Comparison of DNA methylation profiles associated with spontaneous preterm birth in placenta and cord blood

Epigenetic Responses to Nonchemical Stressors: Potential Molecular Links to Perinatal Health Outcomes

PURPOSE OF REVIEW

We summarize the recent literature investigating exposure to four nonchemical stressors (financial stress, racism, psychosocial stress, and trauma) and DNA methylation, miRNA expression, and mRNA expression. We also highlight the relationships between these epigenetic changes and six critical perinatal outcomes (preterm birth, low birth weight, preeclampsia, gestational diabetes, childhood allergic disease, and childhood neurocognition).

RECENT FINDINGS

Multiple studies have found financial stress, psychosocial stress, and trauma to be associated with DNA methylation and/or miRNA and mRNA expression. Fewer studies have investigated the effects of racism. The majority of studies assessed epigenetic or genomic changes in maternal blood, cord blood, or placenta. Several studies included multi-OMIC assessments in which DNA methylation and/or miRNA expression were associated with gene expression. There is strong evidence for the role of epigenetics in driving the health outcomes considered. A total of 22 biomarkers, including numerous HPA axis genes, were identified to be epigenetically altered by both stressors and outcomes. Epigenetic changes related to inflammation, the immune and endocrine systems, and cell growth and survival were highlighted across numerous studies. Maternal exposure to nonchemical stressors is associated with epigenetic and/or genomic changes in a tissue-specific manner among inflammatory, immune, endocrine, and cell growth-related pathways, which may act as mediating pathways to perinatal health outcomes. Future research can test the mediating role of the specific biomarkers identified as linked with both stressors and outcomes. Understanding underlying epigenetic mechanisms altered by nonchemical stressors can provide a better understanding of how chemical and nonchemical exposures interact.

EMQN best practice guidelines for genetic testing in hereditary breast and ovarian cancer

Hereditary Breast and Ovarian Cancer (HBOC) is a genetic condition associated with increased risk of cancers. The past decade has brought about significant changes to hereditary breast and ovarian cancer (HBOC) diagnostic testing with new treatments, testing methods and strategies, and evolving information on genetic associations. These best practice guidelines have been produced to assist clinical laboratories in effectively addressing the complexities of HBOC testing, while taking into account advancements since the last guidelines were published in 2007. These guidelines summarise cancer risk data from recent studies for the most commonly tested high and moderate risk HBOC genes for laboratories to refer to as a guide. Furthermore, recommendations are provided for somatic and germline testing services with regards to clinical referral, laboratory analyses, variant interpretation, and reporting. The guidelines present recommendations where 'must' is assigned to advocate that the recommendation is essential; and 'should' is assigned to advocate that the recommendation is highly advised but may not be universally applicable. Recommendations are presented in the form of shaded italicised statements throughout the document, and in the form of a table in supplementary materials (Table S4). Finally, for the purposes of encouraging standardisation and aiding implementation of recommendations, example report wording covering the essential points to be included is provided for the most common HBOC referral and reporting scenarios. These guidelines are aimed primarily at genomic scientists working in diagnostic testing laboratories.

m6A Methylated Long Noncoding RNA LOC339803 Regulates Intestinal Inflammatory Response

Cytokine mediated sustained inflammation increases the risk to develop different complex chronic inflammatory diseases, but the implicated mechanisms remain unclear. Increasing evidence shows that long noncoding RNAs (lncRNAs) play key roles in the pathogenesis of inflammatory disorders, while inflammation associated variants are described to affect their function or essential RNA modifications as N6-methyladenosine (m6A) methylation, increasing predisposition to inflammatory diseases. Here, the functional implication of the intestinal inflammation associated lncRNA LOC339803 in the production of cytokines by intestinal epithelial cells is described. Allele-specific m6A methylation is found to affect YTHDC1 mediated protein binding affinity. LOC339803-YTHDC1 interaction dictates chromatin localization of LOC339803 ultimately inducing the expression of NFκB mediated proinflammatory cytokines and contributing to the development of intestinal inflammation. These findings are confirmed using human intestinal biopsy samples from different intestinal inflammatory conditions and controls. Additionally, it is demonstrated that LOC339803 targeting can be a useful strategy for the amelioration of intestinal inflammation in vitro and ex vivo. Overall, the results support the importance of the methylated LOC339803 lncRNA as a mediator of intestinal inflammation, explaining genetic susceptibility and presenting this lncRNA as a potential novel therapeutic target for the treatment of inflammatory intestinal disorders.

Epigenetic associations in HPA axis genes related to bronchopulmonary dysplasia and antenatal steroids

BACKGROUND

Bronchopulmonary dysplasia (BPD), a common morbidity among very preterm infants, is associated with chronic disease and neurodevelopmental impairments. A hypothesized mechanism for these outcomes lies in altered glucocorticoid (GC) activity. We hypothesized that BPD and its treatments may result in epigenetic differences in the hypothalamic-pituitary-adrenal (HPA) axis, which is modulated by GC, and could be ascertained using an established GC risk score and DNA methylation (DNAm) of HPA axis genes.

METHODS

DNAm was quantified from buccal tissue (ECHO-NOVI) and from neonatal blood spots (ELGAN ECHO) via the EPIC microarray. Prenatal maternal characteristics, pregnancy complication, and neonatal medical complication data were collected from medical record review and maternal interviews.

RESULTS

The GC score was not associated with steroid exposure or BPD. However, six HPA genes involved in stress response regulation demonstrated differential methylation with antenatal steroid exposure; two CpGs within FKBP5 and POMC were differentially methylated with BPD severity. These findings were sex-specific in both cohorts; males had greater magnitude of differential methylation within these genes.

CONCLUSIONS

These findings suggest that BPD severity and antenatal steroids are associated with DNAm at some HPA genes in very preterm infants and the effects appear to be sex-, tissue-, and age-specific.

IMPACT

This study addresses bronchopulmonary dysplasia (BPD), an important health outcome among preterm neonates, and interrogates a commonly studied pathway, the hypothalamic-pituitary-adrenal (HPA) axis. The combination of BPD, the HPA axis, and epigenetic markers has not been previously reported. In this study, we found that BPD itself was not associated with epigenetic responses in the HPA axis in infants born very preterm; however, antenatal treatment with steroids was associated with epigenetic responses.

"Deficiency in ELF4, X-Linked": a Monogenic Disease Entity Resembling Behçet's Syndrome and Inflammatory Bowel Disease

Defining monogenic drivers of autoinflammatory syndromes elucidates mechanisms of disease in patients with these inborn errors of immunity and can facilitate targeted therapeutic interventions. Here, we describe a cohort of patients with a Behçet's- and inflammatory bowel disease (IBD)-like disorder termed "deficiency in ELF4, X-linked" (DEX) affecting males with loss-of-function variants in the ELF4 transcription factor gene located on the X chromosome. An international cohort of fourteen DEX patients was assessed to identify unifying clinical manifestations and diagnostic criteria as well as collate findings informing therapeutic responses. DEX patients exhibit a heterogeneous clinical phenotype including weight loss, oral and gastrointestinal aphthous ulcers, fevers, skin inflammation, gastrointestinal symptoms, arthritis, arthralgia, and myalgia, with findings of increased inflammatory markers, anemia, neutrophilic leukocytosis, thrombocytosis, intermittently low natural killer and class-switched memory B cells, and increased inflammatory cytokines in the serum. Patients have been predominantly treated with anti-inflammatory agents, with the majority of DEX patients treated with biologics targeting TNFα.

