Cluster of highly expressed interferon-stimulated genes associate more with African ancestry than disease activity in patients with systemic lupus erythematosus. A systematic review of cross-sectional studies

DNA methylation and whole-genome transcription analysis in CD4+ T cells from systemic lupus erythematosus patients with or without renal damage

BACKGROUND

Lupus nephritis (LN) is the most common cause of kidney injury in systemic lupus erythematosus (SLE) patients and is associated with increased mortality. DNA methylation, one of the most important epigenetic modifications, has been reported as a key player in the pathogenesis of SLE. Hence, our article aimed to explore DNA methylation in CD4+ T cells from LNs to identify additional potential biomarkers and pathogenic genes involved in the progression of LN.

METHODS

Our study enrolled 46 SLE patients with or without kidney injury and 23 healthy controls from 2019 to 2022. CD4+ T cells were sorted for DNA methylation genotyping and RNA-seq. Through bioinformatics analysis, we identified the significant differentially methylated CpG positions (DMPs) only in the LN group and validated them by Bisulfite PCR. Integration analysis was used to screen for differentially methylated and expressed genes that might be involved in the progression of LN, and the results were analyzed via cell experiments and flow cytometry.

RESULTS

We identified 243 hypomethylated sites and 778 hypermethylated sites only in the LN cohort. Three of these DMPs, cg08332381, cg03297029, and cg16797344, were validated by Bisulfite PCR and could be potential biomarkers for LN. Integrated analysis revealed that the expression of BCL2L14 and IFI27 was regulated by DNA methylation, which was validated by azacytidine (5-aza) treatment. The overexpression of BCL2L14 in CD4+ T cells might induce renal fibrosis and inflammation by regulating the differentiation and function of Tfh cells.

CONCLUSION

Our study identified novel aberrant DMPs in CD4+ T cells only in LN patients and DNA methylation-regulated genes that could be potential LN biomarkers. BCL2L14 is likely involved in the progression of LN and might be a treatment target.

Burden of systemic lupus erythematosus in clinical practice: baseline data from the SLE Prospective Observational Cohort Study (SPOCS) by interferon gene signature

OBJECTIVE

The longitudinal Systemic Lupus Erythematosus Prospective Observational Cohort Study (SPOCS) aims to assess SLE disease course overall and according to type I interferon 4 gene signature (IFNGS). Here, we describe SPOCS patient characteristics by IFNGS and baseline disease activity.

METHODS

SPOCS (NCT03189875) is an international study of patients with SLE according to Systemic Lupus International Collaborating Clinics (SLICC)/American College of Rheumatology (ACR) criteria. Enrolled patients from 135 centres in 8 countries were followed biannually for ≤3 years from June 2017 to November 2022. Baseline demographics, disease characteristics, organ system involvement/damage and flares were analysed descriptively according to SLE Disease Activity Index-2000 score (SLEDAI-2K <10/≥10) and IFNGS status (high/low).

RESULTS

The study population (n=823) was 93.2% female, with mean (SD) age 45.3 (13.9) years and 11.1 (9.2) years since diagnosis; 52.4% had baseline SLICC/ACR Damage Index score ≥1. Patients with SLEDAI-2K scores ≥10 (241 of 584, 41.3%) vs <10 were younger (mean 42.8 (13.7) vs 46.6 (14.2) years; nominal p=0.001), had shorter SLE duration (10.4 (8.6) vs 12.4 (9.6) years; nominal p=0.012) and more severe flares (12.9% vs 5.3%; nominal p=0.001). IFNGS-high patients (522 of 739, 70.6%) were younger than IFNGS-low patients at first SLE manifestation (30.0 (12.7) vs 36.8 (14.6) years; nominal p<0.001). Proportions of IFNGS-high patients differed according to race (nominal p<0.001), with higher proportions among Asian (83.3%) and black (86.5%) versus white patients (63.5%). Greater proportions of IFNGS-high versus IFNGS-low patients had haematological (12.6% vs 4.1%), immunological (74.4% vs 45.6%) or dermal (69.7% vs 62.2%) involvement.

