{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T02:24:15Z","timestamp":1783131855271,"version":"3.54.6"},"reference-count":64,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,11,21]],"date-time":"2023-11-21T00:00:00Z","timestamp":1700524800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neurosci."],"abstract":"<jats:p>Late-onset Alzheimer\u2019s disease (LOAD) is a major health concern for senior citizens, characterized by memory loss, confusion, and impaired cognitive abilities. Apolipoprotein-E (ApoE) is a well-known risk factor for LOAD, though exactly how ApoE affects LOAD risks is unknown. We hypothesize that ApoE attenuation of LOAD resiliency or vulnerability has a neurodevelopmental origin <jats:italic>via<\/jats:italic> changing brain network architecture. We investigated the brain network structure in adult ApoE knock out (ApoE KO) and wild-type (WT) mice with diffusion tensor imaging (DTI) followed by graph theory to delineate brain network topology. Left and right hemisphere connectivity revealed significant differences in number of connections between the hippocampus, amygdala, caudate putamen and other brain regions. Network topology based on the graph theory of ApoE KO demonstrated decreased functional integration, network efficiency, and network segregation between the hippocampus and amygdala and the rest of the brain, compared to those in WT counterparts. Our data show that brain network developed differently in ApoE KO and WT mice at 5\u2009months of age, especially in the network reflected in the hippocampus, amygdala, and caudate putamen. This indicates that ApoE is involved in brain network development which might modulate LOAD risks <jats:italic>via<\/jats:italic> changing brain network structures.<\/jats:p>","DOI":"10.3389\/fnins.2023.1183312","type":"journal-article","created":{"date-parts":[[2023,11,23]],"date-time":"2023-11-23T15:08:40Z","timestamp":1700752120000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Apolipoprotein-E deficiency leads to brain network alteration characterized by diffusion MRI and graph theory"],"prefix":"10.3389","volume":"17","author":[{"given":"Margaret Caroline","family":"Stapleton","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefan Paul","family":"Koch","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Devin Raine Everaldo","family":"Cortes","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Samuel","family":"Wyman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kristina E.","family":"Schwab","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Susanne","family":"Mueller","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher Gordon","family":"McKennan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Philipp","family":"Boehm-Sturm","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yijen Lin","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2023,11,21]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1523\/JNEUROSCI.3874-05.2006","article-title":"A resilient, low-frequency, small-world human brain functional network with highly connected association cortical hubs","volume":"26","author":"Achard","year":"2006","journal-title":"J. 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