Despite numerous studies on the microstructural changes of the human brain throughout life, we have indeed little direct knowledge about the changes from early to mid-adulthood. The aim of this study was to investigate the microstructural changes of the human brain from early to mid-adulthood. We performed two sets of analyses based on the diffusion tensor imaging (DTI) data of 111 adults aged 18-55 years. Specifically, we first correlated age with skeletonized fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) at global and regional level, and then estimated individuals' ages based on each DTI metric using elastic net, a kind of multivariate pattern analysis (MVPA) method that aims at selecting the model that achieves the best trade-off between goodness of fit and model complexity. We observed statistically significant negative age-vs-FA correlations and relatively less changes of MD. The negative age-vs-FA correlations were associated with negative age-vs-AD and positive age-vs-RD correlations. Regional negative age-vs-FA correlations were observed in the bilateral genu of the corpus callosum (CCg), the corticospinal tract (CST), the fornix and several other tracts, and these negative correlations may indicate the earlier changes of the fibers with aging. In brain age estimation, the chronological-vs-estimated-age correlations based on FA, MD, AD and RD were R = 0.62, 0.44, 0.63 and 0.69 (P = 0.002, 0.008, 0.002 and 0.002 based on 500 permutations), respectively, and these results indicate that even the microstructural changes from early to mid-adulthood alone are sufficiently specific to decode individuals' ages. Overall, the current results not only demonstrated statistically significant FA decreases from early to mid-adulthood and clarified the driving factors of the FA decreases (RD increases and AD decreases, in contrast to increases of both measures in late-adulthood), but highlighted the necessity of considering age effects in related studies.
This research output has an Altmetric Attention Score of 90. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 September 2017.
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