Although hippocampal volume has served as a long-standing predictor of cognitive decline, diffusion MRI studies of white matter have shown similar relationships. Still, it remains unclear if gray and white matter interact to predict cognitive impairment and longitudinal decline. Here, we investigate whether FW and FW-corrected fractional anisotropy (FA T ) within medial temporal lobe white matter tracts provides meaningful contribution to cognition and cognitive decline beyond hippocampal volume. Using data from the Vanderbilt Memory & Aging Project (n=319), we found that FW was associated with baseline memory and executive function beyond that of hippocampal volume and other comorbidities for memory loss and executive function. Longitudinal analyses demonstrated significant interactions of hippocampal volume and FA T within the inferior longitudinal fasciculus (p=0.043) and cingulum bundle (p=0.025) with decline in memory. For decline in executive function, we found significant interactions on hippocampal volume and FA T within fornix (p=0.025). Results suggest that free-water metrics of white matter have a unique role in cognitive decline and should be include in theoretical models of aging, cerebrovascular disease, and AD.

Highlights RD T within several white matter tracts is associated with SCD. RD T contributes unique variance to SCD beyond that of CSF Aβ 42 . Our findings suggest that RD T is a sensitive marker of SCD.

Introduction White matter microstructure may be abnormal along the Alzheimer's disease (AD) continuum. Methods Diffusion magnetic resonance imaging (dMRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI, n = 627), Baltimore Longitudinal Study of Aging (BLSA, n = 684), and Vanderbilt Memory & Aging Project (VMAP, n = 296) cohorts were free‐water (FW) corrected and conventional, and FW‐corrected microstructural metrics were quantified within 48 white matter tracts. Microstructural values were subsequently harmonized using the Longitudinal ComBat technique and inputted as independent variables to predict diagnosis (cognitively unimpaired [CU], mild cognitive impairment [MCI], AD). Models were adjusted for age, sex, race/ethnicity, education, apolipoprotein E (APOE) ε4 carrier status, and APOE ε2 carrier status. Results Conventional dMRI metrics were associated globally with diagnostic status; following FW correction, the FW metric itself exhibited global associations with diagnostic status, but intracellular metric associations were diminished. Discussion White matter microstructure is altered along the AD continuum. FW correction may provide further understanding of the white matter neurodegenerative process in AD. Highlights Longitudinal ComBat successfully harmonized large‐scale diffusion magnetic resonance imaging (dMRI) metrics. Conventional dMRI metrics were globally sensitive to diagnostic status. Free‐water (FW) correction mitigated intracellular associations with diagnostic status. The FW metric itself was globally sensitive to diagnostic status. Multivariate conventional and FW‐corrected models may provide complementary information.

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BackgroundSeveral prior studies have used diffusion MRI to investigate the relationship between white matter microstructure and aging; however, many of these studies used conventional diffusion MRI measures and single site data. The goal of the study is to leverage multi‐site harmonized diffusion MRI data in conjunction with a novel post‐processing technique [i.e., free‐water (FW) correction] to quantify the aging related tract‐specific changes in white matter microstructure.MethodThe dataset used in this study was collated using several well‐established longitudinal cohorts of aging [Alzheimer’s Neuroimaging Initiative (ADNI), Baltimore Longitudinal Study of Aging (BLSA), Vanderbilt Memory & Aging Project (VMAP)]. In total, this dataset included 1,909 participants (mean age at baseline: 72±9 years, 59% female) and 4,844 imaging sessions (mean number of visits: 4 ± 2 years, interval range: 1–12 years). Data was processed using standard approaches and uncorrected fractional anisotropy (FAU) was quantified with seven white matter tractography atlases (see Figure 1A). Data was then post‐processed using the FW correction technique and FW and FW‐corrected FA (FAT) values were quantified. Data were then harmonized using the ComBat technique and linear mixed‐effects regression was conducted on each microstructural measure, covarying for age at baseline, sex, cognitive status, education, APOE‐ε4 carrier status, and APOE‐ε2 carrier status. The effect of aging was modelled using an Age_at_Baseline x Interval interaction term.ResultAge was associated with lower FAU in all seven tracts (pFDR range: 4.77x10‐10 to ‐0.01). In the FW analysis, age was associated with higher FW in all seven tracts (pFDR range: 7.81x10‐12 to 1.33x10‐6). For FAT, however, age was only associated with lower FAT in the limbic tracts (pFDR=0.024) in addition to the occipital (pFDR=1.19x10‐8), parietal (pFDR=2.32x10‐4), and prefrontal (pFDR=0.024) TC tracts. Figure 1B‐D illustrates our findings.ConclusionThis study suggests that while there are global associations with FAU and age, these associations are attenuated once correcting for partial volume effects. Leveraging FW analysis, we found a global association with FW and age, whereby age is associated with higher FW. Further, we found that age is associated with reductions in FAT in the limbic and occipital/parietal/prefrontal TC tracts.