The Role of Genetics in Preterm Birth

Preterm birth (PTB), defined as the birth of a child before 37 completed weeks gestation, affects approximately 11% of live births and is the leading cause of death in children under 5 years. PTB is a complex disease with multiple risk factors including genetic variation. Much research has aimed to establish the biological mechanisms underlying PTB often through identification of genetic markers for PTB risk. The objective of this review is to present a comprehensive and updated summary of the published data relating to the field of PTB genetics. A literature search in PubMed was conducted and English studies related to PTB genetics were included. Genetic studies have identified genes within inflammatory, immunological, tissue remodeling, endocrine, metabolic, and vascular pathways that may be involved in PTB. However, a substantial proportion of published data have been largely inconclusive and multiple studies had limited power to detect associations. On the contrary, a few large hypothesis-free approaches have identified and replicated multiple novel variants associated with PTB in different cohorts. Overall, attempts to predict PTB using single "-omics" datasets including genomic, transcriptomic, and epigenomic biomarkers have been mostly unsuccessful and have failed to translate to the clinical setting. Integration of data from multiple "-omics" datasets has yielded the most promising results.

Encephalopsin (OPN3) is required for normal refractive development and the GO/GROW response to induced myopia

Purpose

Myopia, or nearsightedness, is the most common form of refractive error and is increasing in prevalence. While significant efforts have been made to identify genetic variants that predispose individuals to myopia, these variants are believed to account for only a small portion of the myopia prevalence, leading to a feedback theory of emmetropization, which depends on the active perception of environmental visual cues. Consequently, there has been renewed interest in studying myopia in the context of light perception, beginning with the opsin family of G-protein coupled receptors (GPCRs). Refractive phenotypes have been characterized in every opsin signaling pathway studied, leaving only Opsin 3 (OPN3), the most widely expressed and blue-light sensing noncanonical opsin, to be investigated for function in the eye and refraction.

Methods

Opn3 expression was assessed in various ocular tissues using an Opn3eGFP reporter. Weekly refractive development in Opn3 retinal and germline mutants from 3 to 9 weeks of age was measured using an infrared photorefractor and spectral domain optical coherence tomography (SD-OCT). Susceptibility to lens-induced myopia was then assessed using skull-mounted goggles with a -30 diopter experimental and a 0 diopter control lens. Mouse eye biometry was similarly tracked from 3 to 6 weeks. A myopia gene expression signature was assessed 24 h after lens induction for germline mutants to further assess myopia-induced changes.

Results

Opn3 was found to be expressed in a subset of retinal ganglion cells and a limited number of choroidal cells. Based on an assessment of Opn3 mutants, the OPN3 germline, but not retina conditional Opn3 knockout, exhibits a refractive myopia phenotype, which manifests in decreased lens thickness, shallower aqueous compartment depth, and shorter axial length, atypical of traditional axial myopias. Despite the short axial length, Opn3 null eyes demonstrate normal axial elongation in response to myopia induction and mild changes in choroidal thinning and myopic shift, suggesting that susceptibility to lens-induced myopia is largely unchanged. Additionally, the Opn3 null retinal gene expression signature in response to induced myopia after 24 h is distinct, with opposing Ctgf, Cx43, and Egr1 polarity compared to controls.

Conclusions

The data suggest that an OPN3 expression domain outside the retina can control lens shape and thus the refractive performance of the eye. Prior to this study, the role of Opn3 in the eye had not been investigated. This work adds OPN3 to the list of opsin family GPCRs that are implicated in emmetropization and myopia. Further, the work to exclude retinal OPN3 as the contributing domain in this refractive phenotype is unique and suggests a distinct mechanism when compared to other opsins.

Functional analyses of rare germline BRCA1 variants by transcriptional activation and homologous recombination repair assays

BACKGROUND

Damaging alterations in the BRCA1 gene have been extensively described as one of the main causes of hereditary breast and ovarian cancer (HBOC). BRCA1 alterations can lead to impaired homologous recombination repair (HRR) of double-stranded DNA breaks, a process which involves the RING, BRCT and coiled-coil domains of the BRCA1 protein. In addition, the BRCA1 protein is involved in transcriptional activation (TA) of several genes through its C-terminal BRCT domain.

METHODS

In this study, we have investigated the effect on HRR and TA of 11 rare BRCA1 missense variants classified as variants of uncertain clinical significance (VUS), located within or in close proximity to the BRCT domain, with the aim of generating additional knowledge to guide the correct classification of these variants. The variants were selected from our previous study "BRCA1 Norway", which is a collection of all BRCA1 variants detected at the four medical genetic departments in Norway.

RESULTS

All variants, except one, showed a significantly reduced HRR activity compared to the wild type (WT) protein. Two of the variants (p.Ala1708Val and p.Trp1718Ser) also exhibited low TA activity similar to the pathogenic controls. The variant p.Trp1718Ser could be reclassified to likely pathogenic. However, for ten of the variants, the total strength of pathogenic evidence was not sufficient for reclassification according to the CanVIG-UK BRCA1/BRCA2 gene-specific guidelines for variant interpretation.

CONCLUSIONS

When including the newly achieved functional evidence with other available information, one VUS was reclassified to likely pathogenic. Eight of the investigated variants affected only one of the assessed activities of BRCA1, highlighting the importance of comparing results obtained from several functional assays to better understand the consequences of BRCA1 variants on protein function. This is especially important for multifunctional proteins such as BRCA1.

Enhancer-FRL: Improved and Robust Identification of Enhancers and Their Activities Using Feature Representation Learning

Enhancers are crucial for precise regulation of gene expression, while enhancer identification and strength prediction are challenging because of their free distribution and tremendous number of similar fractions in the genome. Although several bioinformatics tools have been developed, shortfalls in these models remain, and their performances need further improvement. In the present study, a two-layer predictor called Enhancer-FRL was proposed for identifying enhancers (enhancers or nonenhancers) and their activities (strong and weak). More specifically, to build an efficient model, the feature representation learning scheme was applied to generate a 50D probabilistic vector based on 10 feature encodings and five machine learning algorithms. Subsequently, the multiview probabilistic features were integrated to construct the final prediction model. Compared with the single feature-based model, Enhancer-FRL showed significant performance improvement and model robustness. Performance assessment on the independent test dataset indicated that the proposed model outperformed state-of-the-art available toolkits. The webserver Enhancer-FRL is freely accessible at http://lab.malab.cn/∼wangchao/softwares/Enhancer-FRL/, The code and datasets can be downloaded at the webserver page or at the Github https://github.com/wangchao-malab/Enhancer-FRL/.

Notch signaling pathway: a comprehensive prognostic and gene expression profile analysis in breast cancer

Breast cancer is a complex disease exhibiting a great degree of heterogeneity due to different molecular subtypes. Notch signaling regulates the differentiation of breast epithelial cells during normal development and plays a crucial role in breast cancer progression through the abnormal expression of the Notch up-and down-stream effectors. To date, there are only a few patient-centered clinical studies using datasets characterizing the role of Notch signaling pathway regulators in breast cancer; thus, we investigate the role and functionality of these factors in different subtypes using publicly available databases containing records from large studies. High-throughput genomic data and clinical information extracted from TCGA were analyzed. We performed Kaplan-Meier survival and differential gene expression analyses using the HALLMARK_NOTCH_SIGNALING gene set. To determine if epigenetic regulation of the Notch regulators contributes to their expression, we analyzed methylation levels of these factors using the TCGA HumanMethylation450 Array data. Notch receptors and ligands expression is generally associated with the tumor subtype, grade, and stage. Furthermore, we showed gene expression levels of most Notch factors were associated with DNA methylation rate. Modulating the expression levels of Notch receptors and effectors can be a potential therapeutic approach for breast cancer. As we outline herein, elucidating the novel prognostic and regulatory roles of Notch implicate this pathway as an essential mediator controlling breast cancer progression.

