White Matter Abnormalities and Cognition in Aging and Alzheimer Disease

Importance There has yet to be a large-scale study quantifying the association between white matter microstructure and cognitive performance and decline in aging and Alzheimer disease (AD). Objective To investigate the associations between tract-specific white matter microstructure and cognitive performance and decline in aging and AD-related cognitive impairment. Design, Setting, and Participants This prognostic study of aging and AD, a secondary data analysis of multisite cohort studies, acquired data from 9 cohorts between September 2002 and November 2022. Participants were eligible if they had diffusion-weighted magnetic resonance imaging (dMRI) data, domain-specific cognitive composite z scores, demographic and clinical data, were aged 50 years or older, and passed neuroimaging quality control. Demographic and clinical covariates included age, sex, education, race and ethnicity, APOE haplotype status (ε2, ε3, ε4), and clinical status. The present study was conducted from June 2024 to February 2025. Exposures White matter microstructure and cognitive performance and decline. Main Outcomes and Measures Clinical diagnosis, imaging measures (dMRI, T1-weighted MRI, and amyloid and tau positron emission tomography), and cognitive tests. Results Of 4467 participants who underwent 9208 longitudinal cognitive sessions, 2698 (60.4%) were female, and the mean age (SD) was 74.3 (9.2) years; 3213 were cognitively unimpaired, 972 had mild cognitive impairment, and 282 had AD dementia. White matter free water (FW) showed the strongest associations with cross-sectional cognitive performance and longitudinal cognitive decline across all domains, particularly memory. FW in limbic tracts, such as the cingulum, presented the strongest associations with both memory performance (cingulum: β = −0.718; P < .001; fornix: β = −1.069; P < .001) and decline (cingulum: β = −0.115; P < .001; fornix: β = −0.153; P < .001). White matter FW measures interacted with baseline diagnosis, gray matter atrophy, APOE ε4 status, and amyloid positivity to predict poorer cognitive performance and accelerated cognitive decline. Noteworthy interactions include fornix FW and hippocampal volume (β = 10.598; P < .001), cingulum FW and SPARE-AD index (β = −0.532; P < .001), and inferior temporal gyrus transcallosal tract FW and baseline diagnosis (β = −0.537; P < .001), all predicting poorer memory performance. Conclusions and Relevance White matter microstructural changes, particularly FW, play a critical role in cognitive decline in aging and AD-related cognitive impairment. These findings highlight the importance of FW correction in dMRI studies and highlight the limbic system, especially the cingulum and fornix, as key regions associated with cognitive decline; the interaction models highlight that integrating FW-corrected metrics with other AD biomarkers may further elucidate the biological mechanisms of neurodegeneration in aging.