APOE ε4 status in healthy older African Americans is associated with deficits in pattern separation and hippocampal hyperactivation

Sinha, Neha; Berg, Chelsie N.; Tustison, Nicholas J.; Shaw, Ashlee; Hill, Diane; Yassa, Michael A.; Gluck, Mark A.

doi:10.1016/j.neurobiolaging.2018.05.023

Cited by 39 publications

(67 citation statements)

References 57 publications

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“… [ 66 ] Less impaired MCI patients showed this increase, while more impaired MCI patients showed a decrease in activity similar to mild AD cases [ 67 ] More impaired MCI patients showed a decrease in activity similar to mild AD cases [ 68 ] The extent of hippocampal hyperactivation at baseline predicted cognitive decline as measured by the CDR-SB scores over four years after scanning. [ 69 ] High-resolution fMRI studies have shown that this hippocampal hyperactivity is specific to the DG/CA3 subregions of the hippocampus [ 70 , 71 ] Reduced signaling in the LEC coupled with increased signaling in DG/CA3 in the absence of structural thinning of the regions. [ 73 ] Hippocampal activation is associated with longitudinal amyloid accumulation and cognitive decline [ 74 ] Resting-State fMRI Widespread changes in DMN connectivity in MCI and AD [ 58 – 61 ] Hyperconnectivity in the anterior DMN and hypoconnectivity in the posterior DMN in AD [ 63 , 186 ] Aß+ and tau-PET signal specific profiles [ 62 , 187 ] Age-related decrease in connectivity between the entorhinal cortex and the dentate and CA3 regions of the hippocampus, the extent of which was correlated with memory deficits.…”

Section: Discussionmentioning

confidence: 99%

“…High-resolution fMRI studies have shown that this hippocampal hyperactivity is specific to the dentate and CA3 subregions of the hippocampus [ 70 ]. Recent work has also shown that this effect is noted in cognitively intact APOE ε4 carriers [ 71 ]. Studies in aged rodents with memory deficits suggest that CA3 hyperactivity may be due, at least in part, to the loss of GABAergic drive in hilar inhibitory interneurons, particularly somatostatin-positive (SOM+) interneurons [ 72 ].…”

Section: Imaging Neural Injury and Neurodegenerationmentioning

confidence: 99%

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Neuroimaging Biomarkers for Alzheimer’s Disease

Márquez¹,

Yassa²

2019

Mol Neurodegeneration

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Currently, over five million Americans suffer with Alzheimer’s disease (AD). In the absence of a cure, this number could increase to 13.8 million by 2050. A critical goal of biomedical research is to establish indicators of AD during the preclinical stage (i.e. biomarkers) allowing for early diagnosis and intervention. Numerous advances have been made in developing biomarkers for AD using neuroimaging approaches. These approaches offer tremendous versatility in terms of targeting distinct age-related and pathophysiological mechanisms such as structural decline (e.g. volumetry, cortical thinning), functional decline (e.g. fMRI activity, network correlations), connectivity decline (e.g. diffusion anisotropy), and pathological aggregates (e.g. amyloid and tau PET). In this review, we survey the state of the literature on neuroimaging approaches to developing novel biomarkers for the amnestic form of AD, with an emphasis on combining approaches into multimodal biomarkers. We also discuss emerging methods including imaging epigenetics, neuroinflammation, and synaptic integrity using PET tracers. Finally, we review the complementary information that neuroimaging biomarkers provide, which highlights the potential utility of composite biomarkers as suitable outcome measures for proof-of-concept clinical trials with experimental therapeutics.

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Section: Discussionmentioning

confidence: 99%

Section: Imaging Neural Injury and Neurodegenerationmentioning

confidence: 99%

Neuroimaging Biomarkers for Alzheimer’s Disease

Márquez¹,

Yassa²

2019

Mol Neurodegeneration

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207

118

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“…Cognitively-intact children at genetic risk for fAD showed an early hypersynchronisation of the DMN, which coincided with significant higher plasma levels of Aβ 1-42 [46]. Furthermore, healthy young adult APOE-ε4 carriers (known as greatest genetic risk factor for sAD) displayed increased activation in the DMN [47, 48] and in the hippocampus [49]. This hyperactivation seems to be persistent in the hippocampus of older adult APOE-ε4 carriers [50].…”

Section: Discussionmentioning

confidence: 99%

Increased soluble amyloid-beta causes early aberrant brain network hypersynchronisation in a mature-onset mouse model of amyloidosis

