Association of DLK1-MEG3 methylation levels in cord blood with small for gestational age
摘要
The DLK1-MEG3 gene locus on human chromosome 14q32.2 contributes significantly to glucose metabolism and is linked to SGA development, but the role of its methylation in glucose regulation and SGA remains unclear.
MethodsA nested case-control study of 330 participants (165 SGA, 165 AGA) measured methylation levels of IG-DMR (5 CpGs) and MEG3-DMR (7 CpGs) in umbilical cord blood using bisulfite pyrosequencing. Blood glucose and insulin levels were assessed. Logistic regression and mediation analysis were used.
ResultsHigher IG-DMR (Pos. 3) methylation level was associated with elevated SGA risk (OR = 1.068, 95% CI [1.002–1.142]) and lower blood glucose (Percentage change = −2.69%, 95% CI [−4.75% to −0.58%]). The average methylation level of MEG3-DMR was negatively correlated with SGA risk (OR = 0.931, 95% CI [0.876 to 0.987]) and positively with insulin (Percentage change = 3.38%, 95% CI [0.23% to 0.63%]). Mediation analysis suggested insulin mediated the effect between the average methylation level of MEG3-DMR and SGA (explaining 11.7%). After excluding preterm infants, the association between the average methylation level of MEG3-DMR and insulin was not significant, while other results remained similar.
ConclusionThese results offer new insights into how DNA methylation influences pregnancy outcomes and provide a foundation for SGA management and prevention research.
ImpactEpigenetic changes, such as DNA methylation, are believed to play a significant role in regulating intrauterine growth. The DLK1-MEG3 locus, which includes two differentially methylated regions (IG-DMR and MEG3-DMR) is involved in glucose metabolism regulation, a key factor in fetal growth. We identified a marked association of the mean methylation levels of MEG3-DMR and SGA, and insulin may mediate this association. The findings offer novel insights into the epigenetic mechanisms linking DNA methylation patterns with adverse gestational consequences. This research has potential implications for improving the management of SGA risk.