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

Predicting autoimmune diseases: A comprehensive review of classic biomarkers and advances in artificial intelligence

Autoimmune diseases comprise a spectrum of disorders characterized by the dysregulation of immune tolerance, resulting in tissue or organ damage and inflammation. Their prevalence has been on the rise, significantly impacting patients' quality of life and escalating healthcare costs. Consequently, the prediction of autoimmune diseases has recently garnered substantial interest among researchers. Despite their wide heterogeneity, many autoimmune diseases exhibit a consistent pattern of paraclinical findings that hold predictive value. From serum biomarkers to various machine learning approaches, the array of available methods has been continuously expanding. The emergence of artificial intelligence (AI) presents an exciting new range of possibilities, with notable advancements already underway. The ultimate objective should revolve around disease prevention across all levels. This review provides a comprehensive summary of the most recent data pertaining to the prediction of diverse autoimmune diseases and encompasses both traditional biomarkers and the latest innovations in AI.

DNA methylation of IFI44L as a potential blood biomarker for childhood-onset systemic lupus erythematosus

BACKGROUND

IFN-induced protein 44-like (IFI44L) promoter methylation has been demonstrated to serve as an effective blood diagnostic biomarker for adult-onset SLE. However, its utility as a diagnostic marker for childhood-onset SLE (cSLE) remains to be verified.

METHODS

Initially, we conducted a differential analysis of gene methylation and mRNA expression patterns in cSLE whole blood samples obtained from the public GEO database to determine IFI44L gene expression and assess the methylation status at its CpG sites. Subsequently, we collected clinical whole blood samples from 49 cSLE patients and 12 healthy children, employing an HRM-qPCR-based IFI44L methylation detection technique to evaluate its diagnostic efficacy in pediatric clinical practice.

RESULTS

A total of 26 hypomethylated, highly expressed genes in cSLE were identified by intersecting differentially expressed genes (DEGs) and differentially methylation genes (DMGs). GO enrichment analysis for these 26 genes indicated a robust association with type I IFN. Among the overlapping genes, IFI44L exhibited the most pronounced differential expression and methylation. In subsequent clinical validation experiments, IFI44L methylation was confirmed as an effective blood-based diagnostic biomarker for cSLE, achieving an AUC of 0.867, a sensitivity of 0.753, and a specificity of 1.000.

CONCLUSIONS

IFI44L methylation is a promising blood biomarker for cSLE.

IMPACT

IFI44L promoter methylation was reported to serve as a highly sensitive and specific diagnostic marker for adult-onset SLE. However, the diagnostic efficacy of IFI44L in childhood-onset SLE (cSLE) still remains to be confirmed. In this study, we utilized bioinformatics analysis and conducted clinical experiments to demonstrate that IFI44L methylation can also serve as a promising blood biomarker for cSLE. The findings of this study can facilitate the diagnosis of cSLE and broaden our understanding of its molecular mechanisms, with a particular focus on those related to type I interferons.

Immune cells in skin inflammation, wound healing, and skin cancer

Given the self-evident importance of cutaneous immunity in the maintenance of body-surface homeostasis, disturbance of the steady-state skin is inextricably intertwined with dysfunction in cutaneous immunity. It is often overlooked by people that skin, well-known as a solid physical barrier, is also a strong immunological barrier, considering the abundant presence of immune cells including lymphocytes, granulocytes, dendritic cells, and macrophages. What's more, humoral immune components including cytokines, immunoglobulins, and antimicrobial peptides are also rich in the skin. This review centers on skin inflammation (acute and chronic, infection and aseptic inflammation), wound healing, and skin cancer to elucidate the elaborate network of immune cells in skin diseases.

Critical gene signature and immunological characterization in peripheral vascular atherosclerosis: novel insights from mendelian randomization and transcriptomics

Introduction

Peripheral vascular atherosclerosis (PVA) is a chronic inflammatory disease characterized by lipid accumulation in blood vessel walls, leading to vessel narrowing and inadequate blood supply. However, the molecular mechanisms underlying PVA remain poorly understood. In this study, we employed a combination of Mendelian randomization (MR) analysis and integrated transcriptomics to identify the critical gene signature associated with PVA.

