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International journal of obesity (2005) · 2022

Changing genetic architecture of body mass index from infancy to early adulthood: an individual based pooled analysis of 25 twin cohorts.

СтатьяTwin StudyПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Silventoinen Karri, Li Weilong, Jelenkovic Aline, Sund Reijo, Yokoyama Yoshie, Aaltonen Sari, Piirtola Maarit, Sugawara Masumi, Tanaka Mami, Matsumoto Satoko, Baker Laura A, Tuvblad Catherine, Tynelius Per, Rasmussen Finn, Craig Jeffrey M, Saffery Richard, Willemsen Gonneke, Bartels Meike, van Beijsterveldt Catharina E M, Martin Nicholas G, Medland Sarah E, Montgomery Grant W, Lichtenstein Paul, Krueger Robert F, McGue Matt, Pahlen Shandell, Christensen Kaare, Skytthe Axel, Kyvik Kirsten O, Saudino Kimberly J, Dubois Lise, Boivin Michel, Brendgen Mara, Dionne Ginette, Vitaro Frank, Ullemar Vilhelmina, Almqvist Catarina, Magnusson Patrik K E, Corley Robin P, Huibregtse Brooke M, Knafo-Noam Ariel, Mankuta David, Abramson Lior, Haworth Claire M A, Plomin Robert, Bjerregaard-Andersen Morten, Beck-Nielsen Henning, Sodemann Morten, Duncan Glen E, Buchwald Dedra, Burt S Alexandra, Klump Kelly L, Llewellyn Clare H, Fisher Abigail, Boomsma Dorret I, Sørensen Thorkild I A, Kaprio Jaakko

Аннотация

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.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты