a Longitudinal grouping in ADNI data. X-axis shows the scan observations across timepoints in the sample. Each line represents a participant. Single-timepoint ADNI diagnoses (Y-axis; NC normal controls, MCI mild cognitive impairment, AD Alzheimer’s disease) were used to define two longitudinal groups of AD and NC individuals (AD-long; N = 606, obs = 2730; NC-long, N = 372; obs = 1680). NC-long individuals were classified as healthy at every timepoint whereas AD-long individuals were diagnosed with AD by their final timepoint (Methods). Single-timepoint MCI diagnoses were considered only for the purpose of defining the longitudinal AD group. Because the grouping used all diagnosis observations (i.e., not only scan observations), trajectories of AD-long individuals that appear to end with a NC or MCI diagnosis also correspond to individuals with an AD diagnosis by their final timepoint, as do those seemingly reverting. b GAMMs of Age (across groups; upper plot) were used to model age-relative change (individual-specific slopes) in 364 brain features, shown for one example feature (lower plot). The ADNI-derived slopes were then used as input to machine learning binary classification using XGBoost115. c Most features exhibited significant group-differences in age-relative change as expected (datapoints depict t-statistics for t-tests); black stroke indicates significant differences after FDR-correction (p[FDR] < 0.05 applied across 364 two-sided tests). d–f Out-of-sample prediction for the binary classifier (AIBL data; Supplementary Fig. 8) including receiver operator curve (d), confusion matrix and performance metrics (e). The purpose of the classification procedure was to empirically derive brain features with accelerated change in AD, to use these in healthy adult lifespan data. Subcort subcortical, vol volume, int intensity, gm/wm grey/white matter contrast. Error bands depict 95% confidence intervals, while the boxplot displays the median as the measure of centre with the box spanning from the 25th to the 75th percentiles.