Methods

This study utilized three public datasets (GSE43292, GSE100927 and GSE28829) related to peripheral vascular atherosclerosis obtained from the Gene Expression Omnibus database. Instrumental variables (IVs) were identified through expression quantitative trait loci (eQTL) analysis, and two-sample MR analysis was performed using publicly available summary statistics. Disease critical genes were identified based on odds ratios and intersected with differentially expressed genes in the disease dataset. GSE28829 dataset was used to validate the screened disease critical genes. Functional enrichment analysis, GSEA analysis, and immune cell infiltration analysis were performed to further characterize the role of these genes in peripheral vascular atherosclerosis.

Results

A total of 26,152 gene-related SNPs were identified as IVs, and 242 disease-associated genes were identified through MR analysis. Ten disease critical genes (ARHGAP25, HCLS1, HVCN1, RBM47, LILRB1, PLAU, IFI44L, IL1B, IFI6, and CFL2) were significantly associated with peripheral vascular atherosclerosis. Functional enrichment analysis using KEGG pathways revealed enrichment in the NF-kappa B signaling pathway and osteoclast differentiation. Gene set enrichment analysis further demonstrated functional enrichment of these genes in processes related to vascular functions and immune system activation. Additionally, immune cell infiltration analysis showed differential ratios of B cells and mast cells between the disease and control groups. The correlations analysis highlights the intricate interplay between disease critical genes and immune cells associated with PVA.

Conclusion

In conclusion, this study provides new insights into the molecular mechanisms underlying PVA by identifying ten disease critical genes associated with the disease. These findings, supported by differential expression, functional enrichment, and immune system involvement, emphasize the role of these genes in vascular function and immune cell interactions in the context of PVA. These findings contribute to a better understanding of PVA pathogenesis and offer potential targets for further mechanistic exploration and therapeutic interventions.

RNA N6-methyladenosine methylation and skin diseases

Skin diseases are global health issues caused by multiple pathogenic factors, in which epigenetics plays an invaluable role. Post-transcriptional RNA modifications are important epigenetic mechanism that regulate gene expression at the genome-wide level. N6-methyladenosine (m6A) is the most prevalent modification that occurs in the messenger RNAs (mRNA) of most eukaryotes, which is installed by methyltransferases called "writers", removed by demethylases called "erasers", and recognised by RNA-binding proteins called "readers". To date, m6A is emerging to play essential part in both physiological processes and pathological progression, including skin diseases. However, a systematic summary of m6A in skin disease has not yet been reported. This review starts by illustrating each m6A-related modifier specifically and their roles in RNA processing, and then focus on the existing research advances of m6A in immune homeostasis and skin diseases.

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.

DNA methylation alterations in systemic lupus erythematosus: A systematic review of case-control studies

BACKGROUND

Traditionally, the diagnosis and monitoring of disease activity in systemic lupus erythematosus (SLE) are contingent upon clinical manifestations and serological markers. However, researchers are struggling to find biomarkers with higher sensitivity and specificity. DNA methylation has been the most studied epigenetic feature in SLE. So, in this study, we performed a systematic review of studies about DNA methylation alterations in SLE patients compared to healthy controls.

METHODS

By searching PubMed, Scopus, and Google Scholar up to July 2022, all case-control studies in which DNA methylation of specific genes was assessed by a non-high-throughput technique and passed the quality of bias assessment were included.

RESULTS

In total, 44 eligible studies underwent a data extraction process. In all, 3471 SLE patients and 1028 healthy individuals were included. Among the studies that reported the patients' gender (n = 2853), 89.41% were female and 10.59% were male. Forty studies have been conducted on adult patients. The number of works on fractionated and unfractionated blood cells was almost equal. In this regard, 22 studies were conducted on whole blood or peripheral blood mononuclear cells and two studies on unfractionated white blood cells. Sorted blood cells were biological sources in 20 studies. The most investigated gene was IFI44L. Sensitivity, specificity, and diagnostic power of methylation levels were only reported for IFI44L in five studies. The most employed methylation profiling method was bisulfite sequencing polymerase chain reaction. The correlation between methylation patterns and clinical parameters was explored in 22 studies, which of them 16 publications displayed a remarkable association between DNA methylation status and clinical indices.

