The genetic etiology of longitudinal measures of predicted brain ageing in a population-based sample of mid to late-age males
Nathan A. GillespieiD, Sean N. HattoniD, Donald J. HagleriD, Anders Martin DaleiD, Jeremy A. ElmaniD, Linda K. McEvoyiD, Lisa T Elyer, Christine Fennema‐NotestineiD, Mark W. LogueiD, Ruth E. McKenzieiD, Olivia K. PuckettiD, Xin Ming TuiD, Nathan A. WhitseliD, Hong XianiD, Chandra A. ReynoldsiD, Matthew S. PanizzoniD, Michael J. LyonsiD, Michael Churton NealeiD, William S. KremeniD, Carol E. FranziD
Abstract
Magnetic resonance imaging data are being used in statistical models to predicted brain ageing (PBA) and as biomarkers for neurodegenerative diseases such as Alzheimers 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 52 to 72 years. Biometrical genetic analyses twin models revealed significant and highly correlated estimates of additive genetic heritability ranging from 59% to 75%. Multivariate longitudinal modelling 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. HighlightsWe explored the genetic and environmental etiology of MRI-based predicted brain age (PBA) in a longitudinal sample of males starting in midlife. Genetic influences on PBA are detectable in midlife or earlier, are longitudinally very stable, and largely explained by common genetic influences.
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