Lymphocyte DNA methylation mediates genetic risk at shared immune-mediated disease loci

Expression levels of GSDMB and ORMDL3 are associated with relapsing-remitting multiple sclerosis and IKZF3 rs12946510 variant

Multiple sclerosis (MS), a noncurable autoimmune neurodegenerative disease, requires constant research that could improve understanding of both environmental and genetic factors that lead to its occurrence and/or progression. Recognition of the genetic basis of MS further leads to an investigation of the regulatory role of genetic variants on gene expression. Among risk variants for MS, Ikaros zinc finger 3 (IKZF3) gene variant rs12946510 was identified as one of the top-ranked and the expression quantitative trait loci (eQTL) for genes residing in chromosomal locus 17q12-21. The study aimed to investigate the association of gene expression of the immunologically relevant genes, which map to indicated locus, ORMDL3, GSDMB, and IKZF3, with MS and rs12946510 genotype, taking into account disease phase, clinical parameters of disease progression, and severity and immunomodulatory therapy. We used TaqMan® technology for both allelic discrimination and gene expression determination in 67 relapsing MS patients and 50 healthy controls. Decreased ORMDL3 and GSDMB mRNA levels had significant associations with MS and rs12946510 TT rare homozygote among patients. Significant positive correlations between ORMDL3 and GSDMB mRNA expression were observed in both patients and controls. We detected the significant between-effect of sex and rs12946510 on the expression of ORMDL3 in the patient group and interferon β therapy and rs12946510 on GSDMB expression. Our results show the association of ORMDL3 and GSDMB mRNA expression with the clinical manifestation of MS and confirm that IKZF3 rs12946510 exerts the eQTL effect on both genes in multiple sclerosis. Besides providing novel insight related to MS phases and interferon β therapy, the study results confirm previous studies on regulatory genetic variants, autoimmunity, and MS.

Site of invasion revisited: epigenetic drivers of joint destruction in RA

New analytical methods and the increasing availability of synovial biopsies have recently provided unprecedented insights into synovial activation in general and synovial fibroblast (SF) biology in particular. In the course of this development, SFs have become one of the most rapidly evolving and exciting fields of rheumatoid arthritis (RA) research. While their active role in the invasion of RA synovium into cartilage has long been studied, recent studies have brought new aspects of their heterogeneity and propagation in RA. This review integrates old and new evidence to give an overview picture of the processes active at the sites of invasive synovial tissue growth in RA.

Characterization of age-associated B cells in early drug-naïve rheumatoid arthritis patients

Age-associated B cells (ABCs) are an immune cell subset linked to autoimmunity, infection and ageing, and whose pathophysiological importance was recently highlighted using single cell synovial tissue profiling. To elucidate their pathophysiological relevance, peripheral blood (PB) ABCs from early rheumatoid arthritis (eRA) patients naïve to disease-modifying anti-rheumatic drugs (DMARDs) were compared with their synovial fluid (SF) counterparts, and to PB ABCs from psoriatic arthritis patients and healthy controls. PB and SF B-cell subsets were phenotyped by multi-parameter flow cytometry, sorted and subjected to gene expression profiling (NanoString nCounter® Immunology V2 Panel) and functional characterization (stimulated cytokine measurements by immunoassay). PB ABCs of eRA patients, which are transcriptionally distinct from those of control cohorts, express chemokine receptors and adhesion molecules, such as CXCR3, that favour homing to inflammatory sites over lymphoid tissue. These cells are an activated, class-switched B-cell subset expressing high levels of HLA-DR, co-stimulatory molecules and T-bet. Their secretion profile includes IL-12p70 and IL-23 but low levels of IL-10. High surface expression of FcRL family members, including FcRL3, furthermore suggests a role for these cells in autoimmunity. Finally, and unlike in the periphery where they are rare, ABCs are the predominant B-cell subsets in SF. These observations indicate the predilection of ABCs for inflammatory tissue in RA, where their propensity for antigen presentation and pro-inflammatory phenotype may support autoimmune pathology. Their potential as a therapeutic target therefore warrants further study.

