Investigating Grey Matter Network Alterations in Preclinical Alzheimer's Disease Using Graph Theoretical Measures

Alzheimer’s Disease (AD) is the leading cause of dementia. Given the growing number of older population, it becomes a concerning healtcare issue. The brain begins to deteriorate several years before the emergence of clinical symptoms. AD is characterized by neuronal and synaptic degeneration, accumulation of amyloid beta plaques and tau tangles. Besides, changes in gray matter networks have been reported in early stages of the disease which have been associated with amyloid beta deposition and tau pathology. In this study, we investigated the relationship between changes in gray matter networks and biomarkers of amyloid beta and tau in preclinical AD cohort by using graph theoretical measures. We included 362 cognitively unimpaired individuals. We examined which graph properties were changed across individuals. On a global level, we found increased average path length, average betweenness centrality, and gamma, lambda and small world values were increased when p-tau levels were higher. Regionally, significant relationship was found between p-tau levels and betweenness centrality in left superior frontal gyrus orbital. Furthermore, average clustering measure had a significant association with lobule 1-2 of vermis. Findings suggest that in the preclinical stage, gray matter properties show changes and this can be used to identify future clinical symptom progression in AD research.