IFI44L promoter methylation as a blood biomarker for systemic lupus erythematosus

Bioinformatics analysis of potential common pathogenic mechanisms for COVID-19 infection and primary Sjogren’s syndrome

Background

Accumulating evidence has revealed that the prevalence of Coronavirus 2019 (COVID-19) was significantly higher in patients with primary Sjogren’s syndrome (pSS) compared to the general population. However, the mechanism remains incompletely elucidated. This study aimed to further investigate the molecular mechanisms underlying the development of this complication.

Methods

The gene expression profiles of COVID-19 (GSE157103) and pSS (GSE40611) were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the common differentially expressed genes (DEGs) for pSS and COVID-19, functional annotation, protein-protein interaction (PPI) network, module construction and hub gene identification were performed. Finally, we constructed transcription factor (TF)-gene regulatory network and TF-miRNA regulatory network for hub genes.

Results

A total of 40 common DEGs were selected for subsequent analyses. Functional analyses showed that cellular components and metabolic pathways collectively participated in the development and progression of pSS and COVID-19. Finally, 12 significant hub genes were identified using the cytoHubba plugin, including CMPK2, TYMS, RRM2, HERC5, IFI44L, IFI44, IFIT2, IFIT1, IFIT3, MX1, CDCA2 and TOP2A, which had preferable values as diagnostic markers for COVID-19 and pSS.

Conclusions

Our study reveals common pathogenesis of pSS and COVID-19. These common pathways and pivotal genes may provide new ideas for further mechanistic studies.

Identification of COVID-19-Specific Immune Markers Using a Machine Learning Method

Notably, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a tight relationship with the immune system. Human resistance to COVID-19 infection comprises two stages. The first stage is immune defense, while the second stage is extensive inflammation. This process is further divided into innate and adaptive immunity during the immune defense phase. These two stages involve various immune cells, including CD4⁺ T cells, CD8⁺ T cells, monocytes, dendritic cells, B cells, and natural killer cells. Various immune cells are involved and make up the complex and unique immune system response to COVID-19, providing characteristics that set it apart from other respiratory infectious diseases. In the present study, we identified cell markers for differentiating COVID-19 from common inflammatory responses, non-COVID-19 severe respiratory diseases, and healthy populations based on single-cell profiling of the gene expression of six immune cell types by using Boruta and mRMR feature selection methods. Some features such as IFI44L in B cells, S100A8 in monocytes, and NCR2 in natural killer cells are involved in the innate immune response of COVID-19. Other features such as ZFP36L2 in CD4⁺ T cells can regulate the inflammatory process of COVID-19. Subsequently, the IFS method was used to determine the best feature subsets and classifiers in the six immune cell types for two classification algorithms. Furthermore, we established the quantitative rules used to distinguish the disease status. The results of this study can provide theoretical support for a more in-depth investigation of COVID-19 pathogenesis and intervention strategies.

EWAS of post-COVID-19 patients shows methylation differences in the immune-response associated gene, IFI44L, three months after COVID-19 infection

Although substantial progress has been made in managing COVID-19, it is still difficult to predict a patient’s prognosis. We explored the epigenetic signatures of COVID-19 in peripheral blood using data from an ongoing prospective observational study of COVID-19 called the Norwegian Corona Cohort Study. A series of EWASs were performed to compare the DNA methylation profiles between COVID-19 cases and controls three months post-infection. We also investigated differences associated with severity and long-COVID. Three CpGs—cg22399236, cg03607951, and cg09829636—were significantly hypomethylated (FDR < 0.05) in COVID-19 positive individuals. cg03607951 is located in IFI44L which is involved in innate response to viral infection and several systemic autoimmune diseases. cg09829636 is located in ANKRD9, a gene implicated in a wide variety of cellular processes, including the degradation of IMPDH2. The link between ANKRD9 and IMPDH2 is striking given that IMPDHs are considered therapeutic targets for COVID-19. Furthermore, gene ontology analyses revealed pathways involved in response to viruses. The lack of significant differences associated with severity and long-COVID may be real or reflect limitations in sample size. Our findings support the involvement of interferon responsive genes in the pathophysiology of COVID-19 and indicate a possible link to systemic autoimmune diseases.

Identification of Key Biomarkers in Systemic Lupus Erythematosus by a Multi-Cohort Analysis

Systemic lupus erythematosus (SLE) is an autoimmune disease that affects multiple body systems with heterogeneous clinical manifestations. Since gene expression analyses have been accomplished on diverse types of samples to specify SLE-related genes, single-cohort transcriptomics have not produced reliable results. Using an integrated multi-cohort analysis framework, we analyzed whole blood cells from SLE patients from three transcriptomics cohorts (n=1222) and identified a five-gene signature that distinguished SLE patients from controls. We validated the diagnostic performance of this five-gene signature in six independent validation cohorts (n= 469), with an area under the receiver operating characteristic curve of 0.88 [95% CI 0.7 − 0.96]. This five-gene signature may be associated with the proportion of SLE immune cells, and generalizable across ages and sample types with real diagnostic value for clinical application.

Association of Immune-Related Genetic and Epigenetic Alterations with Lupus Nephritis

BACKGROUND

The familial clustering phenomenon together with environmental influences indicates the presence of a genetic and epigenetic predisposition to systematic lupus erythematosus (SLE). Interestingly, regarding lupus nephritis (LN), the worst complication of SLE, mortality, and morbidity were not consistent with SLE in relation to sexuality and ethnicity.

SUMMARY

Genetic and epigenetic alterations in LN include genes and noncoding RNAs that are involved in antigen-presenting, complements, immune cell infiltration, interferon pathways, and so on. Once genetic or epigenetic change occurs alone or simultaneously, they will promote the formation of immune complexes with autoantibodies that target various autoantigens, which results in inflammatory cytokines and autoreactive immune cells colonizing renal tissues and contributing to LN.

KEY MESSAGES

Making additional checks for immunopathology-related heredity and epigenetic factors may lead to a more holistic perspective of LN.

Clinical Values of the Identified Hub Genes in Systemic Lupus Erythematosus

Objective

This study was conducted to identify the biomarkers and mechanisms associated with systemic lupus erythematosus(SLE) at a transcriptome level.

Methods

Microarray datasets were downloaded, and differentially expressed genes (DEGs) were identified. Enrichment and protein-protein interaction networks were analyzed, and hub genes were discovered. The levels of top 10 hub genes were validated by another dataset. The diagnostic accuracy of the hub genes was evaluated with the area under the curve of the receiver operating characteristic curve (ROC-AUC). The odds ratios (OR) and 95% confidence intervals (CI) of the relationship between clinical manifestations and hub genes were estimated with multivariable logistic regression. The relationships between the expression levels of the 10 identified hub genes and SLEDAI scores were subjected to linear correlation analysis. Changes in the expression levels of the hub genes during patient follow-up were examined through one-way repeated measures ANOVA.

Results

A total of 136 DEGs were identified. Enrichment analysis indicated that DEGs were primarily enriched in type I interferon-associated pathways. The identified hub genes were verified by the GSE65391 dataset. The 10 hub genes had good diagnostic performances. Seven (except IFI6, OAS1 and IFIT3) of the 10 hub genes were positively associated with SLEDAI. The combination models of IFIT3, ISG15, MX2, and IFIH1 were effective in diagnosing mucosal ulcers among patients with SLE. The expression levels of IRF7, IFI35, IFIT3, and ISG15 decreased compared with the baseline expression (not significantly).

Conclusions

In this work, the clinical values of the identified hub genes in SLE were demonstrated.

Epigenetic Regulation of IFI44L Expression in Monocytes Affects the Functions of Monocyte-Derived Dendritic Cells in Systemic Lupus Erythematosus

Background

Interferon-inducible 44 like (IFI44L) is a newly discovered interferon-induced gene and has been reported to overexpress in systemic lupus erythematosus (SLE). However, little is known about the mechanism and function of IFI44L overexpression in SLE. In this study, we aimed to investigate the epigenetic mechanism of IFI44L overexpression in SLE monocyte and its potential functions contributing to the pathogenesis of SLE.

