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Entity

Name
Brain atrophy
Namespace
HP
Namespace Version
2017-10-05
Namespace URL
https://arty.scai.fraunhofer.de/artifactory/bel/namespace/hp/hp-20171108.belns

Appears in Networks 1

In-Edges 4

a(GO:"neurofibrillary tangle") association path(HP:"Brain atrophy") View Subject | View Object

NFTs are highly correlated with the rate of ventricular enlargement, an indicator of brain atrophy and hallmark of AD pathology (Silbert et al., 2003) PubMed:30126037

composite(a(CHEBI:"dasatinib (anhydrous)"), a(CHEBI:quercetin)) decreases path(HP:"Brain atrophy") View Subject | View Object

The DQ-dependent reduction in cortical NFTs corresponded with decreased ventricular volume pathology (28% decrease, P = 0.05, Figure 5d, f) and a reduction in cortical brain atrophy (compared to controls: P = 0.0092 and P = 0.0274, vehicle and DQ, respectively; Figure S5a) PubMed:30126037

p(MGI:Cdkn2a) positiveCorrelation path(HP:"Brain atrophy") View Subject | View Object

Further, when plotted against brain weight, Cdkn2a expression was a strong predictor of brain atrophy across mouse lines (P < 0.0001, R2 = 0.5615; Figure 4f) PubMed:30126037

p(MGI:Mapt) increases path(HP:"Brain atrophy") View Subject | View Object

The reduced tau pathology corresponded with 60% lower Cdkn2a expression (P = 0.0041, Figure 4a), decreased SASP (Figure S4) and decreased brain atrophy (tauNFT-Mapt0/0: 0.4058 ± 0.009 versus age-matched tauNFT Maptwt/wt: 0.3451 ± 0.0116; 17.5% difference, P = 0.0143, Figure 4b) PubMed:30126037

Out-Edges 2

path(HP:"Brain atrophy") positiveCorrelation p(MGI:Cdkn2a) View Subject | View Object

Further, when plotted against brain weight, Cdkn2a expression was a strong predictor of brain atrophy across mouse lines (P < 0.0001, R2 = 0.5615; Figure 4f) PubMed:30126037

path(HP:"Brain atrophy") association a(GO:"neurofibrillary tangle") View Subject | View Object

NFTs are highly correlated with the rate of ventricular enlargement, an indicator of brain atrophy and hallmark of AD pathology (Silbert et al., 2003) PubMed:30126037

About

BEL Commons is developed and maintained in an academic capacity by Charles Tapley Hoyt and Daniel Domingo-Fernández at the Fraunhofer SCAI Department of Bioinformatics with support from the IMI project, AETIONOMY. It is built on top of PyBEL, an open source project. Please feel free to contact us here to give us feedback or report any issues. Also, see our Publishing Notes and Data Protection information.

If you find BEL Commons useful in your work, please consider citing: Hoyt, C. T., Domingo-Fernández, D., & Hofmann-Apitius, M. (2018). BEL Commons: an environment for exploration and analysis of networks encoded in Biological Expression Language. Database, 2018(3), 1–11.