DNA methylation analysis of cord blood samples in neonates born to gestational diabetes mothers diagnosed before 24 gestational weeks

Kasuga, Yoshifumi; Kawai, Tomoko; Miyakoshi, Kei; Hori, Asuka; Tamagawa, Masumi; Hasegawa, K.; Ikenoue, Satoru; Ochiai, Daigo; Saisho, Yoshifumi; Hida, Mariko; Tanaka, Mamoru; Hata, Kenichiro

doi:10.1136/bmjdrc-2021-002539

Cited by 6 publications

(6 citation statements)

References 40 publications

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“…However, the incidence of GDM diagnosed before 24 weeks of gestation in the neonatal hypoglycemia group was not different from the non-neonatal hypoglycemia group in this study. We previously reported that umbilical blood DNA methylation in GDM diagnosed before 24 gestational weeks was not different from that in GDM diagnosed after 24 gestational weeks and a normal OGTT [25]. Therefore, glucose control to prevent changes in umbilical blood DNA methylation could prevent neonatal hypoglycemia.…”

Section: Discussionmentioning

confidence: 95%

Risk factors of neonatal hypoglycemia in neonates born to mothers with gestational diabetes

et al. 2023

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Hypoglycemia is one of the most significant problems in neonates born to mothers with gestational diabetes (GDM). This study aimed to identify novel predictors of hypoglycemia in neonates born to mothers with GDM. A total of 443 term singleton infants from mothers diagnosed with GDM and cared for at Keio University Hospital between January 2013 and December 2019 were included in this study. Neonatal hypoglycemia was defined as hypoglycemia of less than 47 mg/dL at 1 or 2 or 4 h after birth, according to previous studies. Among 443 full-term singleton neonates born to mothers with GDM, 200 developed hypoglycemia (45%). Gestational weight gain (GWG), HbA1c at 1st trimester, HbA1c at GDM diagnosis, and the incidence of insulin therapy in the neonatal hypoglycemia group were significantly higher than those in the non-neonatal hypoglycemia group (p = 0.016, p = 0.032, p = 0.011, and p = 0.017, respectively). Regarding the multiple regression analysis adjusted for nulliparity, GWG, and gestational weeks at delivery, the odds ratio for maternal HbA1c ≥5.2% at 1st trimester was 1.63 (p = 0.034), and maternal insulin therapy during pregnancy was 1.72 (p = 0.015). In conclusion, HbA1c in the 1st trimester and insulin therapy during pregnancy were good predictors of hypoglycemia in neonates born to GDM mothers, especially when their HbA1c was 5.2% or more. Further research will be necessary to improve the perinatal management of hypoglycemia.

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Section: Discussionmentioning

confidence: 95%

Risk factors of neonatal hypoglycemia in neonates born to mothers with gestational diabetes

et al. 2023

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“…In this study, we utilized publicly available datasets from the Gene Expression Omnibus (GEO) and ArrayExpress. These datasets consisted of Illumina methylation 450 K or EPIC bead array IDAT files, comprising a comprehensive collection of 10,147 samples (Table 1 ) (Arloth et al., 2020 ; Castro de Moura et al., 2021 ; Chen et al., 2022 ; Chuang et al., 2017 ; Curtis et al., 2019 ; Dabin et al., 2020 ; Diboun et al., 2022 ; Huang, Cai, et al., 2021 ; Johansson et al., 2013 ; Kasuga et al., 2022 ; Kurushima et al., 2019 ; Liu et al., 2013 ; Maschietto et al., 2017 ; Naumova et al., 2021 ; Perez et al., 2019 ; Shang et al., 2023 ; Tan et al., 2014 ; Van Baak et al., 2018 ; Wang et al., 2018 , 2022 ). The subjects included in our study spanned an age range of 0–99 years, ensuring a wide representation of age groups.…”

Section: Methodsmentioning

confidence: 99%

Deciphering the role of immune cell composition in epigenetic age acceleration: Insights from cell‐type deconvolution applied to human blood epigenetic clocks

Zhang,

Reynolds,

Stolrow

et al. 2023

Aging Cell

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Aging is a significant risk factor for various human disorders, and DNA methylation clocks have emerged as powerful tools for estimating biological age and predicting health‐related outcomes. Methylation data from blood DNA has been a focus of more recently developed DNA methylation clocks. However, the impact of immune cell composition on epigenetic age acceleration (EAA) remains unclear as only some clocks incorporate partial cell type composition information when analyzing EAA. We investigated associations of 12 immune cell types measured by cell‐type deconvolution with EAA predicted by six widely‐used DNA methylation clocks in data from >10,000 blood samples. We observed significant associations of immune cell composition with EAA for all six clocks tested. Across the clocks, nine or more of the 12 cell types tested exhibited significant associations with EAA. Higher memory lymphocyte subtype proportions were associated with increased EAA, and naïve lymphocyte subtypes were associated with decreased EAA. To demonstrate the potential confounding of EAA by immune cell composition, we applied EAA in rheumatoid arthritis. Our research maps immune cell type contributions to EAA in human blood and offers opportunities to adjust for immune cell composition in EAA studies to a significantly more granular level. Understanding associations of EAA with immune profiles has implications for the interpretation of epigenetic age and its relevance in aging and disease research. Our detailed map of immune cell type contributions serves as a resource for studies utilizing epigenetic clocks across diverse research fields, including aging‐related diseases, precision medicine, and therapeutic interventions.