Methods

We collected peripheral blood from 20 SLE patients and 20 healthy controls. Expression of IFI44L in monocytes and effects of different signal transducers and activators of transcription (STAT) pathway inhibitors on IFI44L expression were detected. Recruitment of ten-eleven translocation protein (TET) by STAT and methylation of IFI44L promoter were evaluated. Effects of IFI44L overexpression on the expression of surface markers on monocyte-derived dendritic cells (Mo-DCs) were analyzed. T cell differentiation mediated by Mo-DCs and related cytokines production were also analyzed.

Results

Expression level of IFI44L was significantly increased in SLE monocyte. IFI44L expression was decreased most significantly in STAT3 inhibitor compared with other inhibitors. STAT3 regulated IFI44L expression and interacted with TET2 which induced DNA demethylation of IFI44L promoter. Overexpression of IFI44L in monocyte enhanced the maturation and functions of Mo-DC by upregulating costimulatory receptors and inducing Th1/Th17-related cytokines when cocultured with naïve CD4+ T cells.

Conclusion

TET2 recruited by STAT3 induces DNA demethylation of IFI44L promoter which promotes IFI44L overexpression in monocyte contributing to the pathogenesis of SLE by enhancing the maturation and functions of Mo-DC. IFI44L is expected to become a new target for treatment of SLE.

Identifying Methylation Signatures and Rules for COVID-19 With Machine Learning Methods

The occurrence of coronavirus disease 2019 (COVID-19) has become a serious challenge to global public health. Definitive and effective treatments for COVID-19 are still lacking, and targeted antiviral drugs are not available. In addition, viruses can regulate host innate immunity and antiviral processes through the epigenome to promote viral self-replication and disease progression. In this study, we first analyzed the methylation dataset of COVID-19 using the Monte Carlo feature selection method to obtain a feature list. This feature list was subjected to the incremental feature selection method combined with a decision tree algorithm to extract key biomarkers, build effective classification models and classification rules that can remarkably distinguish patients with or without COVID-19. EPSTI1, NACAP1, SHROOM3, C19ORF35, and MX1 as the essential features play important roles in the infection and immune response to novel coronavirus. The six significant rules extracted from the optimal classifier quantitatively explained the expression pattern of COVID-19. Therefore, these findings validated that our method can distinguish COVID-19 at the methylation level and provide guidance for the diagnosis and treatment of COVID-19.

The Role of Oxidative Stress in Epigenetic Changes Underlying Autoimmunity

Significance: Epigenetic dysregulation plays an important role in the pathogenesis and development of autoimmune diseases. Oxidative stress is associated with autoimmunity and is also known to alter epigenetic mechanisms. Understanding the interplay between oxidative stress and epigenetics will provide insights into the role of environmental triggers in the development of autoimmunity in genetically susceptible individuals. Recent Advances: Abnormal DNA and histone methylation patterns in genes and pathways involved in interferon and tumor necrosis factor signaling, cellular survival, proliferation, metabolism, organ development, and autoantibody production have been described in autoimmunity. Inhibitors of DNA and histone methyltransferases showed potential therapeutic effects in animal models of autoimmune diseases. Oxidative stress can regulate epigenetic mechanisms via effects on DNA damage repair mechanisms, cellular metabolism and the local redox environment, and redox-sensitive transcription factors and pathways. Critical Issues: Studies looking into oxidative stress and epigenetics in autoimmunity are relatively limited. The number of available longitudinal studies to explore the role of DNA methylation in the development of autoimmune diseases is small. Future Directions: Exploring the relationship between oxidative stress and epigenetics in autoimmunity will provide clues for potential preventative measures and treatment strategies. Inception cohorts with longitudinal follow-up would help to evaluate epigenetic marks as potential biomarkers for disease development, progression, and treatment response in autoimmunity. Antioxid. Redox Signal. 36, 423-440.

Epigenetic Modifications in the Pathogenesis of Systemic Sclerosis

Systemic sclerosis is a rare chronic autoimmune disease, which mainly manifests as immune disorders, vascular damage, and progressive fibrosis. The etiology of SSc is complex and involves multiple factors. Both genetic and environmental factors are involved in its pathogenesis. As one of the molecular mechanisms of environmental factors, epigenetic regulation plays an important role in the occurrence and development of systemic sclerosis, which involves DNA methylation, histone modification and non-coding RNA regulation. This review summarizes research advances in epigenetics, including exosomes, lncRNA, and mentions possible biomarkers and therapeutic targets among them.

Identification of Diagnostic Biomarkers in Systemic Lupus Erythematosus Based on Bioinformatics Analysis and Machine Learning

Systemic lupus erythematosus (SLE) is a complex autoimmune disease that affects several organs and causes variable clinical symptoms. Exploring new insights on genetic factors may help reveal SLE etiology and improve the survival of SLE patients. The current study is designed to identify key genes involved in SLE and develop potential diagnostic biomarkers for SLE in clinical practice. Expression data of all genes of SLE and control samples in GSE65391 and GSE72509 datasets were downloaded from the Gene Expression Omnibus (GEO) database. A total of 11 accurate differentially expressed genes (DEGs) were identified by the "limma" and "RobustRankAggreg" R package. All these genes were functionally associated with several immune-related biological processes and a single KEGG (Kyoto Encyclopedia of Genes and Genome) pathway of necroptosis. The PPI analysis showed that IFI44, IFI44L, EIF2AK2, IFIT3, IFITM3, ZBP1, TRIM22, PRIC285, XAF1, and PARP9 could interact with each other. In addition, the expression patterns of these DEGs were found to be consistent in GSE39088. Moreover, Receiver operating characteristic (ROC) curves analysis indicated that all these DEGs could serve as potential diagnostic biomarkers according to the area under the ROC curve (AUC) values. Furthermore, we constructed the transcription factor (TF)-diagnostic biomarker-microRNA (miRNA) network composed of 278 nodes and 405 edges, and a drug-diagnostic biomarker network consisting of 218 nodes and 459 edges. To investigate the relationship between diagnostic biomarkers and the immune system, we evaluated the immune infiltration landscape of SLE and control samples from GSE6539. Finally, using a variety of machine learning methods, IFI44 was determined to be the optimal diagnostic biomarker of SLE and then verified by quantitative real-time PCR (qRT-PCR) in an independent cohort. Our findings may benefit the diagnosis of patients with SLE and guide in developing novel targeted therapy in treating SLE patients.

Comprehensive analysis of epigenetic modifications and immune-cell infiltration in tissues from patients with systemic lupus erythematosus

Aim: To explore potential abnormal epigenetic modifications and immune-cell infiltration in tissues from systemic lupus erythematosus (SLE) patients. Materials & methods: To utilize bioinformatics analysis and 'wet lab' methods to identify and verify differentially expressed genes in multiple targeted organs in SLE. Results: Seven key genes, IFI44, IFI44L, IFIT1, IFIT3, PLSCR1, RSAD2 and OAS2, which are regulated by epigenetics and may be involved in the pathogenesis of SLE, are identified by combined long noncoding RNA-miRNA-mRNA network analysis and DNA methylation analysis. The results of quantitative reverse transcription PCR, immunohistochemistry and DNA methylation analysis confirmed the potential of these genes as biomarkers. Conclusion: This study reveals the potential mechanisms in SLE from epigenetic modifications and immune-cell infiltration, providing diagnostic biomarkers and therapeutic targets for SLE.

