Graph analysis of structural brain networks in Alzheimer’s disease

Majnu John; Toshikazu Ikuta; Janina D Ferbinteanu

doi:10.1101/050708

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bioRxiv · 10.1101/050708

Graph analysis of structural brain networks in Alzheimer’s disease

Majnu John·Toshikazu Ikuta·Janina D Ferbinteanu

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Abstract

BackgroundChanges in brain connectivity in patients with early Alzheimers disease (AD) have been investigated using graph analysis. However, these studies were based on small data sets, explored a limited range of network parameters, and did not focus on more restricted sub-networks, where neurodegenerative processes may introduce more prominent alterations.\n\nMethodsIn this study, we constructed structural brain networks out of 87 regions by using data from 135 healthy elders and 100 early AD patients selected from the Open Access Series of Imaging Studies (OASIS) database. We evaluated the graph properties of these networks by investigating metrics of network efficiency, small world properties, segregation, product measures of complexity, and entropy. Because degenerative processes take place at different rates in different brain areas, analysis restricted to sub-networks may reveal changes otherwise undetected. Therefore, we first analyzed the graph properties of a network encompassing all brain areas considered together, and then repeated the analysis after dividing the brain areas into two sub-networks constructed by applying a clustering algorithm.\n\nResultsAt the level of large scale network, the analysis did not reveal differences between AD patients and controls. In contrast, the same analysis performed on the two sub-networks revealed modifications accompanying AD. Changes in small world properties suggested that the ability to engage concomitantly in integration and segregation of information diminished with AD in the sub-network containing the areas of medial temporal lobe known to be heaviest and earliest affected. In contrast, we found that the second network showed an increase in small world propensity, a novel metric that unbiasedly quantifies small world structure. Complexity and entropy measures indicated that the intricacy of connection patterns and structural diversity decreased in both sub-networks.\n\nConclusionsThese results show that neurodegenerative processes impact volumetric networks in a non-global fashion. Our findings provide new quantitative insights into topological principles of structural brain networks and their modifications during early stages of Alzheimers disease.

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Majnu John, Toshikazu Ikuta, Janina D Ferbinteanu. 2016-04-29. Graph analysis of structural brain networks in Alzheimer’s disease. https://doi.org/10.1101/050708

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