Comprehensive Analysis of Gene Expression Profiles and DNA Methylome reveals Oas1, Ppie, Polr2g as Pathogenic Target Genes of Gestational Diabetes Mellitus

Zhang, Yan; Zhang, Tiancheng; Chen, Yunyan

doi:10.1038/s41598-018-34292-z

Cited by 13 publications

(11 citation statements)

References 28 publications

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“…Only in the case of the MSLN gene, a typical negative correlation between gene expression and DNA methylation level was found, as significant hypermethylation in the CpG island and downregulated transcription were noted [56]. Similar differences were found in placenta samples analyzed in 32 GDM pregnant women and 31 controls [57]. The authors attempted to assess biological processes and mechanisms, which affect the occurrence and development of GDM, by the analysis of DNA methylation data and the gene expression profiles.…”

Section: Pregnant Women With Gdm Have a Different Dna Methylation Profile Than In Non-gdm Pregnanciesmentioning

confidence: 88%

Epigenetic Changes in Gestational Diabetes Mellitus

Dłuski

Wolińska

Skrzypczak

2021

IJMS

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Gestational diabetes mellitus (GDM) is defined as carbohydrate intolerance that appears or is for the first time diagnosed during pregnancy. It can lead to many complications in the mother and in the offspring, so diagnostics and management of GDM are important to avoid adverse pregnancy outcomes. Epigenetic studies revealed the different methylation status of genes in pregnancies with GDM compared to pregnancies without GDM. A growing body of evidence shows that the GDM can affect not only the course of the pregnancy, but also the development of the offspring, thus contributing to long-term effects and adverse health outcomes of the progeny. Epigenetic changes occur through histone modification, DNA methylation, and disrupted function of non-coding ribonucleic acid (ncRNA) including microRNAs (miRNAs). In this review, we focus on the recent knowledge about epigenetic changes in GDM. The analysis of this topic may help us to understand pathophysiological mechanisms in GDM and find a solution to prevent their consequences.

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Section: Pregnant Women With Gdm Have a Different Dna Methylation Profile Than In Non-gdm Pregnanciesmentioning

confidence: 88%

Epigenetic Changes in Gestational Diabetes Mellitus

Dłuski

Wolińska

Skrzypczak

2021

IJMS

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“…By contrast, maternal epigenetic modifications reflect the state of different cell types across tissues as they reprogram to prepare for fetal growth [74,75]. Quantification of these modificationsby measuring DNA methylation, histone markers, and chromatin accessibility in the cell subsets of interestoffers insights into whether different cell types in the maternal-fetal interface are adapting properly for a successful pregnancy [76,77].…”

Section: Genetics and Epigenetics For Characterizing Pregnancymentioning

confidence: 99%

Data-Driven Modeling of Pregnancy-Related Complications

Espinosa

Becker

Marić

et al. 2021

Trends in Molecular Medicine

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A multitude of clinical, biological, environmental, and demographic factors influence the trajectory of a pregnancy. Maternal genetics, environment, stress, nutrition, medical history, socioeconomic status, and racial and ethnic background all play a role in determining the success of a pregnancy. Diverse data sources are available for the study of pregnancy and prediction of adverse outcomes, including electronic health records (EHRs) and administrative claims data, high-throughput multiomics data for characterizing biological systems, and more complex sources like time series, imaging and video data, and text. Recent advances in multiview, multitask, and deep learning allow joint modeling across data sources as well as across outcomes and demonstrate the vast potential of such integrated approaches.

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“…For this study we did not set a minimum ratio of differential expression to methylation threshold, but we selected those loci with adjusted significance, as previously described . The methylation data were obtained from a longstanding array (Illumina HumanMethylation27 BeadChip) that showed small significant methylation differences between haplogroups H and J.…”

Section: Discussionmentioning

confidence: 99%

“…To identify the overlapped genes with an inverse correlation between methylation and expression (i.e., genes that were differentially methylated and expressed between the 2 haplogroups in an inverse manner), we crossed the significant genes and differentially methylated loci of both assays, as previously described .…”

Section: Methodsmentioning

confidence: 99%

Differential Association of Mitochondrial DNA Haplogroups J and H With the Methylation Status of Articular Cartilage: Potential Role in Apoptosis and Metabolic and Developmental Processes

Cortés-Pereira

Fernández‐Tajes

Fernández-Moreno

et al. 2019

Arthritis & Rheumatology

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Objective. To analyze the influence of mitochondrial genome variation on the DNA methylome of articular cartilage. Methods. DNA methylation profiling was performed using data deposited in the NCBI Gene Expression Omnibus database (accession no. GSE43269). Data were obtained for 14 cartilage samples from subjects with haplogroup J and 20 cartilage samples from subjects with haplogroup H. Subsequent validation was performed in an independent subset of 7 subjects with haplogroup J and 9 with haplogroup H by RNA-seq. Correlated genes were validated by real-time polymerase chain reaction in an independent cohort of 12 subjects with haplogroup J and 12 with haplogroup H. Appropriate analyses were performed using R Bioconductor and qBasePlus software, and gene ontology analysis was conducted using DAVID version 6.8.Results. DNA methylation profiling revealed 538 differentially methylated loci, while whole-transcriptome profiling identified 2,384 differentially expressed genes, between cartilage samples from subjects with haplogroup H and those with haplogroup J. Seventeen genes showed an inverse correlation between methylation and expression. In terms of gene ontology, differences in correlations between methylation and expression were also detected between cartilage from subjects with haplogroup H and those with haplogroup J, highlighting a significantly enhanced apo ptotic process in cartilage from subjects with haplogroup H (P = 0.007 for methylation and P = 0.019 for expression) and repressed apoptotic process in cartilage from subjects with haplogroup J (P = 0.021 for methylation), as well as a significant enrichment of genes related to metabolic processes (P = 1.93 × 10 −4 for methylation and P = 6.79 x 10 −4 for expression) and regulation of gene expression (P = 0.012 for methylation) in cartilage from subjects with haplogroup H, and to developmental processes (P = 0.015 for methylation and P = 8.25 x 10 −12 for expression) in cartilage from subjects with haplogroup J.Conclusion. Mitochondrial DNA variation differentially associates with the methylation status of articular cartilage by acting on key mechanisms involved in osteoarthritis, such as apoptosis and metabolic and developmental processes.

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Comprehensive Analysis of Gene Expression Profiles and DNA Methylome reveals Oas1, Ppie, Polr2g as Pathogenic Target Genes of Gestational Diabetes Mellitus

Cited by 13 publications

References 28 publications

Epigenetic Changes in Gestational Diabetes Mellitus

Epigenetic Changes in Gestational Diabetes Mellitus

Data-Driven Modeling of Pregnancy-Related Complications

Differential Association of Mitochondrial DNA Haplogroups J and H With the Methylation Status of Articular Cartilage: Potential Role in Apoptosis and Metabolic and Developmental Processes

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