Exercise intervention during pregnancy induces promoter methylation alterations in cord blood

Exercise intervention during pregnancy induces promoter methylation alterations in cord blood | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Exercise intervention during pregnancy induces promoter methylation alterations in cord blood Jie Yan, Chen Wang, Yumei Wei, Huixia Yang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.2.23114/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Environmental events and nutritional conditions may induce permanent DNA methylation changes in utero during the sensitive period and these adaptive changes may be ‘memorized’ and have a lasting impact on adult disease later in life. The potential plasticity of DNA methylation also enables reprogramming, depending on exposure to nutritional, chemical, and environmental factors. We determined the effects of exercise training during pregnancy on epigenetic modifications in offspring. Results: Twenty-four subjects were chosen from a previous clinical study. Overweight/obese pregnant women (body mass index <28/≥28kg/m 2 ) who had an uncomplicated pregnancy at <12 +6 weeks of gestation were randomly allocated to either an exercise or a control group. Patients allocated to the exercise group performed 3 exercise bouts per week (at least 30 min/session with a rating of perceived exertion between 12-14) via a cycling program that was initiated within 3 days of randomization until 37 weeks of gestation. Patients allocated to the control group continued their usual daily activities. Maternal blood, as well as umbilical cord blood samples, were collected and DNA methylation levels were determined by Illumina MethylationEPIC microarray. Nine CpG sites and corresponding genes UMAD1 , RPA3 , PLAGL2 , POFUT1 , SPATA17 , GPATCH2 , CEP170 , MPHOSPH10 , MCEE , as well as MRGPRD showed differential trends in control and exercise groups in maternal blood. Furthermore, four specific genes in umbilical cord blood were differentially methylated in the exercise group compared to the sedentary controls (p < 0.01). Conclusions: DNA methylation in maternal blood is dynamically altered during pregnancy and remodeled by exercise training. Thus, intrauterine environmental exposures play an important role in fetal programming. Epigenetic mechanisms involving changes in DNA methylation may provide an explanation for the phenomenon. Our findings shed light on understanding of long-term effects of in utero exposures on the epigenetic landscape of the offspring. Epigenetics & Genomics DNA methylation obesity exercise cord blood Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background 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 – 3 ]. 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 [ 4 ]. 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. Exercise has long been considered to improve insulin sensitivity and as an adjuvant therapy in the management of Type 2 diabetes in non-pregnant subjects. Type 2 diabetes and GDM share the similarity of insulin resistance and thus exercise therapy may also applied to the GDM population. The International Federation of Gynecology and Obstetrics (FIGO) recommends appropriate, personally adapted, physical activity for all women with gestational diabetes mellitus. Our previous study provided evidence that exposure to exercise intervention during pregnancy improves pregnancy outcomes in overweight and obese pregnant women [ 5 ]. 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 [ 6 – 8 ]. 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. DNA methylation is involved in imprinting, mammalian development, and genomic stability maintenance. A number of cell type-specific DNA methylation patterns are believed to be established in the embryonic stage and the potential plasticity of DNA methylation enables reprogramming, depending on exposures to environmental, nutritional and chemical factors. Intrauterine exposures may induce adaptive DNA methylation changes, through which the in utero exposures may have a lasting impact on future disease manifestation in adult life. We here illustrate the role of epigenetic modifications in umbilical cord blood of offspring in response to intrauterine exposures induced by exercise training. Research Design And Methods Study Participants and sample collection The study was approved by the Institutional Review Board of Peking University First Hospital. All studies were performed according to the declaration of Helsinki. Informed consent was obtained from all participants. We conducted a randomized clinical trial at Peking University First Hospital from December 2014 through July 2016. The study protocol was reported previously [ 5 ]. Briefly, the study recruited nonsmoking women age > 18 years with a singleton pregnancy who met the criteria for overweight/obese status (body mass index < 28/≥28 kg/m 2 ) and had an uncomplicated pregnancy at < 12 + 6 weeks of gestation. The women were randomly allocated to either exercise or a control group. Gestational age was assessed based on the last menstrual period and early ultrasound. Patients did not have contraindications to physical activity. Patients allocated to the exercise group performed exercise 3 times per week (at least 30 min/session with a rating of perceived exertion between 12–14) via a cycling program that was initiated within 3 days of randomization until 37 weeks of gestation. All the exercise sessions occurred at Peking University First Hospital under supervision. Patients assigned to the control group continued their usual daily activities. Both groups received standard prenatal care, albeit without special dietary recommendations. Blood was drawn from the antecubital vein after the participant had fasted for at least 8 hours, but not > 14 hours. Blood was collected in sterile vacutainer tubes preloaded with heparin. There was at least 24 hours between the last exercise bout and the time of blood draw. Blood was centrifuged at 1800 g at 4 °C for 10 minutes within 4 hours of collection; subsequently, the plasma was separated and glucose was measured immediately. The remaining plasma was stored at -80 °C for later analysis of insulin and lipid parameters (triglyceride, total cholesterol, and low- and high-density lipoprotein cholesterol). Insulin was measured using radioimmunoassay commercial kits (Beifang Institute of Biochemical Technology, Beijing, China). The insulin resistance index was calculated according to the homeostasis model of assessment: fasting plasma insulin (µU/mL) × fasting glucose (mmol/L)/22.5 [ 9 ]. Fasting lipid profiles were measured using an automatic analyzer (7600; Hitachi High-Technologies Corp, Tokyo, Japan) in the Department of Clinical Laboratory, Peking University First Hospital. Biochemical tests were repeated at 25 and 36 gestational weeks. Umbilical cord blood samples were obtained and immediately stored once the baby was delivered. Twelve participants from each group were recruited in the following DNA methylation array analysis. Clinical characteristics of participants and pregnancy outcomes were recorded and presented in Table 1. DNA methylation sample preparation DNA was extracted from 2 ml of whole blood from each sample using Blood DNA Midi Kit (Omega). The total amount of DNA was determined by spectrophotometry. The DNA samples were sent to the Beijing KPS Biotechnology Co., Ltd and stored at -20 °C. Quality check was performed by Nanodrop Spectrophotometer and resolution on a 0.8% agarose gel. Bisulfite convert the genomic DNA samples using the Zymo EZ DNA Methylation Kit (Zymo Research). Illumina MethylationEPIC microarray The EPIC platform has probes targeting 866,836 cytosine positions on the human genome, of which 863,904 (99.7%) are CpG dinucleotides and 2932 (0.3%) CNG targets. Additionally, there are 59 probes targeting SNP sites to allow sample matching and 636 probes for sample-dependent and sample-independent quality control. EPIC probes are principally located at promoters (54%), followed by gene bodies (30%) and then intergenic regions (16%), and 19% and 18% of all EPIC probes are located in CpG islands and CpG island shores, respectively. According to Illumina’s specification, DNA was hybridized to Illumina MethylationEPIC microarrays. Briefly, the bisulfite-converted DNA samples were denatured, neutralized and prepared for amplification after overnight incubation. Amplified DNA samples were enzymatically fragmented and precipitated. Subsequently, precipitated DNA samples were resuspended and dispensed onto BeadChips. BeadChips were incubated in the Illumina Hybridization Oven to hybridize the samples onto the BeadChips. The BeadChips were stained and scanned following the instructions. Data analysis was performed by R bioconductor package minfi [ 10 ] for methylation intensity calculation and limma [ 11 ] for differential analysis. Data processing For methylation analysis, IDAT files were loaded into the R (3.4.3) environment using the Bioconductor minfi package (1.26.2). Quality control was performed and CpG sites with detection p value < 0.05 were kept. Signals were then normalized using quantile method [ 12 ]. The level of DNA methylation at a particular CpG site (also called the methylation beta-value (β)) was calculated by taking the ratio of the methylated intensity (M) to unmethylated intensity (U) signal, using the formula: β = M/(M + U). A β-value of 0 represents a completely unmethylated CpG site and a β-value approaching 1 represents a fully methylated CpG site. Probes on sex chromosomes were removed, as well as those identified as cross-hybridizing with other genomic locations or SNP-associated [ 13 ]. A set of 683,126 probes was obtained and used for exploratory and differential methylation analysis. Differential methylation analysis In order to assess differences in methylation between groups, the original β values were converted to M-values via the logit transformation. Differentially methylated probes were detected using the R bioconductor limma (3.36.3) package. Probes with adjusted p value < 0.05 were considered to be differentially methylated. The Benjamini–Hochberg method was used to adjust the p values and ensure that the false discovery rate was < 0.05. The corresponding gene list was derived from the gene annotations associated with the probes. Statistics Clinical results were statistically analyzed by SPSS 20.0. All values are presented as mean ± SD. Two-tailed unpaired Student’s t -test were performed. Regarding differential methylation analysis, probes with adjusted p value < 0.05 were considered to be differentially methylated. The Benjamini–Hochberg method was used to adjust the p values and ensure that the false discovery rate was < 0.05. Results Twelve participants from the exercise group and the control group were recruited for the DNA methylation array analysis (Fig. 1 ). There were no significant differences of age, weight, height, prepregnancy body mass index, gestational age and fasting plasma glucose at study entry between exercise and control groups (Table 1). The exercise intervention increased moderate exercise levels at 25 and 36 gestational weeks (p < 0.05). No vigorous exercise was reported in participants. There was no difference in walking amount and total exercise load between two groups (Table 2 ). The exercise intervention group gained less weight from study entry to 25 + 6 weeks of gestation compared to the control group (p < 0.05). No difference of weight gain in the later stage of gestation (26 + 1 weeks to 36 + 6 weeks) was reported in the current study. The participants in exercise and control groups had the equal homeostatic model assessment for insulin resistance (HOMA-IR), triglyceride, total cholesterol, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) profiles (Supplementary Table). Dynamic alterations of DNA methylation profiles during pregnancy in maternal blood In order to illustrate the DNA methylation alterations in different trimesters in maternal blood, we categorized DNA methylation changes in 1st, 2nd and 3rd trimesters to four groups according to 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”. Thus, we detected four patterns of DNA methylation profiles (0. 