Trophectoderm differentiation to invasive syncytiotrophoblast is promoted by endometrial epithelial cells during human embryo implantation.

STUDY QUESTION: How does the human embryo breach the endometrial epithelium at implantation? SUMMARY ANSWER: Embryo attachment to the endometrial epithelium promotes the formation of multinuclear syncytiotrophoblast from trophectoderm, which goes on to breach the epithelial layer. WHAT IS KNOWN ALREADY: A significant proportion of natural conceptions and assisted reproduction treatments fail due to unsuccessful implantation. The trophectoderm lineage of the embryo attaches to the endometrial epithelium before breaching this barrier to implant into the endometrium. Trophectoderm-derived syncytiotrophoblast has been observed in recent in vitro cultures of peri-implantation embryos, and historical histology has shown invasive syncytiotrophoblast in embryos that have invaded beyond the epithelium, but the cell type mediating invasion of the epithelial layer at implantation is unknown. STUDY DESIGN, SIZE, DURATION: Fresh and frozen human blastocyst-stage embryos (n = 46) or human trophoblast stem cell (TSC) spheroids were co-cultured with confluent monolayers of the Ishikawa endometrial epithelial cell line to model the epithelial phase of implantation in vitro. Systems biology approaches with published transcriptomic datasets were used to model the epithelial phase of implantation in silico. PARTICIPANTS/MATERIALS, SETTING, METHODS: Human embryos surplus to treatment requirements were consented for research. Day 6 blastocysts were co-cultured with Ishikawa cell layers until Day 8, and human TSC spheroids modelling blastocyst trophectoderm were co-cultured with Ishikawa cell layers for 48 h. Embryo and TSC morphology was assessed by immunofluorescence microscopy, and TSC differentiation by real-time quantitative PCR (RT-qPCR) and ELISA. Single-cell human blastocyst transcriptomes, and bulk transcriptomes of TSC and primary human endometrial epithelium were used to model the trophectoderm-epithelium interaction in silico. Hypernetworks, pathway analysis, random forest machine learning and RNA velocity were employed to identify gene networks associated with implantation. MAIN RESULTS AND THE ROLE OF CHANCE: The majority of embryos co-cultured with Ishikawa cell layers from Day 6 to 8 breached the epithelial layer (37/46), and syncytiotrophoblast was seen in all of these. Syncytiotrophoblast was observed at the embryo-epithelium interface before breaching, and syncytiotrophoblast mediated all pioneering breaching events observed (7/7 events). Multiple independent syncytiotrophoblast regions were seen in 26/46 embryos, suggesting derivation from different regions of trophectoderm. Human TSC spheroids co-cultured with Ishikawa layers also exhibited syncytiotrophoblast formation upon invasion into the epithelium. RT-qPCR comparison of TSC spheroids in isolated culture and co-culture demonstrated epithelium-induced upregulation of syncytiotrophoblast genes CGB (P = 0.03) and SDC1 (P = 0.008), and ELISA revealed the induction of hCGß secretion (P = 0.03). Secretory-phase primary endometrial epithelium surface transcriptomes were used to identify trophectoderm surface binding partners to model the embryo-epithelium interface. Hypernetwork analysis established a group of 25 epithelium-interacting trophectoderm genes that were highly connected to the rest of the trophectoderm transcriptome, and epithelium-coupled gene networks in cells of the polar region of the trophectoderm exhibited greater connectivity (P < 0.001) and more organized connections (P < 0.0001) than those in the mural region. Pathway analysis revealed a striking similarity with syncytiotrophoblast differentiation, as 4/6 most highly activated pathways upon TSC-syncytiotrophoblast differentiation (false discovery rate (FDR < 0.026)) were represented in the most enriched pathways of epithelium-coupled gene networks in both polar and mural trophectoderm (FDR < 0.001). Random forest machine learning also showed that 80% of the endometrial epithelium-interacting trophectoderm genes identified in the hypernetwork could be quantified as classifiers of TSC-syncytiotrophoblast differentiation. This multi-model approach suggests that invasive syncytiotrophoblast formation from both polar and mural trophectoderm is promoted by attachment to the endometrial epithelium to enable embryonic invasion. LARGE SCALE DATA: No omics datasets were generated in this study, and those used from previously published studies are cited. LIMITATIONS, REASONS FOR CAUTION: In vitro and in silico models may not recapitulate the dynamic embryo-endometrial interactions that occur in vivo. The influence of other cellular compartments in the endometrium, including decidual stromal cells and leukocytes, was not represented in these models. WIDER IMPLICATIONS OF THE FINDINGS: Understanding the mechanism of human embryo breaching of the epithelium and the gene networks involved is crucial to improve implantation success rates after assisted reproduction. Moreover, early trophoblast lineages arising at the epithelial phase of implantation form the blueprint for the placenta and thus underpin foetal growth trajectories, pregnancy health and offspring health. STUDY FUNDING/COMPETING INTEREST(S): This work was funded by grants from Wellbeing of Women, Diabetes UK, the NIHR Local Comprehensive Research Network and Manchester Clinical Research Facility, and the Department of Health Scientist Practitioner Training Scheme. None of the authors has any conflict of interest to declare.

