TY - JOUR AU - Gillespie, Nathan A. AU - Hatton, Sean N. AU - Hagler, Donald J. AU - Dale, Anders M. AU - Elman, Jeremy A. AU - McEvoy, Linda K. AU - Eyler, Lisa T. AU - Fennema-Notestine, Christine AU - Logue, Mark W. AU - McKenzie, Ruth E. AU - Puckett, Olivia K. AU - Tu, Xin M. AU - Whitsel, Nathan AU - Xian, Hong AU - Reynolds, Chandra A. AU - Panizzon, Matthew S. AU - Lyons, Michael J. AU - Neale, Michael C. AU - Kremen, William S. AU - Franz, Carol PY - 2022 M3 - Original Research TI - The Impact of Genes and Environment on Brain Ageing in Males Aged 51 to 72 Years JO - Frontiers in Aging Neuroscience UR - https://www.frontiersin.org/articles/10.3389/fnagi.2022.831002 VL - 14 SN - 1663-4365 N2 - Magnetic resonance imaging data are being used in statistical models to predicted brain ageing (PBA) and as biomarkers for neurodegenerative diseases such as Alzheimer’s Disease. Despite their increasing application, the genetic and environmental etiology of global PBA indices is unknown. Likewise, the degree to which genetic influences in PBA are longitudinally stable and how PBA changes over time are also unknown. We analyzed data from 734 men from the Vietnam Era Twin Study of Aging with repeated MRI assessments between the ages 51–72 years. Biometrical genetic analyses “twin models” revealed significant and highly correlated estimates of additive genetic heritability ranging from 59 to 75%. Multivariate longitudinal modeling revealed that covariation between PBA at different timepoints could be explained by a single latent factor with 73% heritability. Our results suggest that genetic influences on PBA are detectable in midlife or earlier, are longitudinally very stable, and are largely explained by common genetic influences. ER -