Gene Expression Analysis Reveals Novel Shared Gene Signatures and Candidate Molecular Mechanisms between Pemphigus and Systemic Lupus Erythematosus in CD4+ T Cells

Crucial Roles of RSAD2/viperin in Immunomodulation, Mitochondrial Metabolism and Autoimmune Diseases

Autoimmune diseases are typically characterized by aberrant activation of immune system that leads to excessive inflammatory reactions and tissue damage. Nevertheless, precise targeted and efficient therapies are limited. Thus, studies into novel therapeutic targets for the management of autoimmune diseases are urgently needed. Radical S-adenosyl methionine domain-containing 2 (RSAD2) is an interferon-stimulated gene (ISG) renowned for the antiviral properties of the protein it encodes, named viperin. An increasing number of studies have underscored the new roles of RSAD2/viperin in immunomodulation and mitochondrial metabolism. Previous studies have shown that there is a complex interplay between RSAD2/vipeirn and mitochondria and that binding of the iron-sulfur (Fe-S) cluster is necessary for the involvement of viperin in mitochondrial metabolism. Viperin influences the proliferation and development of immune cells as well as inflammation via different signaling pathways. However, the function of RSAD2/viperin varies in different studies and a comprehensive overview of this emerging theme is lacking. This review will describe the characteristics of RSAD2/viperin, decipher its function in immunometabolic processes, and clarify the crosstalk between RSAD2/viperin and mitochondria. Furthermore, we emphasize the crucial roles of RSAD2 in autoimmune diseases and its potential application value.

Shared Genetic Features of Psoriasis and Myocardial Infarction: Insights From a Weighted Gene Coexpression Network Analysis

BACKGROUND

Increasing evidence suggests a higher propensity for acute myocardial infarction (MI) in patients with psoriasis. However, the shared mechanisms underlying this comorbidity in these patients remain unclear. This study aimed to explore the shared genetic features of psoriasis and MI and to identify potential biomarkers indicating their coexistence.

METHODS AND RESULTS

Data sets obtained from the gene expression omnibus were examined using a weighted gene coexpression network analysis approach. Hub genes were identified using coexpression modules and validated in other data sets and through in vitro cellular experiments. Bioinformatics tools, including the Human microRNA Disease Database, StarBase, and miRNet databases, were used to construct a ceRNA network and predict potential regulatory mechanisms. By applying weighted gene coexpression network analysis, we identified 2 distinct modules that were significant for both MI and psoriasis. Inflammatory and immune pathways were highlighted by gene ontology enrichment analysis of the overlapping genes. Three pivotal genes-Src homology and collagen 1, disruptor of telomeric silencing 1-like, and feline leukemia virus subgroup C cellular receptor family member 2-were identified as potential biomarkers. We constructed a ceRNA network that suggested the upstream regulatory roles of these genes in the coexistence of psoriasis and MI.

CONCLUSIONS

As potential therapeutic targets, Src homology and collagen 1, feline leukemia virus subgroup C cellular receptor family member 2, and disruptor of telomeric silencing 1-like provide novel insights into the shared genetic features between psoriasis and MI. This study paves the way for future studies focusing on the prevention of MI in patients with psoriasis.

DNA hypomethylation ameliorates erosive inflammatory arthritis by modulating interferon regulatory factor-8

Epigenetic regulation plays a crucial role in the pathogenesis of autoimmune diseases such as inflammatory arthritis. DNA hypomethylating agents, such as decitabine (DAC), have been shown to dampen inflammation and restore immune homeostasis. In the present study, we demonstrate that DAC elicits potent anti-inflammatory effects and attenuates disease symptoms in several animal models of arthritis. Transcriptomic and epigenomic profiling show that DAC-mediated hypomethylation regulates a wide range of cell types in arthritis, altering the differentiation trajectories of anti-inflammatory macrophage populations, regulatory T cells, and tissue-protective synovial fibroblasts (SFs). Mechanistically, DAC-mediated demethylation of intragenic 5'-Cytosine phosphate Guanine-3' (CpG) islands of the transcription factor Irf8 (interferon regulatory factor 8) induced its re-expression and promoted its repressor activity. As a result, DAC restored joint homeostasis by resetting the transcriptomic signature of negative regulators of inflammation in synovial macrophages (MerTK, Trem2, and Cx3cr1), TREGs (Foxp3), and SFs (Pdpn and Fapα). In conclusion, we found that Irf8 is necessary for the inhibitory effect of DAC in murine arthritis and that direct expression of Irf8 is sufficient to significantly mitigate arthritis.

Non-invasive diagnosis of primary Sjögren's syndrome using ultrasonography and transcriptome biomarkers

Diagnosing primary Sjögren's syndrome (pSS) is difficult due to clinical heterogeneity and the absence of non-invasive specific biomarkers. To develop non-invasive pSS diagnosis methods that integrate classic clinical indexes, major salivary gland ultrasonography (SGUS), and gene expression profiles shared by labial gland and peripheral blood, we conducted a study on a cohort of 358 subjects. We identified differentially expressed genes (DEGs) in glands and blood that were enriched in defense response to virus and type I interferon production pathways. Four upregulated DEGs common in glands and blood were identified as hub genes based on the protein-protein interaction networks. A random forest model was trained using features, including SGUS, anti-SSA/Ro60, keratoconjunctivitis sicca tests, and gene expression levels of MX1 and RSAD2. The model achieved comparable pSS diagnosis accuracy to the golden standard method based on labial gland biopsy. Our findings implicate this novel model as a promising diagnosis technique of pSS.

TRIM5 Promotes Systemic Lupus Erythematosus Through CD4(+) T Cells and Macrophage

Purpose

Systemic lupus erythematosus (SLE) is a typical autoimmune disease characterized by the involvement of multiple organs and the production of antinuclear antibodies. This study aimed to investigate the molecular mechanism of SLE.

Patients and Methods

We retrieved genome-wide gene expression levels from five public datasets with relatively large sample sizes from the Gene Expression Omnibus (GEO), and we compared the expression profiles of peripheral blood mononuclear cells (PBMCs) from SLE patients and healthy controls (HCs). The expression of seven target genes in PBMCs from 25 cases and 3 HCs was further validated by reverse-transcription quantitative PCR (RT‒qPCR). Flow cytometry was used for verifying the proportion of naive CD4(+) T cells and M2 macrophages in PBMCs from 5 cases and 4 HCs.

