Underexpression of mitochondrial-DNA encoded ATP synthesis-related genes and DNA repair genes in systemic lupus erythematosus

Abnormal energy metabolism in the pathogenesis of systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a severe autoimmune disease with significant socioeconomic impact worldwide. Orderly energy metabolism is essential for normal immune function, and disordered energy metabolism is increasingly recognized as an important contributor to the pathogenesis of SLE. Disorders of energy metabolism are characterized by increased reactive oxygen species, ATP deficiency, and abnormal metabolic pathways. Oxygen and mitochondria are critical for the production of ATP, and both mitochondrial dysfunction and hypoxia affect the energy production processes. In addition, several signaling pathways, including mammalian target of rapamycin (mTOR)/adenosine 5'-monophosphate (AMP)-activated protein kinase (AMPK) signaling and the hypoxia-inducible factor (HIF) pathway also play important regulatory roles in energy metabolism. Furthermore, drugs with clear clinical effects on SLE, such as sirolimus, metformin, and tacrolimus, have been proven to improve the disordered energy metabolism of immune cells, suggesting the potential of targeting energy metabolism for the treatment of SLE. Moreover, several metabolic modulators under investigation are expected to have potential therapeutic effects in SLE. This review aimed to gain insights into the role and mechanism of abnormal energy metabolism in the pathogenesis of SLE, and summarizes the progression of metabolic modulator in the treatment of SLE.

Revealing the impact of autophagy-related genes in rheumatoid arthritis: Insights from bioinformatics

Background

Rheumatoid arthritis is a systemic inflammatory autoimmune disease that severely impacts physical and mental health. Autophagy is a cellular process involving the degradation of cellular components in lysosomes. However, from a bioinformatics perspective, autophagy-related genes have not been comprehensively elucidated in rheumatoid arthritis.

Methods

In this study, we performed differential analysis of autophagy-related genes in rheumatoid arthritis patients using the GSE93272 dataset from the Gene Expression Omnibus database. Marker genes were screened by least absolute shrinkage and selection operator. Based on marker genes, we used unsupervised cluster analysis to elaborate different autophagy clusters, and further identified modules strongly associated with rheumatoid arthritis by weighted gene co-expression network analysis. In addition, we constructed four machine learning models, random forest model, support vector machine model, generalized linear model and extreme gradient boosting based on marker genes, and based on the optimal machine learning model, a nomogram model was constructed for distinguishing between normal individuals and rheumatoid arthritis patients. Finally, five external independent rheumatoid arthritis datasets were used for the validation of our results.

Results

The results showed that autophagy-related genes had significant expression differences between normal individuals and osteoarthritis patients. Through least absolute shrinkage and selection operator screening, we identified 31 marker genes and found that they exhibited significant synergistic or antagonistic effects in rheumatoid arthritis, and immune cell infiltration analysis revealed significant changes in immune cell abundance. Subsequently, we elaborated different autophagy clusters (cluster 1 and cluster 2) using unsupervised cluster analysis. Next, further by weighted gene co-expression network analysis, we identified a brown module strongly associated with rheumatoid arthritis. In addition, we constructed a nomogram model for five marker genes (CDKN2A, TP53, ATG16L2, FKBP1A, and GABARAPL1) based on a generalized linear model (area under the curve = 1.000), and the predictive efficiency and accuracy of this nomogram model were demonstrated in the calibration curves, the decision curves and the five external independent datasets were validated.

Conclusion

This study identified marker autophagy-related genes in rheumatoid arthritis and analyzed their impact on the disease, providing new perspectives for understanding the role of autophagy-related genes in rheumatoid arthritis and providing new directions for its individualized treatment.

SERTAD1 initiates NLRP3-mediated inflammasome activation through restricting NLRP3 polyubiquitination

We here demonstrate that SERTAD1 is an adaptor protein responsible for the regulation of lysine 63 (K63)-linked NLRP3 polyubiquitination by the Cullin1 E3 ubiquitin ligase upon inflammasome activation. SERTAD1 specifically binds to NLRP3 but not to other inflammasome sensors. This endogenous interaction increases after inflammasome activation, interfering with the interaction between NLRP3 and Cullin1. Interleukin (IL)-1β and IL-18 secretion, as well as the cleavage of gasdermin D, are decreased in SERTAD1 knockout bone-marrow-derived macrophages, together with reduced formation of the NLRP3 inflammasome complex. Additionally, SERTAD1-deficient mice show attenuated severity of monosodium-uric-acid-induced peritonitis and experimental autoimmune encephalomyelitis. Analysis of public datasets indicates that expression of SERTAD1 mRNA is significantly increased in the patients of autoimmune diseases. Thus, our findings uncover a function of SERTAD1 that specifically reduces Cullin1-mediated NLRP3 polyubiquitination via direct binding to NLRP3, eventually acting as a crucial factor to regulate the initiation of NLRP3-mediated inflammasome activation.

ProBDNF contributed to patrolling monocyte infiltration and renal damage in systemic lupus erythematosus

Monocyte aberrations have been increasingly recognized as contributors to renal damage in systemic lupus erythematosus (SLE), however, recognition of the underlying mechanisms and modulating strategies is at an early stage. Our studies have demonstrated that brain-derived neurotrophic factor precursor (proBDNF) drives the progress of SLE by perturbing antibody-secreting B cells, and proBDNF facilitates pro-inflammatory responses in monocytes. By utilizing peripheral blood from patients with SLE, GEO database and spontaneous MRL/lpr lupus mice, we demonstrated in the present study that CX3CR1+ patrolling monocytes (PMo) numbers were decreased in SLE. ProBDNF was specifically expressed in CX3CR1+ PMo and was closely correlated with disease activity and the degree of renal injury in SLE patients. In MRL/lpr mice, elevated proBDNF was found in circulating PMo and the kidney, and blockade of proBDNF restored the balance of circulating and kidney-infiltrating PMo. This blockade also led to the reversal of pro-inflammatory responses in monocytes and a noticeable improvement in renal damage in lupus mice. Overall, the results indicate that the upregulation of proBDNF in PMo plays a crucial role in their infiltration into the kidney, thereby contributing to nephritis in SLE. Targeting of proBDNF offers a potential therapeutic role in modulating monocyte-driven renal damage in SLE.

In cis "benign" SOCS1 variants linked to enhanced interferon signaling and autoimmunity

We aimed to characterize the genetic basis of disease in a family with multiple autoimmune manifestations, including systemic lupus erythematosus (SLE), immune thrombocytopenia, and autoimmune thyroiditis. Whole exome sequencing (WES) was conducted to identify candidate variants, which were analyzed by flow cytometry, immunoblotting, immunoprecipitation, and luciferase reporter assay in transfected 293T cells. Gene expression in peripheral blood mononuclear cells (PBMC) was profiled by bulk RNA sequencing and plasma cytokines were measured by proximity extension assay. In two siblings with early-onset SLE and immune thrombocytopenia, WES identified two maternally inherited in cis variants (p. Pro50Leu and p.Ala76Gly) in Suppressor of cytokine signaling 1 (SOCS1), flanking the kinase inhibitory domain that interacts with Janus kinases (JAK). Both variants were predicted to be benign by most in silico algorithms and neither alone affected the ability of SOCS1 to inhibit JAK-STAT1 signaling by functional studies. When both variants were expressed in cis, the mutant SOCS1 protein displayed decreased binding to JAK1 and reduced capacity to inhibit type I interferon (IFN-I) signaling by ∼20-30% compared to the wildtype protein. PBMC from the probands and their mother showed increased expression of interferon-inducible genes compared to healthy controls, supporting defective regulation of IFN-I signaling. Cells from all three subjects displayed heightened sensitivity to IFN-I stimulation, while response to IFN-γ, IL-4, and IL-6 was comparable to healthy controls. Our work illustrates the critical fine-tuning of IFN-I signaling by SOCS1 to prevent autoimmunity. We show that a combination of genetic variants that are individually benign may have deleterious consequences.

Platelets-related signature based diagnostic model in rheumatoid arthritis using WGCNA and machine learning

Background and aim

Rheumatoid arthritis (RA) is an autoinflammatory disease that may lead to severe disability. The diagnosis of RA is limited due to the need for biomarkers with both reliability and efficiency. Platelets are deeply involved in the pathogenesis of RA. Our study aims to identify the underlying mechanism and screening for related biomarkers.

Methods

We obtained two microarray datasets (GSE93272 and GSE17755) from the GEO database. We performed Weighted correlation network analysis (WGCNA) to analyze the expression modules in differentially expressed genes identified from GSE93272. We used KEGG, GO and GSEA enrichment analysis to elucidate the platelets-relating signatures (PRS). We then used the LASSO algorithm to develop a diagnostic model. We then used GSE17755 as a validation cohort to assess the diagnostic performance by operating Receiver Operating Curve (ROC).

