Comparison of Surrogate Markers of the Type I Interferon Response and Their Ability to Mirror Disease Activity in Systemic Lupus Erythematosus

Uncoupling interferons and the interferon signature explains clinical and transcriptional subsets in SLE

Systemic lupus erythematosus (SLE) displays a hallmark interferon (IFN) signature. Yet, clinical trials targeting type I IFN (IFN-I) have shown variable efficacy, and blocking IFN-II failed to treat SLE. Here, we show that IFN type levels in SLE vary significantly across clinical and transcriptional endotypes. Whereas skin involvement correlated with IFN-I alone, systemic features like nephritis associated with co-elevation of IFN-I, IFN-II, and IFN-III, indicating additive IFN effects in severe SLE. Notably, while high IFN-II/-III levels without IFN-I had a limited effect on disease activity, IFN-II was linked to IFN-I-independent transcriptional profiles (e.g., OXPHOS and CD8+GZMH+ cells), and IFN-III enhanced IFN-induced gene expression when co-elevated with IFN-I. Moreover, dysregulated IFNs do not explain the IFN signature in 64% of patients or clinical manifestations including cytopenia, serositis, and anti-phospholipid syndrome, implying IFN-independent endotypes in SLE. This study sheds light on mechanisms underlying SLE heterogeneity and the variable response to IFN-targeted therapies in clinical trials.

Deregulation in adult IgA vasculitis skin as the basis for the discovery of novel serum biomarkers

INTRODUCTION

Immunoglobulin A vasculitis (IgAV) in adults has a variable disease course, with patients often developing gastrointestinal and renal involvement and thus contributing to higher mortality. Due to understudied molecular mechanisms in IgAV currently used biomarkers for IgAV visceral involvement are largely lacking. Our aim was to search for potential serum biomarkers based on the skin transcriptomic signature.

METHODS

RNA sequencing analysis was conducted on skin biopsies collected from 6 treatment-naïve patients (3 skin only and 3 renal involvement) and 3 healthy controls (HC) to get insight into deregulated processes at the transcriptomic level. 15 analytes were selected and measured based on the transcriptome analysis (adiponectin, lipopolysaccharide binding protein (LBP), matrix metalloproteinase-1 (MMP1), C-C motif chemokine ligand (CCL) 19, kallikrein-5, CCL3, leptin, C-X-C motif chemokine ligand (CXCL) 5, osteopontin, interleukin (IL)-15, CXCL10, angiopoietin-like 4 (ANGPTL4), SERPIN A12/vaspin, IL-18 and fatty acid-binding protein 4 (FABP4)) in sera of 59 IgAV and 22 HC. Machine learning was used to assess the ability of the analytes to predict IgAV and its organ involvement.

RESULTS

Based on the gene expression levels in the skin, we were able to differentiate between IgAV patients and HC using principal component analysis (PCA) and a sample-to-sample distance matrix. Differential expression analysis revealed 49 differentially expressed genes (DEGs) in all IgAV patient's vs. HC. Patients with renal involvement had more DEGs than patients with skin involvement only (507 vs. 46 DEGs) as compared to HC, suggesting different skin signatures. Major dysregulated processes in patients with renal involvement were lipid metabolism, acute inflammatory response, and extracellular matrix (ECM)-related processes. 11 of 15 analytes selected based on affected processes in IgAV skin (osteopontin, LBP, ANGPTL4, IL-15, FABP4, CCL19, kallikrein-5, CCL3, leptin, IL-18 and MMP1) were significantly higher (p-adj < 0.05) in IgAV serum as compared to HC. Prediction models utilizing measured analytes showed high potential for predicting adult IgAV.

CONCLUSION

Skin transcriptomic data revealed deregulations in lipid metabolism and acute inflammatory response, reflected also in serum analyte measurements. LBP, among others, could serve as a potential biomarker of renal complications, while adiponectin and CXCL10 could indicate gastrointestinal involvement.

