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Abstract Alzheimer’s disease (AD) is a brain network disorder where pathological proteins accumulate through networks and drive cognitive decline. Yet, the role of network connectivity in facilitating this accumulation remains unclear. Using in-vivo multimodal imaging, we show that the distribution of tau and reactive microglia in humans follows spatial patterns of connectivity variation, the so-called gradients of brain organization. Notably, less distinct connectivity patterns (“gradient contraction”) are associated with cognitive decline in regions with greater tau, suggesting an interaction between reduced network differentiation and tau on cognition. Furthermore, by modeling tau in subject-specific gradient space, we demonstrate that tau accumulation in the frontoparietal and temporo-occipital cortices is associated with greater baseline tau within their functionally and structurally connected hubs, respectively. Our work unveils a role for both functional and structural brain organization in pathology accumulation in AD, and supports subject-specific gradient space as a promising tool to map disease progression.

Introduction: Cerebral small vessel disease (SVD) is a common co-pathology in elderly and individuals with dementia. Neuroimaging markers of SVD include white matter hyperintensities (WMH) and MRI-visible perivascular spaces (PVS). However, the mechanisms underlying changes in these markers over time, whether ischemic or beta-amyloid (Aβ)-related, remain elusive. Here, we evaluated the effects of microstructural injury in the normal-appearing white matter and Aβ in the cerebral cortex on the progression of WMH and PVS over three years. Methods: Data was obtained from two independent cohorts: (i) TRIAD, comprising cognitively normal, MCI, and AD dementia participants (baseline: N=199, follow-up year 1 and 2: N=102 and 62); and (ii) MITNEC-C6, comprising “real-world” patients with mixed dementia and moderate-to- severe WMH burden (baseline: N=52, 2 years follow-up: N=25). We quantified global WMH and PVS volumes from FLAIR and T1w MRI. At baseline, we examined associations between these volumes and diffusion MRI-derived free water. Longitudinally, we employed linear [mixed-effect] models to investigate the relation of WMH or PVS volume changes over time with baseline free water, using cortical Aβ-PET, age, sex, and APOE-ε4 as covariates. Results: In TRIAD and MITNEC-C6 respectively, mean ages were 72±6 and 77±8 y, 60% and 42% were female, and 41% and 48% were Aβ-positive. At baseline, higher free water in normal- appearing white matter was associated with higher WMH volume (β_TRIAD=+0.34±0.06, P_TRIAD