Phenotyping Superagers Using Resting-State fMRI.

BACKGROUND AND PURPOSE: Superagers are defined as older adults with episodic memory performance similar or superior to that in middle-aged adults. This study aimed to investigate the key differences in discriminative networks and their main nodes between superagers and cognitively average elderly controls. In addition, we sought to explore differences in sensitivity in detecting these functional activities across the networks at 3T and 7T MR imaging fields. MATERIALS AND METHODS: Fifty-five subjects 80 years of age or older were screened using a detailed neuropsychological protocol, and 31 participants, comprising 14 superagers and 17 cognitively average elderly controls, were included for analysis. Participants underwent resting-state-fMRI at 3T and 7T MR imaging. A prediction classification algorithm using a penalized regression model on the measurements of the network was used to calculate the probabilities of a healthy older adult being a superager. Additionally, ORs quantified the influence of each node across preselected networks. RESULTS: The key networks that differentiated superagers and elderly controls were the default mode, salience, and language networks. The most discriminative nodes (ORs > 1) in superagers encompassed areas in the precuneus posterior cingulate cortex, prefrontal cortex, temporoparietal junction, temporal pole, extrastriate superior cortex, and insula. The prediction classification model for being a superager showed better performance using the 7T compared with 3T resting-state-fMRI data set. CONCLUSIONS: Our findings suggest that the functional connectivity in the default mode, salience, and language networks can provide potential imaging biomarkers for predicting superagers. The 7T field holds promise for the most appropriate study setting to accurately detect the functional connectivity patterns in superagers.

The Brain Metabolic Signature in Superagers Using In Vivo 1H-MRS: A Pilot Study.

BACKGROUND AND PURPOSE: Youthful memory performance in older adults may reflect an underlying resilience to the conventional pathways of aging. Subjects having this unusual characteristic have been recently termed "superagers." This study aimed to explore the significance of imaging biomarkers acquired by 1H-MRS to characterize superagers and to differentiate them from their normal-aging peers. MATERIALS AND METHODS: Fifty-five patients older than 80 years of age were screened using a detailed neuropsychological protocol, and 25 participants, comprising 12 superagers and 13 age-matched controls, were statistically analyzed. We used state-of-the-art 3T 1H-MR spectroscopy to quantify 18 neurochemicals in the posterior cingulate cortex of our subjects. All 1H-MR spectroscopy data were analyzed using LCModel. Results were further processed using 2 approaches to investigate the technique accuracy: 1) comparison of the average concentration of metabolites estimated with Cramer-Rao lower bounds <20%; and 2) calculation and comparison of the weighted means of metabolites' concentrations. RESULTS: The main finding observed was a higher total N-acetyl aspartate concentration in superagers than in age-matched controls using both approaches (P = .02 and P = .03 for the weighted means), reflecting a positive association of total N-acetyl aspartate with higher cognitive performance. CONCLUSIONS: 1H-MR spectroscopy emerges as a promising technique to unravel neurochemical mechanisms related to cognitive aging in vivo and providing a brain metabolic signature in superagers. This may contribute to monitoring future interventional therapies to avoid or postpone the pathologic processes of aging.