Deep learning and multi-omics approach to predict drug responses in cancer

BACKGROUND

Cancers are genetically heterogeneous, so anticancer drugs show varying degrees of effectiveness on patients due to their differing genetic profiles. Knowing patient's responses to numerous cancer drugs are needed for personalized treatment for cancer. By using molecular profiles of cancer cell lines available from Cancer Cell Line Encyclopedia (CCLE) and anticancer drug responses available in the Genomics of Drug Sensitivity in Cancer (GDSC), we will build computational models to predict anticancer drug responses from molecular features.

RESULTS

We propose a novel deep neural network model that integrates multi-omics data available as gene expressions, copy number variations, gene mutations, reverse phase protein array expressions, and metabolomics expressions, in order to predict cellular responses to known anti-cancer drugs. We employ a novel graph embedding layer that incorporates interactome data as prior information for prediction. Moreover, we propose a novel attention layer that effectively combines different omics features, taking their interactions into account. The network outperformed feedforward neural networks and reported 0.90 for [Formula: see text] values for prediction of drug responses from cancer cell lines data available in CCLE and GDSC.

CONCLUSION

The outstanding results of our experiments demonstrate that the proposed method is capable of capturing the interactions of genes and proteins, and integrating multi-omics features effectively. Furthermore, both the results of ablation studies and the investigations of the attention layer imply that gene mutation has a greater influence on the prediction of drug responses than other omics data types. Therefore, we conclude that our approach can not only predict the anti-cancer drug response precisely but also provides insights into reaction mechanisms of cancer cell lines and drugs as well.

Recursive integration of synergised graph representations of multi-omics data for cancer subtypes identification

Cancer subtypes identification is one of the critical steps toward advancing personalized anti-cancerous therapies. Accumulation of a massive amount of multi-platform omics data measured across the same set of samples provides an opportunity to look into this deadly disease from several views simultaneously. Few integrative clustering approaches are developed to capture shared information from all the views to identify cancer subtypes. However, they have certain limitations. The challenge here is identifying the most relevant feature space from each omic view and systematically integrating them. Both the steps should lead toward a global clustering solution with biological significance. In this respect, a novel multi-omics clustering algorithm named RISynG (Recursive Integration of Synergised Graph-representations) is presented in this study. RISynG represents each omic view as two representation matrices that are Gramian and Laplacian. A parameterised combination function is defined to obtain a synergy matrix from these representation matrices. Then a recursive multi-kernel approach is applied to integrate the most relevant, shared, and complementary information captured via the respective synergy matrices. At last, clustering is applied to the integrated subspace. RISynG is benchmarked on five multi-omics cancer datasets taken from The Cancer Genome Atlas. The experimental results demonstrate RISynG’s efficiency over the other approaches in this domain.

Integrated single-cell RNA-seq and DNA methylation reveal the effects of air pollution in patients with recurrent spontaneous abortion

Background

Maternal air pollutants exposure is associated with a number of adverse pregnancy outcomes, including recurrent spontaneous abortion (RSA). However, the underlying mechanisms are still unknown. The present study aimed to understand the mechanism of RSA and its relationship with air pollution exposure. We compared data of decidual tissue from individuals with induced abortions and those with RSA by bulk RNA sequencing (RNA-seq), reduced representation bisulfite sequencing (RRBS), and single-cell RNA sequencing (scRNA-seq). Differentially expressed genes (DEGs) were verified using RT-qPCR and pyrosequencing. A logistic regression model was used to investigate the association between air pollutants exposure and RSA.

Results

We identified 98 DEGs with aberrant methylation by overlapping the RRBS and RNA-seq data. Nineteen immune cell subsets were identified. Compared with normal controls, NK cells and macrophages accounted for different proportions in the decidua of patients with RSA. We observed that the methylation and expression of IGF2BP1 were different between patients with RSA and controls. Furthermore, we observed significant positive associations between maternal air pollutants exposure during the year prior to pregnancy and in early pregnancy and the risk of RSA. Mediation analyses suggested that 24.5% of the effects of air pollution on the risk of RSA were mediated through IGF2BP1 methylation.

Conclusion

These findings reveal a comprehensive cellular and molecular mechanism of RSA and suggest that air pollution might cause pregnancy loss by affecting the methylation level of the IGF2BP1 promoter.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-022-01327-2.

LncRNA H19 is a potential biomarker and correlated with immune infiltration in thyroid carcinoma

The bulk of evidence has revealed that dysregulated expression of long non-coding RNAs (lncRNAs) plays a crucial functional role in cancer biology. However, the mechanistic role of lncRNAs in the initiation, progression and immune landscape of thyroid carcinoma (THCA) still remains largely unknown. This study aimed to explore the significance of H19 in the diagnostic and immune related roles in THCA. The expression level of H19 was analyzed using the TNMplot, GSCA, UALCAN, GEPIA, Wanderer, UCSC Xena and GEO databases. Enrichment analyses were performed to investigate the possible underlying biological pathways by LinkedOmics. Moreover, cBioPortal web tool was used to analyze genetic alterations of H19. Finally, we used TIMER and GEPIA databases to explore the correlations between H19 and tumor-infiltrated immune cells and immune markers. LncRNA H19 was differentially expressed in various cancers and also remarkably downregulated in the THCA tissues compared to the normal ones. Genetic alteration analysis revealed that there was a significant correlation between alterations in H19 and overall survival of THCA patients. Furthermore, enrichment analysis indicated the functional relationship between co-expression network of H19 and extracellular structure organization, and immune microenvironment. In addition, H19 expression was positively correlated with infiltration level of diverse immune cells including CD4+T cells, CD8+T cells, B cells, dendritic cells, neutrophils and macrophages and was closely associated with multiple immune markers in THCA. Conclusively, this comprehensive study indicates the lncRNA H19 might have a significant role in the initiation and progression of THCA. Hence, our findings might provide ideas on the selection of novel diagnostic biomarkers and assist in the designing of the effective pharmaceutical targets for THCA.

LncRNA H19 is a potential biomarker and correlated with immune infiltration in thyroid carcinoma

The bulk of evidence has revealed that dysregulated expression of long non-coding RNAs (lncRNAs) plays a crucial functional role in cancer biology. However, the mechanistic role of lncRNAs in the initiation, progression and immune landscape of thyroid carcinoma (THCA) still remains largely unknown. This study aimed to explore the significance of H19 in the diagnostic and immune related roles in THCA. The expression level of H19 was analyzed using the TNMplot, GSCA, UALCAN, GEPIA, Wanderer, UCSC Xena and GEO databases. Enrichment analyses were performed to investigate the possible underlying biological pathways by LinkedOmics. Moreover, cBioPortal web tool was used to analyze genetic alterations of H19. Finally, we used TIMER and GEPIA databases to explore the correlations between H19 and tumor-infiltrated immune cells and immune markers. LncRNA H19 was differentially expressed in various cancers and also remarkably downregulated in the THCA tissues compared to the normal ones. Genetic alteration analysis revealed that there was a significant correlation between alterations in H19 and overall survival of THCA patients. Furthermore, enrichment analysis indicated the functional relationship between co-expression network of H19 and extracellular structure organization, and immune microenvironment. In addition, H19 expression was positively correlated with infiltration level of diverse immune cells including CD4+T cells, CD8+T cells, B cells, dendritic cells, neutrophils and macrophages and was closely associated with multiple immune markers in THCA. Conclusively, this comprehensive study indicates the lncRNA H19 might have a significant role in the initiation and progression of THCA. Hence, our findings might provide ideas on the selection of novel diagnostic biomarkers and assist in the designing of the effective pharmaceutical targets for THCA.

