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Record W4410030897 · doi:10.3390/diagnostics15091161

Circulating Cell-Free DNA as an Epigenetic Biomarker for Early Diabetic Retinopathy: A Narrative Review

2025· review· en· W4410030897 on OpenAlexaff
Boaz Li, Megan M. Yim, Yi Jin, Brendan Tao, Jim Shenchu Xie, Michael Balas, Haaris M. Khan, Wai‐Ching Lam, Peng Yan, Eduardo V. Navajas

Bibliographic record

VenueDiagnostics · 2025
Typereview
Languageen
FieldMedicine
TopicRetinal Imaging and Analysis
Canadian institutionsUniversity of TorontoUniversity of British Columbia
Fundersnot available
KeywordsEpigeneticsBiomarkerDNA methylationMedicineDiabetic retinopathyCell-free fetal DNAMethylated DNA immunoprecipitationBioinformaticsHistoneEpigenomicsRetinaDNA sequencingBiologyComputational biologyDiabetes mellitusDNANeuroscienceGeneticsGeneEndocrinologyGene expression

Abstract

fetched live from OpenAlex

Diabetic retinopathy (DR), a complication of type 2 diabetes mellitus (T2DM), is typically asymptomatic in its early stages. Diagnosis typically relies on routine fundoscopy for the clinical detection of microvascular abnormalities. However, permanent retinal damage may occur well before clinical signs are appreciable. In the early stages of DR, the retina undergoes distinct epigenetic changes, including DNA methylation and histone modifications. Recent evidence supports unique epigenetic 'signatures' in patients with DR compared to non-diabetic controls. These DNA 'signature' sequences may be specific to the retina and may circulate in peripheral blood in the form of cell-free DNA (cfDNA). In this review, we explore the literature and clinical application of cfDNA sampling as an early, non-invasive, accessible assessment tool for early DR detection. First, we summarize the known epigenetic signatures of DR. Next, we review current sequencing technologies used for cfDNA detection, such as magnetic bead-based enrichment, next-generation sequencing, and bisulfite sequencing. Finally, we outline the current research limitations and emerging areas of study which aim to improve the clinical utility of cfDNA for DR evaluation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.707
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.038
GPT teacher head0.380
Teacher spread0.342 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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