Browse
Submit Data
Databases
API
Help

Dataset Information

11 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

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

ABSTRACT: 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.

SUBMITTER: Fox-Fisher I

PROVIDER: S-EPMC8651286 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

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

| PRJNA776644 | ENA

Cardiovascular disease biomarkers derived from circulating cell-free DNA methylation.

Project description:Acute coronary syndrome (ACS) remains a major cause of worldwide mortality. The syndrome occurs when blood flow to the heart muscle is decreased or blocked, causing muscle tissues to die or malfunction. There are three main types of ACS: Non-ST-elevation myocardial infarction, ST-elevation myocardial infarction, and unstable angina. The treatment depends on the type of ACS, and this is decided by a combination of clinical findings, such as electrocardiogram and plasma biomarkers. Circulating cell-free DNA (ccfDNA) is proposed as an additional marker for ACS since the damaged tissues can release DNA to the bloodstream. We used ccfDNA methylation profiles for differentiating between the ACS types and provided computational tools to repeat similar analysis for other diseases. We leveraged cell type specificity of DNA methylation to deconvolute the ccfDNA cell types of origin and to find methylation-based biomarkers that stratify patients. We identified hundreds of methylation markers associated with ACS types and validated them in an independent cohort. Many such markers were associated with genes involved in cardiovascular conditions and inflammation. ccfDNA methylation showed promise as a non-invasive diagnostic for acute coronary events. These methods are not limited to acute events, and may be used for chronic cardiovascular diseases as well.

| S-EPMC10304763 | biostudies-literature

Distinct subclonal tumour responses to therapy revealed by circulating cell-free DNA.

Project description:BACKGROUND:The application of precision medicine in oncology requires in-depth characterisation of a patient's tumours and the dynamics of their responses to treatment. PATIENTS AND METHODS:We used next-generation sequencing of circulating cell-free DNA (cfDNA) to monitor the response of a KIT p.L576P-mutant metastatic vaginal mucosal melanoma to sequential targeted, immuno- and chemotherapy. RESULTS:Despite a KIT mutation, the response to imatinib was mixed. Unfortunately, tumours were not accessible for molecular analysis. To study the mechanism underlying the mixed clinical response, we carried out whole-exome sequencing and targeted longitudinal analysis of cfDNA. This revealed two tumour subclones; one with a KIT mutation that responded to imatinib and a second KIT-wild-type subclone that did not respond to imatinib. Notably, the subclones also responded differently to immunotherapy. However, both subclones responded to carboplatin/paclitaxel, and although the KIT-wild-type subclone progressed after chemotherapy, it responded to subsequent re-administration of paclitaxel. CONCLUSION:We show that cfDNA can reveal tumour evolution and subclonal responses to therapy even when biopsies are not available.

| S-EPMC5035787 | biostudies-literature

Multiplexing DNA methylation markers to detect circulating cell-free DNA derived from human pancreatic β cells.

Project description:It has been proposed that unmethylated insulin promoter fragments in plasma derive exclusively from β cells, reflect their recent demise, and can be used to assess β cell damage in type 1 diabetes. Herein we describe an ultrasensitive assay for detection of a β cell-specific DNA methylation signature, by simultaneous assessment of 6 DNA methylation markers, that identifies β cell DNA in mixtures containing as little as 0.03% β cell DNA (less than 1 β cell genome equivalent). Based on this assay, plasma from nondiabetic individuals (N = 218, aged 4-78 years) contained on average only 1 β cell genome equivalent/mL. As expected, cell-free DNA (cfDNA) from β cells was significantly elevated in islet transplant recipients shortly after transplantation. We also detected β cell cfDNA in a patient with KATP congenital hyperinsulinism, in which substantial β cell turnover is thought to occur. Strikingly, in contrast to previous reports, we observed no elevation of β cell-derived cfDNA in autoantibody-positive subjects at risk for type 1 diabetes (N = 32), individuals with recent-onset type 1 diabetes (<4 months, N = 92), or those with long-standing disease (>4 months, N = 38). We discuss the utility of sensitive β cell cfDNA analysis and potential explanations for the lack of a β cell cfDNA signal in type 1 diabetes.

| S-EPMC7453897 | biostudies-literature

Quantification of transplant-derived circulating cell-free DNA in absence of a donor genotype.

Project description:Quantification of cell-free DNA (cfDNA) in circulating blood derived from a transplanted organ is a powerful approach to monitoring post-transplant injury. Genome transplant dynamics (GTD) quantifies donor-derived cfDNA (dd-cfDNA) by taking advantage of single-nucleotide polymorphisms (SNPs) distributed across the genome to discriminate donor and recipient DNA molecules. In its current implementation, GTD requires genotyping of both the transplant recipient and donor. However, in practice, donor genotype information is often unavailable. Here, we address this issue by developing an algorithm that estimates dd-cfDNA levels in the absence of a donor genotype. Our algorithm predicts heart and lung allograft rejection with an accuracy that is similar to conventional GTD. We furthermore refined the algorithm to handle closely related recipients and donors, a scenario that is common in bone marrow and kidney transplantation. We show that it is possible to estimate dd-cfDNA in bone marrow transplant patients that are unrelated or that are siblings of the donors, using a hidden Markov model (HMM) of identity-by-descent (IBD) states along the genome. Last, we demonstrate that comparing dd-cfDNA to the proportion of donor DNA in white blood cells can differentiate between relapse and the onset of graft-versus-host disease (GVHD). These methods alleviate some of the barriers to the implementation of GTD, which will further widen its clinical application.

| S-EPMC5542400 | biostudies-literature

Numerous uncharacterized and highly divergent microbes which colonize humans are revealed by circulating cell-free DNA.