1. -1; 0. 1. 1; 0. -1. 1; 0. -1. -1) in either control or exercise participants (Fig. 2 A, Fig. 2 B). Red lines indicate significant changes of differentially methylated positions (DMPs) (p < 0.05) and grey lines indicate non-significant changes (Fig. 2 A, Fig. 2 B). There were 26573 DMPs in the control group and 15913 DMPs in the exercise group for 0. 1. -1 trend (Fig. 2 C). DMPs were defined as both a significant change for 2nd vs. 1st trimester (p < 0.05) and also a significant change for 3rd vs. 2nd trimester (p < 0.05). Among them, 2562 DMPs in control group and 1345 DMPs in exercise group were significantly altered in 0. 1. -1 pattern (Fig. 2 C). Similarly, for 0. -1. 1 trend, we found 35363 DMPs (2014 significant DMPs) in the control group and 14635 DMPs (1076 significant DMPs) in the exercise group respectively (Fig. 2 C). Interestingly, there were fewer DMPs for 0. 1. 1 and 0. -1. -1 trends both in control and exercise groups (Fig. 2 A, Fig. 2 B). Only two significant DMPs (cg13769674, cg08530065) in the control and one significant DMP (cg04260608) in the exercise-trained group for 0. 1. 1 trend were identified. Similarly, one DMP (cg08586855) and two DMPs (cg12394567, cg02033213) were found for 0. -1. -1 trend in control and exercise groups, respectively (Fig. 2 C). Differentially methylated regions (DMRs) are genomic regions with different DNA methylation status across the biological samples and regarded as possible functional regions involved in gene transcriptional regulation. Compared to 1st trimester in maternal blood, 17781 DMRs were revealed in 2nd trimester in the control group, among which 1293 DMRs were located in promoters. 6565 DMRs were identified in the exercise group and 615 DMRs were located in promoters. 4530 DMRs and 3145 DMRs were found in 3rd trimester compared to 2nd trimester in control and exercise groups, respectively. 477 DMRs and 280 DMRs were located in promoters accordingly (Fig. 3 A). 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 (Fig. 4 ). 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 (Fig. 4 ). The global DNA methylation profile of cord blood is different from that of maternal blood Next, we compared the DNA methylation profiles in maternal blood and cord blood. We studied the epigenome-wide variation in DNA methylation with principal component analysis (PCA), which shows that the leading axis of epigenomic variation reflects the tissue type (Fig. 5 A). Dots represent blood samples and are colored accordingly. The heatmaps show DNA methylation comparisons between cord blood and maternal blood in different trimesters (Fig. 5 B, Fig. 5 C, Fig. 5 D). The differential genes of maternal and cord blood were then grouped into three categories using Gene Ontology (GO) system: biological process (describing the larger cellular or physiological role carried out by the gene, coordinated with other genes) and cellular component (describing the location in the cell where the gene product executes its function) and molecular function (describing the molecular activity of a gene) (Fig. 5 E). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway demonstrated that “metabolic pathways” was the most significant pathway enrichment in differential genes comparing maternal and cord blood (Fig. 5 F). The corresponding proteins of differential genes of maternal and cord blood were analyzed using protein-protein interactions (PPIs) network, whereby the physical contacts of high specificity is established between potential protein molecules (Fig. 5 G). Compared to 3rd trimester in maternal blood, 82676 DMRs were demonstrated in cord blood in control, among which 9464 DMRs were located in promoters. 78318 DMRs were identified in the exercise group and 9130 DMRs were located in promoters (Fig. 3 B). 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 (Fig. 6 A). These CpG sites were located within the CpG islands of Transcription Start Site (TSS) of four specific genes including developing brain homeobox 1 ( DBX1 ), F-box and leucine rich repeat protein 2 ( FBXL2 ), potassium two pore domain channel subfamily K member 9 ( KCNK9 ) and prostaglandin reductase 1 ( PTGR1 ) (Fig. 6 C). 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 (Fig. 6 B). Discussion The general pattern of DNA methylation in human fetal germ cells during development has been comprehensively analyzed [ 14 ]. Nevertheless, the patterns of DNA methylation during pregnancy, as well as DNA methylation of the neonate, have not been established. 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 [ 15 ]. 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. Additionally, more differential DMRs were found in the early half of the pregnancy. Previous study demonstrated that acute gene activation induced by a bout of exercise is associated with a rapid change in DNA methylation in another adult somatic tissue, skeletal muscle [ 16 ]. Specifically, exercise triggered marked hypomethylation on respective promoter of peroxisome proliferator-activated receptor gamma, coactivator 1 a (PGC1α) , pyruvate dehydrogenase kinase , isoenzyme 4 ( PDK4 ) and peroxisome proliferator-activated receptor δ ( PPAR-δ ), genes playing important roles in cell metabolism [ 16 ]. In the current study, we reported dynamic changes in maternal blood in response to exercise training. In contrast to skeletal muscle biopsies, blood samples are relatively easy to obtain from pregnant woman. Thus we are unable to determine whether exercise training elicited effect on DNA methylation in skeletal muscle of pregnant women. In a previous study, DNA methylation alterations were demonstrated immediately after an acute bout of exercise, revealing an exercise intensity-dependent response. The current study showed DNA methylation changes based on a moderate physical activity level over a relatively longer period. Exercise induced significant DNA methylation alterations of specific CpG sites and corresponding genes including UMAD1 (cg12309238), RPA3 (cg12309238), PLAGL2 (cg25811820) and POFUT1 (cg25811820), SPATA17 (cg17026642), GPATCH2 (cg17026642), CEP170 (cg08258520), MPHOSPH10 (cg20854010), MCEE (cg20854010) as well as MRGPRD (cg11903239). Among these genes, MRGPRD was reported to play an important role in protecting osteocytes and preventing bone loss through preventing mitochondrial breakdown in osteocytes [ 17 ]. 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 study provided evidence that metabolic pathways markedly differ between maternal blood and umbilical cord blood. This finding raises an issue related to tissue specificity when using cord blood. Umbilical cord blood, like adult blood, is a heterogeneous tissue (e.g. monocytes neutrophils, eosinophils, basophils, B cells, NK cells, and T cells). The proportions of cells with nuclei fluctuate greatly throughout fetal development and may vary significantly depending on the gestational age [ 18 ]. DNA methylation levels are affected by cell type proportion fluctuation across gestational age. It has been shown blood cell type methylation markers were segregated into two clusters by gestational age. The two clusters of DNA methylation measurement were characterized by proportions of granulocytes, lymphocytes, and B cells in cord blood, which were determined by gestational age [ 19 ]. Therefore, the cell type proportion differences partially contribute to the DNA methylation variations in maternal blood and cord blood. Our previous study reported differentially methylated genes in neonates exposed to the intrauterine hyperglycemia using the array-based method [ 20 ]. Altered DNA methylation levels of Rho guanine nucleotide exchange factor 11 ( ARHGEF11 ) were negatively correlated with glucose levels and neonatal birth weight, which emphasized the potential influence of intrauterine environment and maternal nutrition status on DNA methylation. 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. Our study sheds light on the potential metabolic disease pathogenesis in offspring, which might be related to the maternal life style during pregnancy. Previous studies demonstrated that caffeine mimics exercise-induced expression of genes related to mitochondrial function in L6 myotubes [ 21 ]. Moreover, a time-course study of caffeine exposure of L6 myotubes suggests that exercise mimetics may trigger promoter hypomethylation of specific genes [ 16 ]. Nevertheless, the mechanism by which maternal exercise alters the intrauterine environment and concomitantly influences the fetal DNA methylation establishment remains unknown. 