IL18R1 Human

What is the basic structure of human IL18R1 protein?

IL18R1, also known as IL-18 Rα, IL-18 R1, IL-1 R5, and IL-1 Rrp, is a transmembrane receptor component. The mature human IL18R1 protein consists of a 308 amino acid extracellular domain (ECD) with three immunoglobulin-like domains, a 21 amino acid transmembrane segment, and a 191 amino acid cytoplasmic domain . Within the ECD, human IL18R1 shares 56% amino acid sequence identity with mouse and rat IL18R1 . The protein forms part of the IL-18 receptor complex by associating with IL-18 Rb/IL-1 R7 to create the high-affinity receptor for IL-18 .

What cell types express IL18R1 and what is its primary function?

IL18R1 is widely expressed across multiple cell types including epithelial cells, B cells, NK cells, CD4+ and CD8+ T cells, and dendritic cells . Recent single-cell RNA analysis has shown that IL18R1 is predominantly expressed in mast cells . Its primary function is to associate with IL-18 Rb/IL-1 R7 to form the high-affinity receptor complex for IL-18, which confers cellular responsiveness to IL-18 . IL18R1 is recognized as an important T cytotoxic cell surface marker and plays a significant role in the immune microenvironment .

How does IL18R1 signaling work in the immune system?

IL18R1 forms part of the IL-18 receptor complex that recognizes IL-18, a member of the IL-1 family of cytokines that shares numerous immunoregulatory functions with IL-12 . When IL-18 binds to the receptor complex, it triggers signaling pathways related to cytokine-cytokine receptor interaction, TNF, and NF-κB signaling . Research indicates that IL18R1 expression enhances communication between mast cells and CD8+ T cells . The receptor's signaling is important for immune response regulation, and alterations in expression levels or genetic variants can influence susceptibility to various inflammatory and immune-mediated diseases.

How does IL18R1 contribute to respiratory diseases like asthma and IPF?

IL18R1 and related molecules have emerged as important biomarkers for respiratory diseases:

• In asthma: IL18R1 is upregulated in serum, induced sputum, and bronchoalveolar lavage fluid of patients with uncontrolled or severe asthma . It shows positive correlations with inflammatory markers TNFSF1, OSM, and S100A12 .

• In idiopathic pulmonary fibrosis (IPF): High levels of IL18R1 and related molecules (TNFSF1, OSM, and S100A12) are significantly associated with shorter survival times and worse lung function .

The diagnostic efficacy of serum IL18R1-related molecules for asthma ranges from 0.839 to 0.921 in ROC analyses, indicating strong potential as clinical biomarkers . These findings suggest IL18R1 participates in chronic inflammatory processes within lung tissue, potentially through mast cell activation and CD8+ T cell interactions.

What is known about IL18R1's relationship with COPD risk?

Multiple single nucleotide polymorphisms (SNPs) of the IL18R1 gene have been investigated in relation to Chronic Obstructive Pulmonary Disease (COPD) risk . Five SNPs (rs9807989, rs3771166, rs6543124, rs2287037, and rs2058622) have been examined based on their location, allele frequency, and disease association . Researchers are exploring whether these genetic variants may predispose individuals to COPD development or influence disease progression . The investigation employs various analytical methods including logistic regression models adjusted for age, gender, smoking and drinking, as well as interaction analyses to determine how these SNPs might contribute to COPD susceptibility in combination with environmental factors .

What methodologies are most effective for genotyping IL18R1 SNPs?

For effective IL18R1 SNP genotyping, researchers typically employ a multi-step approach:

• Sample collection and DNA extraction: Peripheral blood samples (usually 5 mL) are collected in EDTA tubes, followed by genomic DNA extraction using commercial kits like GoldMag DNA purification kit .

• Quality assessment: DNA concentration and purity are determined using spectrophotometric methods such as NanoDrop 2000 .

• SNP selection: Candidate IL18R1 variants are selected based on minor allele frequency (MAF) over 5% in the target population using resources like the 1000 Genomes Project .

