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 CACNA1C risk allele rs1006737 is associated with age-related prefrontal cortical thinning in bipolar I disorder.

Calcium channels control the inflow of calcium ions into cells and are involved in diverse cellular functions. The CACNA1C gene polymorphism rs1006737 A allele has been strongly associated with increased risk for bipolar disorder (BD) and with modulation of brain morphology. The medial prefrontal cortex (mPFC) has been widely associated with mood regulation in BD, but the role of this CACNA1C polymorphism in mPFC morphology and brain aging has yet to be elucidated. One hundred seventeen euthymic BD type I subjects were genotyped for CACNA1C rs1006737 and underwent 3 T three-dimensional structural magnetic resonance imaging scans to determine cortical thickness of mPFC components (superior frontal cortex (sFC), medial orbitofrontal cortex (mOFC), caudal anterior cingulate cortex (cACC) and rostral anterior cingulate cortex (rACC)). Carriers of the CACNA1C allele A exhibited greater left mOFC thickness compared to non-carriers. Moreover, CACNA1C A carriers showed age-related cortical thinning of the left cACC, whereas among A non-carriers there was not an effect of age on left cACC cortical thinning. In the sFC, mOFC and rACC (left or right), a negative correlation was observed between age and cortical thickness, regardless of CACNA1C rs1006737 A status. Further studies investigating the direct link between cortical thickness, calcium channel function, apoptosis mechanism and their underlying relationship with aging-associated cognitive decline in BD are warranted.