Evidence for shared molecular pathways of dysregulated decidualization in preeclampsia and endometrial disorders revealed by microarray data integration

Rabaglino, María Belén; Conrad, Kirk P.

doi:10.1096/fj.201900662r

Cited by 42 publications

(18 citation statements)

References 72 publications

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“…Unlike other mucosal tissues it undergoes dynamic, cyclical changes of shedding, regeneration and differentiation throughout reproductive life coordinated by the hypothalamic-pituitary-ovarian axis. Endometrial dysfunction underpins many common disorders including abnormal uterine bleeding, infertility, miscarriage, pre-eclampsia, endometriosis and endometrial carcinoma that collectively affect many women across the world (1)(2)(3)(4)(5). Throughout reproductive years the functional upper layer of the endometrium, the stratum functionalis, is shed at menstruation.…”

mentioning

confidence: 99%

Mapping the temporal and spatial dynamics of the human endometriumin vivoandin vitro

García-Alonso

Handfield

Roberts

et al. 2021

Preprint

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The endometrium, the mucosal lining of the uterus, undergoes dynamic changes throughout the menstrual cycle in response to ovarian hormones. We have generated single-cell and spatial reference maps of the human uterus and 3D endometrial organoid cultures. We dissect the signalling pathways that determine cell fate of the epithelial lineages in the lumenal and glandular microenvironments. Our benchmark of the endometrial organoids highlights common pathways regulating the differentiation of secretory and ciliated lineage in vivo and in vitro. We show in vitro that downregulation of WNT or NOTCH pathways increases the differentiation efficiency along the secretory and ciliated lineages, respectively. These mechanistic insights provide a platform for future development of treatments for a range of common endometrial disorders including endometriosis and carcinoma.

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confidence: 99%

Mapping the temporal and spatial dynamics of the human endometriumin vivoandin vitro

García-Alonso

Handfield

Roberts

et al. 2021

Preprint

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“…The outputs of these investigations are deposited in the public GEO database, which enables the access to a large amount of high-throughput data 16 . Integration of several datasets could lead to a better characterization of the system under study 5 , as done, for example, for the human endometrial transcriptome 17 . On the other hand, ML algorithms have emerged as useful tools to recognize patterns in data generated by "omics" assays 4 .…”

Section: Discussionmentioning

confidence: 99%

Machine learning approach to integrated endometrial transcriptomic datasets reveals biomarkers predicting uterine receptivity in cattle at seven days after estrous

Rabaglino

Kadarmideen

2020

Sci Rep

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The main goal was to apply machine learning (ML) methods on integrated multi-transcriptomic data, to identify endometrial genes capable of predicting uterine receptivity according to their expression patterns in the cow. Public data from five studies were re-analyzed. In all of them, endometrial samples were obtained at day 6–7 of the estrous cycle, from cows or heifers of four different European breeds, classified as pregnant (n = 26) or not (n = 26). First, gene selection was performed through supervised and unsupervised ML algorithms. Then, the predictive ability of potential key genes was evaluated through support vector machine as classifier, using the expression levels of the samples from all the breeds but one, to train the model, and the samples from that one breed, to test it. Finally, the biological meaning of the key genes was explored. Fifty genes were identified, and they could predict uterine receptivity with an overall 96.1% accuracy, despite the animal’s breed and category. Genes with higher expression in the pregnant cows were related to circadian rhythm, Wnt receptor signaling pathway, and embryonic development. This novel and robust combination of computational tools allowed the identification of a group of biologically relevant endometrial genes that could support pregnancy in the cattle.

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“…So far, more and more studies have shown that abnormal decidualization is an important factor leading to PE (6,(25)(26)(27)(28)(29)(30).…”

Section: Differential Gene Expression In the Decidua Parietalis Of Pementioning

confidence: 99%

Dysfunction of Decidual Macrophages Is a Potential Risk Factor in the Occurrence of Preeclampsia

et al. 2021

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Preeclampsia is a multi-factorial and multi-genetic disorder that affects more than eight million mother and baby pairs each year. Currently, most of the attention to the pathogenesis of preeclampsia has been focused on placenta, but recent progresses suggest that excellent decidualization lays foundation for placentation and growth. Moreover, preeclampsia is associated with an imbalance in immunoregulatory mechanisms, however, how the immune regulatory system in the decidua affects preeclampsia is still unclear. In our study, after intersecting the genes of differentially expressed between preeclampsia and the control gotten by conventional expression profile analysis and the genes contained in the ligand receptor network, we found eight differentially expressed genes in a ligand-receptor relationship, and the eight genes have a characteristic: most of them participate in the interaction between decidual macrophages and other decidual immune cells. The results of single-cell sequencing of decidual cells further demonstrated that decidual macrophages affect the functions of other immune cells through export. As a result, abnormal gene expression affects the export function of decidual macrophages, which in turn affects the interaction of decidual macrophages with other immune cells, thereby destroying the original immune regulation mechanism, and ultimately leading to the occurrence of preeclampsia.

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Evidence for shared molecular pathways of dysregulated decidualization in preeclampsia and endometrial disorders revealed by microarray data integration

Cited by 42 publications

References 72 publications

Mapping the temporal and spatial dynamics of the human endometriumin vivoandin vitro

Mapping the temporal and spatial dynamics of the human endometriumin vivoandin vitro

Machine learning approach to integrated endometrial transcriptomic datasets reveals biomarkers predicting uterine receptivity in cattle at seven days after estrous

Dysfunction of Decidual Macrophages Is a Potential Risk Factor in the Occurrence of Preeclampsia

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