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. The effectiveness and modality of physical activity during pregnancy in prevention of gestational diabetes mellitus, as well as the underlying mechanism is still obscure. DNA methylation appears to sense environmental changes, regulates gene expression, and prepares the body to respond to changes in the milieu. Environmental factors have a dynamic effect on the level of DNA methylation in the promoter regions of key genes. Our data provide a comprehensive 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. Changes in DNA methylation may be an early event in reprogramming the metabolic profile in human somatic tissues, as well as cord blood. Our results provides evidence for implementing exercise intervention strategies for disease management in order to modify epigenetic marks. Declarations Ethics approval and consent to participate The study was approved by the Institutional Review Board of Peking University First Hospital (reference numbers: 2014[726], 2019[45]). All studies were performed according to the declaration of Helsinki. Informed consent was obtained from all participants. Consent for publication Not applicable. Availability of data and materials The datasets used and analyzed during the current study are available from the corresponding author. Competing interests The authors declare no conflicts of interest. Funding This work was supported by the National Natural Science Foundation of China [grant numbers 81401215, 81830044, 81801471], the Beijing Natural Science Foundation [grant numbers 7192206], Beijing Talents Foundation from organization department of Beijing municipal committee of the CPC [grant number 2016000021223ZK20], Peking University Medicine Fund of Fostering Young Scholars’ Scientific & Technological Innovation and the Fundamental Research Funds for the Central Universities [grant number BMU2018PY002]. Authors' contributions JY and HY designed research; CW and YW conducted the exercise intervention; JY and CW processed samples; JY and HY wrote the paper; HY had primary responsibility for final content. HY is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. All authors read and approved the final manuscript. Acknowledgements Not applicable. 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Baseline characteristics of participants Characteristics Exercise group n=12 Control group n=12 p Age, y 32.92 ± 1.93 31.92 ± 4.40 0.48 Weight, kg 70.47 ± 7.56 70.46 ± 10.62 1.00 Height, cm 162.92 ± 5.21 162.17 ± 7.53 0.78 p-BMI, kg/m 2 26.61 ± 3.22 26.68 ± 2.35 0.95 Gestational age, wk 9 ± 2 10 ± 2 0.46 Fasting plasma glucose at study entry, mmol/L 4.88 ± 0.41 4.86 ± 0.48 0.91 Data presented as mean ± SD; p-BMI, prepregnancy body mass index. Table 2. Physical activity levels in overweight and obese pregnant women randomized to exercise intervention or control groups Exercise group n=12 Control group n=12 p Vigorous exercise, metabolic equivalents of task min/wk At study entry 0 0 At 25 wk gestation 0 0 At 36 wk gestation 0 0 Moderate exercise, metabolic equivalents of task min/wk At study entry 15 ± 52 3 ± 9 0.42 At 25 wk gestation 151 ± 103 8 ± 22 < 0.0005 At 36 wk gestation 92 ± 49 9 ± 23 < 0.005 Walking, metabolic equivalents of task min/wk At study entry 617 ± 616 494 ± 485 0.59 At 25 wk gestation 435 ± 202 664 ± 627 0.26 At 36 wk gestation 465 ± 397 381 ± 331 0.68 Total, metabolic equivalents of task min/wk At study entry 632 ± 613 496 ± 485 0.55 At 25 wk gestation 586 ± 273 672 ± 632 0.68 At 36 wk gestation 557 ± 427 390 ± 323 0.43 Supplementary Files OnlineSupplementalMaterials.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-13685","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research","associatedPublications":[],"authors":[{"id":339491,"identity":"51ccb0f4-297b-47ac-b028-827ec1dad563","order_by":1,"name":"Jie Yan","email":"","orcid":"","institution":"Peking University First Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Yan","suffix":""},{"id":339492,"identity":"6f49b12e-3397-446d-bef0-33b0f320ae12","order_by":2,"name":"Chen Wang","email":"","orcid":"","institution":"Peking University First Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Chen","middleName":"","lastName":"Wang","suffix":""},{"id":339493,"identity":"92015a73-e9dc-4d76-9470-4c1f51e16596","order_by":3,"name":"Yumei Wei","email":"","orcid":"","institution":"Peking University First Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yumei","middleName":"","lastName":"Wei","suffix":""},{"id":339494,"identity":"8edd7bce-f477-4544-a35b-175c3c358911","order_by":4,"name":"Huixia Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAElEQVRIie2RsUrEQBCGNyzMNb9nm+CR8xFGAmIRPB9lg5AqyJUWFpFAqjyAYuFbWO8RuGuiaQPXRGwtLt1VatIKbq602K9c5uNjdoSwWP4prEQImtxnrdqHOJ6kBymxP0W55q6IZ16hDwqVge/GynugMuTmaqSwedXL9lZGuUg4AGqIRji7LjEo1Y1iVVGvVPyBiy2cp1R6jy8GRSfMUY4od4qhsoWcaZJHJqX+7JUvN8ol+AT0BnLViNIMlZQDIhrW18CY4jV9Ra2VT5DDJ1/DxSoz7jKtk/Oz/d035s/vwykvF4tNttp1BuVUC+Jfb07693zPPBWyNU5YLBaL5Qcjb1NrYgQgvwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-6472-5770","institution":"Peking University First Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Huixia","middleName":"","lastName":"Yang","suffix":""}],"badges":[],"createdAt":"2020-02-07 16:39:58","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.2.23114/v1","doiUrl":"https://doi.org/10.21203/rs.2.23114/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":478526,"identity":"fb7caee1-0006-415a-8b2a-3298feeac304","added_by":"auto","created_at":"2020-02-11 16:11:09","extension":"tiff","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":18466,"visible":true,"origin":"","legend":"Exercise intervention illustration.\nThe study recruited nonsmoking women age \u003e18 years with a singleton pregnancy who met the criteria for overweight/obese status (body mass index \u003c28/≥28kg/m2) and had an uncomplicated pregnancy at \u003c12+6 weeks of gestation were randomly allocated to either exercise or a control group. Patients did not have contraindications to physical activity. Patients allocated to the exercise group were assigned to exercise 3 times per week (at least 30 min/session with a rating of perceived exertion between 12-14) via a cycling program begun within 3 days of randomization until 37 weeks of gestation. Those in the control group continued their usual daily activities.","description":"","filename":"figure1.tiff","url":"https://assets-eu.researchsquare.com/files/41367553-bc05-4c8c-9961-8cc588edc6c7/v1/figure 1.tiff"},{"id":478527,"identity":"8d4c32ef-7220-470e-bf44-35385d4e0c27","added_by":"auto","created_at":"2020-02-11 16:11:09","extension":"tiff","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":222076,"visible":true,"origin":"","legend":"Dynamic alterations of DNA methylation profiles in different trimesters.\n(A) (B) 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 either control or exercise participants. Red lines stand for significant changes of differentially methylated positions (DMPs) (p\u003c0.05) and grey lines stand for non-significant changes. \n(C) The numbers of altered DMPs in control group and exercise group were shown. The significant DMPs in four individual trends were defined as significant change for 2nd vs. 1st trimester (p\u003c0.05) and also significant change for 3rd vs. 2nd trimester (p\u003c0.05). 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. Similarly, there were 1345, 1, 1076, 2 significant DMPs in exercise group for 0. 1. -1, 0. 1. 1, 0. -1. 1 and 0. -1. -1 trends.","description":"","filename":"figure2.tiff","url":"https://assets-eu.researchsquare.com/files/41367553-bc05-4c8c-9961-8cc588edc6c7/v1/figure 2.tiff"},{"id":478528,"identity":"6805dd44-05ee-4aca-8bed-85feccdb1c03","added_by":"auto","created_at":"2020-02-11 16:11:09","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":90113,"visible":true,"origin":"","legend":"Dynamic alterations of DNA methylation profiles between different trimesters in maternal blood and between maternal and cord blood.\n(A) The numbers of DMRs were demonstrated. Compared to 1st trimester in maternal blood, total 17781 DMRs were revealed in 2nd trimester in control, among which 1293 DMRs were located in promoters (red bar), 16488 in non-promoters (blue bar). 6565 DMRs were identified in the exercise group and 615 DMRs were located in promoters (red bar), 5950 in non-promoters (blue bar). 4530 DMRs and 3145 DMRs were found in 3rd trimester compared to 2nd trimester in control and exercise groups, respectively. 477 DMRs and 280 DMRs were located in promoters accordingly (red bar). \n(B) The numbers of DMRs were demonstrated. Compared to 3rd trimester in maternal blood, 82676 DMRs were demonstrated in cord blood in control, among which 9464 DMRs were located in promoters (red bar). 78318 DMRs were identified in the exercise group and 9130 DMRs were located in promoters (red bar).","description":"","filename":"Picture3.png","url":"https://assets-eu.researchsquare.com/files/41367553-bc05-4c8c-9961-8cc588edc6c7/v1/Picture3.png"},{"id":478529,"identity":"408b25cf-37a5-4543-b585-1cfd93d8cc99","added_by":"auto","created_at":"2020-02-11 16:11:09","extension":"tiff","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":43190,"visible":true,"origin":"","legend":"DNA methylation levels of specific genes were altered by exercise in maternal blood.\nWe 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”. \n(A) 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.\n(B) Six CpG sites were demonstrated in opposite trends 0. 1. -1 and 0. -1. 1 during pregnancy.","description":"","filename":"figure4.tiff","url":"https://assets-eu.researchsquare.com/files/41367553-bc05-4c8c-9961-8cc588edc6c7/v1/figure 4.tiff"},{"id":478530,"identity":"364607a0-dd75-4665-b9f5-7a57894c6325","added_by":"auto","created_at":"2020-02-11 16:11:09","extension":"tiff","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":692612,"visible":true,"origin":"","legend":"The global DNA methylation profile of cord blood is different from that of maternal blood.\n(A) The epigenome-wide variation in DNA methylation with principal component analysis (PCA) shows that the leading axis of epigenomic variation reflects the tissue type. Dots represent blood samples and are colored accordingly.\n(B)(C)(D) The heatmaps showed DNA methylation comparisons between cord blood and maternal blood in different trimesters. \n(E) The differential genes of maternal and cord blood were then grouped into three categories using Gene Ontology (GO) system: biological process (describing the larger cellular or physiological role carried out by the gene, coordinated with other genes) and cellular component (describing the location in the cell where the gene product executes its function) and molecular function (describing the molecular activity of a gene).\n(F) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway demonstrated that “metabolic pathways” was the most significant pathway enrichment in differential genes comparing maternal and cord blood.\n(G) The corresponding proteins of differential genes of maternal and cord blood were analyzed using protein-protein interactions (PPIs) network, by which the physical contacts of high specificity established between potential protein molecules.","description":"","filename":"figure5.tiff","url":"https://assets-eu.researchsquare.com/files/41367553-bc05-4c8c-9961-8cc588edc6c7/v1/figure 5.tiff"},{"id":478531,"identity":"19053f12-a7d6-4963-ac7b-7a4b34b034fd","added_by":"auto","created_at":"2020-02-11 16:11:09","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":236345,"visible":true,"origin":"","legend":"Maternal exercise alters gene-specific DNA methylation levels in cord blood.