Retained executive abilities in mild cognitive impairment are associated with increased white matter network connectivity

Farrar, Danielle; Mian, Asim; Budson, Andrew E.; Moss, Mark B.; Koo, Bang Bon; Killiany, Ronald

doi:10.1007/s00330-017-4951-4

Cited by 18 publications

(15 citation statements)

References 27 publications

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“…In this study, structural and functional network changes during the progression of AD have been evaluated using MRI-based connectomics applied to a rat model of AD. Differences in the structural brain network between population at risk of AD or in its preclinical phases in human cohorts have been already reported (Berlot et al, 2016;Chen et al, 2015;Farrar et al, 2017;Fischer et al, 2015;Pereira et al, 2017;Zhao et al, 2015). In our study, the evaluation of the structural brain network in TgF344-AD from ages corresponding to earlier stages than the ones covered in human studies pointed to similar connectivity changes already in young animals (six months of age).…”

Section: Discussionsupporting

confidence: 82%

“…The observed significant relation between structural network metrics and cognitive performance could be related with the ability of functional connectivity to cope with the structural disconnection preserving cognition, until a breakpoint when it is not able to deal with extensive structural network damage. This relationship between structural connectivity and cognition has been also described in MCI subjects (Berlot et al, 2016;Farrar et al, 2017) and in cognitive normal individuals harboring amyloid pathology and neurodegeneration (Pereira et al, 2017), while no correlation was observed in control subjects. Coherently, structural connectivity did not correlate with DNMS in our control cohort, where correlation between DNMS and functional connectivity was observed.…”

Section: Discussionmentioning

confidence: 66%

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Brain connectivity during Alzheimer’s disease progression and its cognitive impact in a transgenic rat model

Muñoz‐Moreno

Tudela

López-Gil

et al. 2019

Preprint

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The research of Alzheimer's disease (AD) in their early stages and its progression till symptomatic onset 12 is essential to understand the pathology and investigate new treatments. Animal models provide a helpful 13 approach to this research, since they allow for controlled follow-up during the disease evolution. In this 14 work, transgenic TgF344-AD rats were longitudinally evaluated starting at 6 months of age. Every 3 15 months, cognitive abilities were assessed by a memory-related task and magnetic resonance imaging 16 (MRI) was acquired. Structural and functional brain networks were estimated and characterized by graph 17 metrics to identify differences between the groups in connectivity, its evolution with age, and its influence 18 on cognition. Structural networks of transgenic animals were altered since the earliest stage. Likewise, 19 aging significantly affected network metrics in TgF344-AD, but not in the control group. In addition, 20 while the structural brain network influenced cognitive outcome in transgenic animals, functional 21 network impacted how control subjects performed. TgF344-AD brain network alterations were present 22 from very early stages, difficult to identify in clinical research. Likewise, the characterization of aging in 23 these animals, involving structural network reorganization and its effects on cognition, opens a window to 24 evaluate new treatments for the disease. 25 1 AUTHOR SUMMARYWe have applied magnetic resonance image based connectomics to characterize TgF344-AD rats, a 26 transgenic model of Alzheimer's disease (AD). This represents a highly translational approach, what is 27 essential to investigate potential treatments. TgF344-AD animals were evaluated from early to advanced 28 ages to describe alterations in brain connectivity and how brain networks are affected by age. Results 29showed that aging had a bigger impact in the structural connectivity of the TgF344-AD than in control 30 animals, and that changes in the structural network, already observed at early ages, significantly 31 influenced cognitive outcome of transgenic animals. Alterations in connectivity were similar to the 32 described in AD human studies, and complement them providing insights into earlier stages and a plot of 33

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Section: Discussionsupporting

confidence: 82%

Section: Discussionmentioning

confidence: 66%

Brain connectivity during Alzheimer’s disease progression and its cognitive impact in a transgenic rat model

Muñoz‐Moreno

Tudela

López-Gil

et al. 2019

Preprint

View full text Add to dashboard Cite

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“…Additionally, we noted that smaller mid-posterior CC volume was related to worse executive function. This relationship suggests that CC degeneration might contribute to or even accelerate cognitive deficit ( Agosta et al, 2015 ; Farrar et al, 2017 ; Luo et al, 2017b ). Combined with the results of bilateral hypometabolism and inter-hemispheric disconnection, we hypothesized that mid-posterior CC atrophy may reflect the Wallerian degeneration secondary to neuronal loss caused by amyloid deposition ( Bozzali et al, 2002 ).…”

Section: Discussionmentioning

confidence: 99%

Decreased Bilateral FDG-PET Uptake and Inter-Hemispheric Connectivity in Multi-Domain Amnestic Mild Cognitive Impairment Patients: A Preliminary Study

Luo

Zeng

et al. 2018

Front. Aging Neurosci.

