Evidence map›Paper›PMID 32849827›Full record

ReviewFrontiers in genetics2020

Circulating Cell-Free Nucleic Acids as Epigenetic Biomarkers in Precision Medicine.

Beenish Rahat, Taqveema Ali, Divika Sapehia, Aatish Mahajan, Jyotdeep Kaur

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
2.6field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed, 60 citations in OpenAlex.

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  12. Biomarkers of mitochondrial disorders.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2024
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 2 countries.

Beenish RahatNational Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States.
Taqveema AliPostgraduate Institute of Medical Education and Research, Chandigarh, India.
Divika SapehiaPostgraduate Institute of Medical Education and Research, Chandigarh, India.
Aatish MahajanPostgraduate Institute of Medical Education and Research, Chandigarh, India.
Jyotdeep KaurPostgraduate Institute of Medical Education and Research, Chandigarh, India.
Post Graduate Institute of Medical Education and Research · INNational Institutes of Health · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The circulating cell-free nucleic acids (ccfNAs) are a mixture of single- or double-stranded nucleic acids, released into the blood plasma/serum by different tissues via apoptosis, necrosis, and secretions. Under healthy conditions, ccfNAs originate from the hematopoietic system, whereas under various clinical scenarios, the concomitant tissues release ccfNAs into the bloodstream. These ccfNAs include DNA, RNA, microRNA (miRNA), long non-coding RNA (lncRNA), fetal DNA/RNA, and mitochondrial DNA/RNA, and act as potential biomarkers in various clinical conditions. These are associated with different epigenetic modifications, which show disease-related variations and so finding their role as epigenetic biomarkers in clinical settings. This field has recently emerged as the latest advance in precision medicine because of its clinical relevance in diagnostic, prognostic, and predictive values. DNA methylation detected in ccfDNA has been widely used in personalized clinical diagnosis; furthermore, there is also the emerging role of ccfRNAs like miRNA and lncRNA as epigenetic biomarkers. This review focuses on the novel approaches for exploring ccfNAs as epigenetic biomarkers in personalized clinical diagnosis and prognosis, their potential as therapeutic targets and disease progression monitors, and reveals the tremendous potential that epigenetic biomarkers present to improve precision medicine. We explore the latest techniques for both quantitative and qualitative detection of epigenetic modifications in ccfNAs. The data on epigenetic modifications on ccfNAs are complex and often milieu-specific posing challenges for its understanding. Artificial intelligence and deep networks are the novel approaches for decoding complex data and providing insight into the decision-making in precision medicine.

Indexed as

autoimmune diseasescancer diagnosiscirculating cell free nucleic acidscirculating nucleic acids in plasma/serumepigenetic biomarkersprecision medicineprenatal and genetic diagnostics

Identifiers

PMID32849827
PMCPMC7431953
OpenAlexW3048737810

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.