\n(A) The heatmap showed DNA methylation comparisons between control and exercise groups in cord blood.\n(B) KEGG pathway demonstrated that “aldosterone synthesis and secretion” was the significant pathway enrichment comparing exercise and control groups in cord blood.\n(C) DNA methylation levels of specific genes. Four specific genes developing brain homeobox 1 (DBX1), F-box and leucine rich repeat protein 2 (FBXL2), potassium two pore domain channel subfamily K member 9 (KCNK9) and prostaglandin reductase 1 (PTGR1). The control group was represented in blue and exercise group was in red. It only showed the relative positions of CpG sites and specific CpG sites within islands. * indicated significant levels of p\u003c0.05.","description":"","filename":"Picture6.png","url":"https://assets-eu.researchsquare.com/files/41367553-bc05-4c8c-9961-8cc588edc6c7/v1/Picture6.png"},{"id":13488605,"identity":"6b678173-2934-475d-b95b-e27535ec4447","added_by":"auto","created_at":"2021-09-16 22:15:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1992539,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-13685/v1/3a79ace0-67d6-4267-b605-dbfee0bbb528.pdf"},{"id":478525,"identity":"2eeef573-08ed-4e5b-8f97-f65554757aa2","added_by":"auto","created_at":"2020-02-11 16:11:09","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":16563,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineSupplementalMaterials.docx","url":"https://assets-eu.researchsquare.com/files/41367553-bc05-4c8c-9961-8cc588edc6c7/v1/Online Supplemental Materials.docx"}],"financialInterests":"","formattedTitle":"Exercise intervention during pregnancy induces promoter methylation alterations in cord blood","fulltext":[{"header":"Background","content":" \u003cp\u003eObesity 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 [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. As early as two decades ago, Dr. David Barker provided evidence that nutritional exposures \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003ein utero\u003c/span\u003e has a lasting impact on offspring\u0026rsquo;s health status in adulthood [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. This emphasizes the critical role of early intrauterine environmental exposures and highlights the potential origins of adult metabolic diseases.\u003c/p\u003e \u003cp\u003eConventional strategies for the management of obesity during pregnancy such as diet modifications are often insufficient. Exercise has long been considered to improve insulin sensitivity and as an adjuvant therapy in the management of Type 2 diabetes in non-pregnant subjects. Type 2 diabetes and GDM share the similarity of insulin resistance and thus exercise therapy may also applied to the GDM population. The International Federation of Gynecology and Obstetrics (FIGO) recommends appropriate, personally adapted, physical activity for all women with gestational diabetes mellitus. Our previous study provided evidence that exposure to exercise intervention during pregnancy improves pregnancy outcomes in overweight and obese pregnant women [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe 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 \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003ein utero\u003c/span\u003e exposure [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. 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.\u003c/p\u003e \u003cp\u003eDNA methylation is involved in imprinting, mammalian development, and genomic stability maintenance. A number of cell type-specific DNA methylation patterns are believed to be established in the embryonic stage and the potential plasticity of DNA methylation enables reprogramming, depending on exposures to environmental, nutritional and chemical factors. Intrauterine exposures may induce adaptive DNA methylation changes, through which the \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003ein utero\u003c/span\u003e exposures may have a lasting impact on future disease manifestation in adult life. We here illustrate the role of epigenetic modifications in umbilical cord blood of offspring in response to intrauterine exposures induced by exercise training.\u003c/p\u003e "},{"header":"Research Design And Methods","content":" \u003cp\u003eStudy Participants and sample collection\u003c/p\u003e \u003cp\u003eThe study was approved by the Institutional Review Board of Peking University First Hospital. All studies were performed according to the declaration of Helsinki. Informed consent was obtained from all participants. We conducted a randomized clinical trial at Peking University First Hospital from December 2014 through July 2016. The study protocol was reported previously [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Briefly, the study recruited nonsmoking women age\u0026thinsp;\u0026gt;\u0026thinsp;18\u0026nbsp;years with a singleton pregnancy who met the criteria for overweight/obese status (body mass index\u0026thinsp;\u0026lt;\u0026thinsp;28/\u0026ge;28\u0026nbsp;kg/m\u003csup\u003e2\u003c/sup\u003e) and had an uncomplicated pregnancy at \u0026lt;\u0026thinsp;12\u003csup\u003e+\u0026thinsp;6\u003c/sup\u003e weeks of gestation. The women were randomly allocated to either exercise or a control group. Gestational age was assessed based on the last menstrual period and early ultrasound. Patients did not have contraindications to physical activity. Patients allocated to the exercise group performed exercise 3 times per week (at least 30\u0026nbsp;min/session with a rating of perceived exertion between 12\u0026ndash;14) via a cycling program that was initiated within 3\u0026nbsp;days of randomization until 37 weeks of gestation. All the exercise sessions occurred at Peking University First Hospital under supervision. Patients assigned to the control group continued their usual daily activities. Both groups received standard prenatal care, albeit without special dietary recommendations.\u003c/p\u003e \u003cp\u003eBlood was drawn from the antecubital vein after the participant had fasted for at least 8 hours, but not \u0026gt;\u0026thinsp;14 hours. Blood was collected in sterile vacutainer tubes preloaded with heparin. There was at least 24 hours between the last exercise bout and the time of blood draw. Blood was centrifuged at 1800\u0026nbsp;g at 4\u0026nbsp;\u0026deg;C for 10 minutes within 4 hours of collection; subsequently, the plasma was separated and glucose was measured immediately. The remaining plasma was stored at -80\u0026nbsp;\u0026deg;C for later analysis of insulin and lipid parameters (triglyceride, total cholesterol, and low- and high-density lipoprotein cholesterol). Insulin was measured using radioimmunoassay commercial kits (Beifang Institute of Biochemical Technology, Beijing, China). The insulin resistance index was calculated according to the homeostasis model of assessment: fasting plasma insulin (\u0026micro;U/mL)\u0026thinsp;\u0026times;\u0026thinsp;fasting glucose (mmol/L)/22.5 [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Fasting lipid profiles were measured using an automatic analyzer (7600; Hitachi High-Technologies Corp, Tokyo, Japan) in the Department of Clinical Laboratory, Peking University First Hospital. Biochemical tests were repeated at 25 and 36 gestational weeks. Umbilical cord blood samples were obtained and immediately stored once the baby was delivered. Twelve participants from each group were recruited in the following DNA methylation array analysis. Clinical characteristics of participants and pregnancy outcomes were recorded and presented in Table\u0026nbsp;1.\u003c/p\u003e \u003cp\u003eDNA methylation sample preparation\u003c/p\u003e \u003cp\u003eDNA was extracted from 2\u0026nbsp;ml of whole blood from each sample using Blood DNA Midi Kit (Omega). The total amount of DNA was determined by spectrophotometry. The DNA samples were sent to the Beijing KPS Biotechnology Co., Ltd and stored at -20\u0026nbsp;\u0026deg;C. Quality check was performed by Nanodrop Spectrophotometer and resolution on a 0.8% agarose gel. Bisulfite convert the genomic DNA samples using the Zymo EZ DNA Methylation Kit (Zymo Research).\u003c/p\u003e \u003cp\u003eIllumina MethylationEPIC microarray\u003c/p\u003e \u003cp\u003eThe EPIC platform has probes targeting 866,836 cytosine positions on the human genome, of which 863,904 (99.7%) are CpG dinucleotides and 2932 (0.3%) CNG targets. Additionally, there are 59 probes targeting SNP sites to allow sample matching and 636 probes for sample-dependent and sample-independent quality control. EPIC probes are principally located at promoters (54%), followed by gene bodies (30%) and then intergenic regions (16%), and 19% and 18% of all EPIC probes are located in CpG islands and CpG island shores, respectively.\u003c/p\u003e \u003cp\u003eAccording to Illumina\u0026rsquo;s specification, DNA was hybridized to Illumina MethylationEPIC microarrays. Briefly, the bisulfite-converted DNA samples were denatured, neutralized and prepared for amplification after overnight incubation. Amplified DNA samples were enzymatically fragmented and precipitated. Subsequently, precipitated DNA samples were resuspended and dispensed onto BeadChips. BeadChips were incubated in the Illumina Hybridization Oven to hybridize the samples onto the BeadChips. The BeadChips were stained and scanned following the instructions. Data analysis was performed by R bioconductor package minfi [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] for methylation intensity calculation and limma [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] for differential analysis.\u003c/p\u003e \u003cp\u003eData processing\u003c/p\u003e \u003cp\u003eFor methylation analysis, IDAT files were loaded into the R (3.4.3) environment using the Bioconductor minfi package (1.26.2). Quality control was performed and CpG sites with detection p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were kept. Signals were then normalized using quantile method [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The level of DNA methylation at a particular CpG site (also called the methylation beta-value (β)) was calculated by taking the ratio of the methylated intensity (M) to unmethylated intensity (U) signal, using the formula: β\u0026thinsp;=\u0026thinsp;M/(M\u0026thinsp;+\u0026thinsp;U). A β-value of 0 represents a completely unmethylated CpG site and a β-value approaching 1 represents a fully methylated CpG site.\u003c/p\u003e \u003cp\u003eProbes on sex chromosomes were removed, as well as those identified as cross-hybridizing with other genomic locations or SNP-associated [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. A set of 683,126 probes was obtained and used for exploratory and differential methylation analysis.