Estimating the Rate of Cell Type Degeneration from Epigenetic Sequencing of Cell-Free DNA

AbstractCirculating cell-free DNA (cfDNA) in the bloodstream originates from dying cells and is a promising non-invasive biomarker for cell death. Here, we develop a method to accurately estimate the relative abundances of cell types contributing to cfDNA. We leverage the distinct DNA methylation profile of each cell type throughout the body. Decomposing the cfDNA mixture is difficult, as fragments from relevant cell types may only be present in a small amount. We propose an algorithm, CelFiE, that estimates cell type proportion from both whole genome cfDNA input and reference data. CelFiE accommodates low coverage data, does not rely on CpG site curation, and estimates contributions from multiple unknown cell types that are not available in reference data. In simulations we show that CelFiE can accurately estimate known and unknown cell type of origin of cfDNA mixtures in low coverage and noisy data. Simulations also demonstrate that we can effectively estimate cfDNA originating from rare cell types composing less than 0.01% of the total cfDNA. To validate CelFiE, we use a positive control: cfDNA extracted from pregnant and non-pregnant women. CelFiE estimates a large placenta component specifically in pregnant women (p = 9.1 × 10−5). Finally, we use CelFiE to decompose cfDNA from ALS patients and age matched controls. We find increased cfDNA concentrations in ALS patients (p = 3.0 × 10−3). Specifically, CelFiE estimates increased skeletal muscle component in the cfDNA of ALS patients (p = 2.6 × 10−3), which is consistent with muscle impairment characterizing ALS. Quantification of skeletal muscle death in ALS is novel, and overall suggests that CelFiE may be a useful tool for biomarker discovery and monitoring of disease progression.

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Comprehensive human cell-type methylation atlas reveals origins of circulating cell-free DNA in health and disease

Nature Communications ◽

10.1038/s41467-018-07466-6 ◽

2018 ◽

Vol 9 (1) ◽

Cited By ~ 118

Author(s):

Joshua Moss ◽

Judith Magenheim ◽

Daniel Neiman ◽

Hai Zemmour ◽

Netanel Loyfer ◽

...

Keyword(s):

Human Cell ◽

Cell Type ◽

Cell Free Dna ◽

Free Dna ◽

Health And Disease ◽

Circulating Cell Free Dna

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Comprehensive cell type decomposition of circulating cell-free DNA with CelFiE

Nature Communications ◽

10.1038/s41467-021-22901-x ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Christa Caggiano ◽

Barbara Celona ◽

Fleur Garton ◽

Joel Mefford ◽

Brian L. Black ◽

...

Keyword(s):

Biomarker Discovery ◽

Cell Types ◽

Cell Type ◽

Cell Free Dna ◽

Free Dna ◽

Noninvasive Biomarker ◽

Dying Cells ◽

Als Patients ◽

Low Coverage ◽

Circulating Cell Free Dna

AbstractCirculating cell-free DNA (cfDNA) in the bloodstream originates from dying cells and is a promising noninvasive biomarker for cell death. Here, we propose an algorithm, CelFiE, to accurately estimate the relative abundances of cell types and tissues contributing to cfDNA from epigenetic cfDNA sequencing. In contrast to previous work, CelFiE accommodates low coverage data, does not require CpG site curation, and estimates contributions from multiple unknown cell types that are not available in external reference data. In simulations, CelFiE accurately estimates known and unknown cell type proportions from low coverage and noisy cfDNA mixtures, including from cell types composing less than 1% of the total mixture. When used in two clinically-relevant situations, CelFiE correctly estimates a large placenta component in pregnant women, and an elevated skeletal muscle component in amyotrophic lateral sclerosis (ALS) patients, consistent with the occurrence of muscle wasting typical in these patients. Together, these results show how CelFiE could be a useful tool for biomarker discovery and monitoring the progression of degenerative disease.

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Cardiovascular disease biomarkers derived from circulating cell-free DNA methylation

10.1101/2021.11.05.21265870 ◽

2021 ◽

Author(s):

Rafael Ricardo de Castro Cuadrat ◽

Adelheid Kratzer ◽

Hector Giral Arnal ◽

Katarzyna Wreczycka ◽

Alexander Blume ◽

...