An integrative model for the comprehensive classification of BRCA1 and BRCA2 variants of uncertain clinical significance

Loss-of-function variants in the BRCA1 and BRCA2 susceptibility genes predispose carriers to breast and/or ovarian cancer. The use of germline testing panels containing these genes has grown dramatically, but the interpretation of the results has been complicated by the identification of many sequence variants of undefined cancer relevance, termed "Variants of Uncertain Significance (VUS)." We have developed functional assays and a statistical model called VarCall for classifying BRCA1 and BRCA2 VUS. Here we describe a multifactorial extension of VarCall, called VarCall XT, that allows for co-analysis of multiple forms of genetic evidence. We evaluated the accuracy of models defined by the combinations of functional, in silico protein predictors, and family data for VUS classification. VarCall XT classified variants of known pathogenicity status with high sensitivity and specificity, with the functional assays contributing the greatest predictive power. This approach could be used to identify more patients that would benefit from personalized cancer risk assessment and management.

Prenatal exposure to polycyclic aromatic hydrocarbons and gestational age at birth

BACKGROUND

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous chemicals with mechanisms of toxicity that include endocrine disruption. We examined associations of prenatal urinary PAH with spontaneous preterm birth (PTB) and gestational age (GA) at birth. We also assessed whether infant sex modifies the association of PAH exposure with spontaneous PTB and GA at birth.

METHODS

Participants included 1,677 non-smoking women from three cohorts (CANDLE, TIDES, and GAPPS) in the ECHO PATHWAYS Consortium. Twelve monohydroxylated-PAHs were measured in second trimester maternal urine. Seven metabolites with >60% overall detection were included in analyses: 1-hydroxynaphthalene [1-OH-NAP], 2-hydroxynaphthalene [2-OH-NAP], 2-hydroxyphenanthrene [2-OH-PHEN], 3-hydroxyphenanthrene [3-OH-PHEN], 1/9-hydroxyphenanthrene [1/9-OH-PHEN], 2/3/9-hydroxyfluorene [2/3/9-OH-FLUO], and 1-hydroxypyrene [1-OH-PYR]. Logistic and linear regression models were fit for spontaneous PTB and GA among births ≥34 weeks, respectively, with log₁₀-transformed OH-PAH concentrations as the exposure, adjusted for specific gravity and suspected confounders. Effect modification by infant sex was assessed using interaction terms and marginal estimates.

RESULTS

Percent detection was highest for 2-OH-NAP (99.8%) and lowest for 1-OH-PYR (65.2%). Prevalence of spontaneous PTB was 5.5% (N = 92). Ten-fold higher 2-OH-NAP exposure was associated with 1.60-day (95% CI: -2.92, -0.28) earlier GA at birth. Remaining associations in the pooled population were null. Among females, we observed significant inverse associations between 1-OH-PYR and PTB (OR: 2.65 [95% CI: 1.39, 5.05]); and 2-OH-NAP with GA: -2.46 days [95% CI: -4.15, -0.77]). Among males, we observed an inverse association between 2/3/9-OH-FLUO and PTB (OR = 0.40 [95% CI: 0.17,0.98]). ORs for PTB were higher among females than males for 2-OH-PHEN (p = 0.02) and 1-OH-PYR (p = 0.02).

DISCUSSION

We observed inverse associations of 2-OH-NAP exposure with GA and null associations of remaining OH-PAHs with GA and PTB. Females may be more susceptible to spontaneous PTB or shorter GA following prenatal exposure to some OH-PAHs. This study is the first to assess sex-specific OH-PAH toxicity in relation to spontaneous PTB and GA.

NR4A Family Genes: A Review of Comprehensive Prognostic and Gene Expression Profile Analysis in Breast Cancer

This report analyzes nuclear receptor (NR) subfamily 4A’s potential role in treating those diagnosed with breast cancer. Here we reviewed the current literature on NR4 family members. We also examined the relative gene expression of the NR4A receptor subfamily in the basal, HER2 (human epidermal growth factor receptor 2) positive, luminal A, and luminal B subtypes using data from tumor samples in The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC). These data showed a positive link between NR4A1-NR4A3 expression and increased overall survival and relapse-free survival in breast cancer patients. In addition, we observed that high expression of NR4A1, NR4A2, and NR4A3 led to better survival. Furthermore, NR4A family genes seem to play an essential regulatory role in glycolysis and oxidative phosphorylation in breast cancer. The novel prognostic role of the NR4A1–NR4A3 receptors implicates these receptors as important mediators controlling breast cancer metabolic reprograming and its progression. The review establishes a strong clinical basis for the investigation of the cellular, molecular, and physiological roles of NR4A genes in breast cancer.

The Placental Epigenome as a Molecular Link Between Prenatal Exposures and Fetal Health Outcomes Through the DOHaD Hypothesis

Purpose of Review

The developmental origins of health and disease (DOHaD) hypothesis posits that the perinatal environment can impact fetal and later life health. The placenta is uniquely situated to assess prenatal exposures in the context of DOHaD because it is an essential ephemeral fetal organ that manages the transport of oxygen, nutrients, waste, and endocrine signals between the mother and fetus. The purpose of this review is to summarize recent studies that evaluated the DOHaD hypothesis in human placentas using epigenomics, including DNA methylation and transcriptomic studies of mRNA, lncRNA, and microRNAs.

Recent Findings

Between 2016 and 2021, 28 articles evaluated associations between prenatal exposures and placental epigenomics across broad exposure categories including maternal smoking, psychosocial stressors, chemicals, air pollution, and metals. Sixteen of these studies connected exposures to health outcome such as birth weight, fetal growth, or infant neurobehavior through mediation analysis, identification of shared associations between exposure and outcome, or network analysis. These aspects of infant and childhood health serve as a foundation for future studies that aim to use placental epigenetics to understand relationships between the prenatal environment and perinatal complications (such as preterm birth or fetal growth restriction) or later life childhood health.

Summary

Placental DNA methylation and RNA expression have been linked to numerous prenatal exposures, such as PM2.5 air pollution, metals, and maternal smoking, as well as infant and childhood health outcomes, including fetal growth and birth weight. Placental epigenomics provides a unique opportunity to expand the DOHaD premise, particularly if research applies novel methodologies such as multi-omics analysis, sequencing of non-coding RNAs, mixtures analysis, and assessment of health outcomes beyond early childhood.

DNA in extracellular vesicles: from evolution to its current application in health and disease

Extracellular vesicle (EV) secretion is a highly conserved evolutionary trait in all organisms in the three domains of life. The packaging and release of EVs appears to be a bulk-flow process which takes place mainly under extreme conditions. EVs participate in horizontal gene transfer, which supports the survival of prokaryotic and eukaryotic microbes. In higher eukaryotes, almost all cells secrete a heterogeneous population of EVs loaded with various biomolecules. EV secretion is typically higher in cancer microenvironments, promoting tumor progression and metastasis. EVs are now recognized as additional mediators of autocrine and paracrine communication in health and disease. In this context, proteins and RNAs have been studied the most, but extracellular vesicle DNA (EV-DNA) has started to gain in importance in the last few years. In this review, we summarize new findings related to the loading mechanism(s), localization, and post-shedding function of EV-DNA. We also discuss the feasibility of using EV-DNA as a biomarker when performing a liquid biopsy, at the same time emphasizing the lack of data from clinical trials in this regard. Finally, we outline the potential of EV-DNA uptake and its interaction with the host genome as a promising tool for understanding the mechanisms of cancer evolution.

