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Expression data in patients with familial (FCS) and multifactorial chylomicronemia (MCM)

ABSTRACT: Expression data in patients with familial (FCS) and multifactorial chylomicronemia (MCM)

PROVIDER: PRJNA629355 | ENA |

REPOSITORIES: ENA

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Expression data in patients with familial (FCS) and multifactorial chylomicronemia (MCM)

Project description:FCS and MCM appear highly similar disorders. However, they importantly differ in term of risk and response to treatments. Some sets of genes might be up or down regulated in both disorders and could partly explain those differences. We used microarrays to explore gene expression patterns in FCS and MCM patients to identify potential targets that can be selected for protein quantification and functional studies.

2020-05-08 | GSE149607 | GEO

Characterisation of patients with familial chylomicronaemia syndrome (FCS) and multifactorial chylomicronaemia syndrome (MCS): Establishment of an FCS clinical diagnostic score.

Project description:Data presented in this article are supplementary material to our article entitled "Identification and diagnosis of patients with familial chylomicronaemia syndrome (FCS): expert panel recommendations and proposal of an "FCS Score" (Moulin et al., 2018, in press). The data describe the genotypes of patients with familial chylomicronaemia syndrome (FCS) and multifactorial chylomicronaemia syndrome (MCS), from the validation and replication cohorts.

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Effect of LPS-MCM and Hemin-MCM on gene expression of astrocytes

Project description:To investigate the transcriptional changes occurred in astrocytes after inflammatory or hemorrhagic stroke in vitro, we performed RNA sequencing (RNA-seq) of resting-MCM treated astrocytes, LPS-MCM treated astrocytes, and Hemin-MCM treated astrocytes.

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Identifying Patients with Familial Chylomicronemia Syndrome Using FCS Score-Based Data Mining Methods.

Project description:BackgroundThere are no exact data about the prevalence of familial chylomicronemia syndrome (FCS) in Central Europe. We aimed to identify FCS patients using either the FCS score proposed by Moulin et al. or with data mining, and assessed the diagnostic applicability of the FCS score.MethodsAnalyzing medical records of 1,342,124 patients, the FCS score of each patient was calculated. Based on the data of previously diagnosed FCS patients, we trained machine learning models to identify other features that may improve FCS score calculation.ResultsWe identified 26 patients with an FCS score of ≥10. From the trained models, boosting tree models and support vector machines performed the best for patient recognition with overall AUC above 0.95, while artificial neural networks accomplished above 0.8, indicating less efficacy. We identified laboratory features that can be considered as additions to the FCS score calculation.ConclusionsThe estimated prevalence of FCS was 19.4 per million in our region, which exceeds the prevalence data of other European countries. Analysis of larger regional and country-wide data might increase the number of FCS cases. Although FCS score is an excellent tool in identifying potential FCS patients, consideration of some other features may improve its accuracy.

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A new MCM modification cycle regulates DNA replication initiation

Project description:The hexameric DNA helicase MCM (Mcm2-7) is a central regulatory target in eukaryotic replication. Chromatin-bound MCM is kept inactive during G1 phase and subsequently activated in S phase to initiate replication. During this transition, the only known chemical change on the Mcm2-7 proteins is the gain of multi-site phosphorylation that promotes recruitment of co-factors. As replication initiation is tied intimately to multiple biological cues, additional changes on these proteins can provide a second regulatory point. Here we describe a new MCM modification cycle mediated by SUMO that enables a negative regulation of replication initiation. We show that all MCM subunits undergo sumoylation upon loading at origins in G1 phase prior to MCM phosphorylation. Then bulk MCM sumoylation is lost as MCM phosphorylation rises. The pattern of MCM sumoylation suggests a negative role in replication. Indeed, increasing MCM sumoylation delays genome-wide replication initiation. Mechanistically, this is partly due to enhancing the recruitment of a conserved phosphatase that delays MCM phosphorylation and activation. By revealing a new MCM modification cycle and its role in replication, our findings suggest a new model, in which MCM sumoylation counterbalances kinase-based regulation to ensure accurate control of replication initiation.

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Project description:Luteiomonas oceanisediminis (strain FCS-9) sp.nov. Genome sequencing and assembly

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Effect of LPS-MCM and Hemin-MCM on gene expression of astrocytes

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MCM complexes are barriers that restrict loops and TADs

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