Multiple Brain Markers are Linked to Age-Related Variation in Cognition

Abstract

Age-related alterations in brain structure and function have been challenging to link to cognition due to potential overlapping influences of multiple neurobiological cascades. We examined multiple brain markers associated with age-related variation in cognition. Clinically normal older humans aged 65-90 from the Harvard Aging Brain Study (N = 186) were characterized on a priori magnetic resonance imaging markers of gray matter thickness and volume, white matter hyperintensities, fractional anisotropy (FA), resting-state functional connectivity, positron emission tomography markers of glucose metabolism and amyloid burden, and cognitive factors of processing speed, executive function, and episodic memory. Partial correlation and mediation analyses estimated age-related variance in cognition shared with individual brain markers and unique to each marker. The largest relationships linked FA and striatum volume to processing speed and executive function, and hippocampal volume to episodic memory. Of the age-related variance in cognition, 70-80% was accounted for by combining all brain markers (but only ∼20% of total variance). Age had significant indirect effects on cognition via brain markers, with significant markers varying across cognitive domains. These results suggest that most age-related variation in cognition is shared among multiple brain markers, but potential specificity between some brain markers and cognitive domains motivates additional study of age-related markers of neural health.

Convergent Results from Neuropsychology and from Neuroimaging in Patients with Mild Cognitive Impairment

“…ROIs were limited and selected based on previous findings [7,8,12,14,32]. In a similar vein, we only included a few neuropsychological tests that have been meticulously shown to predict longitudinal outcome on par or better than biomarkers [28,29,38,39].…”

“…Considerable advances in linking different biomarkers with cognitive symptoms have been achieved [3,4]. Although diagnostic research criteria for Alzheimer disease (AD) now emphasize cognitive symptoms in addition to at least 1 pathological biomarker [5], the correspondence between neuropsychological tests and standard AD neuroimaging markers remains incomplete [6,7]. …”

“…The relationship between neuropsychological performance and individual variation in clinical AD neuroimaging markers is likely to be both convergent and unique [7]. Cognitive decline in AD is postulated as consequential from neural pathology as portrayed by biomarkers [3], and the specificity of these associations has been partly investigated [8,9].…”

“…FDG PET is a functional marker of cortical glucose metabolism, and MRI gives a structural measure of grey matter density [23]. Cortical hypometabolism is postulated to precede and possibly lead to cortical atrophy [3], but the correlation between FDG PET and MRI is not particularly strong [4,7,24,25]. This may be due to discrepant mechanisms that ultimately cause deficient metabolism and cell death [4,25].…”

“…With regard to clinical prediction, evidence indicates that the most sensitive neuropsychological tests have similar or better predictive utility than biomarkers with regard to conversion to dementia [28,29,38,39]. Many studies modify classical tests or they may use elaborate composite scores [6,7,40], which challenges the extrapolation of research findings to the relationship between neuropsychological data available to the clinician and standard neuroimaging markers.…”