Protecting DNA in membrane vesicles seems to be a conserved phenomenon for the horizontal genetic flux between prokaryotes and lower eukaryotes.

Capturing and analyzing this vesicular DNA enables quick and non-invasive monitoring of natural ecosystems.

Cancer-derived extracellular vesicles containing DNA open up novel directions in cell-to-cell communication and therefore disease monitoring.

Complex and fluctuating conditions of the tumor microenvironment, mimicking natural ecosystems, could favor EV-DNA release, mediating tumor multi-clonal evolution and providing survival benefits.

Computational identification of new potential transcriptional partners of ERRα in breast cancer cells: specific partners for specific targets

Estrogen related receptors are orphan members of the nuclear receptor superfamily acting as transcription factors (TFs). In contrast to classical nuclear receptors, the activities of the ERRs are not controlled by a natural ligand. Regulation of their activities thus relies on availability of transcriptional co-regulators. In this paper, we focus on ERRα, whose involvement in cancer progression has been broadly demonstrated. We propose a new approach to identify potential co-activators, starting from previously identified ERRα-activated genes in a breast cancer (BC) cell line. Considering mRNA gene expression from two sets of human BC cells as major endpoint, we used sparse partial least squares modeling to uncover new transcriptional regulators associated with ERRα. Among them, DDX21, MYBBP1A, NFKB1, and SETD7 are functionally relevant in MDA-MB-231 cells, specifically activating the expression of subsets of ERRα-activated genes. We studied SET7 in more details and showed its co-localization with ERRα and its ERRα-dependent transcriptional and phenotypic effects. Our results thus demonstrate the ability of a modeling approach to identify new transcriptional partners from gene expression. Finally, experimental results show that ERRα cooperates with distinct co-regulators to control the expression of distinct sets of target genes, thus reinforcing the combinatorial specificity of transcription.

Preterm birth buccal cell epigenetic biomarkers to facilitate preventative medicine

Preterm birth is the major cause of newborn and infant mortality affecting nearly one in every ten live births. The current study was designed to develop an epigenetic biomarker for susceptibility of preterm birth using buccal cells from the mother, father, and child (triads). An epigenome-wide association study (EWAS) was used to identify differential DNA methylation regions (DMRs) using a comparison of control term birth versus preterm birth triads. Epigenetic DMR associations with preterm birth were identified for both the mother and father that were distinct and suggest potential epigenetic contributions from both parents. The mother (165 DMRs) and female child (136 DMRs) at p < 1e-04 had the highest number of DMRs and were highly similar suggesting potential epigenetic inheritance of the epimutations. The male child had negligible DMR associations. The DMR associated genes for each group involve previously identified preterm birth associated genes. Observations identify a potential paternal germline contribution for preterm birth and identify the potential epigenetic inheritance of preterm birth susceptibility for the female child later in life. Although expanded clinical trials and preconception trials are required to optimize the potential epigenetic biomarkers, such epigenetic biomarkers may allow preventative medicine strategies to reduce the incidence of preterm birth.

Using a Machine Learning Approach to Identify Key Biomarkers for Renal Clear Cell Carcinoma

Background

The most common and deadly subtype of renal carcinoma is kidney renal clear cell carcinoma (KIRC), which accounts for approximately 75% of renal carcinoma. However, the main cause of death in KIRC patients is tumor metastasis. There are no obvious clinical features in the early stage of kidney cancer, and 25–30% of patients have already metastasized when they are first diagnosed. Moreover, KIRC patients whose local tumors have been removed by nephrectomy are still at high risk of metastasis and recurrence and are not sensitive to chemotherapy and radiotherapy, leading to poor prognosis. Therefore, early diagnosis and treatment of this disease are very important.

Methods

KIRC-related patient datasets were downloaded from the GEO database and TCGA database. DEG screening and GO, KEGG and GSEA enrichment analysis was firstly conducted and then the LASSO and support vector machine (SVM) RFE algorithms were adopted to identify KIRC-associated key genes in training sets and validate them in the test set. The clinical prognostic analysis including the association between the expression of key genes and the overall survival, stage, grade across KIRC, the immune infiltration difference between normal samples and cancer samples, the correlation between the key genes and immune cells, immunomodulator, immune subtypes of KIRC were investigated in this research.

Results

We finally screened out 4 key genes, including ACPP, ANGPTL4, SCNN1G, SLC22A7. The expression of key genes show difference among normal samples and tumor samples, SCNN1G and SLC22A7 could be predictor of prognosis of patients. The expression of key genes was related with the abundance of tumor infiltration immune cells and the gene expression of immune checkpoint.

Conclusion

This study screened the 4 key genes, which contributed to early diagnosis, prognosis assessment and immune target treatment of patients with KIRC.

HOXD8 hypermethylation as a fully sensitive and specific biomarker for biliary tract cancer detectable in tissue and bile samples

Background

Biliary tract cancers (BTC) are rare but highly aggressive tumours with poor prognosis, usually detected at advanced stages. Herein, we aimed at identifying BTC-specific DNA methylation alterations.

Methods

Study design included statistical power and sample size estimation. A genome-wide methylation study of an explorative cohort (50 BTC and ten matched non-tumoral tissue samples) has been performed. BTC-specific altered CpG islands were validated in over 180 samples (174 BTCs and 13 non-tumoral controls). The final biomarkers, selected by a machine-learning approach, were validated in independent tissue (18 BTCs, 14 matched non-tumoral samples) and bile (24 BTCs, five non-tumoral samples) replication series, using droplet digital PCR.

Results

We identified and successfully validated BTC-specific DNA methylation alterations in over 200 BTC samples. The two-biomarker panel, selected by an in-house algorithm, showed an AUC > 0.97. The best-performing biomarker (chr2:176993479-176995557), associated with HOXD8, a pivotal gene in cancer-related pathways, achieved 100% sensitivity and specificity in a new series of tissue and bile samples.

Conclusions

We identified a novel fully efficient BTC biomarker, associated with HOXD8 gene, detectable both in tissue and bile by a standardised assay ready-to-use in clinical trials also including samples from non-invasive matrices.

Role of epigenetics in parturition and preterm birth

Preterm birth occurs worldwide and is associated with high morbidity, mortality, and economic cost. Although several risk factors associated with parturition and preterm birth have been identified, mechanisms underlying this syndrome remain unclear, thereby limiting the implementation of interventions for prevention and management. Known triggers of preterm birth include conditions related to inflammatory and immunological pathways, as well as genetics and maternal history. Importantly, epigenetics, which is the study of heritable phenotypic changes that occur without alterations in the DNA sequence, may play a role in linking social and environmental risk factors for preterm birth. Epigenetic approaches to the study of preterm birth, including analyses of the effects of microRNAs, long non-coding RNAs, DNA methylation, and histone modification, have contributed to an improved understanding of the molecular bases of both term and preterm birth. Additionally, epigenetic modifications have been linked to factors already associated with preterm birth, including obesity and smoking. The prevention and management of preterm birth remains a challenge worldwide. Although epigenetic analysis provides valuable insights into the causes and risk factors associated with this syndrome, further studies are necessary to determine whether epigenetic approaches can be used routinely for the diagnosis, prevention, and management of preterm birth.