Serum and urine interferon-inducible protein 10, galectin-9, and SIGLEC-1 as biomarkers of disease activity in systemic lupus erythematosus

Background/aim

In this prospective study, we aimed to investigate the association of serum (s) and urine (u) IP-10, galectin-9, and SIGLEC-1 with disease activity in patients with systemic lupus erythematosus (SLE).

Materials and methods

Sixty-three patients with active SLE (31 renal, 32 extrarenal) were included. Thirty patients with inactive SLE (15 renal, 15 extrarenal), 17 with renal active AAV, and 32 healthy volunteers were selected as control groups. Serum and urine IP-10, galectin-9, and SIGLEC-1 were tested using ELISA.

Results

Levels of sIP-10 (p = 0.046), uIP-10 (p < 0.001), sGalectin-9 (p = 0.03), and uSIGLEC-1 (p = 0.006) were significantly higher in active SLE group compared to the inactive SLE; however, no differences were detected in the comparison of uGalectin-9 (p = 0.18) and sSIGLEC-1 (p = 0.69) between two groups. None of the biomarkers discriminated patients with active renal SLE from active extrarenal SLE. ROC analyses revealed an AUC of 0.63 (0.52-0.73) for sIP-10, 0.78 (0.68-0.86) for uIP-10, 0.64 (0.53-0.74) for sGalectin-9, and 0.68 (0.57-0.77) for uSIGLEC-1 in discriminating disease activity in SLE, which did not outperform C3 (0.75, 0.64-0.84) and C4 (0.72, 0.61-0.82). sIP-10 (p = 0.001), uIP-10 (p = 0.042), and uGalectin-9 (p = 0.009) were significantly increased in patients with active renal SLE compared to active renal AAV. sGalectin-9 (p < 0.001) and sIP-10 levels (p = 0.06) were decreased after 8 (5-22.5) months of treatment.

Conclusion

sIP-10, uIP-10, sGalectin-9, and uSIGLEC-1 reflect global disease activity in SLE but do not outperform C3 and C4. sIP-10 and uIP-10 may be specific for active SLE compared to active AAV. sIP-10 and sGalectin-9 might be valuable in monitoring response after treatment.

Serum level of galectin-9 as a potential biomarker for high risk of malignancy in dermatomyositis

OBJECTIVES

Galectin-9, as immune checkpoint protein, plays a role in regulating autoimmunity and tumour immunity. Therefore, we explored the pathophysiological link between galectin-9 and malignancy in cancer-related DM (CRDM).

METHODS

Serum galectin-9 were quantified via enzyme-linked immunosorbent assay, and its association with serological indices was evaluated using Spearman analysis. Receiver operating characteristic (ROC) analysis was utilized to determine the cut-off value of galectin-9.

RESULTS

Serum levels of galectin-9 were significantly higher in DM patients [23.38 (13.85-32.57) ng/ml] than those in healthy controls (HCs) [6.81 (5.42-7.89) ng/ml, P < 0.0001], and were positively correlated with the cutaneous dermatomyositis disease area severity index activity (CDASI-A) scores (rs=0.3065, P = 0.0172). DM patients with new-onset and untreated cancer (new-CRDM) [31.58 (23.85-38.84) ng/ml] had higher levels of galectin-9 than those with stable and treated cancer (stable-CRDM) [17.49 (10.23-27.91) ng/ml, P = 0.0288], non-cancer-related DM (non-CRDM) [21.05 (11.97-28.02) ng/ml, P = 0.0258], and tumour patients without DM [7.46 (4.90-8.51) ng/ml, P < 0.0001]. Serum galectin-9 levels significantly decreased [27.79 (17.04-41.43) ng/ml vs 13.88 (5.15-20.37) ng/ml, P = 0.002] after anti-cancer treatment in CRDM patients. The combination of serum galectin-9 and anti-transcriptional intermediary factor 1-γ (anti-TIF1-γ) antibody (AUC = 0.889, 95% CI 0.803-0.977) showed the highest predictive value for the presence of cancer in DM.