Results

The application of WGCNA resulted in the identification of 11 distinct co-expression modules. Notably, Module 2 exhibited a prominent association with platelets among the differentially expressed genes (DEGs) analyzed. Furthermore, a predictive model consisting of six genes (MAPK3, ACTB, ACTG1, VAV2, PTPN6, and ACTN1) was constructed using LASSO coefficients. The resultant PRS model demonstrated excellent diagnostic accuracy in both cohorts, as evidenced by area under the curve (AUC) values of 0.801 and 0.979.

Conclusion

We elucidated the PRSs occurred in the pathogenesis of RA and developed a diagnostic model with excellent diagnostic potential.

Genome-wide identification of RNA modification-related single nucleotide polymorphisms associated with rheumatoid arthritis

BACKGROUND

RNA modification plays important roles in many biological processes, such as gene expression control. The aim of this study was to identify single nucleotide polymorphisms related to RNA modification (RNAm-SNPs) for rheumatoid arthritis (RA) as putative functional variants.

METHODS

We examined the association of RNAm-SNPs with RA in summary data from a genome-wide association study of 19,234 RA cases and 61,565 controls. We performed eQTL and pQTL analyses for the RNAm-SNPs to find associated gene expression and protein levels. Furthermore, we examined the associations of gene expression and circulating protein levels with RA using two-sample Mendelian randomization analysis methods.

RESULTS

A total of 160 RNAm-SNPs related to m⁶A, m¹A, A-to-I, m⁷G, m⁵C, m⁵U and m⁶Am modifications were identified to be significantly associated with RA. These RNAm-SNPs were located in 62 protein-coding genes, which were significantly enriched in immune-related pathways. RNAm-SNPs in important RA susceptibility genes, such as PADI2, SPRED2, PLCL2, HLA-A, HLA-B, HLA-DRB1, HLA-DPB1, TRAF1 and TXNDC11, were identified. Most of these RNAm-SNPs showed eQTL effects, and the expression levels of 26 of the modifiable genes (e.g., PADI2, TRAF1, HLA-A, HLA-DRB1, HLA-DPB1 and HLA-B) in blood cells were associated with RA. Circulating protein levels, such as CFB, GZMA, HLA-DQA2, IL21, LRPAP1 and TFF3, were affected by RNAm-SNPs and were associated with RA.

CONCLUSION

The present study identified RNAm-SNPs in the reported RA susceptibility genes and suggested that RNAm-SNPs may affect RA risk by affecting the expression levels of corresponding genes and proteins.

PRDX6AS1 gene polymorphisms and SLE susceptibility in Chinese populations

Background

Systemic lupus erythematosus (SLE) is a complex, multisystem autoimmune disease that is characterized by the production of autoantibodies. Although accumulated evidence suggests that the dysregulation of long non-coding RNAs (lncRNAs) is involved in the pathogenesis of SLE, the genetic contributions of lncRNA coding genes to SLE susceptibility remain largely unknown. Here, we aimed to provide more evidence for the role of lncRNA coding genes to SLE susceptibility.

Methods

The genetic association analysis was first adopted from the previous genome-wide association studies (GWAS) and was then validated in an independent cohort. PRDX6-AS1 is located at chr1:173204199-173446294. It spans a region of approximately 240 kb, and 297 single nucleotide polymorphisms (SNPs) were covered by the previous GWAS. Differential expression at the mRNA level was analyzed based on the ArrayExpress Archive database.

Results

A total of 33 SNPs were associated with SLE susceptibility, with a P<1.68×10^-4. The strongest association signal was detected at rs844649 (P=2.12×10^-6), according to the previous GWAS. Combining the results from the GWAS Chinese cohort and our replication cohort, we pursued a meta-analysis approach and found a pronounced genetic association between PRDX6-AS1 rs844649 and SLE susceptibility (p_meta=1.24×10^-13, OR 1.50, 95% CI: 1.34–1.67). The mRNA expression of PRDX6 was elevated in peripheral blood cells, peripheral blood mononuclear cells (PBMCs), and multiple cell subpopulations, such as B cells, CD4⁺ T cells, CD3⁺ cells, and monocytes in patients with SLE. The PRDX6 protein expression level was also increased in patients with SLE compared with healthy donors.

Conclusion

Our study provides new evidence that variants located in lncRNA coding genes are associated with SLE susceptibility.

IFI44 is an immune evasion biomarker for SARS-CoV-2 and Staphylococcus aureus infection in patients with RA

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a global pandemic of severe coronavirus disease 2019 (COVID-19). Staphylococcus aureus is one of the most common pathogenic bacteria in humans, rheumatoid arthritis (RA) is among the most prevalent autoimmune conditions. RA is a significant risk factor for SARS-CoV-2 and S. aureus infections, although the mechanism of RA and SARS-CoV-2 infection in conjunction with S. aureus infection has not been elucidated. The purpose of this study is to investigate the biomarkers and disease targets between RA and SARS-CoV-2 and S. aureus infections using bioinformatics analysis, to search for the molecular mechanisms of SARS-CoV-2 and S. aureus immune escape and potential drug targets in the RA population, and to provide new directions for further analysis and targeted development of clinical treatments.

Methods

The RA dataset (GSE93272) and the S. aureus bacteremia (SAB) dataset (GSE33341) were used to obtain differentially expressed gene sets, respectively, and the common differentially expressed genes (DEGs) were determined through the intersection. Functional enrichment analysis utilizing GO, KEGG, and ClueGO methods. The PPI network was created utilizing the STRING database, and the top 10 hub genes were identified and further examined for functional enrichment using Metascape and GeneMANIA. The top 10 hub genes were intersected with the SARS-CoV-2 gene pool to identify five hub genes shared by RA, COVID-19, and SAB, and functional enrichment analysis was conducted using Metascape and GeneMANIA. Using the NetworkAnalyst platform, TF-hub gene and miRNA-hub gene networks were built for these five hub genes. The hub gene was verified utilizing GSE17755, GSE55235, and GSE13670, and its effectiveness was assessed utilizing ROC curves. CIBERSORT was applied to examine immune cell infiltration and the link between the hub gene and immune cells.

Results

A total of 199 DEGs were extracted from the GSE93272 and GSE33341 datasets. KEGG analysis of enrichment pathways were NLR signaling pathway, cell membrane DNA sensing pathway, oxidative phosphorylation, and viral infection. Positive/negative regulation of the immune system, regulation of the interferon-I (IFN-I; IFN-α/β) pathway, and associated pathways of the immunological response to viruses were enriched in GO and ClueGO analyses. PPI network and Cytoscape platform identified the top 10 hub genes: RSAD2, IFIT3, GBP1, RTP4, IFI44, OAS1, IFI44L, ISG15, HERC5, and IFIT5. The pathways are mainly enriched in response to viral and bacterial infection, IFN signaling, and 1,25-dihydroxy vitamin D3. IFI44, OAS1, IFI44L, ISG15, and HERC5 are the five hub genes shared by RA, COVID-19, and SAB. The pathways are primarily enriched for response to viral and bacterial infections. The TF-hub gene network and miRNA-hub gene network identified YY1 as a key TF and hsa-mir-1-3p and hsa-mir-146a-5p as two important miRNAs related to IFI44. IFI44 was identified as a hub gene by validating GSE17755, GSE55235, and GSE13670. Immune cell infiltration analysis showed a strong positive correlation between activated dendritic cells and IFI44 expression.

Conclusions

IFI144 was discovered as a shared biomarker and disease target for RA, COVID-19, and SAB by this study. IFI44 negatively regulates the IFN signaling pathway to promote viral replication and bacterial proliferation and is an important molecular target for SARS-CoV-2 and S. aureus immune escape in RA. Dendritic cells play an important role in this process. 1,25-Dihydroxy vitamin D3 may be an important therapeutic agent in treating RA with SARS-CoV-2 and S. aureus infections.

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.

Bioinformatics and System Biology Approach to Identify the Influences of COVID-19 on Rheumatoid Arthritis

Background

Severe coronavirus disease 2019 (COVID -19) has led to a rapid increase in mortality worldwide. Rheumatoid arthritis (RA) was a high-risk factor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, whereas the molecular mechanisms underlying RA and CVOID-19 are not well understood. The objectives of this study were to analyze potential molecular mechanisms and identify potential drugs for the treatment of COVID-19 and RA using bioinformatics and a systems biology approach.

Methods

Two Differentially expressed genes (DEGs) sets extracted from GSE171110 and GSE1775544 datasets were intersected to generate common DEGs, which were used for functional enrichment, pathway analysis, and candidate drugs analysis.

Results

A total of 103 common DEGs were identified in the two datasets between RA and COVID-19. A protein-protein interaction (PPI) was constructed using various combinatorial statistical methods and bioinformatics tools. Subsequently, hub genes and essential modules were identified from the PPI network. In addition, we performed functional analysis and pathway analysis under ontological conditions and found that there was common association between RA and progression of COVID-19 infection. Finally, transcription factor-gene interactions, protein-drug interactions, and DEGs-miRNAs coregulatory networks with common DEGs were also identified in the datasets.

