Objective: Cognitive reserve has emerged as a concept to explain the variable expression of clinical symptoms in the pathology of Alzheimer’s disease (AD). The association between years of education, a proxy of cognitive reserve, and resting-state functional connectivity (rFC), a representative intermediate phenotype, has not been explored in the preclinical phase, considering risk factors for AD. We aimed to evaluate whether the relationship between years of education and rFC in cognitively preserved older adults differs depending on amyloid-beta deposition and APOE ε4 carrier status as effect modifiers. Methods: A total of 121 participants underwent functional magnetic resonance imaging, [ 18F] flutemetamol positron emission tomography-computed tomography, APOE genotyping, and a neuropsychological battery. Potential interactions between years of education and AD risk factors for rFC of AD-vulnerable neural networks were assessed with wholebrain voxel-wise analysis. Results: We found a significant education years-by-APOE ε4 carrier status interaction for the rFC from the seed region of the central executive (CEN) and dorsal attention networks. Moreover, there was a significant interaction of rFC between right superior occipital gyrus and the CEN seed region by APOE ε4 carrier status for memory performances and overall cognitive function. Conclusion In preclinical APOE ε4 carriers, higher years of education were associated with higher rFC of the AD vulnerable network, but this contributed to lower cognitive function. These results contribute to a deeper understanding of the impact of cognitive reserve on sensitive functional intermediate phenotypic markers in the preclinical phase of AD.

Purpose: Neuroinflammation is considered an important pathway associated with several diseases that result in cognitive decline. 18F-THK5351 positron emission tomography (PET) signals might indicate the presence of neuroinflammation, as well as Alzheimer’s disease-type tau aggregates. β-amyloid (Aβ)-negative (Aβ–) amnestic mild cognitive impairment (aMCI) may be associated with non-Alzheimer’s disease pathophysiology. Accordingly, we investigated associations between 18F-THK5351 PET positivity and cognitive decline among Aβ– aMCI patients. Materials and Methods: The present study included 25 amyloid PET negative aMCI patients who underwent a minimum of two follow-up neuropsychological evaluations, including clinical dementia rating-sum of boxes (CDR-SOB). The patients were classified into two groups: 18F-THK5351-positive and -negative groups. The present study used a linear mixed effects model to estimate the effects of 18F-THK5351 PET positivity on cognitive prognosis among Aβ– aMCI patients. Results: Among the 25 Aβ– aMCI patients, 10 (40.0%) were 18F-THK5351 positive. The patients in the 18F-THK5351-positive group were older than those in the 18F-THK5351-negative group (77.4±2.2 years vs. 70.0±5.5 years; p<0.001). There was no difference between the two groups with regard to the proportion of apolipoprotein E ε4 carriers. Interestingly, however, the CDR-SOB scores of the 18F-THK5351-positive group deteriorated at a faster rate than those of the 18F-THK5351-negative group (B=0.003, p=0.033). Conclusion The results of the present study suggest that increased 18F-THK5351 uptake might be a useful predictor of poor prognosis among Aβ– aMCI patients, which might be associated with increased neuroinflammation (ClinicalTrials.gov NCT02656498).

Purpose: The purpose of this study was to calculate the cutoff value for amyloid β (Aβ) positron emission tomography (PET) positivity using the iterative outlier method and to evaluate its validity based on the concordance rate. Methods: We performed the iterative outlier method on 373 cognitively unimpaired (CU) subjects and calculated the optimal cutoff value for Aβ positivity. The validation was performed using the independent dataset, comprising 83 subjects (27 CU, 27 amnestic mild cognitive impairment, and 29 Alzheimer’s dementia). We evaluated the validity of the Aβ cutoff value by calculating its concordance rate with the visual assessment and between two different Aβ tracers performed in the same subject. Results: The concordance rate of Aβ cutoff values with the visual assessment ranged from 84.3% to 91.5%, depending on the reference regions. The concordance rate of the cutoff values between the two Aβ tracers ranged from 90.3% to 97.5%, all of which were higher than that of the visual assessment (86.7%). Conclusion We demonstrated that the iterative outlier method could identify the cutoff value for Aβ PET positivity.