Purpose Neuroinflammation is considered an important pathway associated with several diseases that result in cognitive decline. 18 F-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 18 F-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: 18 F-THK5351-positive and -negative groups. The present study used a linear mixed effects model to estimate the effects of 18 F-THK5351 PET positivity on cognitive prognosis among Aβ– aMCI patients. Results Among the 25 Aβ– aMCI patients, 10 (40.0%) were 18 F-THK5351 positive. The patients in the 18 F-THK5351-positive group were older than those in the 18 F-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 18 F-THK5351-positive group deteriorated at a faster rate than those of the 18 F-THK5351-negative group (B=0.003, p =0.033). Conclusion The results of the present study suggest that increased 18 F-THK5351 uptake might be a useful predictor of poor prognosis among Aβ– aMCI patients, which might be associated with increased neuroinflammation (ClinicalTrials.gov NCT02656498 ).
Background and purpose: Previous studies have developed several cognitive composites in preclinical Alzheimer disease (AD). However, more sensitive measures to track cognitive changes and therapeutic efficacy in preclinical AD are needed considering the diverse sociocultural and linguistic backgrounds. This study developed a composite score that can sensitively detect the amyloidβ (Aβ)-related cognitive trajectory of preclinical AD using Korean data. Methods: A total of 196 cognitively normal participants who underwent amyloid positron emission tomography were followed-up with neuropsychological assessments. We developed the Longitudinal Amyloid Cognitive Composite in Preclinical AD (LACPA) using the linear mixed-effects model (LMM) and z scores. The LMM was also used to investigate the longitudinal sensitivity of the LACPA and the association between time-varying brain atrophy and the LACPA. Results: Considering the group-time interaction effects of each subtest, the Seoul Verbal Learning Test-Elderly version immediate recall/delayed recall/recognition, the Korean Trail Making Test B Time, and the Korean Mini-Mental State Examination were selected as components of the LACPA. The LACPA exhibited a significant group-time interaction effect between the Aβ+ and Aβ− groups (t = −3.288, p = 0.001). Associations between time-varying LACPA and brain atrophy were found in the bilateral medial temporal, right lateral parietal, and right lateral frontal regions, and hippocampal volume. Conclusions:The LACPA may contribute to reduction in time and financial burden when monitoring Aβ-related cognitive decline and therapeutic efficacy of the disease-modifying agents specifically targeting Aβ in secondary prevention trials.
Background: Amyloid-β (Aβ) accumulation, a major biomarker in Alzheimer's disease (AD), induces tau accumulation, eventually resulting in cognitive decline. However, Aβ trajectory in cognitively normal participants has not been extensively investigated, yet.Modeling of Aβ trajectory remains an important goal, as future treatments targeting Aβ are expected to be developed. In the present study, we therefore investigated whether they might be divided into the normal aging group and the pathological group with increased amyloid. We also compared the differences between the non-accumulating group and accumulating group. Method: We included 297 subjects from the Alzheimer's Disease Neuroimaging Initiative database, who showed normal cognition at baseline. All subjects underwent neuropsychological test, apolipoprotein E (APOE) genotype test, brain MRI, and an average of 3.03 follow-up 18 F-florbetapir (AV45) PET scans. The original dataset was divided by 6:4 to create a training set and a validation set. Latent Class Growth Analysis was used for statistical analysis.Result: Based on the information criterion, the model consisting of three classes was found to be the best with a high entropy of 0.979: class 1 (non-accumulating group; n = 117, 65.7%), class 2 (accumulating group; n = 46, 25.8%), and class 3 (high accumulation group; n = 15, 8.4%) (Figure). The accumulating group had more APOE ε4 carriers and a higher tau burden than the non-accumulating group (Table ). Conclusion:Our study showed that there is the heterogeneity of Aβ trajectories according to aging in the normal cognitive elderly. Heterogeneity of Aβ accumulation and early detection of accumulating group may be helpful in early diagnosis and treatment of AD.
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