Hippocampal Metabolic Subregions and Networks: Behavioral, Molecular and Pathological Aging Profiles

Author(s):  
Somayeh Maleki Balajoo ◽  
Simon B. Eickhoff ◽  
Shahrzad Kharabian Masouleh ◽  
Anna Plachti ◽  
Laura Waite ◽  
...  

Abstract Purpose: Hippocampal dysfunction happens across many neuropsychiatric disorders and is the hallmark of Alzheimer’s disease with evidenced metabolic alterations. However, while metabolic changes are a key aspect of Alzheimer’s disease, hippocampal metabolic networks, as defined by metabolic covariance, haven’t been identified in healthy populations. As the hippocampus portrays cytoarchitectural, connectional, and functional heterogeneity, heterogeneous patterns of metabolic covariance could be expected. Methods: We first characterized this heterogeneity with a data-driven approach by identifying the spatial pattern of hippocampus differentiation based on metabolic covariance with the rest of the brain in FDG-PET data of large healthy elderly cohort (n=362). Then, we characterized the metabolic networks of the robustly defined subregions. In the following, we characterized the disentangled hippocampal metabolic networks with regards to behavioral and neurotransmitter systems using quantitative decoding. Finally, we examined how the local metabolism in the hippocampal subregions is influenced by Alzheimer’s disease pathology in a cohort of ADNI participants (n = 580). Results: Based on hippocampal-brain metabolic covariance in a healthy elderly cohort, we found a differentiation into primarily anterior vs. posterior and secondarily Cornu Ammonis (CA) vs. subiculum subregions. Characterizing the associated metabolic networks revealed that the anterior-subiculum network including temporal-pole and orbitofrontal regions relates to self, motivation and mentalizing behavior and is influenced by dopaminergic systems. In contrast, the posterior-subiculum shows a wide cortical network engaged in action- and world-oriented cognition targeted by serotoninergic systems. The anterior- and posterior-CA, connected respectively to amygdala and broader subcortical networks, are associated to several transporters release. Local metabolism comparison between Alzheimer’s disease-related diagnosis groups revealed early CA’s alterations while posterior subicular alterations appear at advanced stages in line with broader cortical atrophy and behavioral dysfunctions.Conclusion: Future studies should delineate patients’ individual profiles according to hippocampal subregions and networks.

2021 ◽  
pp. 1-10
Author(s):  
Hidemasa Takao ◽  
Shiori Amemiya ◽  
Osamu Abe ◽  

Background: Scan acceleration techniques, such as parallel imaging, can reduce scan times, but reliability is essential to implement these techniques in neuroimaging. Objective: To evaluate the reproducibility of the longitudinal changes in brain morphology determined by longitudinal voxel-based morphometry (VBM) between non-accelerated and accelerated magnetic resonance images (MRI) in normal aging, mild cognitive impairment (MCI), and Alzheimer’s disease (AD). Methods: Using data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) 2 database, comprising subjects who underwent non-accelerated and accelerated structural T1-weighted MRI at screening and at a 2-year follow-up on 3.0 T Philips scanners, we examined the reproducibility of longitudinal gray matter volume changes determined by longitudinal VBM processing between non-accelerated and accelerated imaging in 50 healthy elderly subjects, 54 MCI patients, and eight AD patients. Results: The intraclass correlation coefficient (ICC) maps differed among the three groups. The mean ICC was 0.72 overall (healthy elderly, 0.63; MCI, 0.75; AD, 0.63), and the ICC was good to excellent (0.6–1.0) for 81.4%of voxels (healthy elderly, 64.8%; MCI, 85.0%; AD, 65.0%). The differences in image quality (head motion) were not significant (Kruskal–Wallis test, p = 0.18) and the within-subject standard deviations of longitudinal gray matter volume changes were similar among the groups. Conclusion: The results indicate that the reproducibility of longitudinal gray matter volume changes determined by VBM between non-accelerated and accelerated MRI is good to excellent for many regions but may vary between diseases and regions.


2020 ◽  
Vol 16 (S4) ◽  
Author(s):  
Victor LL Villemagne ◽  
Ryuichi Harada ◽  
Vincent Dore ◽  
Shozo Furumoto ◽  
Rachel S Mulligan ◽  
...  

2016 ◽  
Vol 113 (42) ◽  
pp. E6535-E6544 ◽  
Author(s):  
Xiuming Zhang ◽  
Elizabeth C. Mormino ◽  
Nanbo Sun ◽  
Reisa A. Sperling ◽  
Mert R. Sabuncu ◽  
...  

