James Cole

While neurological manifestations are core features of Fabry disease (FD), quantitative neuroimaging biomarkers allowing to measure brain involvement are lacking. We used deep learning and the brain‐age paradigm to assess whether FD patients' brains appear older than normal and to validate brain‐predicted age difference (brain‐PAD) as a possible disease severity biomarker. MRI scans of FD patients and healthy controls (HCs) from a single Institution were, retrospectively, studied. The Fabry stabilization index (FASTEX) was recorded as a measure of disease severity. Using minimally preprocessed 3D T1‐weighted brain scans of healthy subjects from eight publicly available sources ( N = 2160; mean age = 33 years [range 4–86]), we trained a model predicting chronological age based on a DenseNet architecture and used it to generate brain‐age predictions in the internal cohort. Within a linear modeling framework, brain‐PAD was tested for age/sex‐adjusted associations with diagnostic group (FD vs. HC), FASTEX score, and both global and voxel‐level neuroimaging measures. We studied 52 FD patients (40.6 ± 12.6 years; 28F) and 58 HC (38.4 ± 13.4 years; 28F). The brain‐age model achieved accurate out‐of‐sample performance (mean absolute error = 4.01 years, R 2 = .90). FD patients had significantly higher brain‐PAD than HC (estimated marginal means: 3.1 vs. −0.1, p = .01). Brain‐PAD was associated with FASTEX score ( B = 0.10, p = .02), brain parenchymal fraction ( B = −153.50, p = .001), white matter hyperintensities load ( B = 0.85, p = .01), and tissue volume reduction throughout the brain. We demonstrated that FD patients' brains appear older than normal. Brain‐PAD correlates with FD‐related multi‐organ damage and is influenced by both global brain volume and white matter hyperintensities, offering a comprehensive biomarker of (neurological) disease severity.

Study Objectives To assess for associations between sleeping more than or less than recommended by the National Sleep Foundation (NSF), and self-reported insomnia, with brain structure. Methods Data from the UK Biobank cohort were analyzed (N between 9K and 32K, dependent on availability, aged 44 to 82 years). Sleep measures included self-reported adherence to NSF guidelines on sleep duration (sleeping between 7 and 9 hours per night), and self-reported difficulty falling or staying asleep (insomnia). Brain structural measures included global and regional cortical or subcortical morphometry (thickness, surface area, volume), global and tract-related white matter microstructure, brain age gap (difference between chronological age and age estimated from brain scan), and total volume of white matter lesions. Results Longer-than-recommended sleep duration was associated with lower overall grey and white matter volumes, lower global and regional cortical thickness and volume measures, higher brain age gap, higher volume of white matter lesions, higher mean diffusivity globally and in thalamic and association fibers, and lower volume of the hippocampus. Shorter-than-recommended sleep duration was related to higher global and cerebellar white matter volumes, lower global and regional cortical surface areas, and lower fractional anisotropy in projection fibers. Self-reported insomnia was associated with higher global gray and white matter volumes, and with higher volumes of the amygdala, hippocampus, and putamen. Conclusions Sleeping longer than recommended by the NSF is associated with a wide range of differences in brain structure, potentially indicative of poorer brain health. Sleeping less than recommended is distinctly associated with lower cortical surface areas. Future studies should assess the potential mechanisms of these differences and investigate long sleep duration as a putative marker of brain health.