CONCLUSIONS

We identified key characteristics of patients with high disease activity and/or elevated type I IFN signalling, populations with SLE with high unmet needs. Baseline SLEDAI-2K ≥10 was associated with shorter disease duration and more severe flares. IFNGS-high patients were younger at diagnosis and had distinct patterns of organ involvement, compared with IFNGS-low patients.

A comprehensive analysis of type 1 interferon gene signatures in systematic lupus erythematosus and prediction of the crucial susceptible factor for Sjögren syndrome

This study aimed to determine the role of IFN-1 gene signatures in SLE and their association with Sjögren syndrome (SS). Publicly available data from the Gene Expression Omnibus database were used to construct the models. The random forest tree model was used to screen key IFN-1 gene signatures, and consensus clustering algorithms were used for unsupervised cluster analysis of these signatures. CIBERSORT and gene set variation analyses were used to evaluate the relative immune cell infiltration and enriched molecular pathways of the samples, respectively. Weighted gene co-expression network analysis was used to identify the co-expression modules and hub genes. Finally, univariate and multivariate logistic regression models were used to evaluate differences in clinical and laboratory characteristics between the different groups. The role of IFN-1 gene signatures in SLE was comprehensively assessed, which revealed an IFN-1 gene signature including six genes that could easily distinguish SLE patients and healthy individuals and identified two distinct IFN-1 subtypes exhibiting significant differences in clinical characteristics, immune microenvironment, and biological functional pathways. The SLE disease activity index, lower lymphocyte count, nucleotide oligomerization domain (NOD)-like receptor signaling pathway, and dendritic cell activation were strongly correlated with the IFN-1 gene signatures. In addition, we found that IFN-1 gene signatures in SLE may be an important susceptibility factor for SS, and the NOD-like receptor signaling pathway was identified as a common pathway. This study provides a comprehensive evaluation of the IFN-1 gene signatures, which may provide a new direction for the understanding of SLE and SS and help in the selection of optimal strategies for personalized immunotherapy.

Revealing common differential mRNAs, signaling pathways, and immune cells in blood, glomeruli, and tubulointerstitium of lupus nephritis patients based on transcriptomic data

Lupus nephritis (LN) is a potentially fatal autoimmune disease. The purpose of this study was to find potential key molecular markers of LN to aid in the early diagnosis and management of the disease. Datasets GSE99967_blood, GSE32591_glomeruli, and GSE32591_tubulointerstitium were included in this study. Differentially expressed mRNAs (DEmRNAs) were identified between the normal control and LN groups using the limma package in R. Common DEmRNAs in the three datasets were taken. Subsequently, functional enrichment analysis, immune correlation analysis, receiver operating characteristic (ROC) curve analysis and real-time polymerase chain reaction (RT-PCR) verification were performed. In this study, 11 common DEmRNAs were obtained and all of them were up-regulated. In protein-protein interaction (PPI) networks, we found that MX dynamin like GTPase 1 (MX1) and radical S-adenosyl methionine domain containing 2 (RSAD2) had the highest interaction score (0.997). Functional enrichment analysis revealed that MX1 and RSAD2 were enriched in influenza A and hepatitis C signaling pathways. The area under the curve (AUC) values of interferon-induced protein 44 (IFI44) and MX1 in GSE32591_glomeruli and GSE32591_tubulointerstitium datasets are 1, which is worthy of further study on their diagnostic value and molecular mechanism. The xCell analysis showed abnormal distribution of granulocyte-macrophage progenitor (GMP) cells in blood, glomeruli, and tubulointerstitium. Pearson's correlation analysis found that GMP cells were significantly correlated with lactotransferrin (LTF) and cell cycle. Identification of common DEmRNAs and key pathways in the blood, glomeruli, and tubulointerstitium of patients with LN provides potential research directions for exploring the molecular mechanisms of the disease.