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“…The data filtering criteria used for BeadChip array analysis varied significantly across studies. For example, eight of the 12 studies used the more stringent multiple testing correction methods with adjusted p -values <0.05 for their analysis ( 28 , 31 , 36 , 40 , 45 , 46 , 48 , 50 ), whereas four studies used the unadjusted p- value of either < 0.01 or < 0.05, since the multiple testing correction methods do not always identify significant differentially methylated loci when sample sizes are small ( 33 , 42 , 56 , 57 ). Small sample sizes has been identified as a major limitation of genome-wide studies, which can be improved by using additional datasets and independent DNA methylation quantification methods to verify and validate study findings, although this is time consuming and costly.…”

Section: Discussionmentioning

confidence: 99%

“…Conversely, in a more recent study, Kasuga et al. quantified DNA methylation at 754 255 CpG sites in the cord blood of 230 Japanese women and showed no significant differences between women with GDM compared to women without GDM ( 50 ). The identification of differentially methylated genes in peripheral and cord blood provides potential for DNA methylation as a biomarker of GDM.…”

Section: Dna Methylation Profiling In Pregnancies Complicated By Diab...mentioning

confidence: 97%

“…Functional analysis of differentially methylated genes demonstrated an association with pathways linked to endocrine disorders, metabolic diseases, carbohydrate metabolism, and lipid metabolism, as well as metabolically related signaling pathways such as Janus kinase 2/signal transduction and activator of transcription 3 (JAK2/ STAT-3) and mitogen activated protein kinase (MAPK) in women with GDM compared to women without GDM. Conversely, in a more recent study, Kasuga et al quantified DNA methylation at 754 255 CpG sites in the cord blood of 230 Japanese women and showed no significant differences between women with GDM compared to women without GDM (50). The identification of differentially methylated genes in peripheral and cord blood provides potential for DNA methylation as a biomarker of GDM.…”

Section: Genome-wide Methylation Studiesmentioning

confidence: 99%

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The role of maternal DNA methylation in pregnancies complicated by gestational diabetes

Dias¹,

Willmer²,

Adam³

2022

Front. Clin. Diabetes Healthc.

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Diabetes in pregnancy is associated with adverse pregnancy outcomes and poses a serious threat to the health of mother and child. Although the pathophysiological mechanisms that underlie the association between maternal diabetes and pregnancy complications have not yet been elucidated, it has been suggested that the frequency and severity of pregnancy complications are linked to the degree of hyperglycemia. Epigenetic mechanisms reflect gene-environment interactions and have emerged as key players in metabolic adaptation to pregnancy and the development of complications. DNA methylation, the best characterized epigenetic mechanism, has been reported to be dysregulated during various pregnancy complications, including pre-eclampsia, hypertension, diabetes, early pregnancy loss and preterm birth. The identification of altered DNA methylation patterns may serve to elucidate the pathophysiological mechanisms that underlie the different types of maternal diabetes during pregnancy. This review aims to provide a summary of existing knowledge on DNA methylation patterns in pregnancies complicated by pregestational type 1 (T1DM) and type 2 diabetes mellitus (T2DM), and gestational diabetes mellitus (GDM). Four databases, CINAHL, Scopus, PubMed and Google Scholar, were searched for studies on DNA methylation profiling in pregnancies complicated with diabetes. A total of 1985 articles were identified, of which 32 met the inclusion criteria and are included in this review. All studies profiled DNA methylation during GDM or impaired glucose tolerance (IGT), while no studies investigated T1DM or T2DM. We highlight the increased methylation of two genes, Hypoxia‐inducible Factor‐3α (HIF3α) and Peroxisome Proliferator-activated Receptor Gamma-coactivator-Alpha (PGC1-α), and the decreased methylation of one gene, Peroxisome Proliferator Activated Receptor Alpha (PPARα), in women with GDM compared to pregnant women with normoglycemia that were consistently methylated across diverse populations with varying pregnancy durations, and using different diagnostic criteria, methodologies and biological sources. These findings support the candidacy of these three differentially methylated genes as biomarkers for GDM. Furthermore, these genes may provide insight into the pathways that are epigenetically influenced during maternal diabetes and which should be prioritized and replicated in longitudinal studies and in larger populations to ensure their clinical applicability. Finally, we discuss the challenges and limitations of DNA methylation analysis, and the need for DNA methylation profiling to be conducted in different types of maternal diabetes in pregnancy.

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DNA methylation analysis of cord blood samples in neonates born to gestational diabetes mothers diagnosed before 24 gestational weeks

Cited by 6 publications

References 40 publications

Risk factors of neonatal hypoglycemia in neonates born to mothers with gestational diabetes

Risk factors of neonatal hypoglycemia in neonates born to mothers with gestational diabetes

Deciphering the role of immune cell composition in epigenetic age acceleration: Insights from cell‐type deconvolution applied to human blood epigenetic clocks

The role of maternal DNA methylation in pregnancies complicated by gestational diabetes

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