Neuronal γ-secretase regulates lipid metabolism, linking cholesterol to synaptic dysfunction in Alzheimer's disease
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA849203 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR19651145_1.fastq.gz | Fastqsanger.gz | |||
| SRR19651145_2.fastq.gz | Fastqsanger.gz | |||
| SRR19651146_1.fastq.gz | Fastqsanger.gz | |||
| SRR19651146_2.fastq.gz | Fastqsanger.gz | |||
| SRR19651147_1.fastq.gz | Fastqsanger.gz |
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Project description:Presenilin mutations that alter γ-secretase activity cause familial Alzheimer's disease (AD), whereas ApoE4, an apolipoprotein for cholesterol transport, predisposes to sporadic AD. Both sporadic and familial AD feature synaptic dysfunction. Whether γ-secretase is involved in cholesterol metabolism and whether such involvement impacts synaptic function remains unknown. Here, we show that in human neurons, chronic pharmacological or genetic suppression of γ-secretase increases synapse numbers but decreases synaptic transmission by lowering the presynaptic release probability without altering dendritic or axonal arborizations. In search of a mechanism underlying these synaptic impairments, we discovered that chronic γ-secretase suppression robustly decreases cholesterol levels in neurons but not in glia, which in turn stimulates neuron-specific cholesterol-synthesis gene expression. Suppression of cholesterol levels by HMG-CoA reductase inhibitors (statins) impaired synaptic function similar to γ-secretase inhibition. Thus, γ-secretase enables synaptic function by maintaining cholesterol levels, whereas the chronic suppression of γ-secretase impairs synapses by lowering cholesterol levels.
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Project description:Epigenetic dysregulation, which leads to the alteration of gene expression in the brain, is suggested as one of the key pathophysiological bases of aging and neurodegeneration. Here we found that, in the late-stage familial Alzheimer’s disease (FAD) mouse model, repressive histone H3 dimethylation at lysine 9 (H3K9Me2) and euchromatic histone methyltransferases, EHMT1 and EHMT2 (H3K9Me2 catalyzer), were significantly elevated in the prefrontal cortex (PFC) region of post-mortem tissues from human patients with Alzheimer's disease. Concomitantly, H3K9Me2 at the promoter region of glutamate receptors was increased in PFC of aged FAD mice, which was linked to the diminished transcription, expression and function of AMPA and NMDA receptors. Treatment of FAD mice with specific EHMT1/2 inhibitors reversed histone hyper-methylation and led to the recovery of glutamate receptor expression and excitatory synaptic function in PFC and hippocampus. Chromatin immunoprecipitation-sequencing (ChIP-seq) data indicated that FAD mice exhibited genome-wide increase of H3K9Me2 enrichment at genes involved in neuronal signaling (including glutamate receptors), which was reversed by EHMT1/2 inhibition. Moreover, the impaired recognition memory, working memory, and spatial memory in aged FAD mice were rescued by the treatment with EHMT1/2 inhibitors. These results suggest that disrupted epigenetic regulation of glutamate receptor transcription underlies the synaptic and cognitive deficits in Alzheimer's disease, and targeting histone methylation enzymes may represent a novel therapeutic strategy for this prevalent neurodegenerative disorder.
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Project description:Epigenetic aberrations are suggested to play an important role in transcriptional alterations in Alzheimer's disease (AD). One of the key mechanisms of epigenetic regulation of gene expression is through the dynamic organization of chromatin structure via the master genome architecture protein, CCCTC-binding factor (CTCF). By forming chromatin loops, CTCF can influence gene transcription in a complex manner. To find out whether genome-wide DNA binding sites for CTCF are altered in AD, we compared CTCF chromatin immunoprecipitation sequencing (ChIP-Seq) data from frontal cortex of human AD patients and normal controls (n=9 pairs, all females). We have revealed that CTCF-binding affinity on many genes is significantly reduced in AD patients, and these genes are enriched in synaptic organization, cell adhesion, and actin cytoskeleton, including synaptic scaffolding molecules and receptors, such as SHANK2, HOMER1, NRXN1, CNTNAP2 and GRIN2A, and protocadherin (PCDH) and cadherin (CDH) family members. By comparing transcriptomic data from AD patients, we have discovered that many of the synaptic and adhesion genes with reduced CTCF binding in AD are significantly reduced in their mRNA expression. Moreover, a significant overlap of genes with the diminished CTCF binding and the reduced H3K27ac is identified in AD, with the common genes enriched in synaptic organization. These data suggest that the CTCF-controlled 3D chromatin organization is perturbed in AD, which may be linked to the diminished expression of target genes, probably through changes in histone modification.
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2010-06-11 | E-GEOD-6777 | biostudies-arrayexpress
Project description:The intramembrane protease gamma-secretase has broad physiological functions, but also contributes to Notch-dependent tumors and Alzheimer’s disease. To identify naturally short substrates and non-substrates of gamma-secretase, we used four human cell lines of different tissue origins, breast cancer MCF7 cells, cervix carcinoma HeLa cells, T cell leukemia Jurkat cells and lymphoma U937 macrophage-like cells. The cell lines were treated overnight with the established gamma-secretase inhibitor DAPT or DMSO as a control. The proteomes of membrane fractions were determined by nano-liquid chromatography-tandem mass spectrometry and label-free quantitative proteomics. TNFRSF12A, PTPRCAP and C16orf54 were identified as potential naturally short gamma-secretase substrates, whereas other proteins with a short ectodomain including ‘pituitary tumor-transforming gene 1-interacting protein’ (PTTG1IP) did not show an increased abundance upon DAPT treatment.
2024-05-24 | PXD045701 | Pride
Project description:Kyrtsos2011 - A systems biology model for
Alzheimer's disease (Cholesterol in AD)
Encoded non-curated model. Issues:
- Confusing HmgCoA differential equation
- Confusing d2 and t1 parameters
- Lack of initial values for several key species
This model is described in the article:
Of Mice and Math: A Systems
Biology Model for Alzheimer's disease
Kyrtsos, Christina Rose
UMD Theses and Dissertations
Abstract:
Alzheimer's disease (AD) is the most prevalent
neurodegenerative disorder in the US, affecting over 1 in 8
people over the age of 65. There are several well-known
pathological changes in the brains of AD patients, namely: the
presence of diffuse beta amyloid plaques derived from the
amyloid precursor protein (APP), hyper-phosphorylated tau
protein, neuroinflammation and mitochondrial dysfunction.
Recent studies have shown that cholesterol levels in both the
plasma and the brain may play a role in disease pathogenesis,
however, this exact role is not well understood. Additional
proteins of interest have also been identified (ApoE, LRP-1,
IL-1) as possible contributors to AD pathogenesis. To help
understand these roles better, a systems biology mathematical
model was developed. Basic principles from graph theory and
control analysis were used to study the effect of altered
cholesterol, ApoE, LRP and APP on the system as a whole.
Negative feedback regulation and the rate of cholesterol
transfer between astrocytes and neurons were identified as key
modulators in the level of beta amyloid. Experiments were run
concurrently to test whether decreasing plasma and brain
cholesterol levels with simvastatin altered the expression
levels of beta amyloid, ApoE, and LRP-1, to ascertain the edge
directions in the network model and to better understand
whether statin treatment served as a viable treatment option
for AD patients. The work completed herein represents the first
attempt to create a systems-level mathematical model to study
AD that looks at intercellular interactions, as well as
interactions between metabolic and inflammatory pathways.
This model is hosted on
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MODEL1504240000.
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2016-05-09 | MODEL1504240000 | BioModels