Free-water: A promising structural biomarker for cognitive decline in aging and mild cognitive impairment

Aditi Sathe; Yisu Yang; Kurt G Schilling; Niranjana Shashikumar; Elizabeth Moore; Logan Dumitrescu; Kimberly R Pechman; Bennett A Landman; Katherine A Gifford; Timothy J Hohman; Angela L Jefferson; Derek B Archer

doi:10.1162/imag_a_00293

Free-water: A promising structural biomarker for cognitive decline in aging and mild cognitive impairment

Imaging Neurosci (Camb). 2024 Sep 18:2:1-16. doi: 10.1162/imag_a_00293. eCollection 2024 Sep 1.

Authors

Aditi Sathe¹, Yisu Yang¹, Kurt G Schilling^{2

3}, Niranjana Shashikumar¹, Elizabeth Moore¹, Logan Dumitrescu^{1

4}, Kimberly R Pechman¹, Bennett A Landman^{1

2

5

6

7}, Katherine A Gifford¹, Timothy J Hohman^{1

4}, Angela L Jefferson^{1

3

8}, Derek B Archer^{1

4}

Affiliations

¹ Vanderbilt Memory and Alzheimer's Center, Vanderbilt University School of Medicine, Nashville, TN, United States.
² Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States.
³ Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States.
⁴ Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, United States.
⁵ Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States.
⁶ Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, United States.
⁷ Department of Radiology & Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States.
⁸ Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States.

Abstract

Diffusion MRI derived free-water (FW) metrics show promise in predicting cognitive impairment and decline in aging and Alzheimer's disease (AD). FW is sensitive to subtle changes in brain microstructure, so it is possible these measures may be more sensitive than traditional structural neuroimaging biomarkers. In this study, we examined the associations among FW metrics (measured in the hippocampus and two AD signature meta-ROIs) with cognitive performance, and compared FW findings to those from more traditional neuroimaging biomarkers of AD. We leveraged data from a longitudinal cohort (n_participants = 296, n_observations = 870, age at baseline: 73 ± 7 years, 40% mild cognitive impairment [MCI]) of older adults who underwent serial neuropsychological assessment (episodic memory, information processing speed, executive function, language, and visuospatial skills) and brain MRI over a maximum of four time points, including baseline (n = 284), 18-month (n = 246), 3-year (n = 215), and 5-year (n = 125) visits. The mean follow-up period was 2.8 ± 1.3 years. Structural MRI was used to quantify hippocampal volume, in addition to Schwarz and McEvoy AD Signatures. FW and FW-corrected fractional anisotropy (FAFWcorr) were quantified in the hippocampus (hippocampal FW) and the AD signature areas (Schwarz_FW, McEvoy_FW) from diffusion-weighted (dMRI) images using bi-tensor modeling (FW elimination and mapping method). Linear regression assessed the association of each biomarker with baseline cognitive performance. Additionally, linear mixed-effects regression assessed the association between baseline biomarker values and longitudinal cognitive performance. A subsequent competitive model analysis was conducted on both baseline and longitudinal data to determine how much additional variance in cognitive performance was explained by each biomarker compared to the covariate only model, which included age, sex, race/ethnicity, apolipoprotein-ε4 status, cognitive status, and modified Framingham Stroke Risk Profile scores. All analyses were corrected for multiple comparisons using an FDR procedure. Cross-sectional results indicate that hippocampal volume, hippocampal FW, Schwarz and McEvoy AD Signatures, and the Schwarz_FW and McEvoy_FW metrics are all significantly associated with memory performance. Baseline competitive model analyses showed that the McEvoy AD Signature and Schwarz_FW explain the most unique variance beyond covariates for memory (ΔR_adj ² = 3.47 ± 1.65%) and executive function (ΔR_adj ² = 2.43 ± 1.63%), respectively. Longitudinal models revealed that hippocampal FW explained substantial unique variance for memory performance (ΔR_adj ² = 8.13 ± 1.25%), and outperformed all other biomarkers examined in predicting memory decline (p_FDR = 1.95 x 10^-11). This study shows that hippocampal FW is a sensitive biomarker for cognitive impairment and decline, and provides strong evidence for further exploration of this measure in aging and AD.

Keywords: Alzheimer’s disease (AD); aging; cognition; diffusion MRI; fractional anisotropy (FA); free-water.