Nucleic Acid-Sensing and Interferon-Inducible Pathways Show Differential Methylation in MZ Twins Discordant for Lupus and Overexpression in Independent Lupus Samples: Implications for Pathogenic Mechanism and Drug Targeting

Systemic lupus erythematosus (SLE) is a chronic, multisystem, autoimmune inflammatory disease with genomic and non-genomic contributions to risk. We hypothesize that epigenetic factors are a significant contributor to SLE risk and may be informative for identifying pathogenic mechanisms and therapeutic targets. To test this hypothesis while controlling for genetic background, we performed an epigenome-wide analysis of DNA methylation in genomic DNA from whole blood in three pairs of female monozygotic (MZ) twins of European ancestry, discordant for SLE. Results were replicated on the same array in four cell types from a set of four Danish female MZ twin pairs discordant for SLE. Genes implicated by the epigenetic analyses were then evaluated in 10 independent SLE gene expression datasets from the Gene Expression Omnibus (GEO). There were 59 differentially methylated loci between unaffected and affected MZ twins in whole blood, including 11 novel loci. All but two of these loci were hypomethylated in the SLE twins relative to the unaffected twins. The genes harboring these hypomethylated loci exhibited increased expression in multiple independent datasets of SLE patients. This pattern was largely consistent regardless of disease activity, cell type, or renal tissue type. The genes proximal to CpGs exhibiting differential methylation (DM) in the SLE-discordant MZ twins and exhibiting differential expression (DE) in independent SLE GEO cohorts (DM-DE genes) clustered into two pathways: the nucleic acid-sensing pathway and the type I interferon pathway. The DM-DE genes were also informatically queried for potential gene–drug interactions, yielding a list of 41 drugs including a known SLE therapy. The DM-DE genes delineate two important biologic pathways that are not only reflective of the heterogeneity of SLE but may also correlate with distinct IFN responses that depend on the source, type, and location of nucleic acid molecules and the activated receptors in individual patients. Cell- and tissue-specific analyses will be critical to the understanding of genetic factors dysregulating the nucleic acid-sensing and IFN pathways and whether these factors could be appropriate targets for therapeutic intervention.

Insights Into the Role of DNA Methylation in Immune Cell Development and Autoimmune Disease

To date, nearly 100 autoimmune diseases have been an area of focus, and these diseases bring health challenges to approximately 5% of the population worldwide. As a type of disease caused by tolerance breakdown, both environmental and genetic risk factors contribute to autoimmune disease development. However, in most cases, there are still gaps in our understanding of disease pathogenesis, diagnosis, and treatment. Therefore, more detailed knowledge of disease pathogenesis and potential therapies is indispensable. DNA methylation, which does not affect the DNA sequence, is one of the key epigenetic silencing mechanisms and has been indicated to play a key role in gene expression regulation and to participate in the development of certain autoimmune diseases. Potential epigenetic regulation via DNA methylation has garnered more attention as a disease biomarker in recent years. In this review, we clarify the basic function and distribution of DNA methylation, evaluate its effects on gene expression and discuss related key enzymes. In addition, we summarize recent aberrant DNA methylation modifications identified in the most important cell types related to several autoimmune diseases and then provide potential directions for better diagnosing and monitoring disease progression driven by epigenetic control, which may broaden our understanding and contribute to further epigenetic research in autoimmune diseases.

Therapeutic Effects of Dietary Soybean Genistein on Triple-Negative Breast Cancer via Regulation of Epigenetic Mechanisms

Consumption of dietary natural components such as genistein (GE) found in soy-rich sources is strongly associated with a lower risk of breast cancer. However, bioactive dietary component-based therapeutic strategies are largely understudied in breast cancer treatment. Our investigation sought to elucidate the potential mechanisms linking bioactive dietary GE to its breast cancer chemotherapeutic potential in a special subtype of aggressive breast cancer-triple-negative breast cancer (TNBC)-by utilizing two preclinical patient-derived xenograft (PDX) orthotopic mouse models: BCM-3204 and TM00091. Our study revealed that administration of GE resulted in a delay of tumor growth in both PDX models. With transcriptomics analyses in TNBC tumors isolated from BCM-3204 PDXs, we found that dietary soybean GE significantly influenced multiple tumor-regulated gene expressions. Further validation assessment of six candidate differentially expressed genes (DEGs)-Cd74, Lpl, Ifi44, Fzd9, Sat1 and Wwc1-demonstrated a similar trend at gene transcriptional and protein levels as observed in RNA-sequencing results. Mechanistically, GE treatment-induced Cd74 downregulation regulated the NF-κB/Bcl-xL/TAp63 signal pathway, which may contribute to soybean GE-mediated therapeutic effects on TNBC tumors. Additionally, our findings revealed that GE can modify expression levels of key epigenetic-associated genes such as DNA methyltransferases (Dnmt3b), ten-eleven translocation (Tet3) methylcytosine dioxygenases and histone deacetyltransferase (Hdac2), and their enzymatic activities as well as genomic DNA methylation and histone methylation (H3K9) levels. Collectively, our investigation shows high significance for potential development of a novel therapeutic approach by using bioactive soybean GE for TNBC patients who have few treatment options.

Contribution of Dysregulated DNA Methylation to Autoimmunity

Epigenetic mechanisms, such as DNA methylation, histone modifications, and non-coding RNAs are known regulators of gene expression and genomic stability in cell growth, development, and differentiation. Because epigenetic mechanisms can regulate several immune system elements, epigenetic alterations have been found in several autoimmune diseases. The purpose of this review is to discuss the epigenetic modifications, mainly DNA methylation, involved in autoimmune diseases in which T cells play a significant role. For example, Rheumatoid Arthritis and Systemic Lupus Erythematosus display differential gene methylation, mostly hypomethylated 5′-C-phosphate-G-3′ (CpG) sites that may associate with disease activity. However, a clear association between DNA methylation, gene expression, and disease pathogenesis must be demonstrated. A better understanding of the impact of epigenetic modifications on the onset of autoimmunity will contribute to the design of novel therapeutic approaches for these diseases.

Investigation of Genes Associated With Atherosclerosis in Patients With Systemic Lupus Erythematosus

Objectives

In this study, we aimed to identify patients with systemic lupus erythematosus (SLE) who are genetically at risk for developing atherosclerosis.

Patients and methods

Between November 2014 and May 2016, a total of 38 patients with SLE (36 females, 2 males; mean age: 37.6 years; range, 18 to 71 years) and 32 healthy females (mean age: 31.5 years; range, 19 to 54 years) were included in the study. Carotid intima-media thickness (CIMT) was measured using high-resolution B-mode ultrasonography. SurePrint G3 Human Gene Expression 8x60K Microarray kit was used in our study. Genes showing differences in expression between the groups were identified by using GeneSpring GX 10.0 program. Pathway analyses of gene expressions were performed using Ingenuity Pathways Analysis (IPA). Gene ontology analyses were performed using the Protein Analysis Through Evolutionary Relationships (PANTHER).

Results

Clinical findings of SLE patients were mainly photosensitivity (71.1%), arthritis (63.2%), lupus nephritis (55.3%), thrombocytopenia (26.3%), and autoimmune hemolytic anemia (21.1%). A total of 155 genes showing expression level difference were detected between SLE patients and healthy controls. In molecular network analysis, 28.2% of all genes were found to be directly or indirectly associated with atherosclerosis and cardiovascular disease.

Conclusion

In SLE patients, many genes are expressed differently from healthy individuals. Expression of these genes is important in the pathogenesis of SLE. Genes identified differently in gene expression analysis can help us to identify SLE patients at risk for atherosclerosis in the Turkish population.

Epigenetic linkage of systemic lupus erythematosus and nutrition

The term "epigenetics" refers to a series of meiotically/mitotically inheritable alterations in gene expression, related to environmental factors, without disruption on DNA sequences of bases. Recently, the pathophysiology of autoimmune diseases (ADs) has been closely linked to epigenetic modifications. Actually, epigenetic mechanisms can modulate gene expression or repression of targeted cells and tissues involved in autoimmune/inflammatory conditions acting as keys effectors in regulation of adaptive and innate responses. ADs, as systemic lupus erythematosus (SLE), a rare disease that still lacks effective treatment, is characterized by epigenetic marks in affected cells.Taking into account that epigenetic mechanisms have been proposed as a winning strategy in the search of new more specific and personalized therapeutics agents. Thus, pharmacology and pharmacoepigenetic studies about epigenetic regulations of ADs may provide novel individualized therapies. Focussing in possible implicated factors on development and predisposition of SLE, diet is feasibly one of the most important factors since it is linked directly to epigenetic alterations and these epigenetic changes may augment or diminish the risk of SLE. Nevertheless, several studies have guaranteed that dietary therapy could be a promise to SLE patients via prophylactic actions deprived of side effects of pharmacology, decreasing co-morbidities and improving lifestyle of SLE sufferers.Herein, we review and discuss the cross-link between epigenetic mechanisms on SLE predisposition and development, as well as the influence of dietary factors on regulation epigenetic modifications that would eventually make a positive impact on SLE patients.