Results

We found 14 genes (TRIM5, FAM8A1, SHFL, LHFPL2, PARP14, IFIT5, PARP12, DDX60, IRF7, IF144, OAS1, OAS3, RHBDF2, and RSAD2) that were differentially expressed among all five datasets. The heterogeneity test under the fixed effect model showed no obvious heterogeneity of TRIM5, FAM8A1, and SHFL across different populations. TRIM5 was positively correlated with the remaining 13 genes. By separating patient samples into TRIM5-high and TRIM5-low groups, we found that up-regulated genes in the TRIM5-high group were mainly enriched in virus-related pathways. Immune cell proportion analysis and flow cytometry revealed that naive CD4(+) T cells were significantly decreased while M2 macrophages were increased in the SLE group. TRIM5 expression levels were negatively correlated with naive CD4(+) T cells but positively correlated with M2 macrophages.

Conclusion

Our data indicated that TRIM5 might be a key factor that modulates SLE etiology, possibly through naive CD4(+) T cells and M2 macrophages.

Introducing Critical Genes in Response to Photodynamic Therapy: A Network Analysis

Introduction: Photodynamic therapy (PDT) is applied as an efficient method for preventing the progress of cancers. Light and a photosensitive compound which is known as photosensitizer (PS) are the main parts of PDT. In the present study, molecular events after using PDT in the presence of a super lethal dose of a PS were assessed via protein-protein interaction (PPI) analysis. Methods: Data were extracted from Gene Expression Omnibus (GEO). The gene expression profiles of the treated human Sk-Cha1 cells via PDT were compared with the control cells. Expressed change analysis and PPI network analysis were administrated via Cytoscape software v 3.7.2 to find the critical differentially expressed genes (DEGs). Regulatory relationships between the central DEGs were evaluated and the highlighted genes were identified. Results: The significant amounts of gene expression values were grouped and a few DEGs characterized by tremendously expressed values were identified. EGFR, CANX, HSPA5, MYC, JUN, ITGB1, APP, and CDH1 were highlighted as hub-bottleneck DEGs. EGFR, CDH1, and JUN appeared as a set of SEGs, which play a crucial role in response to PDT in the treated Sk-Cha1 cells. Conclusion: In conclusion, regulatory relationships between EGFR, CDH1, and JUN, which have an effect on the regulation of cellular survival, differentiation, and proliferation, were highlighted in the present investigation.

Interferon-α regulates abnormally increased expression of RSAD2 in Th17 and Tfh cells in systemic lupus erythematosus patients

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that often involves abnormal activation of regulatory IFN genes and regulation of B cells by CD4+ T cells. Radical S-adenosyl methionine domain containing 2 (RSAD2) is a viral suppressor protein regulated by type I IFN, and it has been proven to play an important regulatory role in SLE. However, the mechanism by which RSAD2 participates in the pathogenesis of SLE is unclear. In this study, we observed higher expression levels of RSAD2 in CD4+ T-cell subsets from the peripheral blood of SLE patients than in those from healthy controls by bioinformatics analysis and validation experiments. We analyzed the expression of RSAD2 in CD4+ T cells of patients with SLE and other autoimmune diseases. In addition, we found that the expression of RSAD2 in CD4+ T cells might be regulated by IFN-α, and RSAD2 significantly affected the differentiation of Th17 cells and T follicular helper (Tfh) cells. Our findings underlined that RSAD2 may promote B-cell activation by promoting the differentiation of Th17 and Tfh cells in SLE patients, a process that is regulated by IFN-α.

Comprehensive bioinformatics analysis reveals the crosstalk genes and immune relationship between the systemic lupus erythematosus and venous thromboembolism

Background

It is well known that patients with systemic lupus erythematosus (SLE) had a high risk of venous thromboembolism (VTE). This study aimed to identify the crosstalk genes between SLE and VTE and explored their clinical value and molecular mechanism initially.

Methods

We downloaded microarray datasets of SLE and VTE from the Gene Expression Omnibus (GEO) dataset. Differential expression analysis was applied to identify the crosstalk genes (CGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the shared genes. The shared diagnostic biomarkers of the two diseases were further screened from CGs using least absolute shrinkage and selection operator (Lasso) regression. Two risk scores for SLE and VTE were constructed separately to predict the likelihood of illness according to the diagnostic biomarkers using a logical regression algorithm. The immune infiltration levels of SEL and VTE were estimated via the CIBERSORT algorithm and the relationship of CGs with immune cell infiltration was investigated. Finally, we explored potential phenotype subgroups in SLE and VTE based on the expression level of CGs through the consensus clustering method and studied immune cell infiltration in different subtypes.

Result

A total of 171 CGs were obtained by the intersection of differentially expressed genes (DEGs) between SLE and VTE cohorts. The functional enrichment shown these CGs were mainly related to immune pathways. After screening by lasso regression, we found that three hub CGs (RSAD2, HSP90AB1, and FPR2) were the optimal shared diagnostic biomarkers for SLE and VTE. Based on the expression level of RSAD2 and HSP90AB1, two risk prediction models for SLE and VTE were built by multifactor logistic regression and systemically validated in internal and external validation datasets. The immune infiltration results revealed that CGs were highly correlated with multiple infiltrated immunocytes. Consensus clustering was used to respectively regroup SLE and VTE patients into C1 and C2 clusters based on the CGs expression profile. The levels of immune cell infiltration and immune activation were higher in C1 than in C2 subtypes.

Conclusion

In our study, we further screen out diagnostic biomarkers from crosstalk genes SLE and VTE and built two risk scores. Our findings reveal a close relationship between CGs and the immune microenvironment of diseases. This provides clues for further exploring the common mechanism and interaction between the two diseases.

Exploration of the potential common pathogenic mechanisms in COVID-19 and silicosis by using bioinformatics and system biology

Silicosis is an occupational lung disease that is common worldwide. In recent years, coronavirus disease 2019 (COVID-19) has provided daunting challenges to public healthcare systems globally. Although multiple studies have shown a close link between COVID-19 and other respiratory diseases, the inter-relational mechanisms between COVID-19 and silicosis remain unclear. This study aimed to explore the shared molecular mechanisms and drug targets of COVID-19 and silicosis. Gene expression profiling identified four modules that were most closely associated with both diseases. Furthermore, we performed functional analysis and constructed a protein-protein interaction network. Seven hub genes (budding uninhibited by benzimidazoles 1 [BUB1], protein regulator of cytokinesis 1 [PRC1], kinesin family member C1 [KIFC1], ribonucleotide reductase regulatory subunit M2 [RRM2], cyclin-dependent kinase inhibitor 3 [CDKN3], Cyclin B2 [CCNB2], and minichromosome maintenance complex component 6 [MCM6]) were involved in the interaction between COVID-19 and silicosis. We investigated how diverse microRNAs and transcription factors regulate these seven genes. Subsequently, the correlation between the hub genes and infiltrating immune cells was explored. Further in-depth analyses were performed based on single-cell transcriptomic data from COVID-19, and the expression of hub-shared genes was characterized and located in multiple cell clusters. Finally, molecular docking results reveal small molecular compounds that may improve COVID-19 and silicosis. The current study reveals the common pathogenesis of COVID-19 and silicosis, which may provide a novel reference for further research.

