Combining omics data to identify genes associated with allergic rhinitis

Causality between depression and ankylosing spondylitis in a European population: Results from a Mendelian randomization analysis

The aim of this study was to explore the application of Mendelian randomization (MR) Egger and inverse variance weighted (IVW) in a causal effect on depression and ankylosing spondylitis (AS). Instrumental variables (IVs) were determined using genome-wide association studies. The 2-sample MR analysis was conducted by MR Egger to test the causal effect between depression and AS. The pleiotropy of potential instrumental variables was evaluated. The results of MR Egger and IVW were further compared. A total of 3 single nucleotide polymorphisms as the construct IVs were included. IVW results showed a significant causal effect between depression and AS (P < .001). Depression could promote the risk of AS (odds ratio = 1.060, 95% confidence interval: 1.026-1.094). However, the MR Egger showed no causal effect (P = .311). Heterogeneity statistics suggested that no heterogeneity was existed (P > .05). It was also suggested that there was no horizontal pleiotropy in IVs (MR Egger intercept: -0.0004, P = .471). Reverse MR analysis suggested that there was no causal effect between AS and depression (P > .05). Gene expression quantitative trait locus (QTLs) suggested that rs2517601 and RNF39 were positively correlated (beta = 1.066, P < .001). Depression may be one of the causes of AS by MR analysis in a European population. We can estimate the causal effect based on IVW when horizontal pleiotropy is very tiny.

Emerging Roles of MHC Class I Region-Encoded E3 Ubiquitin Ligases in Innate Immunity

The major histocompatibility complex (MHC) class I (MHC-I) region contains a multitude of genes relevant to immune response. Multiple E3 ubiquitin ligase genes, including tripartite motif 10 (TRIM10), TRIM15, TRIM26, TRIM27, TRIM31, TRIM38, TRIM39, TRIM40, and RING finger protein 39 (RNF39), are organized in a tight cluster, and an additional two TRIM genes (namely TRIM38 and TRIM27) telomeric of the cluster within the MHC-I region. The E3 ubiquitin ligases encoded by these genes possess important roles in controlling the intensity of innate immune responses. In this review, we discuss the E3 ubiquitin ligases encoded within the MHC-I region, highlight their regulatory roles in innate immunity, and outline their potential functions in infection, inflammatory and autoimmune diseases.

DNA Methylation in Babies Born to Nonsmoking Mothers Exposed to Secondhand Smoke during Pregnancy: An Epigenome-Wide Association Study

BACKGROUND

Maternal smoking during pregnancy is related to altered DNA methylation in infant umbilical cord blood. The extent to which low levels of smoke exposure among nonsmoking pregnant women relates to offspring DNA methylation is unknown.

OBJECTIVE

This study sought to evaluate relationships between maternal prenatal plasma cotinine levels and DNA methylation in umbilical cord blood in newborns using the Infinium HumanMethylation 450K BeadChip.

METHODS

Participants from the Newborn Epigenetics Study cohort who reported not smoking during pregnancy had verified low levels of cotinine from maternal prenatal plasma (0 ng / mL to < 4  ng / mL ), and offspring epigenetic data from umbilical cord blood were included in this study (n = 79 ). Multivariable linear regression models were fit to the data, controlling for cell proportions, age, race, education, and parity. Estimates represent changes in response to any 1 -ng / mL unit increase in exposure.

RESULTS

Multivariable linear regression models yielded 29,049 CpGs that were differentially methylated in relation to increases in cotinine at a 5% false discovery rate. Top CpGs were within or near genes involved in neuronal functioning (PRKG1, DLGAP2, BSG), carcinogenesis (FHIT, HSPC157) and inflammation (AGER). Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses suggest cotinine was related to methylation of gene pathways controlling neuronal signaling, metabolic regulation, cell signaling and regulation, and cancer. Further, enhancers associated with transcription start sites were enriched in altered CpGs. Using an independent sample from the same study population (n = 115 ), bisulfite pyrosequencing was performed with infant cord blood DNA for two genes within our top 20 hits (AGER and PRKG1). Results from pyrosequencing replicated epigenome results for PRKG1 (cg17079497, estimate = - 1.09 , standard error  ( SE ) = 0.45 , p = 0.018 ) but not for AGER (cg09199225; estimate = - 0.16 , SE = 0.21 , p = 0.44 ).

DISCUSSION

Secondhand smoke exposure among nonsmoking women may alter DNA methylation in regions involved in development, carcinogenesis, and neuronal functioning. These novel findings suggest that even low levels of smoke exposure during pregnancy may be sufficient to alter DNA methylation in distinct sites of mixed umbilical cord blood leukocytes in pathways that are known to be altered in cord blood from pregnant active smokers. https://doi.org/10.1289/EHP8099.

