SBML Qual models of selected COVID-19 Disease Map diagrams
Ontology highlight
ABSTRACT:
SUBMITTER: Marek Ostaszewski
PROVIDER: 714 | FAIRDOMHub | 2020-04-23
REPOSITORIES: FAIRDOMHub
Similar Datasets
Project description:SARS-CoV-2, the virus responsible for COVID-19, causes widespread damage in the lungs in the setting of an overzealous immune response whose origin remains unclear. We present a scalable, propagable, personalized, cost-effective adult stem cell-derived human lung organoid model that is complete with both proximal and distal airway epithelia. Monolayers derived from adult lung organoids (ALOs), primary airway cells, or hiPSC-derived alveolar type-II (AT2) pneumocytes were infected with SARS-CoV-2 to create in vitro lung models of COVID-19. Infected ALO-monolayers best recapitulated the transcriptomic signatures in diverse cohorts of COVID-19 patient-derived respiratory samples. The airway (proximal) cells were critical for sustained viral infection, whereas distal alveolar differentiation (AT2→AT1) was critical for mounting the overzealous host immune response in fatal disease; ALO monolayers with well-mixed proximodistal airway components recapitulated both. Findings validate a human lung model of COVID-19 , which can be immediately utilized to investigate COVID-19 pathogenesis and vet new therapies and vaccines.
2021-01-20 | GSE165200 | GEO
Project description:We performed quantitative proteomic profiling of 786 plasma samples from COVID-19 inpatients, treated at two different hospitals (Charité – Universitätsmedizin Berlin and University Hospital of Innsbruck). Sampling was performed at multiple time points throughout the course of the disease, to create a time-resolved map of COVID-19 progression. Full DIA-NN analysis reports are provided, as well as raw files for the QC runs.
2021-07-19 | PXD025752 | Pride
Project description:The goal of the experiment was to determine whether monocytes from Alzheimer's disease patients with covid had differentially expressed genes when compared to health individuals.
2024-02-28 | E-MTAB-13809 | biostudies-arrayexpress
Project description:The causative organism, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), exhibits a wide spectrum of clinical manifestations in disease-ridden patients. Differences in the severity of COVID-19 ranges from asymptomatic infections and mild cases to the severe form, leading to acute respiratory distress syndrome (ARDS) and multiorgan failure with poor survival. MiRNAs can regulate various cellular processes, including proliferation, apoptosis, and differentiation, by binding to the 3′UTR of target mRNAs inducing their degradation, thus serving a fundamental role in post-transcriptional repression. Alterations of miRNA levels in the blood have been described in multiple inflammatory and infectious diseases, including SARS-related coronaviruses. We used microarrays to delineate the miRNAs and snoRNAs signature in the peripheral blood of severe COVID-19 cases (n=9), as compared to mild (n=10) and asymptomatic (n=10) patients, and identified differentially expressed transcripts in severe versus asymptomatic, and others in severe versus mild COVID-19 cases. A cohort of 29 male age-matched patients were selected. All patients were previously diagnosed with COVID-19 using TaqPath COVID-19 Combo Kit (Thermo Fisher Scientific, Waltham, Massachusetts), or Cobas SARS-CoV-2 Test (Roche Diagnostics, Rotkreuz, Switzerland), with a CT value < 30. Additional criterion for selection was age between 35 and 75 years. Participants were grouped into severe, mild and asymptomatic. Classifying severe cases was based on requirement of high-flow oxygen support and ICU admission (n=9). Whereas mild patients were identified based on symptoms and positive radiographic findings with pulmonary involvement (n=10). Patients with no clinical presentation were labelled as asymptomatic cases (n=10).
2022-03-01 | E-MTAB-10970 | biostudies-arrayexpress
Project description:Adult Stem Cell-derived Complete Lung Organoid Models Emulate Lung Disease in COVID-19
| PRJNA693539 | ENA
Project description:We compared circulating miRNA profiles of hospitalized COVID-positive patients (n = 104, 27 with ARDS) and age and gender matched healthy controls (n = 18) to identify miRNA signatures associated with COVID and COVID-induced ARDS. Meta-analysis incorporating data from published studies and our data was performed to identify a set of differentially expressed miRNAs in 1) COVID-positive patients versus healthy controls as well as 2) severe (ARDS+) COVID vs moderate COVID. Gene ontology enrichment analysis of the genes these miRNAs interact with identified terms associated with immune response, such as interferon and interleukin signaling, as well as viral genome activities associated with COVID disease and severity. Additionally, we observed downregulation of a cluster of miRNAs located on chromosome 14 (14q32) among all COVID patients. To predict COVID disease and severity, we developed machine learning models that achieved AUC scores between 0.88–0.93 for predicting disease, and between 0.62–0.81 for predicting severity, even across diverse studies with different sample types (plasma versus serum), collection methods, and library preparations. Our findings provide network and top miRNA feature insights into COVID disease progression and contribute to the development of tools for disease prognosis and management.