CONCLUSIONS

The methylation status of some genes especially IFI44L, FOXP3, and MX1 has been suggested as promising SLE biomarkers. However, given the conflicting findings between studies because of potential confounders such as different sample types, methylation profiling methods, and ethnicity as well as shared DNA methylation patterns of SLE and other autoimmune diseases, DNA methylation biomarkers are currently not reliable diagnostic biomarkers and do not represent surrogate markers of SLE disease activity. Future investigations on a larger scale with the discarding of limitations of previous studies would probably lead to a consensus.

IFI44L as a novel epigenetic silencing tumor suppressor promotes apoptosis through JAK/STAT1 pathway during lung carcinogenesis

Numerous evidence showed that the occurrence and development of lung cancer is closely related to environmental pollution. Therefore, new environmental response predictive markers are urgently needed for early diagnosis and screening of lung cancer. Interferon-induced protein 44-like (IFI44L) has been shown to be related in a variety of tumors, but its function and mechanism during lung carcinogenesis still have remained largely unknown. In this study, gene expression and methylation status were analyzed through online tools and malignant transformation models. Differentially expressed cell models and xenograft tumor models were established and used to clarify the gene function. RT-qPCR, western blotting, immunohistochemistry, and co-immunoprecipitation (Co-IP) were used to explore the mechanism. Results showed that IFI44L was dramatically downexpressed during lung carcinogenesis, and its low expression may be attributed to DNA methylation. Overexpression of IFI44L obviously inhibited cell growth and promoted apoptosis. After knockdown of IFI44L expression, the proliferation ability was remarkably increased and the apoptosis was significantly reduced. Functional enrichment showed that IFI44L was involved in apoptosis and JAK/STAT1 signaling pathway, and was highly correlated with downstream molecules. After overexpression of IFI44L, the expression of P-STAT1 and downstream molecules XAF1, OAS1, OAS2 and OAS3 were significantly increased. After knockdown of STAT1 expression, the pro-apoptotic effect of IFI44L was reduced. Co-IP results showed that IFI44L had protein interaction with STAT1. Results proved that IFI44L promoted STAT1 phosphorylation and activated the JAK/STAT1 signaling pathway by directly binding to STAT1 protein, thereby leading to cell apoptosis. Our study revealed that IFI44L promotes cell apoptosis and exerts tumor suppressors by activating the JAK/STAT1 signaling pathway. It further suggests that IFI44L has clinical therapeutic potential and may be a promising biomarker during lung carcinogenesis.

Identification of potential biomarkers for systemic lupus erythematosus by integrated analysis of gene expression and methylation data

INTRODUCTION

Systemic lupus erythematosus (SLE) is a heterogeneous and chronic autoimmune disease. Aberrant DNA methylation occurs during various processes of SLE development regulating the mRNA expression of interrelated genes. This study aims to screen potential DNA methylation markers for SLE.

METHODS

Gene expression and methylation datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between SLE patients and healthy controls were screened using the limma R package, and differentially methylated positions (DMPs) and regions (DMRs) were identified using dmpfinder and bumphunter (minfi). Additionally, the DNA methylation markers to distinguish SLE patients from healthy controls were explored through receiver operating characteristic (ROC) curves and logistic regression analyses. Finally, we validated the results of the bioinformatic analysis by pyrosequencing.

RESULTS

In total, 91 DEGs, 90,092 DMPs, 15 DMRs, and 13 DMR-associated genes were identified. Through the integrative analysis of DEG- and DMR-associated genes, we identified five type I interferon (IFN)-related genes as key epigenetic-driven genes in SLE. GO enrichment analysis showed that the five SLE-associated epigenetic-driven genes were mainly enriched in the type I IFN signaling pathway involved in immune response and defense response to virus. Moreover, we identified two SLE-specific DNA methylation markers, three SLE without lupus nephritis (SLE-LN^-)-specific DNA methylation markers, and two SLE with lupus nephritis (SLE-LN⁺)-specific DNA methylation markers by stepwise logistic regression.

CONCLUSIONS

Overall, our study demonstrates potential DNA methylation markers of SLE, SLE-LN^-, and SLE-LN⁺, which may help the diagnosis, boost the development of new epigenetic therapy, and contribute to individualized treatment. Key Points • This study identified five type I IFN-related genes as key epigenetic-driven genes in SLE, which support the importance of the type I IFN pathway in the pathogenesis of SLE • We identified novel DNA methylation biomarkers in SLE, SLE-LN-, and SLE-LN+ by a comprehensive analysis of bioinformatics methods and executed experimental validation, and binary logistic regression analysis showed that they have excellent potential • These results may provide new insights into the biological mechanisms of SLE, and identify reliable biomarkers for SLE, SLE-LN-, and SLE-LN+, which may contribute to diagnosis and individualized treatment.