Conclusion

We successfully identified the top 10 hub genes that could serve as novel targeted therapy for COVID-19 and screened out some potential drugs useful for COVID-19 patients with RA.

Mitochondria in the Pathogenesis of Systemic Lupus Erythematosus

PURPOSE OF REVIEW

Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by autoantibody production and inflammation in multiple organs. In this article, we present data on how various mitochondria pathologies are involved in the pathogenesis of the disease including the fact that they serve as a reservoir of autoantigens which contribute to the upending of lymphocyte tolerance.

RECENT FINDINGS

Mitochondrial DNA from various cell sources, including neutrophil extracellular traps, platelets, and red blood cells, elicits the production of type I interferon which contributes to breaking of peripheral tolerance. Mitochondrial DNA also serves as autoantigen targeted by autoantibodies. Mutations of mitochondrial DNA triggered by reactive oxygen species induce T cell cross-reactivity against self-antigens. Selective gene polymorphisms that regulate mitochondrial apoptosis in autoreactive B and T cells represent another key aspect in the induction of autoimmunity. Various mitochondrial abnormalities, including changes in mitochondrial function, oxidative stress, genetic polymorphism, mitochondrial DNA mutations, and apoptosis pathways, are each linked to different aspects of lupus pathogenesis. However, whether targeting these mitochondrial pathologies can be used to harness autoimmunity remains to be explored.

Integrated Genomic and Transcriptomic Analyses of Diffuse Large B-Cell Lymphoma With Multiple Abnormal Immunologic Markers

Background

Diffuse large B-cell lymphoma (DLBCL) is a highly aggressive subtype of lymphoma and related to autoimmune diseases (AIDs). Primary B-cell receptor-mediated AIDs are associated with poor clinical outcome of DLBCL. To further determine the role of immunological alterations on disease progression, our study integrated genomic and transcriptomic analyses on DLBCL with multiple abnormal immunologic markers.

Methods

The clinical data of 1,792 patients with newly diagnosed DLBCL were collected, with DNA- and RNA-sequencing conducted for 164 and 127 patients, respectively. Frequent gene mutations and the involved dysregulated pathways, along with gene expression pattern and tumor microenvironment alternations, were analyzed and compared based on the immune status of the patients.

Results

DLBCL with multiple abnormal immunologic markers demonstrated a variety of characteristics including elevated serum lactic dehydrogenase level, inferior prognosis, and dysregulated cell cycle and immune response, as well as activated oxidative phosphorylation pathway and increased Th1/Th2 and Th17/Treg ratios, which were highly similar as those that occur in AIDs.

Conclusions

We piloted the description of the clinical and genetic features of DLBCL with multiple abnormal immunologic markers, illustrated possible mechanisms of disease progression, and provided a clinical rationale of mechanism-based targeted therapy in this subset of DLBCL.

Identification of Diagnostic Signatures and Immune Cell Infiltration Characteristics in Rheumatoid Arthritis by Integrating Bioinformatic Analysis and Machine-Learning Strategies

Background

Rheumatoid arthritis (RA) refers to an autoimmune rheumatic disease that imposes a huge burden on patients and society. Early RA diagnosis is critical to preventing disease progression and selecting optimal therapeutic strategies more effectively. In the present study, the aim was at examining RA's diagnostic signatures and the effect of immune cell infiltration in this pathology.

Methods

Gene Expression Omnibus (GEO) database provided three datasets of gene expressions. Firstly, this study adopted R software for identifying differentially expressed genes (DEGs) and conducting functional correlation analyses. Subsequently, we integrated bioinformatic analysis and machine-learning strategies for screening and determining RA's diagnostic signatures and further verify by qRT-PCR. The diagnostic values were assessed through receiver operating characteristic (ROC) curves. Moreover, this study employed cell-type identification by estimating relative subsets of RNA transcript (CIBERSORT) website for assessing the inflammatory state of RA, and an investigation was conducted on the relationship of diagnostic signatures and infiltrating immune cells.

Results

On the whole, 54 robust DEGs received the recognition. Lymphocyte-specific protein 1 (LSP1), Granulysin (GNLY), and Mesenchymal homobox 2 (MEOX2) (AUC = 0.955) were regarded as RA's diagnostic markers and showed their statistically significant difference by qRT-PCR. As indicated from the immune cell infiltration analysis, resting NK cells, neutrophils, activated NK cells, T cells CD8, memory B cells, and M0 macrophages may be involved in the development of RA. Additionally, all diagnostic signatures might be different degrees of correlation with immune cells.

Conclusions

In conclusion, LSP1, GNLY, and MEOX2 are likely to be available in terms of diagnosing and treating RA, and the infiltration of immune cells mentioned above may critically impact RA development and occurrence.

Gene-based association analysis identified a novel gene associated with systemic lupus erythematosus

OBJECTIVE

Systemic lupus erythematosus (SLE) is a complex autoimmune disease with strong genetic predisposition. Genome-wide association studies (GWAS) of SLE have identified more than 50 robust susceptibility loci. However, traditional individual SNP-based GWAS have made it difficult to identify variants with small effects. Moreover, variants revealed by GWAS only explain a limited disease heritability, suggesting that many susceptibility genes remain uncovered.

METHODS

We first curated the published SLE GWAS data from 1047 SLE patients and 1205 healthy controls of Chinese ancestry and performed a gene-based association study. Then quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was conducted to verify novel genes identified above.

RESULTS

Gene-based association study identified 10 SLE-associated genes, nine of which were reported by previous GWAS, the other one, ILRUN, is a newly identified gene and was further validated by qRT-PCR. Gene expression analysis of Gene Expression Omnibus (GEO) datasets also showed that the expression of ILRUN in patients with SLE was lower than that in normal subjects.

CONCLUSION

In this study, gene-based association study and qRT-PCR identified that ILRUN is a novel susceptibility gene of SLE. ILRUN may regulate inflammation and antiviral response through its effect on the transcription of type I interferons )I-IFN, and participate in the pathogenesis of SLE.

A 9 mRNAs-based diagnostic signature for rheumatoid arthritis by integrating bioinformatic analysis and machine-learning

Background

Rheumatoid arthritis (RA) is an autoimmune rheumatic disease that carries a substantial burden for both patients and society. Early diagnosis of RA is essential to prevent disease progression and select an optimal therapeutic strategy. However, RA diagnosis is challenging, partly due to a lack of reliable biomarkers. Here, we aimed to explore the diagnostic signature and establish a predictive model of RA.

Methods

The mRNA expression profiling data of GSE17755, containing blood samples of 112 RA patients and 53 healthy control patients, were obtained from the Gene Expression Omnibus (GEO) database, followed by differential expression, GO (Gene Ontology), and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analysis. A PPI network was constructed to select candidate hub genes, then logistic regression and random forest models were established based on the identified genes.

Results

Significantly, we identified 52 differentially expressed genes (DEGs), including 16 upregulated genes and 36 downregulated genes in RA samples compared with control samples. GO and KEGG analysis showed that several immune-related cellular processes were particularly enriched. We identified nine hub genes in the PPI network, including CFL1, COTL1, ACTG1, PFN1, LCP1, LCK, HLA-E, FYN, and HLA-DRA. The logistic regression and random forest models based on the nine identified genes reliably distinguished the RA samples from the healthy samples with substantially high AUC.

Conclusion

The diagnostic logistic regression and random forest models based on nine hub genes reliably predicted the occurrence of RA. Our findings could provide new insights into RA diagnostics.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13018-020-02180-w.

Integrative analysis identifies potential causal methylation-mRNA regulation chains for rheumatoid arthritis

Genome-wide association studies have identified many genetic loci for rheumatoid arthritis (RA). However, causal factors underlying these loci were largely unknown. The aim of this study was to identify potential causal methylation-mRNA regulation chains for RA. We identified differentially expressed mRNAs and methylations and conducted summary statistic data-based Mendelian randomization (SMR) analysis to detect potential causal mRNAs and methylations for RA. Then causal inference test (CIT) was performed to determine if the methylation-mRNA pairs formed causal chains. We identified 11,170 mRNAs and 24,065 methylations that were nominally associated with RA. Among them, 197 mRNAs and 104 methylations passed the SMR test. According to physical positions, we defined 16 cis methylation-mRNA pairs and inferred 5 chains containing 4 methylations and 4 genes (BACH2, MBP, MX1 and SYNGR1) to be methylation→mRNA→RA causal chains. The effect of SYNGR1 expression in peripheral blood mononuclear cells on RA risk was found to be consistent in both the in-house and public data. The identified methylations located in CpG Islands that overlap promoters in the 5' region of the genes. The promoter regions showed long-range interactions with other enhancers and promoters, suggesting a regulatory potential of these methylations. Therefore, the present study provided a new integrative analysis strategy and highlighted potential causal methylation-mRNA chains for RA. Taking the evidences together, SYNGR1 promoter methylations most probably affect mRNA expressions and then affect RA risk.