Quantitative trait locus (xQTL) approaches identify risk genes and drug targets from human non-coding genomes

Advances and reduction of costs in various sequencing technologies allow for a closer look at variations present in the non-coding regions of the human genome. Correlating non-coding variants with large-scale multi-omic data holds the promise not only of a better understanding of likely causal connections between non-coding DNA and expression of traits but also identifying potential disease-modifying medicines. Genome-phenome association studies have created large datasets of DNA variants that are associated with multiple traits or diseases, such as Alzheimer's disease; yet, the functional consequences of variants, in particular of non-coding variants, remain largely unknown. Recent advances in functional genomics and computational approaches have led to the identification of potential roles of DNA variants, such as various quantitative trait locus (xQTL) techniques. Multi-omic assays and analytic approaches toward xQTL have identified links between genetic loci and human transcriptomic, epigenomic, proteomic and metabolomic data. In this review, we first discuss the recent development of xQTL from multi-omic findings. We then highlight multimodal analysis of xQTL and genetic data for identification of risk genes and drug targets using Alzheimer's disease as an example. We finally discuss challenges and future research directions (e.g. artificial intelligence) for annotation of non-coding variants in complex diseases.

Interferon-α-mediated therapeutic resistance in early rheumatoid arthritis implicates epigenetic reprogramming

OBJECTIVES

An interferon (IFN) gene signature (IGS) is present in approximately 50% of early, treatment naive rheumatoid arthritis (eRA) patients where it has been shown to negatively impact initial response to treatment. We wished to validate this effect and explore potential mechanisms of action.

METHODS

In a multicentre inception cohort of eRA patients (n=191), we examined the whole blood IGS (MxA, IFI44L, OAS1, IFI6, ISG15) with reference to circulating IFN proteins, clinical outcomes and epigenetic influences on circulating CD19+ B and CD4+ T lymphocytes.

RESULTS

We reproduced our previous findings demonstrating a raised baseline IGS. We additionally showed, for the first time, that the IGS in eRA reflects circulating IFN-α protein. Paired longitudinal analysis demonstrated a significant reduction between baseline and 6-month IGS and IFN-α levels (p<0.0001 for both). Despite this fall, a raised baseline IGS predicted worse 6-month clinical outcomes such as increased disease activity score (DAS-28, p=0.025) and lower likelihood of a good EULAR clinical response (p=0.034), which was independent of other conventional predictors of disease activity and clinical response. Molecular analysis of CD4+ T cells and CD19+ B cells demonstrated differentially methylated CPG sites and dysregulated expression of disease relevant genes, including PARP9, STAT1, and EPSTI1, associated with baseline IGS/IFNα levels. Differentially methylated CPG sites implicated altered transcription factor binding in B cells (GATA3, ETSI, NFATC2, EZH2) and T cells (p300, HIF1α).

CONCLUSIONS

Our data suggest that, in eRA, IFN-α can cause a sustained, epigenetically mediated, pathogenic increase in lymphocyte activation and proliferation, and that the IGS is, therefore, a robust prognostic biomarker. Its persistent harmful effects provide a rationale for the initial therapeutic targeting of IFN-α in selected patients with eRA.

TET2 Regulates 5-Hydroxymethylcytosine Signature and CD4+ T-Cell Balance in Allergic Rhinitis

Purpose

Previous studies have shown the role of ten-eleven translocation 2 (TET2) in CD4⁺ T cells. However, its function in CD4⁺ T cells under allergic inflammation is unclear. We aimed to investigate the epigenomic distribution of DNA 5-hydroxymethylcytosine (5hmC) and the role of TET2 in CD4⁺ T cells of allergic rhinitis (AR).

Methods

The hMeDIP-seq was performed to identify sequences with 5hmC deposition in CD4⁺ T cells of AR patients. Tet2-deficient or wild type mice were stimulated with ovalbumin (OVA) to develop an AR mouse model. The histopathology in nasal mucosae, Th1/Th2/Treg/Th17 cell percentage, concentrations of Th-related cytokines, expression of Tet and differential hydroxymethylated genes (DhMG), and the global deposition of 5hmC in sorted CD4⁺ T cells were detected.

Results

Epigenome-wide 5hmC landscape and DhMG in the CD4⁺ T cells of AR patients were identified. Tet2 depletion did not led to spontaneous inflammation. However, under the stimulation of allergen, OVA, loss of Tet2 resulted in the exacerbation of allergic inflammation, which was characterized by severer allergic symptoms, more inflammatory cells infiltrating the nasal lamina propria, sharper imbalances between Th1/Th2 and Treg/Th17 cells, and excessive secretion of OVA-specific IgE and Th2-related cytokines. Moreover, altered mRNA production of several DhMG and sharp decrease in 5hmC deposition were also observed in Tet2-deficient OVA-exposed mice.

Conclusions

TET2 may regulate DNA 5hmC, DhMG expressions, and CD4⁺ T cell balance in AR.

