TY - JOUR
T1 - Changing genetic architecture of body mass index from infancy to early adulthood
T2 - an individual based pooled analysis of 25 twin cohorts
AU - Silventoinen, Karri
AU - Li, Weilong
AU - Jelenkovic, Aline
AU - Sund, Reijo
AU - Yokoyama, Yoshie
AU - Aaltonen, Sari
AU - Piirtola, Maarit
AU - Sugawara, Masumi
AU - Tanaka, Mami
AU - Matsumoto, Satoko
AU - Baker, Laura A.
AU - Tuvblad, Catherine
AU - Tynelius, Per
AU - Rasmussen, Finn
AU - Craig, Jeffrey M.
AU - Saffery, Richard
AU - Willemsen, Gonneke
AU - Bartels, Meike
AU - van Beijsterveldt, Catharina E.M.
AU - Martin, Nicholas G.
AU - Medland, Sarah E.
AU - Montgomery, Grant W.
AU - Lichtenstein, Paul
AU - Krueger, Robert F.
AU - McGue, Matt
AU - Pahlen, Shandell
AU - Christensen, Kaare
AU - Skytthe, Axel
AU - Kyvik, Kirsten O.
AU - Saudino, Kimberly J.
AU - Dubois, Lise
AU - Boivin, Michel
AU - Brendgen, Mara
AU - Dionne, Ginette
AU - Vitaro, Frank
AU - Ullemar, Vilhelmina
AU - Almqvist, Catarina
AU - Magnusson, Patrik K.E.
AU - Corley, Robin P.
AU - Huibregtse, Brooke M.
AU - Knafo-Noam, Ariel
AU - Mankuta, David
AU - Abramson, Lior
AU - Haworth, Claire M.A.
AU - Plomin, Robert
AU - Bjerregaard-Andersen, Morten
AU - Beck-Nielsen, Henning
AU - Sodemann, Morten
AU - Duncan, Glen E.
AU - Buchwald, Dedra
AU - Burt, S. Alexandra
AU - Klump, Kelly L.
AU - Llewellyn, Clare H.
AU - Fisher, Abigail
AU - Boomsma, Dorret I.
AU - Sørensen, Thorkild I.A.
AU - Kaprio, Jaakko
N1 - Funding Information:
This study was conducted within the CODATwins project. Support for collaborators: Colorado Twin Registry is funded by NIDA funded center grant DA011015, & Longititudinal Twin Study HD10333; Author Huibregtse is supported by National Institute on Drug Abuse (5T32DA017637) and National Institute on Aging (5T32AG052371). Finnish Twin Cohort is supported by the Academy of Finland (grants 312073 and 336823) and the Sigrid Juselius Foundation. Michigan State University Twin Registry was supported by National Institute of Mental Health (NIMH) (R01-MH081813, R01-MH0820–54, R01-MH092377-02, R21-MH070542-01, R03-MH63851-01, 1R01-MH118848-01), Eunice Kennedy Shriver National Institute for Child Health and Human Development (NICHD) (R01-HD066040) and MSU Foundation (11-SPG-2518). PETS was funded by the Australian National Health and Medical Research Council (grant numbers 437015 and 607358); the Bonnie Babes Foundation (grant number BBF20704); the Financial Markets Foundation for Children (grant number 032-2007); and the Victorian Government’s Operational Infrastructure Support Program. We acknowledge The Swedish Twin Registry for access to data. The Swedish Twin Registry is managed by Karolinska Institutet and receives funding through the Swedish Research Council under the grant no 2017-00641. TEDS was supported by a program grant to RP from the UK Medical Research Council (MR/M021475/1 and previously G0901245), with additional support from the US National Institutes of Health (AG046938). The West Japan Twins and Higher Order Multiple Births Registry was supported by Grant-in-Aid for Scientific Research (B) (grant number 20H04019) from the Japan Society for the Promotion of Science. Open Access funding provided by University of Helsinki including Helsinki University Central Hospital.
Publisher Copyright:
© 2022, The Author(s).
PY - 2022/10
Y1 - 2022/10
N2 - Background: Body mass index (BMI) shows strong continuity over childhood and adolescence and high childhood BMI is the strongest predictor of adult obesity. Genetic factors strongly contribute to this continuity, but it is still poorly known how their contribution changes over childhood and adolescence. Thus, we used the genetic twin design to estimate the genetic correlations of BMI from infancy to adulthood and compared them to the genetic correlations of height. Methods: We pooled individual level data from 25 longitudinal twin cohorts including 38,530 complete twin pairs and having 283,766 longitudinal height and weight measures. The data were analyzed using Cholesky decomposition offering genetic and environmental correlations of BMI and height between all age combinations from 1 to 19 years of age. Results: The genetic correlations of BMI and height were stronger than the trait correlations. For BMI, we found that genetic correlations decreased as the age between the assessments increased, a trend that was especially visible from early to middle childhood. In contrast, for height, the genetic correlations were strong between all ages. Age-to-age correlations between environmental factors shared by co-twins were found for BMI in early childhood but disappeared altogether by middle childhood. For height, shared environmental correlations persisted from infancy to adulthood. Conclusions: Our results suggest that the genes affecting BMI change over childhood and adolescence leading to decreasing age-to-age genetic correlations. This change is especially visible from early to middle childhood indicating that new genetic factors start to affect BMI in middle childhood. Identifying mediating pathways of these genetic factors can open possibilities for interventions, especially for those children with high genetic predisposition to adult obesity.
AB - Background: Body mass index (BMI) shows strong continuity over childhood and adolescence and high childhood BMI is the strongest predictor of adult obesity. Genetic factors strongly contribute to this continuity, but it is still poorly known how their contribution changes over childhood and adolescence. Thus, we used the genetic twin design to estimate the genetic correlations of BMI from infancy to adulthood and compared them to the genetic correlations of height. Methods: We pooled individual level data from 25 longitudinal twin cohorts including 38,530 complete twin pairs and having 283,766 longitudinal height and weight measures. The data were analyzed using Cholesky decomposition offering genetic and environmental correlations of BMI and height between all age combinations from 1 to 19 years of age. Results: The genetic correlations of BMI and height were stronger than the trait correlations. For BMI, we found that genetic correlations decreased as the age between the assessments increased, a trend that was especially visible from early to middle childhood. In contrast, for height, the genetic correlations were strong between all ages. Age-to-age correlations between environmental factors shared by co-twins were found for BMI in early childhood but disappeared altogether by middle childhood. For height, shared environmental correlations persisted from infancy to adulthood. Conclusions: Our results suggest that the genes affecting BMI change over childhood and adolescence leading to decreasing age-to-age genetic correlations. This change is especially visible from early to middle childhood indicating that new genetic factors start to affect BMI in middle childhood. Identifying mediating pathways of these genetic factors can open possibilities for interventions, especially for those children with high genetic predisposition to adult obesity.
KW - Adolescent
KW - Adult
KW - Body Height/genetics
KW - Body Mass Index
KW - Child
KW - Child, Preschool
KW - Humans
KW - Infant
KW - Obesity/epidemiology
KW - Twins, Dizygotic/genetics
KW - Twins, Monozygotic/genetics
KW - Young Adult
U2 - 10.1038/s41366-022-01202-3
DO - 10.1038/s41366-022-01202-3
M3 - Journal article
C2 - 35945263
AN - SCOPUS:85135772911
SN - 0307-0565
VL - 46
SP - 1901
EP - 1909
JO - International Journal of Obesity
JF - International Journal of Obesity
IS - 10
ER -