• Genotyping platforms: Mass spectrometry-based platforms such as MassARRAY Nanodispenser and MassARRAY iPLEX platform have proven effective for IL18R1 SNP genotyping .

• Quality control: Re-genotyping approximately 5% of samples randomly to ensure concordance (100% concordance rate is expected) .

This methodological approach ensures reliable identification of IL18R1 genetic variants for association studies.

How are IL18R1 gene polymorphisms statistically analyzed in disease association studies?

Statistical analysis of IL18R1 polymorphisms in disease association studies involves several sophisticated approaches:

• Demographic characteristic analysis: Differences in age, gender, smoking, and drinking between case and control groups are analyzed using χ² test/t-test with SPSS software .

• Association testing: Odds ratios (ORs) and 95% confidence intervals (CIs) are calculated using logistic regression analysis adjusted for confounding variables like age, gender, smoking, and drinking using tools such as SNPStats .

• HWE testing: Hardy-Weinberg equilibrium testing is performed in control groups using the χ² test to ensure the genetic variants follow expected population distributions .

• Interaction analysis: Gene-environment interactions are assessed using SNPStats, while SNP-SNP interactions are analyzed using Multifactor Dimensionality Reduction (MDR) software to identify potential multilocus effects .

• Linkage disequilibrium and haplotype analysis: D' and R² values for pairwise linkage disequilibrium are generated using Haploview software, with haplotype associations evaluated by logistic regression models .

• Pathway analysis: Protein-protein interaction networks and pathway enrichment analyses are conducted using the STRING database and KEGG pathway analysis to understand the biological context .

• Multiple testing correction: Bonferroni correction (p < 0.05/number of tests) is applied to control for multiple hypothesis testing .

This comprehensive statistical framework allows for robust evaluation of associations between IL18R1 genetic variants and disease phenotypes.

What is the diagnostic efficacy of IL18R1 as a biomarker for lung cancer?

IL18R1 demonstrates significant potential as a diagnostic biomarker for lung squamous cell carcinoma (LUSC). Research has established that:

• IL18R1 expression is significantly downregulated in LUSC tissues compared to normal lung tissues, as confirmed by multiple data sources including TCGA, GTEx, and GEO databases .

• Diagnostic analysis using RNA data from TCGA and GTEx databases revealed IL18R1's utility in LUSC diagnosis, with evaluation based on area under the curve (AUC) metrics .

• The expression pattern is consistent across different data sources and has been validated in clinical samples (9 normal lung tissue samples and 32 LUSC tissue samples) .

This evidence suggests IL18R1 expression levels could serve as a valuable biomarker for LUSC diagnosis, though specific sensitivity and specificity values would require further clinical validation studies.

How effective are IL18R1-related molecules as biomarkers for asthma severity?

IL18R1 and related molecules demonstrate strong potential as biomarkers for asthma severity and control status:

These biomarkers are particularly valuable because:

• IL18R1 is upregulated in multiple sample types from patients with uncontrolled or severe asthma, including serum, induced sputum, and bronchoalveolar lavage fluid .

• IL18R1 shows positive correlation with other inflammatory markers (TNFSF1, OSM, and S100A12), creating a potential biomarker panel .

• The high diagnostic efficacy (AUC range 0.839-0.921) suggests these molecules could effectively distinguish between controlled and uncontrolled asthma or between mild and severe disease .

This biomarker panel could significantly improve clinical management by identifying patients requiring more aggressive therapy or closer monitoring.

What is the prognostic value of IL18R1 expression in pulmonary diseases?

IL18R1 expression demonstrates significant prognostic value across multiple pulmonary diseases:

These findings indicate that IL18R1 expression analysis could stratify patients by risk, potentially guiding treatment decisions and follow-up protocols in both malignant and non-malignant pulmonary diseases.

What are the optimal protocols for measuring IL18R1 expression in tissue samples?