Guideline for the diagnosis, treatment and long-term management of cutaneous lupus erythematosus

Cutaneous lupus erythematosus (CLE) is an inflammatory, autoimmune disease encompassing a broad spectrum of subtypes including acute, subacute, chronic and intermittent CLE. Among these, chronic CLE can be further classified into several subclasses of lupus erythematosus (LE) such as discoid LE, verrucous LE, LE profundus, chilblain LE and Blaschko linear LE. To provide all dermatologists and rheumatologists with a practical guideline for the diagnosis, treatment and long-term management of CLE, this evidence- and consensus-based guideline was developed following the checklist established by the international Reporting Items for Practice Guidelines in Healthcare (RIGHT) Working Group and was registered at the International Practice Guideline Registry Platform. With the joint efforts of the Asian Dermatological Association (ADA), the Asian Academy of Dermatology and Venereology (AADV) and the Lupus Erythematosus Research Center of Chinese Society of Dermatology (CSD), a total of 25 dermatologists, 7 rheumatologists, one research scientist on lupus and 2 methodologists, from 16 countries/regions in Asia, America and Europe, participated in the development of this guideline. All recommendations were agreed on by at least 80% of the 32 voting physicians. As a consensus, diagnosis of CLE is mainly based on the evaluation of clinical and histopathological manifestations, with an exclusion of SLE by assessment of systemic involvement. For localized CLE lesions, topical corticosteroids and topical calcineurin inhibitors are first-line treatment. For widespread or severe CLE lesions and (or) cases resistant to topical treatment, systemic treatment including antimalarials and (or) short-term corticosteroids can be added. Notably, antimalarials are the first-line systemic treatment for all types of CLE, and can also be used in pregnant patients and pediatric patients. Second-line choices include thalidomide, retinoids, dapsone and MTX, whereas MMF is third-line treatment. Finally, pulsed-dye laser or surgery can be added as fourth-line treatment for localized, refractory lesions of CCLE in cosmetically unacceptable areas, whereas belimumab may be used as fourth-line treatment for widespread CLE lesions in patients with active SLE, or recurrence of ACLE during tapering of corticosteroids. As for management of the disease, patient education and a long-term follow-up are necessary. Disease activity, damage of skin and other organs, quality of life, comorbidities and possible adverse events are suggested to be assessed in every follow-up visit, when appropriate.

Multi-omics approach to precision medicine for immune-mediated diseases

Recent innovation in high-throughput sequencing technologies has drastically empowered the scientific research. Consequently, now, it is possible to capture comprehensive profiles of samples at multiple levels including genome, epigenome, and transcriptome at a time. Applying these kinds of rich information to clinical settings is of great social significance. For some traits such as cardiovascular diseases, attempts to apply omics datasets in clinical practice for the prediction of the disease risk have already shown promising results, although still under way for immune-mediated diseases. Multiple studies have tried to predict treatment response in immune-mediated diseases using genomic, transcriptomic, or clinical information, showing various possible indicators. For better prediction of treatment response or disease outcome in immune-mediated diseases, combining multi-layer information together may increase the power. In addition, in order to efficiently pick up meaningful information from the massive data, high-quality annotation of genomic functions is also crucial. In this review, we discuss the achievement so far and the future direction of multi-omics approach to immune-mediated diseases.

Identification of hub genes, pathways, and related transcription factors in systemic lupus erythematosus: A preliminary bioinformatics analysis

BACKGROUND

Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by multiple organ damage and the production of a variety of autoantibodies. The pathogenesis of SLE has not been fully defined, and it is difficult to treat. Our study aimed to identify candidate genes that may be used as biomarkers for the screening, diagnosis, and treatment of SLE.

METHODS

We used the GEO2R tool to identify the differentially expressed genes (DEGs) in SLE-related datasets retrieved from the Gene Expression Omnibus (GEO). In addition, we also identified the biological functions of the DEGs by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Additionally, we constructed protein-protein interaction (PPI) networks to identify hub genes, as well as the regulatory network of transcription factors related to DEGs.

RESULTS

Two datasets were identified for use from the GEO (GSE50772, GSE4588), and 34 up-regulated genes and 4 down-regulated genes were identified by GEO2R. Pathway analysis of the DEGs revealed enrichment of the interferon alpha/beta signaling pathway; GO analysis was mainly enriched in response to interferon alpha, regulation of ribonuclease activity. PPIs were constructed through the STRING database and 14 hub genes were selected and 1 significant module (score = 12.923) was obtained from the PPI network. Additionally, 11 key transcription factors that interacted closely with the 14 hub DEGs were identified from the gene transcription factor network.

CONCLUSIONS

Bioinformatic analysis is an effective tool for screening the original genomic data in the GEO database, and a large number of SLE-related DEGs were identified. The identified hub DEGs may be potential biomarkers of SLE.

Clinical and Immunological Biomarkers for Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is characterized by immune system dysfunction and is clinically heterogeneous, exhibiting renal, dermatological, neuropsychiatric, and cardiovascular symptoms. Clinical and physiological assessment is usually inadequate for diagnosing and assessing pathophysiological processes in SLE. Clinical and immunological biomarkers could play a critical role in improving diagnosis, assessment, and ultimately, control of SLE. This article reviews clinical and immunological biomarkers that could diagnose and monitor disease activity in SLE, with and without organ-specific injury. In addition, novel SLE biomarkers that have been discovered through “omics” research are also reviewed.

Bioinformatics analysis of epigenetic and SNP-related molecular markers in systemic lupus erythematosus

We analyzed gene expression in peripheral blood mononuclear cells (PBMCs) from patients with systemic lupus erythematosus (SLE) using public databases. The goal was to identify lupus biomarkers by determining whether differentially expressed genes are mediated by methylation, miRNA, or SNP. Two cDNA microarrays were subjected to integration analysis, and we calculated the mutually differentially expressed genes (|log2fold change (FC)| > 1, P < 0.05). These genes were analyzed using gene otology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and protein-protein interaction (PPI) networks. The differences in methylation sites for two methylation chips were calculated and the differentially methylated sites were annotated. These genes were compared to the differentially expressed genes. We obtained 135 differentially expressed microRNAs from the microRNA-chip results using PBMCs from SLE and healthy individuals. Predictive microRNA target genes were identified using GO, KEGG pathways, and PPI networks. The target genes identified were compared to the differentially expressed genes. We downloaded Chinese SLE genome-wide association study data from SLE-related literature, analyzed the loci with a P value < 0.05, and used annotated SLE-associated SNPs. We selected the genes corresponding to an SNP located on an exon and determined the intersection with the differentially expressed genes. We found 18 differentially expressed genes in both cDNA microarrays. The methylation chips had 50 corresponding methylation sites. On the basis of these results, we identified two genes, IFI44 and IFI44L. We further identified 135 differentially expressed microRNAs predicted to affect 5766 target genes. Two identified genes were in common with the differentially expressed genes. Finally, SNP annotated genes and cDNA chip genes overlap with identified MX1. Therefore, we used existing data to analyze the causes of differential gene expression in SLE, introducing new methods for determining biomarkers and therapeutic targets.

