Epigenetic profiling of preterm birth: a dual-tissue methylation patterns using long-read sequencing
Bibliographic record
Abstract
Introduction Preterm birth (PTB), a leading cause of neonatal morbidity and mortality, arises from complex maternal-fetal interactions with multifactorial origins. Emerging evidence suggests that epigenetic dysregulation may mediate these interactions. This study aimed to identify DNA methylation changes associated with PTB to uncover potential biomarkers and underlying mechanisms. Methods We employed long-read sequencing to profile genome-wide DNA methylation followed by gene ontology and pathway enrichment analysis in matched maternal peripheral blood and neonatal cord blood from 15 preterm and 7 full-term deliveries (mother–infant pairs). Results A total of 1,151 significantly differentially methylated regions (DMRs) and 25,336 differentially methylated loci (DMLs) were identified across maternal and neonatal blood samples. In maternal blood from PTB cases, the most significantly hypermethylated genes were MED38 , PSMB11 , and WNT7B , whereas EXTL3 and MMP9 were among the most hypomethylated. Additionally, the promoters of VWA5A , EIF4E3 , ZNF571 , and COPB2 exhibited significant hypermethylation, while those of SIRPB1 and TNFRSF19 showed hypomethylation. In neonatal cord blood from PTB cases, the most significantly hypermethylated genes were LOC401478 , ISG20 , LMTK3 , TCAF2 , and COL4A2 , whereas EXTL3 and MMP9 were among the most hypomethylated. Promoters of DKK3 , CELF2 , and IFI35 were notably hypermethylated, whereas ALOX12 and CLBA1 were among the most hypomethylated. Enrichment analysis revealed that these epigenetic alterations impact critical developmental, immune, and neuroendocrine pathways, including Wnt signaling, calcium signaling, MAPK, oxytocin signaling, and neuroactive ligand-receptor interaction. Comparative analysis identified 120 overlapping DMLs, with 91 hypermethylated and 28 hypomethylated consistently across maternal and neonatal samples, including DPPA3 , ABCA1 , and GKN1 . In contrast, 20,240 and 4,770 DMLs were unique to cord and peripheral blood, respectively. Additionally, 14 overlapping DMRs were mapped to genes such as PLD5 , FBXO40 , GMNC , HHIP , CLEC18B , and LHX1 , exhibiting non-random chromosomal clustering. Enrichment analysis of these shared DMRs revealed significant involvement in developmental processes, including skeletal morphogenesis, axis patterning, and fibroblast growth factor signaling, indicating convergence on core regulatory pathways in PTB. Conclusion This is the first dual-tissue PTB study using long-read methylation profiling. Our results reveal distinct and shared epigenetic signatures in maternal and neonatal compartments, offering insights into the molecular etiology of PTB and potential biomarkers for early detection and therapeutic intervention.
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 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 | 0.001 | 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) | 0.001 | 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".