Resting-State Network Alterations Differ between Alzheimer's Disease Atrophy Subtypes

Boris Stephan Rauchmann, Ersin Ersoezlue, Sophia Stoecklein, Daniel Keeser, Frederic Brosseron, Katharina Buerger, Peter Dechent, Laura Dobisch, Birgit Ertl-Wagner, Klaus Fliessbach, John Dylan Haynes, Michael T. Heneka, Enise I. Incesoy, Daniel Janowitz, Ingo Kilimann, Christoph Laske, Coraline D. Metzger, Matthias H. Munk, Oliver Peters, Josef PrillerAlfredo Ramirez, Sandra Roeske, Nina Roy, Klaus Scheffler, Anja Schneider, Annika Spottke, Eike Jakob Spruth, Stefan Teipel, Maike Tscheuschler, Ruth Vukovich, Michael Wagner, Jens Wiltfang, Renat Yakupov, Emrah Duezel, Frank Jessen, Robert Perneczky

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Several Alzheimer's disease (AD) atrophy subtypes were identified, but their brain network properties are unclear. We analyzed data from two independent datasets, including 166 participants (103 AD/63 controls) from the DZNE-longitudinal cognitive impairment and dementia study and 151 participants (121 AD/30 controls) from the AD neuroimaging initiative cohorts, aiming to identify differences between AD atrophy subtypes in resting-state functional magnetic resonance imaging intra-network connectivity (INC) and global and nodal network properties. Using a data-driven clustering approach, we identified four AD atrophy subtypes with differences in functional connectivity, accompanied by clinical and biomarker alterations, including a medio-temporal-predominant (S-MT), a limbic-predominant (S-L), a diffuse (S-D), and a mild-atrophy (S-MA) subtype. S-MT and S-D showed INC reduction in the default mode, dorsal attention, visual and limbic network, and a pronounced reduction of "global efficiency"and decrease of the "clustering coefficient"in parietal and temporal lobes. Despite severe atrophy in limbic areas, the S-L exhibited only marginal global network but substantial nodal network failure. S-MA, in contrast, showed limited impairment in clinical and cognitive scores but pronounced global network failure. Our results contribute toward a better understanding of heterogeneity in AD with the detection of distinct differences in functional connectivity networks accompanied by CSF biomarker and cognitive differences in AD subtypes.

Original languageEnglish
Pages (from-to)4901-4915
Number of pages15
JournalCerebral Cortex
Volume31
Issue number11
DOIs
StatePublished - 1 Nov 2021
Externally publishedYes

Keywords

  • Alzheimer's disease
  • brain structure
  • graph theory
  • independent component analysis
  • resting-state connectivity

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