Genomic Multiple Sclerosis Risk Variants Modulate the Expression of the ANKRD55-IL6ST Gene Region in Immature Dendritic Cells

Intronic single-nucleotide polymorphisms (SNPs) in the ANKRD55 gene are associated with the risk for multiple sclerosis (MS) and rheumatoid arthritis by genome-wide association studies (GWAS). The risk alleles have been linked to higher expression levels of ANKRD55 and the neighboring IL6ST (gp130) gene in CD4+ T lymphocytes of healthy controls. The biological function of ANKRD55, its role in the immune system, and cellular sources of expression other than lymphocytes remain uncharacterized. Here, we show that monocytes gain capacity to express ANKRD55 during differentiation in immature monocyte-derived dendritic cells (moDCs) in the presence of interleukin (IL)-4/granulocyte-macrophage colony-stimulating factor (GM-CSF). ANKRD55 expression levels are further enhanced by retinoic acid agonist AM580 but downregulated following maturation with interferon (IFN)-γ and lipopolysaccharide (LPS). ANKRD55 was detected in the nucleus of moDC in nuclear speckles. We also analyzed the adjacent IL6ST, IL31RA, and SLC38A9 genes. Of note, in healthy controls, MS risk SNP genotype influenced ANKRD55 and IL6ST expression in immature moDC in opposite directions to that in CD4+ T cells. This effect was stronger for a partially correlated SNP, rs13186299, that is located, similar to the main MS risk SNPs, in an ANKRD55 intron. Upon analysis in MS patients, the main GWAS MS risk SNP rs7731626 was associated with ANKRD55 expression levels in CD4+ T cells. MoDC-specific ANKRD55 and IL6ST mRNA levels showed significant differences according to the clinical form of the disease, but, in contrast to healthy controls, were not influenced by genotype. We also measured serum sgp130 levels, which were found to be higher in homozygotes of the protective allele of rs7731626. Our study characterizes ANKRD55 expression in moDC and indicates monocyte-to-dendritic cell (Mo-DC) differentiation as a process potentially influenced by MS risk SNPs.

Association of ANKRD55 Gene Polymorphism with HT: A Protective Factor for Disease Susceptibility

PURPOSE

Recent studies have shown that Ankyrin Repeat Domain 55 (ANKRD55) gene polymorphism is a risk factor for multiple autoimmune diseases, but its association with autoimmune thyroid diseases (AITDs) has not been reported. The purpose of this study was to investigate the potential relationship between polymorphism of the ANKRD55 gene and AITDs.

METHODS

For this study, we enrolled 2050 subjects, consisting of 1220 patients with AITD and 830 healthy subjects. Five loci (rs321776, rs191205, rs7731626, rs415407, and rs159572) of the ANKRD55 gene were genotyped using Multiplex PCR combined with high-throughput sequencing.

RESULTS

The results showed that the allele frequencies of rs7731626 and rs159572 loci in HT patients were lower than those in normal controls (P=0.048 and P=0.03, respectively). In different genetic model analyses, rs7731626 and rs159572 were also significantly correlated with HT in allele, dominant and additive models before and after age and sex adjustment. There were no differences in rs321776, rs191205, or rs415407 of the ANKRD55 gene in allele frequency or genotype frequency between AITDs patients and controls.

CONCLUSIONS

This study for the first time found that rs7731626 and rs159572 of ANKRD55 were significantly correlated with HT, and individuals carrying the A allele at these two loci had a lower probability of developing HT.

A Bayesian network approach incorporating imputation of missing data enables exploratory analysis of complex causal biological relationships

Bayesian networks can be used to identify possible causal relationships between variables based on their conditional dependencies and independencies, which can be particularly useful in complex biological scenarios with many measured variables. Here we propose two improvements to an existing method for Bayesian network analysis, designed to increase the power to detect potential causal relationships between variables (including potentially a mixture of both discrete and continuous variables). Our first improvement relates to the treatment of missing data. When there is missing data, the standard approach is to remove every individual with any missing data before performing analysis. This can be wasteful and undesirable when there are many individuals with missing data, perhaps with only one or a few variables missing. This motivates the use of imputation. We present a new imputation method that uses a version of nearest neighbour imputation, whereby missing data from one individual is replaced with data from another individual, their nearest neighbour. For each individual with missing data, the subsets of variables to be used to select the nearest neighbour are chosen by sampling without replacement the complete data and estimating a best fit Bayesian network. We show that this approach leads to marked improvements in the recall and precision of directed edges in the final network identified, and we illustrate the approach through application to data from a recent study investigating the causal relationship between methylation and gene expression in early inflammatory arthritis patients. We also describe a second improvement in the form of a pseudo-Bayesian approach for upweighting certain network edges, which can be useful when there is prior evidence concerning their directions.