Sex-specific gene expression in the blood of four primates

Blood is an important non-reproductive tissue, but little is known about the sex-specific gene expressions in the blood. Therefore, we investigated sex-specific gene expression differences in the blood tissues of four primates, rhesus macaques (Macaca mulatta), Tibetan macaques (M. thibetana), yellow baboons (Papio cynocephalus), and humans. We identified seven sex-specific differentially expressed genes (SDEGs) in each non-human primate and 31 SDEGs in humans. The four primates had only one common SDEG, MAP7D2. In humans, immune-related SDEGs were identified as up-regulated, but also down-regulated in females. We also found that most of the X-Y gene pairs had similar expression levels between species, except pair EIF1AY/EIF1AX. The expression level of X-Y gene pairs of rhesus and Tibetan macaques showed no significant differential expression levels, while humans had six significant XY-biased and three XX-biased X-Y gene pairs. Our observed sex differences in blood should increase understanding of sex differences in primate blood tissue.

Association of methylation level and transcript level in TRAF5 gene with ankylosing spondylitis: a case-control study

To explore the association between methylation level and transcript level of TNF receptor-associated factor 5 (TRAF5) gene with ankylosing spondylitis (AS) in Chinese Han population. Methylation and mRNA expression level of the TRAF5 gene were tested in 98 patients and 98 healthy controls. Among the 21 CpG sites, methylation levels at eight sites were significantly different between AS patients and healthy controls. However, only three sites remained significantly different after the correction by the Benjamini-Hochberg method. Compared with controls, the CpG island of TRAF5 gene promoter was highly methylated in AS patients, and the relative mRNA expression level of TRAF5 was significantly reduced in AS patients. And the mRNA level was negatively correlated with the methylation level of TRAF5 gene in AS patients (r_s = -0.453, P < 0.001). Subgroup analyses indicated that there was no significant difference in the level of methylation between groups of different status of HLA-B27 and medications in AS patients. Multiple linear regression showed that disease-modifying antirheumatic drugs could reduce methylation levels of AS patients after adjusting for the effects of other drugs. In conclusion, the hypermethylation of the TRAF5 might contribute to the pathogenesis of AS, but many open questions remain.

Current Status of the Evaluation and Management of Lupus Patients and Future Prospects

The vastly diverse nature of systemic lupus erythematosus (SLE) poses great challenges to clinicians and patients, as well as to research and drug development efforts. Precise management of lupus patients would be advanced by the ability to identify specific abnormalities operative in individual patients at the time of encounter with the clinician. Advances in new technologies and bioinformatics have greatly improved the understanding of the pathophysiology of SLE. Recent research has focused on the discovery and classification of sensitive and specific markers that could aid early accurate diagnosis, better monitoring of disease and identification of appropriate therapy choices based on specific dysregulated molecular pathways. Here, we summarize some of the advances and discuss the challenges in moving toward precise patient-centric management modalities in SLE.

"Precision Medicine in Autoimmune Diseases: Fact or Fiction"

Much is said about precision medicine, but its real significance and the possibility of making it a real possibility is far from certain. Several studies in each of the autoimmune diseases have provided important insight into molecular pathways but the use of molecular studies, particularly those looking into transcriptome pathways, have seldom approached the possibility of using the data for disease stratification and then for prediction, or diagnosis. Only the type I interferon signature has been considered in the use of this signature for therapeutic purposes, particularly in the case of systemic lupus erythematosus. Here, the authors provide an update on precision medicine, what can be translated into clinical practice, and what do single-cell molecular studies provide to our knowledge in autoimmune diseases, focusing on a few examples. The main message being that we should try to move from precision medicine of established disease to preventive medicine in order to predict the development of disease.

Genome-wide DNA methylation patterns in monocytes derived from patients with primary Sjogren syndrome

Background:

Epigenetics, especially DNA methylation, plays an important role in the pathogenesis of primary Sjogren syndrome (pSS). Our study aimed to reveal the role of DNA methylation in peripheral monocytes of pSS patients.

Methods:

A total of 11 pSS patients and five age-matched healthy controls (HCs) were included in this study. Monocytes were isolated from peripheral blood mononuclear cells using magnetic microbeads. DNA methylation profiles were generated using Human Methylation 850K BeadChips.

Results:

In monocytes from pSS patients, we identified 2819 differentially methylated positions (DMPs), comprising 1977 hypomethylated- and 842 hypermethylated-DMPs, corresponding to 1313 unique genes when compared with HCs. IFI44L, MX1, PAARP9, and IFITM1, which influence the interferon (IFN) signaling pathway, were among the genes hypomethylated in pSS. Functional analysis of genes with a minimum of two DMPs showed involvement in antigen binding, transcriptional regulation, cell adhesion, IFN-γ pathway, type I IFN pathway, antigen presentation, Epstein-Barr virus infection, human T-lymphotropic virus type 1 virus infection, and metabolic disease-related pathways. In addition, patients with higher serum IgG levels exhibited enrichment in Notch signaling and metabolic-related pathways. Upon comparing monocytes with salivary gland epithelial cells, an important overlap was observed in the cell cycle, cell senescence, and interleukin-17 signaling pathways. The differentially methylated genes were more enriched in the ribosome- and AMP-activated protein kinase signaling pathway in anti-Ro/SSA and anti-La/SSB autoantibodies double-positive patients.

Conclusion:

Genome-wide DNA methylation profiling revealed significant differences in DNA methylation in monocytes isolated from patients with pSS.

Difference of IFI44L methylation and serum IFN-a1 level among patients with discoid and systemic lupus erythematosus and healthy individuals

Lupus erythematosus (LE) is an autoimmune disease that can be divided into two types. The cutaneous lupus erythematosus (CLE), such as discoid LE (DLE), affects only the skin. While the systemic lupus erythematosus (SLE) affects the hematopoietic, renal, and other systems. We previously found that IFI44L methylation could be a biomarker for SLE. Here, we detect the IFI44L methylation by high-resolution melting-quantitative polymerase chain reaction (HRM-qPCR) assay. The positive percentages of SLE, DLE and healthy controls (HC) are 96.00%, 27.45%, 2.00%, if the curve of 25% methylation was used as the threshold of SLE. And we determined the serum IFN-a1 level by enzyme-linked immunosorbent assay (ELISA) in SLE, DLE and HC. The serum concentration of IFN-a1 in patients with SLE was significantly higher than in the DLE (12.63 ​± ​6.38 ​pg/mL vs 7.99 ​± ​2.28 ​pg/mL, P ​< ​0.05) and HC (12.63 ​± ​6.38 ​pg/mL vs 7.17 ​± ​1.86 ​pg/mL, P ​< ​0.05). But the expression level of IFN-a1 in serum was not significantly different between DLE and HC (7.99 ​± ​2.28 ​pg/mL vs 7.17 ​± ​1.86 ​pg/mL, P ​= ​0.5365). This suggests that methylation of IFI44L and serum concentration of IFN-a1 may be used as biomarkers to distinguish DLE from SLE.

Identification of key biomarkers and immune infiltration in systemic lupus erythematosus by integrated bioinformatics analysis

Background

Systemic lupus erythematosus (SLE) is a multisystemic, chronic inflammatory disease characterized by destructive systemic organ involvement, which could cause the decreased functional capacity, increased morbidity and mortality. Previous studies show that SLE is characterized by autoimmune, inflammatory processes, and tissue destruction. Some seriously-ill patients could develop into lupus nephritis. However, the cause and underlying molecular events of SLE needs to be further resolved.

Methods

The expression profiles of GSE144390, GSE4588, GSE50772 and GSE81622 were downloaded from the Gene Expression Omnibus (GEO) database to obtain differentially expressed genes (DEGs) between SLE and healthy samples. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments of DEGs were performed by metascape etc. online analyses. The protein–protein interaction (PPI) networks of the DEGs were constructed by GENEMANIA software. We performed Gene Set Enrichment Analysis (GSEA) to further understand the functions of the hub gene, Weighted gene co‐expression network analysis (WGCNA) would be utilized to build a gene co‐expression network, and the most significant module and hub genes was identified. CIBERSORT tools have facilitated the analysis of immune cell infiltration patterns of diseases. The receiver operating characteristic (ROC) analyses were conducted to explore the value of DEGs for SLE diagnosis.

