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Emerging evidence suggests that some personality traits may link to the vulnerability to or protection for Alzheimer’s disease (AD). A causal mechanism underlying this relationship, however, remains largely unknown. Using 18F-Florbetaben positron emission tomography (PET) binding to beta-amyloid (Aβ) plaques, a pathological feature of AD, and functional magnetic resonance imaging (fMRI), we investigated pathological and functional correlates of extraversion and neuroticism in a group of healthy young and older subjects. We quantified a level of brain Aβ deposition in older individuals. Brain activity was measured in young adults using a task-switching fMRI paradigm. When we correlated personality scores of extraversion and neuroticism with these pathological and functional measures, higher extraversion, but not neuroticism, was significantly associated with lower global Aβ measures among older adults, accounting for age and sex. This association was present across widespread brain regions. Among young subjects, higher extraversion was associated with lower activity during task switching in anterior cingulate cortex, left anterior insular cortex, left putamen, and middle frontal gyrus bilaterally, while higher neuroticism was associated with increased activity throughout the brain. The present results suggest that possibly via efficient neuronal activity, extraversion, one of lifelong personality traits, may confer the protective mechanism against the development of Aβ pathology during aging.

•MK6240 meningeal off-target signal (OTS) is adjacent to target and reference regions.•Across individuals OTS is continuously distributed and related to sex (F>M).•Erosion of the reference region results in greater OTS influence in target regions.•Approaches to optimize MK6240 processing perform similarly to standard processing. Accurate measurement of Alzheimer's disease (AD) pathology in older adults without significant clinical impairment is critical to assessing intervention strategies aimed at slowing AD-related cognitive decline. The U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (POINTER) is a 2-year randomized controlled trial to evaluate the effect of multicomponent risk reduction strategies in older adults (60-79 years) who are cognitively unimpaired but at increased risk for cognitive decline/dementia due to factors such as cardiovascular disease and family history. The POINTER Imaging ancillary study is collecting tau-PET ([18F]MK6240), beta-amyloid (Aβ)-PET ([18F]florbetaben [FBB]) and MRI data to evaluate neuroimaging biomarkers of AD and cerebrovascular pathophysiology in this at-risk sample. Here 481 participants (70.0±5.0; 66% F) with baseline MK6240, FBB and structural MRI scans were included. PET scans were coregistered to the structural MRI which was used to create FreeSurfer-defined reference regions and target regions of interest (ROIs). We also created off-target signal (OTS) ROIs to examine the magnitude and distribution of MK6240 OTS across the brain as well as relationships between OTS and age, sex, and race. OTS was unimodally distributed, highly correlated across OTS ROIs and related to younger age and sex but not race. Aiming to identify an optimal processing approach for MK6240 that would reduce the influence of OTS, we compared our previously validated MRI-guided standard PET processing and 6 alternative approaches. The alternate approaches included combinations of reference region erosion and meningeal OTS masking before spatial smoothing as well as partial volume correction. To compare processing approaches we examined relationships between target ROIs (entorhinal cortex (ERC), hippocampus or a temporal meta-ROI (MetaROI)) SUVR and age, sex, race, Aβ and a general cognitive status measure, the Modified Telephone Interview for Cognitive Status (TICSm). Overall, the processing approaches performed similarly, and none showed a meaningful improvement over standard processing. Across processing approaches we observed previously reported relationships with MK6240 target ROIs including positive associations with age, an Aβ+> Aβ- effect and negative associations with cognition. In sum, we demonstrated that different methods for minimizing effects of OTS, which is highly correlated across the brain within subject, produced no substantive change in our performance metrics. This is likely because OTS contaminates both reference and target regions and this contamination largely cancels out in SUVR data. Caution should be used when efforts to reduce OTS focus on target or reference regions in isolation as this may exacerbate OTS contamination in SUVR data.

