Brain anatomical connectivity in offspring of patients with Alzheimer?s Disease through graph theory

SÁNCHEZ S. M.; DE PINO G.; BOCACCIO H.; CASTRO M. N.; DUARTE-ABRITTA B.; ABULAFIA C.; GUINJOAN S. M.; VILLARREAL M.

CABA

Congreso; Stat Phys 27; 2019

International Union of Pure and Applied Physics (IUPAP)

In the last decades, graph theoretical approaches have been applied to characterize human brain organization both in health and disease scenarios. One way to describe human brain, is through anatomical brain connectivity, which can be obtained from diffusion MRI techniques developed to reconstruct white matter fiber trajectories and link different gray matter brain regions. Anatomical brain connectomes resulted from the combination of these two elements (fiber trajectories as edges and gray matter regions as nodes) and they have features that can be emphasized by complex networks, even in cases of neurodegenerative disease. According to recent literature, Alzheimer?s Disease (AD) patients present anomalies in white matter fibers that affect anatomical connectivity. In this work, we analysed anatomical connectivity through brain networks in a group of 23 middle-aged (40-60 years), cognitively intact individuals who present a higher risk of developing late-onset Alzheimer?s disease (LOAD) by virtue of having at least one parent diagnosed, and in another group of 22 age- and sex-matched control subjects (CS) without family history of AD. To investigate how these connectomes are structurally organized, we studied whether an average connectome of each group (O-LOAD and CS) have small world or random architecture. Additionally in order to understand their complex dynamics and which edges are crucial for proper communication between brain regions, we removed specific (and important, in terms of graph metrics) edges and we evaluated the behaviour of the new connectome after each remotion. Finally, to characterize the O-LOAD group, we studied its local and global graph metrics. We obtained that connectomes for both O-LOAD and CS groups have small-world topology and their global efficiency decreased when crucial edges were removed. Interestingly, only in CS group one of these crucial edges involved a connection with precune, a brain region which is early affected in AD. Each anatomical connectome obtained differed from its similar random network, in terms of global efficiency. These results suggest that graph theory allows to characterize both groups and could reveal early abnormalities in O-LOAD group.