Characterization of Sex-Based Dna Methylation Signatures in the Airways During Early Life

The X-factor in ART: does the use of assisted reproductive technologies influence DNA methylation on the X chromosome?

BACKGROUND

Assisted reproductive technologies (ART) may perturb DNA methylation (DNAm) in early embryonic development. Although a handful of epigenome-wide association studies of ART have been published, none have investigated CpGs on the X chromosome. To bridge this knowledge gap, we leveraged one of the largest collections of mother-father-newborn trios of ART and non-ART (natural) conceptions to date to investigate sex-specific DNAm differences on the X chromosome. The discovery cohort consisted of 982 ART and 963 non-ART trios from the Norwegian Mother, Father, and Child Cohort Study (MoBa). To verify our results from the MoBa cohort, we used an external cohort of 149 ART and 58 non-ART neonates from the Australian 'Clinical review of the Health of adults conceived following Assisted Reproductive Technologies' (CHART) study. The Illumina EPIC array was used to measure DNAm in both datasets. In the MoBa cohort, we performed a set of X-chromosome-wide association studies ('XWASs' hereafter) to search for sex-specific DNAm differences between ART and non-ART newborns. We tested several models to investigate the influence of various confounders, including parental DNAm. We also searched for differentially methylated regions (DMRs) and regions of co-methylation flanking the most significant CpGs. Additionally, we ran an analogous model to our main model on the external CHART dataset.

RESULTS

In the MoBa cohort, we found more differentially methylated CpGs and DMRs in girls than boys. Most of the associations persisted after controlling for parental DNAm and other confounders. Many of the significant CpGs and DMRs were in gene-promoter regions, and several of the genes linked to these CpGs are expressed in tissues relevant for both ART and sex (testis, placenta, and fallopian tube). We found no support for parental DNAm-dependent features as an explanation for the observed associations in the newborns. The most significant CpG in the boys-only analysis was in UBE2DNL, which is expressed in testes but with unknown function. The most significant CpGs in the girls-only analysis were in EIF2S3 and AMOT. These three loci also displayed differential DNAm in the CHART cohort.

CONCLUSIONS

Genes that co-localized with the significant CpGs and DMRs associated with ART are implicated in several key biological processes (e.g., neurodevelopment) and disorders (e.g., intellectual disability and autism). These connections are particularly compelling in light of previous findings indicating that neurodevelopmental outcomes differ in ART-conceived children compared to those naturally conceived.

Genes, environment, and developmental timing: New insights from translational approaches to understand early origins of respiratory diseases

Over the past decade, "omics" approaches have advanced our understanding of the molecular programming of the airways in humans. Several studies have identified potential molecular mechanisms that contribute to early life epigenetic reprogramming, including DNA methylation, histone modifications, microRNAs, and the homeostasis of the respiratory mucosa (epithelial function and microbiota). Current evidence supports the notion that early infancy is characterized by heightened susceptibility to airway genetic reprogramming in response to the first exposures in life, some of which can have life-long consequences. Here, we summarize and analyze the latest insights from studies that support a novel epigenetic paradigm centered on human maturational and developmental programs including three cardinal elements: genes, environment, and developmental timing. The combination of these factors is likely responsible for the functional trajectory of the respiratory system at the molecular, functional, and clinical levels.

Predicting environmental risk factors in relation to health outcomes among school children from Romania using random forest model - An analysis of data from the SINPHONIE project

BACKGROUND

Few studies have simultaneously assessed the health impact of school and home environmental factors on children, since handling multiple highly correlated environmental variables is challenging. In this study, we examined indoor home and school environments in relation to health outcomes using machine learning methods and logistic regression.

METHODS

We used the data collected by the SINPHONIE (Schools Indoor Pollution and Health: Observatory Network in Europe) project in Romania, a multicenter European research study that collected comprehensive information on school and home environments, health symptoms in children, smoking, and school policies. The health outcomes were categorized as: any health symptoms, asthma, allergy and flu-like symptoms. Both logistic regression and random forest (RF) methods were used to predict the four categories of health outcomes, and the methods prediction performance was compared.