Background Predicting amyloid and tau status in nondemented older adults with AD pathologies using more affordable and accessible measures can facilitate clinical trials by reducing the screen failure rate. The goal of the present study was to develop tree‐based ensemble models to predict PET‐based amyloid and tau burden using non‐invasive measures. Method Two datasets, amyloid (Aβ; n = 1062) and tau (n = 410), from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database were used to predict the biomarker load in the subjects with normal cognition and mild cognitive impairment. Amyloid PET with the [18F]Florbetapir tracer was used as the gold‐standard measure for binary amyloid status classification), while tau PET with the [18F]Flortaucipir tracer was used for the three‐stage (low, intermediate, and high) determination. We trained random forest (RF), extreme gradient boosting machine (XGBoost), and light gradient boosting machine (lightGBM) models using different combinations of demographic, neuropsychological, APOE genotype, and volumetric MRI data, and measured the model performance using area under the receiver operating curve (AUROC). Result The performance of baseline model with demographics showed modest performance for Aβ (RF = 0.665, XGB = 0.650, LGBM = 0.659). Subsequent additions of features improved the predictive performance, with the model using demographic data, cognitive data, and volumetric MRI measures demonstrating the highest performance (RF = 0.762, XGB = 0.763, LGBM = 0.761). Meanwhile, the baseline model achieved modest performance for the three‐stage tau classification (RF = 0.643, XGB = 0.654, LGBM = 0.643), and the further addition of features improved the performance, with the feature combination of demographic data, cognitive, volumetric MRI measures, and continuous Aβ PET SUVRs achieving very good performance (RF = 0.799, XGB = 0.801, LGBM = 0.800). SHAP summary plots showed that age, entorhinal cortex volume, and neuropsychological and functional measures were important for Aβ classification, while Aβ load, high global cognition scores, hippocampal and middle temporal gyrus volume were shown to predict tau status. Conclusion Without using amyloid and tau PET, tree‐based ensemble machine learning models predict amyloid and tau status among nondemented older adults with modest to very good performance and could be incorporated for future clinical trials.

Background Plasma p‐tau181 is an increasingly established diagnostic marker for Alzheimer’s disease (AD); however, its precise relationship with brain tau pathology and the neural mechanisms underlying its association with cognitive impairment remain elusive. Our objective was to assess the association between plasma p‐tau181 and hippocampal (HC) subfield integrity and to investigate whether the subfields mediate the relationship between plasma p‐tau181 and cognition. Method A total of 213 participants (57 cognitively normal, 109 mild cognitive impairment, and 47 AD) with plasma p‐tau181 measurements and high‐resolution T2‐weighted scans were selected from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). HC subfield volume was measured at baseline using the Automatic Segmentation of Hippocampal Subfields (ASHS) software. Follow‐up HC subfield volume collected around one year was measured for eighty‐nine participants. A linear regression adjusted for age and sex evaluated the relationship between plasma p‐tau181 and HC subfields at baseline, as well as HC volume rate of change over one year. A mediation model assessed whether HC subfields mediate the association between plasma p‐tau181 and memory and executive functioning. Result Our findings indicate that increasing levels of plasma p‐tau181(pg/mL) are associated with decreased volume in the left CA1 (β = ‐0.119, p = 0.019, Fig. 1a), right CA1 (β = ‐0.154, p = 0.005, Fig. 1b), left dentate gyrus (β = ‐0.120, p = 0.016, Fig. 1g), right dentate gyrus (β = ‐0.146, p = 0.005, Fig. 1h), and right entorhinal cortex (β = ‐0.091, p = 0.048, Fig. 1l). Moreover, these subfields partially mediate the relationship between plasma p‐tau181 and memory and executive functioning composite scores. Baseline plasma p‐tau181 did not predict longitudinal atrophy of the HC subfields across diagnostic groups. Conclusion Our study reveals consistent associations between plasma p‐tau181 levels and vulnerable HC subfields, including CA1, entorhinal cortex, and dentate gyrus, collectively implicated in normal aging and Alzheimer’s disease pathologies. Volumetric changes in CA1, dentate gyrus, and right entorhinal cortex were shown to underlie the association of plasma p‐tau181 with both memory and executive functioning. Together, our findings indicate that selective changes in HC subfield volume serve as a neural basis underlying the relationship between plasma p‐tau181 levels and cognitive impairment.

While previous results from univariate analysis showed that the activity level of the parahippocampal gyrus (PHG) but not the fusiform gyrus (FG) reflects selective maintenance of the cued picture category, present results from multi-voxel pattern analysis (MVPA) showed that the spatial response patterns of both regions can be used to differentiate the selected picture category in working memory. The ventral temporal and occipital areas including the PHG and FG have been shown to be specialized in perceiving and processing different kinds of visual information, though their role in the representation of visual working memory remains unclear. To test whether the PHG and FG show spatial response patterns that reflect selective maintenance of task-relevant visual working memory in comparison with other posterior association regions, we reanalyzed data from a previous fMRI study of visual working memory with a cue inserted during the delay period of a delayed recognition task. Classification of FG and PHG activation patterns for the selected category (face or scene) during the cue phase was well above chance using classifiers trained with fMRI data from the cue or probe phase. Classification of activity in other temporal and occipital regions for the cued picture category during the cue phase was relatively less consistent even though classification of their activity during the probe recognition was comparable with the FG and PHG. In sum, these findings suggest that the FG and PHG carry information relevant to the cued visual category, and their spatial activation patterns during selective maintenance seem to match those during visual recognition. ► We studied spatial response patterns of visual cortical areas during working memory. ► Multivoxel pattern analysis reveals selective maintenance of face or scene pictures. ► Activity of fusiform and parahippocampal areas reflects the task relevant category. ► Activation patterns during selective maintenance and object recognition are similar.