We used a data-driven Bayesian model to automatically identify distinct latent factors of overlapping atrophy patterns from voxelwise structural MRIs of late-onset Alzheimer’s disease (AD) dementia patients. Our approach estimated the extent to which multiple distinct atrophy patterns were expressed within each participant rather than assuming that each participant expressed a single atrophy factor. The model revealed a temporal atrophy factor (medial temporal cortex, hippocampus, and amygdala), a subcortical atrophy factor (striatum, thalamus, and cerebellum), and a cortical atrophy factor (frontal, parietal, lateral temporal, and lateral occipital cortices). To explore the influence of each factor in early AD, atrophy factor compositions were inferred in beta-amyloid–positive (Aβ+) mild cognitively impaired (MCI) and cognitively normal (CN) participants. All three factors were associated with memory decline across the entire clinical spectrum, whereas the cortical factor was associated with executive function decline in Aβ+ MCI participants and AD dementia patients. Direct comparison between factors revealed that the temporal factor showed the strongest association with memory, whereas the cortical factor showed the strongest association with executive function. The subcortical factor was associated with the slowest decline for both memory and executive function compared with temporal and cortical factors. These results suggest that distinct patterns of atrophy influence decline across different cognitive domains. Quantification of this heterogeneity may enable the computation of individual-level predictions relevant for disease monitoring and customized therapies. Factor compositions of participants and code used in this article are publicly available for future research.


2011 ◽  
Vol 17 (4) ◽  
pp. 674-681 ◽  
Author(s):  
Sietske A.M. Sikkes ◽  
Dirk L. Knol ◽  
Mark T. van den Berg ◽  
Elly S.M. de Lange-de Klerk ◽  
Philip Scheltens ◽  
...  

AbstractA decline in everyday cognitive functioning is important for diagnosing dementia. Informant questionnaires, such as the informant questionnaire on cognitive decline in the elderly (IQCODE), are used to measure this. Previously, conflicting results on the IQCODEs ability to discriminate between Alzheimer's disease (AD), mild cognitive impairment (MCI), and cognitively healthy elderly were found. We aim to investigate whether specific groups of items are more useful than others in discriminating between these patient groups. Informants of 180 AD, 59 MCI, and 89 patients with subjective memory complaints (SMC) completed the IQCODE. To investigate the grouping of questionnaire items, we used a two-dimensional graded response model (GRM).The association between IQCODE, age, gender, education, and diagnosis was modeled using structural equation modeling. The GRM with two groups of items fitted better than the unidimensional model. However, the high correlation between the dimensions (r=.90) suggested unidimensionality. The structural model showed that the IQCODE was able to differentiate between all patient groups. The IQCODE can be considered as unidimensional and as a useful addition to diagnostic screening in a memory clinic setting, as it was able to distinguish between AD, MCI, and SMC and was not influenced by gender or education. (JINS, 2011, 17, 674–681)


PLoS ONE ◽  
2015 ◽  
Vol 10 (6) ◽  
pp. e0129250 ◽  
Author(s):  
Hyuk Jin Yun ◽  
Kichang Kwak ◽  
Jong-Min Lee ◽  

2021 ◽  
Vol 141 (5) ◽  
pp. 697-708
Author(s):  
Yang Shi ◽  
Alexey G. Murzin ◽  
Benjamin Falcon ◽  
Alexander Epstein ◽  
Jonathan Machin ◽  
...  

AbstractTau and Aβ assemblies of Alzheimer’s disease (AD) can be visualized in living subjects using positron emission tomography (PET). Tau assemblies comprise paired helical and straight filaments (PHFs and SFs). APN-1607 (PM-PBB3) is a recently described PET ligand for AD and other tau proteinopathies. Since it is not known where in the tau folds PET ligands bind, we used electron cryo-microscopy (cryo-EM) to determine the binding sites of APN-1607 in the Alzheimer fold. We identified two major sites in the β-helix of PHFs and SFs and a third major site in the C-shaped cavity of SFs. In addition, we report that tau filaments from posterior cortical atrophy (PCA) and primary age-related tauopathy (PART) are identical to those from AD. In support, fluorescence labelling showed binding of APN-1607 to intraneuronal inclusions in AD, PART and PCA. Knowledge of the binding modes of APN-1607 to tau filaments may lead to the development of new ligands with increased specificity and binding activity. We show that cryo-EM can be used to identify the binding sites of small molecules in amyloid filaments.


2021 ◽  
Vol 26 (5) ◽  
pp. 16-23
Author(s):  
A. A. Tappakhov ◽  
T. Ya. Nikolaeva ◽  
T. E. Popova ◽  
N. A. Shnayder

Alzheimer’s disease (AD) is the most common cause of dementia in the population. Late onset AD has a classic clinical picture with short-term memory deficit, apraxia and agnosia. Patients with early-onset AD may have an atypical clinical picture which complicates diagnosis. Atypical AD variants include the logopenic variant of primary progressive aphasia, posterior cortical atrophy, behavioral, biparietal, and cortico-basal variants. These variants have pathomorphological signs similar to classical AD, but at an early stage they are characterized by focal atrophy which explains their clinical polymorphism. This article provides a review of the current literature on atypical types of AD and presents a clinical case of a 62-year-old patient in whom the disease debuted with prosopagnosia due to focal atrophy of the temporo-occipital regions of the non-dominant hemisphere.


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