RESULTS

The RF method we employed for analysis showed that common risk factors for the investigated categories of health outcomes, included: environmental tobacco smoke (ETS), dampness in the indoor school environment, male gender, air freshener use, residence located in proximity of traffic (<200 m), stressful schoolwork, and classroom noise (contributions ranged from 7.91% to 23.12%). Specificity, accuracy and area under the curve (AUC) values for most outcomes were higher when using RF compared to logistic regression, while sensitivity was similar in both methods.

CONCLUSION

This study suggests that ETS, dampness in the indoor school environment, use of air fresheners, living in proximity to traffic (<200 m) and noise are common environmental risk factors for the investigated health outcomes. RF pointed out better predictive values, sensitivity and accuracy compared to logistic regression.

Hierarchal Bayes model with AlexNet for characterization of M-FISH chromosome images

The analysis of chromosomes is a significant and challenging task for clinical diagnosis and biological research. The technique based on color imaging is a multiplex fluorescent in situ hybridization (M-FISH), which was implemented to ease the exploration of the chromosomes. Thus, in this paper, we propose a novel quasi-Newton-based K-means clustering for the M-FISH image segmentation. Then, we use the expectation-maximization-based hierarchical Bayes model to characterize the M-FISH images. The contextual-based classification and region merging of chromosomal images is made to avoid any misclassification, and we made use of AlexNet, by modifying the activation functions of the sigmoid and softmax layer and for the optimum classification between the autosomal chromosomes and the sex chromosome. Finally, we conducted a performance analysis by measuring accuracy, recall, sensitivity, specificity, PPV, NPV, F-score, kappa, Jaccard, and Dice coefficient and compared with other existing methods and found that our proposed methodology can achieve more percentage of accuracy (6.96%) than the state of the art methods.

Genetic effects of allergen-specific IgE levels on exhaled nitric oxide in schoolchildren with asthma: The STOPPA twin study

BACKGROUND

Exhaled nitric oxide and blood eosinophils are clinical asthma T-helper type 2 markers in use. Immunoglobulin E (IgE) is often involved in the inflammation associated with atopic asthma. The effect of both blood eosinophils and allergen-specific IgE on exhaled nitric oxide levels is not completely understood. Twin-design studies can improve understanding of the underlying contribution of genetically and/or environmentally driven inflammation markers in asthma. Our aim was to disentangle the covariance between asthma and exhaled nitric oxide into genetic and environmental contributions that can account for inflammation markers in a paediatric population.

METHODS

This population-based, cross-sectional twin study enrolled 612 monozygotic (MZ) and same-sex dizygotic (DZ) schoolchildren. Multivariate structural equation modelling was utilized to separate the covariance between asthma and exhaled nitric oxide into genetic and/or environmental effects, taking allergen-specific IgE level and blood eosinophil count into account while controlling for confounding factors.

RESULTS

The cross-twin/cross-trait correlations had a higher magnitude in the MZ twins than in the DZ twins, indicating that genes affect the association. The likelihood ratio test for model fitting resulted in the AE model (ie additive genetic effects, A, and non-shared environmental effects, E) as the most parsimonious. A majority, 73%, of the phenotypic correlation between asthma and exhaled nitric oxide, r = .19 (0.05-0.33), was attributable to genetic effects which mainly was due to the allergen-specific IgE level.

CONCLUSIONS

This study indicates that the association between asthma and exhaled nitric oxide in children is to a large extent explained by genetics via allergen-specific IgE level and not blood eosinophils. This might partly explain the clinical heterogeneity in this group. A next step could be to include allergen-specific IgE level in multivariate omic studies.

Age- and gender-specific trends in respiratory outpatient visits and diagnoses at a tertiary pediatric hospital in China: a 10-year retrospective study

Background

Respiratory infections are one of three leading causes of childhood mortality, and worldwide increase and recent plateau in childhood asthma has been reported. However, data on trends of respiratory diseases over long period of time is limited. This study aimed to determine the trends of respiratory disease outpatient visits (ROVs) and diagnoses (RODs) in one of the largest children’s teaching hospitals in China between 2009 and 2018.