Although genetic factors associated with the aggregation of misfolded proteins clearly play a role in Alzheimer's disease (AD), an individual's susceptibility to stress, often expressed as neuropsychiatric symptoms, has been shown to confer an increased risk for AD. The goal of this study was to probe a neuro-mechanistic pathway that underlies the relationship between neuropsychiatric symptoms and AD neuropathology using multimodal neuroimaging and peripheral inflammatory markers. We evaluated whether the relationship between neuropsychiatric symptoms and AD neuropathology are differentially mediated by white matter microstructural integrity, neuronal activity, and inflammatory markers along the spectrum of AD from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset that consists of 398 cognitively normal older adults (CNs), 817 participants with mild cognitive impairment and 307 AD patients. White matter integrity and fMRI data were processed to quantify diffusion measures and neuronal activity levels. Plasma-based inflammatory markers were summarized using principal component analyses. Neuropsychiatric Inventory Questionnaire (NPI-Q) scores represented individuals' stress responses and neuropsychiatric symptoms. NPI-Q scores were significantly associated with brain Aβ indices across the entire cohort. Relationships between the neural activity, stress responses, and Aβ deposition, however, differ by diagnostic groups. As stress indicators increased, CN subjects exhibited increased activity across brain regions, while AD participants exhibited decreased activity. Moreover, as brain Aβ load increased, CN participants experienced hyperactivity, while AD participants experienced hypoactivity. White matter integrity and peripheral inflammatory markers showed diagnostic group differences, but did not significantly mediate the relationship between neuropsychiatric symptoms and AD pathologies. These results indicate a potential link between heightened stress responses and increased susceptibility to the development of AD pathologies through neuronal hyperactivity, especially in the early stages of AD.

Background Although genetic factors associated with the aggregation of misfolded proteins clearly play a role in Alzheimer’s disease (AD), an individual’s susceptibility to stress, often expressed as neuropsychiatric symptoms, has been shown to confer an increased risk for AD. The goal of this study was to probe a neuro‐mechanistic pathway that underlies the relationship between neuropsychiatric symptoms and AD neuropathology using multimodal neuroimaging and peripheral inflammatory markers. Method We evaluated whether the relationship between neuropsychiatric symptoms and AD neuropathology are differentially mediated by white matter microstructural integrity, neuronal activity, and inflammatory markers along the spectrum of AD from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset that consists of 398 cognitively normal older adults (CNs), 817 participants with mild cognitive impairment and 307 AD patients. White matter integrity and fMRI data were processed to quantify diffusion measures and neuronal activity levels. Plasma‐based inflammatory markers were summarized using principal component analyses. Neuropsychiatric Inventory Questionnaire (NPI‐Q) scores represented individuals’ stress responses and neuropsychiatric symptoms. Result NPI‐Q scores were significantly associated with brain Aβ indices across the entire cohort. Relationships between the neural activity, stress responses, and Aβ deposition, however, differ by diagnostic groups. As stress indicators increased, CN subjects exhibited increased activity across brain regions, while AD participants exhibited decreased activity. Moreover, as brain Aβ load increased, CN participants experienced hyperactivity, while AD participants experienced hypoactivity. White matter integrity and peripheral inflammatory markers showed diagnostic group differences, but did not significantly mediate the relationship between neuropsychiatric symptoms and AD pathologies. Conclusion These results indicate a potential link between heightened stress responses and increased susceptibility to the development of AD pathologies through neuronal hyperactivity, especially in the early stages of AD.

