H3K27me3-modulated Hofbauer cell BMP2 signalling enhancement compensates for shallow trophoblast invasion in preeclampsia – ScienceOpen
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      H3K27me3-modulated Hofbauer cell BMP2 signalling enhancement compensates for shallow trophoblast invasion in preeclampsia

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          Summary

          Background

          Preeclampsia (PE) is a common hypertensive pregnancy disorder associated with shallow trophoblast invasion. Although bone morphogenetic protein 2 (BMP2) has been shown to promote trophoblast invasion in vitro, its cellular origin and molecular regulation in placenta, as well as its potential role in PE, has yet to be established. Additionally, whether BMP2 and/or its downstream molecules could serve as potential diagnostic or therapeutic targets for PE has not been explored.

          Methods

          Placentas and sera from PE and healthy pregnant women were subjected to multi-omics analyses, immunoblots, qPCR, and ELISA assays. Immortalized trophoblast cells, primary cultures of human trophoblasts, and first-trimester villous explants were used for in vitro experiments. Adenovirus expressing sFlt-1 (Ad Flt1)-induced PE rat model was used for in vivo studies.

          Findings

          We find globally decreased H3K27me3 modifications and increased BMP2 signalling in preeclamptic placentas, which is negatively correlated with clinical manifestations. BMP2 is derived from Hofbauer cells and epigenetically regulated by H3K27me3 modification. BMP2 promotes trophoblast invasion and vascular mimicry by upregulating BMP6 via BMPR1A-SMAD2/3-SMAD4 signalling. BMP2 supplementation alleviates high blood pressure and fetal growth restriction phenotypes in Ad Flt1-induced rat PE model.

          Interpretation

          Our findings demonstrate that epigenetically regulated Hofbauer cell-derived BMP2 signalling enhancement in late gestation could serve as a compensatory response for shallow trophoblast invasion in PE, suggesting opportunities for diagnostic marker and therapeutic target applications in PE clinical management.

          Funding

          doi 10.13039/501100012166, National Key Research and Development Program of China; (2022YFC2702400), doi 10.13039/501100001809, National Natural Science Foundation of China; (82101784, 82171648, 31988101), and doi 10.13039/501100007129, Natural Science Foundation of Shandong Province; (ZR2020QH051, ZR2020MH039).

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          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
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              PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes.

              DNA microarrays can be used to identify gene expression changes characteristic of human disease. This is challenging, however, when relevant differences are subtle at the level of individual genes. We introduce an analytical strategy, Gene Set Enrichment Analysis, designed to detect modest but coordinate changes in the expression of groups of functionally related genes. Using this approach, we identify a set of genes involved in oxidative phosphorylation whose expression is coordinately decreased in human diabetic muscle. Expression of these genes is high at sites of insulin-mediated glucose disposal, activated by PGC-1alpha and correlated with total-body aerobic capacity. Our results associate this gene set with clinically important variation in human metabolism and illustrate the value of pathway relationships in the analysis of genomic profiling experiments.
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                Author and article information

                Contributors
                Journal
                eBioMedicine
                EBioMedicine
                eBioMedicine
                Elsevier
                2352-3964
                16 June 2023
                July 2023
                16 June 2023
                : 93
                : 104664
                Affiliations
                [a ]Center for Reproductive Medicine, Shandong University, Jinan, Shandong, 250012, China
                [b ]Medical Integration and Practice Center, Shandong University, Jinan, Shandong, 250012, China
                [c ]Department of Cardiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, China
                [d ]Department of Cardiology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, 250021, China
                [e ]Cardiovascular Research Center of the General Medical Services, Massachusetts General Hospital, Boston, MA, 02129, USA
                [f ]Department of Obstetrics and Gynaecology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, 250021, China
                [g ]Department of Anesthesiology, Qilu Hospital of Shandong University, Jinan, Shandong, 250012, China
                [h ]Division of Neonatology, Department of Pediatrics, Massachusetts General Hospital, Boston, MA 02115, USA
                Author notes
                []Corresponding author. Shandong University, Jinan, China. yanli.sdu@ 123456gmail.com
                [∗∗ ]Corresponding author. Massachusetts General Hospital, Boston, MA, USA. wwang@ 123456mgh.harvard.edu
                [∗∗∗ ]Corresponding author. Shandong University, Jinan, China. yyy306@ 123456126.com
                [i]

                Lead contact.

                [j]

                These authors contributed equally.

                Article
                S2352-3964(23)00229-3 104664
                10.1016/j.ebiom.2023.104664
                10300321
                37331163
                14e1a818-aa19-4009-be70-bceda4b2921d
                © 2023 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 21 November 2022
                : 1 June 2023
                : 5 June 2023
                Categories
                Articles

                bmp2,bmp6,h3k27me3,hofbauer cell,trophoblast,preeclampsia
                bmp2, bmp6, h3k27me3, hofbauer cell, trophoblast, preeclampsia

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