Results

In total, 6 DEGs (IFI27, IFI44, IFI44L, IFI6, EPSTI1 and OAS1) were screened, Biological functions analysis identified key related pathways, gene modules and co‐expression networks in SLE. IFI27 may be closely correlated with the occurrence of SLE. We found that an increased infiltration of moncytes, while NK cells resting infiltrated less may be related to the occurrence of SLE.

Conclusion

IFI27 may be closely related pathogenesis of SLE, and represents a new candidate molecular marker of the occurrence and progression of SLE. Moreover immune cell infiltration plays important role in the progession of SLE.

IFI27 may predict and evaluate the severity of respiratory syncytial virus infection in preterm infants

Background

Preterm infants are a special population that vulnerable to respiratory syncytial virus (RSV) infection and the lower respiratory tract infections (LRTIs) caused by RSV could be severe and even life-threating. The purpose of the present study was to identify candidate genes of preterm infants who are susceptible to RSV infection and provide a new insight into the pathogenesis of RSV infection.

Methods

Three datasets (GSE77087, GSE69606 and GSE41374) containing 183 blood samples of RSV infected patients and 33 blood samples of healthy controls from Gene Expression Omnibus (GEO) database were downloaded and the differentially expressed genes (DEGs) were screened out. The function and pathway enrichments were analyzed through Database for Annotation, Visualization and Integrated Discovery (DAVID) website. The protein-protein interaction (PPI) network for DEGs was constructed through Search Tool for the Retrieval of Interacting Genes (STRING). The module analysis was performed by Cytoscape software and hub genes were identified. Clinical verification was employed to verify the expression level of top five hub genes among 72 infants including 50 RSV infected patients and 22 non-RSV-infected patients hospitalized in our center. Further, the RSV infected infants with high-expression IFI27 and those with low-expression IFI27 were compared (defined as higher or lower than the median mRNA level). Finally, the gene set enrichment analysis (GSEA) focusing on IFI27 was carried out.

Results

Totally, 4028 DEGs were screened out and among which, 131 most significant DEGs were selected. Subsequently, 13 hub genes were identified, and function and pathway enrichments of hub genes mainly were: response to virus, defense response to virus, regulation of viral genome replication and regulation of viral life cycle. Furthermore, IFI27 was confirmed to be the most significantly expressed in clinical verification. Gene sets associated with calcium signaling pathway, arachidonic acid metabolism, extracellular matrix receptor interaction and so on were significantly enriched when IFI27 was highly expressed. Moreover, high-expression IFI27 was associated with more severe cases (p = 0.041), more requirements of mechanical ventilation (p = 0.034), more frequent hospitalization (p < 0.001) and longer cumulative hospital stay (p = 0.012).

Conclusion

IFI27 might serve to predict RSV infection and evaluate the severity of RSV infection in preterm infants.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41065-020-00167-5.

Systemic lupus erythematosus: The search for the ideal biomarker

During the last decades, there has been an increased interest in the discovery and validation of biomarkers that reliably reflect specific aspects of lupus. Although many biomarkers have been developed, few of them have been validated and used in clinical practice, but with unsatisfactory performances. Thus, there is still a need to rigorously validate many of these novel promising biomarkers in large-scale longitudinal studies and also identify better biomarkers not only for lupus diagnosis but also for monitoring and predicting upcoming flares and response to treatment. Besides serological biomarkers, urinary and cerebrospinal fluid biomarkers have emerged for assessing both renal and central nervous system involvement in systemic lupus erythematosus, respectively. Also, novel omics techniques help us to understand the molecular basis of the disease and also allow the identification of novel biomarkers which may be potentially useful for guiding new therapeutic targets.

Epigenetic regulation of inflammation in periodontitis: cellular mechanisms and therapeutic potential

Epigenetic mechanisms, namely DNA and histone modifications, are critical regulators of immunity and inflammation which have emerged as potential targets for immunomodulating therapies. The prevalence and significant morbidity of periodontitis, in combination with accumulating evidence that genetic, environmental and lifestyle factors cannot fully explain the susceptibility of individuals to disease development, have driven interest in epigenetic regulation as an important factor in periodontitis pathogenesis. Aberrant promoter methylation profiles of genes involved in inflammatory activation, including TLR2, PTGS2, IFNG, IL6, IL8, and TNF, have been observed in the gingival tissue, peripheral blood or buccal mucosa from patients with periodontitis, correlating with changes in expression and disease severity. The expression of enzymes that regulate histone acetylation, in particular histone deacetylases (HDACs), is also dysregulated in periodontitis-affected gingival tissue. Infection of gingival epithelial cells, gingival fibroblasts and periodontal ligament cells with the oral pathogens Porphyromonas gingivalis or Treponema denticola induces alterations in expression and activity of chromatin-modifying enzymes, as well as site-specific and global changes in DNA methylation profiles and in histone acetylation and methylation marks. These epigenetic changes are associated with excessive production of inflammatory cytokines, chemokines, and matrix-degrading enzymes that can be suppressed by small molecule inhibitors of HDACs (HDACi) or DNA methyltransferases. HDACi and inhibitors of bromodomain-containing BET proteins ameliorate inflammation, osteoclastogenesis, and alveolar bone resorption in animal models of periodontitis, suggesting their clinical potential as host modulation therapeutic agents. However, broader application of epigenomic methods will be required to create a comprehensive map of epigenetic changes in periodontitis. The integration of functional studies with global analyses of the epigenetic landscape will provide critical information on the therapeutic and diagnostic potential of epigenetics in periodontal disease.

A longitudinal and transancestral analysis of DNA methylation patterns and disease activity in lupus patients

Epigenetic dysregulation is implicated in the pathogenesis of lupus. We performed a longitudinal analysis to assess changes in DNA methylation in lupus neutrophils over 4 years of follow-up and across disease activity levels using 229 patient samples. We demonstrate that DNA methylation profiles in lupus are partly determined by ancestry-associated genetic variations and are highly stable over time. DNA methylation levels in 2 CpG sites correlated significantly with changes in lupus disease activity. Progressive demethylation in SNX18 was observed with increasing disease activity in African American patients. Importantly, demethylation of a CpG site located within GALNT18 was associated with the development of active lupus nephritis. Differentially methylated genes between African American and European American lupus patients include type I IFN-response genes such as IRF7 and IFI44, and genes related to the NF-κB pathway. TREML4, which plays a vital role in TLR signaling, was hypomethylated in African American patients and demonstrated a strong cis-methylation quantitative trait loci (cis-meQTL) effect among 8855 cis-meQTL associations identified in our study.

Identification of Early Recurrence Factors in Childhood and Adolescent B-Cell Acute Lymphoblastic Leukemia Based on Integrated Bioinformatics Analysis

Over the past 50 years, great progress has been made in the diagnosis and treatment of acute lymphoblastic leukemia (ALL), especially in pediatric patients. However, early recurrence is still an important threat to the survival of patients. In this study, we used integrated bioinformatics analysis to look for biomarkers of early recurrence of B-cell ALL (B-ALL) in childhood and adolescent patients. Firstly, we obtained gene expression profiles from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database and the Gene Expression Omnibus (GEO) database. Then, we identified differentially expressed genes (DEGs) based on whether the disease relapsed early. LASSO and Cox regression analysis were applied to identify a subset of four genes: HOXA7, S100A11, S100A10, and IFI44L. A genetic risk score model was constructed based on these four optimal prognostic genes. Time-dependent receiver operating characteristic (ROC) curves were used to evaluate the predictive value of this prognostic model (3-, 5-, and 10-year AUC values >0.7). The risk model was significantly associated with overall survival (OS) and event-free survival in B-ALL (all p < 0.0001). In addition, a high risk score was an independent poor prognostic risk factor for OS (p < 0.001; HR = 3.396; 95% CI: 2.387-4.832). Finally, the genetic risk model was successfully tested in B-ALL using an external validation set. The results suggested that this model could be a novel predictive tool for early recurrence and prognosis of B-ALL.

