10Deborah A. Lawlor11Marika Kaakinen12Marjo-Riitta Järvelin13Struan F. A. Grant14Kate Tilling15Inga Prokopenko16Sylvain Sebert17Mickaël Canouil18Nicole M. Warrington19MRC Integrative Epidemiology Unit at the University of BristolResearch Unit of Population Health, University of OuluCenter for Applied Genomics, Children’s Hospital of PhiladelphiaDepartment of Clinical and Experimental Medicine, School of Biosciences, University of SurreyUniv Lille, INSERM/CNRS UMR1283/8199, EGID, Institut Pasteur de Lille, Lille University HospitalUniv Lille, INSERM/CNRS UMR1283/8199, EGID, Institut Pasteur de Lille, Lille University HospitalDivision of Endocrinology, Department of Pediatrics, Boston Children’s HospitalUniv Lille, INSERM/CNRS UMR1283/8199, EGID, Institut Pasteur de Lille, Lille University HospitalUniv Lille, INSERM/CNRS UMR1283/8199, EGID, Institut Pasteur de Lille, Lille University HospitalCenter for Applied Genomics, Children’s Hospital of PhiladelphiaSchool of Biosciences and Medicine, University of SurreyMRC Integrative Epidemiology Unit at the University of BristolDepartment of Clinical and Experimental Medicine, School of Biosciences, University of SurreyResearch Unit of Population Health, University of OuluCenter for Applied Genomics, Children’s Hospital of PhiladelphiaMRC Integrative Epidemiology Unit at the University of BristolDepartment of Clinical and Experimental Medicine, School of Biosciences, University of SurreyResearch Unit of Population Health, University of OuluUniv Lille, INSERM/CNRS UMR1283/8199, EGID, Institut Pasteur de Lille, Lille University HospitalInstitute for Molecular Bioscience, University of QueenslandAbstract 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.https://doi.org/10.1038/s41467-024-53687-3 |
| spellingShingle | 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 A framework for conducting GWAS using repeated measures data with an application to childhood BMI Nature Communications |
| title | A framework for conducting GWAS using repeated measures data with an application to childhood BMI |
| title_full | A framework for conducting GWAS using repeated measures data with an application to childhood BMI |
| title_fullStr | A framework for conducting GWAS using repeated measures data with an application to childhood BMI |
| title_full_unstemmed | A framework for conducting GWAS using repeated measures data with an application to childhood BMI |
| title_short | A framework for conducting GWAS using repeated measures data with an application to childhood BMI |
| title_sort | framework for conducting gwas using repeated measures data with an application to childhood bmi |
| url | https://doi.org/10.1038/s41467-024-53687-3 |
| work_keys_str_mv | AT kimberleyburrows aframeworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT anniheiskala aframeworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT jonathanpbradfield aframeworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT zhannabalkhiyarova aframeworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT lijiaoning aframeworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT mathildeboissel aframeworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT yeemingchan aframeworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT philippefroguel aframeworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT ameliebonnefond aframeworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT hakonhakonarson aframeworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT alexessandercoutoalves aframeworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT deborahalawlor aframeworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT marikakaakinen aframeworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT marjoriittajarvelin aframeworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT struanfagrant aframeworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT katetilling aframeworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT ingaprokopenko aframeworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT sylvainsebert aframeworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT mickaelcanouil aframeworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT nicolemwarrington aframeworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT kimberleyburrows frameworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT anniheiskala frameworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT jonathanpbradfield frameworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT zhannabalkhiyarova frameworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT lijiaoning frameworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT mathildeboissel frameworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT yeemingchan frameworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT philippefroguel frameworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT ameliebonnefond frameworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT hakonhakonarson frameworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT alexessandercoutoalves frameworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT deborahalawlor frameworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT marikakaakinen frameworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT marjoriittajarvelin frameworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT struanfagrant frameworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT katetilling frameworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT ingaprokopenko frameworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT sylvainsebert frameworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT mickaelcanouil frameworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi AT nicolemwarrington frameworkforconductinggwasusingrepeatedmeasuresdatawithanapplicationtochildhoodbmi |