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Remote immune processes revealed by immune-derived circulating cell-free DNA

ABSTRACT: Remote immune processes revealed by immune-derived circulating cell-free DNA

PROVIDER: PRJNA776644 | ENA |

REPOSITORIES: ENA

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Remote immune processes revealed by immune-derived circulating cell-free DNA

Project description:Blood cell counts often fail to report on immune processes occurring in remote tissues. Here we use 25 immune cell type-specific methylation patterns in circulating cell-free DNA (cfDNA) for studying 26 human immune cell dynamics. We characterized cfDNA released from specific immune cell types in 27 healthy individuals (N=242), cross sectionally and longitudinally. Immune cfDNA levels had no 28 individual steady state as opposed to blood cell counts, suggesting that cfDNA concentration reflects 29 adjustment of cell survival to maintain homeostatic cell numbers. We also observed selective elevation 30 of immune-derived cfDNA upon perturbations of immune homeostasis. Following influenza 31 vaccination (N=92), B-cell-derived cfDNA levels increased prior to elevated B-cell counts and 32 predicted efficacy of antibody production. Patients with Eosinophilic Esophagitis (N=21) and B-cell 33 lymphoma (N=27) showed selective elevation of eosinophil and B-cell cfDNA respectively, which 34 were undetectable by cell counts in blood. Immune-derived cfDNA provides a novel biomarker for 35 monitoring immune responses to physiological and pathological processes that are not accessible using 36 conventional methods.

2021-11-26 | GSE186888 | GEO

Remote immune processes revealed by immune-derived circulating cell-free DNA.

Project description:Blood cell counts often fail to report on immune processes occurring in remote tissues. Here, we use immune cell type-specific methylation patterns in circulating cell-free DNA (cfDNA) for studying human immune cell dynamics. We characterized cfDNA released from specific immune cell types in healthy individuals (N = 242), cross sectionally and longitudinally. Immune cfDNA levels had no individual steady state as opposed to blood cell counts, suggesting that cfDNA concentration reflects adjustment of cell survival to maintain homeostatic cell numbers. We also observed selective elevation of immune-derived cfDNA upon perturbations of immune homeostasis. Following influenza vaccination (N = 92), B-cell-derived cfDNA levels increased prior to elevated B-cell counts and predicted efficacy of antibody production. Patients with eosinophilic esophagitis (N = 21) and B-cell lymphoma (N = 27) showed selective elevation of eosinophil and B-cell cfDNA, respectively, which were undetectable by cell counts in blood. Immune-derived cfDNA provides a novel biomarker for monitoring immune responses to physiological and pathological processes that are not accessible using conventional methods.

| S-EPMC8651286 | biostudies-literature

Interpretable Inflammation Landscape of Circulating Immune cells

Project description:Interpretable Inflammation Landscape of Circulating Immune cells

| PRJNA1045608 | ENA

Expression data from plasma exosomal microRNA of rats with remote ischemic conditioning and normal controls

Project description:Remote ischemic conditioning (RIC) is a safely therapeutic strategy for a variety of ischemic diseases, with efficiency comparable to the classic in-situ ischemic methods. Recent evidence has shown that RIC could alter the content of circulating exosomes. microRNAs involves in numerous functionally different biological and physiological processes. The aim of this study is to identify the differentially expressed exosomal microRNAs in rat plasma with RIC and to further explore the functions in ischemic heart diseases. Five RIC rats and 5 control rats were enrolled in this study. We used microarray analysis to identify miRNA expression in their plasma exosomes.

2022-04-01 | GSE198747 | GEO

Ovarian cancer mutational processes drive site-specific immune evasion

Project description:Ovarian cancer mutational processes drive site-specific immune evasion

| PRJNA749041 | ENA

Interpretable Inflammation Landscape of Circulating Immune cells (ILCIC_RespiratoryDiseases)

Project description:Interpretable Inflammation Landscape of Circulating Immune cells (ILCIC_RespiratoryDiseases)

| PRJNA1045612 | ENA

Interpretable Inflammation Landscape of Circulating Immune cells (ILCIC_BRCA)

Project description:Interpretable Inflammation Landscape of Circulating Immune cells (ILCIC_BRCA)

| PRJNA1045593 | ENA

Interpretable Inflammation Landscape of Circulating Immune cells (ILCIC_HealthyExercise)

Project description:Interpretable Inflammation Landscape of Circulating Immune cells (ILCIC_HealthyExercise)

| PRJNA1045594 | ENA

Interpretable Inflammation Landscape of Circulating Immune cells (ILCIC_cirrhosis)

Project description:Interpretable Inflammation Landscape of Circulating Immune cells (ILCIC_cirrhosis)

| PRJNA1045610 | ENA

Interpretable Inflammation Landscape of Circulating Immune cells

Project description:This SuperSeries is composed of the SubSeries listed below. Inflammation is a biological phenomenon beneficial for homeostasis, but unfavorable if dysregulated. Although major progress has been made in characterizing inflammation in specific diseases, a global, holistic understanding is still elusive. This is particularly intriguing, considering its function for human health and the potential for modern medicine if fully deciphered. Here, we leveraged advances in single-cell transcriptomics to delineate inflammatory processes of circulating immune cells during infection, immune-mediated inflammatory diseases and cancer. Our single-cell atlas of >6.5 million peripheral blood mononuclear cells from 1047 patients (56% female, 43% male) and 19 diseases allowed us to learn a comprehensive model of inflammation in circulating immune cells. The atlas expanded our current knowledge of the biology of inflammation of immune-mediated diseases, acute and chronic inflammatory diseases, infection and solid tumors, and laid the foundation to develop a disease classification framework using unsupervised as well as explainable machine learning. Beyond a disease-centered analysis, we charted altered activity of inflammatory molecules in peripheral blood cells, depicting discriminative inflammation-related genes to further understand mechanisms of inflammation. We present a rich resource for the community, and laid the groundwork for learning a classifier for inflammatory diseases, presenting cells in circulation as a potential tool for disease classification.

2025-10-13 | GSE248688 | GEO

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