The Role of Mitochondria in Systemic Lupus Erythematosus: A Glimpse of Various Pathogenetic Mechanisms

BACKGROUND

Systemic Lupus Erythematosus (SLE) is a polysystem autoimmune disease that adversely affects human health. Various organs can be affected, including the kidney or brain. Traditional treatment methods for SLE primarily rely on glucocorticoids and immunosuppressors. Unfortunately, these therapeutic agents cannot prevent a high recurrence rate after SLE remission. Therefore, novel therapeutic targets are urgently required.

METHODS

A systematic search of the published literature regarding the abnormal structure and function of mitochondria in SLE and therapies targeting mitochondria was performed in several databases.

RESULTS

Accumulating evidence indicates that mitochondrial dysfunction plays important roles in the pathogenesis of SLE, including influencing mitochondrial DNA damage, mitochondrial dynamics change, abnormal mitochondrial biogenesis and energy metabolism, mitophagy, oxidative stress, inflammatory reactions, apoptosis and NETosis. Further investigation of mitochondrial pathophysiological roles will result in further clarification of SLE. Specific lupus-induced organ damage also exhibits characteristic mitochondrial changes.

CONCLUSION

This review aimed to summarize the current research on the role of mitochondrial dysfunction in SLE, which will necessarily provide potential novel therapeutic targets for SLE.

An integrative Bayesian network approach to highlight key drivers in systemic lupus erythematosus

BACKGROUND

A comprehensive intuition of the systemic lupus erythematosus (SLE), as a complex and multifactorial disease, is a biological challenge. Dealing with this challenge needs employing sophisticated bioinformatics algorithms to discover the unknown aspects. This study aimed to underscore key molecular characteristics of SLE pathogenesis, which may serve as effective targets for therapeutic intervention.

METHODS

In the present study, the human peripheral blood mononuclear cell (PBMC) microarray datasets (n = 6), generated by three platforms, which included SLE patients (n = 220) and healthy control samples (n = 135) were collected. Across each platform, we integrated the datasets by cross-platform normalization (CPN). Subsequently, through BNrich method, the structures of Bayesian networks (BNs) were extracted from KEGG-indexed SLE, TCR, and BCR signaling pathways; the values of the node (gene) and edge (intergenic relationships) parameters were estimated within each integrated datasets. Parameters with the FDR < 0.05 were considered significant. Finally, a mixture model was performed to decipher the signaling pathway alterations in the SLE patients compared to healthy controls.

RESULTS

In the SLE signaling pathway, we identified the dysregulation of several nodes involved in the (1) clearance mechanism (SSB, MACROH2A2, TRIM21, H2AX, and C1Q gene family), (2) autoantigen presentation by MHCII (HLA gene family, CD80, IL10, TNF, and CD86), and (3) end-organ damage (FCGR1A, ELANE, and FCGR2A). As a remarkable finding, we demonstrated significant perturbation in CD80 and CD86 to CD28, CD40LG to CD40, C1QA and C1R to C2, and C1S to C4A edges. Moreover, we not only replicated previous studies regarding alterations of subnetworks involved in TCR and BCR signaling pathways (PI3K/AKT, MAPK, VAV gene family, AP-1 transcription factor) but also distinguished several significant edges between genes (PPP3 to NFATC gene families). Our findings unprecedentedly showed that different parameter values assign to the same node based on the pathway topology (the PIK3CB parameter values were 1.7 in TCR vs - 0.5 in BCR signaling pathway).

CONCLUSIONS

Applying the BNrich as a hybridized network construction method, we highlight under-appreciated systemic alterations of SLE, TCR, and BCR signaling pathways in SLE. Consequently, having such a systems biology approach opens new insights into the context of multifactorial disorders.

Integrated, multicohort analysis reveals unified signature of systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a complex autoimmune disease that follows an unpredictable disease course and affects multiple organs and tissues. We performed an integrated, multicohort analysis of 7,471 transcriptomic profiles from 40 independent studies to identify robust gene expression changes associated with SLE. We identified a 93-gene signature (SLE MetaSignature) that is differentially expressed in the blood of patients with SLE compared with healthy volunteers; distinguishes SLE from other autoimmune, inflammatory, and infectious diseases; and persists across diverse tissues and cell types. The SLE MetaSignature correlated significantly with disease activity and other clinical measures of inflammation. We prospectively validated the SLE MetaSignature in an independent cohort of pediatric patients with SLE using a microfluidic quantitative PCR (qPCR) array. We found that 14 of the 93 genes in the SLE MetaSignature were independent of IFN-induced and neutrophil-related transcriptional profiles that have previously been associated with SLE. Pathway analysis revealed dysregulation associated with nucleic acid biosynthesis and immunometabolism in SLE. We further refined a neutropoiesis signature and identified underappreciated transcripts related to immune cells and oxidative stress. In our multicohort, transcriptomic analysis has uncovered underappreciated genes and pathways associated with SLE pathogenesis, with the potential to advance clinical diagnosis, biomarker development, and targeted therapeutics for SLE.

Identification of dysregulated genes and pathways of different brain regions in Alzheimer's disease

Background: Alzheimer's disease (AD) is a degenerative neurologic disease. The study aimed to identify the key differentially expressed genes (DEGs) and pathways in AD pathogenesis and obtain potential biomarkers in AD diagnosis.Methods: An integrated analysis of publicly available Gene Expression Omnibus datasets of AD was performed. DEGs in hippocampus tissue (HIP), temporal gyrus tissue (TG), frontal gyrus tissue (FG) and whole blood (WB) were identified. Bioinformatics analyses were used to insight into the functions of DEGs. The expression levels of candidate DEGs were preliminarily validated in GSE1297. The discriminatory ability of candidate DEGs in WB samples of AD patients and healthy individuals was evaluated in GSE63060 and GSE63061 datasets through receiver operating characteristic (ROC) analysis.Results: The DEGs in HIP, TG and FG tissues of AD were identified. Functions involved in regulation of apoptotic process, apoptotic process and cell death were significantly enriched from DEGs in AD. MAPK signaling pathway and Wnt signaling pathway were significantly enriched. YAP1, MAPK9 and GJA1 were the hub proteins in protein-protein interaction network in HIP, TG and FG. The expression levels of 14 DEGs in GSE1297 dataset were consistent with our integrated analysis. Moreover, 7 out of 14 DEGs had the diagnostic value in distinguishing AD patients from healthy controls in both GSE630060 and GSE630061 datasets.Conclusion: The DEGs including YAP1, MAPK1, GJA1 and pathways including MAPK signaling pathway and Wnt signaling pathway may be related to AD progression. RAD51C, SAFB2, SSH3 and TXNDC9 might be potential biomarkers in AD diagnosis.

DNA Damage Response and Oxidative Stress in Systemic Autoimmunity

The DNA damage response and repair (DDR/R) network, a sum of hierarchically structured signaling pathways that recognize and repair DNA damage, and the immune response to endogenous and/or exogenous threats, act synergistically to enhance cellular defense. On the other hand, a deregulated interplay between these systems underlines inflammatory diseases including malignancies and chronic systemic autoimmune diseases, such as systemic lupus erythematosus, systemic sclerosis, and rheumatoid arthritis. Patients with these diseases are characterized by aberrant immune response to self-antigens with widespread production of autoantibodies and multiple-tissue injury, as well as by the presence of increased oxidative stress. Recent data demonstrate accumulation of endogenous DNA damage in peripheral blood mononuclear cells from these patients, which is related to (a) augmented DNA damage formation, at least partly due to the induction of oxidative stress, and (b) epigenetically regulated functional abnormalities of fundamental DNA repair mechanisms. Because endogenous DNA damage accumulation has serious consequences for cellular health, including genomic instability and enhancement of an aberrant immune response, these results can be exploited for understanding pathogenesis and progression of systemic autoimmune diseases, as well as for the development of new treatments.

Identification of Regulatory Modules That Stratify Lupus Disease Mechanism through Integrating Multi-Omics Data

Although recent advances in genetic studies have shed light on systemic lupus erythematosus (SLE), its detailed mechanisms remain elusive. In this study, using datasets on SLE transcriptomic profiles, we identified 750 differentially expressed genes (DEGs) in T and B lymphocytes and peripheral blood cells. Using transcription factor (TF) binding data derived from chromatin immunoprecipitation sequencing (ChIP-seq) experiments from the Encyclopedia of DNA Elements (ENCODE) project, we inferred networks of co-regulated genes (NcRGs) based on binding profiles of the upregulated DEGs by significantly enriched TFs. Modularization analysis of NcRGs identified co-regulatory modules among the DEGs and master TFs vital for each module. Remarkably, the co-regulatory modules stratified the common SLE interferon (IFN) signature and revealed SLE pathogenesis pathways, including the complement cascade, cell cycle regulation, NETosis, and epigenetic regulation. By integrative analyses of disease-associated genes (DAGs), DEGs, and enriched TFs, as well as proteins interacting with them, we identified a hierarchical regulatory cascade with TFs regulated by DAGs, which in turn regulates gene expression. Integrative analysis of multi-omics data provided valuable molecular insights into the molecular mechanisms of SLE.