Identification of Significant Genes and Pathways for the Chronic and Subacute Cutaneous Lupus Erythematosus via Bioinformatics Analysis

Background

Chronic cutaneous lupus erythematosus (CCLE) and subacute cutaneous lupus erythematosus (SCLE) are both common variants of cutaneous lupus erythematosus (CLE) that mainly involve the skin and mucous membrane. Oral mucosal involvement is frequently observed in patients of CLE. Despite that they have different clinicopathological features, whether there is a significant difference in pathogenesis between them remains unclear. Herein, we investigated specific genes and pathways of SCLE and CCLE via bioinformatics analysis.

Methods

Microarray expression datasets of GSE109248 and GSE112943 were both retrieved from the GEO database. Differentially expressed genes (DEGs) between CCLE or SCLE skin tissues and health controls were selected by GEO2R. Common DEGs were picked out via the Venn diagram software. Then, functional enrichment and PPI network analysis were conducted, and the top 10 key genes were identified via Cytohubba.

Results

Totally, 176 DEGs of SCLE and 287 DEGs of CCLE were identified. The GO enrichment and KEGG analysis of DEGs of SCLE is significantly enriched in the response to virus, defense response to virus, response to IFN-gamma, cellular response to IFN-γ, type I IFN signaling pathway, chemokine activity, chemokine receptor binding, NOD-like receptor signaling pathway, etc. The GO enrichment and KEGG analysis of DEGs of CCLE is significantly enriched in the response to virus, regulation of multiorganism process, negative regulation of viral process, regulation of lymphocyte activation, chemokine receptor binding, CCR chemokine receptor binding, NOD-like receptor signaling pathway, etc. The top 10 hub genes of SCLE and CCLE, respectively, include STAT1, CXCL10, IRF7, ISG15, and RSAD2 and CXCL10, IRF7, IFIT3, CTLA4, and ISG15.

Conclusion

Our finding suggests that SCLE and CCLE have the similar potential key genes and pathways and majority of them belong to IFN signatures and IFN signaling pathway. Besides, the NOD-like receptor signaling pathway might also have an essential role in the pathogenesis of SCLE and CCLE. Together, the identified genes and signaling pathways have enhanced our understanding of the mechanism underlying the occurrence and development of both SCLE and CCLE.

Genetic Associations and Differential mRNA Expression Levels of Host Genes Suggest a Viral Trigger for Endemic Pemphigus Foliaceus

The long search for the environmental trigger of the endemic pemphigus foliaceus (EPF, fogo selvagem) has not yet resulted in any tangible findings. Here, we searched for genetic associations and the differential expression of host genes involved in early viral infections and innate antiviral defense. Genetic variants could alter the structure, expression sites, or levels of the gene products, impacting their functions. By analyzing 3063 variants of 166 candidate genes in 227 EPF patients and 194 controls, we found 12 variants within 11 genes associated with differential susceptibility (p < 0.005) to EPF. The products of genes TRIM5, TPCN2, EIF4E, EIF4E3, NUP37, NUP50, NUP88, TPR, USP15, IRF8, and JAK1 are involved in different mechanisms of viral control, for example, the regulation of viral entry into the host cell or recognition of viral nucleic acids and proteins. Only two of nine variants were also associated in an independent German cohort of sporadic PF (75 patients, 150 controls), aligning with our hypothesis that antiviral host genes play a major role in EPF due to a specific virus−human interaction in the endemic region. Moreover, CCL5, P4HB, and APOBEC3G mRNA levels were increased (p < 0.001) in CD4+ T lymphocytes of EPF patients. Because there is limited or no evidence that these genes are involved in autoimmunity, their crucial role in antiviral responses and the associations that we observed support the hypothesis of a viral trigger for EPF, presumably a still unnoticed flavivirus. This work opens new frontiers in searching for the trigger of EPF, with the potential to advance translational research that aims for disease prevention and treatment.

Osteoarticular Involvement-Associated Biomarkers and Pathways in Psoriasis: The Shared Pathway With Ankylosing Spondylitis

Psoriatic arthritis (PsA) is a unique immune-mediated disease with cutaneous and osteoarticular involvement. However, only a few studies have explored the susceptibility of osteoarticular involvement in psoriasis (Ps) at the genetic level. This study investigated the biomarkers associated with osteoarticular participation and potential shared molecular mechanisms for PsA and ankylosing spondylitis (AS).

Transcriptomes of peripheral blood mononuclear cells from juvenile dermatomyositis patients show elevated inflammation even when clinically inactive

In juvenile dermatomyositis (JDM), the most common pediatric inflammatory myopathy, weakness is accompanied by a characteristic rash that often becomes chronic and is associated with vascular damage. We hoped to understand the molecular underpinnings of JDM, particularly when untreated, which would facilitate the identification of novel mechanisms and clinical targets that might disrupt disease progression. We studied the RNA-Seq data from untreated JDM peripheral blood mononuclear cells (PBMCs; n = 11), PBMCs from a subset of the same patients when clinically inactive (n = 8/11), and separate samples of untreated JDM skin and muscle (n = 4 each). All JDM samples were compared to non-inflammatory control tissues. The untreated JDM PBMCs showed a strong signature for type1 interferon response, along with IL-1, IL-10, and NF-κB. Surprisingly, PBMCs from clinically inactive JDM individuals had persistent immune activation that was enriched for IL-1 signaling. JDM skin and muscle both showed evidence for type 1 interferon activation and genes related to antigen presentation and decreased expression of cellular respiration genes. Additionally, we found that PBMC gene expression correlates with disease activity scores (DAS; skin, muscle, and total domains) and with nailfold capillary end row loop number (an indicator of microvascular damage). This included otoferlin, which was significantly increased in untreated JDM PBMCs and correlated with all 3 DAS domains. Overall, these data demonstrate that PBMC transcriptomes are informative of molecular disruptions in JDM and provide transcriptional evidence of chronic inflammation despite clinical quiescence.

Key Common Genes in Obstructive Sleep Apnea and Lung Cancer are Associated with Prognosis of Lung Cancer Patients

Background

Obstructive sleep apnea (OSA) is associated with an increased risk of lung cancer. This study aimed to identify key common genes in OSA and lung cancer and explore their prognostic value in lung cancer.