An update on epigenetic regulation in autoimmune diseases

Autoimmune diseases (AIDs) generally manifest as chronic immune disorders characterized by significant heterogeneity and complex symptoms. The discordant incidence of AIDs between monozygotic twins guided people to attach importance to environmental factors. Epigenetics is one of the major ways to be influenced, some of them can even occur years before clinical diagnosis. With the advent of high-throughput omics times, the mysterious veil of epigenetic modification in AIDs has been gradually unraveled, and some progress has been made in utilizing it as indicators of diagnosis and disease activity. For example, the hypomethylated IFI44L promoter in diagnosing systematic lupus erythematosus (SLE). More recently, newly identified noncoding RNAs (ncRNAs), including long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs), are also believed to be involved in the etiology of AIDs while the initial factor behind those epigenetic alterations can be diverse from metabolism to microbiota. Update and comprehensive insights into epigenetics in AIDs can help us understand the pathogenesis and further orchestrate it to benefit patients in the future. Therefore, we reviewed the latest epigenetic findings in SLE, rheumatoid arthritis (RA), Type 1 diabetes (T1D), systemic sclerosis (SSc) primarily from cellular levels.

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

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

Comprehensive Analysis of Immune Implication and Prognostic Value of IFI44L in Non-Small Cell Lung Cancer

Interferon-induced protein 44-like (IFI44L), a type I interferon-stimulated gene (ISG), has been reported to be involved in innate immune processes and to act as a tumor suppressor in several cancers. However, its immune implication on lung cancer remains unclear. Here, we systemically analyzed the immune association of IFI44L with multiple tumor-infiltrating immune cells (TIICs) and immunomodulators through bioinformatics methods in The Cancer Genome Atlas (TCGA) lung cancer cohorts. Then, the IFI44L-related immunomodulators were selected to construct the prognostic signatures in the lung adenocarcinoma (LUAD) cohort and the lung squamous cell carcinoma (LUSC) cohort, respectively. Concordance index and time-dependent receiver operating characteristics (ROC) curves were applied to evaluate the prognostic signatures. GSE72094 and GSE50081 were used to validate the TCGA-LUAD signature and TCGA-LUSC signature, respectively. A nomogram was established by risk score and clinical features in the LUAD cohort. Finally, the prognostic value and biological function of IFI44L were verified in a real-world cohort and in vitro experiments. The results indicated that IFI44L showed significant correlation with TIICs in LUAD and LUSC samples. Functional enrichment analysis showed that IFI44L may participate in various cancer/immune-related pathways, including JAK/STAT signaling pathway and NF-κB signaling pathway. A total of 44 immunomodulators presented obvious association with IFI44L in the TCGA-LUAD cohort and a robust 10-immunomodulator signature was constructed. Patients in the higher-risk group presented worse prognosis than those in the lower-risk group. Notably, the risk signature was successfully validated in GSE72094. Multivariate Cox regression suggested that the risk signature could act as independent prognostic factors in both TCGA-LUAD and GSE72094 cohorts. Besides, a 17-immunomodulator signature was established in the TCGA-LUSC cohort and similar results were presented through analysis. The nomogram exhibited good accuracy in predicting overall survival (OS) outcome among TCGA-LUAD patients than the risk signature and other clinical features, with the area under curve values being 0.782 at 1 year, 0.825 at 3 years, and 0.792 at 5 years. Finally, tissue microarray analysis indicated that higher expression of IFI44L presented opposite relationship with pathological stage (p = 0.016) and a better outcome among lung cancer patients (p = 0.024). Functional experiments found that IFI44L overexpression significantly inhibited the proliferation, migration, and invasion in LUAD and LUSC cells; RT-qPCR experiments verified the correlation between the expression level of IFI44L with multiple immunomodulators in SPC-A-1 and NCI-H520 cells. In conclusion, our research highlighted that IFI44L is associated with tumor immune infiltration and provided information on IFI44L's immune implication, which indicates that IFI44L has potential clinical immunotherapeutic value and the proposed nomogram is a promising biomarker for non-small cell lung cancer patients.

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

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