The triggers of the cGAS-STING pathway and the connection with inflammatory and autoimmune diseases

Cyclic GMP-AMP synthase (cGAS) is a cytosolic nucleic acid sensor that can bind to dsDNA. It maintains an autoinhibited state in the absence of cytosolic dsDNA, while when activated, it in turn activates its adaptor protein STING, ultimately triggering a cascade that produces inflammatory cytokines and type I interferons (IFNs). With further research, additional types of nucleic acids have been found to be activators of the cGAS-STING pathway. The cGAS-STING pathway can provide protection or resistance against infections; however, improper or overactivation might cause severe inflammatory pathologies, including autoimmunity. This article systematically reviews the latest research progress on the axis, including categorical pathway triggers, the connection with autoimmune disease and drug therapy progress.

Bioinformatics identification of key candidate genes and pathways associated with systemic lupus erythematosus

OBJECTIVE

Systemic lupus erythematosus (SLE) is a complex autoimmune disease characterized by autoantibody production and multi-system involvement, but the etiology is largely unclear. This study aimed to elucidate candidate genes and pathways involved in SLE.

METHODS

Three original datasets GSE72509, GSE20864, and GSE39088 were downloaded from Gene Expression Omnibus (GEO) and the data were further integrated and analyzed. Subsequently, differentially expressed genes (DEGs) between SLE patients and healthy people were identified. And then we performed gene ontology (GO) function and pathway enrichment analyses of common DEGs, and constructed a protein-protein interaction (PPI) network with STRING database. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was carried out to validate the expression levels of candidate genes in blood samples from SLE patients and healthy controls.

RESULTS

In total, 321 common DEGs were identified in SLE patients compared with healthy controls, including 231 upregulated and 90 downregulated genes. GO function analysis revealed that 321 common DEGs were mainly enriched in innate immune response, defense response, cytokine-mediated signaling pathway, response to interferon-alpha, and I-kappaB kinase/NF-kappaB signaling. Additionally, pathway enrichment analysis indicated that DEGs were mainly enriched in several signaling pathways associated with immune system and apoptosis, including RIG-I-like receptor signaling pathway, antigen processing and presentation, and p53 signaling pathway. The expression levels of candidate genes RPL26L1, FBXW11, FOXO1, and SMAD7 were validated by RT-qPCR analysis.

CONCLUSIONS

The four hub genes including RPL26L1, FBXW11, FOXO1, and SMAD7 may play key roles in the pathogenesis and development of SLE. RIG-I-like receptor signaling pathway, antigen processing and presentation pathway, and p53 signaling pathway may be closely implicated in SLE pathogenesis. Collectively, these results may provide valuable novel markers or targets for the diagnosis and treatment of SLE.Key Points• Integrated bioinformatics analysis of three profile datasets based on SLE patients and healthy controls was performed and 321 common DEGs were identified.• The 321 common DEGs were mainly enriched in biological processes related to immune responses and inflammatory responses, including innate immune response, defense response, cytokine-mediated signaling pathway, response to interferon-alpha, I-kappaB kinase/NF-kappaB signaling, whereas the three most significant cellular components were oxidoreductase complex, AIM2 inflammasome complex, and ubiquitin ligase complex.• KEGG pathway enrichment analysis indicated that common DEGs were mainly enriched in several signaling pathways associated with immune system and apoptosis, including RIG-I-like receptor signaling pathway, antigen processing and presentation, and p53 signaling pathway.• Candidate genes RPL26L1, FBXW11, FOXO1, and SMAD7 may be closely involved in the pathogenesis and development of SLE and may provide valuable novel markers or targets for the diagnosis and treatment of SLE.

ImmGen report: sexual dimorphism in the immune system transcriptome

Sexual dimorphism in the mammalian immune system is manifested as more frequent and severe infectious diseases in males and, on the other hand, higher rates of autoimmune disease in females, yet insights underlying those differences are still lacking. Here we characterize sex differences in the immune system by RNA and ATAC sequence profiling of untreated and interferon-induced immune cell types in male and female mice. We detect very few differentially expressed genes between male and female immune cells except in macrophages from three different tissues. Accordingly, very few genomic regions display differences in accessibility between sexes. Transcriptional sexual dimorphism in macrophages is mediated by genes of innate immune pathways, and increases after interferon stimulation. Thus, the stronger immune response of females may be due to more activated innate immune pathways prior to pathogen invasion.

Sexual dimorphism is observed frequently in immune disorders, but the underlying insights are still unclear. Here the authors analyze transcriptome and epigenome changes induced by interferon in various mouse immune cell types, and find only a restricted set of sexual dimorphism genes in innate immunity and macrophages.

Bioinformatics methodologies for coeliac disease and its comorbidities

Coeliac disease (CD) is a complex, multifactorial pathology caused by different factors, such as nutrition, immunological response and genetic factors. Many autoimmune diseases are comorbidities for CD, and a comprehensive and integrated analysis with bioinformatics approaches can help in evaluating the interconnections among all the selected pathologies. We first performed a detailed survey of gene expression data available in public repositories on CD and less commonly considered comorbidities. Then we developed an innovative pipeline that integrates gene expression, cell-type data and online resources (e.g. a list of comorbidities from the literature), using bioinformatics methods such as gene set enrichment analysis and semantic similarity. Our pipeline is written in R language, available at the following link: http://bioinformatica.isa.cnr.it/COELIAC_DISEASE/SCRIPTS/. We found a list of common differential expressed genes, gene ontology terms and pathways among CD and comorbidities and the closeness among the selected pathologies by means of disease ontology terms. Physicians and other researchers, such as molecular biologists, systems biologists and pharmacologists can use it to analyze pathology in detail, from differential expressed genes to ontologies, performing a comparison with the pathology comorbidities or with other diseases.

DNA Damage and Deficiencies in the Mechanisms of Its Repair: Implications in the Pathogenesis of Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is a perplexing and potentially severe disease, the pathogenesis of which is yet to be understood. SLE is considered to be a multifactorial disease, in which genetic factors, immune dysregulation, and environmental factors, such as ultraviolet radiation, are involved. Recently, the description of novel genes conferring susceptibility to develop SLE even in their own (monogenic lupus) has raised the interest in DNA dynamics since many of these genes are linked to DNA repair. Damage to DNA induces an inflammatory response and eventually triggers an immune response, including those targeting self-antigens. We review the evidence that indicates that patients with SLE present higher levels of DNA damage than normal subjects do and that several proteins involved in the preservation of the genomic stability show polymorphisms, some of which increase the risk for SLE development. Also, the experience from animal models reinforces the connection between DNA damage and defective repair in the development of SLE-like disease including characteristic features such as anti-DNA antibodies and nephritis. Defining the role of DNA damage response in SLE pathogenesis might be strategic in the quest for novel therapies.

Identification of ST3AGL4, MFHAS1, CSNK2A2 and CD226 as loci associated with systemic lupus erythematosus (SLE) and evaluation of SLE genetics in drug repositioning

OBJECTIVES

Systemic lupus erythematosus (SLE) is a prototype autoimmune disease with a strong genetic component in its pathogenesis. Through genome-wide association studies (GWAS), we recently identified 10 novel loci associated with SLE and uncovered a number of suggestive loci requiring further validation. This study aimed to validate those loci in independent cohorts and evaluate the role of SLE genetics in drug repositioning.

METHODS

We conducted GWAS and replication studies involving 12 280 SLE cases and 18 828 controls, and performed fine-mapping analyses to identify likely causal variants within the newly identified loci. We further scanned drug target databases to evaluate the role of SLE genetics in drug repositioning.

RESULTS

We identified three novel loci that surpassed genome-wide significance, including ST3AGL4 (rs13238909, p_meta=4.40E-08), MFHAS1 (rs2428, p_meta=1.17E-08) and CSNK2A2 (rs2731783, p_meta=1.08E-09). We also confirmed the association of CD226 locus with SLE (rs763361, p_meta=2.45E-08). Fine-mapping and functional analyses indicated that the putative causal variants in CSNK2A2 locus reside in an enhancer and are associated with expression of CSNK2A2 in B-lymphocytes, suggesting a potential mechanism of association. In addition, we demonstrated that SLE risk genes were more likely to be interacting proteins with targets of approved SLE drugs (OR=2.41, p=1.50E-03) which supports the role of genetic studies to repurpose drugs approved for other diseases for the treatment of SLE.

