Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1328063 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Genome-wide MeDIP-Sequencing of 23 monozygotic twin pairs (n=46) from Australia discordant for major depressive disorder (MDD). MeDIP-seq of 23 monozygotic twin pairs discordant for major depressive disorder. MZ twin pairs were compared to identify significantly differently methylated sites associated with MDD.
2014-01-25 | E-GEOD-54370 | biostudies-arrayexpress
Project description:Genome-wide MeDIP-Sequencing was carried out on a total of 50 monozygotic twin pairs from the UK and Australia that are discordant for depression. We show that major depressive disorder is associated with significant hypermethylation within the coding region of ZBTB20, and is replicated in an independent cohort of 356 unrelated case-control individuals. The twins with major depressive disorder also show increased global variation in methylation in comparison with their unaffected co-twins. ZBTB20 plays an essential role in the specification of the Cornu Ammonis-1 field identity in the developing hippocampus, a region previously implicated in the development of major depressive disorder. Epigenetic study of MZ twins discordant for Major Depressive Disorder
2014-01-21 | E-GEOD-54222 | biostudies-arrayexpress
Project description:The interaction between cancer and depressive disorder remains unclear. In this study, we obtained patient data from TCGA and MDD-related (Major Depressive Disorder) genes from the GEO database and the sequencing data of the PDX model with chronic unpredictable stress (CUS). Molecular subtypes and a prognostic signature were generated based on the MDD-related genes obtained by differential expression analysis. According to our analysis, the gene signature was a promising biomarker in distinguishing the prognosis, the molecular or immune characteristics, and the depressive risk, as well as the therapy candidates for gastric adenocarcinoma patients.
2024-07-19 | GSE262056 | GEO
Project description:RNA was extracted from peripheral blood mononuclear cells (PBMC) of 24 adult healthy controls, 8 adult patients with bipolar disorder, and 21 adult patients with major depressive disorder to analyze gene expression patterns that identify biomarkers of disease and that may be correlated with fMRI data.
2012-07-26 | GSE39653 | GEO
Project description:Whole transcriptome sequencing of major depressive disorder (MDD) patients and healthy controls
| PRJNA787461 | ENA
Project description:Kilian2024 - Immune cell dynamics in Cue-Induced Extended Human Colitis Model
Single-cell technologies such as scRNA-seq and flow cytometry provide critical insights into immune cell behavior in inflammatory bowel disease (IBD). However, integrating these datasets into computational models for dynamic analysis remains challenging. Here, Kilian et al., (2024) developed a deterministic ODE-based model that incorporates these technologies to study immune cell population changes in murine colitis. The model parameters were optimized to fit experimental data, ensuring an accurate representation of immune cell behavior over time. It was then validated by comparing simulations with experimental data using Pearson’s correlation and further tested on independent datasets to confirm its robustness. Additionally, the model was applied to clinical bulk RNA-seq data from human IBD patients, providing valuable insights into immune system dynamics and potential therapeutic strategies.
Figure 4c, obtained from the simulation of human colitis model is highlighted here.
This model is described in the article:
Kilian, C., Ulrich, H., Zouboulis, V.A. et al. Longitudinal single-cell data informs deterministic modelling of inflammatory bowel disease. npj Syst Biol Appl 10, 69 (2024). https://doi.org/10.1038/s41540-024-00395-9
Abstract:
Single-cell-based methods such as flow cytometry or single-cell mRNA sequencing (scRNA-seq) allow deep molecular and cellular profiling of immunological processes. Despite their high throughput, however, these measurements represent only a snapshot in time. Here, we explore how longitudinal single-cell-based datasets can be used for deterministic ordinary differential equation (ODE)-based modelling to mechanistically describe immune dynamics. We derived longitudinal changes in cell numbers of colonic cell types during inflammatory bowel disease (IBD) from flow cytometry and scRNA-seq data of murine colitis using ODE-based models. Our mathematical model generalised well across different protocols and experimental techniques, and we hypothesised that the estimated model parameters reflect biological processes. We validated this prediction of cellular turnover rates with KI-67 staining and with gene expression information from the scRNA-seq data not used for model fitting. Finally, we tested the translational relevance of the mathematical model by deconvolution of longitudinal bulk mRNA-sequencing data from a cohort of human IBD patients treated with olamkicept. We found that neutrophil depletion may contribute to IBD patients entering remission. The predictive power of IBD deterministic modelling highlights its potential to advance our understanding of immune dynamics in health and disease.
This model was curated during the Hackathon hosted by BioMed X GmbH in 2024.
2025-03-07 | MODEL2502180001 | BioModels
Project description:Homo sapiens Exome sequencing in Major Depressive Disorder
| PRJNA774142 | ENA