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      Epigenome wide association study in peripheral blood of pregnant women identifies potential metabolic pathways related to gestational diabetes

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          ABSTRACT

          Gestational diabetes mellitus (GDM) increases the risk of developing metabolic disorders in both pregnant women and their offspring. Factors such as nutrition or the intrauterine environment may play an important role, through epigenetic mechanisms, in the development of GDM. The aim of this work is to identify epigenetic marks involved in the mechanisms or pathways related to gestational diabetes. A total of 32 pregnant women were selected, 16 of them with GDM and 16 non-GDM. DNA methylation pattern was obtained from Illumina Methylation Epic BeadChip, from peripheral blood samples at the diagnostic visit (26–28 weeks). Differential methylated positions (DMPs) were extracted using ChAMP and limma package in R 2.9.10, with a threshold of FDR <0.05, deltabeta >|5|% and B >0. A total of 1.141 DMPs were found, and 714 were annotated in genes. A functional analysis was performed, and we found 23 genes significantly related to carbohydrate metabolism. Finally, a total of 27 DMPs were correlated with biochemical variables such as glucose levels at different points of oral glucose tolerance test, fasting glucose, cholesterol, HOMAIR and HbA1c, at different visits during pregnancy and postpartum. Our results show that there is a differentiated methylation pattern between GDM and non-GDM. Furthermore, the genes annotated to the DMPs could be implicated in the development of GDM as well as in alterations in related metabolic variables.

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          Homeostasis model assessment: insulin resistance and ?-cell function from fasting plasma glucose and insulin concentrations in man

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            DNA methylation and its basic function.

            In the mammalian genome, DNA methylation is an epigenetic mechanism involving the transfer of a methyl group onto the C5 position of the cytosine to form 5-methylcytosine. DNA methylation regulates gene expression by recruiting proteins involved in gene repression or by inhibiting the binding of transcription factor(s) to DNA. During development, the pattern of DNA methylation in the genome changes as a result of a dynamic process involving both de novo DNA methylation and demethylation. As a consequence, differentiated cells develop a stable and unique DNA methylation pattern that regulates tissue-specific gene transcription. In this chapter, we will review the process of DNA methylation and demethylation in the nervous system. We will describe the DNA (de)methylation machinery and its association with other epigenetic mechanisms such as histone modifications and noncoding RNAs. Intriguingly, postmitotic neurons still express DNA methyltransferases and components involved in DNA demethylation. Moreover, neuronal activity can modulate their pattern of DNA methylation in response to physiological and environmental stimuli. The precise regulation of DNA methylation is essential for normal cognitive function. Indeed, when DNA methylation is altered as a result of developmental mutations or environmental risk factors, such as drug exposure and neural injury, mental impairment is a common side effect. The investigation into DNA methylation continues to show a rich and complex picture about epigenetic gene regulation in the central nervous system and provides possible therapeutic targets for the treatment of neuropsychiatric disorders.
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              DNA methylation arrays as surrogate measures of cell mixture distribution

              Background There has been a long-standing need in biomedical research for a method that quantifies the normally mixed composition of leukocytes beyond what is possible by simple histological or flow cytometric assessments. The latter is restricted by the labile nature of protein epitopes, requirements for cell processing, and timely cell analysis. In a diverse array of diseases and following numerous immune-toxic exposures, leukocyte composition will critically inform the underlying immuno-biology to most chronic medical conditions. Emerging research demonstrates that DNA methylation is responsible for cellular differentiation, and when measured in whole peripheral blood, serves to distinguish cancer cases from controls. Results Here we present a method, similar to regression calibration, for inferring changes in the distribution of white blood cells between different subpopulations (e.g. cases and controls) using DNA methylation signatures, in combination with a previously obtained external validation set consisting of signatures from purified leukocyte samples. We validate the fundamental idea in a cell mixture reconstruction experiment, then demonstrate our method on DNA methylation data sets from several studies, including data from a Head and Neck Squamous Cell Carcinoma (HNSCC) study and an ovarian cancer study. Our method produces results consistent with prior biological findings, thereby validating the approach. Conclusions Our method, in combination with an appropriate external validation set, promises new opportunities for large-scale immunological studies of both disease states and noxious exposures.
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                Author and article information

                Journal
                Epigenetics
                Epigenetics
                Epigenetics
                Taylor & Francis
                1559-2294
                1559-2308
                16 May 2023
                2023
                16 May 2023
                : 18
                : 1
                : 2211369
                Affiliations
                [a ]Departamento de Endocrinología y Nutrición, Hospital Universitario Virgen de la Victoria; , Málaga, Spain
                [b ]Obesidad, diabetes y sus comorbilidades: prevención y tratamiento, Instituto de Investigación Biomédica de Málaga (IBIMA)-Plataforma Bionand; , Málaga, Spain
                [c ]Departamento de Bioquímica y Biología Molecular 2, Universidad de Granada; , Granada, Spain
                [d ]Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III; , Madrid, Spain
                [e ]Departamento de Medicina y Dermatología, Universidad de Málaga; , Málaga, Spain
                Author notes
                CONTACT Sonsoles Morcillo sonsoles.morcillo@ 123456ibima.eu
                María Molina-Vega molinavegamaria@ 123456gmail.com Departamento de Endocrinología y Nutrición, Hospital Universitario Virgen de la Victoria; , Campus de Teatinos, S/N, 29010 Málaga, Spain
                [*]

                These authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0001-6932-5637
                Article
                2211369
                10.1080/15592294.2023.2211369
                10190180
                37192269
                cff0e5e3-b5a2-4fac-b020-d851845fba0b
                © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

                History
                Page count
                Figures: 3, Tables: 2, References: 48, Pages: 1
                Categories
                Research Article
                Research Article

                Genetics
                gestational diabetes mellitus,epigenome-wide association,epigenetics,diabetes,metabolism,glucose homoeostasis

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