CONCLUSION

This study identified three novel loci associated with SLE and demonstrated the role of SLE GWAS findings in drug repositioning.

The emerging role of immune dysfunction in mitochondrial diseases as a paradigm for understanding immunometabolism

Immunometabolism aims to define the role of intermediary metabolism in immune cell function, with bioenergetics and the mitochondria recently taking center stage. To date, the medical literature on mitochondria and immune function extols the virtues of mouse models in exploring this biologic intersection. While the laboratory mouse has become a standard for studying mammalian biology, this model comprises part of a comprehensive approach. Humans, with their broad array of inherited phenotypes, serve as a starting point for studying immunometabolism; specifically, patients with mitochondrial disease. Using this top-down approach, the mouse as a model organism facilitates further exploration of the consequences of mutations involved in mitochondrial maintenance and function. In this review, we will discuss the emerging phenotype of immune dysfunction in mitochondrial disease as a model for understanding the role of the mitochondria in immune function in available mouse models.

A novel gene and pathway-level subtyping analysis scheme to understand biological mechanisms in complex disease: a case study in rheumatoid arthritis

Complex diseases have heterogeneous underlying molecular mechanisms. In order to improve the diagnosis and treatment of disease, it is vital to stratify patients into homogeneous subgroups that share a similar disease etiology. In this study, we performed gene-level subtyping analysis on two independent Rheumatoid Arthritis gene expression cohorts from different ethnic groups to discover the possible disease mechanisms associated with each subtype. Also, a novel pathway-level analysis is proposed to increase the subtyping robustness and facilitate biological interpretation. This approach could stratify RA patients into two robust and homogeneous groups with differing activation of central signal transduction pathways and pro-inflammatory cytokines in the pathogenesis of RA. Such a methodology can help understand disease mechanisms at play in different patient sub-populations and also potentially explain why some patients don't respond to anti-TNF treatment.

Alterations of oxygen consumption and extracellular acidification rates by glutamine in PBMCs of SLE patients

We evaluated plasma glutamine levels and basal mitochondrial oxygen consumption rate (mOCR_B) and basal extracellular acidification rate (ECAR_B) of peripheral blood mononuclear cells (PBMCs) of systemic lupus erythematous (SLE) patients and healthy controls (HCs). Lower plasma glutamine levels correlated with higher SLE disease activity indexes (p=0.025). Incubated in DMEM containing 100mg/dL glucose, SLE-PBMCs displayed lower mOCR_B (p=0.018) but similar ECAR_B (p=0.467) to those of HC-PBMCs, and their mOCR_B got elevated (p<0.001) without altering ECAR_B (p=0.239) by supplementation with 2 or 4mM glutamine. We conclude that impaired mitochondrial respiration of SLE-PBMCs could be improved by glutamine under euglycemic condition.

A Therapeutic Connection between Dietary Phytochemicals and ATP Synthase

For centuries, phytochemicals have been used to prevent and cure multiple health ailments. Phytochemicals have been reported to have antioxidant, antidiabetic, antitussive, antiparasitic, anticancer, and antimicrobial properties. Generally, the therapeutic use of phy-tochemicals is based on tradition or word of mouth with few evidence-based studies. Moreo-ver, molecular level interactions or molecular targets for the majority of phytochemicals are unknown. In recent years, antibiotic resistance by microbes has become a major healthcare concern. As such, the use of phytochemicals with antimicrobial properties has become perti-nent. Natural compounds from plants, vegetables, herbs, and spices with strong antimicrobial properties present an excellent opportunity for preventing and combating antibiotic resistant microbial infections. ATP synthase is the fundamental means of cellular energy. Inhibition of ATP synthase may deprive cells of required energy leading to cell death, and a variety of die-tary phytochemicals are known to inhibit ATP synthase. Structural modifications of phyto-chemicals have been shown to increase the inhibitory potency and extent of inhibition. Site-directed mutagenic analysis has elucidated the binding site(s) for some phytochemicals on ATP synthase. Amino acid variations in and around the phytochemical binding sites can re-sult in selective binding and inhibition of microbial ATP synthase. In this review, the therapeu-tic connection between dietary phytochemicals and ATP synthase is summarized based on the inhibition of ATP synthase by dietary phytochemicals. Research suggests selective target-ing of ATP synthase is a valuable alternative molecular level approach to combat antibiotic resistant microbial infections.

TREM-1 and its potential ligands in non-infectious diseases: from biology to clinical perspectives

Triggering receptor expressed on myeloid cells-1 (TREM-1) is expressed on the majority of innate immune cells and to a lesser extent on parenchymal cells. Upon activation, TREM-1 can directly amplify an inflammatory response. Although it was initially demonstrated that TREM-1 was predominantly associated with infectious diseases, recent evidences shed new light into its role in sterile inflammatory diseases. Indeed, TREM-1 receptor and its signaling pathways contribute to the pathology of several non-infectious acute and chronic inflammatory diseases, including atherosclerosis, ischemia reperfusion-induced tissue injury, colitis, fibrosis and cancer. This review, aims to give an extensive overview of TREM-1 in non-infectious diseases, with the focus on the therapeutic potential of TREM-1 intervention strategies herein. In addition, we provide the reader with a functional enrichment analysis of TREM-1 signaling pathway and potential TREM-1 ligands in these diseases, obtained via in silico approach. We discuss pre-clinical studies which show that TREM-1 inhibition, via synthetic soluble TREM-1 protein mimickers, is effective in treating (preventing) specific inflammatory disorders, without significant effects on antibacterial response. Further research aimed at identifying specific TREM-1 ligands, in different inflammatory disorders, is required to further unravel the role of this receptor, and explore new avenues to modulate its function.

The frontline of immune response in peripheral blood

Peripheral blood is an attractive source for the discovery of disease biomarkers. Gene expression profiling of whole blood or its components has been widely conducted for various diseases. However, due to population heterogeneity and the dynamic nature of gene expression, certain biomarkers discovered from blood transcriptome studies could not be replicated in independent studies. In the meantime, it's also important to know whether a reliable biomarker is shared by several diseases or specific to certain health conditions. We hypothesized that common mechanism of immune response in blood may be shared by different diseases. Under this hypothesis, we surveyed publicly available transcriptome data on infectious and autoimmune diseases derived from peripheral blood. We examined to which extent common gene dys-regulation existed in different diseases. We also investigated whether the commonly dys-regulated genes could serve as reliable biomarkers. First, we found that a limited number of genes are frequently dys-regulated in infectious and autoimmune diseases, from which we selected 10 genes co-dysregulated in viral infections and another set of 10 genes co-dysregulated in bacterial infections. In addition to its ability to distinguish viral infections from bacterial infections, these 20 genes could assist in disease classification and monitoring of treatment effect for several infectious and autoimmune diseases. In some cases, a single gene is sufficient to serve this purpose. It was interesting that dys-regulation of these 20 genes were also observed in other types of diseases including cancer and stroke where certain genes could also serve as biomarkers for diagnosis or prognosis. Furthermore, we demonstrated that this set of 20 genes could also be used in continuous monitoring of personal health. The rich information from these commonly dys-regulated genes may find its wide application in clinical practice and personal healthcare. More validation studies and in-depth investigations are warranted in the future.

A Four-Biomarker Blood Signature Discriminates Systemic Inflammation Due to Viral Infection Versus Other Etiologies

The innate immune system of humans and other mammals responds to pathogen-associated molecular patterns (PAMPs) that are conserved across broad classes of infectious agents such as bacteria and viruses. We hypothesized that a blood-based transcriptional signature could be discovered indicating a host systemic response to viral infection. Previous work identified host transcriptional signatures to individual viruses including influenza, respiratory syncytial virus and dengue, but the generality of these signatures across all viral infection types has not been established. Based on 44 publicly available datasets and two clinical studies of our own design, we discovered and validated a four-gene expression signature in whole blood, indicative of a general host systemic response to many types of viral infection. The signature’s genes are: Interferon Stimulated Gene 15 (ISG15), Interleukin 16 (IL16), 2′,5′-Oligoadenylate Synthetase Like (OASL), and Adhesion G Protein Coupled Receptor E5 (ADGRE5). In each of 13 validation datasets encompassing human, macaque, chimpanzee, pig, mouse, rat and all seven Baltimore virus classification groups, the signature provides statistically significant (p < 0.05) discrimination between viral and non-viral conditions. The signature may have clinical utility for differentiating host systemic inflammation (SI) due to viral versus bacterial or non-infectious causes.

Identification of dysregulated genes in rheumatoid arthritis based on bioinformatics analysis

BACKGROUND

Rheumatoid arthritis (RA) is a chronic auto-inflammatory disorder of joints. The present study aimed to identify the key genes in RA for better understanding the underlying mechanisms of RA.