Materials and Methods

Transcriptome data of OSA and lung cancer were obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database, respectively. Genes associated with OSA and lung cancer were screened by weighted gene co-expression network analysis (WGCNA). Univariate and multivariate Cox regression algorithms were applied to identify key genes and construct the risk score model. Receiver operating characteristic (ROC) curves and a nomogram were performed to evaluate the prognostic value of the risk score. The screened key genes and their roles in prognosis were validated by GEO (GSE30219) analysis.

Results

A total of 104 common genes were screened in OSA and lung cancer by WGCNA. Modulator of apoptosis 1 (MOAP1), chromobox 7 (CBX7), platelet-derived growth factor subunit B (PDGFB), and mitogen-activated protein kinase 3 (MAP2K3) were identified as key genes by univariate and then multivariate Cox regression analyses. The risk score model was constructed on the basis of four gene signatures. ROC curves and the nomogram showed that the risk score had a high accuracy in predicting the survival of patients with lung cancer. In addition, the result of multivariate Cox regression analysis indicated that the risk score was an independent prognostic factor in lung cancer.

Conclusion

This study constructed a unique model for predicting the prognosis of lung cancer patients on the basis of four genes common to OSA and lung cancer. These genes may also serve as candidate genes to improve our knowledge about the underlying mechanism of OSA that leads to an increased risk of lung cancer at the genetic level.

Survival-Based Biomarker Module Identification Associated with Oral Squamous Cell Carcinoma (OSCC)

Simple Summary

In this study, four OSCC-specific hub genes were identified using high-throughput RNA-Seq data from TCGA cohort. The significant genes within tumor and normal samples were used for weighted PPI network construction based on survival of patients along with their expression profiles. The analysis revealed the most significant module in the training and test datasets. The genes from this module were used for pathway enrichment analysis followed by hub gene selection. These novel biomarkers might have clinical utility for diagnosis and prognosis prediction in OSCC, providing diagnosis at a very early stage. Moreover, a combination of all these biomarkers might distinguish the OSCC patients with low risk and high risk for cancer progression and recurrence, which will provide useful guidance for personalized and precision therapy. However, the results in the present study were obtained by integrative theoretical analysis, and the findings remain to be confirmed by further experimental validations.

Abstract

Head and neck squamous cell carcinoma (HNSC) is one of the most common malignant tumors worldwide with a high rate of morbidity and mortality, with 90% of predilections occurring for oral squamous cell carcinoma (OSCC). Cancers of the mouth account for 40% of head and neck cancers, including squamous cell carcinomas of the tongue, floor of the mouth, buccal mucosa, lips, hard and soft palate, and gingival. OSCC is the most devastating and commonly occurring oral malignancy, with a mortality rate of 500,000 deaths per year. This has imposed a strong necessity to discover driver genes responsible for its progression and malignancy. In the present study we filtered oral squamous cell carcinoma tissue samples from TCGA-HNSC cohort, which we followed by constructing a weighted PPI network based on the survival of patients and the expression profiles of samples collected from them. We found a total of 46 modules, with 18 modules having more than five edges. The KM and ME analyses revealed a single module (with 12 genes) as significant in the training and test datasets. The genes from this significant module were subjected to pathway enrichment analysis for identification of significant pathways and involved genes. Finally, the overlapping genes between gene sets ranked on the basis of weighted PPI module centralities (i.e., degree and eigenvector), significant pathway genes, and DEGs from a microarray OSCC dataset were considered as OSCC-specific hub genes. These hub genes were clinically validated using the IHC images available from the Human Protein Atlas (HPA) database.

Exploration of the Shared Gene Signatures and Molecular Mechanisms Between Systemic Lupus Erythematosus and Pulmonary Arterial Hypertension: Evidence From Transcriptome Data

Background

Systemic lupus erythematosus (SLE) is an autoimmune disease that can affect multiple systems. Pulmonary arterial hypertension (PAH) has a close linkage with SLE. However, the inter-relational mechanisms between them are still unclear. This article aimed to explore the shared gene signatures and potential molecular mechanisms in SLE and PAH.

Methods

The microarray data of SLE and PAH in the Gene Expression Omnibus (GEO) database were downloaded. The Weighted Gene Co-Expression Network Analysis (WGCNA) was used to identify the co-expression modules related to SLE and PAH. The shared genes existing in the SLE and PAH were performed an enrichment analysis by ClueGO software, and their unique genes were also performed with biological processes analyses using the DAVID website. The results were validated in another cohort by differential gene analysis. Moreover, the common microRNAs (miRNAs) in SLE and PAH were obtained from the Human microRNA Disease Database (HMDD) and the target genes of whom were predicted through the miRTarbase. Finally, we constructed the common miRNAs–mRNAs network with the overlapped genes in target and shared genes.

Results

Using WGCNA, four modules and one module were identified as the significant modules with SLE and PAH, respectively. A ClueGO enrichment analysis of shared genes reported that highly activated type I IFN response was a common feature in the pathophysiology of SLE and PAH. The results of differential analysis in another cohort were extremely similar to them. We also proposed a disease road model for the possible mechanism of PAH secondary to SLE according to the shared and unique gene signatures in SLE and PAH. The miRNA–mRNA network showed that hsa-miR-146a might regulate the shared IFN-induced genes, which might play an important role in PAH secondary to SLE.

Conclusion

Our work firstly revealed the high IFN response in SLE patients might be a crucial susceptible factor for PAH and identified novel gene candidates that could be used as biomarkers or potential therapeutic targets.

SDF4 Is a Prognostic Factor for 28-Days Mortality in Patients With Sepsis via Negatively Regulating ER Stress

Sepsis is a heterogeneous syndrome induced by infection and results in high mortality. Even though more than 100 biomarkers for sepsis prognosis were evaluated, prediction of patient outcomes in sepsis continues to be driven by clinical signs because of unsatisfactory specificity and sensitivity of these biomarkers. This study aimed to elucidate the key candidate genes involved in sepsis response and explore their downstream effects based on weighted gene co-expression network analysis (WGCNA). The dataset GSE63042 with sepsis outcome information was obtained from the Gene Expression Omnibus (GEO) database and then consensus WGCNA was conducted. We identified the hub gene SDF4 (stromal cell derived factor 4) from the M6 module, which was significantly associated with mortality. Subsequently, two datasets (GSE54514 and E-MTAB-4421) and cohort validation (n=89) were performed. Logistic regression analysis was used to build a prediction model and the combined score resulting in a satisfactory prognosis value (area under the ROC curve=0.908). The model was subsequently tested by another sepsis cohort (n=70, ROC= 0.925). We next demonstrated that endoplasmic reticulum (ER) stress tended to be more severe in patients PBMCs with negative outcomes compared to those with positive outcomes and SDF4 was related to this phenomenon. In addition, our results indicated that adenovirus-mediated Sdf4 overexpression attenuated ER stress in cecal ligation and puncture (CLP) mice lung. In summary, our study indicates that incorporation of SDF4 can improve clinical parameters predictive value for the prognosis of sepsis, and decreased expression levels of SDF4 contributes to excessive ER stress, which is associated with worsened outcomes, whereas overexpression of SDF4 attenuated such activation.

