scholarly journals Identification of Abnormal Lipid Profiles Promote Cognitive Decline in Alzheimer's Disease Spectrum via Large-Scale Brain Connectivity

2021 ◽  
Author(s):  
Qing Wang ◽  
Feifei Zang ◽  
Cancan He ◽  
Zhijun Zhang ◽  
Chunming Xie
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Large Scale ◽  
Brain Connectivity ◽  
Lipid Profiles ◽  
Disease Spectrum

scholarly journals Identification of abnormal lipid profiles promote cognitive decline in Alzheimer’s disease spectrum via large-scale brain connectivity

2021 ◽  
Author(s):  
Qing Wang ◽  
Feifei Zang ◽  
Cancan He ◽  
Zhijun Zhang ◽  
Chunming Xie
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Function ◽  
Cognitive Decline ◽  
Large Scale ◽  
Clinical Signs ◽  
Lipid Profiles ◽  
Substantial Contribution ◽  
Support Vector ◽  
Polygenic Scores

Abstract Background: Lipid metabolite dysfunction makes a substantial contribution to the clinical signs and pathophysiology of Alzheimer’s disease (AD). It is unclear that the role of dyslipidemia in the promotion of neuropathological processes and brain functional impairment that subsequently facilitates the progression of AD.Methods: Lipid pathway-based polygenic scores and large-scale resting-state networks (RSNs), was constructed. Together with canonical correlation analysis (CCA) and support vector machine (SVM) model, to explore the effects of lipid-related polygenic scores and blood lipoproteins on the molecular biomarkers, cognitive function, as well as large-scale RSNs. Associations between lipid-related genetic scores, serum lipoproteins, cognitive function, CSF biomarkers and RSNs were examined.Results: Dynamic trajectory of large-scale RSNs was exhibited significantly differential connectivity within-network, one-versus-all-others-network, and pairwise between networks across the AD spectrum (ADS). Importantly, the summative effects of lipid-pathway genetic variants and lipoproteins significantly promoted the process of β-amyloid and Tau levels and cognitive decline, and preferentially targeted functional couplings within- and between RSNs in the ADS, supporting the hypothesis that abnormal lipid profiles in the AD pathogenesis via disrupting large-scale RSNs and accelerating molecular pathological processes, consequently exacerbating cognitive decline.Conclusions: Our findings reveal the importance of lipids in the pathogenesis of AD via disruption of RSNs and acceleration of molecular pathological processes, consequently exacerbating cognitive decline. These findings provide the potential lipid-associated neuroimaging biomarkers for ADS.

scholarly journals Disrupted core-periphery structure of multimodal brain networks in Alzheimer’s disease

2019 ◽  
Vol 3 (2) ◽  
pp. 635-652 ◽  
Author(s):  
Jeremy Guillon ◽  
Mario Chavez ◽  
Federico Battiston ◽  
Yohan Attal ◽  
Valentina La Corte ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Memory Impairment ◽  
Large Scale ◽  
Brain Connectivity ◽  
Functional Integration ◽  
The Core ◽  
Multiplex Network ◽  
Different Types

In Alzheimer’s disease (AD), the progressive atrophy leads to aberrant network reconfigurations both at structural and functional levels. In such network reorganization, the core and peripheral nodes appear to be crucial for the prediction of clinical outcome because of their ability to influence large-scale functional integration. However, the role of the different types of brain connectivity in such prediction still remains unclear. Using a multiplex network approach we integrated information from DWI, fMRI, and MEG brain connectivity to extract an enriched description of the core-periphery structure in a group of AD patients and age-matched controls. Globally, the regional coreness—that is, the probability of a region to be in the multiplex core—significantly decreased in AD patients as result of a random disconnection process initiated by the neurodegeneration. Locally, the most impacted areas were in the core of the network—including temporal, parietal, and occipital areas—while we reported compensatory increments for the peripheral regions in the sensorimotor system. Furthermore, these network changes significantly predicted the cognitive and memory impairment of patients. Taken together these results indicate that a more accurate description of neurodegenerative diseases can be obtained from the multimodal integration of neuroimaging-derived network data.

scholarly journals Cortical atrophy mediates the accumulating effects of vascular risk factors on cognitive decline in the Alzheimer’s disease spectrum