Methods

A retrospective study based on routine administrative data was designed and implemented according to the RECORD statement. Demographic details and diagnoses of the outpatients < 18 years visiting the respiratory department of the hospital were extracted from the Hospital Information System. Age- and gender-specific trends were illustrated by calculating average annual growth rate (AAGR) for ROVs and comparing change of proportion for different RODs over time.

Results

There were 698,054 ROVs from 285,574 children (40.4% female). AAGR of ROVs was 15.2%. Children aged 4 to < 7 years had a faster increase than other age groups. Bronchitis (27.6%), pneumonia (18.5%), pneumonia affecting other systems (18.4%), asthma and status asthmaticus (10.7%), and vasomotor and allergic rhinitis (9.2%) accounted for 84.4% of all RODs. The proportion of bronchitis decreased across years, with the concomitant increasing trend in the proportion of pneumonia. Age-specific trend in diagnoses showed greater proportion of asthma in all visits for the children aged 7 to < 18 years than younger children. Gender-specific trend in diagnoses showed the proportion of asthma was greater for males but the AAGR was greater for females.

Conclusion

The persistent upward trend in ROVs was observed among children at different ages and a gender difference was also seen. In contrast to what has been reported, burden of asthma and allergies diseases continues to increase locally.

DNA Methylation in Nasal Epithelium: Strengths and Limitations of an Emergent Biomarker for Childhood Asthma

Asthma is one of the most widespread chronic respiratory conditions. This disease primarily develops in childhood and is influenced by different factors, mainly genetics and environmental factors. DNA methylation is an epigenetic mechanism which may represent a bridge between these two factors, providing a tool to comprehend the interaction between genetics and environment. Most epidemiological studies in this field have been conducted using blood samples, although DNA methylation marks in blood may not be reliable for drawing exhaustive conclusions about DNA methylation in the airways. Because of the role of nasal epithelium in asthma and the tissue specificity of DNA methylation, studying the relationship between DNA methylation and childhood asthma might reveal crucial information about this widespread respiratory disease. The purpose of this review is to describe current findings in this field of research. We will present a viewpoint of selected studies, consider strengths and limitations, and propose future research in this area.

DNA Methylation Cancer Biomarkers: Translation to the Clinic

Carcinogenesis is accompanied by widespread DNA methylation changes within the cell. These changes are characterized by a globally hypomethylated genome with focal hypermethylation of numerous 5’-cytosine-phosphate-guanine-3’ (CpG) islands, often spanning gene promoters and first exons. Many of these epigenetic changes occur early in tumorigenesis and are highly pervasive across a tumor type. This allows DNA methylation cancer biomarkers to be suitable for early detection and also to have utility across a range of areas relevant to cancer detection and treatment. Such tests are also simple in construction, as only one or a few loci need to be targeted for good test coverage. These properties make cancer-associated DNA methylation changes very attractive for development of cancer biomarker tests with substantive clinical utility. Across the patient journey from initial detection, to treatment and then monitoring, there are several points where DNA methylation assays can inform clinical practice. Assays on surgically removed tumor tissue are useful to determine indicators of treatment resistance, prognostication of outcome, or to molecularly characterize, classify, and determine the tissue of origin of a tumor. Cancer-associated DNA methylation changes can also be detected with accuracy in the cell-free DNA present in blood, stool, urine, and other biosamples. Such tests hold great promise for the development of simple, economical, and highly specific cancer detection tests suitable for population-wide screening, with several successfully translated examples already. The ability of circulating tumor DNA liquid biopsy assays to monitor cancer in situ also allows for the ability to monitor response to therapy, to detect minimal residual disease and as an early biomarker for cancer recurrence. This review will summarize existing DNA methylation cancer biomarkers used in clinical practice across the application domains above, discuss what makes a suitable DNA methylation cancer biomarker, and identify barriers to translation. We discuss technical factors such as the analytical performance and product-market fit, factors that contribute to successful downstream investment, including geography, and how this impacts intellectual property, regulatory hurdles, and the future of the marketplace and healthcare system.