Gene expression signatures predict response to therapy with growth hormone.

Recombinant human growth hormone (r-hGH) is used as a therapeutic agent for disorders of growth including growth hormone deficiency (GHD) and Turner syndrome (TS). Treatment is costly and current methods to model response are inexact. GHD (n = 71) and TS patients (n = 43) were recruited to study response to r-hGH over 5 years. Analysis was performed using 1219 genetic markers and baseline (pre-treatment) blood transcriptome. Random forest was used to determine predictive value of transcriptomic data associated with growth response. No genetic marker passed the stringency criteria for prediction. However, we identified an identical set of genes in both GHD and TS whose expression could be used to classify therapeutic response to r-hGH with a high accuracy (AUC > 0.9). Combining transcriptomic markers with clinical phenotype was shown to significantly reduce predictive error. This work could be translated into a single genomic test linked to a prediction algorithm to improve clinical management. Trial registration numbers: NCT00256126 and NCT00699855.

Pharmacogenomics applied to recombinant human growth hormone responses in children with short stature.

We present current knowledge concerning the pharmacogenomics of growth hormone therapy in children with short stature. We consider the evidence now emerging for the polygenic nature of response to recombinant human growth hormone (r-hGH). These data are related predominantly to the use of transcriptomic data for prediction. The impact of the complex interactions of developmental phenotype over childhood on response to r-hGH are discussed. Finally, the issues that need to be addressed in order to develop a clinical test are described.

Correction: A restricted spectrum of missense KMT2D variants cause a multiple malformations disorder distinct from Kabuki syndrome.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A restricted spectrum of missense KMT2D variants cause a multiple malformations disorder distinct from Kabuki syndrome.

PURPOSE: To investigate if specific exon 38 or 39 KMT2D missense variants (MVs) cause a condition distinct from Kabuki syndrome type 1 (KS1). METHODS: Multiple individuals, with MVs in exons 38 or 39 of KMT2D that encode a highly conserved region of 54 amino acids flanked by Val3527 and Lys3583, were identified and phenotyped. Functional tests were performed to study their pathogenicity and understand the disease mechanism. RESULTS: The consistent clinical features of the affected individuals, from seven unrelated families, included choanal atresia, athelia or hypoplastic nipples, branchial sinus abnormalities, neck pits, lacrimal duct anomalies, hearing loss, external ear malformations, and thyroid abnormalities. None of the individuals had intellectual disability. The frequency of clinical features, objective software-based facial analysis metrics, and genome-wide peripheral blood DNA methylation patterns in these patients were significantly different from that of KS1. Circular dichroism spectroscopy indicated that these MVs perturb KMT2D secondary structure through an increased disordered to ɑ-helical transition. CONCLUSION: KMT2D MVs located in a specific region spanning exons 38 and 39 and affecting highly conserved residues cause a novel multiple malformations syndrome distinct from KS1. Unlike KMT2D haploinsufficiency in KS1, these MVs likely result in disease through a dominant negative mechanism.