Potential therapeutic target genes for systemic lupus erythematosus: a bioinformatics analysis

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease involving multiple organs. However, the underlying etiology and mechanisms remain unclear. This study was performed to identify potential therapeutic targets for SLE using bioinformatics methods. First, 584 differentially expressed genes were identified based on the GSE61635 dataset. Tissue-specific analyses, enrichment analyses, and Protein–Protein interaction network were successively conducted. Furthermore, ELISA was performed to confirm the expression levels of key genes in the control and SLE blood samples. The findings revealed that tissue-specific expression of markers of the hematological system (25.5%, 28/110) varied significantly. CCL2, MMP9, and RSAD2 expression was markedly increased in the SLE samples compared with controls. In conclusion, the identified key genes (CCL2, MMP9, and RSAD2) may act as possible therapeutic targets for the treatment of SLE.

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.

Identification of key genes in hepatitis B associated hepatocellular carcinoma based on WGCNA

Chronic Infection of Hepatitis B virus (HBV) is one risk factor of hepatocellular carcinoma (HCC). Much effort has been made to research the process of HBV-associated HCC, but its molecular mechanisms of carcinogenesis remain vague. Here, weighted gene co-expression network analysis (WGCNA) was employed to explore the co-expressed modules and hub/key genes correlated to HBV-associated HCC. We found that genes of the most significant module related to HBV-associated HCC were enriched in DNA replication, p53 signaling pathway, cell cycle, and HTLV-1 infection associated pathway; these cellular pathways played critical roles in the initiation and development of HCC or viral infections. Furthermore, seven hub/key genes were identified based on the topological network analysis, and their roles in HCC were verified by expression and Kaplan-Meier survival analysis. Protein-protein interaction and KEGG pathway analysis suggested that these key genes may stimulate cellular proliferation to promote the HCC progression. This study provides new perspectives to the knowledge of the key pathways and genes in the carcinogenesis process of HBV-associated HCC, and our findings provided potential therapeutic targets and clues of the carcinogenesis of HBV-associated HCC.

Comprehensive Integration of Genome-Wide Association and Gene Expression Studies Reveals Novel Gene Signatures and Potential Therapeutic Targets for Helicobacter pylori-Induced Gastric Disease

Helicobacter pylori is a gram-negative bacterium that colonizes the human gastric mucosa and can lead to gastric inflammation, ulcers, and stomach cancer. Due to the increase in H. pylori antimicrobial resistance new methods to identify the molecular mechanisms of H. pylori-induced pathology are urgently needed. Here we utilized a computational biology approach, harnessing genome-wide association and gene expression studies to identify genes and pathways determining disease development. We mined gene expression data related to H. pylori-infection and its complications from publicly available databases to identify four human datasets as discovery datasets and used two different multi-cohort analysis pipelines to define a H. pylori-induced gene signature. An initial Helicobacter-signature was curated using the MetaIntegrator pipeline and validated in cell line model datasets. With this approach we identified cell line models that best match gene regulation in human pathology. A second analysis pipeline through NetworkAnalyst was used to refine our initial signature. This approach defined a 55-gene signature that is stably deregulated in disease conditions. The 55-gene signature was validated in datasets from human gastric adenocarcinomas and could separate tumor from normal tissue. As only a small number of H. pylori patients develop cancer, this gene-signature must interact with other host and environmental factors to initiate tumorigenesis. We tested for possible interactions between our curated gene signature and host genomic background mutations and polymorphisms by integrating genome-wide association studies (GWAS) and known oncogenes. We analyzed public databases to identify genes harboring single nucleotide polymorphisms (SNPs) associated with gastric pathologies and driver genes in gastric cancers. Using this approach, we identified 37 genes from GWA studies and 61 oncogenes, which were used with our 55-gene signature to map gene-gene interaction networks. In conclusion, our analysis defines a unique gene signature driven by H. pylori-infection at early phases and that remains relevant through different stages of pathology up to gastric cancer, a stage where H. pylori itself is rarely detectable. Furthermore, this signature elucidates many factors of host gene and pathway regulation in infection and can be used as a target for drug repurposing and testing of infection models suitability to investigate human infection.

ST18 affects cell-cell adhesion in pemphigus vulgaris in a tumour necrosis factor-α-dependent fashion

BACKGROUND

Pemphigus vulgaris (PV) is a life-threatening mucocutaneous autoimmune blistering disease. We previously showed that genetic variants within the ST18 gene promoter area confer a sixfold increase in the propensity to develop PV. ST18, a transcription factor, was found to be overexpressed in the epidermis of patients with PV. In addition, it was found to promote autoantibody-mediated abnormal epidermal cell-cell adhesion and secretion of proinflammatory mediators by keratinocytes.

OBJECTIVES

To delineate the mechanism through which ST18 contributes to destabilization of cell-cell adhesion.

METHODS

We used quantitative reverse-transcriptase polymerase chain reaction, immunofluorescence microscopy, a luciferase reporter system, site-directed mutagenesis, chromatin immunoprecipitation (ChIP) and the dispase dissociation assay.

RESULTS

The ChIP and luciferase reporter assays showed that ST18 directly binds and activates the TNF promoter. Accordingly, increased ST18 expression contributes to PV pathogenesis by destabilizing cell-cell adhesion in a tumour necrosis factor (TNF)-α-dependent fashion. In addition, dual immunofluorescence staining showed increased expression of both ST18 and TNF-α in the skin of patients with PV carrying an ST18-associated PV risk variant, which was found to be associated with a more extensive PV phenotype.

CONCLUSIONS

Our findings suggest a role for TNF-α in mediating the deleterious effect of increased ST18 expression in PV skin.

Weighted gene co-expression network analysis revealed key biomarkers associated with the diagnosis of hypertrophic cardiomyopathy

Objective

To reveal the molecular mechanism underlying the pathogenesis of HCM and find new effective therapeutic strategies using a systematic biological approach.

Methods

The WGCNA algorithm was applied to building the co-expression network of HCM samples. A sample cluster analysis was performed using the hclust tool and a co-expression module was constructed. The WGCNA algorithm was used to study the interactive connection between co-expression modules and draw a heat map to show the strength of interactions between modules. The genetic information of the respective modules was mapped to the associated GO terms and KEGG pathways, and the Hub Genes with the highest connectivity in each module were identified. The Wilcoxon test was used to verify the expression level of hub genes between HCM and normal samples, and the “pROC” R package was used to verify the possibility of hub genes as biomarkers. Finally, the potential functions of hub genes were analyzed by GSEA software.

