Immune pathways and prenatal/perinatal environmental exposures contribute to epigenetic gestational age prediction and acceleration.
The study found a strong association between DNA methylation and gestational age, with a predictive model achieving R² = 0.88, but further research is needed to clarify clinical implications.
Where it sits
this study against the rest of the pramlintide corpusSummary and findings
This study evaluated the association between DNA methylation and chronological gestational age (GA) in a cohort of 391 newborns. The researchers identified 2,435 CpG sites associated with GA and developed a multi-CpG site model with a predictive accuracy of R² = 0.88. Additionally, they assessed the impact of prenatal and perinatal environmental factors on epigenetic gestational age acceleration (EGAA).
Abstract
DNA methylation (DNAm), capturing chronological gestational age (GA) and epigenetic gestational age acceleration (EGAA), can be modified by environmental exposures. The Asthma&Allergy array is a new DNAm array developed with content focused on asthma and allergy loci. The association between content on the Asthma&Allergy array and chronological GA and EGAA has not been evaluated alone or in the context of prenatal/perinatal exposures. We performed an epigenome wide association study (EWAS) chronological GA at single CpG sites and regions in cord blood from 391 newborn children from a Detroit-based birth cohort. We further constructed a multi-CpG site methylation model to predict chronological GA. Also, associations between prenatal/perinatal environmental factors with GA, epigenetic gestational age (EGA), and EGAA were assessed. We identified 2,435 CpG sites associated with chronological GA, and CpGs within the HLA class II locus (<i>HLA-DRB1, HLA-DQB1, HLA-DRB6</i>) were among the most significantly associated with chronological GA. Our multi-CpG site model attained higher predictive accuracy (R<sup>2</sup> = 0.88) comparable to other published methods. Using genes implicated in region-based analyses (<i>n</i> = 395 regions), the pathways most significantly enriched with chronological GA-associated CpGs included T helper 1(Th1) and 2(Th2) activation, B-cell development, and IL-10 signaling, which were also enriched in at least one of the other published epigenetic GA clocks. In multi-exposure models, infant's first-born status and maternal parity were associated with EGAA. Our findings highlight enrichment for T cell modulated pathways and antigen presentation as biological processes associated with chronological GA, as well as prenatal/perinatal factors that may affect EGAA.
Background
This paper addresses the relationship between DNA methylation and gestational age, focusing on how environmental exposures may influence epigenetic gestational age acceleration (EGAA). Prior studies have shown that DNA methylation can reflect chronological GA, but the specific contributions of prenatal and perinatal factors to EGAA were not well understood. This study is significant as it explores new associations that could enhance understanding of developmental biology and potential health implications.
Methods
The study utilized an epigenome-wide association study (EWAS) design involving 391 newborns from a Detroit-based birth cohort. The primary outcome was chronological GA assessed at single CpG sites and regions in cord blood. A multi-CpG site methylation model was constructed to predict chronological GA, and associations with prenatal/perinatal environmental factors were also evaluated.
Results
The primary finding was the identification of 2,435 CpG sites associated with chronological GA. The multi-CpG site model achieved a predictive accuracy of R² = 0.88, indicating a strong correlation with chronological GA. Specific CpGs within the HLA class II locus were highlighted as significantly associated with GA, although p-values and confidence intervals were not reported in the abstract.
Interpretation
These findings suggest a robust association between DNA methylation patterns and chronological GA, with implications for understanding the biological processes involved in gestational development. However, while the statistical significance of the findings is clear, the clinical relevance remains uncertain without further context on the effect sizes and implications for health outcomes. Limitations such as the lack of reported p-values and potential confounding factors from environmental exposures should be considered when interpreting the results.
Key findings
- 2,435 CpG sites associated with chronological GA identified.
- Multi-CpG site model attained predictive accuracy of R² = 0.88.
- HLA class II locus CpGs were among the most significantly associated with chronological GA.
- Infant's first-born status and maternal parity associated with EGAA.
Limitations
- Not reported in abstract.
- Single-site study may limit generalizability.
- Potential confounding from environmental factors not fully explored.
- No p-values or confidence intervals reported for key findings.