The in vitro functional analysis of single-nucleotide polymorphisms associated with growth hormone (GH) response in children with GH deficiency.

Response to recombinant human growth hormone (r-hGH) in the first year of therapy has been associated with single-nucleotide polymorphisms (SNPs) in children with GH deficiency (GHD). Associated SNPs were screened for regulatory function using a combination of in silico techniques. Four SNPs in regulatory sequences were selected for the analysis of in vitro transcriptional activity (TA). There was an additive effect of the alleles in the four genes associated with good growth response. For rs3110697 within IGFBP3, rs1045992 in CYP19A1 and rs2888586 in SOS1, the variant associated with better growth response showed higher TA with r-hGH treatment. For rs1024531 in GRB10, a negative regulator of IGF-I signalling and growth, the variant associated with better growth response had a significantly lower TA on r-hGH stimulation. These results indicate that specific SNP variants have effects on TA that provide a rationale for their clinical impact on growth response to r-hGH therapy.

Developing the 'omic toolkit of comparative physiologists.

Typical 'omic analyses reduce complex biological systems to simple lists of supposedly independent variables, failing to account for changes in the wider transcriptional landscape. In this commentary, we discuss the utility of network approaches for incorporating this wider context into the study of physiological phenomena. We highlight opportunities to build on traditional network tools by utilising cutting-edge techniques to account for higher order interactions (i.e. beyond pairwise associations) within datasets, allowing for more accurate models of complex 'omic systems. Finally, we show examples of previous works utilising network approaches to gain additional insight into their organisms of interest. As 'omics grow in both their popularity and breadth of application, so does the requirement for flexible analytical tools capable of interpreting and synthesising complex datasets.

Gene Expression Signatures Predict First-Year Response to Somapacitan Treatment in Children With Growth Hormone Deficiency.

CONTEXT: The pretreatment blood transcriptome predicts growth response to daily growth hormone (GH) therapy with high accuracy. OBJECTIVE: Investigate response prediction using pretreatment transcriptome in children with GH deficiency (GHD) treated with once-weekly somapacitan, a novel long-acting GH. METHODS: REAL4 is a randomized, multinational, open-label, active-controlled parallel group phase 3 trial, comprising a 52-week main phase and an ongoing 3-year safety extension (NCT03811535). A total of 128/200 treatment-naïve prepubertal children with GHD consented to baseline blood transcriptome profiling. They were randomized 2:1 to subcutaneous somapacitan (0.16 mg/kg/week) or daily GH (0.034 mg/kg/day). Differential RNA-seq analysis and machine learning were used to predict therapy response. RESULTS: 121/128 samples passed quality control. Children treated with somapacitan (n = 76) or daily GH (n = 45) were categorized based on fastest and slowest growing quartiles at week 52. Prediction of height velocity (HV; cm/year) was excellent for both treatments (out of bag [OOB] area under curve [AUC]: 0.98-0.99; validation AUC: 0.83-0.84), as was prediction of secondary markers of growth response: HV standard deviation score (SDS) (0.99-1.0; 0.75-0.78), change from baseline height SDS (ΔHSDS) (0.98-1.0; 0.61-0.75), and change from baseline insulin-like growth factor-I SDS (ΔIGF-I SDS) (0.96-1.0; 0.85-0.88). Genes previously identified as predictive of GH therapy response were consistently better at predicting the fastest growers in both treatments in this study (OOB AUC: 0.93-0.97) than the slowest (0.67-0.85). CONCLUSION: Pretreatment transcriptome predicts first-year growth response in somapacitan-treated children with GHD. A common set of genes can predict the treatment response to both once-weekly somapacitan and conventional daily GH. This approach could potentially be developed into a clinically applicable pretreatment test to improve clinical management.

