Gómez-Vilarrubla Ariadna, Niubó-Pallàs Maria, Mas-Parés Berta, Bonmatí-Santané Alexandra, Martínez-Calcerrada Jose-Maria, López Beatriz, Peñas-Cruz Aaron, de Zegher Francis, Ibáñez Lourdes, López-Bermejo Abel, Bassols Judit
Maternal-Fetal Metabolic Research Group, Girona Institute for Biomedical Research (IDIBGI), 17190 Salt, Spain.
Pediatric Endocrinology Research Group, Girona Institute for Biomedical Research (IDIBGI), 17190 Salt, Spain.
Int J Mol Sci. 2025 Mar 28;26(7):3141. doi: 10.3390/ijms26073141.
Accumulating evidence suggests that the predisposition to metabolic diseases is established in utero through epigenomic modifications. However, it remains unclear whether childhood obesity results from preexisting epigenomic alterations or whether obesity itself induces changes in the epigenome. This study aimed to identify DNA methylation marks in the placenta associated with obesity-related outcomes in children at age 6 and to assess these marks in blood samples at age 6 and whether they correlate with obesity-related outcomes at that time. Using an epigenome-wide DNA methylation microarray on 24 placental samples, we identified differentially methylated CpGs (DMCs) associated with offspring BMI-SDS at 6 years. Individual DMCs were validated in 147 additional placental and leukocyte samples from children at 6 years of age. The methylation and/or gene expression of in both placenta and offspring leukocytes were significantly associated with various metabolic risk parameters at age 6 (all ≤ 0.05). Logistic regression models (LRM) and machine learning (ML) models indicated that methylation in the placenta could strongly predict offspring obesity. Our results suggest that may serve as a potential biomarker for the prediction of obesity and metabolic risk in children.
越来越多的证据表明，代谢性疾病的易感性在子宫内通过表观基因组修饰而确立。然而，儿童肥胖是源于先前存在的表观基因组改变，还是肥胖本身会诱发表观基因组的变化，目前仍不清楚。本研究旨在确定与6岁儿童肥胖相关结局相关的胎盘中的DNA甲基化标记，并评估6岁时血液样本中的这些标记，以及它们是否与当时的肥胖相关结局相关。我们对24份胎盘样本进行了全表观基因组DNA甲基化微阵列分析，确定了与6岁时后代BMI-SDS相关的差异甲基化CpG（DMC）。在另外147份6岁儿童的胎盘和白细胞样本中对单个DMC进行了验证。胎盘和后代白细胞中的甲基化和/或基因表达均与6岁时的各种代谢风险参数显著相关（所有P≤0.05）。逻辑回归模型（LRM）和机器学习（ML）模型表明，胎盘中的甲基化可有力预测后代肥胖。我们的结果表明，可能作为预测儿童肥胖和代谢风险的潜在生物标志物。