Data analysis using Bayesian networks can help identify possible causal relationships between measured biological variables. Here we propose two improvements to an existing method for Bayesian network analysis. Our first improvement relates to the treatment of missing data. When there is missing data, the standard approach is to remove every individual with any missing data before performing analysis, even if only one or a few variables are missing. This is undesirable as it can reduce the ability of the approach to infer correct relationships. We propose a new method to instead fill in (impute) the missing data prior to analysis. We show through computer simulations that our method improves the reliability of the results obtained, and we illustrate the proposed approach by applying it to data from a recent study in early inflammatory arthritis. We also describe a second improvement involving the upweighting of certain network edges, which can be useful when there is prior evidence concerning their directions.

Identification of tissue-specific and common methylation quantitative trait loci in healthy individuals using MAGAR

Background

Understanding the influence of genetic variants on DNA methylation is fundamental for the interpretation of epigenomic data in the context of disease. There is a need for systematic approaches not only for determining methylation quantitative trait loci (methQTL), but also for discriminating general from cell type-specific effects.

Results

Here, we present a two-step computational framework MAGAR (https://bioconductor.org/packages/MAGAR), which fully supports the identification of methQTLs from matched genotyping and DNA methylation data, and additionally allows for illuminating cell type-specific methQTL effects. In a pilot analysis, we apply MAGAR on data in four tissues (ileum, rectum, T cells, B cells) from healthy individuals and demonstrate the discrimination of common from cell type-specific methQTLs. We experimentally validate both types of methQTLs in an independent data set comprising additional cell types and tissues. Finally, we validate selected methQTLs located in the PON1, ZNF155, and NRG2 genes by ultra-deep local sequencing. In line with previous reports, we find cell type-specific methQTLs to be preferentially located in enhancer elements.

Conclusions

Our analysis demonstrates that a systematic analysis of methQTLs provides important new insights on the influences of genetic variants to cell type-specific epigenomic variation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13072-021-00415-6.

Cell-type-specific meQTLs extend melanoma GWAS annotation beyond eQTLs and inform melanocyte gene-regulatory mechanisms

Although expression quantitative trait loci (eQTLs) have been powerful in identifying susceptibility genes from genome-wide association study (GWAS) findings, most trait-associated loci are not explained by eQTLs alone. Alternative QTLs, including DNA methylation QTLs (meQTLs), are emerging, but cell-type-specific meQTLs using cells of disease origin have been lacking. Here, we established an meQTL dataset by using primary melanocytes from 106 individuals and identified 1,497,502 significant cis-meQTLs. Multi-QTL colocalization with meQTLs, eQTLs, and mRNA splice-junction QTLs from the same individuals together with imputed methylome-wide and transcriptome-wide association studies identified candidate susceptibility genes at 63% of melanoma GWAS loci. Among the three molecular QTLs, meQTLs were the single largest contributor. To compare melanocyte meQTLs with those from malignant melanomas, we performed meQTL analysis on skin cutaneous melanomas from The Cancer Genome Atlas (n = 444). A substantial proportion of meQTL probes (45.9%) in primary melanocytes is preserved in melanomas, while a smaller fraction of eQTL genes is preserved (12.7%). Integration of melanocyte multi-QTLs and melanoma meQTLs identified candidate susceptibility genes at 72% of melanoma GWAS loci. Beyond GWAS annotation, meQTL-eQTL colocalization in melanocytes suggested that 841 unique genes potentially share a causal variant with a nearby methylation probe in melanocytes. Finally, melanocyte trans-meQTLs identified a hotspot for rs12203592, a cis-eQTL of a transcription factor, IRF4, with 131 candidate target CpGs. Motif enrichment and IRF4 ChIP-seq analysis demonstrated that these target CpGs are enriched in IRF4 binding sites, suggesting an IRF4-mediated regulatory network. Our study highlights the utility of cell-type-specific meQTLs.