\u003c/p\u003e \u003cp\u003eDifferential methylation analysis\u003c/p\u003e \u003cp\u003eIn order to assess differences in methylation between groups, the original β values were converted to M-values via the logit transformation. Differentially methylated probes were detected using the R bioconductor limma (3.36.3) package. Probes with adjusted p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered to be differentially methylated. The Benjamini\u0026ndash;Hochberg method was used to adjust the p values and ensure that the false discovery rate was \u0026lt;\u0026thinsp;0.05. The corresponding gene list was derived from the gene annotations associated with the probes.\u003c/p\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003cp\u003eClinical results were statistically analyzed by SPSS 20.0. All values are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Two-tailed unpaired Student\u0026rsquo;s \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003et\u003c/span\u003e-test were performed. Regarding differential methylation analysis, probes with adjusted p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered to be differentially methylated. The Benjamini\u0026ndash;Hochberg method was used to adjust the p values and ensure that the false discovery rate was \u0026lt;\u0026thinsp;0.05.\u003c/p\u003e "},{"header":"Results","content":" \u003cp\u003eTwelve participants from the exercise group and the control group were recruited for the DNA methylation array analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). There were no significant differences of age, weight, height, prepregnancy body mass index, gestational age and fasting plasma glucose at study entry between exercise and control groups (Table\u0026nbsp;1). The exercise intervention increased moderate exercise levels at 25 and 36 gestational weeks (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). No vigorous exercise was reported in participants. There was no difference in walking amount and total exercise load between two groups (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The exercise intervention group gained less weight from study entry to 25\u003csup\u003e+\u0026thinsp;6\u003c/sup\u003e weeks of gestation compared to the control group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). No difference of weight gain in the later stage of gestation (26\u003csup\u003e+\u0026thinsp;1\u003c/sup\u003e weeks to 36\u003csup\u003e+\u0026thinsp;6\u003c/sup\u003e weeks) was reported in the current study. The participants in exercise and control groups had the equal homeostatic model assessment for insulin resistance (HOMA-IR), triglyceride, total cholesterol, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) profiles (Supplementary Table).\u003c/p\u003e \n\n \u003cp\u003e \u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eDynamic alterations of DNA methylation profiles during pregnancy in maternal blood\u003c/span\u003e \u003c/p\u003e \u003cp\u003eIn order to illustrate the DNA methylation alterations in different trimesters in maternal blood, we categorized DNA methylation changes in 1st, 2nd and 3rd trimesters to four groups according to the trend. We defined DNA methylation baseline level of 1st trimester as \u0026ldquo;0\u0026rdquo;, DNA methylation level increase between trimesters as \u0026ldquo;1\u0026rdquo; and DNA methylation level decrease between trimesters as \u0026ldquo;-1\u0026rdquo;. Thus, we detected four patterns of DNA methylation profiles (0. 1. -1; 0. 1. 1; 0. -1. 1; 0. -1. -1) in either control or exercise participants (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Red lines indicate significant changes of differentially methylated positions (DMPs) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and grey lines indicate non-significant changes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThere were 26573 DMPs in the control group and 15913 DMPs in the exercise group for 0. 1. -1 trend (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). DMPs were defined as both a significant change for 2nd vs. 1st trimester (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and also a significant change for 3rd vs. 2nd trimester (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Among them, 2562 DMPs in control group and 1345 DMPs in exercise group were significantly altered in 0. 1. -1 pattern (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Similarly, for 0. -1. 1 trend, we found 35363 DMPs (2014 significant DMPs) in the control group and 14635 DMPs (1076 significant DMPs) in the exercise group respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Interestingly, there were fewer DMPs for 0. 1. 1 and 0. -1. -1 trends both in control and exercise groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Only two significant DMPs (cg13769674, cg08530065) in the control and one significant DMP (cg04260608) in the exercise-trained group for 0. 1. 1 trend were identified. Similarly, one DMP (cg08586855) and two DMPs (cg12394567, cg02033213) were found for 0. -1. -1 trend in control and exercise groups, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003eDifferentially methylated regions (DMRs) are genomic regions with different DNA methylation status across the biological samples and regarded as possible functional regions involved in gene transcriptional regulation. Compared to 1st trimester in maternal blood, 17781 DMRs were revealed in 2nd trimester in the control group, among which 1293 DMRs were located in promoters. 6565 DMRs were identified in the exercise group and 615 DMRs were located in promoters. 4530 DMRs and 3145 DMRs were found in 3rd trimester compared to 2nd trimester in control and exercise groups, respectively. 477 DMRs and 280 DMRs were located in promoters accordingly (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eDNA methylation levels of specific genes were altered by exercise in maternal blood\u003c/span\u003e \u003c/p\u003e \u003cp\u003eWe 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 \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eUMAD1\u003c/span\u003e (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eUBAP1-MVB12-associated (UMA) domain containing 1\u003c/span\u003e, cg12309238), \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eRPA3\u003c/span\u003e (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003ereplication protein A3\u003c/span\u003e, cg12309238), \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003ePLAGL2\u003c/span\u003e (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003ePLAG1 like zinc finger 2\u003c/span\u003e, cg25811820) and \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003ePOFUT1\u003c/span\u003e (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eprotein O-fucosyltransferase 1\u003c/span\u003e, cg25811820) showed significantly differential trends in control (0. -1. 1) and exercise (0. 1. -1) groups in maternal blood (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Six CpG sites and corresponding genes including \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eSPATA17\u003c/span\u003e (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003espermatogenesis associated 17\u003c/span\u003e, cg17026642), \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eGPATCH2\u003c/span\u003e (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eG-patch domain containing 2\u003c/span\u003e, cg17026642), \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eCEP170\u003c/span\u003e (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003ecentrosomal protein 170\u003c/span\u003e, cg08258520), \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eMPHOSPH10\u003c/span\u003e (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eM-phase phosphoprotein 10\u003c/span\u003e, cg20854010), \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eMCEE\u003c/span\u003e (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003emethylmalonyl-CoA epimerase\u003c/span\u003e, cg20854010) as well as \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eMRGPRD\u003c/span\u003e (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eMAS related GPR family member D\u003c/span\u003e, cg11903239) demonstrated opposite trends 0. 1. -1 (control) and 0. -1. 1 (exercise) during pregnancy (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eThe global DNA methylation profile of cord blood is different from that of maternal blood\u003c/span\u003e \u003c/p\u003e \u003cp\u003eNext, we compared the DNA methylation profiles in maternal blood and cord blood. We studied the epigenome-wide variation in DNA methylation with principal component analysis (PCA), which shows that the leading axis of epigenomic variation reflects the tissue type (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Dots represent blood samples and are colored accordingly. The heatmaps show DNA methylation comparisons between cord blood and maternal blood in different trimesters (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). The differential genes of maternal and cord blood were then grouped into three categories using Gene Ontology (GO) system: biological process (describing the larger cellular or physiological role carried out by the gene, coordinated with other genes) and cellular component (describing the location in the cell where the gene product executes its function) and molecular function (describing the molecular activity of a gene) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway demonstrated that \u0026ldquo;metabolic pathways\u0026rdquo; was the most significant pathway enrichment in differential genes comparing maternal and cord blood (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF). The corresponding proteins of differential genes of maternal and cord blood were analyzed using protein-protein interactions (PPIs) network, whereby the physical contacts of high specificity is established between potential protein molecules (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCompared to 3rd trimester in maternal blood, 82676 DMRs were demonstrated in cord blood in control, among which 9464 DMRs were located in promoters. 