RNF39 mediates K48-linked ubiquitination of DDX3X and inhibits RLR-dependent antiviral immunity

Retinoic acid-inducible gene-I (RIG-I)-like receptors (RLRs) are major cytosolic RNA sensors and play crucial roles in initiating antiviral innate immunity. Furthermore, RLRs have been implicated in multiple autoimmune disorders. Thus, RLR activation should be tightly controlled to avoid detrimental effects. "DEAD-box RNA helicase 3, X-linked" (DDX3X) is a key adaptor in RLR signaling, but its regulatory mechanisms remain unknown. Here, we show that the E3 ubiquitin ligase RNF39 inhibits RLR pathways through mediating K48-linked ubiquitination and proteasomal degradation of DDX3X. Concordantly, Rnf39 deficiency enhances RNA virus-triggered innate immune responses and attenuates viral replication. Thus, our results uncover a previously unknown mechanism for the control of DDX3X activity and suggest RNF39 as a priming intervention target for diseases caused by aberrant RLR activation.

Epigenetics and the Environment in Airway Disease: Asthma and Allergic Rhinitis

Asthma and rhinitis are complex, heterogeneous diseases characterized by chronic inflammation of the upper and lower airways. While genome-wide association studies (GWAS) have identified a number of susceptible loci and candidate genes associated with the pathogenesis of asthma and allergic rhinitis (AR), the risk-associated alleles account for only a very small percent of the genetic risk. In allergic airway and other complex diseases, it is thought that epigenetic modifications, including DNA methylation, histone modifications, and non-coding microRNAs, caused by complex interactions between the underlying genome and the environment may account for some of this "missing heritability" and may explain the high degree of plasticity in immune responses. In this chapter, we will focus on the current knowledge of classical epigenetic modifications, DNA methylation and histone modifications, and their potential role in asthma and AR. In particular, we will review epigenetic variations associated with maternal airway disease, demographics, environment, and non-specific associations. The role of specific genetic haplotypes in environmentally induced epigenetic changes are also discussed. A major limitation of many of the current studies of asthma epigenetics is that they evaluate epigenetic modifications in both allergic and non-allergic asthma, making it difficult to distinguish those epigenetic modifications that mediate allergic asthma from those that mediate non-allergic asthma. Additionally, most DNA methylation studies in asthma use peripheral or cord blood due to poor accessibility of airway cells or tissue. Unlike DNA sequences, epigenetic alterations are quite cell- and tissue-specific, and epigenetic changes found in airway tissue or cells may be discordant from that of circulating blood. These two confounding factors should be considered when reviewing epigenetic studies in allergic airway disease.

Advances in spatiotemporal models for non-communicable disease surveillance

Surveillance systems are commonly used to provide early warning detection or to assess an impact of an intervention/policy. Traditionally, the methodological and conceptual frameworks for surveillance have been designed for infectious diseases, but the rising burden of non-communicable diseases (NCDs) worldwide suggests a pressing need for surveillance strategies to detect unusual patterns in the data and to help unveil important risk factors in this setting. Surveillance methods need to be able to detect meaningful departures from expectation and exploit dependencies within such data to produce unbiased estimates of risk as well as future forecasts. This has led to the increasing development of a range of space-time methods specifically designed for NCD surveillance. We present an overview of recent advances in spatiotemporal disease surveillance for NCDs, using hierarchically specified models. This provides a coherent framework for modelling complex data structures, dealing with data sparsity, exploiting dependencies between data sources and propagating the inherent uncertainties present in both the data and the modelling process. We then focus on three commonly used models within the Bayesian Hierarchical Model (BHM) framework and, through a simulation study, we compare their performance. We also discuss some challenges faced by researchers when dealing with NCD surveillance, including how to account for false detection and the modifiable areal unit problem. Finally, we consider how to use and interpret the complex models, how model selection may vary depending on the intended user group and how best to communicate results to stakeholders and the general public.

Recent findings in the genetics and epigenetics of asthma and allergy

In asthma and allergy genetics, a trend towards a few main topics developed over the last 2 years. First, a number of studies have been published recently which focus on overlapping and/or very specific phenotypes: within the allergy spectrum but also reaching beyond, looking for common genetic traits shared between different diseases or disease entities. Secondly, an urgently needed focus has been put on asthma and allergy genetics in populations genetically different from European ancestry. This acknowledges that the majority of new asthma patients today are not white and asthma is a truly worldwide disease. In epigenetics, recent years have seen several large-scale epigenome-wide association studies (EWAS) being published and a further focus was on the interaction between the environment and epigenetic signatures. And finally, the major trends in current asthma and allergy genetics and epigenetics comes from the field of pharmacogenetics, where it is necessary to understand the susceptibility for and mechanisms of current asthma and allergy therapies while at the same time, we need to have scientific answers to the recent availability of novel drugs that hold the promise for a more individualized therapy.