Pyroptosis, metabolism, and tumor immune microenvironment

In response to a wide range of stimulations, host cells activate pyroptosis, a kind of inflammatory cell death which is provoked by the cytosolic sensing of danger signals and pathogen infection. In manipulating the cleavage of gasdermins (GSDMs), researchers have found that GSDM proteins serve as the real executors and the deterministic players in fate decisions of pyroptotic cells. Whether inflammatory characteristics induced by pyroptosis could cause damage the host or improve immune activity is largely dependent on the context, timing, and response degree. Here, we systematically review current points involved in regulatory mechanisms and the multidimensional roles of pyroptosis in several metabolic diseases and the tumor microenvironment. Targeting pyroptosis may reveal potential therapeutic avenues.

Variations in DNA methylation and allograft rejection

PURPOSE OF REVIEW

DNA methylation is involved in gene transcription and as such important for cellular function. Here, the literature on DNA methylation in relation to acute rejection is summarized with a focus on the potential clinical utility of DNA methylation for monitoring transplant rejection.

RECENT FINDINGS

The tight transcriptional control of DNA methylation in immune cell function, e.g. demethylation in regulatory T-cell-specific genes for stable immunosuppressive capacities, suggests an important role for DNA methylation variations in the antidonor-directed immune response. Until today, differentially methylated DNA in immune cells, however, has not been described at the moment of allograft rejection. The ability to locus-specific modify DNA methylation could facilitate the generation of stable cells for cellular therapy purposes. The unique cell-specific characteristics of DNA methylation provide the opportunity to identify its cellular origin. Examining methylation of cell-free DNA in blood or urine may serve as a 'liquid biopsy' enabling minimally invasive detection of allograft rejection.

SUMMARY

Actual research publications on DNA methylation in relation to allograft rejection are scarce, which makes it challenging to determine its potential clinical value. Extensive research is needed to investigate the value of DNA methylation in early recognition, diagnosis, and/or successful treatment of allograft rejection.

Multi-Level Analyses of Genome-Wide Association Study to Reveal Significant Risk Genes and Pathways in Neuromyelitis Optica Spectrum Disorder

Background

Neuromyelitis optica spectrum disorder (NMOSD) is an inflammatory disease of the central nervous system and it is understandable that environmental and genetic factors underlie the etiology of NMOSD. However, the susceptibility genes and associated pathways of NMOSD patients who are AQP4-Ab positive and negative have not been elucidated.

Methods

Secondary analysis from a NMOSD Genome-wide association study (GWAS) dataset originally published in 2018 (215 NMOSD cases and 1244 controls) was conducted to identify potential susceptibility genes and associated pathways in AQP4-positive and negative NMOSD patients, respectively (132 AQP4-positive and 83 AQP4-negative).

Results

In AQP4-positive NMOSD cases, five shared risk genes were obtained at chromosome 6 in AQP4-positive NMOSD cases by using more stringent p-Values in both methods (p < 0.05/16,532), comprising CFB, EHMT2, HLA-DQA1, MSH5, and SLC44A4. Fifty potential susceptibility gene sets were determined and 12 significant KEGG pathways were identified. Sixty-seven biological process pathways, 32 cellular-component pathways, and 29 molecular-function pathways with a p-Value of <0.05 were obtained from the GO annotations of the 128 pathways identified. In the AQP4 negative NMOSD group, no significant genes were obtained by using more stringent p-Values in both methods (p < 0.05/16,485). The 22 potential susceptibility gene sets were determined. There were no shared potential susceptibility genes between the AQP4-positive and negative groups, furthermore, four significant KEGG pathways were also identified. Of the GO annotations of the 165 pathways identified, 99 biological process pathways, 37 cellular-component pathways, and 29 molecular-function pathways with a p-Value of <0.05 were obtained.

Conclusion

The potential molecular mechanism underlying NMOSD may be related to proteins encoded by these novel genes in complements, antigen presentation, and immune regulation. The new results may represent an improved comprehension of the genetic and molecular mechanisms underlying NMOSD.

Cell-specific epigenetic drivers of pathogenesis in rheumatoid arthritis

Rheumatoid arthritis is a complex, inflammatory autoimmune disease, which is characterized by pain, swelling and joint damage driven by the altered behavior of a number of different cell types such as synovial fibroblasts macrophages and lymphocytes. The mechanism underlying pathogenesis is unclear but increasing evidence points to altered epigenetic regulation within these cell types which promotes the activated destructive behavior that underlies disease pathogenesis. This review summarizes the key epigenetic modifications in the most important cells types in rheumatoid arthritis, which are associated with disease activity. We also discuss emerging avenues of research focusing on readers of epigenetic markers which may serve to be potential therapeutic targets.