Distinguishing Lifelong Individual Differences from Divergent Aging Trajectories of Adult Brain Volumes

Differences in the volumes of brain structures between individuals are often linked to various conditions, including Alzheimer’s disease, schizophrenia, and overall brain health. However, it remains unclear to what extent these differences reflect individual levels present at young adulthood or diverging aging trajectories at later ages. In this study, we analyze the aging dynamics of the volume of six brain structures based on MRI scans from a large cross-cohort longitudinal sample of cognitively healthy adults (n = 8,311 with 18,520 MRIs, ages from 18 to 97 years). From general assumptions about structural brain dynamics and measurement noise, a stochastic dynamical model was fit to the data to estimate both the variability and persistence of structural changes across adulthood. Using this model, we calculated how much of the variance in individual volumetric differences can be attributed to stable levels from young adulthood versus systematic changes at older ages, as well as the theoretical sensitivity of longitudinal studies to detect individual differences in changes. The findings were as follows: 1) Before age 60 years, inter-individual differences in neuroanatomical volumes almost exclusively reflect stable differences between individuals, while the influence from systematic differences in rate-of-change increases thereafter; up to 40 % of the variation being due to differences in change at 80 years. In contrast, ventricular volume reflects differences in change from early adulthood. 2) Current brain age-models are unlikely to be sensitive to detect differences in aging trajectories. 3) Imaging studies have a low reliability to detect inter-individual brain change before age 60. After 60 years, the study reliability increases sharply with longer intervals between scans and more modestly with additional intermediate observations. In conclusion, it is critical to distinguish stable levels from early adulthood from systematic differences in change when studying adult brain aging.