Diagnosis of childhood and adolescent growth hormone deficiency using transcriptomic data.

Background: Gene expression (GE) data have shown promise as a novel tool to aid in the diagnosis of childhood growth hormone deficiency (GHD) when comparing GHD children to normal children. The aim of this study was to assess the utility of GE data in the diagnosis of GHD in childhood and adolescence using non-GHD short stature children as a control group. Methods: GE data was obtained from patients undergoing growth hormone stimulation testing. Data were taken for the 271 genes whose expression was utilized in our previous study. The synthetic minority oversampling technique was used to balance the dataset and a random forest algorithm applied to predict GHD status. Results: 24 patients were recruited to the study and eight subsequently diagnosed with GHD. There were no significant differences in gender, age, auxology (height SDS, weight SDS, BMI SDS) or biochemistry (IGF-I SDS, IGFBP-3 SDS) between the GHD and non-GHD subjects. A random forest algorithm gave an AUC of 0.97 (95% CI 0.93 - 1.0) for the diagnosis of GHD. Conclusion: This study demonstrates highly accurate diagnosis of childhood GHD using a combination of GE data and random forest analysis.

Warming during embryogenesis induces a lasting transcriptomic signature in fishes.

Exposure to elevated temperatures during embryogenesis can influence the plasticity of tissues in later life. Despite these long-term changes in plasticity, few differentially expressed genes are ever identified, suggesting that the developmental programming of later life plasticity may occur through the modulation of other aspects of transcriptomic architecture, such as gene network organisation. Here, we use network modelling approaches to demonstrate that warm temperatures during embryonic development (developmental warming) have consistent effects in later life on the organisation of transcriptomic networks across four diverse species of fishes: Scyliorhinus canicula, Danio rerio, Dicentrarchus labrax, and Gasterosteus aculeatus. The transcriptomes of developmentally warmed fishes are characterised by an increased entropy of their pairwise gene interaction networks, implying a less structured, more 'random' set of gene interactions. We also show that, in zebrafish subject to developmental warming, the entropy of an individual gene within a network is associated with that gene's probability of expression change during temperature acclimation in later life. However, this association is absent in animals reared under 'control' conditions. Thus, the thermal environment experienced during embryogenesis can alter transcriptomic organisation in later life, and these changes may influence an individual's responsiveness to future temperature challenges.

Human Mast Cells Upregulate Cathepsin B, a Novel Marker of Itch in Psoriasis.

Mast cells (MCs) contribute to skin inflammation. In psoriasis, the activation of cutaneous neuroimmune networks commonly leads to itch. To dissect the unique contribution of MCs to the cutaneous neuroinflammatory response in psoriasis, we examined their density, distribution, relation to nerve fibres and disease severity, and molecular signature by comparing RNA-seq analysis of MCs isolated from the skin of psoriasis patients and healthy volunteers. In involved psoriasis skin, MCs and Calcitonin Gene-Related Peptide (CGRP)-positive nerve fibres were spatially associated, and the increase of both MC and nerve fibre density correlated with disease severity. Gene set enrichment analysis of differentially expressed genes in involved psoriasis skin showed significant representation of neuron-related pathways (i.e., regulation of neuron projection along with dendrite and dendritic spine morphogenesis), indicating MC engagement in neuronal development and supporting the evidence of close MC-nerve fibre interaction. Furthermore, the analysis of 208 identified itch-associated genes revealed that CTSB, TLR4, and TACR1 were upregulated in MCs in involved skin. In both whole-skin published datasets and isolated MCs, CTSB was found to be a reliable indicator of the psoriasis condition. Furthermore, cathepsin B+ cells were increased in psoriasis skin and cathepsin B+ MC density correlated with disease severity. Therefore, our study provides evidence that cathepsin B could serve as a common indicator of the MC-dependent itch signature in psoriasis.

