| Summary: | Abstract Background Amyloid-beta (Aβ) has a dose-response relationship with cognition in healthy adults. Additionally, the levels of functional connectivity within and between brain networks have been associated with cognitive performance in healthy adults. Aiming to explore potential synergistic effects, we investigated the relationship of inter-network functional connectivity, Aβ burden, and memory decline among healthy individuals and individuals with preclinical, prodromal, or clinical Alzheimer’s disease. Methods In this longitudinal cohort study (ADNI2), participants (55–88 years) were followed for a maximum of 5 years. We included cognitively healthy participants and patients with mild cognitive impairment (with or without elevated Aβ) or Alzheimer’s disease. Associations between memory decline, Aβ burden, and connectivity between networks across the groups were investigated using linear and curvilinear mixed-effects models. Results We found a synergistic relationships between inter-network functional connectivity and Aβ burden on memory decline. Dose-response relationships between Aβ and memory decline varied as a function of directionality of inter-network connectivity across groups. When inter-network correlations were negative, the curvilinear mixed-effects models revealed that higher Aβ burden was associated with greater memory decline in cognitively normal participants, but when inter-network correlations were positive, there was no association between the magnitude of Aβ burden and memory decline. Opposite patterns were observed in patients with mild cognitive impairment. Combining negative inter-network correlations with Aβ burden can reduce the required sample size by 88% for clinical trials aiming to slow down memory decline. Conclusions The direction of inter-network connectivity provides additional information about Aβ burden on the rate of expected memory decline, especially in the preclinical phase. These results may be valuable for optimizing patient selection and decreasing study times to assess efficacy in clinical trials.
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