Objective: To determine whether white matter changes influence progression of cognitive decline in individuals with clinically diagnosed Alzheimer disease (AD) and differing biomarker profiles.
Methods: Two hundred thirty-six individuals from the Alzheimer's Disease Neuroimaging Initiative database with clinical diagnoses of cognitively normal older adult (older controls [OCs]), mild cognitive impairment, and AD were studied. Support vector machine experiments were first performed to determine the utility of various biomarkers for classifying individuals by clinical diagnosis. General linear models were implemented to assess the relationships between CSF measures of β-amyloid 1-42, phosphorylated tau181p, and MRI-based white matter signal abnormality (WMSA) volumes and cognitive decline. Analyses were performed across all patients as well as within subgroups of individuals that were defined by clinical cutoff points for both CSF measures.
Results: CSF biomarkers alone classified individuals with AD vs OCs with 82% accuracy, and the addition of WMSA did not enhance this. Both CSF biomarkers as well as WMSA volume significantly contributed to predicting cognitive decline in executive and memory domains when assessed across all 236 individuals. In individuals with pathologic levels of both CSF biomarkers, WMSA only significantly contributed to models of future executive function decline. In individuals with subpathologic CSF biomarker levels (levels similar to those in OC individuals), WMSA significantly contributed to prediction of memory decline and were the sole significant predictor of executive function decline.
Conclusions: WMSA hold additional predictive power regarding cognitive progression in older individuals and are most effective as biomarkers in individuals who are cognitively impaired but do not fit the expected CSF biomarker profile of AD.
© 2018 American Academy of Neurology.