IFI27 as a potential indicator for severe Enterovirus 71-infected hand foot and mouth disease

Interferon-stimulated gene IFI27 as a multifaceted candidate target in precision medicine

IFI27, an interferon (IFN)-stimulated gene, is emerging as a crucial player in immune responses across various species, with significant implications for precision medicine. Commonly found among the most upregulated genes in infections, cancers, as well as inflammatory and autoimmune disorders, IFI27 is ready to be trialed in clinical practice for certain indications, and holds promise as an immunomodulatory target. We hypothesize that IFI27 plays a dual role, typically supporting immune defense but sometimes contributing to disease progression, which might render it a putative biomarker for diagnosis, prognosis, and treatment response. We advocate for focused research on IFI27 to unlock its potential in precision medicine and to contribute to a unifying framework of its mechanisms in the immune response. Our viewpoint is supported by numerous studies highlighting IFI27's involvement across various conditions and the possibilities for clinical application.

Analyzing the Molecular Signature Genes and Pathways of Dengue Fever, Dengue Hemorrhagic Fever and Dengue Shock Syndrome Caused by Dengue Virus in India

Dengue fever, dengue hemorrhagic dengue fever and dengue shock syndrome were caused by Dengue mosquito bites. Common signs such as fever and headache, are connected to distinctive medical disorders. From the previous and ongoing studies, it is far unknown what genes or protein signaling pathway mechanism underlies the association between DF, DHF and DSS in Indian context. In our study, the gene expression dataset was retrieved from the GEO database with accession number GSE94892. Here, mRNA sequence analysis done of each DF, DHF and DSS patients from peripheral blood mononuclear cells sample. GEO2R became used to carry out differential gene expression analysis using a dengue data set. Protein-protein interaction networks have been built, gene set GO enrichment and KEGG Pathway enrichment done in SR plot, and cluster analyses have been performed in STRING and MCODE. During this study, we diagnosed 10 hub genes in all 3 condition. The gene set of showed that the ten hub genes diagnosed in each condition constituted the best range of common hub genes discovered beneath all 3 conditions in India. The conclusion of this study can be beneficial for treating DF, DHF and DSS conditions within the context of handling DEV in India.

Transcriptomic Biomarkers Associated With Microbiological Etiology and Disease Severity in Childhood Pneumonia

BACKGROUND

Challenges remain in discerning microbiologic etiology and disease severity in childhood pneumonia. Defining host transcriptomic profiles during illness may facilitate improved diagnostic and prognostic approaches.

METHODS

Using whole blood RNA sequencing from 222 hospitalized children with radiographic pneumonia and 45 age-matched controls, we identified differentially expressed (DE) genes that best identified children according to detected microbial pathogens (viral only vs bacterial only and typical vs atypical bacterial [with or without [±] viral co-detection]) and an ordinal measure of phenotypic severity (moderate, severe, very severe).

RESULTS

Overall, 135 (61%) children had viral-only detections, 15 (7%) had typical bacterial detections (± viral co-detections), and 26 (12%) had atypical bacterial detections (± viral co-detections). Eleven DE genes distinguished between viral-only and bacterial-only detections. Sixteen DE genes distinguished between atypical and typical bacterial detections (± viral co-detections). Nineteen DE genes distinguished between levels of pneumonia severity, including 4 genes also identified in the viral-only versus bacterial-only model (IGHGP, PI3, CD177, RAP1GAP1) and 4 genes from the typical versus atypical bacterial model (PRSS23, IFI27, OLFM4, ABO).

CONCLUSIONS

We identified transcriptomic biomarkers associated with microbial detections and phenotypic severity in children hospitalized with pneumonia. These DE genes are promising candidates for validation and translation into diagnostic and prognostic tools.