CONCLUSION

Increased galectin-9 levels were related to tumor progression in CRDM, and galectin-9 was downregulated upon cancer treatment. Monitoring serum galectin-9 levels and anti-TIF1-γ antibodies might be an attractive strategy to achieve tumour diagnosis and predict CRDM outcome.

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.

Combined proteomics and single cell RNA-sequencing analysis to identify biomarkers of disease diagnosis and disease exacerbation for systemic lupus erythematosus

Introduction

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease for which there is no cure. Effective diagnosis and precise assessment of disease exacerbation remains a major challenge.

Methods

We performed peripheral blood mononuclear cell (PBMC) proteomics of a discovery cohort, including patients with active SLE and inactive SLE, patients with rheumatoid arthritis (RA), and healthy controls (HC). Then, we performed a machine learning pipeline to identify biomarker combinations. The biomarker combinations were further validated using enzyme-linked immunosorbent assays (ELISAs) in another cohort. Single-cell RNA sequencing (scRNA-seq) data from active SLE, inactive SLE, and HC PBMC samples further elucidated the potential immune cellular sources of each of these PBMC biomarkers.

Results

Screening of the PBMC proteome identified 1023, 168, and 124 proteins that were significantly different between SLE vs. HC, SLE vs. RA, and active SLE vs. inactive SLE, respectively. The machine learning pipeline identified two biomarker combinations that accurately distinguished patients with SLE from controls and discriminated between active and inactive SLE. The validated results of ELISAs for two biomarker combinations were in line with the discovery cohort results. Among them, the six-protein combination (IFIT3, MX1, TOMM40, STAT1, STAT2, and OAS3) exhibited good performance for SLE disease diagnosis, with AUC of 0.723 and 0.815 for distinguishing SLE from HC and RA, respectively. Nine-protein combination (PHACTR2, GOT2, L-selectin, CMC4, MAP2K1, CMPK2, ECPAS, SRA1, and STAT2) showed a robust performance in assessing disease exacerbation (AUC=0.990). Further, the potential immune cellular sources of nine PBMC biomarkers, which had the consistent changes with the proteomics data, were elucidated by PBMC scRNAseq.

Discussion

Unbiased proteomic quantification and experimental validation of PBMC samples from two cohorts of patients with SLE were identified as biomarker combinations for diagnosis and activity monitoring. Furthermore, the immune cell subtype origin of the biomarkers in the transcript expression level was determined using PBMC scRNAseq. These findings present valuable PBMC biomarkers associated with SLE and may reveal potential therapeutic targets.

Identification and analysis of the predictive urinary exosomal miR-195-5p in lupus nephritis based on renal miRNA-mRNA co-expression network

OBJECTIVE

Lupus nephritis (LN) is the main complication of systemic lupus erythematosus (SLE), causing huge financial burden and poor quality of life. Due to the low compliance of renal biopsy, we aim to find a non-invasive biomarker of LN to optimize its predictive, preventive, and personalized medical service or management.

METHOD

Herein, we provided a bioinformatic screen combined clinical validation strategy for rapidly mining exosomal miRNAs for LN diagnosis and management. We screened out differentially expressed miRNAs (DEMs) and differentially expressed mRNAs (DEGs) in LN database and performed a miRNA-mRNA integrated analysis to select out reliable changed miRNAs in LN tissues by using R and Cytoscape. Urinary exosomes were collected by ultracentrifugation and analyzed by nano-tracking analysis and western blotting. Detection of aquaporin-2 showed the tubular source of urinary exosomes. Urinary exosomal miRNAs were detected by RT-qPCR and the target of miR-195-5p was verified by using bioinformatic, dual-luciferase, and western blotting.

