To the Editor: Obesity characterized with excess accumulation of white adipose tissue increases the prevalence of gestational diabetes mellitus (GDM). Exposure to intrauterine hyperglycemia increases the long-term sequelae including cardiovascular abnormalities and metabolic syndrome in adult offspring.[1] As early as two decades ago, Dr. David Barker provided evidence that nutritional exposures in utero has a lasting impact on offspring's health status in adulthood.[2] This emphasizes the critical role of early intrauterine environmental exposures and highlights the potential origins of adult metabolic diseases. Conventional strategies for the management of obesity during pregnancy such as diet modifications are often insufficient. Our previous study provided evidence that exposure to exercise intervention during pregnancy improves pregnancy outcomes in overweight and obese pregnant women.[3] The underlying mechanism by which environmental influences affect the offspring is still obscure. Epigenetic modifications have been proposed to be a potential mechanism, thereby contributing to our understanding of long-term influences of in utero exposure. DNA methylation is one of the major epigenetic modifications. CpG dinucleotide (5-methyl cytosine followed by guanosine) is the dominant type of methylation in mammals and CpG dinucleotides are usually clustered (also known as CpG islands) in the promoter regions of genes, which thereby regulate gene expression by interfering transcription factors access to DNA template. We here illustrate the role of epigenetic modifications in umbilical cord blood of offspring in response to intrauterine exposures induced by exercise training. The detailed materials and methods, https://links.lww.com/CM9/B114 provided as online materials. Dynamic alterations of DNA methylation profiles during pregnancy in maternal blood: Twelve participants from the exercise group and the control group were recruited for the DNA methylation array analysis. At first, we evaluated if DNA methylation levels were altered through pregnancy in maternal blood. In order to illustrate the DNA methylation alterations in different trimesters, we categorized DNA methylation changes in 1st, 2nd, and 3rd trimesters to four groups according to the trend. Thus, we detected four patterns of DNA methylation profiles (0. 1. –1; 0. 1. 1; 0. –1. 1; 0. –1. –1) in either control participants [Figure 1A]. The significant trend of DMPs were defined as significant change for 2ndvs. 1st trimester (P < 0.05) and also significant change for 3rdvs. 2nd trimester (P < 0.05).Figure 1: Maternal exercise alters gene-specific DNA methylation levels in maternal blood and cord blood. (A) In order to illustrate the DNA methylation alterations in different trimesters, we categorized DNA methylation changes during the pregnancy to four groups according the trend. We defined DNA methylation baseline level of 1st trimester as “0”, DNA methylation level increase between trimesters as “1” and DNA methylation level decrease between trimesters as “–1”. There will be four trends of DNA methylation profiles (0, 1, –1; 0, 1, 1; 0, –1, 1; 0, –1, –1) in control participants. Red lines stand for significant changes of differentially methylated positions (DMPs) (P < 0.05) and grey lines stand for non-significant changes. (B) The numbers of altered DMPs in control group were shown. The significant DMPs in four individual trends were defined as significant change for 2nd vs. 1st trimester (P < 0.05) and also significant change for 3rd vs. 2nd trimester (P < 0.05). Among them, there were 2562, 2, 2014, 1 significant DMPs in control group for 0. 1. –1, 0. 1. 1, 0. –1. 1 and 0. –1. –1 trends, respectively. (C) DNA methylation levels of specific genes were altered by exercise in maternal blood. We examined the DMPs in control and exercise groups with opposite trends of 0. –1. 1 and 0. 1. –1. Three CpG sites were shown significantly differential trends in control (0. –1. 1) and exercise (0. 1. –1) groups in maternal blood. Six CpG sites were demonstrated in opposite trends 0. 1. –1 and 0. –1. 1 during pregnancy. (D) The heatmap showed DNA methylation comparisons between control and exercise groups in cord blood. (E) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway demonstrated that “aldosterone synthesis and secretion” was the significant pathway enrichment comparing exercise and control groups in cord blood.There were 2562 DMPs were significantly altered in 0. 1. −1 pattern (P < 0.05). Similarly, for 0. –1. 1 trend, we found 2014 DMPs were significantly changed (P < 0.05) [Figure 1B]. Interestingly, there were fewer DMPs for 0. 1. 1 and 0. –1. –1 trends [Figure 1A and 1B]. Only two significant DMPs (cg13769674, cg08530065) for 0. 1. 1 trend and one DMP (cg08586855) for 0. –1. –1 trend were identified, respectively [Figure 1B]. DNA methylation levels of specific genes were altered by exercise in maternal blood: We next examined the DMPs with opposite trends in control and exercise groups in order to determine whether exercise training affects the DNA methylation trends in maternal blood. We compared the significant DMPs between control and exercise groups with four opposite trend combinations (trends 0. –1. 1 and 0. 1. –1; trends 0. 