Dataset Information

Prenatal Growth Patterns and Birthweight Are Associated With Differential DNA Methylation and Gene Expression of Cardiometabolic Risk Genes in Human Placentas: A Discovery-Based Approach.

ABSTRACT: Inherent genetic programming and environmental factors affect fetal growth in utero. Epidemiologic data in growth-altered fetuses, either intrauterine growth restricted (IUGR) or large for gestational age (LGA), demonstrate that these newborns are at increased risk of cardiometabolic disease in adulthood. There is growing evidence that the in utero environment leads to epigenetic modification, contributing to eventual risk of developing heart disease or diabetes. In this study, we used reduced representation bisulfite sequencing to examine genome-wide DNA methylation variation in placental samples from offspring born IUGR, LGA, and appropriate for gestational age (AGA) and to identify differential methylation of genes important for conferring risk of cardiometabolic disease. We found that there were distinct methylation signatures for IUGR, LGA, and AGA groups and identified over 500 differentially methylated genes (DMGs) among these group comparisons. Functional and gene network analyses revealed expected relationships of DMGs to placental physiology and transport, but also identified novel pathways with biologic plausibility and potential clinical importance to cardiometabolic disease. Specific loci for DMGs of interest had methylation patterns that were strongly associated with anthropometric presentations. We further validated altered gene expression of these specific DMGs contributing to vascular and metabolic diseases (SLC36A1, PTPRN2, CASZ1, IL10), thereby establishing transcriptional effects toward assigning functional significance. Our results suggest that the gene expression and methylation state of the human placenta are related and sensitive to the intrauterine environment, as it affects fetal growth patterns. We speculate that these observed changes may affect risk for offspring in developing adult cardiometabolic disease.

SUBMITTER: Chen PY

PROVIDER: S-EPMC6348426 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Prenatal Growth Patterns and Birthweight Are Associated With Differential DNA Methylation and Gene Expression of Cardiometabolic Risk Genes in Human Placentas: A Discovery-Based Approach.

Chen Pao-Yang PY Chu Alison A Liao Wen-Wei WW Rubbi Liudmilla L Janzen Carla C Hsu Fei-Man FM Thamotharan Shanthie S Ganguly Amit A Lam Larry L Montoya Dennis D Pellegrini Matteo M Devaskar Sherin U SU

Reproductive sciences (Thousand Oaks, Calif.) 20170711 4

Inherent genetic programming and environmental factors affect fetal growth in utero. Epidemiologic data in growth-altered fetuses, either intrauterine growth restricted (IUGR) or large for gestational age (LGA), demonstrate that these newborns are at increased risk of cardiometabolic disease in adulthood. There is growing evidence that the in utero environment leads to epigenetic modification, contributing to eventual risk of developing heart disease or diabetes. In this study, we used reduced r ...[more]

PMID: 28693373

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Project description:Background/objectivesPrenatal growth, which is widely marked by birthweight, may have a pivotal role in affecting the lifelong risk of cardiometabolic disorders; however, comprehensive evaluation of its relations with childhood cardiometabolic risk patterns and the ethnic and gender disparities in national representative populations is still lacking. The aim of this study was to evaluate the associations between birthweight and comprehensive patterns of cardiometabolic risk in a nationally representative sample of children and adolescents.Subjects/methodsProspective analyses were performed using data from 28 153 children 0 to 15 years in the National Health and Nutrition Examination Survey from 1999 through 2014. We defined childhood cardiometabolic disorders using standard definitions for obesity, high blood pressure, hyperglycemia and dyslipidemia.ResultsFive birthweight categories <2.5, 2.5-3.0, 3.0-3.5, 3.5-4.2 and ⩾4.2 kg accounted for 8.2%, 17.9%, 35.7%, 27.9% and 10.4% of the population, respectively. In all children, with increasing birthweight, we observed significantly increasing trends of the risk of general and central obesity (P for trend <0.01) and significantly decreasing trends of the risk of high systolic blood pressure (SBP), high HbA1c and low high-density lipoprotein cholesterol (HDL-C) (P for trend <0.05). The associations were independent of current body mass index (BMI). In addition, we found that the relations of birthweight with high waist circumference in Black children showed U-shape, as well as high SBP in Mexican and Hispanic children. Moreover, we found that the associations of low birthweight with high SBP and low HDL-C appeared to more prominent significant in boys, whereas the inverse association with high HbA1c was more evident in girls.ConclusionsOur data indicate that birthweight is significantly related to childhood cardiometabolic risk, independent of current BMI, and the associations exhibit race and gender-specific patterns.

