Table 2.
Mixed effect models predicting longitudinal global cognitive changes
| MCSA (R2 = 0.51) | ADNI (R2 = 0.36) | |||
|---|---|---|---|---|
| βstd (95% CI) | p | βstd (95% CI) | p | |
| Intercept | 0.194 (0.129, 0.259) | 5.6 × 10–9 | –0.067 (–0.154, 0.021) | 0.135 |
| Time from baseline, years | –0.394 (–0.448, –0.339) | 3.2 × 10-44 | –0.209 (–0.263, -0.155) | 2.8 × 10–14 |
| Number of visits | 0.285 (0.222, 0.347) | 6.4 × 10–19 | –0.033 (–0.082, 0.017) | 0.195 |
| Demographic variables | ||||
| Baseline age, years | –0.445 (–0.501, –0.389) | 4.1 × 10-51 | 0.063 (0.006, 0.120) | 0.029 |
| Males | –0.171 (–0.256, –0.086) | 7.7 × 10-5 | –0.020 (−0.126, 0.086) | 0.715 |
| APOE-ε4 carrier | –0.078 (-0.170, 0.013) | 0.094 | −0.138 (–0.250, –0.026) | 0.016 |
| Education, years | 0.346 (0.306, 0.386) | 2.1 × 10–60 | 0.109 (0.059, 0.160) | 2.4 × 10–5 |
| Baseline age × time | -0.093 (-0.105, -0.082) | 1.0 × 10–55 | 0.000 (–0.018, 0.018) | 0.977 |
| Males × time | 0.005 (–0.012, 0.021) | 0.557 | 0.059 (0.027, 0.090) | 2.5 × 10–4 |
| APOE-ε4 carrier × time | –0.027 (–0.045, –0.009) | 0.003 | –0.048 (–0.081, –0.015) | 0.005 |
| Education × time | -0.005 (-0.013, 0.003) | 0.193 | 0.000 (–0.015, 0.015) | 0.996 |
| WM metabolism | ||||
| EWM FDG SUVR | 0.268 (0.218, 0.317) | 1.7 × 10–25 | 0.474 (0.413, 0.535) | 1.6 × 10–47 |
| AWM FDG SUVR | –0.204 (–0.249, –0.160) | 6.1 × 10–19 | –0.130 (–0.185, –0.076) | 3.4 × 10–6 |
| EWM FDG SUVR × time | 0.048 (0.037, 0.059) | 2.5 × 10–18 | 0.087 (0.068, 0.107) | 3.2 × 10–18 |
| AWM FDG SUVR × time | –0.027 (-0.036, –0.017) | 7.0 × 10–7 | –0.019 (–0.036, –0.002) | 0.026 |
| Pathologies | ||||
| Aβ Centiloid | –0.251 (–0.292, –0.209) | 1.5 × 10–31 | –0.445 (–0.500, -0.389) | 2.5 × 10–50 |
| WMH/TIV (%) | –0.082 (–0.125, –0.038) | 2.2 × 10–4 | 0.019 (–0.033, 0.071) | 0.474 |
| Aβ Centiloid × time | –0.102 (–0.112, –0.092) | 4.8 × 10–92 | –0.200 (−0.222, −0.181) | 1.7 × 10–78 |
| WMH/TIV (%) × time | –0.030 (–0.040, –0.020) | 7.2 × 10–9 | 0.020 (–0.001, 0.035) | 0.060 |
Linear mixed-effects models were fitted separately in MCSA and ADNI. Two-sided tests were used for all analyses. R² for fixed effects, standardized coefficients (βstd), 95% CIs, and exact p values are reported. In MCSA, global cognition was measured using global cognitive z-scores (higher scores indicate better cognition). In ADNI, cognition was assessed using the ADAS-Cog-11 total score (higher scores indicate poorer cognition), which was inverted prior to modeling to align the direction of effects across cohorts. MCSA (n = 1722 participants; 9948 observations) and ADNI (n = 1055 participants; 5339 observations).
EWM expected white matter, AWM atypical white matter, SUVR standardized uptake value ratio, ADAS-Cog Alzheimer’s Disease Assessment Scale-Cognitive Subscale, WMH white matter hyperintensity, TIV total intracranial volume.