Dissociable, species-specific impact of Aβ on static and dynamic functional connectomes

Abstract

Temporal dynamics in functional connectomes offer a physiologically grounded signature of hidden pathologies during preclinical stages of Alzheimers disease (AD). We evaluated the effect of beta-amyloid (A{beta}) on dynamic functional connectomes in transgenic mice and human subjects. Functional magnetic resonance images (fMRI) were collected in two strains of A{beta} mice. fMRI-derived connectomes were segmented into discrete states using a hidden Markov model and network strength, efficiency, and transitivity were analyzed per state. Human fMRI-derived connectome measures were analyzed across 3 states. Static network measures were significantly different between A{beta} mice and controls, the former having high values for strength, efficiency and clustering coefficient in anterior cingulate, hippocampus and retrosplenium. Dynamic network measures were stable within-states in A{beta} mice. Similarly, human subjects with high A{beta} had high node strength in precuneus and temporoparietal areas compared to low A{beta}. In contrast, however, high A{beta} was associated with high state switch rates, high fractional occupancy and state dwell times. Also, global strength, efficiency, and transitivity were less stable within states in the high A{beta} group. Our results indicate that static, but not dynamic, connectome strength, efficiency and network integration are increased in A{beta} mice, while dynamic network states appear less stable in human functional connectomes. This data supports a dissociable, species-specific impact of A{beta}, with dynamic network alterations present in humans but not in A{beta} mouse models, suggesting additional non-A{beta}-driven influences on dynamic functional connectivity in preclinical AD. SIGNIFICANT STATEMENTDetecting Alzheimers disease before symptoms appear remains a critical challenge. This study reveals that beta-amyloid -- a hallmark Alzheimers protein -- disrupts brain network dynamics differently across species. While both transgenic mice and humans with elevated amyloid show stronger static brain connectivity, only humans exhibit unstable, rapidly shifting brain network states. This dissociation suggests that the dynamic network disruptions seen in preclinical Alzheimers patients are not solely driven by amyloid accumulation, but likely reflect additional biological factors absent in mouse models. These findings highlight an important translational gap between animal models and human disease, with implications for how we design and interpret preclinical Alzheimers research and develop early diagnostic biomarkers.