Results

Seven co-expression modules were constructed using sample clustering analysis. GO and KEGG enrichment analysis judged that the turquoise module is an important module. The hub genes of each module are RPL35A for module Black, FH for module Blue, PREI3 for module Brown, CREB1 for module Green, LOC641848 for module Pink, MYH7 for module Turquoise and MYL6 for module Yellow. The results of the differential expression analysis indicate that MYH7 and FH are considered true hub genes. In addition, the ROC curves revealed their high diagnostic value as biomarkers for HCM. Finally, in the results of the GSEA analysis, MYH7 and FH highly expressed genes were enriched with the “proteasome” and a “PPAR signaling pathway,” respectively.

Conclusions

The MYH7 and FH genes may be the true hub genes of HCM. Their respective enriched pathways, namely the “proteasome” and the “PPAR signaling pathway,” may play an important role in the development of HCM.

Identification and Validation of Key Genes Associated With Systemic Sclerosis-Related Pulmonary Hypertension

Systemic sclerosis-associated with pulmonary arterial hypertension (SSc-PAH) is still a major cause of SSc related deaths. Early diagnosis and prompt treatment are crucial to reduce the mortality of patients with SSc-PAH. To screen the candidate biomarkers and potential therapeutic targets for SSc-PAH, we analyzed the data set (GSE33463 and GSE19617) for confirming key genes in peripheral blood mononuclear cells from SSc-PAH patients. A total of 105 SSc patients from gene expression omnibus (GEO) were included as discovery cohort (n = 69) and duplication cohort (n = 36) for screening hub genes by weighted gene co-expression network analysis (WGCNA). Furthermore, an independent validation cohort (n = 40), including healthy controls, SSc and SSc-PAH patients, was used for further validation by quantitative real-time polymerase chain reaction. The results showed that four key genes, including IFIT2, IFIT3, RSAD2, and PARP14, may serve as potential biomarkers in SSc-PAH. Also, they could be independent risk factors for SSc-PAH. In conclusion, the four key genes can be expected to become the potential therapeutic targets and early biomarkers for accurate therapy and diagnosis of SSc-PAH in the future, which also provides promising insights into the pathogenesis of SSc-PAH at the molecular level.

Bioinformatic analysis reveals that the OAS family may play an important role in lupus nephritis

BACKGROUND

Lupus nephritis (LN) is a common complication of systemic lupus erythematosus that presents a high risk of end-stage renal disease. However, the molecular mechanisms of LN remain unclear. The lack of understanding hinders the development of specific targeted therapy for this progressive disease.

OBJECTIVES

In the present study, we used bioinformatics analysis of gene expression profiles from the Gene Expression Omnibus to identify novel targets and potential biomarkers for LN.

MATERIAL AND METHODS

A GSE32591 dataset, which included 31 LN glomerular biopsy tissues and 14 living donors' glomerular tissues, was downloaded for further analysis. Differentially expressed genes in LN were analyzed by the limma package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed for the differentially expressed genes by using the Disease Ontology Semantic and Enrichment and the clusterProfiler software. The protein-protein interaction (PPI) network was then formed using STRING online tool.

RESULTS

440 genes, including 310 upregulated genes and 130 downregulated genes, were found as differentially expressed genes. GO and KEGG analyses revealed that immune response is significantly enriched in such genes. The PPI network showed that ISG15, MX1, OAS1, OAS2, and OAS3 were the hub genes enriched in LN. Along with literature review, the OAS family genes were revealed to be closely associated with LN progression.

CONCLUSIONS

our studies provided new insight into the molecular pathogenesis of LN. The OAS family may play an important role in LN and act as a novel molecular candidate for the further study of LN.

Comprehensive bioinformatics analysis of mRNA expression profiles and identification of a miRNA-mRNA network associated with lupus nephritis

OBJECTIVE

Lupus nephritis (LN) is one of the serious complications of systemic lupus erythematosus. The aim of this study was to identify core genes and pathways involved in the pathogenesis of LN.

METHODS

We screened differentially expressed genes (DEGs) in LN patients using mRNA expression profile data from the Gene Expression Omnibus. The functional and pathway enrichment analysis of DEGs was performed utilizing the Database for annotation, Visualization and Integrated Discovery. Target genes with differentially expressed miRNAs (DEMIs) were predicted using the miRTarBase database, and the intersection between these target genes and DEGs was selected to be studied further.

RESULTS

In total, 107 common DEGs (CDEGs) were identified from the Tub_LN group and Glom_LN group, and 66 DEMIs were identified. Fifty-three hub genes and two significant modules were identified from the protein-protein interaction (PPI) network, and a miRNA-mRNA network was constructed. The CDEGs, module genes in the PPI network and genes intersecting with the CDEGs and target genes of DEMIs were all associated with the PI3K-Akt signalling pathway.

CONCLUSION

In summary, this study reveals some crucial genes and pathways potentially involving in the pathogenesis of LN. These findings provide a new insight for the research and treatment of LN.

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.

Immune cell infiltration characteristics and related core genes in lupus nephritis: results from bioinformatic analysis

BACKGROUND

Lupus nephritis (LN) is a common complication of systemic lupus erythematosus that presents a high risk of end-stage renal disease. In the present study, we used CIBERSORT and gene set enrichment analysis (GSEA) of gene expression profiles to identify immune cell infiltration characteristics and related core genes in LN.

RESULTS

Datasets from the Gene Expression Omnibus, GSE32591 and GSE113342, were downloaded for further analysis. The GSE32591 dataset, which included 32 LN glomerular biopsy tissues and 14 glomerular tissues from living donors, was analyzed by CIBERSORT. Different immune cell types in LN were analyzed by the Limma software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis based on GSEA were performed by clusterProfiler software. Lists of core genes were derived from Spearman correlation between the most significant GO term and differentially expressed immune cell gene from CIBERSORT. GSE113342 was employed to validate the association between selected core genes and clinical manifestation. Five types of immune cells revealed important associations with LN, and monocytes emerged as having the most prominent differences. GO and KEGG analyses indicated that immune response pathways are significantly enriched in LN. The Spearman correlation indicated that 15 genes, including FCER1G, CLEC7A, MARCO, CLEC7A, PSMB9, and PSMB8, were closely related to clinical features.

CONCLUSIONS

This study is the first to identify immune cell infiltration with microarray data of glomeruli in LN by using CIBERSORT analysis and provides novel evidence and clues for further research of the molecular mechanisms of LN.