Interferons and systemic lupus erythematosus: Pathogenesis, clinical features, and treatments in interferon-driven disease

Type I interferons (IFNs) have recently received a lot of attention with the elucidation of the pathogenesis of systemic lupus erythematosus (SLE). Type I IFNs are associated with many SLE symptoms and play a role in the pathogenesis of autoimmune diseases that may occur concurrently with SLE, such as Sjögren's syndrome, antiphospholipid syndrome, myositis, scleroderma, and interferonopathy. Type I IFNs could be the link between these diseases. However, direct measurement of type I IFN levels and the IFN gene signature is currently unavailable in clinical practice. This review discusses type I IFN signalling in SLE, investigates the role of type I IFN in the clinical manifestations and symptoms associated with SLE and other IFN-related diseases, and discusses the clinical tests that can be used to diagnose SLE and measure disease activity. In addition, the role of type I IFN-blocking therapies as potential treatments for SLE is discussed.

Identification and Clinical Correlation Analysis of IFI44 in Systemic Lupus Erythematosus Combined with Bioinformatics and Immune Infiltration Analysis

Purpose

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that can cause systemic damage to multiple organs. This study aims to analyze the value and function of IFI44 in the diagnosis and pathology of SLE by bioinformatics and immune infiltration analysis.

Patients and Methods

GSE49454 and GSE65391 of SLE were obtained from the GEO dataset, and R software was employed to identify DEGs and investigate their functions. The PPI network was utilized to identify hub genes associated with SLE. CIBERSORT was used to assess differences in immune cell infiltration in SLE patients and controls. ROC curve analysis was performed to evaluate the diagnostic value of IFI44 in SLE. The expression of IFI44 in PBMCs was detected by RT-qPCR, and the correlation between IFI44 expression and SLE-related clinical indicators was analyzed.

Results

A total of 65 DEGs were identified from the GSE49454 and GSE65391 databases. Through PPI analysis, IFI44 and RSAD2 were identified as significantly aberrantly expressed in SLE patients. SLE patients and controls showed a significant difference in the proportion of immune cell infiltration. IFI44 expression was positively correlated with activated DCs, monocytes, PCs, neutrophils, and activated memory CD4+T cells, while negatively correlated with M0 and CD8+T cells. The expression of IFI44 was significantly higher in SLE patients (P<0.01), especially in male patients (P=0.0376). ROC curve analysis demonstrated that IFI44 had a high diagnostic value for SLE. Correlation analysis indicated that IFI44 expression was correlated with levels of RBC, HGB, HCT, IgA, ESR, UPRO, C3, C4, and ENA in SLE patients.

Conclusion

IFI44 may play a role in the pathogenesis of SLE by influencing the immune microenvironment of SLE patients, and thus has the potential to serve as a diagnostic marker and therapeutic target for SLE.

IFI27 transcription is an early predictor for COVID-19 outcomes, a multi-cohort observational study

Purpose

Robust biomarkers that predict disease outcomes amongst COVID-19 patients are necessary for both patient triage and resource prioritisation. Numerous candidate biomarkers have been proposed for COVID-19. However, at present, there is no consensus on the best diagnostic approach to predict outcomes in infected patients. Moreover, it is not clear whether such tools would apply to other potentially pandemic pathogens and therefore of use as stockpile for future pandemic preparedness.

Methods

We conducted a multi-cohort observational study to investigate the biology and the prognostic role of interferon alpha-inducible protein 27 (IFI27) in COVID-19 patients.

Results

We show that IFI27 is expressed in the respiratory tract of COVID-19 patients and elevated IFI27 expression in the lower respiratory tract is associated with the presence of a high viral load. We further demonstrate that the systemic host response, as measured by blood IFI27 expression, is associated with COVID-19 infection. For clinical outcome prediction (e.g., respiratory failure), IFI27 expression displays a high sensitivity (0.95) and specificity (0.83), outperforming other known predictors of COVID-19 outcomes. Furthermore, IFI27 is upregulated in the blood of infected patients in response to other respiratory viruses. For example, in the pandemic H1N1/09 influenza virus infection, IFI27-like genes were highly upregulated in the blood samples of severely infected patients.