RESULT

15 miRNAs and their 60 target mRNAs were contained in miRNA-mRNA integrated map. Bioinformatic analysis showed these miRNAs were involved in various cellular biological process. Exosomal miR-195-5p, miR-25-3p, miR-429, and miR-218-5p were verified in a small clinical group (n = 47). Urinary exosomal miR-195-5p, miR-25-3p, and miR-429 were downregulated in patients and miR-195-5p could recognize LN patients from SLE with good sensitivity and specificity, showing good potential in LN disease monitoring and diagnosis.

CONCLUSION

We analyzed and obtained a series of differential miRNAs in LN kidney tissues and suggested that urinary exosomal miR-195-5p could serve as a novel biomarker in LN. Further, miR-195-5p-CXCL10 axis could be a therapeutic target of LN.

MDA5 signaling induces type 1 IFN- and IL-1-dependent lung vascular permeability which protects mice from opportunistic fungal infection

Lungs balance threat from primary viral infection, secondary infection, and inflammatory damage. Severe pulmonary inflammation induces vascular permeability, edema, and organ dysfunction. We previously demonstrated that poly(I:C) (pICLC) induced type 1 interferon (t1IFN) protected mice from Cryptococcus gattii (Cg) via local iron restriction. Here we show pICLC increased serum protein and intravenously injected FITC-dextran in the lung airspace suggesting pICLC induces vascular permeability. Interestingly, pICLC induced a pro-inflammatory signature with significant expression of IL-1 and IL-6 which depended on MDA5 and t1IFN. Vascular permeability depended on MDA5, t1IFN, IL-1, and IL-6. T1IFN also induced MDA5 and other MDA5 signaling components suggesting that positive feedback contributes to t1IFN dependent expression of the pro-inflammatory signature. Vascular permeability, induced by pICLC or another compound, inhibited Cg by limiting iron. These data suggest that pICLC induces t1IFN which potentiates pICLC-MDA5 signaling increasing IL-1 and IL-6 resulting in leakage of antimicrobial serum factors into lung airspace. Thus, induced vascular permeability may act as an innate defense mechanism against opportunistic fungal infection, such as cryptococcosis, and may be exploited as a host-directed therapeutic target.

Affected Microcirculation and Vascular Hemodynamics in Takayasu Arteritis

Introduction: Takayasu arteritis (TAK) is a rare inflammatory disease affecting aorta and its major branches. Ultrasound (US) can detect inflammatory features in the arterial wall, but less is known regarding skin microcirculation and vascular hemodynamics. The aim was to study if assessment of these variables could add valuable information regarding vascular affection in TAK.

Methods: 17 patients diagnosed with TAK and 17 age- and sex-matched healthy controls were included. Microcirculatory peak oxygen saturation (OxyP) in the skin after induced ischemia was evaluated with laser Doppler flowmetry/diffuse reflectance spectroscopy. Cerebrovascular reserve capacity (CVR) in the brain was assessed with transcranial Doppler (TCD). Pulse waves were recorded in the radial artery by the aid of applanation tonometry, for calculation of central augmentation index (AIx75). Intima-media thickness (IMT) and stenosis/occlusions were evaluated using US in carotid and central arteries.

Results: Reduced OxyP (79 ± 8% vs. 87 ± 4%, p &lt; 0.001) was seen in patients with TAK regardless of significant arterial stenosis/occlusion or not. Increased AIx75 (22.3 ± 13.6 vs. 9.2 ± 16.3, p = 0.01) was seen in TAK patients without significant stenosis/occlusions. No differences were found in CVR, regardless of proximal stenosis. However, signs of a more high-resistance flow profile were seen in arteria cerebri media.

Conclusion: Regardless of arterial stenosis or not, impaired microcirculation of the skin and preserved CVR in the brain were found in subjects with TAK. Signs of increased arterial stiffness in the brain and central arteries were observed. The value of these findings for prediction of future cardiovascular events needs to be clarified in further studies.