title: A robust biomarker of large-scale network failure in Alzheimer's disease.
abstract: BACKGROUND
  Biomarkers for Alzheimer's disease (AD) pathophysiology have been developed that focus on various levels of brain organization. However, no robust biomarker of large-scale network failure has been developed. Using the recently introduced cascading network failure model of AD, we developed the network failure quotient (NFQ) as a biomarker of this process.
  
  
  METHODS
  We developed and optimized the NFQ using our recently published analyses of task-free functional magnetic resonance imaging data in clinically normal (n = 43) and AD dementia participants (n = 28) from the Alzheimer's Disease Neuroimaging Initiative. The optimized NFQ (oNFQ) was then validated in a cohort spanning the AD spectrum from the Mayo Clinic (n = 218).
  
  
  RESULTS
  The oNFQ (d= 1.25, 95% confidence interval [1.25, 1.26]) had the highest effect size for differentiating persons with AD dementia from clinically normal participants. The oNFQ measure performed similarly well on the validation Mayo Clinic sample (d= 1.44, 95% confidence interval [1.43, 1.44]). The oNFQ was also associated with other available key biomarkers in the Mayo cohort.
  
  
  CONCLUSIONS
  This study demonstrates a measure of functional connectivity, based on a cascading network failure model of AD, and was highly successful in identifying AD dementia. A robust biomarker of the large-scale effects of AD pathophysiology will allow for richer descriptions of the disease process and its modifiers, but is not currently suitable for discriminating clinical diagnostic categories. The large-scale network level may be one of the earliest manifestations of AD, making this an attractive target for continued biomarker development to be used in prevention trials.
authors.affiliation: Department of Neurology, Mayo Clinic, Rochester, MN, USA.
authors.forename: Daniela A
authors.initials: DA
authors.lastname: Wiepert
authors.affiliation: Department of Radiology, Mayo Clinic, Rochester, MN, USA.
authors.forename: Val J
authors.initials: VJ
authors.lastname: Lowe
authors.affiliation: Department of Neurology, Mayo Clinic, Rochester, MN, USA.
authors.forename: David S
authors.initials: DS
authors.lastname: Knopman
authors.affiliation: Department of Neurology, Mayo Clinic, Rochester, MN, USA.
authors.forename: Bradley F
authors.initials: BF
authors.lastname: Boeve
authors.affiliation: Department of Neurology, Mayo Clinic, Rochester, MN, USA.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Graff-Radford
authors.affiliation: Department of Neurology, Mayo Clinic, Rochester, MN, USA.
authors.forename: Ronald C
authors.initials: RC
authors.lastname: Petersen
authors.affiliation: Department of Radiology, Mayo Clinic, Rochester, MN, USA.
authors.forename: Clifford R
authors.initials: CR
authors.lastname: Jack
authors.affiliation: Department of Neurology, Mayo Clinic, Rochester, MN, USA; Department of Radiology, Mayo Clinic, Rochester, MN, USA.
authors.forename: David T
authors.initials: DT
authors.lastname: Jones
keywords: Alzheimer's disease; Biomarker; Cascading network failure; Connectivity; Default mode network