Polygenic prediction of body mass index and obesity through the life course and across ancestries
Roelof A. J. Smit, Kaitlin H. Wade, Qin Hui, Joshua Arias, Xianyong Yin, Malene R. Christiansen, Loïc Yengo, Michael Preuß, Mariam Nakabuye, Ghislain Rocheleau, Sarah E. Graham, Victoria L. Buchanan, Geetha Chittoor, Marielisa Graff, Marta Guindo-Martínez, Yingchang Lu, Eirini Marouli, Saori Sakaue, Cassandra N. Spracklen, Sailaja Vedantam, Emma P Wilson, Shyh‐Huei Chen, Teresa Ferreira, Yingjie Ji, Tugce Karaderi, Kreete Lüll, Moara Machado, Deborah E. Malden, Carolina Medina‐Gómez, Amy Moore, Sina Rüeger, Masato Akiyama, Matthew Allison, Marcus Alvarez, Mette K. Andersen, Vivek Appadurai, Liubov Arbeeva, Eric Bartell, Seema Bhaskar, Lawrence F. Bielak, Joshua C. Bis, Sailalitha Bollepalli, Jette Bork‐Jensen, Jonathan P. Bradfield, Yuki Bradford, Caroline Brandl, Peter S. Braund, Jennifer A. Brody, Ulrich Broeckel, Kristoffer Sølvsten Burgdorf, Brian E. Cade, Qiuyin Cai, Silvia Camarda, Archie Campbell, Marisa Cañadas‐Garre, Jin Fang Chai, Alessandra Chesi, Seung Hoan Choi, Paraskevi Christofidou, Christian Couture, Gabriel Cuéllar-Partida, Rebecca Danning, Frauke Degenhardt, Graciela E. Delgado, Alessandro Delitala, Ayşe Demirkan, Xuan Deng, Alexander Dietl, Maria Dimitriou, Latchezar Dimitrov, Rajkumar Dorajoo, Fabian Eichelmann, Anders Eliasen, Jorgen Engmann, Michael R. Erdos, Zammy Fairhurst-Hunter, Aliki‐Eleni Farmaki, Jessica D. Faul, Juan-Carlos Fernandez-Lopez, Lukas Forer, Mirjam Frank, Sandra Freitag-Wolf, Lars Fritsche, Christian Fuchsberger, Tessel E. Galesloot, Yan Gao, Frank Geller, Olga Giannakopoulou, Franco Giulianini, Anette P. Gjesing, Anuj Goel, Scott D. Gordon, Mathias Gorski, Jakob Grove, Xiuqing Guo, Stefan Gustafsson, J. Haessler, Thomas Folkmann Hansen, Aki S. Havulinna, Simon Haworth
Abstract
Polygenic scores (PGSs) for body mass index (BMI) may guide early prevention and targeted treatment of obesity. Using genetic data from up to 5.1 million people (4.6% African ancestry, 14.4% American ancestry, 8.4% East Asian ancestry, 71.1% European ancestry and 1.5% South Asian ancestry) from the GIANT consortium and 23andMe, Inc., we developed ancestry-specific and multi-ancestry PGSs. The multi-ancestry score explained 17.6% of BMI variation among UK Biobank participants of European ancestry. For other populations, this ranged from 16% in East Asian-Americans to 2.2% in rural Ugandans. In the ALSPAC study, children with higher PGSs showed accelerated BMI gain from age 2.5 years to adolescence, with earlier adiposity rebound. Adding the PGS to predictors available at birth nearly doubled explained variance for BMI from age 5 onward (for example, from 11% to 21% at age 8). Up to age 5, adding the PGS to early-life BMI improved prediction of BMI at age 18 (for example, from 22% to 35% at age 5). Higher PGSs were associated with greater adult weight gain. In intensive lifestyle intervention trials, individuals with higher PGSs lost modestly more weight in the first year (0.55 kg per s.d.) but were more likely to regain it. Overall, these data show that PGSs have the potential to improve obesity prediction, particularly when implemented early in life.