METHODS

The integrated analysis of expression profiling was conducted to identify differentially expressed genes (DEGs) in RA. Moreover, functional annotation, protein-protein interaction (PPI) network and transcription factor (TF) regulatory network construction were applied for exploring the potential biological roles of DEGs in RA. In addition, the expression level of identified candidate DEGs was preliminarily detected in peripheral blood cells of RA patients in the GSE17755 dataset. Quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to validate the expression levels of identified DEGs in RA.

RESULTS

A total of 378 DEGs, including 202 up- and 176 down-regulated genes, were identified in synovial tissues of RA patients compared with healthy controls. DEGs were significantly enriched in axon guidance, RNA transport and MAPK signaling pathway. RBFOX2, LCK and SERBP1 were the hub proteins in the PPI network. In the TF-target gene network, RBFOX2, POU6F1, WIPF1 and PFKFB3 had the high connectivity with TFs. The expression status of 11 candidate DEGs was detected in GSE17755, the expression levels of MAT2A and NSA2 were significantly down-regulated and CD47 had the up-regulated tendency in peripheral blood cells of patients with RA compared with healthy individuals. qRT-PCR results of MAT2A, NSA2, CD47 were compatible with our bioinformatics analyses.

DISCUSSION

Our study might provide valuable information for exploring the pathogenesis mechanism of RA and identifying the potential biomarkers for RA diagnosis.

Gene-Based Genome-Wide Association Analysis in European and Asian Populations Identified Novel Genes for Rheumatoid Arthritis

Objective

Rheumatoid arthritis (RA) is a complex autoimmune disease. Using a gene-based association research strategy, the present study aims to detect unknown susceptibility to RA and to address the ethnic differences in genetic susceptibility to RA between European and Asian populations.

Methods

Gene-based association analyses were performed with KGG 2.5 by using publicly available large RA datasets (14,361 RA cases and 43,923 controls of European subjects, 4,873 RA cases and 17,642 controls of Asian Subjects). For the newly identified RA-associated genes, gene set enrichment analyses and protein-protein interactions analyses were carried out with DAVID and STRING version 10.0, respectively. Differential expression verification was conducted using 4 GEO datasets. The expression levels of three selected ‘highly verified’ genes were measured by ELISA among our in-house RA cases and controls.

Results

A total of 221 RA-associated genes were newly identified by gene-based association study, including 71‘overlapped’, 76 ‘European-specific’ and 74 ‘Asian-specific’ genes. Among them, 105 genes had significant differential expressions between RA patients and health controls at least in one dataset, especially for 20 genes including 11 ‘overlapped’ (ABCF1, FLOT1, HLA-F, IER3, TUBB, ZKSCAN4, BTN3A3, HSP90AB1, CUTA, BRD2, HLA-DMA), 5 ‘European-specific’ (PHTF1, RPS18, BAK1, TNFRSF14, SUOX) and 4 ‘Asian-specific’ (RNASET2, HFE, BTN2A2, MAPK13) genes whose differential expressions were significant at least in three datasets. The protein expressions of two selected genes FLOT1 (P value = 1.70E-02) and HLA-DMA (P value = 4.70E-02) in plasma were significantly different in our in-house samples.

Conclusion

Our study identified 221 novel RA-associated genes and especially highlighted the importance of 20 candidate genes on RA. The results addressed ethnic genetic background differences for RA susceptibility between European and Asian populations and detected a long list of overlapped or ethnic specific RA genes. The study not only greatly increases our understanding of genetic susceptibility to RA, but also provides important insights into the ethno-genetic homogeneity and heterogeneity of RA in both ethnicities.

A meta-analysis of public microarray data identifies gene regulatory pathways deregulated in peripheral blood mononuclear cells from individuals with Systemic Lupus Erythematosus compared to those without

BACKGROUND

Systemic Lupus Erythematosus (SLE) is a complex, multi-systemic, autoimmune disease for which the underlying aetiological mechanisms are poorly understood. The genetic and molecular processes underlying lupus have been extensively investigated using a variety of -omics approaches, including genome-wide association studies, candidate gene studies and microarray experiments of differential gene expression in lupus samples compared to controls.

METHODS

This study analyses a combination of existing microarray data sets to identify differentially regulated genetic pathways that are dysregulated in human peripheral blood mononuclear cells from SLE patients compared to unaffected controls. Two statistical approaches, quantile discretisation and scaling, are used to combine publicly available expression microarray datasets and perform a meta-analysis of differentially expressed genes.

RESULTS

Differentially expressed genes implicated in interferon signaling were identified by the meta-analysis, in agreement with the findings of the individual studies that generated the datasets used. In contrast to the individual studies, however, the meta-analysis and subsequent pathway analysis additionally highlighted TLR signaling, oxidative phosphorylation and diapedesis and adhesion regulatory networks as being differentially regulated in peripheral blood mononuclear cells (PBMCs) from SLE patients compared to controls.

CONCLUSION

Our analysis demonstrates that it is possible to derive additional information from publicly available expression data using meta-analysis techniques, which is particularly relevant to research into rare diseases where sample numbers can be limiting.

Disease-specific classification using deconvoluted whole blood gene expression

Blood-based biomarker assays have an advantage in being minimally invasive. Diagnostic and prognostic models built on peripheral blood gene expression have been reported for various types of disease. However, most of these studies focused on only one disease type, and failed to address whether the identified gene expression signature is disease-specific or more widely applicable across diseases. We conducted a meta-analysis of 46 whole blood gene expression datasets covering a wide range of diseases and physiological conditions. Our analysis uncovered a striking overlap of signature genes shared by multiple diseases, driven by an underlying common pattern of cell component change, specifically an increase in myeloid cells and decrease in lymphocytes. These observations reveal the necessity of building disease-specific classifiers that can distinguish different disease types as well as normal controls, and highlight the importance of cell component change in deriving blood gene expression based models. We developed a new strategy to develop blood-based disease-specific models by leveraging both cell component changes and cell molecular state changes, and demonstrate its superiority using independent datasets.

The Mechanism for Type I Interferon Induction by Mycobacterium tuberculosis is Bacterial Strain-Dependent

Type I interferons (including IFNαβ) are innate cytokines that may contribute to pathogenesis during Mycobacterium tuberculosis (Mtb) infection. To induce IFNβ, Mtb must gain access to the host cytosol and trigger stimulator of interferon genes (STING) signaling. A recently proposed model suggests that Mtb triggers STING signaling through bacterial DNA binding cyclic GMP-AMP synthase (cGAS) in the cytosol. The aim of this study was to test the generalizability of this model using phylogenetically distinct strains of the Mtb complex (MTBC). We infected bone marrow derived macrophages with strains from MTBC Lineages 2, 4 and 6. We found that the Lineage 6 strain induced less IFNβ, and that the Lineage 2 strain induced more IFNβ, than the Lineage 4 strain. The strains did not differ in their access to the host cytosol and IFNβ induction by each strain required both STING and cGAS. We also found that the three strains shed similar amounts of bacterial DNA. Interestingly, we found that the Lineage 6 strain was associated with less mitochondrial stress and less mitochondrial DNA (mtDNA) in the cytosol compared with the Lineage 4 strain. Treating macrophages with a mitochondria-specific antioxidant reduced cytosolic mtDNA and inhibited IFNβ induction by the Lineage 2 and 4 strains. We also found that the Lineage 2 strain did not induce more mitochondrial stress than the Lineage 4 strain, suggesting that additional pathways contribute to higher IFNβ induction. These results indicate that the mechanism for IFNβ by Mtb is more complex than the established model suggests. We show that mitochondrial dynamics and mtDNA contribute to IFNβ induction by Mtb. Moreover, we show that the contribution of mtDNA to the IFNβ response varies by MTBC strain and that additional mechanisms exist for Mtb to induce IFNβ.

Defective DNA repair and chromatin organization in patients with quiescent systemic lupus erythematosus

Background

Excessive autoantibody production characterizing systemic lupus erythematosus (SLE) occurs irrespective of the disease’s clinical status and is linked to increased lymphocyte apoptosis. Herein, we tested the hypothesis that defective DNA damage repair contributes to increased apoptosis in SLE.

Methods

We evaluated nucleotide excision repair at the N-ras locus, DNA double-strand breaks repair and apoptosis rates in peripheral blood mononuclear cells from anti-dsDNA autoantibody-positive patients (six with quiescent disease and six with proliferative nephritis) and matched healthy controls following ex vivo treatment with melphalan. Chromatin organization and expression levels of DNA repair- and apoptosis-associated genes were also studied in quiescent SLE.