Monocarboxylate Transporters Are Involved in Extracellular Matrix Remodelling in Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with a five-year survival rate of <8%. PDAC is characterised by desmoplasia with an abundant extracellular matrix (ECM) rendering current therapies ineffective. Monocarboxylate transporters (MCTs) are key regulators of cellular metabolism and are upregulated in different cancers; however, their role in PDAC desmoplasia is little understood. Here, we investigated MCT and ECM gene expression in primary PDAC patient biopsies using RNA-sequencing data obtained from Gene Expression Omnibus. We generated a hypernetwork model from these data to investigate whether a causal relationship exists between MCTs and ECMs. Our analysis of stromal and epithelial tissues (n = 189) revealed nine differentially expressed MCTs, including the upregulation of SLC16A2/6/10 and the non-coding SLC16A1-AS1, and 502 ECMs, including collagens, laminins, and ECM remodelling enzymes (false discovery rate < 0.05). A causal hypernetwork analysis demonstrated a bidirectional relationship between MCTs and ECMs; four MCT and 255 ECM-related transcripts correlated with 90% of the differentially expressed ECMs (n = 376) and MCTs (n = 7), respectively. The hypernetwork model was robust, established by iterated sampling, direct path analysis, validation by an independent dataset, and random forests. This transcriptomic analysis highlights the role of MCTs in PDAC desmoplasia via associations with ECMs, opening novel treatment pathways to improve patient survival.

Identification of human glucocorticoid response markers using integrated multi-omic analysis from a randomized crossover trial.

Background: Glucocorticoids are among the most commonly prescribed drugs, but there is no biomarker that can quantify their action. The aim of the study was to identify and validate circulating biomarkers of glucocorticoid action. Methods: In a randomized, crossover, single-blind, discovery study, 10 subjects with primary adrenal insufficiency (and no other endocrinopathies) were admitted at the in-patient clinic and studied during physiological glucocorticoid exposure and withdrawal. A randomization plan before the first intervention was used. Besides mild physical and/or mental fatigue and salt craving, no serious adverse events were observed. The transcriptome in peripheral blood mononuclear cells and adipose tissue, plasma miRNAomic, and serum metabolomics were compared between the interventions using integrated multi-omic analysis. Results: We identified a transcriptomic profile derived from two tissues and a multi-omic cluster, both predictive of glucocorticoid exposure. A microRNA (miR-122-5p) that was correlated with genes and metabolites regulated by glucocorticoid exposure was identified (p=0.009) and replicated in independent studies with varying glucocorticoid exposure (0.01 ≤ p≤0.05). Conclusions: We have generated results that construct the basis for successful discovery of biomarker(s) to measure effects of glucocorticoids, allowing strategies to individualize and optimize glucocorticoid therapy, and shedding light on disease etiology related to unphysiological glucocorticoid exposure, such as in cardiovascular disease and obesity. Funding: The Swedish Research Council (Grant 2015-02561 and 2019-01112); The Swedish federal government under the LUA/ALF agreement (Grant ALFGBG-719531); The Swedish Endocrinology Association; The Gothenburg Medical Society; Wellcome Trust; The Medical Research Council, UK; The Chief Scientist Office, UK; The Eva Madura's Foundation; The Research Foundation of Copenhagen University Hospital; and The Danish Rheumatism Association. Clinical trial number: NCT02152553.

