INFLAMMATION's cognitive impact revealed by a novel "Line of Identity" approach.

Abstract

ImportanceDementia is an "overdetermined" syndrome. Few individuals are demented by any single biomarker, while several may independently explain small fractions of dementia severity. It may be advantageous to identify individuals afflicted by a specific biomarker to guide individualized treatment.ObjectiveWe aim to validate a psychometric classifier to identify persons adversely impacted by inflammation and replicate it in a second cohort.DesignSecondary analyses of data collected by the Texas Alzheimer's Research and Care Consortium (TARCC) (N = 3497) and the Alzheimer's Disease Neuroimaging Initiative (ADNI) (N = 1737).SettingTwo large, well-characterized multi-center convenience samples.ParticipantsVolunteers with normal cognition (NC), Mild Cognitive Impairment (MCI) or clinical "Alzheimer's Disease (AD)".ExposureParticipants were assigned to "Afflicted" or "Resilient" classes on the basis of a psychometric classifier derived by confirmatory factor analysis.Main outcome(s) and measure(s)The groups were contrasted on multiple assessments and biomarkers. The groups were also contrasted regarding 4-year prospective conversions to "AD" from non-demented baseline diagnoses (controls and MCI). The Afflicted groups were predicted to have adverse levels of inflammation-related blood-based biomarkers, greater dementia severity and greater risk of prospective conversion.ResultsIn ADNI /plasma, 47.1% of subjects were assigned to the Afflicted class. 44.6% of TARCC's subjects were afflicted, 49.5% of non-Hispanic Whites (NHW) and 37.2% of Mexican Americans (MA). There was greater dementia severity in the Afflicted class [by ANOVA: ADNI /F(1) = 686.99, p Conclusions and relevanceOur inflammation-specific psychometric classifier selects individuals with pre-specified biomarker profiles and predicts conversion to "AD" across cohorts, biofluids, and ethnicities. This algorithm might be applied to any dementia-related biomarker making the psychometric estimation of individual biomarker effects feasible without biomarker assessment. Our approach also distinguishes individuals resilient to individual biomarker effects allowing for more accurate prediction and precision intervention.