Network analysis of cognition and function in Alzheimer's disease: a cross-sectional study

Traditional approaches in Alzheimer's disease (AD) research examine cognitive symptoms in isolation, potentially overlooking dynamic interrelationships among impairment domains. This study employed network analysis to examine structural organization of cognitive and functional domains in mild (mAD) and moderate-to-severe (Mod-sAD) Alzheimer's disease, aiming to identify stage-specific symptom structures and inform targeted interventions.

A cross-sectional study included 134 participants diagnosed with AD according to DSM-5 criteria. Participants were classified into mAD (n=37) and Mod-sAD (n=97) groups. Regularized partial correlation networks with extended Bayesian information criterion regularization examined symptom interdependencies across six CDR domains: memory, orientation, judgment and problem solving, community affairs, home and hobbies, and personal care. Network comparison tests and centrality analyses identified structural differences between disease stages.

The Mod-sAD group demonstrated significantly higher impairment scores across all domains (p < 0.001) with large effect sizes (Cohen's d: 1.83-2.71). Network analysis revealed increased global strength in Mod-sAD versus mAD networks (2.60 vs. 2.49, p < 0.05), indicating greater symptom interconnectedness in advanced stages. Centrality analyses revealed fundamental reorganization: memory emerged as most central in Mod-sAD (strength = 1.62), while judgment and problem-solving showed highest centrality in mAD (strength = 1.65). Orientation centrality increased substantially across progression (strength: -1.32 to 0.40).

AD progression features increasing network density and centrality shifts from executive-function-centered networks in mild AD to memory-centered networks in moderate-to-severe stages. Findings suggest stage-specific interventions: executive enhancement in mild AD and memory-focused approaches in advanced stages.