Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1303239 | ENA |
REPOSITORIES: ENA
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Project description:Dynamical network biomarker (DNB) theory has emerged as a powerful framework for detecting early warning signals of pre-disease states. Based on our previous work demonstrating its utility in adipose tissue of metabolic syndrome model mice, we conducted a comprehensive DNB analysis using RNA sequencing data across 13 organs and 14 to 16 time points in high-fat diet-fed mice. Our findings revealed organ-specific variation in the timing of early warning signals, suggesting heterogeneous inter-organ dynamics during the pre-disease state of metabolic syndrome. These results highlight the potential of DNB theory for elucidating systemic early-stage pathophysiology in complex metabolic disorders.
2025-08-23 | GSE305719 | GEO
Project description:The establishment of new therapeutic strategies for metabolic syndrome is urgently needed because metabolic syndrome, which is characterized by several disorders, such as hypertension, increases the risk of lifestyle-related diseases. One approach is to focus on the pre-disease state, a state with high susceptibility before the disease onset, which is considered as the best period for preventive treatment. In order to detect the pre-disease state, we recently proposed mathematical theory called the dynamical network biomarker (DNB) theory based on the critical transition paradigm. Here, we investigated time-course gene expression profiles of a mouse model of metabolic syndrome using 64 whole-genome microarrays based on the DNB theory, and showed the detection of a pre-disease state before metabolic syndrome defined by characteristic behavior of 147 DNB genes. The results of our study demonstrating the existence of a notable pre-disease state before metabolic syndrome may help to design novel and effective therapeutic strategies for preventing metabolic syndrome, enabling just-in-time preemptive interventions.
2019-06-24 | GSE112653 | GEO
Project description:Identifying pre-disease signals before metabolic syndrome in mice by dynamical network biomarkers
| PRJNA448613 | ENA
Project description:Purpose: Flies with Yki gut tumors is a widely used Drosophila model of cancer cachexia. Since cancer cachexia is a multi-organ syndrome, its investigation requires understanding how tumors induce metabolic dysfunction in peripheral organs. To address this, we performed a body-wide single-cell transcriptome analysis of Yki tumor model flies. Methods: snRNA-seq analysis of whole-body flies (without heads) with and without Yki gut tumors. Results: The data provides information of transcriptome alternations related to tumor-induced cachexia, including expression of metabolic genes and tumor-host organ communications. Conclusions: Cachexia phenotypes in Yki tumor model flies originated from metabolic dysregulation in peripheral organs that induced by tumor secreted factors.
2025-02-21 | GSE229526 | GEO
Project description:Integration of a multi-omics stem cell differentiation dataset using a dynamical model
| PRJNA360574 | ENA
Project description:Schinzel-Giedion syndrome (SGS) is a developmental syndrome, due to the accumulation of SETBP1 protein, which is fatal in early infancy. SGS has a multi-organ involvement with severe and persistent intellectual and physical problems. We produced a human SGS model that outlines disease-relevant phenotypes using patient-derived induced pluripotent stem cells and isogenic controls. Whole transcriptome profiling describes cancer-like alterations in SGS neural progenitors including deregulation of oncogenes and suppressors and enhanced proliferation. These findings demonstrated how SGS post-natal pathological traits mayhave developmental origin in the failure of controlling cell identity and homeostasis due to SETBP1 protein accumulation.
2021-06-03 | GSE150810 | GEO
Project description:Mangrove-derived Streptomyces xiamenensis 318, with a relatively compact genome and simpler secondary metabolism, is used as model organism in our investigation. We performed integrated studies of metabolic dynamical modeling, transcriptome level measurements, and metabolic profiling experiments on this strain. To explore the relationship between primary and secondary metabolism, the global gene expression levels of strain 318 from early stationary phase to late stationary phase were compared by RNAseq analysis at 16 hour, 24 hour, 36 hour and 72 hour after batch culture started.
2019-02-10 | E-MTAB-7314 | biostudies-arrayexpress
Project description:Kidney fibrosis, characterized by excessive extracellular matrix (ECM) deposition, is a progressive disease that, despite affecting 10% of the population, lacks specific treatments and suitable biomarkers. Aimed at unraveling disease mechanisms and identifying potential therapeutic targets, this study presents a comprehensive, time-resolved multi-omics analysis of kidney fibrosis using an in vitro model system based on human kidney PDGFRβ+ mesenchymal cells. Using computational network modeling we integrated transcriptomics, proteomics, phosphoproteomics, and secretomics with imaging of the extracellular matrix (ECM). We quantified over 14,000 biomolecules across seven time points following TGF-β stimulation, revealing distinct temporal patterns in the expression and activity of known and potential novel renal fibrosis markers and modulators. The resulting time-resolved multi-omic network models allowed us to propose mechanisms related to fibrosis progression through early transcriptional reprogramming. Using siRNA knockdowns and phenotypic assays, we validated predictions and elucidated regulatory mechanisms underlying kidney fibrosis. Notably, we demonstrate that several early-activated transcription factors, including FLI1 and E2F1, act as negative regulators of collagen deposition and propose underlying molecular mechanisms. This work advances our understanding of the pathogenesis of kidney fibrosis and provides a valuable resource for the organ fibrosis research community.
2024-11-07 | E-MTAB-14521 | biostudies-arrayexpress
Project description:It is difficult to develop effective treatments for neurodevelopmental genetic disorders, such as Rett syndrome, which are caused by a single gene mutation but trigger changes in numerous other genes, and thereby also severely impair functions of organs beyond the central nervous system (CNS). This challenge is further complicated by the lack of sufficiently broad and biologically relevant drug screens, and the inherent complexity in identifying clinically relevant targets responsible for diverse phenotypes. Here, we combined human gene regulatory network-based computational drug prediction with in vivo screening in a population-level diversity, CRISPR-edited, Xenopus laevis tadpole model of Rett syndrome to carry out target-agnostic drug discovery, which rapidly led to the identification of the FDA-approved drug vorinostat as a potential repurposing candidate. Vorinostat broadly improved both CNS and non-CNS (e.g., gastrointestinal, respiratory, inflammatory) abnormalities in a pre-clinical mouse model of Rett syndrome. This is the first Rett syndrome treatment to demonstrate pre-clinical efficacy across multiple organ systems when dosed after the onset of symptoms, and network analysis revealed a putative therapeutic mechanism for its cross-organ normalizing effects based on its impact on acetylation metabolism and post-translational modifications of microtubules.
2022-03-22 | GSE199049 | GEO
Project description:In a radiation mass casualty event, exposed populations will suffer dose-dependent toxicity to multiple-organ systems. Although several therapies are FDA-approved for treatment of the hematopoietic acute radiation syndrome (H-ARS), there are no FDA-approved medical countermeasures (MCM) for either acute gastrointestinal injury (GI) or late multi-organ toxicities known as the delayed effects of acute radiation exposure (DEARE). Prior data suggest activation of the alternative renin angiotensin (RAS) enzyme angiotensin-converting enzyme 2 (ACE2) has therapeutic potential for mitigating multi-organ radiation injury, including GI acute radiation syndrome (GI-ARS). Here, we evaluated whether pharmacologic activation of ACE2 mitigates GI-ARS in rodent models and protects against DEARE in GI-ARS survivors.
2025-08-04 | GSE303960 | GEO