Therapeutic effect of Bacillus Calmette-Guerin polysaccharide nucleic acid on mast cell at the transcriptional level

Background

Chronic spontaneous urticaria (CSU) is a common and recurrent autoimmune-related disease with unclear pathogenesis. Dysfunction of immune cells, such as T cells, mast cells, and basophils, is involved. Bacillus Calmette-Guerin polysaccharide nucleic acid (BCG-PSN), an immunomodulator partially extracted from BCG, can be used in the combined treatment of CSU with an unknown mechanism.

Methods

To study the therapeutic effect and mechanism of BCG-PSN on CSU, we initially assessed the clinical efficacy in 110 enrolled CSU patients of 4-week antihistamine monotherapy vs. antihistamine plus BCG-PSN combined therapy. Subsequently, to explore the further mechanism of BCG-PSN, the mast cell line RBL-2H3 pretreated with BCG-PSN was used to evaluate the transcriptional expression profiles via lncRNA sequencing. Real time PCR was conducted to validate the candidate gene expression.

Results

We found no significant difference in treatment efficacy between the BCG-PSN group (71.7%) and the monotherapy group (71.9%). However, the average time of complete relief in the BCG-PSN group was significantly shorter than that in the monotherapy group (36.77 ± 17.33 vs. 51.27 ± 16.80, p = 0.026). In vitro experiments showed that BCG-PSN inhibited β-hexosaminidase release rates in IgE-sensitized RBL-2H3 cells (p < 0.001). Sequencing data revealed the expression profiles of functional genes, including a significant decrease in Erb-B2 receptor tyrosine kinase 4, which can be regulated by the nuclear factor kappa B (NF-κB) pathway.

Discussion

CSU is a chronic, recurrent disease with complex pathogenesis. Mast cells and basophils are the primary target cells of the disease. BCG-PSN decrease the β-HEX release rates and regulated IgE-mediated mast cell activation in RBL-2H3 cells by mediating immune-related gene expression including ERBB4. These findings suggest that BCG-PSN may mediate ERBB4 expression via the NF-κB pathway and may have value in the treatment of CSU.

Vesiculobullous diseases in relation to lupus erythematosus

Vesiculobullous lesions in lupus erythematosus (LE) are a rare cutaneous manifestation of cutaneous and/or systemic LE with variable presentation. While the minor forms of LE-associated vesiculobullous disease may cause disfigurement and discomfort, the severe forms can present with hyperacute reaction and life-threatening consequences. Specific LE and aspecific cutaneous LE are defined by the presence or absence of interface change on histopathology that can be applied to vesiculobullous diseases in relation to LE. However, the diagnosis of LE-associated vesiculobullous diseases remains difficult, due to the poorly defined nosology and the similarities in clinical and immunohistopathological features among them. Herein, we thoroughly review the topic of vesiculobullous skin disorders that can be encountered in LE patients and organize them into four groups: LE-specific and aspecific vesiculobullous diseases, LE-related autoimmune bullous diseases, and LE in association to non-autoimmune conditions. We sought to provide an updated overview highlighting the pathogenesis, clinical, histological, and immunopathological features, laboratory findings, and treatments and prognosis among vesiculobullous conditions in LE.

Head Start Immunity: Characterizing the Early Protection of C Strain Vaccine Against Subsequent Classical Swine Fever Virus Infection

Classical Swine Fever Virus (CSFV) is an ongoing threat to the pig industry due to the high transmission and mortality rates associated with infection. Live attenuated vaccines such as the CSFV C strain vaccine are capable of protecting against infection within 5 days of vaccination, but the molecular mechanisms through which this early protection is mediated have yet to be established. In this study, we compared the response of pigs vaccinated with the C strain to non-vaccinated pigs both challenged with a pathogenic strain of CSFV. Analysis of transcriptomic data from the tonsils of these animals during the early stages after vaccination and challenge reveals a set of regulated genes that appear throughout the analysis. Many of these are linked to the ISG15 antiviral pathway suggesting it may play a role in the rapid and early protection conferred by C strain vaccination.

Autoreactive T-Lymphocytes in Inflammatory Skin Diseases

The presence of one or several autoantigen(s) and a response by the adaptive immune system are the key criteria to classify a pathology as an autoimmune disease. The list of entities fulfilling this criterion is currently growing in the light of recent advancements in the pathogenetic understanding of a number of important dermatoses. The role of autoreactive T-lymphocytes differs amongst these pathologies. While they are directly involved as effector cells attacking and sometimes killing their respective target in some diseases (e.g., vitiligo), they provide help to B-lymphocytes, which in turn produce the pathogenic autoreactive antibodies in others (pemphigus and pemphigoid). Atopic dermatits is a chimera in this regard, as there is evidence for both functions. Psoriasis is an example for an entity where autoantigens were finally identified, suggesting that at least a subgroup of patients should be classified as suffering from a true autoimmune rather than autoinflammatory condition. Identification of resident memory T-lymphocytes (T_RM) helped to understand why certain diseases relapse at the same site after seemingly effective therapy. Therefore, the in-depth characterization of autoreactive T-lyphocytes goes way beyond an academic exercise and opens the door toward improved therapies yielding durable responses. T_RM are particularly suitable targets in this regard, and the clinical efficacy of some established and emerging therapeutic strategies such as the inhibition of Janus Kinase 3 or interleukin 15 may rely on their capacity to prevent T_RM differentiation and maintenance. Research in this field brings us closer to the ultimate goal in the management of autoimmunity at large, namely resetting the immune system in order to restore the state of tolerance.

Gene expression profiling meta-analysis reveals novel gene signatures and pathways shared between tuberculosis and rheumatoid arthritis

Tuberculosis (TB) is among the leading causes of death by infectious diseases. An epidemiological association between Mycobacterium tuberculosis infection and autoimmune diseases like rheumatoid arthritis (RA) has been reported but it remains unclear if there is a causal relationship, and if so, which molecular pathways and regulatory mechanisms contribute to it. Here we used a computational biology approach by global gene expression meta-analysis to identify candidate genes and pathways that may link TB and RA. Data were collected from public expression databases such as NCBI GEO. Studies were selected that analyzed mRNA-expression in whole blood or blood cell populations in human case control studies at comparable conditions. Six TB and RA datasets (41 active TB patients, 33 RA patients, and 67 healthy controls) were included in the downstream analysis. This approach allowed the identification of deregulated genes that had not been identified in the single analysis of TB or RA patients and that were co-regulated in TB and RA patients compared to healthy subjects. The genes encoding TLR5, TNFSF10/TRAIL, PPP1R16B/TIMAP, SIAH1, PIK3IP1, and IL17RA were among the genes that were most significantly deregulated in TB and RA. Pathway enrichment analysis revealed 'T cell receptor signaling pathway', 'Toll-like receptor signaling pathway,' and 'virus defense related pathways' among the pathways most strongly associated with both diseases. The identification of a common gene signature and pathways substantiates the observation of an epidemiological association of TB and RA and provides clues on the mechanistic basis of this association. Newly identified genes may be a basis for future functional and epidemiological studies.

