Abstract
BackgroundBiomarkers of amyloidopathy/tauopathy/neurodegeneration (A/T/N) are being invoked as evidence of Alzheimer's disease (AD). However, some individuals are resilient against their effects. We have developed a psychometric algorithm to distinguish resilient from afflicted persons, and have demonstrated it in relation to inflammation, adipokines and amyloidopathy.ObjectiveThis analysis addresses neurodegeneration.Methods1737 participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) were assigned to neurodegeneration affliction classes through a "Line of Identity (LOI)" approach. A neurodegeneration "N Factor" indicated by three biomarkers was constructed. A previously validated measure of dementia severity, "dTEL″, was regressed onto the N Factor. Affliction classes were defined by each subject's deviation from the LOI obtained from the correlation of dTEL's N-Factor-adjusted residual (CR) versus unadjusted dTEL scores. Moderation effects on the N Factor's association with dTEL were tested by Chi Square difference. Class effects on prospective conversion to clinical "AD" from non-demented baseline diagnoses (NC + MCI) were tested by survival analysis.Results49.4% of ADNI subjects were afflicted by neurodegeneration. The Afflicted class had greater dementia severity, lower (adverse) N factor composite scores and higher observed levels of CNS neurodegeneration. These differences reflected the unique effect of neurodegeneration. Affliction class was not associated with other AD-related biomarkers. Afflicted cases were more likely to convert to clinical "AD" over 48 months [by Cox's F: F (164, 356) = 3.65, p < 0.001.ConclusionsOur approach could allow for more accurate prediction of biomarker effects and guide precision interventions.