Background The locus coeruleus (LC), a major norepinephrine‐producing region, plays a central role in arousal and cognition functions. Understanding how the LC exerts its impact on cognition is of paramount importance especially given the region has been known to accumulate tau pathology even in young adulthood, preceding broad tau and amyloid deposition in the brain. Here, we examined the relationships between LC integrity and spontaneous regional brain activity across the adult lifespan to test the hypothesis of the role of LC‐related regional brain activity in cognition. Method Forty‐nine cognitively normal adults (22 older (mean age: 70.7.44; 11 females) and 27 young (mean age: 25.5.81; 21 females)) from Brown Multimodal Imaging of Cognition, Aging, and Alzheimer’s Disease (MICAAD) study completed extensive neuropsychological tests and resting‐state T2* blood‐oxygenation‐level‐dependent (BOLD) MRI (rsfMRI) and LC MT‐MRI T1 imaging. LC intensity was calculated by normalizing the LC signal relative to the pontine tegmentum and five highest intensity voxels from each hemisphere were averaged to mean LC intensity values. Resting‐state fMRI data were preprocessed and denoised using nuisance variables, including the Friston 24 parameters as well as white matter and cerebrospinal fluid signals, to compute regional brain activity level implemented in the RESTplus v1.31 toolbox. Whole‐brain voxel‐wise analyses were conducted to examine LC intensity‐ and age‐related differences in regional brain activity across age groups, controlling for sex. Result Across all participants, higher LC intensity was related to lower regional brain activity in widespread brain regions including the dorsomedial prefrontal cortex and the cerebellum. Age was mostly associated with lower regional brain activity, while activity in the left Insular cortex and right amygdala increased with advanced age. Within each age group, higher LC intensity was related to lower regional activity in the putamen and cerebellum among young, but not older adults, while older age was associated with greater dorsolateral PFC activity among older, but not young adults. Conclusion LC intensity relates to regional brain activity differently across age groups. This differential relationships between LC intensity and regional brain activity by age groups may underlie a potentially different role of LC intensity in cognition across the lifespan.

Previous studies have emphasized that the dorsolateral prefrontal cortex is important for manipulating information in working memory, although activations in other frontal and parietal areas are commonly observed under the same conditions. We conducted an fMRI experiment to examine brain responses as a parametric function of memory updating, which is considered as an elemental process in working memory. In a variant spatial delayed-response task, human subjects performed updating operations over a 9-second delay period, during which they mentally transform the location of a memorized target in a 4 by 4 grid according to 3 to 12 instruction cues. Activity increased monotonically with increasing updating load in numerous cortical and subcortical regions including the rostrodorsal premotor (rdPM), lateral precentral sulcus, lateral prefrontal, posterior associative, striatal and cerebellar areas. The rdPM and superior parietal were particularly sensitive to the updating manipulation. There were several main findings. First, updating spatial working memory involved mostly the same cortical and subcortical regions that were activated during maintenance of spatial information. Second, the updating load response functions of regions in the spatial working memory circuit showed a strong linear component. However, none shows significant increases in activity from 9 to 12 updating operations. Third, activity in the right rdPM and anterior inferior frontal gyrus correlated positively with working memory performance in the high updating load condition. Our findings suggest that updating and maintenance of spatial information may share similar processes and that the rostrodorsal premotor cortex and anterior inferior frontal gyrus may be important for the success of tracking spatial information in working memory.

Background The locus coeruleus (LC), a key source of norepinephrine production, plays an essential role in arousal and cognitive functions. Abnormal tau begins to appear in the brain stem, the LC in particular, even in young adulthood long before brain tau and amyloid pathology. To what extent LC integrity affects cognitive performance accounting for age is unknown. In this study, we examined age‐related differences in LC integrity and its relationship with cognition in the lifespan sample. Methods A total of 124 cognitively normal adults (72 older (mean age: 68.85.9; 52 females) and 52 young (mean age: 24.25.4; 35 females)) from Brown Multimodal Imaging of Cognition, Aging, and Alzheimer’s Disease (MICAAD) study underwent extensive neuropsychological assessment and a subset of 40 adults completed LC MT‐MRI imaging. Principal component (PC) analyses were applied to a set of neuropsychological tests that included standard measures of verbal and visual memory, executive function, language, semantic memory, and working memory. LC intensity was calculated by normalizing the LC signal relative to the pontine tegmentum and five highest intensity voxels from each hemisphere were averaged to compute the left LC, right LC, and mean LC (left LC and right LC combined) intensity values. Multiple regressions were performed to assess the relationships between cognitive score and LC intensity, age group, and their interaction, with sex as a covariate. Results Across the whole sample, age group‐related differences were found in executive function, language, and visual memory. LC intensity was significantly higher in older compared to young adults and in the left compared to the right hemisphere across both age groups. No direct association between mean LC intensity and cognitive domains was found in either age group, while significant relationships were found in the left LC intensity and language and the right LC intensity and working memory only among young adults. Conclusions While there is an age‐related difference in LC intensity, the relationships between LC intensity and cognition are domain‐specific and age‐group dependent. Further research is warranted to evaluate the contribution of laterality and resilience factors in the LC integrity and cognition relationship in a larger sample.