78318 DMRs were identified in the exercise group and 9130 DMRs were located in promoters (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eMaternal exercise alters gene-specific DNA methylation levels in cord blood\u003c/span\u003e \u003c/p\u003e \u003cp\u003eThe 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 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). These CpG sites were located within the CpG islands of Transcription Start Site (TSS) of four specific genes including \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003edeveloping brain homeobox 1\u003c/span\u003e (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eDBX1\u003c/span\u003e), \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eF-box and leucine rich repeat protein 2\u003c/span\u003e (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eFBXL2\u003c/span\u003e), \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003epotassium two pore domain channel subfamily K member 9\u003c/span\u003e (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eKCNK9\u003c/span\u003e) and \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eprostaglandin reductase 1\u003c/span\u003e (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003ePTGR1\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eKEGG pathway analysis revealed that \u0026ldquo;aldosterone synthesis and secretion\u0026rdquo; was the most significant pathway enrichment in cord blood from the exercise versus the control groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB).\u003c/p\u003e "},{"header":"Discussion","content":" \u003cp\u003eThe general pattern of DNA methylation in human fetal germ cells during development has been comprehensively analyzed [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Nevertheless, the patterns of DNA methylation during pregnancy, as well as DNA methylation of the neonate, have not been established. 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 [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. 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. Additionally, more differential DMRs were found in the early half of the pregnancy.\u003c/p\u003e \u003cp\u003ePrevious study demonstrated that acute gene activation induced by a bout of exercise is associated with a rapid change in DNA methylation in another adult somatic tissue, skeletal muscle [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Specifically, exercise triggered marked hypomethylation on respective promoter of \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eperoxisome proliferator-activated receptor gamma, coactivator 1 a (PGC1α)\u003c/span\u003e, \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003epyruvate dehydrogenase kinase\u003c/span\u003e, \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eisoenzyme 4\u003c/span\u003e (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003ePDK4\u003c/span\u003e) and \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eperoxisome proliferator-activated receptor δ\u003c/span\u003e (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003ePPAR-δ\u003c/span\u003e), genes playing important roles in cell metabolism [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In the current study, we reported dynamic changes in maternal blood in response to exercise training. In contrast to skeletal muscle biopsies, blood samples are relatively easy to obtain from pregnant woman. Thus we are unable to determine whether exercise training elicited effect on DNA methylation in skeletal muscle of pregnant women. In a previous study, DNA methylation alterations were demonstrated immediately after an acute bout of exercise, revealing an exercise intensity-dependent response. The current study showed DNA methylation changes based on a moderate physical activity level over a relatively longer period.\u003c/p\u003e \u003cp\u003eExercise induced significant DNA methylation alterations of specific CpG sites and corresponding genes including \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eUMAD1\u003c/span\u003e (cg12309238), \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eRPA3\u003c/span\u003e (cg12309238), \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003ePLAGL2\u003c/span\u003e (cg25811820) and \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003ePOFUT1\u003c/span\u003e (cg25811820), \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eSPATA17\u003c/span\u003e (cg17026642), \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eGPATCH2\u003c/span\u003e (cg17026642), \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eCEP170\u003c/span\u003e (cg08258520), \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eMPHOSPH10\u003c/span\u003e (cg20854010), \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eMCEE\u003c/span\u003e (cg20854010) as well as \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eMRGPRD\u003c/span\u003e (cg11903239). Among these genes, \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eMRGPRD\u003c/span\u003e was reported to play an important role in protecting osteocytes and preventing bone loss through preventing mitochondrial breakdown in osteocytes [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In the current study, we demonstrated dynamic, opposing alterations of DNA methylation levels of \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eMRGPRD\u003c/span\u003e 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.\u003c/p\u003e \u003cp\u003eOur study provided evidence that metabolic pathways markedly differ between maternal blood and umbilical cord blood. This finding raises an issue related to tissue specificity when using cord blood. Umbilical cord blood, like adult blood, is a heterogeneous tissue (e.g. monocytes neutrophils, eosinophils, basophils, B cells, NK cells, and T cells). The proportions of cells with nuclei fluctuate greatly throughout fetal development and may vary significantly depending on the gestational age [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. DNA methylation levels are affected by cell type proportion fluctuation across gestational age. It has been shown blood cell type methylation markers were segregated into two clusters by gestational age. The two clusters of DNA methylation measurement were characterized by proportions of granulocytes, lymphocytes, and B cells in cord blood, which were determined by gestational age [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Therefore, the cell type proportion differences partially contribute to the DNA methylation variations in maternal blood and cord blood.\u003c/p\u003e \u003cp\u003eOur previous study reported differentially methylated genes in neonates exposed to the intrauterine hyperglycemia using the array-based method [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Altered DNA methylation levels of \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eRho guanine nucleotide exchange factor 11\u003c/span\u003e (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eARHGEF11\u003c/span\u003e) were negatively correlated with glucose levels and neonatal birth weight, which emphasized the potential influence of intrauterine environment and maternal nutrition status on DNA methylation. 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 \u0026ldquo;aldosterone synthesis and secretion\u0026rdquo; 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. Our study sheds light on the potential metabolic disease pathogenesis in offspring, which might be related to the maternal life style during pregnancy.\u003c/p\u003e \u003cp\u003ePrevious studies demonstrated that caffeine mimics exercise-induced expression of genes related to mitochondrial function in L6 myotubes [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Moreover, a time-course study of caffeine exposure of L6 myotubes suggests that exercise mimetics may trigger promoter hypomethylation of specific genes [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Nevertheless, the mechanism by which maternal exercise alters the intrauterine environment and concomitantly influences the fetal DNA methylation establishment remains unknown.\u003c/p\u003e \u003cp\u003eNotably, 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.\u003c/p\u003e \u003cp\u003eThe effectiveness and modality of physical activity during pregnancy in prevention of gestational diabetes mellitus, as well as the underlying mechanism is still obscure. DNA methylation appears to sense environmental changes, regulates gene expression, and prepares the body to respond to changes in the milieu. Environmental factors have a dynamic effect on the level of DNA methylation in the promoter regions of key genes. Our data provide a comprehensive 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. Changes in DNA methylation may be an early event in reprogramming the metabolic profile in human somatic tissues, as well as cord blood. Our results provides evidence for implementing exercise intervention strategies for disease management in order to modify epigenetic marks.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Institutional Review Board of Peking University First Hospital (reference numbers: 2014[726], 2019[45]). All studies were performed according to the declaration of Helsinki. Informed consent was obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study are available from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China [grant numbers 81401215, 81830044, 81801471], the Beijing Natural Science Foundation [grant numbers 7192206], Beijing Talents Foundation from organization department of Beijing municipal committee of the CPC [grant number 2016000021223ZK20], Peking University Medicine Fund of Fostering Young Scholars\u0026rsquo; Scientific \u0026amp; Technological Innovation and the Fundamental Research Funds for the Central Universities [grant number BMU2018PY002].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJY and HY designed research; CW and YW conducted the exercise intervention; JY and CW processed samples; JY and HY wrote the paper; HY had primary responsibility for final content. HY is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDabelea D, Hanson RL, Bennett PH, Roumain J, Knowler WC, Pettitt DJ: \u003cstrong\u003eIncreasing prevalence of Type II diabetes in American Indian children\u003c/strong\u003e. \u003cem\u003eDiabetologia \u003c/em\u003e1998, \u003cstrong\u003e41\u003c/strong\u003e(8):904-910.\u003c/li\u003e\n\u003cli\u003eMetzger BE, Lowe LP, Dyer AR, Trimble ER, Chaovarindr U, Coustan DR, Hadden DR, McCance DR, Hod M, McIntyre HD\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eHyperglycemia and adverse pregnancy outcomes\u003c/strong\u003e. \u003cem\u003eN Engl J Med \u003c/em\u003e2008, \u003cstrong\u003e358\u003c/strong\u003e(19):1991-2002.\u003c/li\u003e\n\u003cli\u003eSimeoni U, Barker DJ: \u003cstrong\u003eOffspring of diabetic 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RF, Fazzari MJ, Niu H, Barzilai N, Simmons RA, Greally JM: \u003cstrong\u003eExperimental intrauterine growth restriction induces alterations in DNA methylation and gene expression in pancreatic islets of rats\u003c/strong\u003e. \u003cem\u003eJ Biol Chem \u003c/em\u003e2010, \u003cstrong\u003e285\u003c/strong\u003e(20):15111-15118.\u003c/li\u003e\n\u003cli\u003eSimmons RA: \u003cstrong\u003eDevelopmental origins of adult disease\u003c/strong\u003e. \u003cem\u003ePediatr Clin North Am \u003c/em\u003e2009, \u003cstrong\u003e56\u003c/strong\u003e(3):449-466, Table of Contents.