Conclusion

These data suggest that prognostic biomarkers targeting the family of IFI27 genes could potentially supplement conventional diagnostic tools in future virus pandemics, independent of whether such pandemics are caused by a coronavirus, an influenza virus or another as yet-to-be discovered respiratory virus.

Predicting diagnostic gene expression profiles associated with immune infiltration in patients with lupus nephritis

Objective

To identify potential diagnostic markers of lupus nephritis (LN) based on bioinformatics and machine learning and to explore the significance of immune cell infiltration in this pathology.

Methods

Seven LN gene expression datasets were downloaded from the GEO database, and the larger sample size was used as the training group to obtain differential genes (DEGs) between LN and healthy controls, and to perform gene function, disease ontology (DO), and gene set enrichment analyses (GSEA). Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE), were applied to identify candidate biomarkers. The diagnostic value of LN diagnostic gene biomarkers was further evaluated in the area under the ROC curve observed in the validation dataset. CIBERSORT was used to analyze 22 immune cell fractions from LN patients and to analyze their correlation with diagnostic markers.

Results

Thirty and twenty-one DEGs were screened in kidney tissue and peripheral blood, respectively. Both of which covered macrophages and interferons. The disease enrichment analysis of DEGs in kidney tissues showed that they were mainly involved in immune and renal diseases, and in peripheral blood it was mainly enriched in cardiovascular system, bone marrow, and oral cavity. The machine learning algorithm combined with external dataset validation revealed that C1QA(AUC = 0.741), C1QB(AUC = 0.758), MX1(AUC = 0.865), RORC(AUC = 0.911), CD177(AUC = 0.855), DEFA4(AUC= 0.843)and HERC5(AUC = 0.880) had high diagnostic value and could be used as diagnostic biomarkers of LN. Compared to controls, pathways such as cell adhesion molecule cam, and systemic lupus erythematosus were activated in kidney tissues; cell cycle, cytoplasmic DNA sensing pathways, NOD-like receptor signaling pathways, proteasome, and RIG-1-like receptors were activated in peripheral blood. Immune cell infiltration analysis showed that diagnostic markers in kidney tissue were associated with T cells CD8 and Dendritic cells resting, and in blood were associated with T cells CD4 memory resting, suggesting that CD4 T cells, CD8 T cells and dendritic cells are closely related to the development and progression of LN.

Conclusion

C1QA, C1QB, MX1, RORC, CD177, DEFA4 and HERC5 could be used as new candidate molecular markers for LN. It may provide new insights into the diagnosis and molecular treatment of LN in the future.

A cluster of type II interferon-regulated genes associates with disease activity in patients with systemic lupus erythematosus

Upregulation of interferon-regulated genes (IRGs), denoted IFN signature, in peripheral blood has been used as an indirect measure of IFN pathway activation in patients with systemic lupus erythematosus (SLE). However, it has not been determined, which IFN signatures that optimally reflect clinical disease activity. In this study, we determined an IFN signature based on the expression of 128 IRGs in whole blood from 34 SLE patients in a cross-sectional (CS) study, 11 with active lupus nephritis followed longitudinally (LS) and 15 healthy controls. Blood samples were collected in PAXgene tubes and RNA was extracted and purified using a PAXgene blood RNA kit (Qiagen). Gene expression was measured using the NanoString nCounter Gene Expression platform. The CS SLE patients with higher disease activity displayed thrice as many upregulated IRGs (n = 46) as the rest. These IRGs clustered in three groups, consisting of IRGs known to be predominantly stimulated by type I (gene cluster K1) and type II (gene clusters K2 and 3) IFNs. SLEDAI-2K scores associated with the K2 and K3 gene scores (β = 0.372 and β = 0.419, both p < 0.015) but not with K1. In the longitudinal study, the mean SLEDAI-2K score decreased after an average follow-up of 360 days (β = -2.08, P = 5.09 × 10^-12). The mean K1, K2 and K3 gene scores did not change over time, however longitudinal changes in SLEDAI-2K and K3 scores were associated (β = 0.814, p = 0.007). This study validates the presence of type I IRG subsets that do not associate with disease activity in SLE patients. The novel finding in this study is the association between a type II IRG subset and disease activity. Both findings may have significant implications for choosing IRGs defining clinically relevant IFN signatures.