Project description:BackgroundIndividuals born very low birthweight (VLBW) are at increased risk of impaired cardiovascular and respiratory function in adulthood. To identify markers to predict future risk for VLBW individuals, we analyzed DNA methylation at birth and at 28 years in the New Zealand (NZ) VLBW cohort (all infants born < 1500 g in NZ in 1986) compared with age-matched, normal birthweight controls. Associations between neonatal methylation and cardiac structure and function (echocardiography), vascular function and respiratory outcomes at age 28 years were documented.ResultsGenomic DNA from archived newborn heel-prick blood (n = 109 VLBW, 51 controls) and from peripheral blood at ~ 28 years (n = 215 VLBW, 96 controls) was analyzed on Illumina Infinium MethylationEPIC 850 K arrays. Following quality assurance and normalization, methylation levels were compared between VLBW cases and controls at both ages by linear regression, with genome-wide significance set to p < 0.05 adjusted for false discovery rate (FDR, Benjamini-Hochberg). In neonates, methylation at over 16,400 CpG methylation sites differed between VLBW cases and controls and the canonical pathway most enriched for these CpGs was Cardiac Hypertrophy Signaling (p = 3.44E-11). The top 20 CpGs that differed most between VLBW cases and controls featured clusters in ARID3A, SPATA33, and PLCH1 and these 3 genes, along with MCF2L, TRBJ2-1 and SRC, led the list of 15,000 differentially methylated regions (DMRs) reaching FDR-adj significance. Fifteen of the 20 top CpGs in the neonate EWAS showed associations between methylation at birth and adult cardiovascular traits (particularly LnRHI). In 28-year-old adults, twelve CpGs differed between VLBW cases and controls at FDR-adjusted significance, including hypermethylation in EBF4 (four CpGs), CFI and UNC119B and hypomethylation at three CpGs in HIF3A and one in KCNQ1. DNA methylation GrimAge scores at 28 years were significantly greater in VLBW cases versus controls and weakly associated with cardiovascular traits. Four CpGs were identified where methylation differed between VLBW cases and controls in both neonates and adults, three reversing directions with age (two CpGs in EBF4, one in SNAI1 were hypomethylated in neonates, hypermethylated in adults). Of these, cg16426670 in EBF4 at birth showed associations with several cardiovascular traits in adults.ConclusionsThese findings suggest that methylation patterns in VLBW neonates may be informative about future adult cardiovascular and respiratory outcomes and have value in guiding early preventative care to improve adult health.

Project description:BackgroundDNA methylation is a key epigenetic regulator contributing to cancer development. To understand the role of DNA methylation in tumorigenesis, it is important to investigate and compare differential methylation (DM) patterns between normal and case samples across different cancer types. However, current pan-cancer analyses call DM separately for each cancer, which suffers from lower statistical power and fails to provide a comprehensive view for patterns across cancers.MethodsIn this work, we propose a rigorous statistical model, PanDM, to jointly characterize DM patterns across diverse cancer types. PanDM uses the hidden correlations in the combined dataset to improve statistical power through joint modeling. PanDM takes summary statistics from separate analyses as input and performs methylation site clustering, differential methylation detection, and pan-cancer pattern discovery. We demonstrate the favorable performance of PanDM using simulation data. We apply our model to 12 cancer methylome data collected from The Cancer Genome Atlas (TCGA) project. We further conduct ontology- and pathway-enrichment analyses to gain new biological insights into the pan-cancer DM patterns learned by PanDM.ResultsPanDM outperforms two types of separate analyses in the power of DM calling in the simulation study. Application of PanDM to TCGA data reveals 37 pan-cancer DM patterns in the 12 cancer methylomes, including both common and cancer-type-specific patterns. These 37 patterns are in turn used to group cancer types. Functional ontology and biological pathways enriched in the non-common patterns not only underpin the cancer-type-specific etiology and pathogenesis but also unveil the common environmental risk factors shared by multiple cancer types. Moreover, we also identify PanDM-specific DM CpG sites that the common strategy fails to detect.ConclusionsPanDM is a powerful tool that provides a systematic way to investigate aberrant methylation patterns across multiple cancer types. Results from real data analyses suggest a novel angle for us to understand the common and specific DM patterns in different cancers. Moreover, as PanDM works on the summary statistics for each cancer type, the same framework can in principle be applied to pan-cancer analyses of other functional genomic profiles. We implement PanDM as an R package, which is freely available at http://www.sta.cuhk.edu.hk/YWei/PanDM.html .

Dataset Information

Prenatal Growth Patterns and Birthweight Are Associated With Differential DNA Methylation and Gene Expression of Cardiometabolic Risk Genes in Human Placentas: A Discovery-Based Approach.

Publications

Prenatal Growth Patterns and Birthweight Are Associated With Differential DNA Methylation and Gene Expression of Cardiometabolic Risk Genes in Human Placentas: A Discovery-Based Approach.

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