\u003c/li\u003e\n\u003cli\u003eBreton CV, Byun HM, Wenten M, Pan F, Yang A, Gilliland FD: \u003cstrong\u003ePrenatal tobacco smoke exposure affects global and gene-specific DNA methylation\u003c/strong\u003e. \u003cem\u003eAm J Respir Crit Care Med \u003c/em\u003e2009, \u003cstrong\u003e180\u003c/strong\u003e(5):462-467.\u003c/li\u003e\n\u003cli\u003eMuniyappa R, Lee S, Chen H, Quon MJ: \u003cstrong\u003eCurrent approaches for assessing insulin sensitivity and resistance in vivo: advantages, limitations, and appropriate usage\u003c/strong\u003e. \u003cem\u003eAmerican journal of physiology Endocrinology and metabolism \u003c/em\u003e2008, \u003cstrong\u003e294\u003c/strong\u003e(1):E15-26.\u003c/li\u003e\n\u003cli\u003eAryee MJ, Jaffe AE, Corrada-Bravo H, Ladd-Acosta C, Feinberg AP, Hansen KD, Irizarry RA: \u003cstrong\u003eMinfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays\u003c/strong\u003e. \u003cem\u003eBioinformatics \u003c/em\u003e2014, \u003cstrong\u003e30\u003c/strong\u003e(10):1363-1369.\u003c/li\u003e\n\u003cli\u003eRitchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, Smyth GK: \u003cstrong\u003elimma powers differential expression analyses for RNA-sequencing and microarray studies\u003c/strong\u003e. \u003cem\u003eNucleic acids research \u003c/em\u003e2015, 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profiling of mouse and human fetal germ cells\u003c/strong\u003e. \u003cem\u003eCell research \u003c/em\u003e2017, \u003cstrong\u003e27\u003c/strong\u003e(2):165-183.\u003c/li\u003e\n\u003cli\u003eReik W, Dean W, Walter J: \u003cstrong\u003eEpigenetic reprogramming in mammalian development\u003c/strong\u003e. \u003cem\u003eScience \u003c/em\u003e2001, \u003cstrong\u003e293\u003c/strong\u003e(5532):1089-1093.\u003c/li\u003e\n\u003cli\u003eBarres R, Yan J, Egan B, Treebak JT, Rasmussen M, Fritz T, Caidahl K, Krook A, O'Gorman DJ, Zierath JR: \u003cstrong\u003eAcute exercise remodels promoter methylation in human skeletal muscle\u003c/strong\u003e. \u003cem\u003eCell metabolism \u003c/em\u003e2012, \u003cstrong\u003e15\u003c/strong\u003e(3):405-411.\u003c/li\u003e\n\u003cli\u003eKitase Y, Vallejo JA, Gutheil W, Vemula H, Jahn K, Yi J, Zhou J, Brotto M, Bonewald LF: \u003cstrong\u003ebeta-aminoisobutyric Acid, l-BAIBA, Is a Muscle-Derived Osteocyte Survival Factor\u003c/strong\u003e. \u003cem\u003eCell reports \u003c/em\u003e2018, \u003cstrong\u003e22\u003c/strong\u003e(6):1531-1544.\u003c/li\u003e\n\u003cli\u003eYgberg S, Nilsson A: \u003cstrong\u003eThe developing immune system - from foetus to toddler\u003c/strong\u003e. \u003cem\u003eActa Paediatr \u003c/em\u003e2012, \u003cstrong\u003e101\u003c/strong\u003e(2):120-127.\u003c/li\u003e\n\u003cli\u003eBraid SM, Okrah K, Shetty A, Corrada Bravo H: \u003cstrong\u003eDNA Methylation Patterns in Cord Blood of Neonates Across Gestational Age: Association With Cell-Type Proportions\u003c/strong\u003e. \u003cem\u003eNursing research \u003c/em\u003e2017, \u003cstrong\u003e66\u003c/strong\u003e(2):115-122.\u003c/li\u003e\n\u003cli\u003eYan J, Su R, Zhang W, Wei Y, Wang C, Lin L, Feng H, Yang H: \u003cstrong\u003eEpigenetic alteration of Rho guanine nucleotide exchange Factor 11 (ARHGEF11) in cord blood samples in macrosomia exposed to intrauterine hyperglycemia\u003c/strong\u003e. \u003cem\u003eThe journal of maternal-fetal \u0026amp; neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstet \u003c/em\u003e2019:1-10.\u003c/li\u003e\n\u003cli\u003eOjuka EO, Jones TE, Han DH, Chen M, Holloszy JO: \u003cstrong\u003eRaising Ca2+ in L6 myotubes mimics effects of exercise on mitochondrial biogenesis in muscle\u003c/strong\u003e. \u003cem\u003eFASEB journal : official publication of the Federation of American Societies for Experimental Biology \u003c/em\u003e2003, \u003cstrong\u003e17\u003c/strong\u003e(6):675-681.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable style=\"margin-left: 4.65pt; border-collapse: collapse;\" width=\"748\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 560.7pt; border: none; border-bottom: solid windowtext 2.25pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" colspan=\"4\" width=\"748\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eTable 1. Baseline characteristics of participants\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 319.7pt; border: none; border-bottom: solid windowtext 2.25pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"426\"\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eCharacteristics\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; border: none; border-bottom: solid windowtext 2.25pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eExercise group\u003c/span\u003e\u003c/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003en=12\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; border: none; border-bottom: solid windowtext 2.25pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eControl group\u003c/span\u003e\u003c/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003en=12\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; border: none; border-bottom: solid windowtext 2.25pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003ep\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 319.7pt; border: none; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"426\"\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eAge, y\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; border: none; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\n\u003cp style=\"text-align: center; word-break: break-all;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e32.92 \u0026plusmn; 1.93\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; border: none; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\n\u003cp style=\"text-align: center; word-break: break-all;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e31.92 \u0026plusmn; 4.40\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; border: none; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e0.48\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 319.7pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"426\"\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eWeight, kg\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e70.47 \u0026plusmn; 7.56\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e70.46 \u0026plusmn; 10.62\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e1.00\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 319.7pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"426\"\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eHeight, cm\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e162.92 \u0026plusmn; 5.21\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e162.17 \u0026plusmn; 7.53\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e0.78\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 319.7pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"426\"\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003ep-BMI, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e26.61 \u0026plusmn; 3.22\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e26.68 \u0026plusmn; 2.35\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e0.95\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 319.7pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"426\"\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eGestational age, wk\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e9 \u0026plusmn; 2\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e10 \u0026plusmn; 2\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e0.46\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 319.7pt; border: none; border-bottom: solid windowtext 2.25pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"426\"\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eFasting plasma glucose at study entry, mmol/L\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; border: none; border-bottom: solid windowtext 2.25pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e4.88 \u0026plusmn; 0.41\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; border: none; border-bottom: solid windowtext 2.25pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e4.86 \u0026plusmn; 0.48\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; border: none; border-bottom: solid windowtext 2.25pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e0.91\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman',serif;\"\u003eData presented as mean \u0026plusmn; SD; p-BMI, prepregnancy body mass index.\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cspan style=\"font-size: 12pt; font-family: 'Times New Roman', serif;\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eTable 2. Physical activity levels in overweight and obese pregnant women randomized to exercise intervention or control groups\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003ctable style=\"margin-left: 4.65pt; border-collapse: collapse;\" width=\"748\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 22.05pt; border-top: solid windowtext 2.25pt; border-left: none; border-bottom: solid windowtext 2.25pt; border-right: none; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"29\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 297.65pt; border-top: solid windowtext 2.25pt; border-left: none; border-bottom: solid windowtext 2.25pt; border-right: none; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; border-top: solid windowtext 2.25pt; border-left: none; border-bottom: solid windowtext 2.25pt; border-right: none; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eExercise group\u003c/span\u003e\u003c/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003en=12\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; border-top: solid windowtext 2.25pt; border-left: none; border-bottom: solid windowtext 2.25pt; border-right: none; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eControl group\u003c/span\u003e\u003c/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003en=12\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; border-top: solid windowtext 2.25pt; border-left: none; border-bottom: solid windowtext 2.25pt; border-right: none; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003ep\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 319.7pt; border: none; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" colspan=\"2\" width=\"426\"\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eVigorous exercise, metabolic equivalents of task min/wk\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; border: none; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; border: none; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; border: none; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 22.