Unraveling potential gene biomarkers for dengue infection through RNA sequencing

Dengue virus hijacks host cell mechanisms and immune responses in order to replicate efficiently. The interaction between the host and the virus affects the host's gene expression, which remains largely unexplored. This pilot study aimed to profile the host transcriptome as a potential strategy for identifying specific biomarkers for dengue prediction and detection. High-throughput RNA sequencing (RNA-seq) was employed to generate host transcriptome profiles in 16 dengue patients and 10 healthy controls. Differentially expressed genes (DEGs) were identified in patients with severe dengue and those with dengue with warning signs compared to healthy individuals. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to elucidate the functions of upregulated and downregulated genes. Compared to healthy controls, 6466 genes were significantly differentially expressed (p < 0.05) in the dengue with warning signs group and 3082 genes in the severe dengue group, with over half being upregulated. The major KEGG pathways implicated included transport and catabolism (14.4%-16.3%), signal transduction (6.6%-7.3%), global and overview maps (6.7%-7.1%), viral diseases (4.6%-4.8%), and the immune system (4.4%-4.6%). Several genes exhibited consistent and significant upregulation across all dengue patients, regardless of severity: Interferon alpha inducible protein 27 (IFI27), Potassium Channel Tetramerization Domain Containing 14 (KCTD14), Syndecan 1 (SDC1), DCC netrin 1 receptor (DCC), Ubiquitin C-terminal hydrolase L1 (UCHL1), Marginal zone B and B1 cell-specific protein (MZB1), Nestin (NES), C-C motif chemokine ligand 2 (CCL2), TNF receptor superfamily member 17 (TNFSF17), and TNF receptor superfamily member 13B (TNFRSF13B). Further analysis revealed potential biomarkers for severe dengue prediction, including TNF superfamily member 15 (TNFSF15), Plasminogen Activator Inhibitor-2 (SERPINB2), motif chemokine ligand 7 (CCL7), aconitate decarboxylase 1 (ACOD1), Metallothionein 1G (MT1G), and Myosin Light Chain Kinase (MYLK2), which were expressed 3.5 times, 2.9 times, 2.3 times, 2.1 times, 1.7 times, and 1.4 times greater, respectively, than dengue patients exhibiting warning signs. The identification of these host biomarkers through RNA-sequencing holds promising implications and potential to augment existing dengue detection algorithms, contributing significantly to improved diagnostic and prognostic capabilities.

Interferon-Stimulated Genes and Immune Metabolites as Broad-Spectrum Biomarkers for Viral Infections

The type I interferon (IFN-I) response is a critical component of the immune defense against various viral pathogens, triggering the expression of hundreds of interferon-stimulated genes (ISGs). These ISGs encode proteins with diverse antiviral functions, targeting various stages of viral replication and restricting infection spread. Beyond their antiviral functions, ISGs and associated immune metabolites have emerged as promising broad-spectrum biomarkers that can differentiate viral infections from other conditions. This review provides an overview of the diagnostic potential of ISGs at transcript and protein levels, as well as their immune metabolites. We focus on their clinical applications and the sensitivity and specificity of these biomarkers through receiver operating characteristic (ROC) analysis. We highlight the need for further research to facilitate the effective translation of these biomarkers into clinical practice.

Thioredoxin Domain Containing 5 (TXNDC5): Friend or Foe?

This review focuses on the thioredoxin domain containing 5 (TXNDC5), also known as endoplasmic reticulum protein 46 (ERp46), a member of the protein disulfide isomerase (PDI) family with a dual role in multiple diseases. TXNDC5 is highly expressed in endothelial cells, fibroblasts, pancreatic β-cells, liver cells, and hypoxic tissues, such as cancer endothelial cells and atherosclerotic plaques. TXNDC5 plays a crucial role in regulating cell proliferation, apoptosis, migration, and antioxidative stress. Its potential significance in cancer warrants further investigation, given the altered and highly adaptable metabolism of tumor cells. It has been reported that both high and low levels of TXNDC5 expression are associated with multiple diseases, such as arthritis, cancer, diabetes, brain diseases, and infections, as well as worse prognoses. TXNDC5 has been attributed to both oncogenic and tumor-suppressive features. It has been concluded that in cancer, TXNDC5 acts as a foe and responds to metabolic and cellular stress signals to promote the survival of tumor cells against apoptosis. Conversely, in normal cells, TXNDC5 acts as a friend to safeguard cells against oxidative and endoplasmic reticulum stress. Therefore, TXNDC5 could serve as a viable biomarker or even a potential pharmacological target.

In situ single-cell profiling sheds light on IFI27 localisation during SARS-CoV-2 infection

The utilization of single-cell resolved spatial transcriptomics to delineate immune responses during SARS-CoV-2 infection was able to identify M1 macrophages to have elevated expression of IFI27 in areas of infection.

Behçet syndrome: The disturbed balance between anti- (CLEC12A, CLC) and proinflammatory (IFI27) gene expressions

INTRODUCTION

Behçet syndrome (BS) is a chronic, multisystemic inflammatory condition with unanswered questions regarding its pathogenesis and rational therapeutics. A microarray-based comparative transcriptomic analysis was performed to elucidate the molecular mechanisms of BS and identify any potential therapeutic targets.

METHODS

Twenty-nine BS patients (B) and 15 age and sex-matched control subjects (C) were recruited. Patients were grouped as mucocutaneous (M), ocular (O), and vascular (V) according to their clinical phenotypes. GeneChip Human Genome U133 Plus 2.0 arrays were used for expression profiling on peripheral blood samples of the patients and the control subjects. Following documentation of the differentially expressed gene (DEG) sets, the data were further evaluated with bioinformatics analysis, visualization, and enrichment tools. Validation of the microarray data was performed using quantitative reverse transcriptase polymerase chain reaction.

