Modeling Alzheimer's disease progression using the disease system analysis approach

Alzheimers Dement. 2012 Jan;8(1):39-50. doi: 10.1016/j.jalz.2010.12.012. Epub 2011 Jul 22.

Abstract

A novel mechanistic model based on a disease system analysis paradigm was developed to explore the role of homeostatic mechanisms involved in Alzheimer's disease (AD) progression. We used longitudinal AD Assessment Scale-cognitive subscale (ADAS-cog) scores from 926 subjects with AD on stable acetylcholinesterase inhibitor therapy randomized to placebo treatment in two 54-week clinical trials. Alternative mechanistic models were evaluated by assuming that the rate of change of ADAS-cog over time was jointly regulated by a process characterizing the deterioration of ADAS-cog and by a process associated with a compensatory regulatory response. The model based on a time-varying deterioration rate of ADAS-cog performed better than the model based on a time-varying homeostatic control. The covariate analysis indicated that baseline Mini-Mental State Examination score, education, age, and apolipoprotein ɛ4 genotype had a significant effect on the level and shape of the trajectories of the mean model predicted ADAS-cog change from baseline.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Alzheimer Disease / complications*
  • Alzheimer Disease / diagnosis*
  • Alzheimer Disease / drug therapy
  • Apolipoprotein E4 / genetics
  • Cholinesterase Inhibitors / therapeutic use
  • Cognition Disorders / etiology*
  • Databases, Bibliographic / statistics & numerical data
  • Disease Progression
  • Female
  • Humans
  • Linear Models
  • Longitudinal Studies
  • Male
  • Middle Aged
  • Models, Theoretical*
  • Neuropsychological Tests
  • Randomized Controlled Trials as Topic
  • Time Factors

Substances

  • Apolipoprotein E4
  • Cholinesterase Inhibitors