1. –1 and 0. –1. 1; trends 0. 1. 1 and 0. –1. –1; trends 0. –1. –1 and 0. 1. 1, respectively). There were no significant CpG sites identified in the latter two opposite trend combinations (trends 0. 1. 1 and 0. –1. –1; trends 0. –1. –1 and 0. 1. 1). Three CpG sites and corresponding genes UMAD1 (UBAP1-MVB12-associated (UMA) domain containing 1, cg12309238), RPA3 (replication protein A3, cg12309238), PLAGL2 (PLAG1 like zinc finger 2, cg25811820) and POFUT1 (protein O-fucosyltransferase 1, cg25811820) showed significantly differential trends in control (0. –1. 1) and exercise (0. 1. –1) groups in maternal blood [Figure 1C]. Six CpG sites and corresponding genes including SPATA17 (spermatogenesis associated 17, cg17026642), GPATCH2 (G-patch domain containing 2, cg17026642), CEP170 (centrosomal protein 170, cg08258520), MPHOSPH10 (M-phase phosphoprotein 10, cg20854010), MCEE (methylmalonyl-CoA epimerase, cg20854010) as well as MRGPRD (MAS related GPR family member D, cg11903239) demonstrated opposite trends 0. 1. –1 (control) and 0. –1. 1 (exercise) during pregnancy [Figure 1C]. Maternal exercise alters gene-specific DNA methylation levels in cord blood: The methylation microarray data showed that five specific CpG sites cg02878244, cg02819231, cg02505749, cg11660360, cg03084276 were significantly differentially methylated in the exercise group compared the control group in cord blood [Figure 1D]. These CpG sites were located within the CpG islands of Transcription Start Site of four specific genes including developing brain homeobox 1, F-box and leucine rich repeat protein 2, potassium two pore domain channel subfamily K member 9 and prostaglandin reductase 1 [Supplementary Figure 1, https://links.lww.com/CM9/B114]. KEGG pathway analysis revealed that “aldosterone synthesis and secretion” was the most significant pathway enrichment in cord blood from the exercise versus the control groups [Figure 1E]. DNA methylation is thought to be mitotically stable, with environmental events and nutritional conditions after birth unlikely to alter DNA methylation changes in adult tissues. Nevertheless, our study provides evidence that DNA methylation could be dynamically altered during pregnancy, as well as in response to exercise training, in maternal blood. Interestingly, there were few significant CpG sites showing increasing or decreasing trends during the whole pregnancy. The majority CpG sites have two patterns of DNA methylation waves, either firstly increasing from the first to second trimester and then decreasing from the second to third trimester, or vice versa. Exercise induced significant DNA methylation alterations of specific CpG sites and corresponding genes. Among these genes, MRGPRD was reported to play an important role in protecting osteocytes and preventing bone loss through preventing mitochondrial breakdown in osteocytes.[4] In the current study, we demonstrated dynamic, opposing alterations of DNA methylation levels of MRGPRD in maternal blood induced by exercise. This provided evidence that exercise might trigger functional changes in critical factors by regulating gene expression through DNA methylation mechanism. Our previous study reported differentially methylated genes in neonates exposed to the intrauterine hyperglycemia using the array-based method.[5] The current study further illustrated the DNA methylation alterations could be induced by maternal nutritional and metabolic status triggered by exercise. KEGG pathway showed that “aldosterone synthesis and secretion” was the most significant pathway enrichment in cord blood comparing exercise and control groups. Aldosterone is a steroid hormone synthesized in and secreted from the outer layer of the adrenal cortex. Aldosterone plays an important role in the regulation of systemic blood pressure through the absorption of sodium and water. Notably, the glucose and lipid profiles were unaltered between the exercise intervention and control groups in the current study. Nevertheless, the exercise intervention decreased weight gain in the first half of gestation. The importance of intensity, duration and frequency of exercise in a critical window of pregnancy needs to be emphasized, which may affect DNA methylation marks of offspring. This question warrants further studies since intensity, duration and frequency are important components of exercise prescription as well as weight management through exercise in gestational diabetes mellitus management. Environmental factors have a dynamic effect on the level of DNA methylation in the promoter regions of key genes. Our data provide a picture of the dynamic alterations of DNA methylation during pregnancy in maternal blood, as well as the effect of exercise on fetal DNA methylation profiles. Future studies are needed to reveal the functional verification of the DNA methylation and underlying regulatory mechanism. Funding This study was supported by the National Key Research and Development Program of China (No. 2021YFC2700700), the National Natural Science Foundation of China under grant (Nos. 81830044, 81801471), the Beijing Natural Science Foundation under grant (Nos. 7192206), Peking University First Hospital Medicine Fund of Fostering Young Scholars under grant (No. 2021CR01).