RESULTS

When p ≤ 0.05 and fold change ≥2.0 were chosen, the following numbers of DEGs were obtained; B versus C: 28, M versus C: 20, O versus C: 8, V versus C: 555, M versus O: 6, M versus V: 324, O versus V: 142. Venn diagram analysis indicated only two genes, CLEC12A and IFI27, in the intersection of M versus C ∩ O versus C ∩ V versus C. Another noteworthy gene appeared as CLC in the DEG sets. Cluster analyses successfully clustered distinct clinical phenotypes of BS. While innate immunity-related processes were enriched in the M group, adaptive immunity-specific processes were significantly enriched in the O and V groups.

CONCLUSIONS

Distinct clinical phenotypes of BS patients displayed distinct expression profiles. In Turkish BS patients, expression differences regarding the genes CLEC12A, IFI27, and CLC seemed to be operative in the disease pathogenesis. Based on these findings, future research should consider the immunogenetic heterogeneity of BS clinical phenotypes. Two anti-inflammatory genes, namely CLEC12A and CLC, may be valuable as therapeutic targets and may also help design an experimental model in BS.

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.

CX3CR1 might be a promising predictor of systemic lupus erythematosus patients with pulmonary fibrosis

The inflammatory process in systemic lupus erythematosus (SLE) affects many organs including the lungs. Chemokines are suggested to play important roles in the pathogenesis of SLE with pulmonary fibrosis (PF). In the present study, our objective is to evaluate the correlation between chemokines and PF in SLE patients. Transcriptome sequencing analysis was used to find the different expressed genes between SLE patients with PF and without PF. Enzyme-linked immunosorbent assay (ELISA) was used to detect serum levels of chemokines in SLE patients and healthy controls. Expression of CX3CR1 was measured by real-time polymerase chain reaction (PCR) and flow cytometer. Sixteen differentially chemokine genes were found to be associated to SLE with PF. Meanwhile, the upregulation of C-X3-C motif chemokine receptor 1 (CX3CR1) and its ligand, CX3C chemokine ligand 1 (CX3CL1) were observed in SLE patients with PF than that of SLE patients without PF and healthy control. Phenotypic analysis also showed that the surface expression of CX3CR1 increased in PBMCs from SLE patients with PF. Our observations indicated that CX3CL1/CX3CR1 axis is associated with PF in SLE. CX3CR1 might be a promising predictor of SLE with PF and the interactions between CX3CL1 and CX3CR1 might provide potential candidate target for the treatment of SLE with PF.

IFI27 may predict and evaluate the severity of respiratory syncytial virus infection in preterm infants

Background

Preterm infants are a special population that vulnerable to respiratory syncytial virus (RSV) infection and the lower respiratory tract infections (LRTIs) caused by RSV could be severe and even life-threating. The purpose of the present study was to identify candidate genes of preterm infants who are susceptible to RSV infection and provide a new insight into the pathogenesis of RSV infection.

Methods

Three datasets (GSE77087, GSE69606 and GSE41374) containing 183 blood samples of RSV infected patients and 33 blood samples of healthy controls from Gene Expression Omnibus (GEO) database were downloaded and the differentially expressed genes (DEGs) were screened out. The function and pathway enrichments were analyzed through Database for Annotation, Visualization and Integrated Discovery (DAVID) website. The protein-protein interaction (PPI) network for DEGs was constructed through Search Tool for the Retrieval of Interacting Genes (STRING). The module analysis was performed by Cytoscape software and hub genes were identified. Clinical verification was employed to verify the expression level of top five hub genes among 72 infants including 50 RSV infected patients and 22 non-RSV-infected patients hospitalized in our center. Further, the RSV infected infants with high-expression IFI27 and those with low-expression IFI27 were compared (defined as higher or lower than the median mRNA level). Finally, the gene set enrichment analysis (GSEA) focusing on IFI27 was carried out.

Results

Totally, 4028 DEGs were screened out and among which, 131 most significant DEGs were selected. Subsequently, 13 hub genes were identified, and function and pathway enrichments of hub genes mainly were: response to virus, defense response to virus, regulation of viral genome replication and regulation of viral life cycle. Furthermore, IFI27 was confirmed to be the most significantly expressed in clinical verification. Gene sets associated with calcium signaling pathway, arachidonic acid metabolism, extracellular matrix receptor interaction and so on were significantly enriched when IFI27 was highly expressed. Moreover, high-expression IFI27 was associated with more severe cases (p = 0.041), more requirements of mechanical ventilation (p = 0.034), more frequent hospitalization (p < 0.001) and longer cumulative hospital stay (p = 0.012).

Conclusion

IFI27 might serve to predict RSV infection and evaluate the severity of RSV infection in preterm infants.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41065-020-00167-5.