The relationship between pemphigus and systemic lupus erythematosus: a cross-sectional study, systematic review, and meta-analysis

The coexistence of pemphigus and systemic lupus erythematosus (SLE) had been reported anecdotally. Anti-desmoglein (Dsg)1 and anti-Dsg3 antibodies were detected concomitantly with antinuclear autoantibodies among blood donors. The aim of the current study was to study the association between pemphigus and SLE in Israeli patients and to synthesize existing data on this association in the current literature. The current study included two sections. Initially, a cross-sectional study was performed to compare pemphigus patients with age-, sex-, and ethnicity-matched control subjects regarding the prevalence of SLE using a real-life large-scale computerized database. Next, a systematic review and meta-analysis of similar observational studies in Medline, Embase, and Web of Science (1823-2017) was conducted. As for the cross-sectional study, a total of 1985 patients with pemphigus and 9874 controls were included in the study. The prevalence of SLE was slightly higher among patients with pemphigus as compared to controls (OR, 1.85; 95% CI, 0.89-3.82). In a sensitivity analysis that included patients who received pemphigus-related treatments, the association between pemphigus and SLE had been substantiated and was statistically significant (OR, 2.10; 95% CI, 1.00-4.48). In the meta-analysis section, three eligible studies, comprising 10,389 pemphigus patients met the eligibility criteria. The overall pooled multivariate OR was 2.50 (95% CI 1.54-4.07, I² = 44.19%, P = 0.167) across all studies. In conclusion, the meta-analysis provides epidemiologic evidence that these B cell-driven diseases are significantly associated. Further research is required to elucidate the molecular mechanism underlying this association.

Identification of Crucial Genes and Pathways in Human Arrhythmogenic Right Ventricular Cardiomyopathy by Coexpression Analysis

As one common disease causing young people to die suddenly due to cardiac arrest, arrhythmogenic right ventricular cardiomyopathy (ARVC) is a disorder of heart muscle whose progression covers one complicated gene interaction network that influence the diagnosis and prognosis of it. In our research, differentially expressed genes (DEGs) were screened, and we established a weighted gene coexpression network analysis (WGCNA) and gene set net correlations analysis (GSNCA) for identifying crucial genes as well as pathways related to ARVC pathogenic mechanism (n = 12). In the research, the results demonstrated that there were 619 DEGs in total between non-failing donor myocardial samples and ARVC tissues (FDR < 0.05). WGCNA analysis identified the two gene modules (brown and turquoise) as being most significantly associated with ARVC state. Then the ARVC-related four key biological pathways (cytokine–cytokine receptor interaction, chemokine signaling pathway, neuroactive ligand receptor interaction, and JAK-STAT signaling pathway) and four hub genes (CXCL2, TNFRSF11B, LIFR, and C5AR1) in ARVC samples were further identified by GSNCA method. Finally, we used t-test and receiver operating characteristic (ROC) curves for validating hub genes, results showed significant differences in t-test and their AUC areas all greater than 0.8. Together, these results revealed that the new four hub genes as well as key pathways that might be involved into ARVC diagnosis. Even though further experimental validation is required for the implication by association, our findings demonstrate that the computational methods based on systems biology might complement the traditional gene-wide approaches, as such, might offer a new insight in therapeutic intervention within rare diseases of people like ARVC.

Meta-analysis of the clinical and immunopathological characteristics and treatment outcomes in epidermolysis bullosa acquisita patients

Background

Epidermolysis bullosa acquisita (EBA) is an orphan autoimmune disease. Several clinical phenotypes have been described, but subepidermal blistering is characteristic of all variants. Limited data on clinical and immunopathological characteristics and treatment outcomes in EBA are available. To fill this gap, we collected this information from EBA cases, meeting current diagnostic criteria, published between 1971 and 2016.

Results

We identified 1159 EBA cases. This number must be, however, interpreted with caution, as it is not possible to check for multiple reporting. The analysis of all cases indicated that EBA affects all age groups (median: 50 years, range: 1 to 94 years) at an equal gender distribution. Non-mechanobullous (non-MB) forms of EBA were observed in 55% of patients, whereas the mechanobullous variant (MB-EBA) or a combination of both variants was described in 38 or 7% of patients, respectively. Type VII collagen (COL7)-specific autoantibodies were primarily of the IgG isotype, but anti-COL7 IgA, IgM and IgE were also documented. Comparison of the 2 clinical EBA types showed a higher frequency of IgA deposits in non-MB EBA as opposed to MB EBA. Mucous membrane involvement was observed in 23% of patients, and 4.4% of cases were associated with other chronic inflammatory diseases. Of note, IgA deposits were more frequently observed in cases with mucous membrane involvement. Our analysis indicated that EBA is difficult to treat and that the choice of treatment varies widely. Chi square was applied to identify medications associated with complete remission (CR). Considering all EBA cases, intravenous immunoglobulin (IVIG, p = 0.0047) and rituximab (p = 0.0114) were associated with CR. Subgroup analysis demonstrated that no treatment was associated with CR for non-MB EBA, while IVIG (p = 0.003) was associated with CR in MB EBA.

Conclusions

Within the limitations of the study, we here document the clinical and immunopathological characteristics and treatment outcomes in a large cohort of EBA patients. The observed associations of single drugs with treatment outcome may serve as a guide to develop clinical trials.

Electronic supplementary material

The online version of this article (10.1186/s13023-018-0896-1) contains supplementary material, which is available to authorized users.

The Genetics of Pemphigus Vulgaris

Pemphigus vulgaris (PV) is a severe autoimmune blistering disease caused by auto-antibodies (auto-Abs) directed against epithelial desmosomal components and leading to disruption of cell-cell adhesion. The exact mechanisms underlying the disease pathogenesis remain unknown and treatment is still based on immunosuppressive drugs, such as corticosteroids, which are associated with potentially significant side effects. Ethnic susceptibility, familial occurrence, and autoimmune comorbidity, suggest a genetic component to the pathogenesis of the disease, which, if discovered, could advance our understanding of PV pathogenesis and thereby point to novel therapeutic targets for this life-threatening disorder. In this article, we review the evidence for a genetic basis of PV, summarize the different approaches used to investigate susceptibility traits for the disease and describe past and recent discoveries regarding genes associated with PV, most of which belong to the human leukocyte antigen (HLA) locus with limited data regarding association of non-HLA genes with the disease.