Disease specific and nonspecific metabolic brain networks in behavioral variant of frontotemporal dementia

Tomaž Rus, Matej Perovnik, An Vo, Nha Nguyen, Chris Tang, Jan Jamšek, Katarina Šurlan Popović, Timo Grimmer, Igor Yakushev, Janine Diehl-Schmid, David Eidelberg, Maja Trošt

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Behavioral variant of frontotemporal dementia (bvFTD) is common among young-onset dementia patients. While bvFTD-specific multivariate metabolic brain pattern (bFDRP) has been identified previously, little is known about its temporal evolution, internal structure, effect of atrophy, and its relationship with nonspecific resting-state networks such as default mode network (DMN). In this multicenter study, we explored FDG-PET brain scans of 111 bvFTD, 26 Alzheimer's disease, 16 Creutzfeldt-Jakob's disease, 24 semantic variant primary progressive aphasia (PPA), 18 nonfluent variant PPA and 77 healthy control subjects (HC) from Slovenia, USA, and Germany. bFDRP was identified in a cohort of 20 bvFTD patients and age-matched HC using scaled subprofile model/principle component analysis and validated in three independent cohorts. It was characterized by hypometabolism in frontal cortex, insula, anterior/middle cingulate, caudate, thalamus, and temporal poles. Its expression in bvFTD patients was significantly higher compared to HC and other dementia syndromes (p <.0004), correlated with cognitive decline (p =.0001), and increased over time in longitudinal cohort (p =.0007). Analysis of internal network organization by graph-theory methods revealed prominent network disruption in bvFTD patients. We have further found a specific atrophy-related pattern grossly corresponding to bFDRP; however, its contribution to the metabolic pattern was minimal. Finally, despite the overlap between bFDRP and FDG-PET-derived DMN, we demonstrated a predominant role of the specific bFDRP. Taken together, we validated the bFDRP network as a diagnostic/prognostic biomarker specific for bvFTD, provided a unique insight into its highly reproducible internal structure, and proved that bFDRP is unaffected by structural atrophy and independent of normal resting state networks loss.

Original languageEnglish
Pages (from-to)1079-1093
Number of pages15
JournalHuman Brain Mapping
Volume44
Issue number3
DOIs
StatePublished - 15 Feb 2023
Externally publishedYes

Keywords

  • FDG-PET
  • SSM/PCA
  • behavioral variant of frontotemporal dementia
  • default mode network
  • functional connectivity
  • network analysis

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