Several diseases, including asthma, arthritis, some skin conditions, and cancer, are treated with medications called glucocorticoids, which are synthetic versions of human hormones. These drugs are also used to treat people with a condition call adrenal insufficiency who do not produce enough of an important hormone called cortisol. Use of glucocorticoids is very common, the proportion of people in a given country taking them can range from 0.5% to 21% of the population depending on the duration of the treatment. But, like any medication, glucocorticoids have both benefits and risks: people who take glucocorticoids for a long time have an increased risk of diabetes, obesity, cardiovascular disease, and death. Because of the risks associated with taking glucocorticoids, it is very important for physicians to tailor the dose to each patient's needs. Doing this can be tricky, because the levels of glucocorticoids in a patient's blood are not a good indicator of the medication's activity in the body. A test that can accurately measure the glucocorticoid activity could help physicians personalize treatment and reduce harmful side effects. As a first step towards developing such a test, Chantzichristos et al. identified a potential way to measure glucocorticoid activity in patient's blood. In the experiments, blood samples were collected from ten patients with adrenal insufficiency both when they were on no medication, and when they were taking a glucocorticoid to replace their missing hormones. Next, the blood samples were analyzed to determine which genes were turned on and off in each patient with and without the medication. They also compared small molecules in the blood called metabolites and tiny pieces of genetic material called microRNAs that turn genes on and off. The experiments revealed networks of genes, metabolites, and microRNAs that are associated with glucocorticoid activity, and one microRNA called miR-122-5p stood out as a potential way to measure glucocorticoid activity. To verify this microRNA's usefulness, Chantzichristos et al. looked at levels of miR-122-5p in people participating in three other studies and confirmed that it was a good indicator of the glucocorticoid activity. More research is needed to confirm Chantzichristos et al.'s findings and to develop a test that can be used by physicians to measure glucocorticoid activity. The microRNA identified, miR-122-5p, has been previously linked to diabetes, so studying it further may also help scientists understand how taking glucocorticoids may increase the risk of developing diabetes and related diseases.

EVI1 phosphorylation at S436 regulates interactions with CtBP1 and DNMT3A and promotes self-renewal.

The transcriptional regulator EVI1 has an essential role in early development and haematopoiesis. However, acute myeloid leukaemia (AML) driven by aberrantly high EVI1 expression has very poor prognosis. To investigate the effects of post-translational modifications on EVI1 function, we carried out a mass spectrometry (MS) analysis of EVI1 in AML and detected dynamic phosphorylation at serine 436 (S436). Wild-type EVI1 (EVI1-WT) with S436 available for phosphorylation, but not non-phosphorylatable EVI1-S436A, conferred haematopoietic progenitor cell self-renewal and was associated with significantly higher organised transcriptional patterns. In silico modelling of EVI1-S436 phosphorylation showed reduced affinity to CtBP1, and CtBP1 showed reduced interaction with EVI1-WT compared with EVI1-S436A. The motif harbouring S436 is a target of CDK2 and CDK3 kinases, which interacted with EVI1-WT. The methyltransferase DNMT3A bound preferentially to EVI1-WT compared with EVI1-S436A, and a hypomethylated cell population associated by EVI1-WT expression in murine haematopoietic progenitors is not maintained with EVI1-S436A. These data point to EVI1-S436 phosphorylation directing functional protein interactions for haematopoietic self-renewal. Targeting EVI1-S436 phosphorylation may be of therapeutic benefit when treating EVI1-driven leukaemia.

Rachis morphology cannot accurately predict the mechanical performance of primary feathers in extant (and therefore fossil) feathered flyers.

It was previously suggested that the flight ability of feathered fossils could be hypothesized from the diameter of their feather rachises. Central to the idea is the unvalidated assumption that the strength of a primary flight feather (i.e. its material and structural properties) may be consistently calculated from the external diameter of the feather rachis, which is the only dimension that is likely to relate to structural properties available from fossils. Here, using three-point bending tests, the relationship between feather structural properties (maximum bending moment, Mmax and Young's modulus, Ebend) and external morphological parameters (primary feather rachis length, diameter and second moment of area at the calamus) in 180 primary feathers from four species of bird of differing flight style was investigated. Intraspecifically, both Ebend and Mmax were strongly correlated with morphology, decreasing and increasing, respectively, with all three morphological measures. Without accounting for species, however, external morphology was a poor predictor of rachis structural properties, meaning that precise determination of aerial performance in extinct, feathered species from external rachis dimensions alone is not possible. Even if it were possible to calculate the second moment of area of the rachis, our data suggest that feather strength could still not be reliably estimated.