Results

Defective nucleotide excision repair and DNA double-strand breaks repair were found in SLE, with lupus nephritis patients showing higher DNA damage levels than those with quiescent disease. Melphalan-induced apoptosis rates were higher in SLE than control cells and correlated inversely with DNA repair efficiency. Chromatin at the N-ras locus was more condensed in SLE than controls, while treatment with the histone deacetylase inhibitor vorinostat resulted in hyperacetylation of histone H4, chromatin decondensation, amelioration of DNA repair efficiency and decreased apoptosis. Accordingly, genes involved in DNA damage repair and signaling pathways, such as DDB1, ERCC2, XPA, XPC, MRE11A, RAD50, PARP1, MLH1, MLH3, and ATM were significantly underexpressed in SLE versus controls, whereas PPP1R15A, BARD1 and BBC3 genes implicated in apoptosis were significantly overexpressed.

Conclusions

Epigenetically regulated functional abnormalities of DNA repair machinery occur in SLE, regardless of clinical disease activity, and may promote lymphocyte apoptosis. Approaches to correct these abnormalities may be of therapeutic value in SLE.

Electronic supplementary material

The online version of this article (doi:10.1186/s13075-016-1081-3) contains supplementary material, which is available to authorized users.

Parsing the Interferon Transcriptional Network and Its Disease Associations

Type 1 interferon (IFN) is a key mediator of organismal responses to pathogens, eliciting prototypical "interferon signature genes" that encode antiviral and inflammatory mediators. For a global view of IFN signatures and regulatory pathways, we performed gene expression and chromatin analyses of the IFN-induced response across a range of immunocyte lineages. These distinguished ISGs by cell-type specificity, kinetics, and sensitivity to tonic IFN and revealed underlying changes in chromatin configuration. We combined 1,398 human and mouse datasets to computationally infer ISG modules and their regulators, validated by genetic analysis in both species. Some ISGs are controlled by Stat1/2 and Irf9 and the ISRE DNA motif, but others appeared dependent on non-canonical factors. This regulatory framework helped to interpret JAK1 blockade pharmacology, different clusters being affected under tonic or IFN-stimulated conditions, and the IFN signatures previously associated with human diseases, revealing unrecognized subtleties in disease footprints, as affected by human ancestry.

Physiological evidence for diversification of IFNα- and IFNβ-mediated response programs in different autoimmune diseases

Background

Activation of the type I interferon (IFN) response program is described for several autoimmune diseases, including systemic lupus erythematosus (SLE), multiple sclerosis (MS), myositis (IIM) and rheumatoid arthritis (RA). While IFNα contributes to SLE pathology, IFNβ therapy is often beneficial in MS, implying different immunoregulatory roles for these IFNs. This study was aimed to investigate potential diversification of IFNα-and IFNβ-mediated response programs in autoimmune diseases.

Methods

Peripheral blood gene expression of 23 prototypical type I IFN response genes (IRGs) was determined in 54 healthy controls (HCs), 69 SLE (47 test, 22 validation), 149 IFNβ-treated MS (71 test, 78 validation), 160 untreated MS, 78 IIM and 76 RA patients. Patients with a type I IFN signature were selected for analysis.

Results

We identified IFNα- and IFNβ-specific response programs (GC-A and GC-B, respectively) in SLE and IFNβ-treated MS patients. Concordantly, the GC-A/GC-B log-ratio was positive for all SLE patients and negative for virtually all IFNβ-treated MS patients, which was confirmed in additional cohorts. Applying this information to other autoimmune diseases, IIM patients displayed positive GC-A/GC-B log-ratios, indicating predominant IFNα activity. The GC-A/GC-B log-ratio in RA was lower and approached zero in part of the patients, implying relative importance of both clusters. Remarkably, GC-A/GC-B log-ratios appeared most heterogeneous in untreated MS; half of the patients displayed GC-A dominance, whereas others showed GC-B dominance or log-ratios near zero.

Conclusions

Our findings show diversification of the type I IFN response in autoimmune diseases, suggesting different pathogenic roles of the type I IFNs.

Electronic supplementary material

The online version of this article (doi:10.1186/s13075-016-0946-9) contains supplementary material, which is available to authorized users.

Mitochondrial and oxidative stress genes are differentially expressed in neutrophils of sJIA patients treated with tocilizumab: a pilot microarray study

BACKGROUND

Various pathways involved in the pathogenesis of sJIA have been identified through gene expression profiling in peripheral blood mononuclear cells (PBMC), but not in neutrophils. Since neutrophils are important in tissue damage during inflammation, and are elevated as part of the acute phase response, we hypothesised that neutrophil pathways could also be important in the pathogenesis of sJIA. We therefore studied the gene profile in both PBMC and neutrophils of sJIA patients treated with tocilizumab.

METHODS

We studied the transcriptomes of peripheral blood mononuclear cells (PBMC) and neutrophils from eight paired samples obtained from 4 sJIA patients taken before and after treatment, selected on the basis that they achieved ACR90 responses within 12 weeks of therapy initiation with tocilizumab. RNA was extracted and gene expression profiling was performed using Affymetrix GeneChip Human Genome U133 Plus 2.0 microarray platform. A longitudinal analysis using paired t-test (p < 0.05 and FC ≥ 1.5) was applied to identify differentially expressed genes (DEGs) between the two time points followed by ingenuity pathway analysis. Gene Set Enrichment Analysis (GSEA) and quantitative real-time PCR were then performed to verify the microarray results.

RESULTS

Gene ontology analysis in neutrophils revealed that response to tocilizumab significantly altered genes regulating mitochondrial dysfunction and oxidative stress (p = 4.6E-05). This was independently verified with GSEA, by identifying a set of oxidative genes whose expression correlated with response to tocilizumab. In PBMC, treatment of sJIA with tocilizumab appeared to affect genes in Oncostatin M signalling and B cell pathways.

CONCLUSIONS

For the first time we demonstrate that neutrophils from sJIA patients responding to tocilizumab showed significantly different changes in gene expression. These data could highlight the importance of mitochondrial genes that modulate oxidative stress in the pathogenesis of sJIA.

Integrated Analyses of Gene Expression Profiles Digs out Common Markers for Rheumatic Diseases

OBJECTIVE

Rheumatic diseases have some common symptoms. Extensive gene expression studies, accumulated thus far, have successfully identified signature molecules for each rheumatic disease, individually. However, whether there exist shared factors across rheumatic diseases has yet to be tested.

METHODS

We collected and utilized 6 public microarray datasets covering 4 types of representative rheumatic diseases including rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis, and osteoarthritis. Then we detected overlaps of differentially expressed genes across datasets and performed a meta-analysis aiming at identifying common differentially expressed genes that discriminate between pathological cases and normal controls. To further gain insights into the functions of the identified common differentially expressed genes, we conducted gene ontology enrichment analysis and protein-protein interaction analysis.

RESULTS

We identified a total of eight differentially expressed genes (TNFSF10, CX3CR1, LY96, TLR5, TXN, TIA1, PRKCH, PRF1), each associated with at least 3 of the 4 studied rheumatic diseases. Meta-analysis warranted the significance of the eight genes and highlighted the general significance of four genes (CX3CR1, LY96, TLR5, and PRF1). Protein-protein interaction and gene ontology enrichment analyses indicated that the eight genes interact with each other to exert functions related to immune response and immune regulation.

CONCLUSION

The findings support that there exist common factors underlying rheumatic diseases. For rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis and osteoarthritis diseases, those common factors include TNFSF10, CX3CR1, LY96, TLR5, TXN, TIA1, PRKCH, and PRF1. In-depth studies on these common factors may provide keys to understanding the pathogenesis and developing intervention strategies for rheumatic diseases.

Mitochondrial DNA stress primes the antiviral innate immune response

Mitochondrial DNA (mtDNA) is normally present at thousands of copies per cell and is packaged into several hundred higher-order structures termed nucleoids¹. The abundant mtDNA-binding protein, transcription factor A mitochondrial (TFAM), regulates nucleoid architecture, abundance, and segregation². Complete mtDNA depletion profoundly impairs oxidative phosphorylation (OXPHOS), triggering calcium-dependent stress signaling and adaptive metabolic responses³. However, the cellular responses to mtDNA instability, a physiologically relevant stress observed in many human diseases and aging, remain ill-defined⁴. Here we show that moderate mtDNA stress elicited by TFAM deficiency engages cytosolic antiviral signaling to enhance the expression of a subset of interferon-stimulated genes (ISG). Mechanistically, we have found that aberrant mtDNA packaging promotes escape of mtDNA into the cytosol, where it engages the DNA sensor cGAS and promotes STING-IRF3-dependent signaling to elevate ISG expression, potentiate type I interferon responses, and confer broad viral resistance. Furthermore, we demonstrate that herpesviruses induce mtDNA stress, which potentiates antiviral signaling and type I interferon responses during infection. Our results further demonstrate that mitochondria are central participants in innate immunity, identify mtDNA stress as a cell-intrinsic trigger of antiviral signaling, and suggest that cellular monitoring of mtDNA homeostasis cooperates with canonical virus sensing mechanisms to fully license antiviral innate immunity.