Multiple complementary methods have demonstrated reliability for measuring IL18R1 expression in tissue samples:

RNA level analysis:

• RNA extraction from tissues followed by quantitative real-time PCR using validated primers: IL18R1 forward: CGCCGAGTTTGAAGATCAGG, reverse: TCAGCAAAGCAGAGCAGTTG, with GAPDH as reference gene .

• RNA-seq analysis of tissues with data processing through established pipelines for TPM (Transcripts Per Million) or FPKM (Fragments Per Kilobase Million) normalization, as employed in TCGA and GTEx databases .

Protein level analysis:

• Immunohistochemistry protocol:

  • Standard dewaxing and antigen retrieval

  • Incubation with IL18R1 antibody (typically 1:200 dilution)

  • Counterstaining, dehydrating, and sealing

  • Quantification using scanner systems (e.g., Quant Center 2.3 software)

• Western blot analysis with 1:2000 IL18R1 antibody concentration and appropriate reference protein (GAPDH at 1:20000) .

Advanced methods:

• Single-cell RNA sequencing to determine cell-specific expression patterns, which has revealed IL18R1's predominant expression in mast cells .

• Proteomic analysis using platforms like Olink to measure IL18R1 among panels of inflammation-related proteins in serum or other bodily fluids .

The choice of method depends on research objectives, with RNA-seq providing global expression patterns, qPCR offering targeted quantification, and protein-level analyses confirming functional expression.

How can functional studies of IL18R1 be designed in cell culture models?

Functional studies of IL18R1 in cell culture models can be systematically designed using established protocols:

Overexpression model construction:

• Selection of appropriate cell lines (e.g., lung squamous carcinoma cell lines for cancer studies)

• Construction of IL18R1 overexpression vectors

• Transfection and stable cell line selection

• Verification of overexpression by qPCR and Western blot

Functional assays to evaluate IL18R1's biological effects:

• Proliferation assays: Cell Counting Kit-8 (CCK-8) assay with measurements at 0, 24, 48, and 72 hours to track growth patterns

• Migration assays: Wound healing assay with imaging at 0, 12, 24, 36, and 48 hours

• Invasion assays: Matrigel-coated Transwell chamber assays with 24-hour incubation, followed by fixing, staining, and quantification

• Signaling pathway analysis: Western blotting for downstream signaling molecules or phosphorylation states

• Immune interaction studies: Co-culture systems with immune cells (particularly mast cells and CD8+ T cells given IL18R1's role in their communication)

Data analysis approaches:

• Student's t-test for comparing IL18R1 overexpression versus control conditions

• Time course analysis for proliferation and migration studies

• Pathway enrichment analysis to identify molecular mechanisms

These methods provide comprehensive assessment of IL18R1's functional impact on cellular phenotypes and molecular pathways.

What techniques are available for studying IL18R1 in the context of the immune microenvironment?

Advanced techniques for studying IL18R1 in the immune microenvironment include:

Computational methods:

• ESTIMATE algorithm: Calculates stromal, immune, and estimate scores to quantify immune infiltration in tissues

• ssGSEA (single-sample Gene Set Enrichment Analysis): Determines the expression levels of immune microenvironment components

• Correlation analysis: Pearson correlation between IL18R1 expression and 24 immune cell types

• Cell marker analysis: Association between IL18R1 and established immune cell markers (PDCD1, CTLA4, CD8A, etc.)

Experimental approaches:

• Single-cell RNA sequencing: Identifies cell-specific expression patterns of IL18R1 across immune populations, revealing its predominance in mast cells

• Multiplex immunofluorescence: Visualizes IL18R1 expression alongside immune cell markers in tissue sections

• Flow cytometry: Quantifies IL18R1 expression on specific immune cell populations

• Cell-cell interaction assays: Evaluates how IL18R1 expression affects communication between immune cells, particularly between mast cells and CD8+ T cells

In vivo models:

• Transgenic mouse models with IL18R1 knockout or overexpression

• Humanized mouse models for studying human IL18R1 function in immune contexts

These methodologies provide complementary insights into IL18R1's role in shaping the immune microenvironment in both health and disease states.

