scholarly journals 5-Hydroxymethylcytosine Signatures in Circulating Cell-Free DNA as Early Warning Biomarkers for COVID-19 Progression and Myocardial Injury

2022 ◽  
Vol 9 ◽  
Author(s):  
Hang-yu Chen ◽  
Xiao-xiao Li ◽  
Chao Li ◽  
Hai-chuan Zhu ◽  
Hong-yan Hou ◽  
...  
Keyword(s):  
Early Warning ◽  
Myocardial Injury ◽  
Area Under The Curve ◽  
Critical Conditions ◽  
Cell Free Dna ◽  
Free Dna ◽  
Genome Wide ◽  
Machine Learning Model ◽  
Warning Model ◽  
Phosphodiesterase 4D

Background: The symptoms of coronavirus disease 2019 (COVID-19) range from moderate to critical conditions, leading to death in some patients, and the early warning indicators of the COVID-19 progression and the occurrence of its serious complications such as myocardial injury are limited.Methods: We carried out a multi-center, prospective cohort study in three hospitals in Wuhan. Genome-wide 5-hydroxymethylcytosine (5hmC) profiles in plasma cell-free DNA (cfDNA) was used to identify risk factors for COVID-19 pneumonia and develop a machine learning model using samples from 53 healthy volunteers, 66 patients with moderate COVID-19, 99 patients with severe COVID-19, and 38 patients with critical COVID-19.Results: Our warning model demonstrated that an area under the curve (AUC) for 5hmC warning moderate patients developed into severe status was 0.81 (95% CI 0.77–0.85) and for severe patients developed into critical status was 0.92 (95% CI 0.89–0.96). We further built a warning model on patients with and without myocardial injury with the AUC of 0.89 (95% CI 0.84–0.95).Conclusion: This is the first study showing the utility of 5hmC as an accurate early warning marker for disease progression and myocardial injury in patients with COVID-19. Our results show that phosphodiesterase 4D and ten-eleven translocation 2 may be important markers in the progression of COVID-19 disease.

scholarly journals Sub-nucleosomal organization in urine cell-free DNA

2019 ◽  
Author(s):  
Havell Markus ◽  
Jun Zhao ◽  
Tania Contente-Cuomo ◽  
Elizabeth Raupach ◽  
Ahuva Odenheimer-Bergman ◽  
...  
Keyword(s):  
Nucleosome Occupancy ◽  
Area Under The Curve ◽  
Wide Distribution ◽  
Cancer Diagnostics ◽  
Cell Of Origin ◽  
Cell Free Dna ◽  
Noninvasive Diagnostics ◽  
Free Dna ◽  
Genome Wide ◽  
Fragmentation Patterns

AbstractCell-free DNA (cfDNA) in urine is a promising analyte for noninvasive diagnostics. However, urine cfDNA is highly fragmented and whether characteristics of these fragments reflect underlying genomic architecture is unknown. Here, we perform comprehensive characterization of fragmentation patterns in urine cfDNA. We show modal size and genome-wide distribution of urine cfDNA fragments are consistent with transient protection from degradation by stable intermediates of nucleosome disassembly. Genome-wide nucleosome occupancy and fragment sizes in urine cfDNA are informative of cell of origin and renal epithelial cells are amongst the highest contributors in urine. Compared to a nucleosome occupancy map based on control urine samples, we observe a higher fraction of fragments with aberrant ends in cancer patients, distinguishing cancer samples with an area under the curve of 0.89. Our results demonstrate sub-nucleosomal organization in urine cfDNA and are proof-of-principle that genome-wide fragmentation analysis of urine cfDNA can enable cancer diagnostics.

scholarly journals Aging-associated distinctive DNA methylation changes of LINE-1 retrotransposons in pure cell-free DNA from human blood

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Wardah Mahmood ◽  
Lars Erichsen ◽  
Pauline Ott ◽  
Wolfgang A. Schulz ◽  
Johannes C. Fischer ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Cell Free Dna ◽  
The Past ◽  
Free Dna ◽  
Genome Wide ◽  
Cancerous Cell ◽  
Pure Cell ◽  
Epigenetic Biomarker ◽  
Methylation Patterns ◽  
Cancerous Cells