A simple and highly efficient method of IFI44L methylation detection for the diagnosis of systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a complex heterogenous autoimmune disease that can be challenging to diagnose. We previously identified the IFN-induced protein 44-like (IFI44L) methylation marker for SLE diagnosis, which can be detected by pyrosequencing. Although the previous technique has high sensitivity and specificity, it requires special equipment and high cost for detection. Here, we established a high-resolution melting-quantitative polymerase chain reaction (HRM-qPCR) assay to detect the methylation of IFI44L promoter for the diagnosis of SLE. The result was determined according to the standard melting curve of the methylation level of the IFI44L promoter region. The sensitivity was 88.571% and the specificity was 97.087%. The HRM-qPCR and pyrosequencing results presented good consistency when both methods were used to detect the methylation of the IFI44L promoter for SLE diagnosis. Furthermore, the HRM-qPCR method can be used to distinguish SLE from other autoimmune diseases, infectious diseases and virus-related cancers.

Interferon-Induced Protein 44 and Interferon-Induced Protein 44-Like Restrict Replication of Respiratory Syncytial Virus

RSV infects all children under 2 years of age, but only a subset of children get severe disease. We hypothesize that susceptibility to severe RSV necessitating hospitalization in children without predefined risk factors is, in part, mediated at the antiviral gene level. However, there is a large array of antiviral genes, particularly in the ISG family, the mechanism of which is poorly understood. Having previously identified IFI44 and IFI44L as possible genes of interest in a bioinformatic screen, we dissected the function of these two genes in the control of RSV. Through a range of overexpression and knockout studies, we show that the genes are antiviral and antiproliferative. This study is important because IFI44 and IFI44L are upregulated after a wide range of viral infections, and IFI44L can serve as a diagnostic biomarker of viral infection.

Cellular intrinsic immunity, mediated by the expression of an array of interferon-stimulated antiviral genes, is a vital part of host defense. We have previously used a bioinformatic screen to identify two interferon-stimulated genes (ISG) with poorly characterized function, interferon-induced protein 44 (IFI44) and interferon-induced protein 44-like (IFI44L), as potentially being important in respiratory syncytial virus (RSV) infection. Using overexpression systems, CRISPR-Cas9-mediated knockout, and a knockout mouse model, we investigated the antiviral capability of these genes in the control of RSV replication. Overexpression of IFI44 or IFI44L was sufficient to restrict RSV infection at an early time postinfection. Knocking out these genes in mammalian airway epithelial cells increased levels of infection. Both genes express antiproliferative factors that have no effect on RSV attachment but reduce RSV replication in a minigenome assay. The loss of Ifi44 was associated with a more severe infection phenotype in a mouse model of infection. These studies demonstrate a function for IFI44 and IFI44L in controlling RSV infection.

IMPORTANCE RSV infects all children under 2 years of age, but only a subset of children get severe disease. We hypothesize that susceptibility to severe RSV necessitating hospitalization in children without predefined risk factors is, in part, mediated at the antiviral gene level. However, there is a large array of antiviral genes, particularly in the ISG family, the mechanism of which is poorly understood. Having previously identified IFI44 and IFI44L as possible genes of interest in a bioinformatic screen, we dissected the function of these two genes in the control of RSV. Through a range of overexpression and knockout studies, we show that the genes are antiviral and antiproliferative. This study is important because IFI44 and IFI44L are upregulated after a wide range of viral infections, and IFI44L can serve as a diagnostic biomarker of viral infection.

Circulating Cell-Free Nucleic Acids as Epigenetic Biomarkers in Precision Medicine

The circulating cell-free nucleic acids (ccfNAs) are a mixture of single- or double-stranded nucleic acids, released into the blood plasma/serum by different tissues via apoptosis, necrosis, and secretions. Under healthy conditions, ccfNAs originate from the hematopoietic system, whereas under various clinical scenarios, the concomitant tissues release ccfNAs into the bloodstream. These ccfNAs include DNA, RNA, microRNA (miRNA), long non-coding RNA (lncRNA), fetal DNA/RNA, and mitochondrial DNA/RNA, and act as potential biomarkers in various clinical conditions. These are associated with different epigenetic modifications, which show disease-related variations and so finding their role as epigenetic biomarkers in clinical settings. This field has recently emerged as the latest advance in precision medicine because of its clinical relevance in diagnostic, prognostic, and predictive values. DNA methylation detected in ccfDNA has been widely used in personalized clinical diagnosis; furthermore, there is also the emerging role of ccfRNAs like miRNA and lncRNA as epigenetic biomarkers. This review focuses on the novel approaches for exploring ccfNAs as epigenetic biomarkers in personalized clinical diagnosis and prognosis, their potential as therapeutic targets and disease progression monitors, and reveals the tremendous potential that epigenetic biomarkers present to improve precision medicine. We explore the latest techniques for both quantitative and qualitative detection of epigenetic modifications in ccfNAs. The data on epigenetic modifications on ccfNAs are complex and often milieu-specific posing challenges for its understanding. Artificial intelligence and deep networks are the novel approaches for decoding complex data and providing insight into the decision-making in precision medicine.

Clinical value of DNA methylation markers in autoimmune rheumatic diseases

Methylation of cytosine residues in DNA, the best studied epigenetic modification, is associated with gene transcription and nuclear organization, and ultimately the function of a cell. DNA methylation can be influenced by various factors, including changes in neighbouring genomic sites such as those induced by transcription factor binding. The DNA methylation profiles in relevant cell types are altered in most human diseases compared with the healthy state. Given the physical stability of DNA and methylated DNA compared with other epigenetic modifications, DNA methylation is an ideal marker for clinical purposes. However, few DNA methylation-based markers have made it into clinical practice, with the notable exception of some markers used in the field of oncology. Autoimmune rheumatic diseases are genetically complex entities that can vary widely in terms of prognosis, subtypes, progression and treatment responses. Increasing reports showing strong links between DNA methylation profiles and different clinical outcomes and other clinical aspects in autoimmune rheumatic diseases reinforce the usefulness of DNA methylation profiles as novel clinical markers. In this Review, we provide an updated discussion on DNA methylation alterations in autoimmune rheumatic diseases and the advantages and disadvantages of using these markers in clinical practice.

New insights into the progression from cutaneous lupus to systemic lupus erythematosus

INTRODUCTION

Between 5 and 25% of patients with cutaneous lupus erythematosus (CLE) can progress to systemic lupus erythematosus (SLE) during the course of the disease. There is no clear predictive guideline for the progression of CLE to SLE.

AREAS COVERED

Lupus erythematosus (LE), a chronic autoimmune disease, has a wide spectrum of manifestations. On one side of the spectrum is CLE, in which patients only display skin lesions. On the other side of the spectrum is SLE, which develops severe systemic involvement. CLE has even been considered as a separate entity from LE, while CLE is also proposed to be associated with SLE. In this review, the authors will describe the relationship between CLE and SLE; summarize the incidence, risk factors, systemic involvement, and management of patients who transition to SLE. The literature search was conducted mainly through PubMed from March to July 2020.

EXPERT OPINION

The identification of clinical characteristics and biomarkers in patients facing risk of developing SLE and monitoring the disease on a regular basis are essential to promptly manage and hopefully prevent transition to the systemic form.

The multifaceted functional role of DNA methylation in immune-mediated rheumatic diseases

Genomic predisposition cannot explain the onset of complex diseases, as well illustrated by the largely incomplete concordance among monozygotic twins. Epigenetic mechanisms, including DNA methylation, chromatin remodelling and non-coding RNA, are considered to be the link between environmental stimuli and disease onset on a permissive genetic background in autoimmune and chronic inflammatory diseases. The paradigmatic cases of rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), systemic sclerosis (SSc), Sjogren's syndrome (SjS) and type-1 diabetes (T1D) share the loss of immunological tolerance to self-antigen influenced by several factors, with a largely incomplete role of individual genomic susceptibility. The most widely investigated epigenetic mechanism is DNA methylation which is associated with gene silencing and is due to the binding of methyl-CpG binding domain (MBD)-containing proteins, such as MECP2, to 5-methylcytosine (5mC). Indeed, a causal relationship occurs between DNA methylation and transcription factors occupancy and recruitment at specific genomic locus. In most cases, the results obtained in different studies are controversial in terms of DNA methylation comparison while fascinating evidence comes from the comparison of the epigenome in clinically discordant monozygotic twins. In this manuscript, we will review the mechanisms of epigenetics and DNA methylation changes in specific immune-mediated rheumatic diseases to highlight remaining unmet needs and to identify possible shared mechanisms beyond different tissue involvements with common therapeutic opportunities. Key Points • DNA methylation has a crucial role in regulating and tuning the immune system. • Evidences suggest that dysregulation of DNA methylation is pivotal in the context of immune-mediated rheumatic diseases. • DNA methylation dysregulation in FOXP3 and interferons-related genes is shared within several autoimmune diseases. • DNA methylation is an attractive marker for diagnosis and therapy.