Aging ◽  
2020 ◽  
Vol 12 (14) ◽  
pp. 15058-15076
Author(s):  
Qing Wang ◽  
Cancan He ◽  
Yao Zhu ◽  
Qianqian Zhang ◽  
Zhijun Zhang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Vascular Risk Factors ◽  
Cortical Atrophy ◽  
Vascular Risk ◽  
Disease Spectrum

Olfactory Dysfunction Is Already Present with Subjective Cognitive Decline and Deepens with Disease Severity in the Alzheimer’s Disease Spectrum

2020 ◽  
pp. 1-11
Author(s):  
Qiang Wang ◽  
Ben Chen ◽  
Xiaomei Zhong ◽  
Huarong Zhou ◽  
Min Zhang ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Disease Severity ◽  
Olfactory Dysfunction ◽  
Odor Identification ◽  
Subjective Cognitive Decline ◽  
Verbal Recall ◽  
Disease Spectrum ◽  
Significant Difference

Background: Odor identification dysfunction occurs early in Alzheimer’s disease (AD) and is considered a preclinical symptom along with subjective cognitive decline (SCD). Nevertheless, whether subjects with SCD are co-symptomatic with odor identification dysfunction remains unclear. Objective: To compare the degree of odor identification dysfunction and assess the relation between odor identification and cognitive performance in the AD spectrum (including SCD, mild cognitive impairment (MCI), and AD). Methods: Patients (84 SCD, 129 MCI, 52 AD) and 35 controls underwent the Sniffin’ Sticks Screen 16 test and comprehensive neuropsychological examination. Results: Odor identification scores were progressively lower moving from normal older adult to SCD, MCI, and AD. Additionally,the proportion of odor identification dysfunction were increasingly higher in the AD spectrum (p for trend <0.001), but no significant difference was found in the proportion of subjective olfactory dysfunction. No significant correlation was found between odor identification and cognition in the normal older adults and SCD subjects, but odor identification correlated with global cognition in the MCI (r = 0.199, p = 0.033) and in the AD (r = 0.300, p = 0.036) patients. Multiple linear regression showed that odor identification dysfunction was most strongly associated with memory among different cognitive subdomains and was most strongly associated with immediate verbal recall among different memory subdomains. Conclusion: Odor identification dysfunction is already present with SCD and deepens with disease severity in the AD spectrum, and it may contribute to predicting cognitive decline and identifying SCD subjects who are at risk of developing AD.

scholarly journals Large-Scale Deep Multi-Layer Analysis of Alzheimer’s Disease Brain Reveals Strong Proteomic Disease-Related Changes Not Observed at the RNA Level

2021 ◽  
Author(s):  
Erik C.B. Johnson ◽  
E. Kathleen Carter ◽  
Eric B. Dammer ◽  
Duc M. Duong ◽  
Ekaterina S. Gerasimov ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Large Scale ◽  
Brain Regions ◽  
Mapk Signaling ◽  
Proteomic Data ◽  
Tandem Mass Tag ◽  
Within Subjects ◽  
Decline Disease

AbstractThe biological processes that are disrupted in the Alzheimer’s disease (AD) brain remain incompletely understood. We recently performed a proteomic analysis of >2000 brains to better understand these changes, which highlighted alterations in astrocytes and microglia as likely key drivers of disease. Here, we extend this analysis by analyzing >1000 brain tissues using a tandem mass tag mass spectrometry (TMT-MS) pipeline, which allowed us to nearly triple the number of quantified proteins across cases. A consensus protein co-expression network analysis of this deeper dataset revealed new co-expression modules that were highly preserved across cohorts and brain regions, and strongly altered in AD. Nearly half of the protein co-expression modules, including modules significantly altered in AD, were not observed in RNA networks from the same cohorts and brain regions, highlighting the proteopathic nature of AD. Two such AD-associated modules unique to the proteomic network included a module related to MAPK signaling and metabolism, and a module related to the matrisome. Analysis of paired genomic and proteomic data within subjects showed that expression level of the matrisome module was influenced by the APOE ε4 genotype, but was not related to the rate of cognitive decline after adjustment for neuropathology. In contrast, the MAPK/metabolism module was strongly associated with the rate of cognitive decline. Disease-associated modules unique to the proteome are sources of promising therapeutic targets and biomarkers for AD.

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