孕期PM2.5和热浪暴露对SGA和追赶生长影响的交互作用及其机制研究

气候变化和空气污染共同威胁公众健康。孕妇是脆弱人群，孕期PM2.5和热浪暴露可导致胎儿表观遗传改变并持续至出生后，从而连续影响小于胎龄儿（SGA）的发生和出生后追赶生长。但复合暴露是否存在交互作用及作用机制尚不清楚。印记基因DLK1-MEG3可通过调控糖代谢影响胎儿生长发育。我们近期研究发现，孕期PM2.5和高温暴露可增加SGA风险，影响糖稳态。因此，本研究建立假设：PM2.5/热浪→DLK1-MEG3→糖稳态→SGA及追赶生长。首先开展人群研究，基于已建立的孕妇队列继续随访儿童0-2岁生长发育，阐明研究假设路径中的暴露-反应关系链，解析PM2.5和热浪的独立和交互效应。再结合动物实验，通过PM2.5和热浪暴露析因设计，阐明暴露-反应过程中DLK1-MEG3甲基化调控糖代谢的机制。研究结果可为探讨生命早期大气危害因素暴露的近远期健康影响提供新思路和干预靶点，为气象和环境部门制定措施提供依据

Climate change and air pollution are threatening public health. Pregnant women are especially vulnerable to these exposures. Prenatal exposure to particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM2.5) or heatwave may increase the risk of small for gestational age (SGA). It’s observed that 85%-90% of SGA would be followed by rapid infant weight gain within two years (i.e., catch-up growth). However, if PM2.5 could interact with heatwave to affect the risk of SGA and catch-up growth, and the underlying mechanisms for this causal chain are still unclear. Imprinted gene, delta-like homolog 1-maternally expressed gene 3 (DLK1-MEG3), plays key roles in fetal growth by regulating glucose metabolism. Our previous studies observed that PM2.5 or high-temperature exposure during pregnancy was associated with SGA, and PM2.5 exposure could affect glucose metabolism. Therefore, we hypothesize that PM2.5 or heatwave exposure during pregnancy could change the DLK1-MEG3 methylation level. The epigenetic change could program the glucose metabolism phenotype (e.g., developing insulin resistance) and finally lead to SGA and catch-up growth..To clarify the interaction of PM2.5 and heatwave exposures during pregnancy on SGA and catch-up growth, and to explore the underlying mechanisms, we will conduct an epidemiological study and animal experiments. .We will conduct the epidemiological study by enrolling 1200 SGA and 1200 appropriate for gestational age (AGA) newborns from our birth cohort in Guangzhou and follow them up to two years. Height and weight at birth, 0.5, 1.0, 1.5, and 2.0 years will be collected, and Z-scores will be calculated as the indicator of catch-up growth. Weekly ambient PM2.5 and heatwave exposure during pregnancy will be calculated by spatiotemporal land-use regression combined with time-activities. Distributed lag nonlinear model using Logistic regression will be used to estimate the effects of PM2.5 and heatwave on SGA and catch-up growth, and also to identify the critical exposure window at a weekly level. The additive interaction between PM2.5 and heatwave will be examined. Moreover, we will detect the methylation level of DLK1-MEG3 at two different methylation regions: IG-DMR and MEG3-DMR at umbilical cord blood. Also, the fasting glucose and insulin levels at birth, 1.0 and 2.0 years will be repeatedly measured. The structural equation model will be applied to confirm the role of DLK1-MEG3 methylation, glucose metabolisms in the relationships of PM2.5, heatwave exposure with SGA and catch-up growth..Animal experiments will be conducted using Wistar rat model. The pregnant rats will be classified into four groups, including (1) PM2.5 and heatwave co-exposure group; (2) only PM2.5 exposure group; (3) only heatwave exposure group and (4) control group. All pups will be weighed twice a week from postnatal day 1 (PD1) until PD42. At PD42 all pups fasted overnight will be sacrificed to obtain plasma samples, and tissues of the pancreas, retroperitoneal adipose and skeletal muscle. We will measure plasma glucose and insulin levels and DLK1-MEG3 methylation of all tissues. DLK1 and GLUT4 mRNA and protein levels in retroperitoneal adipose and skeletal muscle, as well as MEG3 LncRNA, MafA mRNA and protein level in pancreas, will also be detected. Therefore, we will be able to exam the effects of DLK1-MEG3 methylation on glucose metabolisms by regulating DLK1/GLUT4 and MEG3/MafA signal pathways. .The project will add evidence to understand the effects of climate change and air pollution on adverse birth outcomes, growth and development during childhood, as well as the underlying mechanisms. The findings will provide new ideas and intervention targets for exploring the health effects of early-life exposure, and can help policymakers to establish measures to reduce the adverse health effects of air pollution and climate change.