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 genome-wide association studies (GWASs). Using childhood body mass index (BMI) as an example, 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 on each of the estimated phenotypes identified 28 genome-wide significant variants at 13 loci across the 12 estimated phenotypes, one of which was novel (in DAOA) and had not been previously associated with childhood or adult BMI. Genetic studies of changes in human traits over time could uncover novel biological mechanisms influencing quantitative traits.

DAL received support from Medtronic Ltd and Roche Diagnostics for research unrelated to that presented here. All other authors report no conflict of interest.

KB, DAL and KT contributions to this work are supported by the UK Medical Research Council (MRC_UU_00032/02 and MC_UU_00032/05). DAL's contribution is further supported by the British Heart Foundation (CH/F/20/90003 and AA/18/1/34219) and the European Research Council under the European Union's Horizon 2020 research and innovation program (grant agreement No 101021566). AH is supported by the European Union's Horizon 2020 research and innovation program under grant agreement No. 874739 (LongITools), and the Academy of Finland decision 336449 (Profi6). IP and ZB were funded in part by the Diabetes UK (British Diabetic Association no. 20/0006307), European Union's Horizon 2020 research and innovation program (H2020 Science with and for Society)(LONGITOOLS, H2020-SC1-2019-874739). IP is in part supported by the BHR Basic Science Research fellowships (FS/15/59/31839 and FS/SBSRF/21/31025). SFAG is supported by the NICHD (R01 HD056465) and the Daniel B. Burke Endowed Chair for Diabetes Research. NMW is funded by an Australian National Health and Medical Research Council Investigator grant (APP2008723).

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

ALSPAC: Ethical approval for the study was obtained from the ALSPAC Ethics and Law Committee and the Local Research Ethics Committees. NFBC1966: Approval for the studies was granted by the Northern Ostrobothnia Hospital District Ethical Committee 94/2011 (12.12.2011), Finland in accordance with the declaration of Helsinki. NFBC1986: Approval for the studies was granted by the Northern Ostrobothnia Hospital District Ethical Committee 108/2017 (15.1.2018), Finland in accordance with the declaration of Helsinki. CHOP: The Research Ethics Board of CHOP approved the study, and written informed consent was obtained from all subjects. OBE: The study protocols were approved by local ethics committees.

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I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

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To access phenotype and genotype data from individual cohorts participating in the manuscript, the cohorts should be contacted directly as each cohort has different data access policies. GWAS summary statistics from this study will be available via the Early Growth Genetics (EGG) website (https://egg-consortium.org/) upon publication.