The impact of subjective cognitive decline on aging effects in the brain as measured by diffusion tensor imaging

Abstract

AbstractBackgroundDiffusion tensor imaging (DTI) can separate subjective cognitive decline (SCD) participants who progress to mild cognitive impairment and those who do not 1. We explored the effect age and memory performance has on DTI measures in SCD and controls in the hippocampal cingulum bundle, which is typically affected early in the course of Alzheimer’s disease2.Method325 participants Cam‐CAN 3 (127 SCD) older than 55 were included in the analysis. Diffusion imaging data was collected on a 3T Siemens TIM Trio scanner with a 32‐channel head coil for 0, 1000 and 2000 s/mm2 b‐values and 30 gradient directions. Preprocessing and calculation of the DTI metrics fractional anisotropy (FA, mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AxD) were completed using MRTrix3, FSL and MATLAB. The hippocampal cingulum bundle regions of interest (ROIs) were extracted from the ICBM‐DTI‐81 atlas. Memory was assessed using the delayed story recall (DSR) task from WMS‐III. Linear regression models were completed in R. Gender was included as a nuisance variable.ResultThere were no differences in gender or age distribution between cohorts, however participants with SCD had a 14% lower DSR score (Table 1). There was a significant interaction effect between age and cohort in MD, AxD, and RD (Figure 1), as well as between memory and age in AxD (Figure 2). In post‐hoc analyses, compared to controls, the SCD group showed a stronger correlation with age in MD, AxD, and RD (Figure 1) while participants with worse memory showed a stronger correlation with age in MD (Figure 2), indicating an accelerated aging effect.ConclusionParticipants with SCD and worse memory present with an accelerated aging effect, showing steeper variations in diffusion microstructure with age. Since SCD is likely to be a preclinical stage of Alzheimer’s disease, future work will analyze this effect with more advanced diffusion microstructure models to further elucidate the underlying pathophysiology.1. Selnes P, Aarsland D, Bjornerud A, et al. J Alzheimers Dis. 2013;33(3):723‐36.2. Jack Jr CR, Knopman DS, Jagust WJ, et al. The Lancet Neurology. 2013;12(2):207‐16.3. Shafto MA, Tyler LK, Dixon M, et al. BMC neurology. 2014;14(1):1‐25.