An Update on the Pathogenesis of Skin Damage in Lupus

PURPOSE OF REVIEW

Lupus erythematosus (LE) is characterized by broad and varied clinical forms ranging from a localized skin lesion to a life-threatening form with severe systemic manifestations. The overlapping between cutaneous LE (CLE) and systemic LE (SLE) brings difficulties to physicians for early accurate diagnosis and sometimes may lead to delayed treatment for patients. We comprehensively review recent progress about the similarities and differences of the main three subsets of LE in pathogenesis and immunological mechanisms, with a particular focus on the skin damage.

RECENT FINDINGS

Recent studies on the mechanisms contributing to the skin damage in lupus have shown a close association of abnormal circulating inflammatory cells and abundant production of IgG autoantibodies with the skin damage of SLE, whereas few evidences if serum autoantibodies and circulating inflammatory cells are involved in the pathogenesis of CLE, especially for the discoid LE (DLE). Till now, the pathogenesis and molecular/cellular mechanism for the progress from CLE to SLE are far from clear. But more and more factors correlated with the differences among the subsets of LE and progression from CLE to SLE have been found, such as the mutation of IRF5, IFN regulatory factors and abnormalities of plasmacytoid dendritic cells (PDCs), Th1 cells, and B cells, which could be the potential biomarkers for the interventions in the development of LE. A further understanding in pathogenesis and immunological mechanisms for skin damage in different subsets of LE makes us think more about the differences and cross-links in the pathogenic mechanism of CLE and SLE, which will shed a light in predictive biomarkers and therapies in LE.

DNA methylation changes on immune cells in Systemic Lupus Erythematosus

DNA methylation as a process that regulates gene expression is crucial in immune cells biology. Global and gene specific methylation changes have been described in autoimmunity, especially in Systemic Lupus Erythematosus. These changes not only contribute to the understanding of the disease, but also some have been proposed as diagnostic or disease activity biomarkers. The present review compiles the most recent discoveries on this field on each type of immune cells, including specific changes in signalling pathways, genes of interest and its possible applications on diagnosis or treatment.

The Epigenetics of Lupus Erythematosus

Systemic lupus erythematosus (SLE) is a life-threatening autoimmune disease that is characterized by dysregulated dendritic cells, T and B cells, and abundant autoantibodies. The pathogenesis of lupus remains unclear. However, increasing evidence has shown that environment factors, genetic susceptibilities, and epigenetic regulation contribute to abnormalities in the immune system. In the past decades, several risk gene loci have been identified, such as MHC and C1q. However, genetics cannot explain the high discordance of lupus incidence in homozygous twins. Environmental factor-induced epigenetic modifications on immune cells may provide some insight. Epigenetics refers to inheritable changes in a chromosome without altering DNA sequence. The primary mechanisms of epigenetics include DNA methylation, histone modifications, and non-coding RNA regulations. Increasing evidence has shown the importance of dysregulated epigenetic modifications in immune cells in pathogenesis of lupus, and has identified epigenetic changes as potential biomarkers and therapeutic targets. Environmental factors, such as drugs, diet, and pollution, may also be the triggers of epigenetic changes. Therefore, this chapter will summarize the up-to-date progress on epigenetics regulation in lupus, in order to broaden our understanding of lupus and discuss the potential roles of epigenetic regulations for clinical applications.

The Development of Epigenetics in the Study of Disease Pathogenesis

The study of epigenetics has its roots in the study of organism change over time and response to environmental change, although over the past several decades the definition has been formalized to include heritable alterations in gene expression that are not a result of alterations in underlying DNA sequence. In this chapter, we discuss first the history and milestones in the 100+ years of epigenetic study, including early discoveries of DNA methylation, histone posttranslational modification, and noncoding RNA. We then discuss how epigenetics has changed the way that we think of both health and disease, offering as examples studies examining the epigenetic contributions to aging, including the recent development of an epigenetic "clock", and explore how antiaging therapies may work through epigenetic modifications. We then discuss a nonpathogenic role for epigenetics in the clinic: epigenetic biomarkers. We conclude by offering two examples of modern state-of-the-art integrated multi-omics studies of epigenetics in disease pathogenesis, one which sought to capture shared mechanisms among multiple diseases, and another which used epigenetic big data to better understand the pathogenesis of a single tissue from one disease.

Interferon-induced protein 44-like gene promoter is differentially methylated in peripheral blood mononuclear cells of systemic lupus erythematosus patients

Background:

The objectives of this study were to compare the interferon-induced protein 44-like (IFI44L) promoter methylation level between systemic lupus erythematosus (SLE) patients and healthy controls and to evaluate its diagnostic value in SLE.

Materials and Methods:

The IFI44L promoter methylation level was measured in 49 patients with SLE and 50 healthy controls. Quantitative analysis of promoter methylation IFI44L gene in genomic DNA samples extracted from peripheral blood mononuclear cells was examined in SLE patients and healthy controls. The level of DNA methylation was compared between SLE patients and healthy controls as well as within SLE patient groups based on the presence of renal involvement. Moreover, diagnostic values of IFI44L were calculated.

Results:

The IFI44L promoter methylation level in SLE patients was significantly lower than healthy controls (median, 43.8 vs. 57, respectively; P = 0.008). The level of IFI44L promoter methylation was not significantly different between SLE patients with renal involvement and SLE patients without renal involvement (84.6% vs. 92.7%, respectively; P = 0.774). The IFI44L promoter methylation level ≤94.3% was the best cutoff point with a sensitivity of 91.8% and a specificity of 38% to distinguish patients with SLE from healthy individuals.

Conclusion:

The level of IFI44L promoter methylation from whole peripheral blood in Iranian SLE patients was significantly lower than healthy controls. Furthermore, the DNA methylation level of IFI44L promoter was not associated with renal damage in patients with SLE.

The pathogenesis of systemic lupus erythematosus: Harnessing big data to understand the molecular basis of lupus

Systemic lupus erythematosus (SLE) is a chronic, systemic autoimmune disease that causes damage to multiple organ systems. Despite decades of research and available murine models that capture some aspects of the human disease, new treatments for SLE lag behind other autoimmune diseases such as Rheumatoid Arthritis and Crohn's disease. Big data genomic assays have transformed our understanding of SLE by providing important insights into the molecular heterogeneity of this multigenic disease. Gene wide association studies have demonstrated more than 100 risk loci, supporting a model of multiple genetic hits increasing SLE risk in a non-linear fashion, and providing evidence of ancestral diversity in susceptibility loci. Epigenetic studies to determine the role of methylation, acetylation and non-coding RNAs have provided new understanding of the modulation of gene expression in SLE patients and identified new drug targets and biomarkers for SLE. Gene expression profiling has led to a greater understanding of the role of myeloid cells in the pathogenesis of SLE, confirmed roles for T and B cells in SLE, promoted clinical trials based on the prominent interferon signature found in SLE patients, and identified candidate biomarkers and cellular signatures to further drug development and drug repurposing. Gene expression studies are advancing our understanding of the underlying molecular heterogeneity in SLE and providing hope that patient stratification will expedite new therapies based on personal molecular signatures. Although big data analyses present unique interpretation challenges, both computationally and biologically, advances in machine learning applications may facilitate the ability to predict changes in SLE disease activity and optimize therapeutic strategies.