DNA methylation episignature as a novel diagnostic tool for diamond-blackfan anemia
Bibliographic record
Abstract
Abstract Background Diamond-Blackfan anemia syndrome (DBAS) is a rare inherited bone marrow failure syndrome (IBMFS) characterized by impaired erythropoiesis and significant phenotypic and genetic heterogeneity. Diagnosis can be challenging due to clinical variability and the lack of sensitive and specific biomarkers. Over the past few years, several studies have identified characteristic DNA methylation (DNAm) signatures, or episignatures, associated with various genetic disorders, arising from pathogenic variants impacting epigenetic regulation. In recent years, growing number of episignatures have been utilized as stable and reliable biomarkers for the diagnosis of congenital genetic disorders and for the reclassification of variants of uncertain significance (VUSs), and have been implemented in clinical diagnostic laboratories with significant diagnostic utility in genetically unresolved patients with suspected rare disorders. Purpose and methods In this study, we investigated evidence for a DNA methylation (DNAm) episignature in a cohort of 80 DBAS patients with causative variants in various ribosomal protein genes: DBA1 (RPS19, n=30), DBA4 (RPS17, n=6), DBA5 (RPL35A, n=8), DBA6 (RPL5, n=15), DBA7 (RPL11, n=13), DBA10 (RPS26, n=8). Peripheral blood DNA was extracted using standard techniques. DNAm profiling was performed using the Illumina Infinium Methylation EPIC BeadChip arrays (EPIC v.2) according to the manufacturer's protocol (Illumina, San Diego, CA, USA). Controls were randomly selected from EpiSign Knowledge Database (EKD), at London Health Sciences Centre. Matching of controls and cases for age, sex, and array type was performed using the MatchIt package (version 4.5.1). Results The comparison of DBAS cases with matched controls from the EKD resulted in the identification of a total of 206 differentially methylated probes (DMPs), which enabled the definition of a specific episignature associated with DBAS. Given the clinical overlap between DBAS and Fanconi Anemia (FA), we tested the DBAS episignature in a cohort of FA patients using both supervised and unsupervised clustering approaches. This analysis clearly distinguished FA cases from DBAS cases, highlighting distinct underlying epigenetic differences despite their similar clinical presentations. Furthermore, we developed a specific DNAm classifier for the clinically similar DBA6 and DBA7 subgroups. Additionally, methylation profiles from revertant cases due to uniparental disomy (RPS19:P47L and RPS17 full gene deletion) were consistent with those of non-revertant DBAS cases, with RPS19:P47L showing identical DNAm patterns to non-revertant RPS19:P47L. Applying the DBA episignature analysis to six molecularly uncharacterized cases, three exhibited the DBA pattern. Subsequent genome sequencing identified causative genetic variants in two (RPL5: c.325-380A>G:p.?; RPL26: c.-6+3_-6+25del:p.?), validating the test robustness. Discussion and conclusions This work supports the use of DNA methylation profiling as a valuable diagnostic biomarker in all patients with clinical suspicion of DBAS and critically aiding in the resolution of VUS and molecularly uncharacterized cases. The presence of DBAS episignature in two revertant cases, despite phenotypic correction, indicates that the episignature is a persistent developmental biomarker associated with the underlying genetic mutation, rather than being solely dictated by the current functional status of ribosomal protein production or the severity of the clinical phenotype. Future collaborative efforts via DBA registries are crucial for validating these findings and identifying episignatures for rarer DBA subtypes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".