What regulatory mechanisms control IL18R1 expression in different tissues and disease states?

Research has begun to uncover the complex regulatory mechanisms controlling IL18R1 expression:

Transcriptional regulation:
While not fully characterized, evidence suggests tissue-specific transcription factors likely regulate IL18R1 expression, as indicated by its varied expression across cell types .

Post-transcriptional regulation:
A ceRNA (competitive endogenous RNA) network has been identified involving:

• MicroRNAs: miR-128-3p and miR-556-5p negatively regulate IL18R1 expression

• LncRNAs: AC091563.1 and RBPMS-AS1 can positively regulate IL18R1 by competitively binding to miR-128-3p, creating a miR-128-3p/IL18R1 signaling pathway

Epigenetic regulation:
While not explicitly described in the search results, epigenetic mechanisms like DNA methylation and histone modifications likely play roles in context-dependent IL18R1 expression.

Disease state influences:
IL18R1 expression patterns differ dramatically between health and disease:

• Downregulated in lung squamous cell carcinoma

• Upregulated in severe or uncontrolled asthma

These findings indicate a complex regulatory network that controls IL18R1 expression in a context-dependent manner, representing an area requiring further research.

How do genetic variants of IL18R1 impact protein function and disease susceptibility?

The impact of IL18R1 genetic variants on protein function and disease susceptibility represents an active research area:

SNP selection criteria for functional impact:
Researchers select candidate IL18R1 variants based on:

• Minor allele frequency (MAF) over 5% in the target population

• Location within the gene

• Known associations with diseases

Prediction tools for functional effects:
Tools employed to predict SNP functions include:

• HaploReg v4.1: Assesses regulatory potential of variants

• GTEx Portal database: Evaluates expression quantitative trait loci (eQTLs)

Disease association methodologies:
Multiple approaches determine relationships between IL18R1 variants and disease:

• Case-control studies with logistic regression adjusted for covariates

• Hardy-Weinberg equilibrium testing

• SNP-SNP interaction analysis using MDR

• PPI network and pathway enrichment to understand biological context

Specific variants under investigation:
Five SNPs of particular interest include rs9807989, rs3771166, rs6543124, rs2287037, and rs2058622, with ongoing research exploring their functional impacts .

While the precise mechanisms by which these variants affect IL18R1 function remain under investigation, they potentially influence:

• Receptor expression levels

• Protein structure and binding affinity

• Signaling pathway activation

• Cell-specific expression patterns

These genetic variations may ultimately contribute to individual differences in disease susceptibility and treatment response.

What is the role of IL18R1 in the cross-talk between innate and adaptive immunity?

IL18R1 appears to function at the critical interface between innate and adaptive immunity:

Cell type expression pattern:
IL18R1 is expressed on both innate immune cells (NK cells, dendritic cells, mast cells) and adaptive immune cells (CD4+ T cells, CD8+ T cells, B cells) , positioning it as a potential mediator of cross-talk.

Predominant expression in mast cells:
Single-cell RNA analysis reveals IL18R1 is predominantly expressed in mast cells , which are key innate immune sentinels that can initiate and modulate adaptive responses.

Enhanced communication with CD8+ T cells:
Research suggests IL18R1 enhances communication between mast cells (innate) and CD8+ T cells (adaptive) , potentially facilitating coordinated immune responses.

Pathway involvement:
IL18R1 signaling is linked to cytokine-cytokine receptor interaction, TNF, and NF-κB signaling pathways , which are central to both innate and adaptive immune responses.

Disease context findings:

• In LUSC, IL18R1 expression correlates with immune infiltration scores and multiple immune cell types

• In asthma and IPF, IL18R1-related molecules serve as biomarkers for disease severity

These findings suggest IL18R1 may function as a molecular bridge between innate and adaptive immunity, with its dysregulation potentially contributing to immune-mediated diseases through altered cross-talk between these systems.