Keyword(s):

Myocardial Infarction ◽

Dna Methylation ◽

Cell Type ◽

Cell Free Dna ◽

St Segment Elevation ◽

Segment Elevation Myocardial Infarction ◽

Free Dna ◽

St Segment ◽

Heart Injury ◽

Circulating Cell Free Dna

Acute coronary syndromes (ACS) remain a major cause of worldwide mortality. ACS diagnosis is done by a combination of factors, such as electrocardiogram and plasma biomarkers. These biomarkers, however, lack the power to accurately stratify patients into different risk groups. Instead, we used changes in the circulating cell-free DNA (ccfDNA) methylation profiles to estimate the extent of heart injury and the severity of ACS. Our approach relies on the fact that dying cells in acutely damaged tissue release DNA into the blood, causing an increase in the ccfDNA. In addition, each cell type has a distinct DNA methylation profile. We leverage cell type/state specificity of DNA methylation to deconvolute the cell types of origin for ccfDNA and also find DNA methylation-based biomarkers that stratify patient cohorts. The cohorts consisted of healthy subjects, and patients from three ACS conditions: ST-segment elevation myocardial infarction (STEMI), non-ST-segment elevation myocardial infarction (NSTEMI) and unstable angina (UA). We have used two cohorts of patients - discovery, and validation, both consisting of the same conditions . We have sequenced the ccfDNA from the discovery cohort using Whole Bisulfite Genome Sequencing (WBGS), to obtain an unbiased overview of plasma DNA methylation profiles. We have found a total of 1,614 differential methylated regions (DMRs) in the three ACS groups. Many of the regions are associated with genes involved in cardiovascular conditions and inflammation. Using linear models we were able to narrow down to 254 DMRs significantly associated with ACS severity. The reduced list of DMRs enabled a more accurate stratification of ACS patients. The predictive power of the DMRs was validated in the confirmation cohort using targeted methylation sequencing of the validation cohort. Measuring methylation on ccfDNA showed promise as a method for estimating the level of heart injury during an acute coronary event, and accurate patient risk stratification. The method is however not limited to acute events, and can be extended to other heart related diseases. It can be used for estimating the status of the disease in patients with chronic states, such as heart failure and coronary artery disease.

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Brain-derived circulating cell-free DNA defines the brain region and cell specific origins associated with neuronal atrophy

10.1101/538827 ◽

2019 ◽

Cited By ~ 1

Author(s):

Zac Chatterton ◽

Natalia Mendelev ◽

Sean Chen ◽

Towfique Raj ◽

Ruth Walker ◽

...

Keyword(s):

Brain Region ◽

Genetic Variance ◽

Cell Of Origin ◽

Cell Type ◽

Liquid Biopsies ◽

Cell Free Dna ◽

Non Invasive ◽

Free Dna ◽

Attractive Option ◽

The Brain

Liquid biopsies are revolutionizing the fields of prenatal non-invasive testing and cancer diagnosis by leveraging the genetic differences between mother and fetus, and, host and cancer. In the absence of genetic variance, epigenetics has been used to decipher the cell-of-origin of cell-free DNA (cfDNA). Liquid biopsies are minimally invasive and thus represent an attractive option for hard to biopsy tissues such as the brain. Here we report the first evidence of neuron derived cfDNA and cerebellum cfDNA within acute neurotrauma and chronic neurodegeneration, establishing the first class of peripheral biomarkers with specificity for the cell-type and brain-region undergoing potential injury and/or neurodegeneration.

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Physical activity specifically evokes release of cell-free DNA from granulocytes thereby affecting liquid biopsy

10.1101/2021.09.01.21262910 ◽

2021 ◽

Author(s):

Elmo WI Neuberger ◽

Stephanie Sontag ◽

Alexandra Brahmer ◽

Keito F.A. Philippi ◽

Markus P. Radsak ◽

...

Keyword(s):

Liquid Biopsy ◽

Hematological Malignancies ◽

Cell Types ◽

Immune Homeostasis ◽

Cell Type ◽

Cell Free Dna ◽

Free Dna ◽

Myeloid Neoplasms ◽

Cell Type Specific ◽

Exercise Induced

Cell-free DNA (cfDNA) methylation-based diagnostics is a promising approach in oncology and hematooncology. Exercise impacts immune homeostasis and leads to a rapid and marked increase of cfDNA levels in blood. Since the origin of cfDNA during exercise remains elusive, the implications for liquid biopsy are unknown. In this study, we identified the source of cfDNA in 10 healthy untrained individuals before, immediately after, and 30 min after exercise, and in 6 patients with myeloid neoplasms or acute leukemia under resting conditions. A pyrosequencing assay was used to analyze the methylation levels of four CpGs, representing DNA from granulocytes, lymphocytes, monocytes, and non-hematopoietic cells. After exercise, cfDNA was almost exclusively released from granulocytes, with cell type specific proportions increasing significantly from 54.1% to 90.2%. Exercise did not trigger the release of cfDNA from lymphocytes or other analyzed cell types, whereas a small amount of cfDNA was released from monocytes. Compared to healthy people, patients with hematological malignancies show significantly higher cfDNA levels at rest with 48.1 (19.1; 78) vs. 8.5 (8.2; 9.5) ng/ml, data expressed as median (25th; 75th percentiles), and considerably higher levels of lymphocyte specific hypomethylated cg17587997 (P<.001). Hence, exercise-induced cfDNA elevations can compromise diagnostic accuracy.

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