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Associations between body mass index-related genetic variants and adult body composition: the Fenland cohort study

BACKGROUND/OBJECTIVE: Body mass index (BMI) is a surrogate measure of adiposity but does not distinguish fat from lean or bone mass. The genetic determinants of BMI are thought to predominantly influence adiposity but this has not been confirmed. Here we characterise the association between BMI-rela...

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Detalles Bibliográficos
Autores principales: Clifton, Emma A D, Day, Felix R, De Lucia Rolfe, Emanuella, Forouhi, Nita G, Brage, Soren, Griffin, Simon J, Wareham, Nicholas J, Ong, Ken K
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5382973/
https://www.ncbi.nlm.nih.gov/pubmed/28096530
http://dx.doi.org/10.1038/ijo.2017.11
Descripción
Sumario:BACKGROUND/OBJECTIVE: Body mass index (BMI) is a surrogate measure of adiposity but does not distinguish fat from lean or bone mass. The genetic determinants of BMI are thought to predominantly influence adiposity but this has not been confirmed. Here we characterise the association between BMI-related genetic variants and body composition in adults. SUBJECTS/METHODS: Among 9667 adults aged 29-64 years from the Fenland study, a genetic risk score for BMI (BMI-GRS) was calculated for each individual as the weighted sum of BMI-increasing alleles across 96 reported BMI-related variants. Associations between the BMI-GRS and body composition, estimated by DXA scans, were examined using age-adjusted linear regression models, separately by sex. RESULTS: The BMI-GRS was positively associated with all fat, lean and bone variables. Across body regions, associations of the greatest magnitude were observed for adiposity variables e.g. for each standard deviation (SD) increase in BMI-GRS predicted BMI, we observed a 0.90 SD (95% CI: 0.71, 1.09) increase in total fat mass for men (P=3.75×10(−21)) and a 0.96 SD (95% CI: 0.77, 1.16) increase for women (P=6.12×10(−22)). Associations of intermediate magnitude were observed with lean variables e.g. total lean mass: men: 0.68 SD (95% CI: 0.49, 0.86) (P=1.91×10(−12)); women: 0.85 SD (95% CI: 0.65, 1.04) (P=2.66×10(−17)) and of a lower magnitude with bone variables e.g. total bone mass: men: 0.39 SD (95% CI: 0.20, 0.58) (P=5.69×10(−5)); women: 0.45 SD (95% CI: 0.26, 0.65) (P=3.96×10(−6)). Nominally significant associations with BMI were observed for 28 SNPs. All 28 were positively associated with fat mass and 13 showed adipose-specific effects. CONCLUSION: In adults, genetic susceptibility to elevated BMI influences adiposity more than lean or bone mass. This mirrors the association between BMI and body composition. The BMI-GRS can be used to model the effects of measured BMI and adiposity on health and other outcomes.