Identification of key interferon-stimulated genes for indicating the condition of patients with systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease with highly heterogeneous clinical symptoms and severity. There is complex pathogenesis of SLE, one of which is IFNs overproduction and downstream IFN-stimulated genes (ISGs) upregulation. Identifying the key ISGs differentially expressed in peripheral blood mononuclear cells (PBMCs) of patients with SLE and healthy people could help to further understand the role of the IFN pathway in SLE and discover potential diagnostic biomarkers.

The differentially expressed ISGs (DEISG) in PBMCs of SLE patients and healthy persons were screened from two datasets of the Gene Expression Omnibus (GEO) database. A total of 67 DEISGs, including 6 long noncoding RNAs (lncRNAs) and 61 messenger RNAs (mRNAs) were identified by the “DESeq2” R package. According to Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, those DEISGs were mainly concentrated in the response to virus and immune system processes. Protein-protein interaction (PPI) network showed that most of these DEISGs could interact strongly with each other. Then, IFIT1, RSAD2, IFIT3, USP18, ISG15, OASL, MX1, OAS2, OAS3, and IFI44 were considered to be hub ISGs in SLE by “MCODE” and “Cytohubba” plugins of Cytoscape, Moreover, the results of expression correlation suggested that 3 lncRNAs (NRIR, FAM225A, and LY6E-DT) were closely related to the IFN pathway.

The lncRNA NRIR and mRNAs (RSAD2, USP18, IFI44, and ISG15) were selected as candidate ISGs for verification. RT-qPCR results showed that PBMCs from SLE patients had substantially higher expression levels of 5 ISGs compared to healthy controls (HCs). Additionally, statistical analyses revealed that the expression levels of these ISGs were strongly associated to various clinical symptoms, including thrombocytopenia and facial erythema, as well as laboratory indications, including the white blood cell (WBC) count and levels of autoantibodies. The Receiver Operating Characteristic (ROC) curve demonstrated that the IFI44, USP18, RSAD2, and IFN score had good diagnostic capabilities of SLE.

According to our study, SLE was associated with ISGs including NRIR, RSAD2, USP18, IFI44, and ISG15, which may contribute to the future diagnosis and new personalized targeted therapies.

Lupus nephritis correlates with B cell interferon-β, anti-Smith, and anti-DNA: a retrospective study

Background

In systemic lupus erythematosus (SLE), detection of interferon-β (IFNβ) in B cells was found to be most prominent in patients with high anti-Smith (Sm) and renal disease, but a mechanistic connection was not clear. The objective of the present study is to determine the association of IFNβ in peripheral blood naïve B cells with the histopathological features of lupus nephritis (LN).

Methods

The percentage of IFNβ⁺ cells in IgD⁺CD27⁻ naïve CD19⁺ B cells (B cell IFNβ) among peripheral blood mononuclear cells (PBMCs) from 80 SLE patients were analyzed using flow cytometry. Serological and clinical data were collected. The correlations of B cell IFNβ with LN classification and with histopathological findings (light, electron, and immunofluorescence [IF] microscopic analyses for deposition of IgM, IgG, IgA, C1q, and C3) were determined in 23 available biopsy specimens.