AbstractLINE-1 hypomethylation of cell-free DNA has been described as an epigenetic biomarker of human aging. However, in the past, insufficient differentiation between cellular and cell-free DNA may have confounded analyses of genome-wide methylation levels in aging cells. Here we present a new methodological strategy to properly and unambiguously extract DNA methylation patterns of repetitive, as well as single genetic loci from pure cell-free DNA from peripheral blood. Since this nucleic acid fraction originates mainly in apoptotic, senescent and cancerous cells, this approach allows efficient analysis of aged and cancerous cell-specific DNA methylation patterns for diagnostic and prognostic purposes. Using this methodology, we observe a significant age-associated erosion of LINE-1 methylation in cfDNA suggesting that the threshold of hypomethylation sufficient for relevant LINE-1 activation and consequential harmful retrotransposition might be reached at higher age. We speculate that this process might contribute to making aging the main risk factor for many cancers.

scholarly journals The use of plasma donor-derived, cell-free DNA to monitor acute rejection after kidney transplantation

2019 ◽  
Vol 35 (4) ◽  
pp. 714-721 ◽  
Author(s):  
Els M Gielis ◽  
Kristien J Ledeganck ◽  
Amélie Dendooven ◽  
Pieter Meysman ◽  
Charlie Beirnaert ◽  
...  
Keyword(s):  
Acute Rejection ◽  
Serum Creatinine ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Threshold Value ◽  
Nucleotide Polymorphisms ◽  
Kidney Transplant Recipients ◽  
Cell Free Dna ◽  
Free Dna ◽  
Set Up

Abstract Background After transplantation, cell-free deoxyribonucleic acid (DNA) derived from the donor organ (ddcfDNA) can be detected in the recipient’s circulation. We aimed to investigate the role of plasma ddcfDNA as biomarker for acute kidney rejection. Methods From 107 kidney transplant recipients, plasma samples were collected longitudinally after transplantation (Day 1 to 3 months) within a multicentre set-up. Cell-free DNA from the donor was quantified in plasma as a fraction of the total cell-free DNA by next generation sequencing using a targeted, multiplex polymerase chain reaction-based method for the analysis of single nucleotide polymorphisms. Results Increases of the ddcfDNA% above a threshold value of 0.88% were significantly associated with the occurrence of episodes of acute rejection (P = 0.017), acute tubular necrosis (P = 0.011) and acute pyelonephritis (P = 0.032). A receiver operating characteristic curve analysis revealed an equal area under the curve of the ddcfDNA% and serum creatinine of 0.64 for the diagnosis of acute rejection. Conclusions Although increases in plasma ddcfDNA% are associated with graft injury, plasma ddcfDNA does not outperform the diagnostic capacity of the serum creatinine in the diagnosis of acute rejection.

scholarly journals Alterations of 5-hydroxymethylation in circulating cell-free DNA reflect molecular distinctions of subtypes of non-Hodgkin lymphoma

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Brian C.-H. Chiu ◽  
Chang Chen ◽  
Qiancheng You ◽  
Rudyard Chiu ◽  
Girish Venkataraman ◽  
...  
Keyword(s):  
B Cell Lymphoma ◽  
Cell Free Dna ◽  
Invasive Approach ◽  
Non Invasive ◽  
Signature Genes ◽  
Non Hodgkin Lymphoma ◽  
Free Dna ◽  
Genome Wide ◽  
Circulating Cell Free Dna

AbstractThe 5-methylcytosines (5mC) have been implicated in the pathogenesis of diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL). However, the role of 5-hydroxymethylcytosines (5hmC) that are generated from 5mC through active demethylation, in lymphomagenesis is unknown. We profiled genome-wide 5hmC in circulating cell-free DNA (cfDNA) from 73 newly diagnosed patients with DLBCL and FL. We identified 294 differentially modified genes between DLBCL and FL. The differential 5hmC in the DLBCL/FL-differentiating genes co-localized with enhancer marks H3K4me1 and H3K27ac. A four-gene panel (CNN2, HMG20B, ACRBP, IZUMO1) robustly represented the overall 5hmC modification pattern that distinguished FL from DLBCL with an area under curve of 88.5% in the testing set. The median 5hmC modification levels in signature genes showed potential for separating patients for risk of all-cause mortality. This study provides evidence that genome-wide 5hmC profiles in cfDNA differ between DLBCL and FL and could be exploited as a non-invasive approach.