2023-12-13 | GSE240888 | GEO
Project description:Translating findings from animal models to human disease is essential for dissecting disease mechanisms, developing and testing precise therapeutic strategies. The coronavirus disease 2019 (COVID-19) pandemic has highlighted this need, particularly for models showing disease severity-dependent immune responses. Single-cell transcriptomics (scRNAseq) is well poised to reveal similarities and differences between species at the molecular and cellular level with unprecedented resolution. However, computational methods enabling detailed matching are still scarce. Here, we provide a structured scRNAseq-based approach that we applied to scRNAseq from blood leukocytes originating from humans and hamsters affected with moderate or severe COVID-19. Integration of COVID-19 patient data with two hamster models that develop moderate (Syrian hamster, Mesocricetus auratus) or severe (Roborovski hamster, Phodopus roborovskii) disease revealed that most cellular states are shared across species. A neural network-based analysis using variational autoencoders quantified the overall transcriptomic similarity across species and severity levels, showing highest similarity between neutrophils of Roborovski hamsters and severe COVID-19 patients, while Syrian hamsters better matched patients with moderate disease, particularly in classical monocytes. We further used transcriptome-wide differential expression analysis to identify which disease stages and cell types display strongest transcriptional changes. Consistently, hamster’s response to COVID-19 was most similar to humans in monocytes and neutrophils. Disease-linked pathways found in all species specifically related to interferon response or inhibition of viral replication. Analysis of candidate genes and signatures supported the results. Our structured neural network-supported workflow could be applied to other diseases, allowing better identification of suitable animal models with similar pathomechanisms across species.
2024-12-13 | GSE253845 | GEO
Project description:Mizuno2012 - AlzPathway: a comprehensive map
of Alzheimer's disease
Non-kinetic molecular map.
Pure SBML file of AlzPathway provided by the authors as
Additional file 5.
This model is described in the article:
AlzPathway: a comprehensive
map of signaling pathways of Alzheimer's disease.
Mizuno S, Iijima R, Ogishima S,
Kikuchi M, Matsuoka Y, Ghosh S, Miyamoto T, Miyashita A, Kuwano
R, Tanaka H.
BMC Syst Biol 2012; 6: 52
Abstract:
BACKGROUND: Alzheimer's disease (AD) is the most common
cause of dementia among the elderly. To clarify pathogenesis of
AD, thousands of reports have been accumulating. However,
knowledge of signaling pathways in the field of AD has not been
compiled as a database before. DESCRIPTION: Here, we have
constructed a publicly available pathway map called
"AlzPathway" that comprehensively catalogs signaling pathways
in the field of AD. We have collected and manually curated over
100 review articles related to AD, and have built an AD pathway
map using CellDesigner. AlzPathway is currently composed of
1347 molecules and 1070 reactions in neuron, brain blood
barrier, presynaptic, postsynaptic, astrocyte, and microglial
cells and their cellular localizations. AlzPathway is available
as both the SBML (Systems Biology Markup Language) map for
CellDesigner and the high resolution image map. AlzPathway is
also available as a web service (online map) based on Payao
system, a community-based, collaborative web service platform
for pathway model curation, enabling continuous updates by AD
researchers. CONCLUSIONS: AlzPathway is the first comprehensive
map of intra, inter and extra cellular AD signaling pathways
which can enable mechanistic deciphering of AD pathogenesis.
The AlzPathway map is accessible at http://alzpathway.org/.
This model is hosted on
BioModels Database
and identified by:
MODEL1504290001.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2016-05-09 | MODEL1504290001 | BioModels
Project description:In order to identify differentially abundant proteins, human plasma samples from COVID-19 patients with either a mild or moderate (MM) or a critical or severe (CS) disease course from acute phase of infection were analyzed on antibody microarrays 998 different proteins by 1,425 antibodies.
2023-03-15 | E-MTAB-12777 | biostudies-arrayexpress
Project description:In order to identify differentially abundant proteins, human plasma samples from COVID-19 patients with either a mild or moderate (MM) or a critical or severe (CS) disease course from the acute phases of infection were analyzed on antibody microarrays targeting 351 different proteins by 517 antibodies.
2023-04-11 | E-MTAB-12779 | biostudies-arrayexpress