Results

B cell IFNβ is positively associated with anti-Sm (p = 0.001), anti-DNA (p = 0.013), and LN (p < 0.001) but was negatively associated with oral/nasal ulcer (p = 0.003) and photosensitivity (p = 0.045). B cell IFNβ positively correlated with immune complex (IC) deposit in the glomerular basement membrane (GBM) (p = 0.002) but not in the mesangial (p = 0.107) or tubular region (p = 0.313). Patients with high B cell IFNβ had statistically increased development of the proliferative LN (Classes III, IV and/or V), compared to patients with low B cell IFNβ (p < 0.0001). Histopathological features positively associated with increased B cell IFNβ included active glomerular lesions as determined by fibrocellular crescents (p = 0.023), chronic glomerular lesions indicated by segmental sclerosis (p = 0.033), and a membranous pattern of renal damage indicated by spike/holes (p = 0.015).

Conclusion

B cell IFNβ correlates with history of severe LN, glomerular basement membrane (GBM) IC deposition, and anatomical features of both active and chronic glomerular lesions.

Anti-RNP antibodies are associated with the interferon gene signature but not decreased complement levels in SLE

OBJECTIVES

The goals of these studies were to elucidate the inter-relationships of specific anti-nuclear antibody (ANA), complement, and the interferon gene signature (IGS) in the pathogenesis of systemic lupus erythematosus (SLE).

METHODS

Data from the Illuminate trials were analysed for antibodies to dsDNA as well as RNA-binding proteins (RBP), levels of C3, C4 and various IGS. Statistical hypothesis testing, linear regression analyses and classification and regression trees analysis were employed to assess relationships between the laboratory features of SLE.

RESULTS

Inter-relationships of ANAs, complement and the IGS differed between patients of African Ancestry (AA) and European Ancestry (EA); anti-RNP and multiple autoantibodies were more common in AA patients and, although both related to the presence of the IGS, relationships between autoantibodies and complement differed. Whereas, anti-dsDNA had an inverse relationship to C3 and C4, levels of anti-RNP were not related to these markers. The IGS was only correlated with anti-dsDNA in EA SLE and complement was more correlated to the IGS in AA SLE. Finally, autoantibodies occurred in the presence and absence of the IGS, whereas the IGS was infrequent in anti-dsDNA/anti-RBP-negative SLE patients.

CONCLUSION

There is a complex relationship between autoantibodies and the IGS, with anti-RNP associated in AA and both anti-dsDNA and RNP associated in EA. Moreover, there was a difference in the relationship between anti-dsDNA, but not anti-RBP, with complement levels. The lack of a relationship of anti-RNP with C3 and C4 suggests that anti-RNP immune complexes (ICs) may drive the IGS without complement fixation, whereas anti-dsDNA ICs involve complement consumption.

Small RNAs encoded by human endogenous retrovirus K overexpressed in PBMCs may contribute to the diagnosis and evaluation of systemic lupus erythematosus as novel biomarkers

This study aimed to identify the genes and small RNAs (sRNAs) expressed by the human endogenous retrovirus K (HERV-K) HML2 and their associations with the immune process of systemic lupus erythematosus (SLE). RNA-Seq data including 99 SLE patients and 18 controls (GSE72420) was obtained from the Gene Expression Omnibus. Differentially expressed genes (DEGs) as well as HML2-DEGs between SLE patients and normal controls were identified. Five HML2-DEGs involved in immune-regulating function were identified using weighted gene co-expression network analysis (WGCNA). The associations between these genes and the proportions of immune cells were determined by CIBERSORT. Ten candidate HML2-encoded sRNAs were identified based on specific criteria, and three of them were further validated in SLE patients by qRT-PCR. The diagnostic values of these three sRNAs were evaluated in SLE and lupus nephritis (LN). This study suggested that HML2 genes and their encoded sRNAs might be involved in the immune regulation and progress of SLE. These potential sRNAs might function as regulatory molecules and diagnostic biomarkers of SLE and LN.