236 Trends from over 85,000 genome-wide cell-free DNA tests

2021 ◽  
Vol 224 (2) ◽  
pp. S156
Author(s):  
Jill Rafalko ◽  
Samantha Caldwell ◽  
Eyad Almasri ◽  
Erica Soster ◽  
Kimberly Fanelli ◽  
...  
Keyword(s):  
Cell Free Dna ◽  
Free Dna ◽  
Genome Wide

Modeling cell-free DNA fragment size densities for non-invasive detection of cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 3058-3058
Author(s):  
Jacob Carey ◽  
Bryan Chesnick ◽  
Denise Butler ◽  
Michael Rongione ◽  
Giovanni Parmigiani ◽  
...  
Keyword(s):  
Fragment Size ◽  
Length Distribution ◽  
Mixture Component ◽  
Base Pairs ◽  
Machine Model ◽  
Cell Free Dna ◽  
Non Invasive ◽  
Free Dna ◽  
Genome Wide ◽  
Low Coverage

3058 Background: Circulating cell-free DNA (cfDNA) is largely nucleosomal in origin with typical fragment lengths of 167 base-pairs reflecting the length of DNA wrapped around-the histone and H1 linker. Given the nucleosomal origin of cfDNA, we have previously used low coverage whole genome sequencing to evaluate DNA fragmentation profiles to sensitively and specifically detect tumor-derived DNA with altered fragment lengths or coverage. Methods: Here we evaluate the use of Bayesian finite mixtures to model the fragment length distribution and demonstrate how the parameters from these models can be useful to distinguish between individuals with and without cancer. We examined the number of cfDNA fragments by size ranging from 100-220bp and approximated the mixture component location, scale, and weight using Markov Chain Monte Carlo. The performance of the method was determined using a ten-fold, ten repeat cross-validation of Gradient Boosted Machine model using 1) our previously described genome-wide fragmentation profile approach, 2) the parameters from the mixture model and 3) a combination of approaches 1) and 2) as features. Results: In this study of 215 cancer patients and 208 cancer-free individuals, we observed cross-validated AUCs of 1) 0.94, 2) 0.95, and 3) 0.97 among the three approaches. Conclusions: Our findings indicate that parsimonious mixture models may improve detection of cancer in conjunction with fragmentation profile analyses across the genome.

Cell-Free DNA Screening for Fetal Aneuploidy

2021 ◽  
pp. 115-120
Author(s):  
Ashley N. Battarbee ◽  
Neeta L. Vora
Keyword(s):  
Trisomy 21 ◽  
Dna Analysis ◽  
Chromosomal Abnormalities ◽  
Area Under The Curve ◽  
First Trimester ◽  
Outcome Data ◽  
Cell Free Dna ◽  
High Risk Women ◽  
Free Dna ◽  
Trimester Screening

In a prospective, multicenter blinded study at 35 international centers, the Noninvasive Examination of Trisomy (NEXT) study evaluated the performance of cell-free DNA screening for fetal trisomy compared to standard first trimester screening with nuchal translucency and serum analytes in a routine prenatal population. Among the 15,841 women who had standard screening and cell-free DNA analysis with neonatal outcome data, there were 68 chromosomal abnormalities (1 in 236). Of these, 38 were Trisomy 21 (1 in 417). Cell-free DNA analysis had a higher area under the curve (AUC) for trisomy 21, compared to standard screening (0.999 vs. 0.958, p = 0.001). Cell-free DNA analysis also had greater sensitivity, specificity, and positive predictive value compared to standard screening for trisomy 21, 18, and 13. While cell-free DNA analysis cannot detect all chromosome abnormalities, it performed better than standard screening for detection of trisomies 21, 18, and 13 in a routine population including low- and high-risk women.

scholarly journals Genome-wide chromosomal instability by cell-free DNA sequencing predicts survival in patients with metastatic breast cancer

The Breast ◽  
2020 ◽  
Vol 53 ◽  
pp. 111-118
Author(s):  
Hongnan Mo ◽  
Xiaobing Wang ◽  
Fei Ma ◽  
Ziliang Qian ◽  
Xiaoying Sun ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Metastatic Breast Cancer ◽  
Dna Sequencing ◽  
Chromosomal Instability ◽  
Metastatic Breast ◽  
Cell Free Dna ◽  
Free Dna ◽  
Genome Wide
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