Ben-Nejma

Keliris

Daans

et al. 2019

Preprint

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19Background: Alzheimer's disease (AD) is the most common form of dementia in the elderly 20 population. Currently, no effective cure is available for AD. According to the amyloid 21 hypothesis, the accumulation and deposition of the amyloid-beta (Aβ) peptides plays a key 22 role in AD pathology. Soluble Aβ (sAβ) oligomers were shown to be synaptotoxic and involved 23 in pathological hypersynchronisation of brain resting-state networks in different transgenic 24 developmental-onset mouse models of amyloidosis. However, the impact of protein 25 overexpression during brain postnatal development may cause additional phenotypes 26 unrelated to AD. To address this concern, we investigated sAβ effects on functional resting-27 state networks in transgenic mature-onset amyloidosis Tet-Off APP (TG) mice. 28Methods: TG mice and control littermates were raised on doxycycline (DOX) diet from 3d up 29 to 3m of age to suppress transgenic Aβ production. Thereafter, longitudinal resting-state 30 functional MRI was performed on a 9.4T MR-system starting from week 0 (3m old mice) up to 31 28w post DOX treatment. Ex vivo immunohistochemistry and ELISA analysis (additional mice 32 cohort) was performed to address the development of amyloid pathology. 33 Results: Functional Connectivity (FC) analysis demonstrated early abnormal 34 hypersynchronisation in the TG mice compared to the controls at 8w post DOX treatment. This 35 effect was observed particularly across regions of the default mode-like network, known to be 36 affected in AD. Ex vivo analyses performed at this time point confirmed a 20-fold increase in 37total sAβ levels and the absence of Aβ plaques in the TG mice compared to the controls. On 38 the contrary at week 28, TG mice showed an overall hypoconnectivity, coinciding with a 39 widespread deposition of Aβ plaques in the brain. 40 Conclusions: By preventing developmental influence of APP and/or sAβ during brain 41 postnatal development, we demonstrated FC abnormalities driven by sAβ synaptotoxicity on 42 resting state neuronal networks in mature-induced TG mice. Thus, the Tet-Off APP mouse 43 model could be a powerful tool while used as a mature-onset model to shed light into 44 amyloidosis mechanisms in AD. Therefore, this inducible APP expression model used in 45 combination with early non-invasive in vivo rsfMRI readout for sAβ synaptotoxicity sets the 46 stage for future Aβ targeting preventative treatment studies.47 KEYWORDS 48 3 Alzheimer's disease, resting state fMRI, neuronal networks, Aβ, hypersynchronisation 49 BACKGROUND 50 Alzheimer's disease (AD) is a devastating progressive neurodegenerative disorder, 51 mainly characterized by the accumulation of amyloid-beta (Aβ) plaques and neurofibrillary 52 tangles (NFTs), which leads to dementia [1]. Most of AD patients develop the late-onset 53 sporadic form of AD (sAD), while the early-onset familial form of AD (fAD) is rare (<1% of AD 54 cases) [2-4]. Ageing has been identified as the greatest known risk factor of sAD, with the 55 prevalence doubling every 5 year...

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“…Once the atlas set was normalized to the unlabeled subject, the regional labeling was determined using weighted averaging where the weighting takes into account the unique intensity information contributed by each atlas member. This approach which combines label information and intensity information has been used in a number of recent publications to segment hippocampal subfields (Brown, Kulikova, et al, 2019;Sinha et al, 2018).…”

Section: Anatomical Regions Of Interestmentioning

confidence: 99%

Negative Overgeneralization is Associated with Anxiety and Mechanisms of Pattern Completion in Peripubertal Youth

McMakin

Kimbler

Tustison

et al. 2020

Preprint

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Negative overgeneralization is a dimension of anxiety whereby responses to one aversive situation (e.g., severe weather) spread to others that share contextual features (e.g., breezy day). We aim to sharpen mechanistic understanding of negative overgeneralization. In peripuberty -a time when changes in neurodevelopment potentiate generalization of salient experiences -these mechanisms may shape behavior and contribute to emotional health. In an emotional mnemonic similarity task conducted with youth, negative, relative to neutral, scene images were generalized more frequently. Negative overgeneralization was related to both greater and more similar patterns of activation in the CA1 hippocampal subfield and medial prefrontal cortex (mPFC) for negative relative to neutral stimuli. At encoding, the amygdala increased functional coupling with CA1 and mPFC during negative items that were later generalized. Negative overgeneralization is rooted in mechanisms of modulation at encoding and pattern completion at retrieval. Targeting these mechanisms during peripuberty could positively shape emotional health. previously stored representations, is associated with behavioral generalization

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APOE ε4 status in healthy older African Americans is associated with deficits in pattern separation and hippocampal hyperactivation

Cited by 39 publications

References 57 publications

Neuroimaging Biomarkers for Alzheimer’s Disease

Neuroimaging Biomarkers for Alzheimer’s Disease

Increased soluble amyloid-beta causes early aberrant brain network hypersynchronisation in a mature-onset mouse model of amyloidosis

Negative Overgeneralization is Associated with Anxiety and Mechanisms of Pattern Completion in Peripubertal Youth

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