A weighted patient network-based framework for predicting chronic diseases using graph neural networks

Chronic disease prediction is a critical task in healthcare. Existing studies fulfil this requirement by employing machine learning techniques based on patient features, but they suffer from high dimensional data problems and a high level of bias. We propose a framework for predicting chronic disease based on Graph Neural Networks (GNNs) to address these issues. We begin by projecting a patient-disease bipartite graph to create a weighted patient network (WPN) that extracts the latent relationship among patients. We then use GNN-based techniques to build prediction models. These models use features extracted from WPN to create robust patient representations for chronic disease prediction. We compare the output of GNN-based models to machine learning methods by using cardiovascular disease and chronic pulmonary disease. The results show that our framework enhances the accuracy of chronic disease prediction. The model with attention mechanisms achieves an accuracy of 93.49% for cardiovascular disease prediction and 89.15% for chronic pulmonary disease prediction. Furthermore, the visualisation of the last hidden layers of GNN-based models shows the pattern for the two cohorts, demonstrating the discriminative strength of the framework. The proposed framework can help stakeholders improve health management systems for patients at risk of developing chronic diseases and conditions.

Anti-tumour effect of neo-antigen-reactive T cells induced by RNA mutanome vaccine in mouse lung cancer

PURPOSE

Mutation-specific T-cell response to epithelial cancers and T-cell-based immunotherapy has been successfully used to treat several human solid cancers. We aimed to investigate the anti-tumour effect of neo-antigen-reactive T(NRT) cells induced by RNA mutanome vaccine, which may serve as a feasible and effective therapeutic approach for lung cancer.

METHODS

We predicted candidate neo-antigens according to the mutant gene analysis by sequencing the mouse Lewis cells and C57BL/6 mouse tail tissue. RNA vaccine was prepared with the neo-antigens as the template. We assessed antitumor efficacy, cytokine secretion and pathological changes after adoptive transfer of NRT cells in vitro and vivo experiments.

RESULTS

We identified 10 non-synonymous somatic mutations and successfully generated NRT cells. The percentage of T-cell activation proportion was increased from 0.072% in conventional T cells to 9.96% in NRT cells. Interferon-γ secretion augmented from 17.8 to 24.2% as well. As an in vivo model, adoptive NRT cell infusion could promote active T-cell infiltration into the tumour tissue and could delay tumour progression.

CONCLUSION

NRT cells induced by RNA mutanome vaccine exert a significant anti-tumour effect in mouse lung cancer, and adoptive NRT cell therapy might be considered a feasible, effective therapeutic approach for lung cancer.

DNA Methylation Pattern of CALCA and CALCB in Extremely Premature Infants with Monochorionic Triplets after Single-Embryo Transfer

Compared with full-term peers, premature infants are more likely to suffer from neonatal diseases and death. Variations in DNA methylation may affect these pathological processes. Calcitonin gene-related peptide (CGRP) plays a complex and diversified role in reproduction and chronic inflammation, and participates in the functional maintenance of vascular adaptation and trophoblast cells during pregnancy. Here, premature live births with single-chorionic triple embryos after single-embryo transfer were used as research objects, while full-term infants with double embryos and double-chorionic twins were used as controls. DNA was extracted from umbilical cord tissues for pyrosequencing to detect the methylation level of CpG island in CGRP promoter region. The average values of CGRP methylation in the umbilical cord tissues of very premature fetuses were higher than that of normal controls obtained from the databases. Immunofluorescence results showed that the expression of αCGRP was decreased in the blood vessel wall of the umbilical cord of monozygotic triplets, especially in death cases, while the βCGRP had a compensatory expression. In conclusion, our findings suggest that hypermethylation of CGRP might be considered as an important cause of serious neonatal morbidities.

Clinical utility of clonal origin determination in managing recurrent hepatocellular carcinoma

INTRODUCTION

Recurrence is the driving factor for reduced long-term survival in patients following resected hepatocellular carcinoma (HCC). Extensive research efforts have been conducted to understand the molecular processes precipitating disease recurrence. Modern genomic techniques have identified two distinct mechanisms for recurrent HCC (RHCC): Intrahepatic metastasis (IM-HCC); and multicentric origin (MO-HCC). Medline, EMBASE and Cochrane library were methodically searched for primary research articles in English with the aim of appraising existing literature on the identification of clonal origin of RHCC and its potential clinical utility.

AREAS COVERED

Molecular and next-generation sequencing techniques, when applied to clonal origin identification, yield superior accuracy than traditional clinicopathological criteria. Despite various treatment modalities, no optimal therapy has yet been identified for treating clonally differentiated RHCC. Patients with MO-HCC appear to experience improved long-term survival following re-treatment compared to their IM-HCC counterparts (91.7% vs 22.9% 5-year survival, p < 0.001). However, cautious interpretation is advised as heterogeneous classification criteria and small sample sizes restrict the generalizability of such findings.

EXPERT OPINION

Improved identification of clonal origin in RHCC may facilitate further research on RHCC treatment strategies and enable the development of novel therapeutic targets, potentially leading to individualized treatment approaches in the future.

Perinatal stress and methylation of the NR3C1 gene in newborns: systematic review

Adverse experiences in the perinatal period have been associated with the methylation of the human glucocorticoid receptor gene (NR3C1) and long-term diseases. We conducted a systematic review on the association between adversities in the perinatal period and DNA methylation in the 1 _F region of the NR3C1 gene in newborns. We explored the MEDLINE, Web of Science, Scopus, Scielo, and Lilacs databases without time or language limitations. Two independent reviewers performed the selection of articles and data extraction. A third participated in the methodological quality assessment and consensus meetings at all stages. Finally, ten studies were selected. Methodological quality was considered moderate in six and low in four. Methylation changes were reported in 41 of the 47 CpG sites of exon 1 _F. Six studies addressed maternal conditions during pregnancy: two reported methylation changes at the same sites (CpG 10, 13, 20, 21 and 47), and four at one or more sites from CpG 35 to 39. Four studies addressed neonatal parameters and morbidities: methylation changes at the same sites 4, 8, 10, 16, 25, and 35 were reported in two. Hypermethylation associated with stressful conditions prevailed. Hypomethylation was more often associated with protective conditions (maternal-foetal attachment during pregnancy, breast milk intake, higher birth weight or Apgar). In conclusion, methylation changes in several sites of the 1 _F region of the NR3C1 gene in newborns and very young infants were associated with perinatal stress, but more robust and comparable results are needed to corroborate site-specific associations.

DNA methylation changes in African American women with a history of preterm birth from the InterGEN study

Background

Preterm birth (< 37 weeks’ gestation) is a common outcome of pregnancy that has been associated with increased risk of cardiovascular disease for women later in life. Little is known about the physiologic mechanisms underlying this risk. To date, no studies have evaluated if differences in DNA methylation (DNAm) among women who experience preterm birth are short-term or if they persist and are associated with subsequent cardiovascular sequelae or other health disorders. The purpose of this study was to examine long-term epigenetic effects of preterm birth in African American mothers (n = 182) from the InterGEN Study (2014–2019). In this study, we determine if differences in DNAm exist between women who reported a preterm birth in the last 3–5 years compared to those who had full-term births by using two different approaches: epigenome-wide association study (EWAS) and genome-wide co-methylation analyses.

Results

Though no significant CpG sites were identified using the EWAS approach, we did identify significant modules of co-methylation associated with preterm birth. Co-methylation analyses showed correlations with preterm birth in gene ontology and KEGG pathways. Functional annotation analysis revealed enrichment for pathways related to central nervous system and sensory perception. No association was observed between DNAm age and preterm birth, though larger samples are needed to confirm this further.

