Decoding Cytokine Networks in Ulcerative Colitis to Identify Pathogenic Mechanisms and Therapeutic Targets

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Сен. 16, 2024

Abstract Ulcerative colitis (UC) is a chronic inflammatory disorder of the gastrointestinal tract characterised by dysregulated cytokine signalling. Despite advent advanced therapies targeting signalling, treatment outcomes for UC patients remain suboptimal. Hence, there pressing need to better understand complexity regulation in comprehensively mapping interconnected signalling networks that are perturbed patients. To address this, we undertook systems immunology modelling single-cell transcriptomics data from colonic biopsies treatment-naive and treatment-exposed build complex underpinned putative cytokine–cytokine interactions. The generated effectively captured known physiologically relevant interactions which recapitulated vitro patient-derived epithelial organoids. These revealed new aspects pathogenesis, including subnetwork unique patients, identification highly rewired cytokines across disease states (IL22, TL1A, IL23A, OSM), JAK paralogue-specific cytokine-cytokine interactions, positioning TL1A as an important upstream regulator TNF IL23A well attractive therapeutic target. Overall, these findings open up several avenues guiding future cytokine-targeting approaches UC, presented methodology can be readily applied gain similar insights into other immune-mediated diseases (IMIDs). One Sentence Summary A map interaction ulcerative reveals novel with potential guide strategies.

Язык: Английский

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SCUBA implements a storage format-agnostic API for single-cell data access in R

F1000Research, Год журнала: 2024, Номер 13, С. 1256 - 1256

Опубликована: Окт. 21, 2024

While robust tools exist for the analysis of single-cell datasets in both Python and R, interoperability is limited, generally only accept one object class. Considerable programming expertise required to integrate across package ecosystems into a comprehensive analysis, due their differing languages internal data structures. This complicates validation results leads inconsistent visualizations between suites. Conversion formats most common solution, but this difficult error-prone rapid pace development suites underlying To address this, we created SCUBA (Single-Cell Unified Backend API), an R that implements unified access API all formats. extends approach from widely used Seurat SingleCellExperiment anndata objects. also new data-specific functions supported types. Performance scales well SCUBA-supported In addition performance, offers several advantages over conversion visualization further pre-processed data. First, extracts operation at hand, leaving original unmodified. process simpler, less error prone, memory intensive than conversion, which operates on entire dataset. Second, code written with can use any class as input, simple consistent syntax allows single script or (like our interactive browser, scExploreR) work seamlessly multiple types, reducing complexity improving readability reproducibility. Adoption will ultimately improve collaboration reproducible research by lowering barriers ecosystems.

Язык: Английский

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Identify novel therapeutic targets for type II diabetes and periodontitis: insights from single-cell analysis and Mendelian randomization analysis

Frontiers in Endocrinology, Год журнала: 2024, Номер 15

Опубликована: Окт. 31, 2024

Periodontitis is a common complication of type II diabetes (T2D). However, the existing research cannot fully elucidate association between them, let alone identify therapeutic targets for precise treatment diabetic periodontitis. Therefore, we employed integrated genetic approaches such as single-cell analysis, Mendelian randomization (MR) analysis and colocalization to uncover novel T2D This study MR phenotype scanning, cell-cell communication metabolic pathway activity unveil periodontitis T2D. We firstly identified core cell clusters periodontitis, important marker genes were selected. The causal associations these two diseases evaluated through analysis. Reverse additional validation scanning further supported our findings. Finally, preliminarily investigate mechanisms observed associations. Through scRNA-seq data, classical monocytes intermediate subclusters. Differential 221 differentially expressed (DEGs). 13 exhibiting with T2D, 11 Colocalization reverse enhanced robustness results. NCF1 target (OR = 1.09, 95% CI: 1.03-1.14, p 1.85 ×10-3 ) LRRC25 0.96, 0.93-0.99, 3.44 ×10-2 0.92, 0.84-0.99, 4.45 ). At last, indicated significant differences in functions expressing or not genes, which interpreted Among regarded targets. Our findings bridge gap understanding pave way targeted therapy diseases.

Язык: Английский

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Integrative Analysis of Multi Omic Data

Elsevier eBooks, Год журнала: 2024, Номер unknown

Опубликована: Янв. 1, 2024

Язык: Английский

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Organismal mucosal immunology: A perspective through the eyes of game theory

Mucosal Immunology, Год журнала: 2024, Номер unknown

Опубликована: Дек. 1, 2024

In complex organisms, functional units must interact cohesively to maintain homeostasis, especially within mucosal barriers that house diverse, specialized cell exposed constant environmental challenges. Understanding how homeostasis at is maintained and its disruption can lead autoimmune diseases or cancer, requires a holistic view. Although omics approaches systems immunology have become powerful tools, they are not without limitations; interpretations may reflect researchers' assumptions, even if other explanations exist. this perspective, I propose applying game theory concepts could help interpret data, offering fresh perspectives supporting the exploration of alternative scenarios. By framing immune system as network strategic interactions with multiple possible outcomes, theory, which analyzes decision-making processes, illuminate novel types functions, interactions, responses pathogens commensals, leading more comprehensive understanding diseases. addition, might encourage researchers consider broader range possibilities, reduce risk myopic thinking, ultimately enable refined complexity barriers. This perspective aims introduce complementary framework for immunologists, encouraging them incorporate these into data interpretation modeling.

Язык: Английский

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Rap1 and mTOR signaling pathways drive opposing immunotoxic effects of structurally similar aryl-OPFRs, TPHP and TOCP

Environment International, Год журнала: 2024, Номер 195, С. 109215 - 109215

Опубликована: Дек. 16, 2024

Язык: Английский

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Cracking the code of adaptive immunity: The role of computational tools

Cell Systems, Год журнала: 2024, Номер 15(12), С. 1156 - 1167

Опубликована: Дек. 1, 2024

Язык: Английский

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Future Directions for Quantitative Systems Pharmacology

Handbook of experimental pharmacology, Год журнала: 2024, Номер unknown

Опубликована: Янв. 1, 2024

Язык: Английский

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