Associations between amyloid‐β, white matter disease, functional brain networks, and mobility function: Possible indicators of reserve and resilience: Neuroimaging / Normal brain aging. (7th December 2020)

• Record Type: Journal Article
• Authors: Neyland, Blake R.; Hugenschmidt, Christina E.; Lockhart, Samuel N.; Okonmah‐Obazee, Stephanie; Sai, Kiran Solingapuram; Baker, Laura D.; Craft, Suzanne; Miller, Michael E.; Laurienti, Paul J.; Kritchevsky, Stephen B.
• Is Part Of: Alzheimer's & dementia. Volume 16(2020)Supplement 5
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-12-07
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.041213
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Undetected AD pathology in cognitively normal older adults may increase risk for mobility decline by both increasing white matter pathology and directly interfering with functional networks through Aβ deposition. Methods: Thirty‐one cognitively normal older adults (75.01 ± 4.15 y, 35.5% female) enrolled in the Brain Networks and Mobility Function (B‐NET) study received PiB PET and MRI. A global cortical PiB average for each participant was calculated by coregistering PET to MRI using Freesurfer v5.6 to generate masks and thresholding at 1.21 to create PiB positivity groups (PiB‐ = 16, PiB+ = 15). White matter hyperintensity (WMH) volume was calculated with the Lesion Segmentation Toolbox (LST) implemented in SPM12. Mobility function was assessed using the expanded Short Physical Performance Battery (eSPPB), a 4‐meter walk, and a 400‐meter walk. Cognitive measures included the Montreal Cognitive Assessment (MOCA) and Digit Symbol Substitution Task (DSST). Associations were explored using linear regression, correcting for age, sex, and BMI in the fully adjusted mobility model while age, sex, and education were used in the fully adjusted cognition and WMH model. Results: PiB+ individuals had significantly faster 4‐meter gait speed (p<0.05) and a trend for higher DSST (p=0.052). These associations were independent of WMH volume. PiB+ individuals also had significantly higher total (p<0.05) and motor WMH (p<0.05). Conclusions: The observation that PiB+ individuals had better physical function than PiB‐ was unexpected given existing literature showing associations between regional Aβ volume and slower gait speed. It was also unexpected given that the PiB+ group had higher WMH volume, which is associated with slower gait speed. The current sample, which includes primarily individuals with good physical and cognitive function, may represent a resilient phenotype. Continued recruitment of more diverse participants with lower physical function will be an important addition to this sample. Future analyses will allow for the inclusion of APOE and an increased sample size. Whole‐brain functional connectivity will also be assessed in this cohort using graph‐theory based methods.