Systems biology and big data in asthma and allergy: recent discoveries and emerging challenges

Asthma is a common condition caused by immune and respiratory dysfunction, and it is often linked to allergy. A systems perspective may prove helpful in unravelling the complexity of asthma and allergy. Our aim is to give an overview of systems biology approaches used in allergy and asthma research. Specifically, we describe recent "omic"-level findings, and examine how these findings have been systematically integrated to generate further insight.Current research suggests that allergy is driven by genetic and epigenetic factors, in concert with environmental factors such as microbiome and diet, leading to early-life disturbance in immunological development and disruption of balance within key immuno-inflammatory pathways. Variation in inherited susceptibility and exposures causes heterogeneity in manifestations of asthma and other allergic diseases. Machine learning approaches are being used to explore this heterogeneity, and to probe the pathophysiological patterns or "endotypes" that correlate with subphenotypes of asthma and allergy. Mathematical models are being built based on genomic, transcriptomic and proteomic data to predict or discriminate disease phenotypes, and to describe the biomolecular networks behind asthma.The use of systems biology in allergy and asthma research is rapidly growing, and has so far yielded fruitful results. However, the scale and multidisciplinary nature of this research means that it is accompanied by new challenges. Ultimately, it is hoped that systems medicine, with its integration of omics data into clinical practice, can pave the way to more precise, personalised and effective management of asthma.

Epigenetic changes: An emerging potential pharmacological target in allergic rhinitis

The importance of epigenetics has increased due to identification of its role in the pathophysiology of a number of diseases including allergic rhinitis. Amongst the different epigenetic changes in allergic retinitis, deacetylation of histone proteins by histone deacetylase (HDACs), hypermethylation of DNA by DNA methyltransferases (DNMT) and alteration in post-transcriptional process by the changes in the levels of miRNA are widely studied. Studies conducted related to allergic rhinitis have shown the elevation in the levels of HDAC1, 3 and 11 in the nasal epithelia and HDAC inhibitors have shown effectiveness in decreasing the symptoms of rhinitis. Their beneficial effects are attributed to restoration of the expression of TWIK-related potassium channel-1, correction of cytokine profile along with normalization of Th1/Th2 imbalance. Another epigenetic change due to increase in DNMT activity may induce DNA hypermethylation in CpG sites in the airway epithelial cells and CD4⁺ T-cells. The reduction in DNA methylation decreases allergic symptoms and normalizes the over-reactive immune system. Mechanistically, allergens may promote the hypermethylation in the promoter region of IFN-γ gene in CD4⁺ T cells via activation of ERK pathway to decrease the expression of IFN-γ. In allergic rhinitis patients, there is also a downregulation of certain miRNAs including miR-135a, miR-146a, miR-181a, miR-155 and upregulation of miRNA19a. This review discusses the studies describing the epigenetic changes taking place in the host cells in response to allergen along with possible mechanisms.

Exploring rare and low-frequency variants in the Saguenay-Lac-Saint-Jean population identified genes associated with asthma and allergy traits

The Saguenay–Lac-Saint-Jean (SLSJ) region is located in northeastern Quebec and is known for its unique demographic history and founder effect. As founder populations are enriched with population-specific variants, we characterized the variants distribution in SLSJ and compared it with four European populations (Finnish, Sweden, United Kingdom and France), of which the Finnish population is another founder population. Targeted sequencing of the coding and non-coding immune regulatory regions of the SLSJ asthma familial cohort and the four European populations were performed. Rare and low-frequency coding and non-coding regulatory variants identified in the SLSJ population were then investigated for variant- and gene-level associations with asthma and allergy-related traits (eosinophil percentage, immunoglobulin (Ig) E levels and lung function). Our data showed that (1) rare or deleterious variants were not enriched in the two founder populations as compared with the three non-founder European populations; (2) a larger proportion of founder population-specific variants occurred with higher frequencies; and (3) low-frequency variants appeared to be more deleterious. Furthermore, a rare variant, rs1386931, located in the 3ʹ-UTR of CXCR6 and intron of FYCO1 was found to be associated with eosinophil percentage. Gene-based analyses identified NRP2, MRPL44 and SERPINE2 to be associated with various asthma and allergy-related traits. Our study demonstrated the usefulness of using a founder population to identify new genes associated with asthma and allergy-related traits; thus better understand the genes and pathways implicated in pathophysiology.

A comparison of multiple testing adjustment methods with block-correlation positively-dependent tests

In high dimensional data analysis (such as gene expression, spatial epidemiology, or brain imaging studies), we often test thousands or more hypotheses simultaneously. As the number of tests increases, the chance of observing some statistically significant tests is very high even when all null hypotheses are true. Consequently, we could reach incorrect conclusions regarding the hypotheses. Researchers frequently use multiplicity adjustment methods to control type I error rates-primarily the family-wise error rate (FWER) or the false discovery rate (FDR)-while still desiring high statistical power. In practice, such studies may have dependent test statistics (or p-values) as tests can be dependent on each other. However, some commonly-used multiplicity adjustment methods assume independent tests. We perform a simulation study comparing several of the most common adjustment methods involved in multiple hypothesis testing, under varying degrees of block-correlation positive dependence among tests.