Conclusions

We identified differentially methylated gene networks associated with preterm birth in African American women 3–5 years after birth, including pathways related to neurogenesis and sensory processing. More research is needed to understand better these associations and replicate them in an independent cohort. Further study should be done in this area to elucidate mechanisms linking preterm birth and later epigenomic changes that may contribute to the development of health disorders and maternal mood and well-being.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-021-00988-x.

Differential metabolic network construction for personalized medicine: Study of type 2 diabetes mellitus patients' response to gliclazide-modified-release-treated

Individual variation in genetic and environmental factors can cause the differences in metabolic phenotypes, which may have an effect on drug responses of patients. Deep exploration of patients' responses to therapeutic agents is a crucial and urgent event in the personalized treatment study. Using machine learning methods for the discovery of suitability evaluation biomarkers can provide deep insight into the mechanism of disease therapy and facilitate the development of personalized medicine. To find important metabolic network signals for the prediction of patients' drug responses, a novel method referred to as differential metabolic network construction (DMNC) was proposed. In DMNC, concentration changes in metabolite ratios between different pathological states are measured to construct differential metabolic networks, which can be used to advance clinical decision-making. In this study, DMNC was applied to characterize type 2 diabetes mellitus (T2DM) patients' responses against gliclazide modified-release (MR) therapy. Two T2DM metabolomics datasets from different batches of subjects treated by gliclazide MR were analyzed in depth. A network biomarker was defined to assess the patients' suitability for gliclazide MR. It can be effective in the prediction of significant responders from nonsignificant responders, achieving area under the curve values of 0.893 and 1.000 for the discovery and validation sets, respectively. Compared with the metabolites selected by the other methods, the network biomarker selected by DMNC was more stable and precise to reflect the metabolic responses in patients to gliclazide MR therapy, thereby contributing for the personalized medicine of T2DM patients. The better performance of DMNC validated its potential for the identification of network biomarkers to characterize the responses against therapeutic treatments and provide valuable information for personalized medicine.

DNA Methylation, Preterm Birth and Blood Pressure in African American Children: The DPREG Study

Preterm birth (< 37 weeks) has been associated with high blood pressure (BP) and cardiovascular disease in adulthood. Epigenetic mechanisms may explain how preterm birth influences later BP. In this study, we examined the association between DNA methylation (DNAm), preterm birth and BP in African American children. We recruited 100 children and collected clinical and birth history data. DNA was extracted from saliva and the Illumina EPIC BeadChip was used for epigenetic analyses. Preterm birth was not associated with systolic or diastolic BP. No significant DNAm sites were associated with preterm birth in candidate gene methylation analyses. Body mass index was associated with systolic BP (p = 0.01). We did not observe an effect of preterm birth on DNAm or BP in early childhood. Our study is one of the few, however, to examine these associations among African Americans.

A novel deep autoencoder based survival analysis approach for microarray dataset

BACKGROUND

Breast cancer is one of the major causes of mortality globally. Therefore, different Machine Learning (ML) techniques were deployed for computing survival and diagnosis. Survival analysis methods are used to compute survival probability and the most important factors affecting that probability. Most survival analysis methods are used to deal with clinical features (up to hundreds), hence applying survival analysis methods like cox regression on RNAseq microarray data with many features (up to thousands) is considered a major challenge.

METHODS

In this paper, a novel approach applying autoencoder to reduce the number of features is proposed. Our approach works on features reconstruction, and removal of noise within the data and features with zero variance across the samples, which facilitates extraction of features with the highest variances (across the samples) that most influence the survival probabilities. Then, it estimates the survival probability for each patient by applying random survival forests and cox regression. Applying the autoencoder on thousands of features takes a long time, thus our model is applied to the Graphical Processing Unit (GPU) in order to speed up the process. Finally, the model is evaluated and compared with the existing models on three different datasets in terms of run time, concordance index, and calibration curve, and the most related genes to survival are discovered. Finally, the biological pathways and GO molecular functions are analyzed for these significant genes.

RESULTS

We fine-tuned our autoencoder model on RNA-seq data of three datasets to train the weights in our survival prediction model, then using different samples in each dataset for testing the model. The results show that the proposed AutoCox and AutoRandom algorithms based on our feature selection autoencoder approach have better concordance index results comparing the most recent deep learning approaches when applied to each dataset. Each gene resulting from our autoencoder model weight is computed. The weights show the degree of effect for each gene upon the survival probability. For instance, four of the most survival-related experimentally validated genes are on the top of our discovered genes weights list, including PTPRG, MYST1, BG683264, and AK094562 for the breast cancer gene expression dataset. Our approach improves the survival analysis in terms of speeding up the process, enhancing the prediction accuracy, and reducing the error rate in the estimated survival probability.

An EPIC predictor of gestational age and its application to newborns conceived by assisted reproductive technologies

Background

Gestational age is a useful proxy for assessing developmental maturity, but correct estimation of gestational age is difficult using clinical measures. DNA methylation at birth has proven to be an accurate predictor of gestational age. Previous predictors of epigenetic gestational age were based on DNA methylation data from the Illumina HumanMethylation 27 K or 450 K array, which have subsequently been replaced by the Illumina MethylationEPIC 850 K array (EPIC). Our aims here were to build an epigenetic gestational age clock specific for the EPIC array and to evaluate its precision and accuracy using the embryo transfer date of newborns from the largest EPIC-derived dataset to date on assisted reproductive technologies (ART).

Methods

We built an epigenetic gestational age clock using Lasso regression trained on 755 randomly selected non-ART newborns from the Norwegian Study of Assisted Reproductive Technologies (START)—a substudy of the Norwegian Mother, Father, and Child Cohort Study (MoBa). For the ART-conceived newborns, the START dataset had detailed information on the embryo transfer date and the specific ART procedure used for conception. The predicted gestational age was compared to clinically estimated gestational age in 200 non-ART and 838 ART newborns using MM-type robust regression. The performance of the clock was compared to previously published gestational age clocks in an independent replication sample of 148 newborns from the Prediction and Prevention of Preeclampsia and Intrauterine Growth Restrictions (PREDO) study—a prospective pregnancy cohort of Finnish women.

Results

Our new epigenetic gestational age clock showed higher precision and accuracy in predicting gestational age than previous gestational age clocks (R² = 0.724, median absolute deviation (MAD) = 3.14 days). Restricting the analysis to CpGs shared between 450 K and EPIC did not reduce the precision of the clock. Furthermore, validating the clock on ART newborns with known embryo transfer date confirmed that DNA methylation is an accurate predictor of gestational age (R² = 0.767, MAD = 3.7 days).

Conclusions

We present the first EPIC-based predictor of gestational age and demonstrate its robustness and precision in ART and non-ART newborns. As more datasets are being generated on the EPIC platform, this clock will be valuable in studies using gestational age to assess neonatal development.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01055-z.

An effective polymeric nanocarrier that allows for active targeting and selective drug delivery in cell coculture systems

In this manuscript, we report the development of a versatile, robust, and stable targeting nanocarrier for active delivery. This nanocarrier is based on bifunctionalized polymeric nanoparticles conjugated to a monoclonal antibody that allows for active targeting of either (i) a fluorophore for tracking or (ii) a drug for monitoring specific cell responses. This nanodevice can efficiently discriminate between cells in coculture based on the expression levels of cell surface receptors. As a proof of concept, we have demonstrated efficient delivery using a broadly established cell surface receptor as the target, the epidermal growth factor receptor (EGFR), which is overexpressed in several types of cancers. Additionally, a second validation of this nanodevice was successfully carried out using another cell surface receptor as the target, the cluster of differentiation 147 (CD147). Our results suggest that this versatile nanocarrier can be expanded to other cell receptors and bioactive cargoes, offering remarkable discrimination efficiency between cells with different expression levels of a specific marker. This work supports the ability of nanoplatforms to boost and improve the progress towards personalized medicine.