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"29\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 297.65pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"397\"\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eAt study entry\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e0\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e0\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 22.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"29\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 297.65pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"397\"\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eAt 25 wk gestation\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e0\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e0\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 22.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"29\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 297.65pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"397\"\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eAt 36 wk gestation\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e0\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e0\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 319.7pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" colspan=\"2\" width=\"426\"\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eModerate exercise, metabolic equivalents of task min/wk\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 22.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"29\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 297.65pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"397\"\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eAt study entry\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e15 \u0026plusmn; 52\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e3 \u0026plusmn; 9\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e0.42\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 22.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"29\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 297.65pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"397\"\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eAt 25 wk gestation\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e151 \u0026plusmn; 103\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e8 \u0026plusmn; 22\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e\u0026lt; 0.0005\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 22.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"29\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 297.65pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"397\"\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eAt 36 wk gestation\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e92 \u0026plusmn; 49\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e9 \u0026plusmn; 23\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e\u0026lt; 0.005\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 319.7pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" colspan=\"2\" width=\"426\"\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eWalking, metabolic equivalents of task min/wk\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 22.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"29\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 297.65pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"397\"\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eAt study entry\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e617 \u0026plusmn; 616\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e494 \u0026plusmn; 485\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e0.59\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 22.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"29\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 297.65pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"397\"\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eAt 25 wk gestation\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e435 \u0026plusmn; 202\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e664 \u0026plusmn; 627\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e0.26\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 22.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"29\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 297.65pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"397\"\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eAt 36 wk gestation\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e465 \u0026plusmn; 397\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e381 \u0026plusmn; 331\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e0.68\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 319.7pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" colspan=\"2\" width=\"426\"\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eTotal, metabolic equivalents of task min/wk\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 22.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"29\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 297.65pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"397\"\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eAt study entry\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e632 \u0026plusmn; 613\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e496 \u0026plusmn; 485\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e0.55\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 22.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"29\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 297.65pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"397\"\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eAt 25 wk gestation\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e586 \u0026plusmn; 273\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e672 \u0026plusmn; 632\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e0.68\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15.0pt;\"\u003e\n\u003ctd style=\"width: 22.05pt; border: none; border-bottom: solid windowtext 2.25pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"29\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 297.65pt; border: none; border-bottom: solid windowtext 2.25pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"397\"\u003e\n\u003cp\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003eAt 36 wk gestation\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85.05pt; border: none; border-bottom: solid windowtext 2.25pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"113\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e557 \u0026plusmn; 427\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 92.15pt; border: none; border-bottom: solid windowtext 2.25pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"123\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e390 \u0026plusmn; 323\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 63.8pt; border: none; border-bottom: solid windowtext 2.25pt; padding: 0in 5.4pt 0in 5.4pt; height: 15.0pt;\" width=\"85\"\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"font-family: 'Times New Roman', serif;\"\u003e0.43\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"DNA methylation, obesity, exercise, cord blood","lastPublishedDoi":"10.21203/rs.2.23114/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.2.23114/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: Environmental events and nutritional conditions may induce permanent DNA methylation changes \u003cem\u003ein utero\u003c/em\u003e during the sensitive period and these adaptive changes may be ‘memorized’ and have a lasting impact on adult disease later in life. The potential plasticity of DNA methylation also enables reprogramming, depending on exposure to nutritional, chemical, and environmental factors. We determined the effects of exercise training during pregnancy on epigenetic modifications in offspring.\u003c/p\u003e\u003cp\u003eResults: Twenty-four subjects were chosen from a previous clinical study. Overweight/obese pregnant women (body mass index \u0026lt;28/≥28kg/m\u003csup\u003e2\u003c/sup\u003e) who had an uncomplicated pregnancy at \u0026lt;12\u003csup\u003e+6\u003c/sup\u003e weeks of gestation were randomly allocated to either an exercise or a control group. Patients allocated to the exercise group performed 3 exercise bouts per week (at least 30 min/session with a rating of perceived exertion between 12-14) via a cycling program that was initiated within 3 days of randomization until 37 weeks of gestation. Patients allocated to the control group continued their usual daily activities. Maternal blood, as well as umbilical cord blood samples, were collected and DNA methylation levels were determined by Illumina MethylationEPIC microarray. \u003c/p\u003e\u003cp\u003eNine CpG sites and corresponding genes \u003cem\u003eUMAD1\u003c/em\u003e, \u003cem\u003eRPA3\u003c/em\u003e, \u003cem\u003ePLAGL2\u003c/em\u003e, \u003cem\u003ePOFUT1\u003c/em\u003e, \u003cem\u003eSPATA17\u003c/em\u003e, \u003cem\u003eGPATCH2\u003c/em\u003e, \u003cem\u003eCEP170\u003c/em\u003e, \u003cem\u003eMPHOSPH10\u003c/em\u003e, \u003cem\u003eMCEE\u003c/em\u003e, as well as \u003cem\u003eMRGPRD\u003c/em\u003e showed differential trends in control and exercise groups in maternal blood. Furthermore, four specific genes in umbilical cord blood were differentially methylated in the exercise group compared to the sedentary controls (p \u0026lt; 0.01). \u003c/p\u003e\u003cp\u003eConclusions: DNA methylation in maternal blood is dynamically altered during pregnancy and remodeled by exercise training. Thus, intrauterine environmental exposures play an important role in fetal programming. Epigenetic mechanisms involving changes in DNA methylation may provide an explanation for the phenomenon. Our findings shed light on understanding of long-term effects of \u003cem\u003ein utero\u003c/em\u003e exposures on the epigenetic landscape of the offspring.\u003c/p\u003e","manuscriptTitle":"Exercise intervention during pregnancy induces promoter methylation alterations in cord blood","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2020-02-11 16:11:08","doi":"10.21203/rs.2.23114/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"98a5c40c-aea6-4fa9-8a6d-c92570959230","owner":[],"postedDate":"February 11th, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57470,"name":"Epigenetics \u0026 Genomics"}],"tags":[],"updatedAt":"","versionOfRecord":[],"versionCreatedAt":"2020-02-11 16:11:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-13685","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"identity":"rs-13685","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}