Project description:Blood circulates throughout the human body and contains molecules drawn from virtually every tissue, including the microbes and viruses which colonize the body. Through massive shotgun sequencing of circulating cell-free DNA from the blood, we identified hundreds of new bacteria and viruses which represent previously unidentified members of the human microbiome. Analyzing cumulative sequence data from 1,351 blood samples collected from 188 patients enabled us to assemble 7,190 contiguous regions (contigs) larger than 1 kbp, of which 3,761 are novel with little or no sequence homology in any existing databases. The vast majority of these novel contigs possess coding sequences, and we have validated their existence both by finding their presence in independent experiments and by performing direct PCR amplification. When their nearest neighbors are located in the tree of life, many of the organisms represent entirely novel taxa, showing that microbial diversity within the human body is substantially broader than previously appreciated.

| S-EPMC5594678 | biostudies-literature

Quantifying circulating cell-free DNA in humans.

Project description:To our knowledge, this is the first comprehensive study on the influence of several pre-analytical and demographic parameters that could be a source of variability in the quantification of nuclear and mitochondrial circulating DNA (NcirDNA and McirDNA). We report data from a total of 222 subjects, 104 healthy individuals and 118 metastatic colorectal cancer (mCRC) patients. Approximately 50,000 and 3,000-fold more mitochondrial than nuclear genome copies were found in the plasma of healthy individuals and mCRC patients, respectively. In healthy individuals, NcirDNA concentration was statistically influenced by age (p?=?0.009) and gender (p?=?0.048). Multivariate analysis with logistic regression specified that age over 47 years-old was predictive to have higher NcirDNA concentration (OR?=?2.41; p?=?0.033). McirDNA concentration was independent of age and gender in healthy individuals. In mCRC patients, NcirDNA and McirDNA levels were independent of age, gender, delay between food intake and blood collection, and plasma aspect, either with univariate or multivariate analysis. Nonetheless, ad hoc study suggested that menopause and blood collection time might have tendency to influence cirDNA quantification. In addition, high significant statistical differences were found between mCRC patients and healthy individuals for NcirDNA (p?<?0.0001), McirDNA (p?<?0.0001) and McirDNA/NcirDNA ratio (p?<?0.0001). NcirDNA and McirDNA levels do not vary in the same way with regards to cancer vs healthy status, pre-analytical and demographic factors.

| S-EPMC6435718 | biostudies-literature

Brain-derived cell-free DNA.

Project description: Not available

| S-EPMC9083148 | biostudies-literature

Remote monitoring using donor-derived, cell-free DNA after kidney transplantation during the coronavirus disease 2019 pandemic.

Project description:BackgroundDonor-derived, cell-free DNA (dd-cfDNA) level correlates with allograft injury with clinical validity and utility for quiescence and active acute rejection (AR) in kidney transplant recipients. We analyzed trends in dd-cfDNA level immediately preceding and during the coronavirus disease 2019 (COVID-19) pandemic with implemented "shelter in place" and a tele-health strategy with remote home phlebotomy to limit COVID-19 exposure.MethodsDuring COVID-19 in the United States (US), we surveyed weekly (January 6, 2020-May 25, 2020) metrics for dd-cfDNA corresponding to both a low risk for active rejection (dd-cfDNA < 0.5%) and cohorts with indeterminate levels of 0.5% to 1.0% and > 1.0%. During the study timeframe, over 11,000 patient samples (67%) from 150 kidney transplantation centers were transitioned from standard facility-based to remote phlebotomy.ResultsThe proportion of dd-cfDNA samples, analyzed in 21 weekly aggregated cohorts by risk-stratification category, was unchanged during the COVID-19 escalation in the US. Linearized slopes for numbers of samples corresponding to indeterminate risk for AR cohorts of > 1.0% and 0.5% to 1.0% were -0.31 and -0.12, respectively; indicating that prevalence of these "at risk for AR cohorts" decreased during remote surveillance. Approximately 73% of samples corresponded to low risk of AR (dd-cfDNA < 0.5%), while an additional 15% of samples had dd-cfDNA level ? 1.0%.ConclusionThe combination of remote home phlebotomy including dd-cfDNA analysis and a tele-health program offer a new paradigm that may substantially improve patient compliance and assuage anxiety regarding the state of kidney allograft health during the COVID-19 pandemic. Further prospective multi-center studies with robust outcomes data are warranted.

| S-EPMC7770990 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data