- Moore, Timothy M;
- Lee, Sindre;
- Olsen, Thomas;
- Morselli, Marco;
- Strumwasser, Alexander R;
- Lin, Amanda J;
- Zhou, Zhenqi;
- Abrishami, Aaron;
- Garcia, Steven M;
- Bribiesca, Jennifer;
- Cory, Kevin;
- Whitney, Kate;
- Ho, Theodore;
- Ho, Timothy;
- Lee, Joseph L;
- Rucker, Daniel H;
- Nguyen, Christina QA;
- Anand, Akshay TS;
- Yackly, Aidan;
- Mendoza, Lorna Q;
- Leyva, Brayden K;
- Aliman, Claudia;
- Artiga, Daniel J;
- Meng, Yonghong;
- Charugundla, Sarada;
- Pan, Calvin;
- Jedian, Vida;
- Seldin, Marcus M;
- Ahn, In Sook;
- Diamante, Graciel;
- Blencowe, Montgomery;
- Yang, Xia;
- Mouisel, Etienne;
- Pellegrini, Matteo;
- Turcotte, Lorraine P;
- Birkeland, Kåre I;
- Norheim, Frode;
- Drevon, Christian A;
- Lusis, Aldons J;
- Hevener, Andrea L
Physical activity is associated with beneficial adaptations in human and rodent metabolism. We studied over 50 complex traits before and after exercise intervention in middle-aged men and a panel of 100 diverse strains of female mice. Candidate gene analyses in three brain regions, muscle, liver, heart, and adipose tissue of mice indicate genetic drivers of clinically relevant traits, including volitional exercise volume, muscle metabolism, adiposity, and hepatic lipids. Although ∼33% of genes differentially expressed in skeletal muscle following the exercise intervention are similar in mice and humans independent of BMI, responsiveness of adipose tissue to exercise-stimulated weight loss appears controlled by species and underlying genotype. We leveraged genetic diversity to generate prediction models of metabolic trait responsiveness to volitional activity offering a framework for advancing personalized exercise prescription. The human and mouse data are publicly available via a user-friendly Web-based application to enhance data mining and hypothesis development.