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Background: Amnestic mild cognitive impairment (aMCI) is a heterogeneous condition. Based on clinical symptoms, aMCI could be categorized into single-domain aMCI (SD-aMCI, only memory deficit) and multi-domain aMCI (MD-aMCI, one or more cognitive domain deficit). As core intrinsic functional architecture, inter-hemispheric connectivity maintains many cognitive abilities. However, few studies investigated whether SD-aMCI and MD-aMCI have different inter-hemispheric connectivity pattern.Methods: We evaluated inter-hemispheric connection pattern using fluorine-18 positron emission tomography – fluorodeoxyglucose (18F PET-FDG), resting-state functional MRI and structural T1 in 49 controls, 32 SD-aMCI, and 32 MD-aMCI patients. Specifically, we analyzed the 18F PET-FDG (intensity normalized by cerebellar vermis) in a voxel-wise manner. Then, we estimated inter-hemispheric functional and structural connectivity by calculating the voxel-mirrored homotopic connectivity (VMHC) and corpus callosum (CC) subregions volume. Further, we correlated inter-hemispheric indices with the behavioral score and pathological biomarkers.Results: We found that MD-aMCI exhibited more several inter-hemispheric connectivity damages than SD-aMCI. Specifically, MD-aMCI displayed hypometabolism in the bilateral middle temporal gyrus (MTG), inferior parietal lobe, and left precuneus (PCu) (p < 0.001, corrected). Correspondingly, MD-aMCI showed decreased VMHC in MTG, PCu, calcarine gyrus, and postcentral gyrus, as well as smaller mid-posterior CC than the SD-aMCI and controls (p < 0.05, corrected). Contrary to MD-aMCI, there were no neuroimaging indices with significant differences between SD-aMCI and controls, except reduced hypometabolism in bilateral MTG. Within aMCI patients, hypometabolism and reduced inter-hemispheric connectivity correlated with worse executive ability. Moreover, hypometabolism indices correlated to increased amyloid deposition.Conclusion: In conclusion, patients with MD-aMCI exhibited the more severe deficit in inter-hemispheric communication than SD-aMCI. This long-range connectivity deficit may contribute to cognitive profiles and potentially serve as a biomarker to estimate disease progression of aMCI patients.

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“…Other network measures such as network size [11], density [11], PageRank versatility [12], path length [10] and modularity [10] can further be used to evaluate networks. For an extensive review of network measures, the reader is referred to [13].…”

Section: Systems Bioinformaticsmentioning

confidence: 99%

Systems Bioinformatics: increasing precision of computational diagnostics and therapeutics through network-based approaches

Oulas

Minadakis

Zachariou

et al. 2017

Briefings in Bioinformatics

109

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Systems Bioinformatics is a relatively new approach, which lies in the intersection of systems biology and classical bioinformatics. It focuses on integrating information across different levels using a bottom-up approach as in systems biology with a data-driven top-down approach as in bioinformatics. The advent of omics technologies has provided the stepping-stone for the emergence of Systems Bioinformatics. These technologies provide a spectrum of information ranging from genomics, transcriptomics and proteomics to epigenomics, pharmacogenomics, metagenomics and metabolomics. Systems Bioinformatics is the framework in which systems approaches are applied to such data, setting the level of resolution as well as the boundary of the system of interest and studying the emerging properties of the system as a whole rather than the sum of the properties derived from the system's individual components. A key approach in Systems Bioinformatics is the construction of multiple networks representing each level of the omics spectrum and their integration in a layered network that exchanges information within and between layers. Here, we provide evidence on how Systems Bioinformatics enhances computational therapeutics and diagnostics, hence paving the way to precision medicine. The aim of this review is to familiarize the reader with the emerging field of Systems Bioinformatics and to provide a comprehensive overview of its current state-of-the-art methods and technologies. Moreover, we provide examples of success stories and case studies that utilize such methods and tools to significantly advance research in the fields of systems biology and systems medicine.

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Retained executive abilities in mild cognitive impairment are associated with increased white matter network connectivity

Cited by 18 publications

References 27 publications

Brain connectivity during Alzheimer’s disease progression and its cognitive impact in a transgenic rat model

Brain connectivity during Alzheimer’s disease progression and its cognitive impact in a transgenic rat model

Decreased Bilateral FDG-PET Uptake and Inter-Hemispheric Connectivity in Multi-Domain Amnestic Mild Cognitive Impairment Patients: A Preliminary Study

Systems Bioinformatics: increasing precision of computational diagnostics and therapeutics through network-based approaches

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