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Network analyses of single cell-based digital twins for individualized treatment of antigen induced arthritis in mice.

ABSTRACT: Network analyses of single cell-based digital twins for individualized treatment of antigen induced arthritis in mice.

PROVIDER: PRJNA796553 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR17584862.fastq.gz	Fastqsanger.gz
	SRR17584863.fastq.gz	Fastqsanger.gz
	SRR17584864.fastq.gz	Fastqsanger.gz
	SRR17584865.fastq.gz	Fastqsanger.gz
	SRR17584866.fastq.gz	Fastqsanger.gz

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Network analyses of single cell-based digital twins for individualized treatment of antigen induced arthritis in mice.

Project description:Computational treatment of digital twins of individual patients has been proposed as a strategy to personalize treatment. Systematic solutions are though currently lacking for inflammatory diseases. Here, we propose a strategy (scDrugPrio) that creates scRNA-seq based multicellular disease models that incorporate the key biological and pharmacological properties such as gene interactions within and between cell types, varying gene expression levels between cells and individuals, and inhibitory or enhancing drug effects. scDrugPrio was constructed based on joint scRNA-seq data from a mouse model of antigen induced arthritis. It was and validated by improved precision/recall for known drug targets and in vitro studies of predicted but yet unknown drug targets. When applied to human multiple sclerosis and Crohn’s disease, scDrugPrio was able to stratify predicted treatments based on interindividual variations. We hence propose scDrugPrio as a solution to personalize treatment by projecting network-based drug screening to digital twins of individual patients on cellulome-, genome-and drugome-wide scales.

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High-specificity bioinformatics framework for epigenomic profiling of discordant twins reveals specific and shared markers for ACPA and ACPA-positive rheumatoid arthritis.

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A dynamic single cell-based framework for digital twins to prioritize disease genes and drug targets

Project description:A major health care problems today is that drug treatment is ineffective for many patients. This may depend on the involvement of thousands of genes, which vary between patients with the same diagnosis at different time points. Identification and prioritization of upstream regulatory (UR) genes for precision medicine are therefore great challenges. In this study, we present a framework to model dynamic cellulome- and genome-wide changes in digital twins, to prioritize UR genes. We used seasonal allergic rhinitis (SAR) as a disease model because the external trigger (pollen) is known, so that the disease process can be mimicked by time series analyses of in vitro allergen-stimulated PBMC from SAR patients. Based on single cell profiling data from different stages of the disease, we constructed network models, hypothesizing that the directed molecular interactions between cell types could be traced to find an UR cell type and gene. This hypothesis was rejected because the cellular interactions formed multi-directional networks, rather than linear hierarchies. Instead, we were successfully able to rank and prioritize the URs based on their relative effects on the different cell types. We propose that this ranking strategy is a scalable approach for organizing and analyzing cellulome- and genome-wide data in digital twins.

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HumanMethylation450 (450k) data for 79 rheumatoid arthritis disease discordant monozygotic twin pairs

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Project description:A longstanding goal has been to find an antigen-specific preventive therapy, i.e., a vaccine, for autoimmune diseases. Major hindrances have so far been to select natural regulatory antigen targets and side-effects induced by clustering the T cell receptor (TCR) or activating the costimulatory signals. Here we show that the administration of a mouse major histocompatibility complex class II protein binding a unique galactosylated collagen type II (COL2) peptide (Aq-galCOL2) directly interacts with the antigen specific TCR, and expands peripheral regulatory T cells, displaying a potent dominant suppressive effect and protection of collagen induced arthritis. The therapeutic effect is dominant and tissue specific as it is possible to transfer the effect with induced regulatory T cells and downregulate autoimmune arthritis induced by other antigens than COL2 or by passive transfer of antibodies. Thus, the here described tolerogenic approach may be a promising dominant antigen-specific therapy for RA, and in principle, for autoimmune diseases in general.

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NSCLP-Twins

Project description:NSCLP-Twins

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Clinical study on individualized and precise immunotherapy for colorectal cancer based on high-throughput tumor antigen polypeptides screening

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Gene expression profile of preclinical arthritis and its modulation by antigen-induced tolerance

Project description:During the course of adjuvant arthritis, maximal changes in gene expression were observed at the incubation phase. A major group of genes affected was related to immune activity. Tolerance induction by mycobacterial heat-shock protein 65 (Bhsp65), the disease-related antigen, caused upregulation of a large number of genes. These included immune activity genes as well as cell proliferation-related genes. We used microarrays to detail the global programme of gene expression underlying cellularisation and identified distinct classes of up-regulated genes during this process. The draining lymph node cells (LNC) were harvested from arthritic rats at different phases of adjuvant arthritis (incubation,peak and recovery). Also tested were LNC of naïve rats. LNC were tested ex vivo. Total RNA isolated from LNC was used for testing with affymetrix gene chip following manufacturer's instructions. Similarly, LNC of Bhsp65-tolerized rats harvested at incubation phase were tested with or without Bhsp65 restimulation in vitro. LNC of arthritic rats in incubation phase were similarly restimulated with Bhsp65 in vitro as controls, and the results compared with that of the tolerized rats.

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