Racial and ethnic representation in epigenomic studies of preterm birth: a systematic review

Aim: We conducted a systematic review evaluating race/ethnicity representation in DNA methylomic studies of preterm birth. Data sources: PubMed, EMBASE, CINHAL, Scopus and relevant citations from 1 January 2000 to 30 June 2019. Study appraisal & synthesis methods: Two authors independently identified abstracts comparing DNA methylomic differences between term and preterm births that included race/ethnicity data. Results: 16 studies were included. Black and non-Hispanic Black deliveries were well represented (28%). However, large studies originating from more than 95% White populations were excluded due to unreported race/ethnicity data. Most studies were cross-sectional, allowing for reverse causation. Most studies were also racially/ethnically homogeneous, preventing direct comparison of DNA methylomic differences across race/ethnicities. Conclusion: In DNA methylomic studies, Black women and infants were well represented. However, the literature has limitations and precludes drawing definitive conclusions.

High-resolution epigenomic liquid biopsy for noninvasive phenotyping in pregnancy

OBJECTIVE

We explored the potential of genome-wide epigenomic liquid biopsy for the comprehensive analysis of cell-free DNA (cfDNA) methylation signatures in maternal plasma in early gestation.

METHOD

We used solution phase hybridization for targeted region capture of bisulfite-converted DNA obtained from plasma of pregnant women in early gestation and nonpregnant female controls.

RESULTS

Targeted sequencing of ~80.5 Mb of the plasma methylome generated an average read depth across all 17 plasma samples of ~42x. We used these data to explore the pregnancy-specific characteristics of cfDNA methylation in plasma and found that pregnancy resulted in clearly detectable global alterations in DNA methylation patterns that were influenced by genomic location. We analyzed similar, previously published, data from first-trimester maternal leukocyte populations and gestational age-matched chorionic villus (CV) and confirmed that tissue-specific DNA methylation signatures in these samples had a significant influence on global and gene-specific methylation in the plasma of pregnant women.

CONCLUSION

We describe an approach for targeted epigenomic liquid biopsy in pregnancy and discuss our findings in the context of noninvasive prenatal testing with respect to phenotypic pregnancy monitoring and the early detection of complex gestational phenotypes such as preeclampsia and preterm birth.

Epigenome Wide Association and Stochastic Epigenetic Mutation Analysis on Cord Blood of Preterm Birth

Preterm birth (PTB) can be defined as the endpoint of a complex process that could be influenced by maternal and environmental factors. Epigenetics recently emerged as an interesting field of investigation since it represents an important mechanism of regulation. This study evaluates epigenetic impact of preterm birth on DNA methylation. Genome-wide DNAm was measured using the Illumina 450K array in cord blood samples obtained from 72 full term and 18 preterm newborns. Lymphocyte composition was calculated based on specific epigenetic markers that are present on the 450k array. Differential methylation analysis was performed both at site and region level; moreover, stochastic epigenetic mutations (SEMs) were also evaluated. The study showed significant differences in blood cell composition between the two groups. Moreover, after multiple testing correction, statistically significant differences in DNA methylation levels emerged between the two groups both at site and region levels. Results obtained were compared to those reported by previous EWAS, leading to a list of more consistent genes associated with PTB. Finally, the SEMs analysis revealed that the burden of SEMs resulted significantly higher in the preterm group. In conclusion, PTB resulted associated to specific epigenetic signatures that involve immune system. Moreover, SEMs analysis revealed an increased epigenetic drift at birth in the preterm group.

Ageing in human parturition: impetus of the gestation clock in the decidua†

Despite sharing many common features, the relationship between ageing and parturition remains poorly understood. The decidua is a specialized lining of endometrial tissue, which develops in preparation for pregnancy. The structure and location of the decidua support its role as the physical scaffold for the growing embryo and placenta, and thus, it is vital to sustain pregnancy. Approaching term, the physical support properties of the decidua are naturally weakened to permit parturition. In this review, we hypothesize that the natural weakening of decidual tissue at parturition is promoted by the ageing process. Studies of the ageing-related functional and molecular changes in the decidua at parturition are reviewed and classified using hallmarks of ageing as the framework. The potential roles of decidual mesenchymal stem/stromal cell (DMSC) ageing in labor are also discussed because, although stem cell exhaustion is also a hallmark of ageing, its role in labor is not completely understood. In addition, the potential roles of extracellular vesicles secreted by DMSCs in labor, and their parturition-related miRNAs, are reviewed to gain further insight into this research area. In summary, the literature supports the notion that the decidua ages as the pregnancy progresses, and this may facilitate parturition, suggesting that ageing is the probable impetus of the gestational clocks in the decidua. This conceptual framework was developed to provide a better understanding of the natural ageing process of the decidua during parturition as well as to encourage future studies of the importance of healthy ageing for optimal pregnancy outcomes.

Stress During Pregnancy and Epigenetic Modifications to Offspring DNA: A Systematic Review of Associations and Implications for Preterm Birth

Offspring born preterm (ie, before 37 weeks of gestation) are more likely to die or experience long-standing illness than full-term offspring. Maternal genetic variants (ie, heritable, stable variations in the genetic code) and epigenetic modifications (ie, chemical modifications to the genetic code that can affect which genes are turned on or off) in response to stress have been implicated in preterm birth. Fetal genetic variants have been linked to preterm birth though the role of offspring epigenetics in preterm birth remains understudied. This systematic review synthesizes the literature examining associations among stress during pregnancy and epigenetic modifications to offspring DNA, with 25 reports identified. Ten reports examined DNA methylation (ie, addition/removal of methyl groups to/from DNA) across the epigenome. The remainder examined DNA methylation near genes of interest, primarily genes linked to hypothalamic-pituitary-adrenal axis function (NR3C1, FKBP51), growth/immune function (IGF2), and socioemotional regulation (SLC6A4, OXTR). The majority of reports noted associations among stress and offspring DNA methylation, primarily when perceived stress, anxiety, or depression served as the predictor. Findings suggest that differences in offspring epigenetic patterns may play a role in stress-associated preterm birth and serve as targets for novel interventions.

Autologous cord blood in children with cerebral palsy: a review

The aim of this narrative review is to report on the current knowledge regarding the clinical use of umbilical cord blood (CB) based on articles from PubMed and clinical trials registered on ClinicalTrials.gov. An increasing amount of evidence suggests that CB may be used for both early diagnostics and treatment of cerebral palsy. The acidity of CB and its biochemical parameters, including dozens of cytokines, growth factors, and other metabolites (such as amino acids, acylcarnitines, phosphatidylcholines, succinate, glycerol, 3-hydroxybutyrate, and O-phosphocholine) are predictors of future neurodevelopment. In addition, several clinical studies confirmed the safety and efficacy of CB administration in both autologous and allogeneic models, including a meta-analysis of five clinical trials involving a total of 328 participants. Currently, nine clinical trials assessing the use of autologous umbilical CB in children diagnosed with hypoxic-ischemic encephalopathy or cerebral palsy are in progress. The total population assessed in these trials exceeds 2500 patients.